Cytokine Gene Polymorphisms in Multifactorial Conditions

CYTOKINE GENE POLYMORPHISMS IN MULTIFACTORIAL CONDITIONS

Edited by

Koen Vandenbroeck

3619_Discl.fm Page 1 Wednesday, May 17, 2006 12:54 PM

Central front cover illustration: Pairwise linkage disequilibrium (r2) for single nucleotide polymorphisms (SNPs) in the human cytokine cluster region (containing IL3, CSF, IL5, IL13 and IL4) on chromosome 5q31 for the four International HapMap population panels. European American, Japanese, Han Chinese and Yoruba panels are shown in order from top to bottom. The plots include all SNPs in 2 million base pairs of chromosome 5 (5q31), from position 131090086 to 133090086 in the NCBI human genome B34. Images were downloaded from the International HapMap genome browser - http://hapmap.org on October 29, 2005, using Phase II HapMap data release #19. The illustration was prepared by Ross Lazarus and Koen Vandenbroeck. Graphic design by Beatriz Alonso-Alvarez.

Published in 2006 by CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2006 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-10: 0-8493-3619-8 (Hardcover) International Standard Book Number-13: 978-0-8493-3619-5 (Hardcover) Library of Congress Card Number 2005037444 This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. No part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC) 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data Cytokine gene polymorphisms in multifactorial conditions / editor, Koen Vandenbroeck. p. ; cm. Includes bibliographical references and index. ISBN-13: 978-0-8493-3619-5 (alk. paper) ISBN-10: 0-8493-3619-8 (alk. paper) 1. Immunology. 2. Cytokines. 3. Gene targeting. [DNLM: 1. Cytokines. 2. Genetic Predisposition to Disease. 3. Immunity--genetics. 4. Multifactorial Inheritance--genetics. 5. Polymorphism, Genetic. QW 568 C9935 2006] I. Vandenbroeck, Koen. QR185.8.C95C98 2006 616.07’9--dc22

2005037444

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Foreword The degree to which antigens induce an immune response varies markedly between individuals. Similarly, there is great variation in individual susceptibility to disease as well as subsequent severity. In well-defined cases, there can even be extreme differences in disease outcome when individuals are presented with the same aetiological agent - the mutuallyexclusive cancer or ulcer responses to H.pylori, for example. Much of this variation is determined by the combination of antigen presenting molecules, both class-I and class-II MHC, that the individual is expressing and the range of T-cell receptor structures that have accumulated. Together, these determine whether and how well that individual’s immune system will see any given antigen and it will be apparent that the random nature of T-cell and B-cell receptor construction means that even monozygotic twins will show variation in this respect, or at least have this potential. These aspects of the immune system have formed the backbone of the science of immunogenetics and continue to do so. However, as this volume so capably demonstrates, genetic variation in cytokines, the messengers of the immune system, and their receptors is now recognised as playing an important role in disease susceptibility and outcome. Indeed, the journal which we edit, ‘‘Genes and Immunity’’, (http://www.nature.com/gene) was born from this concept. This body of work on cytokines and their receptors demonstrates that our understanding of the effect of genetic variation on human immune responses continues to widen and this book is a timely anthology of knowledge, techniques as well as informed speculation. The book comprises three sections. The first deals with general principles and practices. Over six chapters, the Authors discuss general cytokine biology, the genetics of multifactorial conditions, modern statistical methods, bioinformatics resources, how simple alignment strategies can provide useful information and modern genotyping methodologies. The biology of cytokines is discussed with particular focus on adaptive responses and in particular, the Th1/Th2 system that underpins so many autoimmune disorders and responses to infection. As subsequent chapters illustrate, there have been many studies on cytokine polymorphisms. These have been traditionally weak in statistical power and analysis and so the inclusion of chapters where the complex interplay between genetic and environmental elements, and modern essential statistical tools are described is an excellent addition, often disregarded. These chapters present complex concepts with a sliding scale of difficulty, allowing the reader to go as far as s/he wants into the area, yet ensuring that some new understanding will be had. Two chapters illustrate different approaches to the bioinformatics problems that confront novice and experienced workers alike in this field and the final chapter in this section focuses on the high throughput techniques that are used to analyse SNPs and which are at the heart of both the global haplotyping effort and the large-scale disease association studies. The second section deals in detail with polymorphic elements in individual genes or gene families. The nine chapters in this section provide a comprehensive analysis of important findings in genes that are key to inflammatory and immune responses. The chapters on IL-1, TNF and IL-10 represent excellent resources for those learning the subject for application to infectious and autoimmune inflammatory diseases. The comprehensive description of the genes, markers and haplotypes found in this complex region is excellent. Similarly, there is an excellent description of the TNF and TNF receptor loci which will provide excellent

starting material for those interested in these genes and their history as polymorphic markers of disease. As pointed out by more than one author, IL-10 has received an enormous amount of attention and its genetics might warrant a volume of their own. The chapter here, while short, presents many of the facts and remaining questions well. Of particular interest is the discussion here of how genetic variation itself varies with human ethnicity. IL-10 is now known to be the founder member of a family of 6 cytokines (IL-10, IL-19, IL-20, IL-22, IL-24 and IL-26). These cytokines are considered in the contexts of their genomic clusters: IL-19, 20 and 24 on chromosome 1 and IL-22 and 26, with IFN-g on chromosome 12. The two chapters on these cytokines represent the cutting edge of what is known about their polymorphic nature, their haplotype blocks and their involvement with disease, particularly proinflammatory autoimmune disorders. Like the members of the IL-10 family, genes structurally and evolutionarily associated with IL-4 lie together in a cluster on chromosome 5. The concise description of these genes and their evolutionary relationship both in humans and in lesser mammals and birds is revealing and contains a few surprises! An excellent chapter on IL-2 reminds the reader that information on immunophysiology can be gained from the genetics of animal models and also presents the genetics of the three components of the IL-2 receptor well. While the majority of the chapters in this section focus on what were once called ‘‘lymphokines’’ the chapter on chemokines and their receptors describes a relatively new area of immunogenetics research. The body of data which exists for cytokines such as TNF is absent for the chemokines (for now!) but this does not prevent the authors from describing a marker which they believe may provide some measure of resistance to smallpox. Finally, a comprehensive and eloquent discussion of MIF, in humans and mice, describes the role of this molecule in health and disease in both animal models and human infection and autoimmunity. The third and largest section of this book — fourteen chapters in all — describes the role that polymorphism and genetic variation in cytokines and their receptors plays in human disease. This section is a real tour de force. It covers infectious diseases, autoimmune disorders and longevity. These chapters are the essential complement to those in the preceding section. Where the properties of the individual cytokines were discussed, here these are re-presented from the point of view of the individual disease or condition. Many careful descriptions of studies that relate cytokine markers to diseases and their individual symptomatic presentations will be found. The question of whether a person’s genetic makeup or living environment contributes more to their risk of disease has been an important one for some time. In 1988 Sorensen and colleagues demonstrated clearly that adopted individuals carried a risk of death from infectious causes that was equivalent to that of their natural, rather than adoptive, parents. In so doing they established that premature death in adults from infectious causes had a strong genetic background. This is seen nowadays in the context of the wide genetic variation known to exist in the immune system. Broadly speaking however, the rationale for studying cytokine gene polymorphisms is as follows:     

To improve our understanding of the control over cytokine expression and function To improve our understanding of the origin and mechanism of human disease To identify novel diagnostic markers of susceptibility, severity and outcome To identify novel therapeutic targets and suitable patients for immunomodulatory treatments To identify novel intervention strategies (enhanced vaccination, for example)

Such examples are predicated upon the assumption that cytokine levels do vary between individuals, so it is worthwhile to ask if this is the case and if, being so, diseases are affected.

The chapters in this book represent an excellent and timely means of addressing these questions and will serve as an important reference work. Grant Gallagher and Michael F Seldin Editors, Genes and Immunity

Preface The first cytokine gene polymorphisms were reported around fifteen to twenty years ago. With the increasing availability of cost-effective genotyping and polymorphism discovery methods, as well as of publicly accessible polymorphism and genome databases, the number of research articles dealing with cytokine genetics published in scientific journals has in recent years exploded. This surge coincides, not unexpectedly, with a growing awareness for a genetic component in a multitude of common, complex disorders such as allergies, autoimmune, and cardiovascular diseases. This is most clearly demonstrated by familial aggregation, the clustering of such diseases in families. Most of the risk to contract such diseases is multifactorial, and results from the interaction of multiple genetic and environmental factors. Many, if not all, multifactorial diseases have in some way been linked to aberrant immune or inflammatory reactions. Cytokines and chemokines, being crucial inducers, amplifiers and modulators of immune responses, constitute therefore obviously a very appealing group of putative disease risk factors. Single nucleotide polymorphisms (SNPs) in regulatory regions may alter cytokine gene expression levels, nonsynonymous coding SNPs may change amino acid composition and activity of protein coded for. As cytokines and chemokines operate in networks, the underlying thought is that even genetic variations with relatively moderate functional impacts might still bring about pronounced changes in phenotypic expression or risk of disease. The recent availability of potent cytokine agonists and antagonists as drugs for treatment of certain chronic inflammatory diseases has provided yet another drive for exploration of cytokine genetic effects. The literature on cytokine genetics is vast; so vast that it is now practically beyond the time or logistical constraints of most scientists to successfully keep pace with it. Reviewing, structuring, and bringing together essential information on cytokine polymorphisms in the most intensely studied cytokine genes and on their association patterns with various multifactorial conditions have therefore been the main objectives of this book. One challenge was how to structure that information. Each of many cytokine genes has been studied separately in many different diseases. A cytokine gene-centered approach would focus on polymorphisms in each gene and evaluate their association patterns in a multitude of disorders. A disease-centered approach would basically entail comparison and assessment of association patterns of many different cytokine genes with a specific disease. Both are informative and, as we realized, not mutually exclusive. We decided thus to allow for both options. In addition, we thought it to be of relevance to include a series of chapters dealing with generic aspects of genetic research. This first edition of Cytokine Gene Polymorphisms in Multifactorial Conditions is therefore organized in three parts. The six chapters in Part A form an introductory section, and deal with general biological, genetic, statistical, technical and bioinformatic concepts that together provide the backdrop for modern cytokine genetics research. Part B contains a series of cytokine gene-centered (Chapter 7 through Chapter 15) and part C of disease-centered chapters (Chapter 16 through Chapter 29). All in all, we hope that both structure and scope of this book make it a valuable, instructive, and easily accessible resource for both novice and expert (cytokine) geneticists, as well as for immunologists, cell biologists, and clinicians. Chapter 1 by Agnello and Gadina provides an extensive overview of the biology of cytokines, with a special emphasis on lessons learned from animal models. In Chapter 2 Rioux and Oksenberg document the latest concepts in our understanding of the genetics of

complex, multifactorial disorders. Goris and Andrade, in Chapter 3, explain statistical methods based on linkage and linkage disequilibrium and their pitfalls, and introduce the concept of admixture mapping. This is followed by an introduction to some of the most important integrated bioinformatic resources for cytokine genetics research by Lazarus (Chapter 4). In Chapter 5 Bidwell introduces some of the more useful software and data repositories which permit easy acquisition of user-generated or pre-generated cytokine gene nucleotide sequence alignments. Part A is conclude with Chapter 6 in which Kwok reviews and compares a choice of modern SNP genotyping methods. Part B of the book opens with an overview by Pessi et al. of the structure and common polymorphisms in the IL1 gene cluster (Chapter 7). In Chapter 8, Matesanz et al. concentrate on the role of mouse IL-2 allotypes in autoimmune pathology, and discuss disease association studies of human IL2 and IL2R polymorphisms. Laitinen analyzes the cytokine gene cluster on chromosome 5q23.1–q31.1, well-known to contain a series of cytokine genes (IL3, IL5, IL13, IL4, and IL9) and pays particular attention to the emerging importance of IL13 polymorphisms (Chapter 9). Lazarus discusses genetic variation in the IL10 gene region and critically reviews disease association studies in Chapter 10. The IL19 subfamily of cytokines contains three members, IL19, IL20, and IL24 that form a cytokine gene cluster on chromosome 1q31–q32 in vicinity to IL10. In Chapter 11, Ko˜ks et al. review molecular genetic studies on IL19 subfamily members. Chapter 12, by Vandenbroeck and Goris, deals with yet another cytokine gene cluster, i.e. the IFNG–IL22-IL26 cluster on chromosome 12q15, and includes a discussion of IFNGR disease association studies as well. Gorczynski and Boudakov review current knowledge of TNFA, TNFB, TNFR1, and TNFR2 polymorphisms in Chapter 13. Alourfi et al., in Chapter 14, introduce the reader to the MIF gene, highlight the unusual biological properties of the cytokine it codes for, and report genetic associations with disease. Part B is brought to a close by Puissant et al., who review polymorphisms in the genes of chemokines and their receptors, and evaluate their associations with many common diseases in Chapter 15. Part C of the book kicks off with an overview of genetic associations between cytokine gene polymorphisms and asthma and atopy by Karjalainen et al. (Chapter 16). In Chapter 17, Kilding and Wilson review the cytokine genetics of rheumatoid arthritis, spondyloarthropathies and osteoarthritis. Systemic lupus erythematosus is the subject of Chapter 18, written by D’Alfonso, who also dissects the extensive literature on IL10 association studies performed on this disease. Pertovaara concludes this series of three chapters on autoimmune rheumatic disorders with a review of cytokine genetics in Sjo¨gren’s syndrome (Chapter 19). In Chapter 20, Kantarci and Weinshenker review biological and genetic cytokine effects in multiple sclerosis, and address the prospects for targeting cytokine networks as treatment of this disease. Bergholdt and Pociot focus on the role of cytokines in the pathophysiology and genetics of Type I and II diabetes in Chapter 21. In Chapter 22, Ko˜ks et al. scrutinize the current state of knowledge on the cytokine genetics of psoriasis. Ho¨hler, in Chapter 23, examines cytokine genetics of diseases of the gastrointestinal tract — in particular Helicobacter infection and gastric cancer, chronic inflammatory bowel diseases, and liver diseases caused by hepatitis B or C virus infections. Yucesoy and Luster present evidence of a role of cytokine polymorphisms in pulmonary fibrotic diseases in Chapter 24. Indications for a role of chemokine and cytokine polymorphisms in atherosclerosis are presented by Candore et al. in Chapter 25. Life span is a multifactorial quantitative trait, which is influenced by both genetic and environmental factors. The popular adage that ‘‘long life runs in families’’ is indicative for a genetic component indeed. Rea et al. examine emerging support for a role of cytokine gene polymorphisms in predisposition to longevity in Chapter 26. A series of three chapters on infectious diseases draws this book to a close. In Chapter 27, Vasilescu et al. discuss the relevance of polymorphisms in the genes of chemokines, cytokines and their receptors

to AIDS. Quirico-Santos et al. review recent data on cytokine polymorphisms in a series of tropical infectious diseases including tuberculosis, leprosy, leishmaniasis, Chagas disease, and viral haemorrhagic fevers in Chapter 28. In Chapter 29, lastly, Arnaud and Chevillard give proof for a role of cytokine genes in host control of Schistosoma infection as well as in susceptibility to advanced schistosomiasis. The area of cytokine genetics is rapidly evolving, as is that of genetics in general. When reading this book, then, it is important to remember that deciphering the full story of cytokine genetics will likely be achieved only in the context of further progress in our understanding of the entire genetics of common, complex diseases. Cytokine genetics constitutes therefore a work in progress, and much remains to be done. Both in terms of significance and number of independent, reproducible replications, there is however no doubt whatsoever that solid genetic associations are starting to emerge. For instance, nine independent studies have associated the R130Q polymorphism in IL13 with atopy-related traits (see Chapter 9). Polymorphisms in IL1B have repeatedly been shown to increase the risk for gastric cancer (Chapter 23). Polymorphisms in chemokine and chemokine receptor genes influence infection with HIV and progression of AIDS (Chapter 15 and Chapter 27). IFNG polymorphisms have been reproducibly associated with susceptibility to tuberculosis infection (Chapter 12 and Chapter 28). For more examples, I invite you to immerse yourself into this book. Koen Vandenbroeck Editor, Cytokine Gene Polymorphisms in Multifactorial Conditions

Acknowledgments I am deeply indebted to each and every author who has contributed to this book. Especially noteworthy are the enthusiasm with which all authors responded to my initial invitation to participate in this endeavor, and the obvious quality of their contributions. I thank Judith Spiegel, Senior Editor of Life Sciences at CRC Press, who was highly supportive for this project from the very onset. I thank David Fausel, Joette Lynch and Imran Mirza who all contributed a great deal to guide the book smoothly through the production process. I thank Grant Gallagher and Michael F. Seldin for writing the Foreword to this book. I owe a lot of gratitude to Beatriz Alonso-Alvarez for design of the terrific front cover. For everything else I thank Iraide. Koen Vandenbroeck Editor, Cytokine Gene Polymorphisms in Multifactorial Conditions

Editor Koen Vandenbroeck studied zoology and molecular biology at the University of Leuven, and obtained his Ph.D. in 1993 at the Rega Institute for Medical Research in Belgium under supervision of professor emeritus Alfons Billiau. Postdoctoral research periods were spent at the San Raffaele Scientific Institute (Milan, Italy), and back at the Rega Institute. He was appointed as Allen J. McClay lecturer at Queen’s University of Belfast in 1999, and promoted there successively to senior lecturer in 2002 and to the chair in applied genomics in 2004. His main research interests include the genetics of multifactorial diseases and pharmacogenomics of cytokine therapeutics. He is grantee of MS Ireland, the Northern Ireland Health and Personal Social Services (HPSS) R&D Office, the National Institutes of Health and the National MS Society. He is currently a visiting professor in functional genomics at the Centro de Investigacio´n Cooperativa en Biociencias (CIC bioGUNE), Bilbao, Spain.

Contributors Kati A˚djers Department of Microbiology and Immunology University of Tampere Medical School Tampere, Finland Davide Agnello Laboratoire de Virologie Faculte´ de Me´decine Universite´ de Bourgogne Dijon, France Antonio Alcina Instituto de Parasitologı´ a y Biomedicina Lo´pez Neyra Consejo Superior de Investigaciones Cientı´ ficas Granada, Spain Zaynab Alourfi Endocrine Sciences Research Group Centre for Molecular Medicine The University of Manchester Manchester, United Kingdom Mariza de Andrade Division of Biostatistics Department of Health Sciences Research Mayo Clinic Rochester, Minnesota Violaine Arnaud INSERM U399 Universite´ de la Me´diterrane´e Faculte´ de Me´decine Marseille, France Regine Bergholdt Steno Diabetes Center Gentofte, Denmark

Jeffrey Bidwell Department of Cellular and Molecular Medicine University of Bristol School of Medical Sciences Bristol, United Kingdom

Ivo Boudakov Division of Transplant Research Toronto General Hospital Toronto, Ontario, Canada

Giuseppina Candore Gruppo di Studio sull’Immunosenescenza Dipartimento di Biopatologia e Metodologia Biomediche Universita` di Palermo Palermo, Italy

Maurizio Cardelli Italian National Research Center on Aging Ancona, Italy

Calogero Caruso Gruppo di Studio sull’Immunosenescenza Dipartimento di Biopatologia e Metodologia Biomediche Universita` di Palermo Palermo, Italy

Marco Caruso Dipartimento di Medicina Interna Malattie Cardiovascolari e Nefrourologiche Universita` di Palermo Palermo, Italy

Luca Cavallone Gruppo di Studio sull’Immunosenescenza Dipartimento di Biopatologia e Metodologia Biomediche Universita` di Palermo Palermo, Italy and Italian National Research Center on Aging Ancona, Italy Christophe Chevillard INSERM U399 Universite´ de la Me´diterrane´e Faculte´ de Me´decine Marseille, France Giuseppina Colonna-Romano Gruppo di Studio sull’Immunosenescenza Dipartimento di Biopatologia e Metodologia Biomediche Universita` di Palermo Palermo, Italy Christophe Combadie`re Laboratoire d’Immunologie Cellulaire INSERM U543 and Universite´ Pierre et Marie Curie Faculte´ de Me´decine Pitie´-Salpeˆtrie`re Paris, France Alda Maria Da-Cruz Laboratorio de Imunopatologia Instituto Oswaldo Cruz. FIOCRUZ Rio de Janeiro, Brazil Sandra D’Alfonso Department of Medical Sciences A. Avogadro University Novara, Italy Herve´ Do Centre National de Ge´notypage Evry, France and E´quipe Ge´nomique Bioinformatique et Pathologies du Syste`me Immunitaire INSERM U736 Centre de Recherche des Cordeliers Paris, France

Rachelle Donn Centre for Molecular Medicine ARC Epidemiology Unit The University of Manchester Manchester, United Kingdom Carita Eklund Department of Microbiology and Immunology Medical School, University of Tampere Tampere, Finland Marı´ a Fedetz Instituto de Parasitologı´ a y Biomedicina Lo´pez Neyra Consejo Superior de Investigaciones Cientı´ ficas Granada, Spain Claudio Franceschi Italian National Research Center on Aging Ancona, Italy and Department of Experimental Pathology and C.I.G. Interdepartmental Center ‘‘L. Galvani’’ University of Bologna Bologna, Italy Massimo Gadina Centre for Cancer Research and Cell Biology Queen’s University Belfast Belfast, United Kingdom Reginald M. Gorczynski Division of Transplant Research Toronto General Hospital Toronto, Ontario, Canada An Goris Laboratory of Clinical and Experimental Neurology Katholieke Universiteit Leuven U.Z. Gasthuisberg Leuven, Belgium

Thomas Ho¨hler Medizinische Klinik I Prosper-Hospital Recklinghauen, Germany Mikko Hurme Department of Microbiology and Immunology Medical School, University of Tampere Tampere University Hospital Centre for Laboratory Medicine Tampere, Finland Orhun H. Kantarci Department of Neurology Mayo Clinic and Foundation Rochester, Minnesota Jussi Karjalainen Department of Respiratory Medicine Tampere University Hospital Tampere, Finland Rachael Kilding Division of Genomic Medicine University of Sheffield Sheffield, United Kingdom Ku¨lli Kingo Department of Dermatology and Venerology University of Tartu Tartu, Estonia Sulev Ko˜ks Department of Physiology University of Tartu Tartu, Estonia Claire Fernandez Kubelka Laboratorio de Imunologia Viral Instituto Oswaldo Cruz. FIOCRUZ Rio de Janeiro, Brazil

Pui-Yan Kwok Cardiovascular Research Institute and Center for Human Genetics University of California San Francisco, California Tarja Laitinen GeneOS Ltd. Helsinki, Finland Joseli Lannes-Vieira Laboratorio de Pesquisa em Autoimunoidade e Imuno-Regulac¸a˜o Instituto Oswaldo Cruz. FIOCRUZ Rio de Janeiro, Brazil Elise Lavergne Laboratoire d’Immunologie Cellulaire INSERM U543 and Universite´ Pierre et Marie Curie Faculte´ de Me´decine Pitie´-Salpeˆtrie`re Paris, France Ross Lazarus Channing Laboratory Brigham and Women’s Hospital and Harvard Medical School Boston, Massachusetts Domenico Lio Gruppo di Studio sull’Immunosenescenza Dipartimento di Biopatologia e Metodologia Biomediche Universita` di Palermo Palermo, Italy Michael I. Luster Toxicology and Molecular Biology Branch Health Effects Laboratory Division National Institute for Occupational Safety and Health Morgantown, West Virginia

Fuencisla Matesanz Instituto de Parasitologı´ a y Biomedicina Lo´pez Neyra Consejo Superior de Investigaciones Cientı´ ficas Granada, Spain Milton Ozo´rio Moraes Laboratorio de Hanseniase Instituto Oswaldo Cruz. FIOCRUZ Rio de Janeiro, Brazil Jorge R. Oksenberg Department of Neurology University of California San Francisco, California Fabiola Olivieri Italian National Research Center on Aging Ancona, Italy Marja Pertovaara Department of Internal Medicine Section of Rheumatology Tampere University Hospital Tampere, Finland Tanja Pessi Department of Microbiology and Immunology Medical School, University of Tampere Tampere, Finland

Thereza Quirico-Santos Laborato´rio de Patologia Celular Instituto de Biologı´ a Universidade Federal Fluminense Campus do Valonguinho Rua Visconde do Rio Branco s/no Niteroi Rio de Janeiro, Brazil Annika Raitala Department of Microbiology and Immunology Medical School, University of Tampere Tampere University Hospital Centre for Laboratory Medicine Tampere, Finland David W. Ray Endocrine Sciences Research Group Centre for Molecular Medicine The University of Manchester Manchester, United Kingdom Irene Maeve Rea Public Health Medicine and Primary Care Geriatric Medicine Whitla Medical Building Queens University Belfast Belfast, United Kingdom

Flemming Pociot Steno Diabetes Center Gentofte, Denmark

John D. Rioux University of Montreal Montreal Heart Institute Montreal, Quebec, Canada

Be´ne´dicte Puissant Laboratoire d’Immunologie Cellulaire INSERM U543 and Universite´ Pierre et Marie Curie Faculte´ de Me´decine Pitie´-Salpeˆtrie`re Paris, France

Owen A. Ross Northern Ireland Regional Histocompatibility and Immunogenetics Laboratory Belfast City Hospital Belfast, United Kingdom

Helgi Silm Department of Dermatology and Venerology, University of Tartu Tartu, Estonia Koen Vandenbroeck School of Pharmacy Center of Molecular Therapeutics Queen’s University of Belfast Belfast, Northern Ireland United Kingdom Eero Vasar Department of Physiology University of Tartu Tartu, Estonia Alexandre Vasilescu Centre National de Ge´notypage Evry, France and E´quipe Ge´nomique Bioinformatique et Pathologies du Syste`me Immunitaire INSERM U736 Centre de Recherche des Cordeliers Paris, France Sonya Vasto Gruppo di Studio sull’Immunosenescenza Dipartimento di Biopatologia e Metodologia Biomediche Universita` di Palermo Palermo, Italy

Miia Virta Department of Microbiology and Immunology University of Tampere Medical School Tampere, Finland Brian G. Weinshenker Department of Neurology Mayo Clinic and Foundation Rochester, Minnesota Anthony G. Wilson Division of Genomic Medicine University of Sheffield Sheffield, United Kingdom Berran Yucesoy Toxicology and Molecular Biology Branch Health Effects Laboratory Division National Institute for Occupational Safety and Health Morgantown, West Virginia Jean-Francois Zagury Chaire de Bioinformatique Conservatoire National des Arts et Me´tiers Paris, France and E´quipe Ge´nomique Bioinformatique et Pathologies du Syste`me Immunitaire INSERM U736 Centre de Recherche des Cordeliers Paris, France

Introduction Recent years have seen an explosion in the publication of scientific articles dealing with cytokine genetics. This volume constitutes the very first integral effort to bring together, review and structure up-to-date information on polymorphisms in cytokine genes, on haplotype structures and linkage disequilibrium patterns in cytokine gene loci, on functional biological effects of polymorphisms, and on genetic associations with disease. In a series of 29 chapters, spread over three parts, written by the world’s leading specialists, the reader is first introduced to general concepts related to genetics of multifactorial diseases (Part A). In Part B, polymorphisms in the most important cytokine genes or gene clusters and their biological and genetic effects in multifactorial diseases are documented in nine cytokine gene-centered chapters. In the fourteen disease-centered chapters of Part C, the role of cytokine gene polymorphisms in a multitude of multifactorial conditions is examined, including autoimmune or chronic inflammatory diseases (rheumatoid arthritis, osteoarthritis, spondyloarthropathies, systemic lupus erythematosus, Sjo¨gren’s syndrome, multiple sclerosis, psoriasis, Type 1 and 2 diabetes, asthma and atopy, inflammatory bowel disease and pulmonary fibrosis), cardiovascular disease (atherosclerosis), infectious diseases (HIV/AIDS, schistosomiasis, Helicobacter infection and gastric cancer, hepatitis B and C virus infection, viral haemorrhagic fevers, tuberculosis, leprosy, leishmaniasis and Chagas disease) and longevity. The structure, scope and information content of this book will make it a valuable and easily accessible resource for both novice and expert geneticists, and immunologists, cell biologists and clinicians alike, and is a must for everyone involved in or planning to perform cytokine genetics or immunogenetics studies.

List of Abbreviations AD AIDS AS CD CHD ECM HBV HCV HIV HSV IBD IDDM IFN-i IL-j IPF LD MI MS OR Ps RA RR SLE SNP SS TB TNF T1D T2D UTR VHF

Alzheimer’s disease acquired immunodeficiency syndrome ankylosing spondylitis Crohn’s disease coronary heart disease extracellular matrix hepatitis B virus hepatitis C virus human immunodeficiency virus herpes simplex virus inflammatory bowel disease insulin-dependent diabetes mellitus interferon-i interleukin-j idiopathic pulmonary fibrosis linkage disequilibrium myocardial infarction multiple sclerosis odds ratio psoriasis rheumatoid arthritis relative risk systemic lupus erythematosus single nucleotide polymorphism Sjo¨gren’s syndrome tuberculosis tumor necrosis factor Type 1 (insulin-dependent) diabetes mellitus Type 2 diabetes mellitus untranslated region viral haemorrhagic fevers

Contents Part A: General Concepts.................................................................................................. 1 Chapter 1

The Biology of Cytokines: General Principles, Properties, and Lessons from Animal Models ................................................. 3

Davide Agnello and Massimo Gadina Chapter 2

Genetics of Multifactorial Disorders............................................................... 35

Jorge R. Oksenberg and John D. Rioux Chapter 3

Statistical Approaches to Analysis of Polymorphisms in Multifactorial Conditions............................................................................ 47

An Goris and Mariza de Andrade Chapter 4

Introduction to Integrated Bioinformatic Resources for Cytokine Genetics Research...................................................................... 61

Ross Lazarus Chapter 5

Cytokine Gene Nucleotide Sequence Alignments ........................................... 73

Jeffrey Bidwell Chapter 6

SNP Genotyping Techniques .......................................................................... 83

Pui-Yan Kwok Part B: Cytokine Gene Polymorphisms ........................................................................... 93 Chapter 7

The IL1 Cluster ............................................................................................... 95

Tanja Pessi, Carita Eklund, Annika Raitala, and Mikko Hurme Chapter 8

IL-2 Biology and Polymorphisms in Multifactorial Conditions ................... 109

Fuencisla Matesanz, Marı´a Fedetz, and Antonio Alcina Chapter 9

The Chromosome 5q23.1–q31.1 Cluster of Cytokines.................................. 121

Tarja Laitinen Chapter 10 Ross Lazarus

IL10 ............................................................................................................. 133

Chapter 11

The IL19 Subfamily of Cytokines ............................................................... 147

Sulev Ko˜ks, Ku¨lli Kingo, Eero Vasar, and Helgi Silm Chapter 12

The IFNG–IL26–IL22 Cytokine Gene Cluster............................................ 157

Koen Vandenbroeck and An Goris Chapter 13

TNF Polymorphisms and Disease ............................................................... 175

Reginald M. Gorczynski and Ivo Boudakov Chapter 14

Macrophage Migration Inhibitory Factor (MIF )....................................... 191

Zaynab Alourfi, David W. Ray, and Rachelle Donn Chapter 15

Polymorphisms of Chemokines and Their Receptors ................................. 207

Be´ne´dicte Puissant, Christophe Combadie`re, and Elise Lavergne Part C: Polymorphic Cytokine Networks in Multifactorial Conditions............................ 227 Chapter 16

Asthma and Atopy ...................................................................................... 229

Jussi Karjalainen, Miia Virta, Kati A˚djers, and Mikko Hurme Chapter 17

Common Rheumatic Diseases ..................................................................... 245

Rachael Kilding and Anthony G. Wilson Chapter 18

Systemic Lupus Erythematosus ................................................................... 257

Sandra D’Alfonso Chapter 19

Sjo¨gren’s Syndrome ..................................................................................... 279

Marja Pertovaara Chapter 20

Multiple Sclerosis ........................................................................................ 289

Orhun H. Kantarci and Brian G. Weinshenker Chapter 21

Type 1 and 2 Diabetes................................................................................. 305

Regine Bergholdt and Flemming Pociot Chapter 22

Psoriasis ....................................................................................................... 321

Sulev Ko˜ks, Ku¨lli Kingo, Eero Vasar, and Helgi Silm Chapter 23

Diseases of the Gastrointestinal Tract ........................................................ 337

Thomas Ho¨hler

Chapter 24

Pulmonary Fibrosis ..................................................................................... 351

Berran Yucesoy and Michael I. Luster Chapter 25

Atherosclerosis............................................................................................. 363

Giuseppina Candore, Sonya Vasto, Giuseppina Colonna-Romano, Domenico Lio, Marco Caruso, Irene Maeve Rea, and Calogero Caruso Chapter 26

Longevity ..................................................................................................... 379

Irene Maeve Rea, Giuseppina Candore, Luca Cavallone, Fabiola Olivieri, Maurizio Cardelli, Claudio Franceschi, Giuseppina Colonna-Romano, Domenico Lio, Owen Anthony Ross, and Calogero Caruso Chapter 27

AIDS ........................................................................................................... 395

Alexandre Vasilescu, Herve´ Do, and Jean-Francois Zagury Chapter 28

Tropical Infectious Diseases ........................................................................ 413

Thereza Quirico-Santos, Alda Maria Da-Cruz, Claire Fernandez Kubelka, Joseli Lannes-Vieira, and Milton Ozo´rio Moraes Chapter 29

Suseptibility to Infection and Severe Disease in Schistosomiasis ............................................................................................ 431

Violaine Arnaud and Christophe Chevillard Index............................................................................................................................ 447

Part A General Concepts

1

The Biology of Cytokines: General Principles, Properties, and Lessons from Animal Models Davide Agnello and Massimo Gadina

CONTENTS 1.1 1.2

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Cytokines of Innate Immunity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.1 Cytokines Involved in Inflammation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.1.1 Tumor Necrosis Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.1.2 Interleukin-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2.1.3 Interleukin-6 and Cytokines Sharing the gp130 Receptor Subunit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.2.2 Cytokines with Antiviral Activity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2.2.1 Type I Interferons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3 Cytokines of Adaptive Immunity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.3.1 Cytokines Involved in T Cell Development, Proliferation, Death, and Survival . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.3.1.1 Interleukin-7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.3.1.2 Interleukin-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.3.1.3 Interleukin-15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.3.1.4 Interleukin-21 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.3.2 Cytokines Involved in Th1 Immune Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.3.2.1 Interleukin-12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.3.2.2 Interleukin-23 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.3.2.3 Interleukin-27 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.3.2.4 Interleukin-18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.3.2.5 Interferon-g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.3.2.6 Lymphotoxins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.3.3 Cytokines Involved in Th2 Immune Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.3.3.1 Interleukin-4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 1.3.3.2 Interleukin-5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.3.3.3 Interleukin-13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.3.4 Cytokines Involved in Regulation of Immune Response . . . . . . . . . . . . . . . . . . . . . . . . 22 1.3.4.1 Interleukin-10 and IL-10-Related Cytokines . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 1.3.4.2 Transforming Growth Factor-b . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1.4 Chemokines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3

4

1.1

Cytokine Gene Polymorphisms in Multifactorial Conditions

INTRODUCTION

Cytokines are soluble factors which play a critical role in regulating all aspects of immune responses. Inflammation, lymphoid development, homeostasis, differentiation, tolerance, and memory are all regulated by cytokines which exert their activity by binding to specific receptors on the surface of target cells and inducing a signalling cascade which ultimately results in the aforementioned biological effects. Cytokines are usually distinguished from hormones as they usually act locally, in an autocrine or paracrine fashion, whereas hormones act at distance. However some cytokines may also enter the blood stream and act at longer distances as well. Many cytokines are pleiotropic since they may induce several different types of responses, often on different cell types. For instance interleukin (IL)-6 induces acute-phase protein (APP) synthesis in the liver and stimulates terminal differentiation of B cells into antibody-secreting plasma cells. However cytokine activity may be also redundant since many different cytokines may induce the same biological action. For instance APP synthesis in hepatocytes can be induced not only by IL-6, but also by the other cytokines that share the gp130 receptor subunit. Cytokines are often classified according to the type of receptor they bind. This classification includes the type I cytokine or hematopoietin family, the type II cytokine or interferon (IFN) family, the tumor necrosis factor (TNF) family, the IL-1 family and the transforming growth factor (TGF)-b family. In the following chapter cytokines have been grouped according to their main immunological function: cytokines involved in inflammation and innate immunity, cytokines involved in T cell development and proliferation, cytokines produced by T helper (Th) 1 and Th2 lymphocytes and cytokines that regulate the immune response. In the final section we will review some aspects of chemokine biology. Growth factors and hematopoietic cytokines will not be described here, as they are beyond the scope of the textbook. Phenotypes of cytokine and cytokine receptor-deficient mice are represented in Table 1.1 and Table 1.2, respectively.

1.2

CYTOKINES OF INNATE IMMUNITY

1.2.1

CYTOKINES INVOLVED

IN INFLAMMATION

Inflammation is defined as a complex response by which vascularized tissues respond to injury and results in redness, heat, swelling, and pain. This process involves a cascade of events that include mediator production, cell trafficking, microvascular permeability, extravasation, coagulation, etc. Pro-inflammatory cytokines such as TNF and IL-1 are among the key mediators of inflammation and their production is induced by microorganisms or microbial products such as the lipopolysaccharides (LPSs) of Gram-negative bacteria. These cytokines play an important role in defense against infectious agents by activating the microbicidal potential of neutrophils and macrophages. Moreover, both microbial products and pro-inflammatory cytokines induce the differentiation of immature dendritic cells (DCs) into mature DCs that have the ability to activate naı¨ ve T cells, hence initiating the adaptive immune response. However, an excessive production of pro-inflammatory cytokines can also lead to severe side effects with increased vascular permeability, hypotension, multiple organ failure and ultimately shock and death.1 1.2.1.1

Tumor Necrosis Factor

TNF (previously known as TNFa) was identified as a factor present in the serum of LPStreated animals that produced hemorrhagic necrosis of solid tumors and acted as a mediator of cachexia and wasting associated with infection and cancer.2 TNF is one of the most

The Biology of Cytokines

5

TABLE 1.1 Phenotype of Cytokine-Deficient Mice IL-1 Family IL-1b

IL-1ra IL-18 TNF Family TNF LTa

LTb Type I Cytokines IL-2 IL-4 IL-5 IL-6 IL-7 IL-12 p40 IL-12 p35 IL-13 IL-15 IL-23 p19 EBI3 Type II Cytokines IFN-g IL-10

TGF-b Family TGF-b1

TGF-b2 TGF-b3

Reduced APP and IL-6 production and no fever and anorexia after turpentine-induced inflammation. Almost normal response to LPS administration (decreased LPS-induced leptin production). Low litter number and growth retardation in adult life. Elevated IL-6 and APP levels. Spontaneous development of chronic inflammatory polyarthropathy in selected strains. Reduced NK activity. Defective Th1 immune response. Increased susceptibility to infections. Resistance to experimental arthritis. Resistance to endotoxin toxicity. Increased susceptibility to infections. Defective germinal center formation. Absence of Peyer’s patches and peripheral lymphoid structures (mesenteric lymph nodes sometimes present). Major defects in spleen architecture. Defective germinal center formation. Absence of Peyer’s patches and some peripheral lymph nodes (presence of mesenteric and cervical lymph nodes). Defective germinal center formation. Massive enlargement of peripheral lymphoid organs. Polyclonal T and B cell expansion. Impaired AICD. Development of hemolytic anemia and inflammatory bowel disease. Defective Th2 differentiation and IgE production. Decreased allergic responses. Decreased eosinophilia in asthma models. Impaired acute phase response. Decreased numbers of hematopoietic progenitor cells. Impaired antibody production. Greatly reduced T and B cell development (less severe than IL-7Ra
/
). Absence of gdT cells. Reduced Th1 response. Enhanced Th2 response. Impaired NK activity. Increased susceptibility to intracellular pathogens (more severe than p35
/
). Resistance to EAE. Reduced Th1 response. Enhanced Th2 response. Increased susceptibility to intracellular pathogens (less severe than p40
/
). Increased susceptibility to EAE. Resistance to allergen-induced airways hypersensitivity. Decreased IgE levels. Absence of NK cells. Reduction of memory CD8þ T cells. Resistance to EAE and CIA. Impaired DTH reaction. Transient reduction of Th1 response. Increased susceptibility to intracellular pathogens. Increased or decreased susceptibility to autoimmune diseases (depending on the model). Increased susceptibility to endotoxin toxicity. Enhanced Th1 immune response. Increased resistance to infections. Increased susceptibility to autoimmune diseases (spontaneous development of inflammatory bowel disease). Embryonic lethality (50 to 99%, depending on the strains). Severe multiorgan autoimmune inflammation. Myeloid hyperplasia. Reduced IgA-producing plasma cells. Development of colon cancers in immunodeficient backgrounds. Death by 4 weeks of age. 100% perinatal lethality. Many developmental defects. 100% perinatal lethality. Abnormal lung development and cleft palate.

important mediators of inflammation and the host’s response to injury or pathogens. It is produced primarily by macrophages and monocytes after activation by bacterial products such as LPS. Administration of TNF to laboratory animals is able to reproduce many of the effects of LPS.

6

Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 1.2 Phenotype of Cytokine Receptor-Deficient Mice IL-1 Family IL-1RI IL-1RAcP IL-18Ra TNF Family TNFRI (p55) TNFRII (p75) LTbR

Type I Cytokines IL-2Ra

IL-2Rb

IL-4Ra IL-7Ra IL-13Ra2 IL-15Ra gc IL-12Rb1 IL-12Rb2 WSX-1 gp130 LIFRb Type II Cytokines IFNAR1 IFNGR1

Reduced inflammation and acute phase response after turpentine administration. No response to IL-1 administration in vivo. Reduced NK activity. Defective Th1 immune response. Resistance to endotoxin toxicity. Increased susceptibility to infections. Defective Peyer’s patches formation. Defective germinal center formation. Exaggerated inflammatory responses. Reduced activated T cell apoptosis. Complete absence of peripheral lymph nodes and Peyer’s patches. Completely altered spleen architecture. Defective germinal center formation and impaired humoral responses. Decreased numbers of NK cells. Reduced DC migration to secondary lymphoid organs. Massive enlargement of peripheral lymphoid organs. Polyclonal T and B cell expansion. Impaired AICD. Development of haemolytic anemia and inflammatory bowel disease. Absence of NK cells. Enlargement of lymph nodes and spleen with expansion of activated T cells. Increased serum IgG1 and IgE levels. Development of hemolytic anemia. Death within 3 months of age. Defective Th2 differentiation and IgE production. Greatly reduced T and B cell development (more severe than IL-7
/
). Absence of gdT cells. Enhanced IL-13 response. Absence of NK cells. Reduction of memory CD8þ T cells. Impaired T and B cell development (with expansion of ‘‘memory/activated’’ CD4þ T cells in older mice). Absence of gdT cells and NK cells. Impaired Th1 differentiation. Resistance to EAE. Impaired Th1 differentiation. Increased susceptibility to EAE. Transient defect in Th1 response. Increased T cell proliferation in some inflammatory models. Embryonic lethality. Hypoplastic development of heart ventricular walls. Reduced hematopoietic progenitor numbers. Postnatal lethality. Profound loss of motor neurons. Reduction in bone mass. Increased susceptibility to viral infections. Increased susceptibility to intracellular pathogens. Increased or decreased susceptibility to autoimmune diseases (depending on the model).

TNF is synthesized as a type II transmembrane protein which is cleaved in the extracellular domain by a protease to release the soluble form of TNF.3,4 Both soluble and membrane-bound forms of TNF are active. TNF exerts its biological functions by binding to two receptors, type I (TNFRI or p55) and type II (TNFRII or p75), that are present in almost all cell types and also serve as receptors for lymphotoxin (LT)a (see below).3–5 The primary inflammatory response to TNF is mediated by TNFRI which is the main signalling receptor and contains a death domain region within its intracellular portion. TNFRII can deliver some intracellular signals but this receptor is believed to act mainly as a ligand passer, binding TNF molecules and passing them to TNFRI. Both TNFRs can be cleaved by matrix metalloproteases and their extracellular portions are shed from the cell surfaces. The shed soluble TNFRs retain the ability to bind the ligand without signalling, thereby neutralizing TNF activity. Defective proteolytic shedding of TNFRI has been associated with

The Biology of Cytokines

7

constitutional inflammation and fever in certain cases of TNF receptor-associated periodic syndrome (better known as TRAPS).6 The inflammatory responses to TNF are mediated both directly and through induction of IL-1 or other proinflammatory cytokines. TNF induces the expression of cyclooxygenase type-2 (COX-2), promotes adhesion of leukocytes to endothelium by increasing the expression of adhesion molecules, and activates neutrophils boosting phagocytosis and production of reactive oxygen species. It also elicits the synthesis of IL-1, IL-6, chemokines, and TNF itself in mononuclear cells and up-regulates the expression of MHC molecules.7 These activities are important in host resistance to infection and mice lacking TNFRI are much more susceptible to pathogens such as Listeria monocytogenes or mycobacteria.5 TNF pro-inflammatory activities explain why this cytokine is also a pathogenic factor in several autoimmune diseases. Inhibition of TNF activity by either a human/murine chimeric antibody against human TNF (infliximab) or a fusion protein of TNFRII and human IgG1 (etanercept) has proven to be remarkably effective in treating rheumatoid arthritis and Crohn’s disease and both drugs are now in clinical use.8 Beside the local effects on the inflammatory process, TNF also acts in an endocrine fashion inducing some of the systemic signs of inflammation such as fever and APP synthesis in the liver. It activates the hypothalamic–pituitary–adrenal axis (HPAA) with increased levels of adrenocorticotropin hormone (ACTH) that in turn induces an elevation of glucocorticoids. Since glucocorticoids are potent inhibitors of cytokine synthesis, the HPAA activation might represent a negative feedback to limit TNF production and the inflammatory process.9 TNF is also thought to be one of the key mediators of cachexia, a wasting condition that is characterized by anorexia in association with the development of a net catabolic state.7,10 High TNF levels result in severe adverse effects and even death. Administration of high doses of TNF to animals leads to a septic shock-like syndrome with myocardial suppression, hypotension, vascular leakage, and stimulation of the clotting cascades.5,7 The key role of TNF in the pathogenesis of septic shock has been supported by experimental observations showing that infusion of anti-TNF antibodies can prevent septic shock during lethal bacteremia and that TNF- and TNFR-deficient mice are protected from LPS toxicity. However, in contrast to the animal models, treatment of septic shock with anti-TNF antibodies in humans did not show any therapeutic benefit.5 1.2.1.2

Interleukin-1

IL-1 was originally described as a macrophage-derived factor with co-mitogenic effect on T lymphocytes and was referred to as lymphocyte activating factor (LAF). In a completely different field, scientists studying the pathogenesis of fever found a circulating pyrogenic factor in febrile rabbits they termed endogenous pyrogen (EP). When human IL-1b was cloned it became clear that LAF and EP were in fact the same molecule. IL-1 exists in two forms, IL-1a and IL-1b which are the products of two different genes. Both forms are synthesized as 31 kDa precursors and both lack the conventional leader sequence. IL-1a is biologically active as a precursor but remains mostly intracellular and is not usually found in body fluids or circulating except during severe disease when it may be released from dying cells. On the contrary, IL-1b precursor becomes fully active after being processed to the mature 17 kDa form that is then secreted in considerable amounts.11,12 The main enzyme responsible for the cleavage of pro-IL-1b is an intracellular cysteine protease, the IL-1 converting enzyme (ICE, also known as caspase-1), which also processes the IL-18 precursor.11,12 There are two receptors for IL-1, type I (IL-1RI) and type II (IL-1RII), but only IL-1RI transduces signals. When IL-1 binds to IL-1RI a complex is formed which then binds to the IL-1R accessory protein (IL-1RAcP) and it is likely that the heterodimerization of the

8

Cytokine Gene Polymorphisms in Multifactorial Conditions

cytosolic domains of IL-1RI and IL-1RAcP triggers IL-1 signal transduction.11,12 By contrast IL-1RII has a short cytoplasmic tail and is incapable of signalling and it has been suggested to be a decoy receptor functioning as a negative regulator of IL-1 system.13 The extracellular domains of both IL-1 receptors are susceptible to proteolytic cleavage near the membrane surface and the soluble shed receptors bind and inhibit IL-1 functions.11,12 Like TNF, the primary sources of IL-1b are monocytes, macrophages and DCs and nearly all microbial products, such as LPS, are able to induce IL-1b synthesis. Biological activities of IL-1 largely overlap with those of TNF. Moreover TNF and IL-1 act synergistically in nearly every model of local and systemic inflammation. Contrary to TNF though, IL-1 does not induce programmed cell death.14 When produced locally IL-1 acts as an autocrine or paracrine mediator of inflammatory response and induces the expression of COX-2, IL-6, and adhesion molecules. Similarly to TNF, when released in larger quantities into the circulation IL-1 acts systemically and induces fever, anorexia, APP synthesis, and activates the HPAA. Accordingly, IL-1bdeficient mice do not develop anorexia or fever, have no circulating IL-6 and have an impaired acute-phase response in a model of inflammation induced with turpentine. In contrast, IL-1b-deficient mice have nearly the same response to LPS as do wild-type mice, indicating that IL-1b is not essential for the systemic response to LPS.12 IL-1 is the only cytokine that is regulated by a natural competitive homologue, the IL-1 receptor antagonist (IL-1ra). Like IL-1, IL-1ra binds IL-1RI but it does not recruit IL1RAcP to form the complex necessary to signal. When IL-1ra occupies IL-1RI, IL-1 cannot bind the receptor and thus there is no biological response. In contrast with IL-1-deficient mice which are born healthy and develop normally, IL-1ra-deficient mice exhibit growth retardation in adult life. In selected strains, IL-1ra-deficient mice spontaneously develop a chronic inflammatory arthropathy resembling rheumatoid arthritis.12 IL-1ra administration has been shown to reduce inflammation and bone loss in animal models of arthritis and the recombinant form of IL-1ra is now approved for treating rheumatoid arthritis in humans.12 1.2.1.3

Interleukin-6 and Cytokines Sharing the gp130 Receptor Subunit

IL-6 was originally identified as a factor that induced immunoglobulin production in activated B cells and was named B cell stimulatory factor (BSF)-2.15 IL-6 is produced by lymphoid and nonlymphoid cells such as T and B lymphocytes, endothelial cells, fibroblasts, keratinocytes, and several tumor cells. IL-6 expression in mononuclear phagocytes after stimulation with LPS, TNF, or IL-1 has been well documented. IL-6 induces fever and leukocytosis when administered in vivo. This cytokine is a major inducer of APPs in the liver and stimulates hepatocytes to produce C-reactive protein (CRP), fibrinogen and serum amyloid A (SAA) whereas it simultaneously suppresses albumin production. APPs synthesis is impaired in IL-6-deficient mice after mineral oil injection.16,17 Circulating IL-6 levels rise after infection, inflammation, or trauma and patients with rheumatoid arthritis, Castelman’s disease, and Crohn’s disease show high levels of IL-6 in their sera.18 Besides its effects on the inflammatory process, IL-6 is a pleiotropic cytokine with a wide range of activities. IL-6 is an important growth and differentiation factor for B cells, and IL6-deficient mice exhibit severe impairment in antibody production following viral infection. However, IL-6 also induces growth of T cells and differentiation of cytotoxic T cells; it acts synergistically with IL-3 to support hematopoiesis inducing differentiation of macrophages, megakaryocytes and osteoclasts. This cytokine also stimulates the release of ACTH and a variety of anteriopituitary hormones and in the nervous system induces the differentiation of pheochromocytoma PC12 cells into neuronal cells.16,17 IL-6 binds to an 80 kDa receptor named IL-6Ra. This receptor has a short cytoplasmic domain that is not essential for signal transduction. The complex of IL-6 and IL-6Ra then

9

The Biology of Cytokines

associates with a 130 kDa signal transducing membrane protein called gp130, expressed by almost all cells of the body. A naturally occurring soluble form of the extracellular domain of IL-6Ra (sIL-6Ra) has been found in various body fluids. This sIL-6Ra retains ligandbinding activity and the IL-6/sIL-6Ra complex is able to associate with gp130 and to initiate receptor signalling. So the presence of sIL-6Ra can confer IL-6 responsiveness on cells that express gp130 but not IL-6Ra.16 Besides IL-6, seven other cytokines are known to use gp130 as a critical component for signal transduction: IL-11, IL-27, leukemia inhibitory factor (LIF), oncostatin M (OSM), ciliary neurotrophic factor (CNTF), cardiotrophin-1 (CT-1), and novel neurotrophin-1/B cell stimulating factor-3 (NNT-1/BSF-3). IL-11 and CNTF, like IL-6, first bind to specific receptors (termed IL-11Ra and CNTFRa, respectively) and then the IL-11/IL-11Ra complex associates with a homodimer of gp130 whereas the CNTF/CNTFRa complex associates with a heterodimer of gp130 and LIF receptor b (LIFRb), a molecule that is structurally related to gp130. LIF and CT-1 also use a receptor complex which is a heterodimer of LIFRb and gp130. OSM instead binds directly to gp130 and then signals through two types of receptor complexes, one containing LIFRb and the other containing a specific subunit (OSMRb) closely related to gp130 and LIFRb. NNT-1/BSF-3 associates with the soluble receptor cytokine-like factor-1 (CLF-1) and together they form a second ligand for CNTFRa.19 All those cytokines are pleiotropic and exhibit overlapping biological functions because of the shared usage of receptor components. For instance, LIF was originally isolated as a factor inducing macrophage differentiation of a murine myeloid leukemia cell line but also IL-6, OSM, and CT-1 are now known to have the same activity. The hematopoietic functions of IL-6, especially on platelet production, and the cardiotrophic functions of CT-1 are also shared by IL-11, LIF, and OSM, and all the cytokines of the IL-6 family can induce hepatic APP production.16 Disruption of gp130 gene in mice results in a fetal-lethal phenotype because of a defect in myocardial development, presumably related to the absence of CT-1 signalling, in addition to certain defects in hematopoiesis.16 The properties of IL-27 will be discussed later.

1.2.2 CYTOKINES 1.2.2.1

WITH

ANTIVIRAL ACTIVITY

Type I Interferons

IFNs are probably the oldest known cytokines and were identified because of their ability to interfere with virus replication.20 The IFNs are classified into two distinct types: type I and type II IFNs. Type I IFNs are produced by many cell types in direct response to viral infection and include IFN-a, IFN-b, and IFN-o. IFN-a is preferentially expressed by cells of a lymphoid origin and IFN-b is expressed by almost all cell types. The only type II IFN is IFN-g that is produced mainly by activated T lymphocytes and NK cells and will be discussed later. Whereas IFN-b and IFN-o are encoded by single genes, there are many genes encoding for different forms of IFN-a. Nevertheless all type I IFNs have similar amino acid sequences and they all bind to a single receptor, known as IFN-a/b receptor. This receptor is a heterodimer composed of two subunits termed IFNAR1 and IFNAR2 that are members of the type II cytokine receptor family and are expressed on many different cell types.21 Type I IFNs are made by virus-infected cells to directly induce anti-viral states in neighboring uninfected cells. Even if IFN-a/b can be induced by intracellular bacteria and LPS, it is generally assumed that the major inducer of type I IFNs is double-stranded RNA (dsRNA) which is frequently present in virus-infected cells where it may be provided by the viral genome itself or formed as a result of replication or transcription of viral genomes.22 The two best characterized components of the antiviral response induced by IFNs are the

10

Cytokine Gene Polymorphisms in Multifactorial Conditions

20 –50 oligoadenylate synthetases and the dsRNA-dependent protein kinase R. Both these enzymes activate biochemical pathways leading to the inhibition of protein synthesis in the host cells and rendering them refractory to viral replication. Type I IFNs also have antiproliferative activity, slowing target cells growth or making them more susceptible to apoptosis, thereby limiting virus spread.23 In addition to their direct anti-viral functions, type I IFNs also exert several immunoregulatory effects. They increase the cytolytic activity of NK cells, up-regulate the expression of MHC class I proteins, enhance antigen presentation through the class I pathway, and promote the CD8þ T cell responses. They also promote polarization of CD4þ T cells towards the Th1 phenotype, hence representing a key link between innate and adaptive immune responses.24 IFN-a is used clinically in the treatment of certain viral infections, such as hepatitis B and C.25,26 Because of its antiproliferative action it is also used in the treatment of certain malignancies, particularly hairy cell leukemia.27 IFN-b is used in the treatment of multiple sclerosis.28 Recently, IL-28A, IL-28B, and IL-29, also known as IFN-2, IFN-3, and IFN-1, respectively, have been shown to be induced by viral infection and to exhibit antiviral activity, although the relative roles of IFN- a/b and IL-28/29 in antiviral immunity remain to be established.29,30

1.3

CYTOKINES OF ADAPTIVE IMMUNITY

1.3.1

CYTOKINES INVOLVED IN T CELL DEVELOPMENT, PROLIFERATION, DEATH, AND SURVIVAL

T lymphocytes develop in the thymus where bone marrow precursors undergo a process of proliferation, differentiation, and selection that ultimately converts them into mature T cells. The development of T cells in the thymus critically depends on IL-7. Mature lymphocytes emigrate from the thymus and before contact with foreign antigens the survival of naı¨ ve T cells in the periphery still requires IL-7 as well as continuous contact with self peptides bound to the MHC. After encountering an appropriate antigen, T lymphocytes undergo vigorous clonal expansion and acquire effector functions. During this stage IL-2 and IL-15 act as growth factors and potentiate the proliferation of activated T cells. However after this expansion phase, a substantial death of T cells occurs, resulting in a large reduction of antigen-specific lymphocytes. IL-2 may play an active role in driving the contraction phase by inducing T cell death whereas IL-7 and IL-15 likely promote lymphocyte survival, allowing memory T cell generation.31,32 1.3.1.1

Interleukin-7

IL-7 was originally discovered based on its activity in inducing proliferation of murine pro-B cells.33 In fact, this cytokine plays a critical role in the development of both T and B cells in mice and of T (but not B) cells in humans. IL-7 is produced mainly in the thymus by cortical epithelial cells but also in bone marrow by stromal cells or in intestinal epithelium. IL-7 is a member of the family of cytokines that signal through the common cytokine receptor g chain (gc) which is shared by the receptors for IL-2, IL-4, IL-7, IL-9, IL-15, and IL-21. IL-7 also uses a second receptor component, IL-7Ra, that is found on immature B cells, on thymocytes (with the exception of CD4þCD8þ double positive cells) and on most mature T cells.34,35 In the thymus IL-7 sustains survival and proliferation of thymic progenitors and promotes the rearrangement of the genes for the T cell receptor (TCR). IL-7-null mice are highly lymphopenic and thymic cellularity is reduced with a complete absence of gd T cell

The Biology of Cytokines

11

development. IL-7Ra
/
mice display an even more striking phenotype with a thymic cellularity ranging from 0.01 to 10% of normal. The different phenotype found in IL-7
/
and IL-7Ra
/
mice may depend on the fact that IL-7Ra is also part of the receptor complex for thymic stromal-derived lymphopoietin (TSLP) and hence IL-7Ra
/
mice are deficient in both IL-7 and TSLP signals.34,35 Mice deficient in gc, the second component of the IL-7 receptor, have diminished T cell numbers and absence of NK cells. In humans, mutations in gc and Jak3, the Janus kinase associated with gc, result in a severe combined immunodeficiency syndrome (also known as SCID) with defective T and NK cell generation, similar to that observed in gc-deficient mice. Mutations in IL-7Ra have also been identified in patients with deficiencies in T cells but normal or increased NK cells. Indeed the NK cell deficiency found in gc-deficient mice and in patients with gc or Jak3 mutations is due to the lack of IL-15 signal (see below), rather than IL-7. The development of B cells is also greatly reduced in IL-7
/
, IL-7Ra
/
, and gc
/
mice whereas in patients with deficiencies in gc or Jak3, B cell numbers are normal. Thus, whereas IL-7 is required for B cell development in mice, it is not absolutely required in humans.34,35 IL-7 also potently modulates mature T cell functions. IL-7 is required for the survival of peripheral naı¨ ve T cells and for the expansion of these cells in states of T cell depletion.36 During activation, IL-7 acts as a costimulator for T cells enhancing proliferation, inhibiting T cell death and facilitating the generation of memory lymphocytes.35 IL-7 also plays a role in the maintenance of memory CD8þ T cells but, unlike IL-15, seems to promote lymphocyte survival, rather than proliferation.32 1.3.1.2

Interleukin-2

IL-2 was originally identified as a T cell growth factor and was one of the first cytokines to be intensively studied.37 IL-2 is produced by T lymphocytes after antigen encounter as a consequence of signalling through the TCR and co-stimulatory molecules. Then IL-2 acts as an autocrine and paracrine growth factor and promotes clonal expansion of antigen-specific T cells by inducing cell cycle progression from the G0 to the G1 and S phases. In addition IL2 also supports the effector functions of mature lymphocytes, such as cytokine secretion and cytotoxic T lymphocyte (CTL) activity. Analogous to its effect on T cells, IL-2 also promotes the proliferation of activated B cells, increasing immunoglobulin synthesis. Also, NK cells proliferate and up-regulate their cytolytic activity in response to IL-2. However, since resting NK cells do not constitutively express the high affinity receptor (see below), stimulation generally requires relatively high doses of IL-2 and may not represent a physiologically important phenomenon.38 Importantly, IL-2 is also an essential cytokine for limiting the immune responses. In fact, IL-2 sensitizes activated T cells to undergo apoptosis when repeatedly or continuously stimulated through TCR, a process known as activation-induced cell death (AICD). AICD is believed to be an important mechanism for limiting the immune response by reducing the number of antigen-specific lymphocytes but also for maintaining peripheral tolerance by eliminating self-reactive T cells. The IL-2-mediated sensitization of T cells to AICD is partly explained by increased expression of Fas ligand and suppression of the FLIP inhibitor of Fas signalling.39 IL-2 binds to a receptor complex consisting of three distinct subunits designated IL-2Ra (also known as CD25 or Tac antigen), IL-2Rb, and the common gc. Whereas only IL-2Rb and gc are necessary for signal transduction in response to IL-2, the IL-2Ra subunit is required to create a high-affinity receptor. IL-2Ra is absent on resting T cells, but is induced in activated T cells following TCR stimulation. By contrast, resting NK cells only express IL-2Rb and gc and respond to high doses of IL-2. IL-2Ra and its homologous IL-15Ra have

12

Cytokine Gene Polymorphisms in Multifactorial Conditions

short cytoplasmic domains and share an extracellular protein-binding motif known as ‘‘sushi domain’’ that is also found in complement receptors.38 Because IL-2 potently induces T cell expansion in vitro it was thought that this cytokine also amplified T cell responses in vivo. This led to the development of therapeutic strategies aimed at modulating the IL-2 system for clinical benefit. IL-2 is used to boost immunity in patients with cancer or AIDS, although the clinical utility of IL-2 is limited by its toxicity.40,41 Conversely, a humanized anti-IL-2Ra monoclonal antibody (daclizumab) is used to suppress the rejection of transplanted organs.42 However, the idea that the main function of IL-2 is to promote T cell immunity was questioned when IL-2 and IL-2Ra-deficient mice were generated. These mice have no defects in T, B or NK cell development and display largely intact humoral and cellular immune responses. Moreover, at 4–6 weeks of age, IL-2 and IL-2Ra-deficient mice develop massive enlargements of peripheral lymphoid organs due to polyclonal expansion of T and B cells and show marked increases in serum autoantibodies resulting in severe autoimmunity with the development of hemolytic anemia and inflammatory bowel disease resembling ulcerative colitis in humans.38 These results were originally explained with the role of IL-2 in sensitizing T cells to AICD. However, it has been recently discovered that IL-2 is also critical for the development and expansion of a subset of regulatory T (Treg) lymphocytes, termed CD4þCD25þ Treg, which promote self-tolerance by suppressing T cell responses (see below). Indeed IL-2 and IL-2Ra-deficient mice are also deficient in CD4þCD25þ Treg cells and the development of autoimmunity in these mice can be prevented by adoptive transfer of wild-type Treg lymphocytes. Even if in vitro studies have suggested an important role for IL-2 in amplifying immune responses by acting as T cell growth factor, it seems that IL-2 is dispensable for inducing cellular immunity in vivo and the major physiological and non-redundant function of this cytokine is to limit rather than enhance T cell responses.43,44 1.3.1.3

Interleukin-15

IL-15 has been identified as a T cell growth factor able to stimulate the proliferation of an IL2-dependent T cell line in the presence of neutralizing anti-IL-2 antibodies.45,46 The receptor for IL-15 includes the two components of the IL-2 receptor, IL-2Rb and the common gc, as well as an IL-15-specific receptor component, IL-15Ra, that is structurally similar to IL-2Ra. Besides sharing receptor subunits and their use of common Jak/STAT signalling elements, IL-2 and IL-15 also share a number of biological activities, including the ability to stimulate the proliferation of activated T cells in vitro. However, the two cytokines also provide contrasting contributions to the life and death of lymphocytes. In fact, IL-15 acts to extend the survival of T cells inhibiting IL-2-mediated cell death. Furthermore, IL-15 stimulates the maintenance and the division of memory CD8þ T lymphocytes in vivo, whereas IL-2 inhibits their persistence. The production of IL-15 is also different from that of IL-2. IL-15 mRNA has been found in many organs and tissues however, since IL-15 production is tightly regulated at post-transcriptional level, mRNA is often expressed without concomitant protein synthesis. IL-15 production has been demonstrated in monocytes, macrophages, DCs, bone marrow stromal cells, and thymic epithelium, whereas T cells typically do not produce this cytokine.47–49 The notion that IL-2 and IL-15 perform distinct functions in vivo is supported by the analysis of mice with disrupted cytokine or cytokine receptor genes. IL-15 and IL-15Radeficient mice do not manifest lymphoid organ enlargement and autoimmune disease, but instead are lymphopenic, despite apparent normal lymphocyte development in thymus, exhibiting a decreased number of CD8þ lymphocytes and a lack of memory-phenotype CD8þ T cells. IL-15
/
and IL-15Ra
/
are also completely deficient in NK cells. The fact that

13

The Biology of Cytokines

IL-15 plays a central and non-redundant role in NK cell development also explains the absence of NK cells in patients with gc mutations. In contrast, IL-15 transgenic mice manifested an inhibition of IL-2-mediated AICD and an increased number of NK cells and memory CD8þ lymphocytes.47,49,50 1.3.1.4

Interleukin-21

IL-21 is the newest member of the common gc-dependent cytokine family. It is produced by activated CD4þ lymphocytes, especially Th2 effector cells. The biological roles of this cytokine in the immune system are still largely unknown and seem to be complex, as IL-21 has been shown to both promote and inhibit immune responses. In B cells, IL-21 augments proliferation when combined with CD40 but inhibits proliferation induced by anti-IgM. In T cells IL-21 increases proliferation after TCR ligation and enhances lytic activity of CD8þ cells but blocks IL-15-mediated expansion of memory CD8þ lymphocytes. In NK cells IL-21 has been reported to inhibit IL-15-induced expansion of resting NK cells while enhancing cytotoxicity of previously activated NK cells. The receptor for IL-21 consists of the gc plus a subunit named IL-21R that has been found on B, T, NK, and DCs and is homologous to IL-2Rb.51,52

1.3.2 CYTOKINES INVOLVED RESPONSES

IN

TH1 IMMUNE

The developmental regulation of naı¨ ve CD4þ T cells into either T helper (Th)1 or Th2 cells is critically important for effective acquired immunity and cytokines play a key role in this process. In fact when CD4þ lymphocytes are stimulated in vitro in presence of IL-12 they acquire a Th1 phenotype, whereas in the presence of IL-4 they acquire a Th2 phenotype. Th1 cells produce IFN-g and LTa and promote cell-mediated immunity, which is essential for the response against intracellular pathogens such as viruses and some types of bacteria and protozoa. Moreover Th1 cytokines are increased in chronic inflammation, autoimmune diseases such as rheumatoid arthritis (RA) and multiple sclerosis (MS), and in the animal models of those diseases. The cytokines of IL-12 family, which includes IL-23 and IL-27, are key mediators for polarizing the CD4þ T cells towards the Th1 phenotype. These cytokines often synergize with IL-18, another important cytokine in inducing a Th1-driven immune response. 1.3.2.1

Interleukin-12

IL-12 is a heterodimeric cytokine composed of two disulfide-linked subunits designated p35 and p40.53 The p40 subunit is homologous to cytokine receptors, whereas the p35 subunit is similar to IL-6 and G-CSF. IL-12 is produced by monocytes, macrophages, DCs, neutrophils, and B cells. While p35 is broadly expressed, the expression of the p40 chain is limited to phagocytic cells and results in the production of IL-12p70. The p40 gene is transcriptionally regulated and is highly inducible by microbial products whereas p35 is deregulated both transcriptionally and translationally. A variety of different pathogens induce high levels of IL-12p40 and p70 production, including Gram-positive and Gram-negative bacteria, parasites, viruses, and fungi. Microbial products such as LPS, lipoteichoic acid, peptidoglycan, and bacterial DNA induce T cellindependent production of IL-12 by cells of the innate immune system via toll-like receptor signalling.54 IL-12 is also produced in a T cell-dependent manner through the engagement of CD40 on antigen-presenting cells (APCs) with its cognate receptor CD40L on T cells.55 IL-12 production is positively regulated by IFN-g which is induced by IL-12 itself (see below). IL-12 promotes IFN-g secretion that, in turn, in a positive feedback loop, potently primes

14

Cytokine Gene Polymorphisms in Multifactorial Conditions

monocytes and PMN for further IL-12 production.56 Conversely, IL-12 production is inhibited by IL-10, IL-11, IL-13, and type I IFNs. There is some controversy as to whether IL-4 inhibits IL-12 production. In some cases it clearly does, whereas in other circumstances pre-treatment with IL-4 can enhance IL-12 production.57,58 G-protein coupled receptors (GPCRs) including CCR2, prostaglandin E2, histamine, and FcR cross-linking also inhibit IL-12 production, although some GPCRs like CCR5 positively regulate production.59 The IL-12 receptor (IL-12R) consists of two receptor subunits, b1 and b2, which are homologous to gp130. Co-expression of both b1 and b2 subunits is required for the generation of human high-affinity IL-12 binding sites. The receptor-like subunit, IL-12p40, interacts with the b1 subunit, whereas p35 interacts with the b2 subunit. The b2 subunit functions as the primary signal transducing component and recruits signalling molecules, such as signal transducers and activators of transcription (STAT)3 and STAT4.60 In contrast, IL-12Rb1 has no known signalling functions. IL-12Rb1 and IL-12Rb2 are expressed on T cells, NK cells, and DCs and this expression is tightly controlled. Resting T cells do not express b1 or b2 but these subunits are up-regulated upon T cell activation. Moreover, IFN-g stimulation up-regulates the transcription factor T-bet, which in turn, maintains IL-12Rb2 chain expression. Conversely, IL-4 has been shown to down-regulate IL-12Rb2 expression.61,62 The regulation of IL-12 receptor expression by IFN-g and IL-4 is therefore an important control mechanism for Th1/Th2 differentiation. IL-12 induces production of IFN-g by T and NK cells and this production is further enhanced by an unrelated cytokine, IL-18 (see below), the combination of these cytokines being highly synergistic. IL-12, especially in combination with IL-18, can also induce IFN-g production in macrophages. It also acts on DCs to induce further production of IL-12.63 IL12 and IFN-g antagonize Th2 differentiation and the production of IL-4, IL-5, and IL-13. In addition, IL-12 potentiates NK and T cells cytolytic activity and induces T cell proliferation. IL-12p35, p40, IL-12Rb1, and b1 knockout mice are phenotypically very similar. The mice display no obvious development abnormalities; however IFN-g secretion, Th1 development and NK activity are impaired. Conversely, generation of Th2 cells is enhanced. Deletion of p40 or IL-12Rb1 would be expected to abrogate both IL-12 and IL-23 signalling (see below). In fact, the phenotype of p40 (or IL-12Rb1) knockouts is more severe than deficiency of p35 (or IL-12Rb2) and p40
/
mice are more immunocompromised than p35
/
mice.64–67 Patients with atypical mycobacterial and salmonella infections have also been found to have mutations in the genes encoding IL-12p40 and IL-12Rb1.68 A similar phenotype is shown also by STAT4 knockout mice with defective IL-12 responses, production of IFN-g, and Th1 differentiation. These mice also have impaired expression of IL-12R, IL-18R, CCR5, E-selectin, and P-selectin ligand.69,70 Considering the clear role of IL-12 in the pathogenesis of autoimmune diseases, targeting this cytokine has been considered important. In fact, anti-IL-12 therapy is being developed and tested, especially for the treatment of inflammatory bowel disease. 1.3.2.2

Interleukin-23

The identification of a novel protein, p19, which is homologous to IL-12p35, has added new complexity to the biological role of IL-12. Identified by computational search, p19 heterodimerizes with p40 to form a new cytokine designated IL-23.71 p19 is produced by macrophages, DCs, T cells, and endothelial cells. Like IL-12, IL-23 also induces the production of IFN-g in human T cells. However, in contrast to IL-12 which is important for differentiation of naı¨ ve T cells, IL-23 acts primarily on memory T cells to induce their proliferation.72 Additionally it has been reported that in murine CD4þ T cells, IL-23 is a potent inducer of the proinflammatory cytokine IL-17.73 Interestingly, IL-23 also induces IL-12 and IFN-g production by DCs, but only IL-23 acts on CD8þ splenic DCs to promote

The Biology of Cytokines

15

antigen presentation.72 Moreover, IL-12 can increase the transcriptional expression of murine p19 in DCs, suggesting a mutual regulation between IL-12 and IL-23.72 IL-23 binds a receptor composed of IL-12Rb1 and a second subunit designated IL-23R normally expressed at low levels on T cells, NK cells, monocytes, and DCs. The IL-23R contains seven intracellular tyrosine residues potentially involved in signalling. Similar to IL-12, the major signalling pathway activated by IL-23 involves the activation of the Janus kinases Tyk2 and Jak2, as well as STATs, especially STAT4. Whether IL-23 is able to activate other pathways as shown for IL-12 is still unknown.74 The exact role of IL-23 in vivo has been elucidated by comparing the phenotypes of IL-23p19, IL-12/IL-23p40, and IL-12p35-deficient mice. Since p40
/
mice lack both IL-12 and IL-23, deficiency of p40 results in a more severe phenotype than IL-12p35 deficiency, as indicated by experiments with experimental autoimmune encephalomyelitis (EAE). In fact before the discovery of IL-23, it was hypothesized that IL-12 was essential for EAE induction, as p40
/
mice are protected from disease.75 However further studies using IL-12p35
/
mice and IL-12Rb2
/
mice have excluded a major role for IL-12 in EAE.76,77 IL-23 instead seems to be critical for the development of this autoimmune disease, since p19
/
mice are resistant to EAE induction and EAE symptoms are restored upon IL-23 administration.78 IL-23 deficiency also prevents collagen-induced arthritis (CIA) and disease resistance correlates with the absence of IL-17-producing CD4þ T cells. The involvement of IL-23 in the inflammatory processes is further emphasized in mice with ubiquitous overexpression of IL-23 which develop a systemic inflammatory response with increased circulating levels of TNF and IL-1.79 1.3.2.3

Interleukin-27

IL-27 is the newest member of this family of cytokines and is also a heterodimeric cytokine.80 It comprises subunits encoded by two genes, designated Epstein–Barr induced gene 3 (EBI3) (and a novel protein p28. EBI3 is homologous to IL-12p40.81,82 p28 instead is related to IL-12p35. Like IL-12, EBI3 co-expression is required for secretion of p28. IL-27 is produced by APCs with the highest levels of p28 and EBI3 occurring in LPS-activated monocytes and monocyte-derived DCs. IL-27 expression is also induced by several inflammatory stimuli. Interestingly, IL-27 can be classified as both a pro- and an anti-inflammatory cytokine and T cell functions can be augmented or inhibited by IL-27. Similar to IL-12, IL-27 induces the proliferation of naı¨ ve T cells and, in combination with IL-12, it promotes IFN-g production and therefore induces Th1 polarization. Interestingly though, IL-27 is not essential for IFN-g production in vivo and its effects on the prevention of experimental leishmaniasis are transient as shown in IL-27R
/
mice.83 IL-27 binds the previously orphan receptor WSX-1/TCCR, another receptor with homology to the gp130 family mainly expressed in T cells. The second chain of the IL-27 receptor is gp130, making IL-27 a member of two families of cytokines.84 The signalling pathways activated by IL-12 and IL-27 largely overlap. Activation of STAT1, STAT3, and STAT5 has been reported. Whereas gp130 is expressed on several tissue types, WSX-1 is preferentially expressed in lymphoid tissues with the highest levels on naı¨ ve T cells and NK cells. Interestingly, mice nullizygous for this receptor had been generated prior to the discovery of the ligand and showed impaired Th1 development and IFN-g production in response to antigen stimulation.85 The biology of IL-27 in fact has been uncovered through the study of both WSX-1 and EBI3-deficient mice. WSX-1
/
mice have increased susceptibility to intracellular pathogens like L. monocytogenes with increased Th2 response. A similar situation has been observed during Leishmania infections although after some time mice started developing a Th1 response and were able to control the infection. WSX-1
/
mice

16

Cytokine Gene Polymorphisms in Multifactorial Conditions

infected with Toxoplasma gondii instead showed a normal Th1 response and surprisingly the mice succumbed because of T cell-dependent inflammatory disease. Similar results were obtained after infection with Trypanosoma cruzii which leads to the development of liver necrosis due to excessive IFN-g and TNF production. Thus, the pathogenic activation of the Th1-mediated response observed in these models suggests that IL-27 may have an inhibitory effect on this arm of the adaptive immune response.83 IL-27 induces IFN-g production in NK cells but the opposite effect is exerted on NK-T cells, thus supporting the dual role of pro- and anti-inflammatory cytokines. Because of this peculiarity, it is difficult to envisage a strategy involving IL-27 manipulation in vivo. 1.3.2.4

Interleukin-18

IL-18 was initially discovered as an IFN-g-inducing factor (IGIF) produced by macrophages stimulated with microbes or microbial products.86 It belongs to the IL-1 superfamily of cytokines and like IL-1 is produced as an inactive precursor that is cleaved by the IL-1 converting enzyme (ICE) to generate an 18 kDa biologically active peptide.87 Proteinase-3, caspase-3, and cathepsin proteases can also cleave the precursor polypeptide but this sometimes results in inactive forms of IL-18.88 Along with macrophages, IL-18 is also secreted by DCs and by epithelial cells. Mature IL-18 binds a heterodimeric surface receptor (IL-18R) which is comprised of an a chain responsible for extracellular binding and a b chain which is a nonbinding but signal transducing chain. This receptor complex utilizes signalling cascades which are typical of the IL-1 superfamily and involve recruitment of the adaptor MyD88 and eventually the activation of the transcription factor NF-B, although this cascade does not appear to happen in all the cells for which IL-18 has a biological activity. Similar to IL-1, a soluble IL-18 binding protein exists. This protein which is constitutively secreted has high affinity for IL-18 and blocks its biological activity.86 IL-18 acts synergistically with IL-12 to induce IFN-g production by several types of cells. The two cytokines also cooperate in inducing their respective receptors, therefore augmenting their biological effects. IL-18 can induce IFN-g production from T cells independently of TCR activation, a property unique to IL-18. Considering the importance of IFN-g for pathogen clearance, IL-18 has been shown using several animal models to be required for the eradication of several microbial infections. Its biological role though goes beyond IFN-g production and Th1 polarization. IL-18 induces both T and NK cell maturation and potentiates cytotoxicity. In fact, IL-18-deficient mice show reduced NK cytolitic activity.89 IL-18 can also induce TNF production, an effect which links this cytokine to the development of the inflammatory response and the pathogenesis of several autoimmune diseases. Chemokine (CXCL8, CCL2, and CCL3) as well as adhesion molecule (ICAM-1, VCAM-1) expression is also induced by IL-18. Patients with Crohn’s disease have high serum levels of IL-18.90 Accordingly, a correlation between the levels of IL-18 and severity of the disease has been shown in animal models, whereas mice treated with IL-18 binding protein instead are protected from disease. IL-18 also promotes the onset of insulin-dependent diabetes mellitus, where the Th1-mediated destruction of pancreatic b cells has been well characterized.91 Rheumatoid arthritis and osteoarthritis are two other autoimmune diseases in which IL-18 has been implicated. The cytokine can be released by synovial cells obtained from arthritis patients without exogenous stimulation. IL-18 in turn, can activate the synoviocytes to produce TNF, IL-1 and chemokines, therefore amplifying the inflammatory response.92 On the other hand IL-18 has been shown to have a role in inducing a proper Th2 response. IL-18 directly induces IL-4 and IL-13 secretion, as well as high IgE expression by B cells. The capacity of IL-18 to induce a Th2 response depends on CD4þ T cells, NK-T cells, and IL-4. In fact IL-18-induced IgE production is abrogated in CD4þ T cell-depleted and in

The Biology of Cytokines

17

IL-4
/
mice.93 Basophils and mast cells, which release a large amount of IL-4 and IL-13 after FceR cross-linking, are key cells for the Th2-driven response and IgE production. IL-18 can induce the production of IL-4 and IL-13 even in the absence of FCeR engagement if IL-3 is present in the milieu. Interestingly, IL-12 and IFN-g are incapable of blocking this IL-18-driven activation suggesting that IL-18 involvement in the Th2 response occurs in parallel with a Th1 response.94 Transgenic mice which over-secrete IL-18 in keratinocytes develop a spontaneous atopic dermatitis. Moreover, several studies conducted in atopic dermatitis patients have shown a correlation among serum IL-18 levels, IgE levels, and severity of the disease. A role for IL-18 has also been postulated in bronchial asthma with elevated serum IL-18 levels that correlate with the severity of the disease.95 In mice, IL-18 exacerbates airway inflammation and infiltration, possibly through the induction of chemokine release.95 1.3.2.5

Interferon-c

IFN-g, the type II interferon, was one of the first cytokines to be recognized and characterized. At the protein level it bears no resemblance to type I interferons and its gene is also located on a different chromosome. The molecule is a non-covalent homodimer consisting of two polypeptide chains which are normally glycosylated.96 Contrary to type I IFNs that are produced by most cells, IFN-g is secreted by cells of the immune system, mainly Th1 cells, CD8þ T cells, and NK cells. Cytokines such as IL-12 and IL-18 can induce IFN-g production in other cell types such as macrophages and DCs.97,98 In T cells the main stimulus for the production and secretion of IFN-g is the cross-linking and activation of the TCR. NK cells instead produce IFN-g if stimulated with cytokines such as TNF, IL-12, IL-27, and IFN-g itself.99 This cytokine plays an important role in antigen recognition as it can induce the expression of both classes of MHC.97,100 It is also a potent activator of macrophages which respond by secreting cytokines involved in antimicrobial immunity such as TNF, IL-1, IL-12, and IL-27 which further induce IFN-g. Besides inducing cytokines and chemokines, IFN-g also mediates the induction of other molecules involved in bacterial killing such as iNOS. Along with IL-12 and IL-27 it promotes and sustains the differentiation of naı¨ ve T cells into Th1 cells. It can also act on B cells, inducing isotype switching and the production of the complement-fixing IgG subclasses, such as IgG1 in humans and IgG2a in mice.101 The IFN-g receptor (IFN-gR) belongs to the class II family of cytokine receptors and it consists of two chains, IFNGR1 (or IFN-gRI) and IFNGR2 (or IFN-gRII). IFN-g binds to two chains of IFNGR1, which are the main signal transducing components of the receptor. In addition IFNGR2 chains are also needed for the formation of a high affinity functional receptor complex. Ligand binding induces the complex oligomerization and the activation of JAK1 (constitutively associated with IFNGR1) and JAK2 (associated with IFNGR2) which results in activation of STAT1 and, in turn, induction of genes containing the g-activation sequence in their promoter. The IFN-gR is expressed on a wide variety of hematopoietic cells ranging from T cells, B cells, macrophages, and platelets. Epithelial and endothelial cells as well as many tumor cells also express it.96 IFN-g has a mild antiviral and antiproliferative activity but it potentiates the antiviral and antitumor action of type I IFNs. In vitro, IFN-g can stimulate macrophages to kill a wide array of bacteria, fungi, and protozoa. IFN-g plays a critical role in macrophage-mediated killing of intracellular pathogens, such as Mycobacterium, Leishmania, Legionella, and Chlamydia species. The fundamental role played by IFN-g in the host immune response has been demonstrated in mice with targeted deletions of either IFN-g or IFN-gR. These knockout mice have impaired ability to control infections by intracellular pathogens, such as viruses, mycobacteria, and L. monocytogenes. Experimental infections in animal

18

Cytokine Gene Polymorphisms in Multifactorial Conditions

models have also been used to study the effects of IFN-g administration. Mice infected with Cryptococcus neoformans and treated with IFN-g had significantly increased survival and decreased lung colony-forming unit counts compared with untreated mice. Furthermore, systemic administration of IFN-g enhanced resistance against acute disseminated Candida albicans infection and invasive aspergillosis in mice. Several other models have been used to prove IFN-g efficacy in the therapy of bacterial, protozoan, fungal, and helminth infections.102–106 Gene targeting models have also been fundamental in defining the complex immunomodulatory role of IFN-g in many autoimmune diseases. Disease-promoting effects of IFN-g have been shown in several models. For instance, in diabetes-prone NOD mice, treatment with anti-IFN-g antibody reduced the incidence and severity of the disease while IFN-g and IFN-gR nullizygous mice showed delayed disease onset. However the incidence and severity of other experimental autoimmune diseases, such as EAE and CIA, are frequently increased in animals that have deficient IFN-g response. This disease-limiting effect of IFN-g came initially as a surprise and the validity of these models was questioned. However this paradoxical phenomenon is now explained with the inhibitory effect of IFN-g on the myelopoiesis elicited by the mycobacterial adjuvant used for inducing these autoimmune diseases in laboratory animals.107,108 Besides its involvement in arthritis, lupus, and inflammatory bowel disease, the presence of IFN-g has been documented within the central nervous system (CNS) in several diseases, including multiple sclerosis. IFN-g-positive cells have been detected in the CNSs of multiple sclerosis patients by immunohistochemistry. The abnormal expression of IFN-g in the CNS contributes to inflammatory events by upregulating MHC, CD40, and ICAM-1 expression.109 In humans IFN-g has been approved for the treatment of chronic granulomatous disease (CGD). Using CGD cells, it was observed that IFN-g can stimulate the antimicrobial mechanisms of human monocytes. Patients with antimicrobial-refractory respiratory tract infections caused by atypical (nontuberculous) mycobacteria have also been reportedly treated successfully with both systemic and aerosolized IFN-g. Systemic therapy with recombinant human IFN-g has also been postulated to improve the clinical course in patients with atopic dermatitis and hyper-IgE syndrome by decreasing IgE and IL-4 levels, restoring immune balance, and thereby leading to clinical improvement.110 1.3.2.6

Lymphotoxins

Lymphotoxins (LTa, LTb, and LIGHT) are a family of molecules closely related to TNF: in fact LTa was described and characterized along with TNF and was originally named TNFb. The initial observation that LTa binds the same receptors as TNF supported the choice of nomenclature and only after the discovery of LTb was the initial name dropped.111 LTa and LTb bind together to form three different biologically active ligands: LTa3 (from now on simply defined as LTa), LTa1b2, and LTa2b1 where the b subunit is membrane-anchored. The trimers (homo or hetero) bind different receptors: TNFRI and TNFRII are utilized by LTa and LTa2b1, whereas LTa1b2 (the most important biological form of LTb) binds to LTbR. This receptor is also utilized by another ligand, LIGHT, which is also tethered to the cell membrane like the LTabs. Notably, LIGHT can also bind an additional receptor, the herpes virus entry mediator (HVEM). LTab is expressed selectively on cells of the lymphoid lineage (including NK) and on lymphoid progenitors. In contrast, LIGHT is expressed on T cells, on immature DCs as well as on monocytes and granulocytes. LTbR instead is expressed in myeloid cells and non-hematopoietic cells.112 Despite their usage of TNF receptors, which would suggest an involvement in the inflammatory response, LT cytokines are crucial for the development and organization of secondary lymphoid organs such as lymph nodes and Peyer’s patches. The biological

The Biology of Cytokines

19

function of LT cytokines has been elucidated by using two different approaches, gene targeting/manipulation and inhibitors of the LT system. The latter approach proved to be essential in precisely defining their functions since mice lacking LTab or LTbR have profound defects in the development and architecture of the spleen and peripheral lymphoid tissues as a result of failed signalling during embryogenesis.113 The lack of lymph nodes and Peyer’s patches was the first phenotype recognized in LTa
/
mice that completely lack the anlagen required for the accumulation of lymphocytes.114 These mice also have a dramatic decrease in expression of chemokines such as CXCL13, CCL19, and CCL21 and in fact deficiency in the receptor for these ligands also results in defective lymph node formation and altered splenic architecture, clearly placing the regulation of these chemokines as an LTregulated event. Expression of MAdCAM-1, VCAM-1, and ICAM-1 has also been found to be regulated by the LT system.115 LIGHT is an important mediator of T cell activation in the periphery, and also induces ectopic lymphoid structure in the intestine.116,117 Experiments from gene-targeted animals demonstrate that LIGHT is not required for lymph node or splenic development/organization. This protein, however, is able to replace LTb signalling in order to drive organogenesis of mesenteric lymph nodes. As suggested before, the use of a decoy receptor such as the LTbR-Ig fusion protein helped to define better the role of the LT pathway in the adult mouse. Administration of the decoy receptor dissolved B-cell follicles, altered the spleen architecture and impaired immunoglobulin production in response to immunization. However, the treatment only partially reduced chemokine levels, suggesting that these molecules are critical for the full development and differentiation of chemokineproducing stromal cells. Besides its role in induction of chemokines and adhesion molecules, which account for LT’s importance to adaptive immune response, the LT/LIGHT family is also involved in the innate immune response. Induction of IFN-b downstream of LTbR has been shown using the human cytomegalovirus (CMV) system. CMV infection blocks the induction of IFN-b, but signalling through LTbR can bypass the viral effects.118 Moreover, LTa
/
mice are highly susceptible to murine CMV. LT signalling is also important for DC migration to the secondary lymphoid organs and to the site of infection. LTs also play an important role in NK development as LTa and LTbR
/
mice show a dramatic reduction in NK cell numbers in the spleen and bone marrow and the existing cells have impaired antitumor activities.119,120 Considering the importance that this family of cytokines has in the development of a functional immune system, it is not surprising that they have been reported to be important in several autoimmune and infectious diseases. Mice treated with the LTbR-Ig fusion protein have been shown to be less susceptible to CIA, EAE, and insulin-dependent diabetes mellitus.112 As the decoy receptor can block signalling for both LTab and LIGHT, the mechanisms underlying these effects are multiple but effects on the microenvironment of the lymph nodes and spleen as well as effects on the capacity of autoreactive T cells to migrate to the inflammatory sites have been observed. The susceptibility of LT-deficient mice to infectious agents is probably due to the structural defects of the lymphoid organs as well as lack of signalling during the infection. Nonetheless, only certain pathogens such as lymphocytic choriomeningitis virus (LCMV), Theiler’s virus, Leishmania major, and Mycobacterium tuberculosis appear to have enhanced pathogenicity when the LT pathway is shut down. On the other hand, B and T cell responses to influenza virus were not impaired in LTa
/
mice.121–125

1.3.3 CYTOKINES INVOLVED IN Th2 IMMUNE RESPONSES Th2 effector cells secrete IL-4, IL-5, and IL-13 (type 2 cytokines), and promote humoral immunity and resistance to extracellular pathogens, such as helminths. Similar to Th1

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Cytokine Gene Polymorphisms in Multifactorial Conditions

response, deregulated production of these cytokines may result in severe morbidity, especially if the inflammatory response persists for a period of time or becomes chronic. Type 2 cytokine patterns are clearly associated with allergic reactions to environmental antigens, such as atopic dermatitis or asthma, but also to idiopathic pulmonary fibrosis, ulcerative colitis, and granulomatous inflammation.

1.3.3.1

Interleukin-4

IL-4 was discovered as a cofactor in the proliferation of resting B cells stimulated with anti-IgM antibodies. It was also shown to be a T cell-secreted molecule that induced differentiation of B cells into plasma cells. This accounts for the initial use of the terms B-cell stimulation factor-I (BSF-I), B-cell differentiation factor-I (BCDF-I), and B-cell growth factor-I (BCGF-I). IL-4 is produced by Th2 cells and is an autocrine cytokine for Th2 cells. Other cells, like mast cells, are also an important source of IL-4 especially in the inflammatory process.126,127 Besides its activity on Th2 cells, IL-4 can act on B cells at several stages of their cell cycle. It activates resting B cells, inducing expression of MHC II. After activation, in the presence of antigen, it functions as a growth factor. Finally it acts as a differentiation factor by regulating class switching to IgE and non-complement-fixing IgG subclasses. Interestingly, it is apparently not essential for B cell development and function since IL-4
/
and IL-4Ra
/
mice develop B cells and are capable of mounting primary and secondary antibody responses. IL-4 has also been shown to act in an autocrine fashion on mast cells as well in tissues such as gut or lung where it can act as a growth factor.128 IL-4 exerts its effect via the IL-4R, which is expressed mostly on hematopoietic cells and is a heterodimeric complex consisting of an alpha chain (IL-4Ra) and the common gc (see above). IL-4 can also exert its activity on other cell types such as the airway epithelium in the absence of the gc. In this instance IL-4 utilizes the IL-13Ra1 chain to form a high affinity receptor (see below). Several studies support the role of IL-4 in allergic diseases and asthma development. For instance, neutralizing antibodies to IL-4 or a soluble IL-4R acting as a decoy can inhibit the development of antigen-specific IgE production, and reduce lung eosinophil infiltration and IL-5 production in murine asthma models. Similar results have been obtained by using mice deficient in IL-4, IL-4Ra or the IL-4-activated transcription factor STAT6.129–131 Although IL-4 is essential for the initial development of the Th2 response, it seems that the effector phase is instead mainly under the control of IL-13 (see below). The different role of these two cytokines was also confirmed in other models. Transgenic mice overexpressing IL-4 in the lungs did not show subepithelial fibrosis which instead was marked in IL-13 transgenic mice.132,133 Instead, IL-4 increases the release of chemokines such as CCL11 and VCAM-1 expression in lung fibroblasts, thus promoting airway inflammation. IL-4 also inhibits apoptosis in eosinophils and Th2 lymphocytes by promoting the expression of the Bcl-2 protein. Several clinical observations have demonstrated the fundamental role of IL-4 in human allergic disease. IL-4 is increased in the serum and bronchoalveolar lavage of allergic patients. Atopic individuals have altered regulation of IL-4 production in response to bacterial or dust mite antigens. Furthermore, atopic patients have higher numbers of IL4-secreting T cells than normal subjects. Polymorphisms in the genes for IL-4 and IL-4Ra (as well as IL-13 and IL-13Ra) have been genetically associated with atopy and asthma.134 IL-4 has been suggested to play a role in the development of autoimmune diseases like lupus, promoting the secretion and deposition of autoantibodies although the real involvement of this cytokine in the pathogenesis of this disease is still debated.135

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Since IL-4 appears to be critical only in the early stages of allergen-driven allergic disease it is difficult to envisage an effective therapy based on blocking IL-4 activities. Nonetheless, a soluble form of the IL-4 receptor with decoy activities has been tested in asthmatic patients where it appears to stabilize airway functions following corticosteroid withdrawal.136 1.3.3.2

Interleukin-5

IL-5 was initially discovered as an eosinophil differentiation factor (EDF). It was also shown to act as a growth factor for B cells. However, these activities have only been demonstrated in mice, not in humans.137 Like many other cytokines, IL-5 belongs to the family of short chain 4-a-helix bundle hematopoietic cytokines and along with IL-3 and GM-CSF, it uses the common b chain for receptor signalling. As for many cytokines, receptor specificity is achieved by the formation of a heterodimeric complex with the IL-5Ra chain.138 IL-5 is produced by Th2 cells, mast cells, and eosinophils.139 Interestingly, these cells are also among the targets of IL-5 biological actions. For example, IL-5 activates eosinophils upregulating their CD11b expression and resulting in proliferation and prolongation of their life span.140 Consistently IL-5 and IL-5Ra deficiency abolishes eosinophilia in a murine model of asthma. Besides its expression on eosinophils, IL-5Ra is also expressed by basophils and by CD34þ progenitor cells in the bone marrow.141,142 Together with the other b chain-using cytokines, IL-5 regulates differentiation and function of myeloid cells. Much evidence supports a key role for IL-5 in the pathophysiology of allergic inflammation and asthma. A marked eosinophilic infiltration in lung tissue is a typical feature of asthma. In keeping with this observation, both IL-5 and IL-5-producing cells are increased in the bronchoalveolar lavage of asthmatic patients and in their bronchial mucosa. Moreover, higher IL-5 levels in the lungs correlate with the severity of the disease.143 As mentioned before, murine models also support the role of IL-5 in allergic inflammation and asthma. In addition to the observations in IL-5
/
mice, IL-5 transgenic animals that overexpress the cytokine in their airways develop substantial bronchial hyperreactivity and eosinophilia, even in the absence of an allergen challenge.144,145 However, administration of anti-IL-5 antibodies to asthmatic patients did not show any therapeutic efficacy. While the treatment reduced circulating eosinophil numbers, eosinophilia in the lung tissue was unaffected, thus explaining the lack of efficacy.146 1.3.3.3

Interleukin-13

IL-13 was originally discovered during a screening of a library derived from peripheral blood mononuclear cells stimulated with CD28. IL-13 (also known as P600 and NC30), is produced mainly, but not exclusively, by Th2 cells.147 Recently, it has been shown that other cells involved in the allergic response such as mast cells, basophils, and eosinophils can secrete IL-13 in response to GM-CSF or IL-5. Moreover, NK cells and CD8þ T cells have also been shown to secrete IL-13.148 Other cytokines such as IL-9 and mediators like histamine and adenosine can regulate IL-13 production, possibly leading to a feedback loop that maintains and amplifies the Th2-mediated immune response.149 The il13 gene is located just 25 kb upstream of the il4 gene and this is also reflected by the fact that IL-13 presents many structural and functional properties of IL-4. IL-13 effects are mediated by a relatively complex receptor system which includes the IL-4Ra chain. Additionally, two other IL-13-specific receptor chains have been described: IL-13Ra1 and IL-13Ra2. IL-13Ra1 forms a high affinity receptor heterodimer with IL-4Ra. In contrast IL-13Ra2 binds solely with high affinity IL-13, and is thought to act as an inhibitory receptor. As previously mentioned, the IL-4Ra/IL-13Ra complex can serve as a receptor for IL-4 in cells that lack the common gc. The IL-13R/IL-4R dimer is expressed on

22

Cytokine Gene Polymorphisms in Multifactorial Conditions

hematopoietic and non-hematopoietic cells. The former includes B cells (human but not murine), monocytes, DCs, and basophils. Non-hematopoietic cell types include fibroblasts, endothelial cells, and airway epithelial cells. This distribution of IL-13 receptor expression is consistent with its purported role in the pathogenesis of allergic diseases.150 IL-13 is found at higher levels in the lungs of asthmatic patients.151 Administration of IL-13 can cause airway inflammation, eosinophilic recruitment and mucus cell hyperplasia even in non-antigen-challenged mice. Furthermore, blocking of IL-13 activity using soluble IL-13Ra2 can reduce airway hypersensitivity in allergen-challenged mice.152 Transgenic mice with pulmonary over-expression of IL-13 develop an asthma-like syndrome,133 while allergen-challenged IL-13
/
mice fail to develop airway hyper-reactivity even if IL-4 and IL-5 levels are significantly increased.153,154 Other studies have shown that in contrast to IL-4, which is essential for the Th2 initial response, IL-13 is more important in the development of other allergic disease factors such as mucus secretion, airway inflammation, and subepithelial fibrosis. Nonetheless, for a full inflammatory response, the synergism between IL-4 and IL-13 is clearly required. The mechanisms by which IL-13 exerts its biological actions are multiple. IL-13 can induce a wide array of chemokines: CCL2, CCL3, CCL8, CCL11, and CCL24, which coordinate the recruitment of inflammatory cells from the bloodstream into the airways.155 Metalloproteases, which have been reported to be involved in extracellular matrix degradation and in modulation of inflammation, are also induced by IL-13. Along with the induction of arginase 1 these may participate in the IL-13-driven development of subepithelial fibrosis.156 Fibrosis may also be mediated via the induction of another cytokine induced by IL-13, namely TGF-b which is produced directly by epithelial cells as well as by monocytes and macrophages.157 Mucus production is also controlled by IL-13. This feature of airway hyper-responsiveness can be blocked by administration of soluble IL-13Ra2. Additionally, mucus secretion can still be observed in adoptive transfer mouse models where IL-4 and IL-5
/
cells were used.158 Polymorphisms in the IL13 gene in asthmatic patients have also been reported, suggesting that deregulation of the IL-13 production in human asthma may in fact occur through a variety of mechanisms.159

1.3.4

CYTOKINES INVOLVED IN REGULATION RESPONSE

OF IMMUNE

The immune system has evolved several complex mechanisms for mounting robust responses against a virtually infinite variety of invading pathogens while avoiding harmful responses to the body’s own tissues. Although a major mechanism for maintaining self-tolerance is thymic deletion of T cells bearing a TCR specific for self-antigens, there is now substantial evidence that autoreactive lymphocytes can also be actively suppressed in the periphery by a subset of T cells known as regulatory T (Treg) cells, that are specialized in inhibiting both proliferation and effector functions of lymphocytes. Beside preventing autoimmunity, Treg cells are also important in controlling the magnitude of immune response against foreign micro-organisms and in limiting the inflammatory reaction that may damage normal uninfected cells in the proximity of the immune attack. However the suppression exerted by Treg cells may sometimes hamper the effective control of viruses and bacteria and may also impede the immunosurveillance of tumors. Several populations of Treg lymphocytes have now been described such as the naturally occurring Treg cells that originate in the thymus and constitutively express high levels of CD25 (hence they are usually termed CD4þCD25þ Treg) and the IL-10-producing Treg that can be induced in vitro and in vivo under particular conditions of antigenic stimulation. Even though Treg cells inhibit the proliferation of naı¨ ve T cells in vitro mainly by direct cell–cell contact, it has been shown that

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23

their suppressor function in vivo may also be mediated by the immunoregulatory cytokines IL-10 and TGF-b.160–163 1.3.4.1

Interleukin-10 and IL-10-Related Cytokines

IL-10 was initially characterized as ‘‘cytokine synthesis inhibitory factor’’ produced by Th2 cell clones that inhibited the production of IFN-g by Th1 cells.164 IL-10 is produced by monocytes and macrophages after stimulation with LPS and other microbial products, by several T cell subsets (Th2, Treg, but also Th1) after antigen stimulation and also by B cells. Keratinocytes are also a source of IL-10. The IL-10 receptor is composed of two subunits (IL-10R1 and IL-10R2) that are member of the type II cytokine receptor family. The major function of IL-10 is to serve as an anti-inflammatory and immunosuppressive cytokine. IL-10 inhibits the production of pro-inflammatory cytokines like TNF and IL-1. It decreases the generation of nitric oxide and reactive oxygen species in monocytes and macrophages while increasing the production of IL-1ra and sTNFRs. LPS administration induces IL-10 production that protects it from the harmful effects of endotoxin. In fact, IL-10
/
mice are highly susceptible to endotoxin lethality and display high levels of LPS-induced TNF.165 IL-10 strongly inhibits cytokine production and proliferation of CD4þ T cells but this effect is mainly indirect through the inhibition of antigen presentation by DCs and macrophages. IL-10 down-regulates the expression of MHC class II molecules and of co-stimulatory molecules such as CD80 and CD86 and inhibits the production of IL-12 by monocytes and DCs, thus limiting the development of Th1-mediated immune responses.165,166 IL-10-deficient mice have also been shown to have a prolonged delayed-type hypersensitivity (DTH) response and this enhanced Th1 response leads to increased resistance to a variety of pathogens such as L. monocytogenes, T. gondii, or C. albicans. However, in some cases this improved clearance of infectious agents also results in increased immunopathology likely due to a higher production of pro-inflammatory mediators. IL-10 seems to play a very important role in limiting the immune responses to pathogens in order to eradicate the invading micro-organisms with minimum immunopathology for the host. Likewise, IL-10 also plays an important role in tolerance to self-antigens and in protection against autoimmunity. Indeed IL-10
/
mice spontaneously develop inflammatory bowel disease that appears due to a defect in IL-10-producing Treg cells that moderate responsiveness to normal enteric antigens. IL-10-deficient mice are also more susceptible than wild-type mice to induction of organ-specific autoimmune diseases such as EAE.161,165 IL-10 also enhances proliferation and antibody production in B cells and might play a critical role in the pathogenesis of systemic lupus erythematosus (SLE), an autoimmune disease characterized by high autoantibody production. IL-10 hyperproduction has been described in SLE patients and serum IL-10 levels correlate with disease severity.165,166 Five novel cytokines with limited primary and likely structural homology with IL-10 have been identified: IL-19, IL-20, IL-22, IL-24, and IL-26. Whereas the biological functions of IL-10 have been extensively studied, the role of the IL-10-related cytokines in inflammation and immunity is much more elusive. Most of these factors are inducible by LPS but, unlike IL-10, they seem to exert pro-inflammatory rather than anti-inflammatory activities. IL-19 for instance induces TNF, IL-6, and reactive oxygen species in monocytes whereas injection of IL-22 in mice leads to APP synthesis. Transgenic mice overexpressing IL-20 show skin abnormalities with abnormal differentiation and proliferation of keratinocytes reminiscent of psoriasis in humans. IL-24 is expressed by normal melanocytes and its expression decreases during the process of melanoma transformation. Interestingly, ectopic expression of IL-24 has been shown to induce growth suppression in melanoma and other cancer cells but not in normal cells.21,167

24

1.3.4.2

Cytokine Gene Polymorphisms in Multifactorial Conditions

Transforming Growth Factor-b

TGF-b was first characterized because of its ability to stimulate the anchorage-independent growth of fibroblasts. Platelets were initially shown to contain large amounts of this cytokine.168,169 TGF-b belongs to a family of more than 40 growth factors which also includes activins, inhibins, and bone morphogenetic proteins. TGF-b is produced by many cells and tissues and is involved in a wide range of physiological and pathological processes, including development, oncogenesis, immunomodulation, and wound healing.170 There are three highly homologous isoforms of TGF-b (TGF-b1, TGF-b2, and TGF-b3), each one encoded by a distinct gene. Each isoform is synthesized as part of a large precursor molecule containing a propeptide region. Before secretion the TGF-b is cleaved from the propeptide that however remains attached to the mature TGF-b by non-covalent bonds and inhibits its activity. After secretion most of the TGF-b is stored in the extracellular matrix as a complex of TGF-b, propeptide and a protein called latent TGF-b binding protein (LTBP). The activation of these latent forms of TGF-b in vivo is mediated by multiple pathways involving proteolytic mechanisms and binding to molecules such as thrombospondin-1.170,171 TGF-b elicits its biological effects by binding to three types of receptors that are termed type I, type II, and type III and are expressed by many cell types. The type I and type II receptors have a cytoplasmic domain with a serine/threonine kinase activity that phosphorylates a group of proteins known as SMADs, whereas the type III receptor does not participate in signal transduction but functions by presenting TGF-b to the signalling receptors.170,171 TGF-b regulates several aspects of lymphocyte function. It was discovered that TGF-b exerts an anti-proliferative effect on primary T cells and this was largely attributed to inhibition of IL-2 production. Later it was shown that TGF-b also inhibits the acquisition of most of the effector functions of T cells. In fact, CD8þ T cells activated in the presence of TGF-b do not acquire cytotoxic activity and CD4þ T cells fail to become Th1 or Th2 lymphocytes. In B cells, TGF-b inhibits proliferation and immunoglobulin secretion; however, in intestinal mucosa TGF-b produced by stromal cells seems to induce class switch recombination to IgA. In addition to its immunosuppressive effects on lymphocytes, TGF-b also prevents the maturation of DCs with down-regulation of MHC class II molecule expression, and blocks macrophage activation by inhibiting the production of TNF, IL-1, and reactive oxygen species. TGF-b1-deficient mice display severe multi-organ inflammation characterized by auto-antibody and pro-inflammatory cytokine production, lymphoid and mononuclear cell infiltration in heart and lung, and expression of MHC class II molecules on multiple tissues where they are normally not expressed.172 Furthermore, TGF-b1
/
mice have an embryonic lethality rate higher than 50%, indicating that TGF-b1 is also crucial for embryonic development. TGF-b2-deficient mice exhibit cardiac, lung, craniofacial, and urogenital defects whereas TGF-b3-deficient mice show abnormal lung development and cleft palate. Their deficiency results in 100% embryonic or perinatal mortality, suggesting that although the three isoforms of TGF-b display similar activities in vitro, they have distinct roles in vivo. Interestingly, in humans polymorphisms in the gene for TGF-b3 have been linked to the development of cleft palate.170 TGF-b also enhances wound healing and tissue repair. When released at the wound site from macrophages or degranulating platelets it promotes the deposition of extracellular matrix by stimulating the production of fibronectin and collagen from fibroblasts and inhibiting their degradation by decreasing collagenase or heparinase synthesis. However, when the deposition of extracellular matrix becomes excessive, fibrosis occurs and increased TGF-b production has been found in patients with fibrotic kidney disease,

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25

hepatic and pulmonary fibrosis. Transgenic mice overexpressing TGF-b1 develop fibrosis in liver, kidney, and heart whereas SMAD3-deficient mice are less susceptible to fibrosis development in several experimental models.170,173 Due to its potent growth-suppressing effects TGF-b may function as a tumor suppressor. However, in cancer cells several mutations in the molecules of TGF-b signalling pathways have been described conferring resistance to the growth inhibition by TGF-b and leading to uncontrolled proliferation. Moreover, after tumor cells become resistant to the inhibitory activity, they often increase TGF-b production which instead promotes tumor invasiveness and metastasis formation, as a result of the immunosuppression and of the effects on extracellular matrix.174

1.4 CHEMOKINES The immune system consists of diverse subpopulations of leukocytes which must migrate through all tissues of the body in order to exert their functions. Chemotactic migration of leukocytes largely depends on adhesive interaction with the substratum and recognition of a chemotactic gradient. Chemokines (or chemotactic cytokines) are a superfamily of small proteins whose main role consists in chemotaxis, that is migration of cells bearing specific receptors toward areas that exhibit higher concentration of these molecules. In addition, certain chemokines also trigger firm adhesion of leukocytes to endothelium by increasing integrin affinity for adhesion molecules such as ICAM-1 or VCAM-1 or induce release of oxygen radicals, histamine or cytotoxic protein from granulocytes. Chemokines are also involved in processes like organogenesis, hematopoiesis, and angiogenesis.175 Chemokines are subclassified into four families, CXC, CC, C, and CX3C, based on the organization of the N-terminal conserved cysteine residues. In the systematic nomenclature, chemokines are identified by using these cysteine motifs as roots followed by L for ligand and the number of the respective gene (e.g., CXCL1). The great majority of chemokines belong to the CXC and CC families. The CXC chemokine family can be further divided into two subfamilies, depending on whether the primary amino acid structure possesses an ELR motif prior to the CXC motif. The ELR chemokines, such as CXCL8, bind to the receptor CXCR2 and are chemotactic for neutrophils whereas the non-ELR CXC chemokines attract leukocytes. The CC chemokines are chemoattractant for monocytes, DCs, various populations of lymphocytes, eosinophils and basophils, but not for neutrophils.175 Although most chemokines are secreted molecules, they are also immobilized on the extracellular matrix by their interaction with glycosaminoglycan. This interaction may be important for preserving a gradient with higher concentrations of chemokines near the initiating inflammatory or trafficking stimulus. Unlike all other chemokines that are exclusively secreted, CXCL16 and CX3CL1 are expressed on the cell surface since they have a unique multimodular structure with an N-terminal chemokine domain, a mucin-like stalk, a transmembrane domain, and a C-terminal cytoplasmic tail. In the membrane-bound form, CX3CL1 acts as an adhesion molecule but when it is released from the cell surface following proteolytic cleavage it functions as a soluble chemotactic factor.175 Chemokines can also be classified as homeostatic or inflammatory according to their function. Homeostatic chemokines, such as CXCL12, CXCL13, CCL19, CCL21, CCL25, or CCL27 are constitutively expressed and regulate movement of leukocytes in the bone marrow and thymus during hematopoiesis or lymphocytes and DCs into secondary lymphoid organs. Inflammatory chemokines by contrast control the recruitment of effector leukocytes in infection, inflammation, or tissue injury and are up-regulated by stimuli like LPS, TNF, or IL-1b.175 Chemokines exert their biological activity upon binding to receptors that are

26

Cytokine Gene Polymorphisms in Multifactorial Conditions

members of the seven-transmembrane domains, G protein-coupled receptors. Chemokine receptors are designated according to the type of chemokine they bind (CXC, CC, C, or CX3C), followed by R for receptor and a number indicating the order of discovery (e.g., CXCR1). Several chemokine receptors are promiscuous as they bind more than one chemokine and also several chemokines bind more than one receptor. For instance, CCR3 has been shown to bind CCL5, CCL7, CCL8, CCL11, CCL13, CCL24, and CCL26, whereas CCL5 binds CCR1, CCR3, and CCR5. These redundant systems are most frequently associated with inflammatory chemokines, whereas those involved in homeostatic homing tend to be less promiscuous.175 LPS and other microbial products induce synthesis of pro-inflammatory chemokines such as CXCL8, CXCL10, CCL3, CCL4, or CCL5. This results in the amplification of the inflammatory response by inducing the recruitment of neutrophils, monocytes, NK cells, and activated T cells. Also immature DCs express inflammatory chemokine receptors such as CCR1, CCR2, and CCR5 and are attracted to inflammatory sites where they can pick up foreign antigens. Moreover, the local milieu in which these cells are attracted contains microbial products and pro-inflammatory cytokines which induce the maturation of DCs into potent APCs. Maturation of DCs is associated with the inhibition of chemotactic response to inflammatory chemokines and the up-regulation of CCR7 that, on the contrary, confers responsiveness to CCL19 and CCL21. These chemokines are present in lymphoid organs and in particular on afferent lymphatic endothelium, on the luminal sites of high endothelial venules (HEVs) and within the T zones of lymph nodes. This up-regulation of CCR7 in mature DCs enables them to leave the sites of infection and to migrate through afferent lymphatics into lymph nodes to prime naı¨ ve T cells.176,177 Naı¨ ve T cells also express CCR7 and are attracted from blood into the T zones of lymph nodes in response to CCL19 and CCL21. Thus both the CCR7-deficient mouse and the mutant plt/plt (paucity in lymph node T cells) mouse which lacks CCL19 and the HEV-expressed isoform of CCL21 show a defective migration of naı¨ ve T cells and mature DCs into lymph nodes. In contrast, trafficking of naı¨ ve B cells from blood into lymph nodes seems to depend mainly on the CXCR5 ligand CXCL13, that is expressed in B cell follicles.178–180 Once activated, some CD4þ T cells up-regulate their expression of CXCR5 and migrate to B cell follicles to provide help to B cells. Activated T cells expand clonally and differentiate into central memory and effector memory cells. Central memory T cells express CCR7 so they can traffic between the blood and secondary lymphoid organs. Effector memory T cells instead lack CCR7 but express inflammatory chemokine receptors that facilitate their exit from lymphoid tissues and their migration into sites of infection or inflammation where they might find again their cognate antigen. The two main helper T cell effector subsets, Th1 and Th2, also express different chemokine receptors: Th1 cells preferentially express CXCR3 and CCR5 whereas Th2 cells typically express CCR3, CCR4, and CCR8. Moreover the CXCR3 agonists CXCL9, CXCL10, and CXCL11 are strongly induced by IFN-g but not by IL-4 or IL-13. Hence IFN-g produced at sites of Th1-mediated inflammation can amplify the immune response by inducing chemokines that selectively attract other Th1 effector cells. Similarly, the Th2-associated cytokines IL-4 and IL-13 induce the expression of the CCR3 ligands CCL7, CCL11, CCL24, and CCL26, the CCR4 ligands CCL17 and CCL22, and the CCR8 ligand CCL1. Moreover, CCR3 ligands are also chemotactic for eosinophils and basophils, the major cell types associated with Th2 inflammation and allergic diseases.177,179,181 If lymphocytes have been activated by antigens in lymph nodes draining skin or intestinal mucosa, they become programmed to home preferentially to the original tissue and to recirculate between it and its draining lymph nodes. This specificity derives from the expression of specific adhesion molecules and chemokine receptors that recognize ligands selectively expressed in these tissues. In particular, homing of T cells and IgA-producing

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27

plasma cells to the small intestine depends on the expression of CCR9 and of the integrin a4b7. The integrin a4b7 interacts with the mucosal addressin cell-adhesion molecule (MAdCAM)-1, which is expressed on intestinal endothelium, whereas CCR9 interacts with CCL25 that is abundantly produced by epithelial and endothelial cells of the small intestine. Skin-homing T cells instead express CCR10 whose ligand, CCL27, is produced by keratinocytes.182

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2

Genetics of Multifactorial Disorders Jorge R. Oksenberg and John D. Rioux

CONTENTS 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 2.2 Disease-Gene Discovery in the HapMap Era . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.3 Extending the Definition of Phenotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.4 An Interplay of Genes and Environmental Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 2.5 Conclusions and Future Directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

2.1 INTRODUCTION Complex diseases are characterized by modest disease risk heritability and multifaceted interactions with environmental influences (Figure 2.1). This category includes most of the common diseases (cancer, cardiovascular diseases, behavior disorders, allergies, autoimmunity; the so-called diseases of civilization). The complexity arises from the fact that we cannot accurately predict the expression of the phenotype from knowledge of the effects of individual factors (genes or environment) considered alone; however, identifying and understanding the causal link between gene variation and disease risk is crucial to achieve the full biological description of the pathogenic processes. The genetic component in these disorders is not strictly Mendelian (dominant, recessive, or sex-linked), but rather results from the action of allelic variants in several genes. Crude theoretical modeling of human population history suggested that variants that have a high population frequency are likely to be responsible for complex traits — the common disease–common variant hypothesis. Other observers argue that these common variants are too old to be responsible for complex diseases affecting non-African populations — the common disease–rare variant hypothesis. In either case, their incomplete penetrance and moderate individual effect probably reflect epistatic interactions and post-genomic events; these include genes that rearrange somatically to encode a vast variety of immune receptors, post-transcriptional regulatory mechanisms, and incorporation of retroviral sequences (Table 2.1). An additional layer of difficulty is encountered when genetic heterogeneity, whereby specific genes or alleles influence susceptibility and pathogenesis in some individuals but not in others is considered (Figure 2.2). The past few years have seen real progress in the development of large-scale laboratory methods and tools to efficiently catalog human genomic diversity, as well as in the application of new analytical and data management approaches, setting the stage for the characterization of the genes involved in susceptibility and pathogenesis of multifactorial diseases. Further, a better-guided mining of data is leading to the identification of co-regulated genes and to the characterization of genetic networks that underlie specific cellular processes. This complex organization is what ultimately defines the function and, 35

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FIGURE 2.1 Mendelian vs. complex traits. A complex trait is defined by a genetic component that is not strictly Mendelian (dominant, recessive, or sex-linked), and involves the interaction, either programmed or stochastic, of two or more genes with environmental factors.

TABLE 2.1 Model of Genetic Contributions in Complex Genetic Disorders 1. 2. 3. 4. 5. 6. 7. 8. 9.

Multiple genes of moderate and cumulative effect dictate susceptibility and influence disease course Post-genomic (transcriptional) mechanisms Difficult-to-identify non-heritable (environmental) factors Unknown genetic parameters and mode of inheritance Complex gene–gene and gene–environment interactions Gender effect in susceptibility Etiologic heterogeneity. Identical genes, different phenotypes Genetic heterogeneity. Different genes, identical phenotypes Allelic heterogeneity. Identical genes, different alleles, identical phenotypes

therefore, the phenotype. With the aid of novel analytical algorithms, the combined study of genomic, transcriptional, proteomic, and phenotypic information in well controlled and adequately powered study groups will define useful conceptual models of pathogenesis and a framework for understanding the mechanisms of action of existing therapies for each disorder, as well as the rationale for novel curative strategies. Although genetic components in multifactorial diseases are clearly present, the lack of an obvious and homogeneous mode of transmission has slowed progress by preventing the full exploitation of classical genetic epidemiologic techniques. Nevertheless, an early approach used for gene discovery in complex disorders involved first determining the chromosomal region of the genetic effect by linkage analysis, which has been extremely

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FIGURE 2.2 Heterogeneity is an important feature in complex-diseases. The clinical thinking that common diseases are single disorders with varied clinical manifestations and courses may be at odds with data derived from a variety of disciplines — clinical, pathologic, imaging, immunologic, and genetic — all suggesting that biologic diversity is an important feature of these diseases. Locus heterogeneity, for example, means that different genes can cause identical or similar forms of the disease in different subjects. In other cases, an environmental factor may be triggering a phenotype that mimics a complex genetic disease. The implications of heterogeneity are considerable because fundamentally distinct pathogenic mechanisms may be acting in different individuals diagnosed as affected by the same disease and treated with the same drugs. Progress in deciphering the genomes of these diseases is necessarily linked to a full description of heterogeneity at all etiological levels.

productive for mapping genes responsible for monogenic diseases. The establishment of genetic linkage requires the collection of family pedigrees from more than one affected member to track the inheritance of discrete chromosomal segments that deviate from independent segregation and co-segregate with the disease. The theoretical foundation and methodologies are currently available to examine family data in a variety of ways based upon the structure of pedigrees in a given study.1,2 For example, family collections may consist of extended multigenerational pedigrees with more than one affected individual, or affected sibling pairs, alone or with parents and other affected siblings. The estimated frequency and penetrance of the susceptibility alleles, together with practical considerations, may determine the optimal ascertainment strategy. Once these regions have been identified and confirmed, a narrow and well-defined list of candidate genes can be compiled for analysis, even in the absence of a unifying model of pathogenesis (Figure 2.3). The early success of this approach with complex traits, such as the discovery of the role of APOE in late-onset Alzheimer’s disease3 and the availability of improved maps of highly polymorphic markers (i.e., microsatellites) for all chromosomes powered in the 1980s and 1990s, the rationale for the wide application of this method in non-Mendelian disorders. The potential of genetic mapping for gene identification in complex diseases was highlighted in a study of type 2 diabetes.4 The investigators followed original linkage data that implicated

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Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 2.3 Gene discovery strategies in complex traits.

the distal long arm of chromosome 2 and identified a disease-associated intronic polymorphism in calpain-10, an ubiquitously expressed member of the calpain-like family of cysteine proteases. In another example, the identification in 1996 of a locus linked to Crohn’s disease (CD) on chromosome 16 resulted in the identification of a frameshift mutation in CARD15/NOD2, a member of the Apaf-1/Ced-4 superfamily of apoptosis regulators, associated with disease susceptibility.5,6 More recently, Stefanson and colleagues reported the association of Neuregulin 1 to schizophrenia, supporting previous work done in five populations showing that schizophrenia maps to 8p21.7 However, for many common diseases, linkage analysis has achieved only limited success. For example, genetic studies in multiple sclerosis (MS) in the previous decade were dominated by three multi-stage whole genome screens performed in multiple-affected families ascertained in the U.S., U.K., and Canada.8–10 A fourth study concentrated on a genetically isolated region of Finland but was based on a small number of families.11 Since then, followup screenings in confirmatory and additional datasets have been completed as well. Together these studies identified approximately 70 genomic regions potentially involved in disease susceptibility, consistent with the long-held view that MS is a polygenic disorder. Each study used a somewhat overlapping but different set of genetic markers and different clinical inclusion criteria; thus the direct comparison of results is not straightforward. Nevertheless, total or even predominant replication between the different screens was not present. This is in part due to the incomplete genomic maps available at that time, limited power of the datasets, and the strategy of reporting all hits of potential linkage, recognizing that false positives will be generated along with the true positives. It is also possible that the study design in each case underestimated the confounding influence of disease heterogeneity and

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the limitations of parametric methods of statistical analysis. Meta-analyses of the raw and published data have refined the MS linkage map, but linkage exceeding unequivocally the threshold for genome-wide statistical significance was only detected in chromosome 6p21.3, confirming the known association with the HLA class II genes.12–14 Association studies with well selected candidate genes may be more powerful for the detection of susceptibility alleles in complex disorders. Allelic association refers to a significantly increased or decreased frequency of a marker allele in an individual carrying a disease trait, representing deviations from the random occurrence of the allele with respect to disease phenotype (Figure 2.3). Candidate genes, are defined as genes that are logical possibilities to play a role in a disease; for immune-mediated diseases for example, candidate genes might encode cytokines, immune-receptors, and proteins involved in pathogen clearance. Within each candidate locus, multiple polymorphisms must be tested in wellpowered datasets to ensure that any true effect is identified. Unfortunately, the direct testing by association of possibly relevant candidate genes, selected by speculation based upon concepts of pathogenesis, has been, in general, unproductive for gene identification in complex disorders. It has been recently argued that the application of epidemiological principles to candidate gene selection and study design, together with a rational prioritization of single nucleotide polymorphisms (SNPs) based on functionality, will improve the chances for successful outcomes in candidate gene studies.15 Progress in developing affordable high-throughput genotyping technology (see Chapter 6 for a thorough description of SNP genotyping methods) and a better understanding of the human genome structural landscape, suggest that genome-wide association studies are within reach, but a number of important challenges, including problems with multiple testing and study design, full information extraction, definition of phenotypes, and interactions among polymorphisms, remain to be matched.16,17

2.2 DISEASE-GENE DISCOVERY IN THE HapMap ERA Several recent discoveries have dramatically changed our ability to examine genetic variation as it relates to human disease. Obviously, the first key development was the completion of the final sequence of the human genome, which provided a direct way to connect a chromosomal region with its DNA sequence and gene content. The second key advance was the successful effort to define DNA sequence variation in the human genome. Specifically, a genome-wide SNP map has grown from an initial version with 4000 SNPs in 1999 to a current map of 10 million SNPs (www.ncbi.nlm.nih.gov/SNP/). It is estimated that SNPs occur on average every 1000 base pairs and have low mutation rates. Both factors are advantageous in disease association studies. Although most SNPs are likely to be neutral with no phenotypic consequences, some may mark the causative sequence difference contributing to disease susceptibility and/or resistance. However, to correctly interpret SNP genomic data we must discern to what extent the SNPs under analysis are within segmental duplications,18 inversions,19 loss of imprinting regions,20 polymorphic genomic imbalances,21 or genes resistant to X inactivation.22 A recent study using representational oligonucleotide microarrays shows that large-scale copy number polymorphisms (CNPs) of about 100 kilobases contribute substantially to normal human genomic variation in numerous genes involved in neurological function, regulation of cell growth and regulation of metabolism.23 It is also important to consider that preferential allelic gene expression provides an additional source of variability.24,25 The third key advance is shown in recent studies that define the long-range extent of correlations among SNPs in the human genome, and punctuate the extent of linkage disequilibrium (LD) into so-called haplotype blocks.26,27 LD refers to the presence of alleles

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Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 2.4 Schematic representation of haplotype blocks. A set of associated SNP alleles in a region of a chromosome is called a haplotype. A chromosome region may contain many SNPs, but only a few tag SNPs can provide most of the information on the pattern of genetic variation in the region. In the figure, 5 haplotypes are represented by 12 SNPs and 11 SNP patterns. However, 5 SNPs are sufficient to identify the patterns that tag each of the haplotypes and differentiate the susceptibility (1, 2) from the resistant (1, 2, and 3) haplotypes. Direct sequencing will identify the causative SNP pattern (H). The HapMap Project (http://www.hapmap.org/) will identify the full repertoire of tag SNPs, which should suffice to describe the common patterns of genetic variation in humans.

at neighboring loci segregating together at the population level more frequently than would be expected according to the genetic distance that separates them. The maintenance of these blocks with their limited number of haplotypes is most likely due to the non-uniform distribution of recombination that tends to occur at hot spots demarcating one block from the next. Such extended haplotypes are the results of recent population history and if common in a population may indicate recent positive selection events. In simple terms, these blocks can be considered the basic units of inheritance. Therefore, rather than considering each individual chromosome as carrying a unique combination of polymorphisms, human chromosomes may be viewed as mosaics, comprised of blocks of SNP alleles with common patterns (Figure 2.4). It has been estimated that in Europeans over 85% of the genome exists in haplotype blocks at least 20 kb in length. Within these blocks there are on average only four common haplotype variants. The immediate implication of these observations is that it may be possible to use only a representative fraction of the total genetic variation to serve as an adequate test for the extended chromosomal region under investigation, regardless of whether all variants have been discovered. It should be noted that the concept of blocks is a simple statistical framework to describe the patterns of genetic variation and the experimental definition of

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TABLE 2.2 Examples for Relative Risk, Frequency and Population Attributable Risk of Some Common Variants Associated with Common Diseases Disease

Variant Relative risk (95%CI) Frequency

Alzheimer’s

Type II Diabetes

Crohn’s Disease

Inflam. Bowel Disease

Graves

Type I Diabetes

SLE

ApoE*E4 8 (2–15.5) 9%

PPARG*Ala 1.25 (ND) 83–87%

IBD5 1.3 (1.2–1.4) 35%

DLG5 1.74 (1.31–2.32) 10%

CTLA4 CT60 1.5 (1.3–1.75) 47–53%

CTLA4 CT60 1.14 (1.1–1.2) 47–53%

PDCD1 2.6 (ND) 7%

blocks is sensitive to the resolution of genotyping used to analyze a particular chromosomal segment. Regardless, what is important is the fact that historical recombination events that shape the patterns of genetic variation may help define the limits of where a causal variant might be situated. Therefore, knowledge of the structure and location of LD and recombination in the genome can aid in the localization of susceptibility genes as described earlier for CD.4,5 More recently, Rioux and colleagues performed a high-density SNP-based LD mapping of this disease, and successfully identified the haplotypic variation in the cytokine gene cluster on 5q31 conferring susceptibility to CD,28 for which two potentially causal variants have been proposed.29 A similar approach was used to identify ADAM33 and GPRA as putative susceptibility genes for asthma, NRG1 for schizophrenia, and the IDDM12/CTLA4 locus in Graves’ disease and in type 1 diabetes (Table 2.2).7,30–32 These studies also show that even within a strong block of LD, a well powered study can resolve a signal of association to the trait within 2 to 10 kb, although the resolution will certainly depend on the extent of recombination in the region. Establishing a multi-ethnic whole genome map of the SNP-block and developing genotyping assays for large numbers of these blocks have been the goals of the International HapMap Project and a few private companies. Recently, geneticists at Perlegen, in collaboration with computer scientists from Berkeley and San Diego, published the genotyping of 1.58 million SNPs in 71 Americans of European, African, and Asian ancestry, describing allele frequencies and whole-genome LD patterns.33 The authors concluded that an equivalent level of statistical power can be maintained by typing about 300 000 tag SNPs in sample sets with European or Asian ancestry, and about 500 000 tag SNPs in African-American sample sets, providing a remarkable experimental tool for disease and evolution research.

2.3 EXTENDING THE DEFINITION OF PHENOTYPE Some authors argue that the limited success of genomic studies in complex diseases is in part due to the paucity of identifiable and well defined homogeneous traits against which to correlate the observed genomic variation. Measurable quantitative trait loci (QTL), for example, blood pressure for hypertension, rheumatoid factors for rheumatoid arthritis, and glucose levels for type I diabetes are not readily observable for many complex disorders, thereby limiting the power of these analyses. The development and widespread use of microarrays that allow the systematic interrogation of thousands of RNA transcripts opened a new and exciting venue for the genetic analysis of complex diseases. A method named genetical genomic, initially developed by plant geneticists, makes use of gene expression levels and evaluates them as potential QTL in linkage analyses (eQTL) using either microsatellite or SNP-based genetic maps.34 Unlike classic linkage analysis in which a single (or a few)

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phenotypic traits are evaluated for statistical correlation against a genomic region, a very large number of gene expression values are considered as traits, and hence, thousands of LOD scores are calculated. Using this method, a gene expression pattern strongly associated with murine obesity was identified leading to the identification of four new QTL linked to this complex phenotype.35 More recently, genetical genomics yielded the identification of regulatory networks affecting stem cell function,36 blood pressure,37 and some neural phenotypes.38 In humans, analysis of genomically controlled variation in gene expression has also been reported.39 This study showed familial aggregation of the transcriptional phenotype after comparing variation among unrelated individuals, among siblings within families, and between monozygotic twins. In a follow-up study, the investigators demonstrated linkage and association for more than 1000 eQTLs derived from expression analysis of 14 large CEPH reference families.40 Some of these expression phenotypes appear to be controlled by chromosomal regions within 5 Mb of the expressed gene (cis regulation) and some by regions further than 5 Mb or even in a different chromosome (trans regulation). Emerging advances in protein analysis (mass spectroscopy, NMR spectroscopy, x-ray crystallography, yeast two- or three-hybrid systems) will facilitate the transition from gene identification to gene function.

2.4

AN INTERPLAY OF GENES AND ENVIRONMENTAL FACTORS

In a 1981 review on the causes of cancer in the U.S., Doll and Peto estimated that approximately one third of deaths from cancer could be attributed to diet. Epidemiological, cluster or outbreak, and migration studies have been widely used to illustrate potential environmental influences on common diseases. Although the interpretation of most of these studies has been difficult, in part because of the small numbers of participants in some of the studies, they have been influential and do suggest the existence of critical periods for exposure to putative environmental disease agents. A large number of environmental exposures have been investigated in these diseases. Those include viral and bacterial infections, nutritional and dietary factors, smoking, well water, animals, minerals, trauma due to accident or surgery, pollution, solar radiation, temperature, rainfall, humidity, chemical agents, metals, organic solvents, geographical influences, and various occupational hazards. However, most attempts to isolate the causative environmental factor have been largely unproductive and failed to provide major insights into mechanisms of disease susceptibility and pathogenesis. This may be due to heterogeneity operating also at the level of triggering factors. Whether the genotype dictates different forms of the same disease in response to a common causative agent or trigger, or whether the genotype reflects different diseases with different environmental causes, is not known. The expectation that a single agent would have enough specificity and universality to account for all cases of a single disorder may be unrealistic. Infectious diseases, for which the environmental factor is usually known through the strict application of Koch postulates, belong by definition to the category of multifactorial diseases as individual susceptibility is strongly influenced by the genetic profile of the host. For example, the initial immune reaction to the human immunodeficiency virus-1 (HIV-1), as well as the ability to durably control viral replication and restore immune function, varies across individuals in a manner dependent on allelic variants of host molecules. Individuals homozygous for the CCR5 delta32 deletion mutation have no surface expression of the receptor and are highly protected against HIV-1 infection.41 Differences in the copy number of a segmental duplication encompassing the gene encoding CCL3L1 (MIP-1alphaP), a potent HIV-1-suppressive chemokine and ligand for CCR5, have been recently associated with differential HIV/acquired immunodeficiency syndrome (AIDS) susceptibility.42 In addition, HLA class-I allelic variants have been implicated repeatedly with susceptibility,

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course and outcome of HIV-1 infection.43 Furthermore, certain HLA alleles that are members of the Bw4 molecular epitope have been associated with delayed progression to AIDS, when present, along with an allelic form of the NK cell receptor KIR, the KIR3DS1 allele.44

2.5 CONCLUSIONS AND FUTURE DIRECTIONS Population, family, and molecular studies show that the disease-prone genotype in common disorders is likely to result from multiple independent or interacting polymorphic genes, each contributing a small or at most a moderate effect to the overall risk. It is also likely that genetic heterogeneity exists, meaning that specific genes influence susceptibility and pathogenesis in some individuals but not in others. Concordance in families for early and late clinical features has been observed as well, indicating that in addition to susceptibility, genes influence disease severity and other aspects of the clinical phenotype. Hence, some genes may be involved in the initial pathogenic events, while others could influence the development and progression of the disease. Their characterization will help to define basic etiopathogenic pathways. The confluence of recent technological and analytical advances proposes a new experimental view to elucidate the pathogenic mechanisms of multifactorial diseases. Specifically: 1. Groups and consortia with the appropriate experimental, clinical and financial resources will continue the analysis of the disease genomes, using large well characterized DNA data sets and dense arrays of informative genetic markers to further narrow the chromosomal segments harboring causative genes. The potentially critical importance of identifying and studying rare families that might have a single gene variant cannot be overstated; this approach has been successful in genetic dissection of complex neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. Similarly, semi-isolated or homogeneous populations could prove to be instructive as well. The analysis of multi-ethnic patient populations with different disease risks, both in their native environment and after migration, will provide important new insights and clues about genetic and clinical heterogeneity in multifactorial diseases. Finally, the comparative study of different diseases with shared features (autoimmune for example) may help to identify common fundamental genomic factors. Key to the success of the proposed studies will be the availability of rapid, reliable, non-labor-intensive and affordable methods for high-throughput polymorphism screening. A recent study reported the identification of complement factor H (CFH) polymorphism strongly associated with age-related macular degeneration (AMD) by means of a whole-wide screen with over 100 000 SNPs.45 The CFH gene is located on chromosome 1 in a region repeatedly linked to AMD in family-based studies (q32) and was confirmed in two additional studies. Remarkably, the studies included only 96 cases and 50 controls. It is conceivable that for most disorders, substantially larger study groups will be necessary. With 500 000 SNP platforms readily available and one million SNP arrays in the pipeline, association studies of this type harbor great potential for gene discovery in complex disorders, but cost still represents a formidable obstacle. At 2006 prices, a modest, probably underpowered 500-case-500-control study will cost between U.S.$1.5 and 2 million. In addition, a number of very important analytical challenges, including how to interpret results obtained from large numbers of statistical tests and how to detect biologically meaningful interactions between polymorphisms that confer disease risk, will need to be overcome.46

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2. In all likelihood, the use of phenotypic (clinical and paraclinical), epidemiological, and demographic variables will assume increasing importance as stratifying elements for genetic studies of multifactorial diseases to increase homogeneity and to address important genotype–phenotype correlations. 3. Gender differences are well documented in some multifactorial diseases. Rigorous studies assessing the potential role of genetic factors in disease sexual dimorphism remain to be performed. Further, reproductive histories of females including factors such as pregnancy and breastfeeding may influence disease pathogenesis. Genomic, clinical and reproductive information will be combined to investigate potential risk factors in large groups of female patients. 4. Genetic polymorphisms in drug receptors, metabolizing enzymes, transporters, and targets have been linked to interindividual differences in efficacy and toxicity of many medications. Pharmacogenomic studies in large data sets with validated clinical end points will directly address the correlation between different genotypes and clinical responses to therapeutic modalities. 5. In parallel with the expansion of genomic and genetic knowledge, a substantial effort to improve acquisition of unbiased non-genetic data merits serious consideration.47 Sophisticated and longitudinal assessment of dietary, lifestyle and environmental exposure should be carried out using both questionnaires and biological measures. Large-scale explorations of gene diversity and expression have become routine over the past few years. Multi-disciplinary and multi-analytical approaches will decipher within the next few years the complete rosters of disease loci, and define unifying conceptual models of pathogenesis. These studies need to be linked to the development of novel mathematical formulations designed to identify modest genetic effects, interactions between multiple genes and interactions between genetic, clinical, and environmental factors. Their characterization will help to define basic etiologies, improve risk assessment, and influence therapeutics for common multifactorial diseases.

REFERENCES 1. Hoh, J. and Ott, J., Genetic dissection of diseases: design and methods, Curr. Opinion Genet. Dev., 3, 229, 2004. 2. Thornton-Wells, T. A., Moore, J. H., and Haines, J. L., Genetics, statistics and human disease: analytical retooling for complexity, Trends Genet., 20, 640, 2004. 3. Corder, E. H. et al., Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families, Science, 261, 921, 1993. 4. Horikawa, Y. et al., Genetic variation in the gene encoding calpain-10 is associated with type 2 diabetes mellitus, Nature Genet., 26, 163, 2000. 5. Hugot, J. P. et al., Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn’s disease, Nature, 411, 599, 2001. 6. Ogura, Y. et al., A frameshift mutation in NOD2 associated with susceptibility to Crohn’s disease, Nature, 411, 603, 2001. 7. Stefansson, H. et al., Neuregulin 1 and susceptibility to schizophrenia, Am. J. Hum. Genet., 71, 877, 2002. 8. Ebers, G. C. et al., A full genome search in multiple sclerosis, Nature Genet., 13, 472, 1996. 9. Haines, J. L. et al., A complete genomic screen for multiple sclerosis underscores a role for the major histocompatability complex. The Multiple Sclerosis Genetics Group, Nature Genet., 13, 469, 1996.

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10. Sawcer, S. et al., A genome screen in multiple sclerosis reveals susceptibility loci on chromosome 6p21 and 17q22, Nature Genetics, 13, 464, 1996. 11. Kuokkanen, S. et al., Genomewide scan of multiple sclerosis in Finnish multiplex families, Am. J. Hum. Genet., 61, 1379, 1997. 12. Transatlantic multiple sclerosis genetics cooperative, A meta-analysis of genomic screens in multiple sclerosis, Mult. Scler., 7, 3, 2001. 13. Transatlantic multiple sclerosis genetics cooperative, A meta-analysis of whole genome linkage screens in multiple sclerosis, J. Neuroimmunol., 143, 39, 2003. 14. Wise, L. H., Lanchbury, J. S., and Lewis, C. M., Meta-analysis of genome searches, Ann. Hum. Genet., 63, 263, 1999. 15. Tabor, H. K., Risch, N. J., and Myers, R. M., Opinion: Candidate-gene approaches for studying complex genetic traits: practical considerations, Nat. Rev. Genet., 3, 391, 2002. 16. Carlson, C. S. et al., Mapping complex disease loci in whole-genome association studies, Nature, 429, 446, 2004. 17. Freimer, N. and Sabatti, C., The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology, Nature Genet., 36, 1045, 2004. 18. Fredman, D. et al., Complex SNP-related sequence variation in segmental genome duplications, Nature Genet., 36, 861, 2004. 19. Stefansson, H. et al., A common inversion under selection in Europeans, Nature Genet., 37, 129, 2005. 20. Mummert, S. K., Lobanenkov, V. A., and Feinberg, A. P., Association of chromosome arm 16q loss with loss of imprinting of insulin-like growth factor-II in Wilms tumor, Genes Chromosomes Cancer, 43, 155, 2005. 21. Iafrate, A. J. et al., Detection of large-scale variation in the human genome, Nature Genet., 36, 949, 2004. 22. Carrel, L. and Willard, H. F., X-inactivation profile reveals extensive variability in X-linked gene expression in females, Nature, 434, 400, 2005. 23. Sebat, J. et al., Large-scale copy number polymorphism in the human genome, Science, 305, 525, 2004. 24. Yan, H. et al., Allelic variation in human gene expression, Science, 297, 1143, 2002. 25. Lo, H. S. et al., Allelic variation in gene expression is common in the human genome, Genome Res., 13, 1855, 2003. 26. Daly, M. J. et al., High-resolution haplotype structure in the human genome, Nature Genet., 29, 229, 2001. 27. Gabriel, S. B. et al., The structure of haplotype blocks in the human genome, Science, 296, 2225, 2002. 28. Rioux, J. D. et al., Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease, Nature Genet., 29, 223, 2001. 29. Peltekova, V. D. et al., Functional variants of OCTN cation transporter genes are associated with Crohn disease, Nature Genet., 36, 471, 2004. 30. Van Eerdewegh, P. et al., Association of the ADAM33 gene with asthma and bronchial hyperresponsiveness, Nature, 418, 426, 2002. 31. Ueda, H. et al., Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease, Nature, 423, 506, 2003. 32. Laitinen, T. et al., Characterization of a common susceptibility locus for asthma-related traits, Science, 304, 300, 2004. 33. Hinds, D. A. et al., Whole-genome patterns of common DNA variation in three human populations, Science, 307, 1072, 2005. 34. Jansen, R. C. and Nap, J. P., Genetical genomics: the added value from segregation, Trends Genet., 17, 388, 2001. 35. Schadt, E. E. et al., Genetics of gene expression surveyed in maize, mouse and man, Nature, 422, 297, 2003. 36. Bystrykh, L. et al., Uncovering regulatory pathways that affect hematopoietic stem cell function using ‘genetical genomics’, Nature Genet., 37, 225, 2005.

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Cytokine Gene Polymorphisms in Multifactorial Conditions 37. Hubner, N. et al., Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease, Nature Genet., 37, 243, 2005. 38. Chesler, E. J. et al., Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function, Nature Genet., 37, 233, 2005. 39. Cheung, V. G. et al., Natural variation in human gene expression assessed in lymphoblastoid cells, Nature Genet., 33, 422, 2003. 40. Morley, M. et al., Genetic analysis of genome-wide variation in human gene expression, Nature, 430, 743, 2004. 41. Carrington, M. et al., Genetics of HIV-1 infection: chemokine receptor CCR5 polymorphism and its consequences, Hum. Mol. Genet., 8, 1939, 1999. 42. Gonzalez, E. et al., The influence of CCL3L1 gene-containing segmental duplications on HIV-1/ AIDS susceptibility, Science, 307, 1434, 2005. 43. Carrington, M. et al., HLA and HIV-1: heterozygote advantage and B*35-Cw*04 disadvantage, Science, 283, 1748, 1999. 44. Martin, M. P. et al., Epistatic interaction between KIR3DS1 and HLA-B delays the progression to AIDS, Nature Genet., 31, 429, 2002. 45. Klein, R. J. et al., Complement factor H polymorphism in age-related macular degeneration, Science, 308, 385, 2005. 46. Marchini, J., Donnelly, P., and Cardon L. R., Genome-wide strategies for detecting multiple loci that influence complex diseases, Nature Genet., 37, 413, 2005. 47. Collins, F. S., The case for a US prospective cohort study of genes and environment, Nature, 429, 475, 2004.

3

Statistical Approaches to Analysis of Polymorphisms in Multifactorial Conditions An Goris and Mariza de Andrade

CONTENTS 3.1 3.2

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Linkage Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.2.1 Definition and Study Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.2.2 Interpretation of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 3.2.3 Power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.3 Linkage Disequilibrium- or Association-Based Methods . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.3.1 Definition and Study Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.3.2 Selection of Markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.3.3 Candidate-Gene and Whole-Genome Association Studies . . . . . . . . . . . . . . . . . . 54 3.3.4 Replication and False Positives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.3.4.1 Population Stratification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.3.4.2 Technical Artifacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.3.4.3 Statistical Fluctuations Arising by Chance and Multiple Testing Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.3.4.4 Sample Sizes for Detection and Replication. . . . . . . . . . . . . . . . . . . . . . . . 56 3.4 Admixture Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

3.1 INTRODUCTION The vast majority (99.9%) of the ca. 3 billion nucleotide long, recently deciphered human genome sequence, is identical between individuals. The remaining 0.1% is responsible for the genetic diversity between individuals. The potential sources of this diversity include:


Single nucleotide polymorphism or SNP: differing in one nucleotide, e.g. C/A
Indel: insertion or deletion of one or a few nucleotides, e.g. TTA/
Repeat polymorphism: differing in the number of times a basic motif of two to five (microsatellite repeat) or several tens (minisatellite, variable number tandem repeat or VNTR) of nucleotides is repeated, e.g. (CA)12/(CA)13/(CA)14
Structural variation: deletions, duplications, or inversions of up to hundreds of kilobases of sequence1–4 SNPs are usually binary and lend themselves well to accurate and automated highthroughput genotyping, as described in Chapter 6. Moreover, they are widely distributed 47

48

Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 3.1 The relationship we wish to detect in order to better understand a disease or condition is that between the genotype at a trait-contributing locus and the trait phenotype. Compared to Mendelian disorders, this relationship is obscured by several issues typical of multifactorial disorders. Moreover, we usually have to rely on an indirect testing strategy, where power depends on the degree of linkage and linkage disequilibrium between marker and trait locus. As a result, the correlation actually tested in a genetic experiment is that between the genotype at a marker locus and the trait phenotype.

throughout the genome. When comparing two chromosome copies randomly selected from a population, the likelihood of a nucleotide position being different is 7.1–7.5  104, corresponding to one variation every 1300–1400 nucleotides.5,6 Some of these differences will be more or less specific to an individual or family (rare variants) whereas others will be observed in many other individuals (common variants). The total number of common SNPs, i.e. SNPs with both alleles having a frequency of 41%, in the human population is expected to be 10–15 million.5,6 The whole of the human genetic diversity contributes, together with environmental factors, to the wide range of phenotypic variation observed between individuals, including differences in susceptibility to multifactorial disorders, disease course, or response to treatment. The goal of genetics is to pinpoint those DNA variants that contribute most significantly to the population variation in each trait. Whereas it is currently not feasible to test all genetic variants directly, the human genome itself offers an alternative, indirect strategy based on the phenomenon that variants close to each other on the same chromosome tend not to behave independently of each other. An assayed variant may therefore act as a surrogate marker and ‘‘mark’’ the presence of an unassayed trait-contributing variant nearby, with which it is correlated, i.e. in linkage and possibly linkage disequilibrium (Figure 3.1). The degree of linkage and linkage disequilibrium between the marker and trait locus are pivotal for the success of the indirect testing strategy, and the recent dramatic advances in technology and in knowledge of the human genome are beneficial in this context. Biological factors typical of complex disorders, such as low penetrance or small effect sizes, the influence of several other genes and environmental factors, and heterogeneity among individuals with the trait, obscure however to some extent the relation between variant and trait and continue to make the unraveling of these traits challenging, in contrast to the consecutive successes seen for Mendelian disorders (Figure 3.1).

3.2 3.2.1

LINKAGE ANALYSIS DEFINITION

AND

STUDY DESIGN

For two loci located on different chromosomes, the alleles of one locus are inherited independently of those of the second locus, as formulated in Mendel’s second law. The same

Statistical Approaches to Analysis of Polymorphisms in Multifactorial Conditions

49

holds true for two loci on the same chromosome but separated by a large distance, the reason being that during gamete formation recombination between them can freely occur. The probability of a recombination event decreases however for two loci located relatively close to each other, leading to the alleles occurring together on parental chromosomes being preferentially transmitted as units to the offspring, and thereby violating Mendel’s law of independent assortment. This phenomenon of linkage allows inferring the presence and location of an unknown susceptibility locus from the observation that, for a genomic region surrounding it, alleles cosegregate with the disease phenotype within families. Since for complex disorders extended pedigrees with multiple individuals affected are generally very rare and classical parametric linkage analysis is difficult to apply, linkage studies in these conditions frequently employ model-free or non-parametric analytic methods that do not assume Mendelian dominant or recessive modes of inheritance. An ‘‘affecteds-only’’ strategy is usually adopted because of the lower information contribution from unaffected relatives, which may — despite their unaffected state — also have inherited risk alleles when penetrance is low. Typical study populations consist of any affected relative pairs except for parent–child pairs since they are uninformative for linkage. For diseases of old age, such as Alzheimer’s and Parkinson’s disease, an affected sibling-pairs design is the most frequently used. Regions of the genome in linkage with a trait locus will be inherited by both affected relatives of a pair more often than expected by chance alone. Twopoint measures consider the segregation of alleles at a single marker with a trait, whereas multipoint measures take into account a set of two or more adjacent markers and a trait. The latter is more powerful than the former; however it is more susceptible to genetic mapping errors than the former. The extent to which allele sharing can reliably be determined throughout the genome is limited by factors related to the marker map, such as map accuracy and marker density, and the amount of missing information. The latter can result from the difficulty to distinguish between alleles identical-by-descent, i.e. inherited from the same ancestor, and alleles identical-by-state only — especially when relatives linking the affecteds are untyped, from genotyping failure and from genotyping error. Since both individuals in a pair need to be genotyped for the pair to be informative, a genotyping failure rate of 20% for a microsatellite marker leads to 40% of pairs not being analyzed.7 An error rate of just 1%, typically observed for microsatellite markers, may decrease the logarithm of odds (LOD) score for linkage by as much as half.8 Evidence has emerged that newly available high-density SNP sets compare favorably to traditional microsatellite maps for these issues and will increase significantly accuracy, information extraction, and power of linkage studies.7,9–12 Linkage disequilibrium between markers in such a dense map does need to be accounted for, however, since it can erroneously inflate linkage scores.12

3.2.2 INTERPRETATION

OF

RESULTS

The LOD score indicates how much more likely there is a true genetic effect on disease present at a specific genomic region than not. A LOD score of 3–4, for example, means a 1000–10 000 times higher likelihood of linkage and corresponds to 5% genome-wide significance for linkage, i.e. such a linkage peak is expected by chance only (false positive) once in every 20 genome-wide linkage screens. Less stringent criteria, which are fulfilled by chance alone more frequently, are used to indicate regions of potential or suggestive linkage.13 A measure of effect size used in the context of linkage studies is R, the ratio of the type R relative recurrence risk attributable to a specific genetic effect compared to the population lifetime risk.14 The recurrence risk ratio of a sibling, s, can be estimated in linkage studies on the basis of the amount of allele sharing in affected sibling pairs.15 If based on single studies, these effect sizes tend to be overestimated, however, following the same argument as for the odds ratio, used as a measure of effect size in association studies (see below).16

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Cytokine Gene Polymorphisms in Multifactorial Conditions

The relationship between the effect size measures s and odds ratio is complex and dependent upon the allele frequency and the disease model.17

3.2.3

POWER

Application of the linkage approach and detection of a robust peak with genome-wide significant linkage has been instrumental, for example, in the identification of a role for the NOD2/CARD15 gene and the 5q31 cytokine cluster in Crohn’s disease.18,19 For many of the susceptibility loci with smaller effects expected in complex disorders, on the other hand, linkage analysis will not provide statistical evidence except in unrealistically large sample sizes.20 By contrast, association or linkage-disequilibrium methods may still have adequate power for these modest effects.20,21 For example, the effect of the peroxisome proliferator activated receptor gamma (PPARG) gene in type 2 diabetes, which has been replicated in several association studies, would only have been detected in a linkage study with more than one million affected sibling pairs.22

3.3

LINKAGE DISEQUILIBRIUM- OR ASSOCIATION-BASED METHODS

3.3.1

DEFINITION

AND

STUDY DESIGN

Association is the correlation between a variant and a trait in the population. It is detected by comparing a group of individuals with the disease (cases) with a group of comparable unaffected individuals (controls) and observing significant allele or genotype frequencies between the two groups. Different options for the selection of controls can be adopted. The first one is the use of unrelated controls, e.g. healthy controls matched by age and sex (Table 3.1). An alternative is a family-based control design that is based on trio families, i.e. patients with both parents (Figure 3.2 and Table 3.2). It can be shown that the virtual controls formed by the untransmitted parental alleles are a good representation of the background population while at the same time being perfectly ethnically matched to their corresponding cases. This design was first introduced by Falk and Rubinstein,23

TABLE 3.1 Test Statistic for Association in Case-Control Study Observed Contingency Table

Allele A Allele B Total

Expected Contingency Table

Cases

Controls

Total

Cases

Controls

Total

O11 ¼ nA,cases O21 ¼ nB,cases

O12 ¼ nA,controls O22 ¼ nB,controls

nA nB

E11 ¼ (nA/N)  ncases E21 ¼ (nB/N)  ncases

E12 ¼ (nA/N)  ncontrols E22 ¼ (nA/N)  ncontrols

nA nB

ncases

ncontrols

N

ncontrols

N

2

 ¼

ncases P ðOij Eij Þ2 ij

E

The contingency table on the left contains the observed allele counts for both alleles in cases and controls (N ¼ total number of alleles, i.e. twice the total number of individuals). The contingency table on the right has the same row and column totals but, as expected under the null hypothesis, equal allele frequencies between cases and controls. The test statistic follows a 2 distribution with one degree of freedom. The contingency tables and test statistic can be extended to include more than two alleles, where the degrees of freedom amount to the number of alleles minus one.

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Statistical Approaches to Analysis of Polymorphisms in Multifactorial Conditions

FIGURE 3.2 Each parent has two alleles for a marker, of which one is transmitted to his/her affected child and the other is not. The non-transmitted alleles from both parents can be considered to form a virtual control individual that could theoretically have been born as a child of these parents (Figure 3.3a). The groups of cases and virtual controls (Affected Family-Based Controls or AFBAC) can then be compared in a 2 test as before. An alternative form of analysis with family-based controls is the Transmission Disequilibrium Test or TDT (see Table 3.2).

TABLE 3.2 Transmitted Allele

Non-transmitted Allele

Allele A

Allele B

Total

Allele A Allele B

nT(A),NT(A) nT(A),NT(B)

nT(B),NT(A) nT(B),NT(B)

nNT(A) nNT(B)

Total

nT(A)

nT(B)

N

ðnTðAÞ, NTðBÞ  nNTðAÞ, TðBÞ Þ2 TDT ¼ nTðAÞ, NTðBÞ þ nNTðAÞ, TðBÞ Each parent (N parents in total) is classified in one of the cells of the table on the basis of the transmitted/nontransmitted alleles (see Figure 3.2). Parents homozygous for an allele necessarily transmit that allele (e.g. the first parent in Figure 3.2) and are therefore not informative (upper left and lower right cells in B). Heterozygous parents can transmit either allele A or allele B, theoretically each with equal, i.e. 50%, probability. A MacNemar’s test is applied to evaluate whether the number of parents transmitting allele A and not transmitting allele B is equal to the number of parents with the inverse pattern (upper right and lower left cells), as expected under the null hypothesis, or whether there is a significant deviation in the transmission ratio, indicating association. The test statistic follows a 2 distribution with one degree of freedom.

and further developed by Thomson24 (affected family-based controls) and Spielman et al.25 (transmission disequilibrium test). Lastly, unaffected siblings may be used as controls. Study designs involving parents, and especially siblings, suffer from some loss of power compared to a design with unrelated controls.20 Other drawbacks of the inclusion of parents in the design are their possible unavailability for sampling, especially for late-onset diseases, and the larger genotyping effort involved, with three instead of two samples to be genotyped for each marker. On the other hand, the advantage of ethnical matching, long considered as predominantly theoretical, may in fact prove a real benefit (see below). The significance (P value) of a test, i.e. how often a test statistic equal to or larger than the one observed in the dataset would be expected to occur by chance only, can be calculated by comparing the observed 2 or TDT test statistic to a null distribution of test statistics expected on the basis of chance. A 2 distribution with the appropriate degrees of freedom is

52

Cytokine Gene Polymorphisms in Multifactorial Conditions

such a null distribution. Alternatively, a null distribution can be provided by a permutation or bootstrapping procedure. This consists of a large number of steps, in each of which the case and control or transmitted and non-transmitted labels in the observed dataset are randomly reshuffled and the corresponding test statistic is calculated (see Reference 26 for an illustration). The finding of one value equal to or larger than the observed test statistic in 10 000 steps would correspond, for example, to a P value of 104. Multiple testing issues do require additional control of the false positive rate (see below).

3.3.2

SELECTION

OF

MARKERS

Whereas linkage is based on the sharing of large chromosome fragments within one or a few generations in families, association essentially relies on the sharing of small fragments among individuals that are very distantly related (see below) and therefore requires the study of many more markers that are carefully selected. Approximately 70–80% of the genome is located in regions of strong linkage disequilibrium (LD).27 For variants in such regions, the number of combinations of alleles occurring on the same chromosome (haplotypes) is strikingly less than theoretically expected, usually around 3–5, and the haplotype frequencies deviate from the simple product of allele frequencies expected for independent variants (Figure 3.3a). Figure 3.3b depicts a typical example of such a region. It also illustrates the origins of linkage disequilibrium: the minor allele of SNP 15 seems to have arisen in this population — through a new mutation or the immigration of a founder carrying this allele — on the specific background of the fourth haplotype. Recombinations over the generations since have not been able yet to reshuffle this haplotype, but population history with genetic drift, bottlenecks, and/or selection has shaped its frequency in the population. Two common measures of LD are D0 and the correlation coefficient r2. They are both built on the basic pairwise disequilibrium coefficient D, i.e. the difference between the observed haplotype frequency and the product of the allele frequencies as expected if the two loci were independent.21 For two SNPs in close vicinity with alleles (A, a) and (B, b), chosen so that D  0 and frequency of A ( fA)  frequency of B ( fB), the following formulas apply28 D ¼ fAB  fA fB D0 ¼

D Dmax

r2 ¼

D2 fa fB ¼ ðD0 Þ2  fA fa fB fb fA fb

Ne ¼

with Dmax ¼ fa fB

N r2

D0 is a commonly used measure of historical recombination, reaching a value of 1 for complete LD and decreasing towards 0 with decay of LD. It offers information on the physical extent of useful LD by providing an upper-bound of the correlation coefficient r2. However, D0 is prone to yield inflated values when the allele frequencies are small, and should be interpreted with caution.29 An r2 value of 1 is only observed for two SNPs in complete LD (D0 ¼ 1) with equal allele frequencies ( fA ¼ fB) and a perfect correlation of alleles at the two loci, i.e. the allele at one SNP perfectly predicts the allele of the second SNP and inversely (see example in Figure 3.3b). r2 is especially useful because it is inversely proportional to the

Statistical Approaches to Analysis of Polymorphisms in Multifactorial Conditions

53

FIGURE 3.3 a. Theoretical expectations for independent variants. Consider two SNPs in close vicinity to each other, with alleles A/a and B/b respectively (A and B represented by black squares and a and b by gray squares). There are four combinations of alleles on the same chromosome (haplotypes) possible. The expected haplotype frequencies are the products of the allele frequencies. For more than two variants, the number of expected haplotypes increases rapidly, as indicated in the table. b. A typical example of 20 SNPs over a 60-kb region in strong linkage disequilibrium (generated from HapMap data with Haploview software). For each SNP, a black square represents the major allele and a gray square the minor one. Instead of over one million expected haplotypes (table in A), only five common (41%) haplotypes and a few very rare ones are observed. The first haplotype, with the major allele at all sites except SNP11, is observed in 28% of chromosomes, whereas on the basis of the product of allele frequencies (as in A) it would be expected to have a frequency of 0.02% only. Illustration of measures of LD and haplotype tagging SNPs The combinations SNP06–SNP09 and SNP09–SNP11 both have a D0 of 1.0. However, whereas the correlation between the alleles of the first two SNPs is perfect (r2 ¼ 1.0), i.e. typing SNP06 will perfectly predict the allele of SNP09 occurring on the same chromosome, the correlation between the alleles of the second combination is much weaker (r2 ¼ 0.11). SNP11 is not highly correlated with any other SNP in the set, but is perfectly correlated with the combination of SNPs 01, 02 and 06: observation of the major allele at all three SNPs perfectly predicts occurrence of the minor allele at SNP11, whereas any other combination corresponds to the major allele at SNP11. In an analogous manner, it can be shown that each of the 20 SNPs is highly correlated with a single SNP or a combination of SNPs among the set of ‘‘haplotype-tagging SNPS’’ 01, 02, 06 and 15 (indicated by triangles at the top). Illustration of the influence of r2 on the sample size SNP15 is a nonsynonymous coding SNP in the PTPN22 gene that was recently found to be associated with a subset of autoimmune diseases (see text). Suppose a sample size of 500 cases and 500 controls was needed to have sufficient power to detect this effect by typing SNP15 directly. If typing SNP17 (SNP17–SNP15: D0 ¼ 1.0, r2 ¼ 0.44) instead of SNP15, the sample size needed to retain the same power would be approximately double (500/0.44 ¼ 1136 cases and controls). By typing SNP14 (SNP14–SNP15: D0 ¼ 1.0, r2 ¼ 0.05) only, it would be very difficult to detect the effect, since a sample size of 10 000 cases and controls (500/0.05) would be required.

54

Cytokine Gene Polymorphisms in Multifactorial Conditions

increased sample size (Ne) needed, instead, of the original sample size N, to allow for reduced LD when using one SNP as a surrogate for another (see example in Figure 3.3b). In regions of strong linkage disequilibrium, subsets of SNPs can be chosen so that most of the known SNPs in the region are highly correlated with either a single SNP or a combination of SNPs in the subset (see example in Figure 3.3b). Any unknown variants in the region may also have a reasonable likelihood of being correlated with this subset of SNPs. Typing only these haplotype tagging SNPs allows capturing most of the common variation in a region with highly reduced genotyping efforts but without sacrificing too much power.30,31 Such an approach would, for example, have permitted the identification of CARD15 variants influencing the risk of Crohn’s disease, where three different risk alleles arose independently on different chromosomes, but coincidentally on the same haplotype.32 The growing knowledge of variations and of patterns of linkage disequilibrium in the human genome (www.hapmap.org; genome.perlegen.com) facilitates performing carefully designed studies that capture most of the variation in the region of interest in an efficient way. Instead of identifying specific well-defined haplotypes to be tested, an alternative is applying a data mining approach such as Haplotype Pattern Mining.33 This approach searches the observed data for any combinations of marker alleles or ‘‘haplotype patterns’’ that roughly correspond to haplotypes identical-by-descent surrounding a susceptibility allele in affected individuals that are assumed to be very distantly related. Patterns are permitted to include gaps, allowing for haplotypes identical-by-descent being interrupted by missing data, genotyping errors, new mutations, recombinations, or gene conversions. All haplotype patterns that fulfill parameter settings for maximum genetic length and maximum number and length of gaps and that are different in frequency between case and control chromosomes, are identified and ranked according to their evidence for association, but no formal significance testing is provided. An example of the application of Haplotype Pattern Mining is the report of association of asthma-related phenotypes with a conserved 133-kb pattern within the gene for an orphan G protein-coupled receptor named GPRA.34 All approaches involving haplotype testing require methods to determine phase. For example, for an individual with genotypes A/a and B/b for two nearby SNPs, the two possible phases are A–B on one chromosome and a–b on the other, or A–b and a–B each occurring on one chromosome. The inclusion of parents in the study design has the advantage that phase can be deduced directly: since no recombination is expected to occur between two SNPs in close vicinity, the combinations of alleles occurring on the same chromosome are either transmitted or not transmitted together from parents to children. For case-control designs, computational methods such as the expectation-maximization (EM) algorithm are being employed to infer haplotypes from genotype data.35

3.3.3

CANDIDATE-GENE AND WHOLE-GENOME ASSOCIATION STUDIES

A candidate-gene association approach tries to prioritize the many genes and variants in the human genome for study in a specific disease, on the basis of available data, on their function, expression, position in the genome, or other features that increase the prior probability of association. A recent success of this approach was the finding that a coding SNP (R620W) in the lymphoid tyrosine phosphatase PTPN22 gene, a negative regulator of T-cell activation, is associated with susceptibility to a subset of autoimmune diseases including type 1 diabetes, rheumatoid arthritis, systemic lupus erythematosus, and Graves’ disease.36–39 Spectacular advances in genotyping technology (see Chapter 6) and in knowledge of human genetic variation and linkage disequilibrium are starting to make it feasible to exploit the advantages of association also in a whole-genome approach. Sets of 100 000– 500 000 SNPs are expected to be required in order to cover most of the genome.21,26

Statistical Approaches to Analysis of Polymorphisms in Multifactorial Conditions

55

New developments in genome-wide association studies are under way,40 and the first whole-genome association screens in multifactorial conditions are currently being undertaken.41,42

3.3.4 REPLICATION

AND

FALSE POSITIVES

Association studies have acquired a reputation for the rate of false positives and the frequent failure of replication. However, careful study design and interpretation go a long way to remedy the different causes underlying this issue.43 3.3.4.1

Population Stratification

The first empirical evidence is emerging that indicates that subtle population substructure can occur within populations at a level that could be a significant problem when trying to detect modest susceptibility effects.44,45 In Icelandic birth cohorts, individuals from different regions of the island were compared for a random set of microsatellite markers. For an important fraction of these, significant allele frequencies were observed between different geographical regions, especially for the older population cohorts.45 Simulations show that if regions are not equally represented between cases and controls, spurious associations with disease may be obtained or true associations may be overlooked.46 If this is the case in the relatively small, recent, and homogeneous Icelandic population, this will probably be even more important in larger populations. Family-based study designs guard against population substructure because of the perfect ethnical matching between cases and family-based controls (see above). For designs with cases and unrelated controls, careful selection may be of some benefit and genotyping a number of markers unrelated to the trait under study may detect and account for population substructure.47,48 Test statistics for markers unrelated to the disease studied theoretically follow a 2 distribution with (number of alleles  1) degrees of freedom, but in the presence of population substructure more markers show association than expected by chance and the distribution is inflated. Testing a random set of markers allows estimating the factor of inflation, which can then be used to adjust all association tests with markers of interest for population stratification.47 Alternatively, on the basis of information from markers unrelated to the disease, the study population may be clustered into more homogeneous groups and markers may be tested within each subgroup, albeit accompanied by some loss of power.48 3.3.4.2

Technical Artifacts

When typing large numbers of markers even unusual technical artifacts are likely to occur occasionally. Some artifacts can be detected by including reference and duplicate samples in the study design or through the observation of violation of Hardy–Weinberg equilibrium or of Mendelian errors. It should be noted that researchers currently take very different approaches at tests of Hardy–Weinberg equilibrium: Hardy–Weinberg equilibrium in cases and controls or in controls only is considered as a quality control measure for genotyping, or deviation of Hardy–Weinberg equilibrium is seen to be consistent with some disease models and therefore of use in fine-mapping of susceptibility loci (for extensive discussion and examples see Reference 49). On average 25–33% of genotyping errors for SNPs and 40–60% for microsatellites are detectable as Mendelian errors in trio families.50–52 Genotyping errors always lead to loss of power to detect a true effect and may in some instances increase false positive rates, especially leading to false-positive over-transmission of common alleles in TDT tests.51,53,54 Methods have been developed to allow for these effects in the analysis.53

56

Cytokine Gene Polymorphisms in Multifactorial Conditions

Missing data can also result in false positives, especially in the situation where a particular genotype is more likely to fail typing than others.26 Lower genotyping success rates for heterozygotes might, for example, occur with SNP genotyping technologies. Overall, genotyping success and error rates should be monitored and any associations observed for a marker with low genotyping success and/or high error rates should be treated with caution. 3.3.4.3

Statistical Fluctuations Arising by Chance and Multiple Testing Issues

For the null hypothesis that a specific gene is not associated with a specific disease, a significance level of 0.05 means that once in every 20 repeated experiments the null hypothesis would be rejected, i.e. the gene would be found to have an effect on disease, by chance only (Type I error or likelihood of obtaining a false positive result). If the same null hypothesis is actually verified through multiple tests, e.g. in several stratified subsets of the study population or through typing several variants in the same study population, the likelihood of wrongly concluding that the gene has in some way an effect on disease becomes inflated. The probability of observing at least one Type I error among n independent multiple tests, each with significance level a is 1  (1  a)n. For five or ten independent tests, each at a significance level of 0.05, the overall false positive likelihood amounts to 0.22 or 0.40, respectively. A much applied method to adjust the significance level for each of the multiple tests in such a way that the overall experiment-wise Type I error remains 0.05 is Bonferroni correction. The significance level is adjusted to 1  (1  a)1/n, which is for small values of a equivalent to a/n. Alternatively, instead of lowering the a level the observed P value may be increased according to 1  (1  P)n or, for small P values, nP. When multiple tests are partly dependent, such as for several variants in a gene that are in linkage disequilibrium with each other, applying this formula would result in over-correction. Two approaches were developed to handle this issue. One is a simple method that calculates the appropriate correction factor for multiple testing of several neighboring SNPs taking into account the degree of non-independence (http://genepi.qimr.edu.au/general/daleN/SNPSpD/).55 The other is the false discovery rate (FDR) developed by Benjamini and colleagues56 and extended for more complex situations by Storey et al.57 Permutation or bootstrap methods can also incorporate and thereby account for multiple hypothesis testing. All adjustment methods show, however, that while controlling the Type I error (false positive rate), at the same time they increase the Type II error, i.e. the likelihood of not detecting a true effect. This is all the more problematic for studies with modest power. It remains an issue of ongoing debate how to find an optimal equilibrium between these two concerns. 3.3.4.4

Sample Sizes for Detection and Replication

The power to detect a true genetic effect depends on the allele frequency of the variant, its effect size, its interaction with non-genetic risk factors, the sample size for study, and the nominal or multiple testing-adjusted significance level applied. A more detailed overview with illustrations can be found in References 20 and 21. For association studies, a commonly used measure of effect size is the odds ratio (OR) or genotype relative risk (GRR or g). These measures estimate the ratio of the risk for carriers of a disease-associated allele (or homozygotes or heterozygotes) versus the risk for non-carriers. It should be noted, however, that estimates based on a single positive study tend to be heavily biased upwards compared to the real effect size,16 as observed indeed in metaanalyses of association studies where the odds ratio for the first positive study frequently exceeds the genetic effect estimated by subsequent work and meta-analysis.58,59 For the small

Statistical Approaches to Analysis of Polymorphisms in Multifactorial Conditions

57

to modest effect sizes in multifactorial conditions, power of most studies is incomplete. Detection of a true effect therefore depends to some extent upon chance, and in a ‘‘lucky’’ experiment, the effect size is likely to have been at the extreme end due to sampling variations.16 Publication bias towards studies with significant results further contributes to these biased effect sizes in the literature. The implication of this phenomenon is that using the overestimated effect sizes as input values for sample size calculations for replication studies will often lead to underpowered studies, suggested to be a frequent cause of replication failure.16,58,59

3.4 ADMIXTURE MAPPING A novel and specific approach that is being developed and that is different from both linkage and linkage-disequilibrium based methods is admixture mapping (for review see Reference 60). This is the ancestry-based mapping of trait loci when the frequency of a trait differs between two human populations, and a third admixed population exists that contains genetic contributions from both parental populations. The hypothesis is that in affected individuals from the admixed population, the proportion of the ancestral DNA that is associated with greater prevalence of the trait is shifted upwards, and that those genomic segments with higher than expected high-prevalence ancestry are likely to harbor disease-risk loci. The ancestry of any genomic segment can be predicted from the small subset of SNPs that have significantly different allele frequencies in different human populations (ancestryinformative SNPs). For populations that have been admixed only relatively recently, such as the African-American population with less than 20 generations since admixture of European and African ancestry, recombination has not had much opportunity yet to reshuffle chromosomes. The genomes of African Americans are therefore mosaics of large segments of DNA of either European or African ancestry and only relatively few SNPs are required to screen the whole genome.61 A first-generation admixture map with ca. 2000 ancestry-informative SNPs has been designed for the study of this population.62 Thus, whereas admixture mapping has higher power than linkage methods, it needs much less markers than whole-genome association screening. Any identified regions of diseaseassociated ancestry will, however, likely be relatively large and will therefore need follow-up with classical association methods. A first real-life example is a scan for hypertension genes in African Americans. The distribution of marker-specific African ancestry was shifted upwards in hypertensive versus normotensive individuals, consistent with the higher prevalence of hypertension in Africans. This shift was largely due to a small number of chromosomal regions, which may contain genes influencing risk of hypertension in Africans and African Americans.63

REFERENCES 1. Iafrate, A. J. et al., Detection of large-scale variation in the human genome, Nat. Genet., 36, 949, 2004. 2. Sebat, J. et al., Large-scale copy number polymorphism in the human genome, Science, 305, 525, 2004. 3. Carter, N. P., As normal as normal can be?, Nat. Genet., 36, 931, 2004. 4. Tuzun, E. et al., Fine-scale structural variation of the human genome, Nat. Genet., 2005. 5. Sachidanandam, R. et al., A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms, Nature, 409, 928, 2001. 6. Reich, D. E. et al., Human genome sequence variation and the influence of gene history, mutation and recombination, Nat. Genet., 32, 135, 2002.

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Cytokine Gene Polymorphisms in Multifactorial Conditions 7. Sawcer, S. J. et al., Enhancing linkage analysis of complex disorders: an evaluation of high-density genotyping, Hum. Mol. Genet., 13, 1943, 2004. 8. Abecasis, G. R., Cherny, S. S., and Cardon, L. R., The impact of genotyping error on family-based analysis of quantitative traits, Eur. J. Hum. Genet., 9, 130, 2001. 9. John, S. et al., Whole-genome scan, in a complex disease, using 11,245 single-nucleotide polymorphisms: comparison with microsatellites, Am. J. Hum. Genet., 75, 54, 2004. 10. Middleton, F. A. et al., Genomewide linkage analysis of bipolar disorder by use of a high-density single-nucleotide-polymorphism (SNP) genotyping assay: a comparison with microsatellite marker assays and finding of significant linkage to chromosome 6q22, Am. J. Hum. Genet., 74, 886, 2004. 11. Evans, D. M. and Cardon, L. R., Guidelines for genotyping in genomewide linkage studies: single-nucleotide-polymorphism maps versus microsatellite maps, Am. J. Hum. Genet., 75, 687, 2004. 12. Schaid, D. J. et al., Comparison of microsatellites versus single-nucleotide polymorphisms in a genome linkage screen for prostate cancer-susceptibility Loci, Am. J. Hum. Genet., 75, 948, 2004. 13. Morton, N. E., Significance levels in complex inheritance, Am. J. Hum. Genet., 62, 690, 1998. 14. Risch, N., Linkage strategies for genetically complex traits, Am. J. Hum. Genet., 46, 222, 1990. 15. Risch, N., Assessing the role of HLA-linked and unlinked determinants of disease, Am. J. Hum. Genet., 40, 1, 1987. 16. Terwilliger, J. D. et al., A bias-ed assessment of the use of SNPs in human complex traits, Curr. Opin. Genet. Dev., 12, 726, 2002. 17. Rybicki, B. A. and Elston, R. C., The relationship between the sibling recurrence-risk ratio and genotype relative risk, Am. J. Hum. Genet., 66, 593, 2000. 18. Hugot, J. P. et al., Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn’s disease, Nature, 411, 599, 2001. 19. Rioux, J. D. et al., Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease, Nat. Genet., 29, 223, 2001. 20. Risch, N. J., Searching for genetic determinants in the new millennium, Nature, 405, 847, 2000. 21. Wang, W. Y. et al., Genome-wide association studies: theoretical and practical concerns, Nat. Rev. Genet., 6, 109, 2005. 22. Altshuler, D. et al., The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes, Nat. Genet., 26, 76, 2000. 23. Falk, C. T. and Rubinstein, P., Haplotype relative risks: an easy reliable way to construct a proper control sample for risk calculations, Ann. Hum. Genet., 51 (Pt 3), 227, 1987. 24. Thomson, G., Mapping disease genes: family-based association studies, Am. J. Hum. Genet., 57, 487, 1995. 25. Spielman, R. S., McGinnis, R. E. and Ewens, W. J., Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM), Am. J. Hum. Genet., 52, 506, 1993. 26. Hirschhorn, J. N. and Daly, M. J., Genome-wide association studies for common diseases and complex traits, Nat. Rev. Genet., 6, 95, 2005. 27. Gabriel, S. B. et al., The structure of haplotype blocks in the human genome, Science, 296, 2225, 2002. 28. Zondervan, K. T. and Cardon, L. R., The complex interplay among factors that influence allelic association, Nat. Rev. Genet., 5, 89, 2004. 29. Ardlie, K. G., Kruglyak, L. and Seielstad, M., Patterns of linkage disequilibrium in the human genome, Nat. Rev. Genet., 3, 299, 2002. 30. Carlson, C. S. et al., Selecting a maximally informative set of single-nucleotide polymorphisms for association analysis using linkage disequilibrium, Am. J. Hum. Genet., 74, 106, 2004. 31. Thompson, D. et al., Haplotype tagging single nucleotide polymorphisms and association studies, Hum. Hered., 56, 48, 2003. 32. Vermeire, S. et al., CARD15 genetic variation in a Quebec population: prevalence, genotype– phenotype relationship, and haplotype structure, Am. J. Hum. Genet., 71, 74, 2002.

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33. Toivonen, H. T. et al., Data mining applied to linkage disequilibrium mapping, Am. J. Hum. Genet., 67, 133, 2000. 34. Laitinen, T. et al., Characterization of a common susceptibility locus for asthma-related traits, Science, 304, 300, 2004. 35. Fallin, D. and Schork, N. J., Accuracy of haplotype frequency estimation for biallelic loci, via the expectation-maximization algorithm for unphased diploid genotype data, Am. J. Hum. Genet., 67, 947, 2000. 36. Bottini, N. et al., A functional variant of lymphoid tyrosine phosphatase is associated with type I diabetes, Nat. Genet., 36, 337, 2004. 37. Begovich, A. B. et al., A missense single-nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis, Am. J. Hum. Genet., 75, 330, 2004. 38. Kyogoku, C. et al., Genetic association of the R620W polymorphism of protein tyrosine phosphatase PTPN22 with human SLE, Am. J. Hum. Genet., 75, 504, 2004. 39. Smyth, D. et al., Replication of an association between the lymphoid tyrosine phosphatase locus (LYP/PTPN22) with type 1 diabetes, and evidence for its role as a general autoimmunity locus, Diabetes, 53, 3020, 2004. 40. Thomas, D. C., Haile, R. W. and Duggan, D., Recent developments in genomewide association scans: a workshop summary and review, Am. J. Hum. Genet., 77, 337, 2005. 41. Klein, R. J. et al., Complement factor H polymorphism in age-related macular degeneration, Science, 308, 385, 2005. 42. Maraganore, D. M. et al., High-resolution whole-genome association study of Parkinson’s Disease, Am. J. Hum. Genet., 77, 685, 2005. 43. Tabor, H. K., Risch, N. J., and Myers, R. M., Opinion: Candidate-gene approaches for studying complex genetic traits: practical considerations, Nat. Rev. Genet., 3, 391, 2002. 44. Ardlie, K. G., Lunetta, K. L., and Seielstad, M., Testing for population subdivision and association in four case-control studies, Am. J. Hum. Genet., 71, 304, 2002. 45. Helgason, A. et al., An Icelandic example of the impact of population structure on association studies, Nat. Genet., 37, 90, 2005. 46. Stefansson, H. et al., A common inversion under selection in Europeans, Nat. Genet., 37, 129, 2005. 47. Devlin, B., and Roeder, K., Genomic control for association studies, Biometrics, 55, 997, 1999. 48. Pritchard, J. K. and Rosenberg, N. A., Use of unlinked genetic markers to detect population stratification in association studies, Am. J. Hum. Genet., 65, 220, 1999. 49. Wittke-Thompson, J. K., Pluzhnikov, A., and Cox, N. J., Rational Inferences about Departures from Hardy-Weinberg Equilibrium, Am. J. Hum. Genet., 76, 967, 2005. 50. Gordon, D., Heath, S. C. and Ott, J., True pedigree errors more frequent than apparent errors for single nucleotide polymorphisms, Hum. Hered., 49, 65, 1999. 51. Mitchell, A. A., Cutler, D. J. and Chakravarti, A., Undetected genotyping errors cause apparent overtransmission of common alleles in the transmission/disequilibrium test, Am. J. Hum. Genet., 72, 598, 2003. 52. Abecasis, G. R. et al., Merlin – rapid analysis of dense genetic maps using sparse gene flow trees, Nat. Genet., 30, 97, 2002. 53. Gordon, D. et al., A transmission disequilibrium test for general pedigrees that is robust to the presence of random genotyping errors and any number of untyped parents, Eur. J. Hum. Genet., 12, 752, 2004. 54. Kang, S. J. et al., Quantifying the percent increase in minimum sample size for SNP genotyping errors in genetic model-based association studies, Hum. Hered., 58, 139, 2004. 55. Nyholt, D. R., A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other, Am. J. Hum. Genet., 74, 765, 2004. 56. Benjamini, Y. and Hochberg, Y., Controlling the false discovery rate: a practical and powerful approach to multiple testing, J. Royal Stat. Soc. Ser. B, 57, 289, 1995. 57. Storey, J. D. and Tibshirani, R., Statistical significance for genomewide studies, Proc. Natl. Acad. Sci. USA, 100, 9440, 2003.

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Cytokine Gene Polymorphisms in Multifactorial Conditions 58. Ioannidis, J. P. et al., Replication validity of genetic association studies, Nat. Genet., 29, 306, 2001. 59. Lohmueller, K. E. et al., Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease, Nat. Genet., 33, 177, 2003. 60. Hafler, D. A. and De Jager, P. L., Applying a new generation of genetic maps to understand human inflammatory disease, Nat. Rev. Immunol., 5, 83, 2005. 61. Patterson, N. et al., Methods for high-density admixture mapping of disease genes, Am. J. Hum. Genet., 74, 979, 2004. 62. Smith, M. W. et al., A high-density admixture map for disease gene discovery in African Americans, Am. J. Hum. Genet., 74, 1001, 2004. 63. Zhu, X. et al., Admixture mapping for hypertension loci with genome-scan markers, Nat. Genet., 37, 177, 2005.

4

Introduction to Integrated Bioinformatic Resources for Cytokine Genetics Research Ross Lazarus

CONTENTS 4.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.1.1 Unprecedented Opportunity; Novel Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.1.2 Integrative Bioinformatic Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.1.3 Challenges Facing Biologists and Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.1.4 Assumptions and Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.2 Fundamental Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.2.1 Specific Resource Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.2.1.1 Sequence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.2.1.2 Annotation and Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.2.1.3 Protein Structure and Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 4.2.1.4 Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 4.2.2 Navigation and Presentation Metaphors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 4.2.2.1 Navigation and Content Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 4.2.2.2 Presentation Metaphors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 4.2.3 Simple Text Search and Direct Sequence Navigation . . . . . . . . . . . . . . . . . . . . . . 66 4.2.4 Learning How to Use Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 4.3 Integrative Bioinformatic Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 4.3.1 UCSC Bioinformatics (Golden Path) — http://genome.ucsc.edu. . . . . . . . . . . . 66 4.3.1.1 Learning to Use It . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.3.1.2 Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.3.1.3 Navigation Tips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.3.1.4 Typical Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.3.2 NCBI — http://www.ncbi.nlm.nih.gov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.3.2.1 Learning to Use It . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.3.2.2 Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.3.2.3 Navigation Tips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.3.2.4 Typical Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.3.3 Ensembl: http://ensembl.org . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.3.3.1 Learning to Use It . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.3.3.2 Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.3.3.3 Navigation Tips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.3.3.4 Typical Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.3.4 SNPper: http://snpper.chip.org . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.3.4.1 Learning to Use It . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.3.4.2 Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 61

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4.3.4.3 Navigation Tips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.3.4.4 Typical Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 4.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Acknowledgments 72 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

4.1 4.1.1

INTRODUCTION UNPRECEDENTED OPPORTUNITY; NOVEL CHALLENGES

In terms of access to genetic and genomic data, we live in a time of extraordinary opportunity, literally awash in a rich flood of genomic data. The complete genomic sequences of a widening range of organisms, together with detailed annotation describing genomic features, are pouring out of large, publicly funded projects. These projects make all of their data freely available through the internet. Interested scientists can use freely available tools to explore it and apply it to their own work. For most scientists, this richness of data presents a new challenge. It is almost impossible to keep up with the rate at which new data and new ways of accessing it appear on the information landscape. In theory, access is free and readily available through the public internet, but in practice may be limited either because the potential user is not aware of the existence, extent, or applicability of the material available, or because the basic skills required to make use of the resources have not yet been acquired. One key to gaining access and making good use of these new resources lies in making the best possible use of bioinformatic tools which have been purpose built to provide integrated access to multiple large-scale genomic resources. While the discipline is yet relatively young, and continues to evolve rapidly, bioinformatics may be informally and very generally defined as the art and science of adding value to biological data. In practice, bioinformatics is an eclectic and opportunistic discipline, applying combinations of elements, often taken from mathematics, statistics, computer science, information science, but potentially from other disciplines, to solve interesting problems which arise in biological research. Scientists who wish to make contributions in bioinformatics must be well grounded in all the contributing disciplines. Fortunately, in many cases, the fruits of their labors can be enjoyed without acquiring all of the skills needed to be a bioinformatician. Many well designed tools which are well documented and easy to use are available for biologists needing access to genetic and genomic data. The purpose of this chapter is to provide a brief introduction to four of these important resources, with emphasis on research tasks relevant to cytokine genetics.

4.1.2

INTEGRATIVE BIOINFORMATIC RESOURCES

Like organisms, bioinformatic and genomic resources compete to undergo rapid growth after birth. Initially, they often arise as highly specialized databases focussed on some relatively confined topic, growing in depth as more information is added. Many of these databases are complex, and historically, most evolved such byzantine user interfaces, that it takes considerable time and effort to learn to use them effectively. It soon became increasingly clear to the bioinformatic community that these individual resources were underused because very few biologists could afford the time to familiarize themselves with the arcane interface associated with each individual resource. The idea of amalgamating many individual resources into an integrated whole was the obvious solution and a great deal of progress has been made in this regard, fortuitously supported by the increasingly ubiquitous internet and web browser.

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For many common tasks in cytokine genetics, it is helpful to be able to combine data from more than one of these highly specialized resources and view them as an integrated whole. Integrative bioinformatic resources are the subject of this chapter because they are generally the most widely applicable. It is possible to make good use of the best of these integrated resources without needing to know much about the many underlying distinct databases. Learning to use one or two of the major integrative bioinformatic resources will add powerful new tools and vast quantities of data to any biologist’s armamentarium.

4.1.3 CHALLENGES FACING BIOLOGISTS AUTHORS

AND

Two major hurdles for most biologists are (1) locating appropriate tools and (2) learning how to use them. For the author, it would be futile to try to cover every available bioinformatic resource here, because it would require more text than can fit into this modest space, and because the bioinformatic landscape is changing so rapidly that any complete survey is outdated by the time it is complete. So, this chapter will briefly introduce some important tools and resources, and more importantly, offer some introductory advice about learning how to use them. All of the resources described here have extensive and excellent support for learning how to make use of them — user guides, frequently asked questions and tutorials. While this chapter will help the reader learn to use each resource, the main emphasis is on techniques which can make learning easier, so the reader is advised to concentrate on the meta-task of learning how to teach themselves, while following the text.

4.1.4 ASSUMPTIONS

AND

SCOPE

The reader is assumed to have access to a computer with a reliable connection to the internet, since all of the major bioinformatic resources are readily accessed over the public internet. Basic skills and experience with almost any recent web browser (such as Firefox or Netscape) installed on the computer are also required, since all of the tools described here are designed to be used through an ordinary web browser. Readers lacking these basic skills are advised to ask computer-savvy co-workers for assistance. Most adolescents and many children are an excellent resource for advice on using the internet, and they are often happy to teach these skills. Saving internet locations as bookmarks and organizing those bookmarks into groups is a very useful skill. If you need help, you should ask your coworkers, because it saves having to retype long, error-prone internet addresses: Make a bookmark the first time you visit a useful site and organize your bookmarks into groups which suit the way you work. Finally, it is assumed that the reader is willing to take risks and try things out when working with web-based bioinformatic resources. All of the resources described here are extremely robust and are unlikely to break, no matter what a user does using an ordinary web browser. Readers should feel free (or perhaps even obliged) to try different strategies in order to discover which ones work. Playfullness is an important ingredient in a successful learning strategy, particularly when combined with judicious use of the many on-line tutorials, examples, and guides which all of these resources offer. This chapter will introduce three relatively well-known resources (NCBI Entrez, the UCSC genome browser, and Ensemble), together with one very useful but less well known resource called SNPper. All of these resources integrate multiple sources of data in different ways and each has its own strengths. While they share the same underlying data in many cases, they have different models of integration, different ways of presenting data, and different interfaces. The wise researcher will explore each of them and learn which of them suits the specific needs they have in their work.

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FUNDAMENTAL CONCEPTS

Three distinct sets of concepts are outlined below. These may help make best use of integrative bioinformatic tools. The first is a simple classification of genetic and genomic information, which while neither complete nor necessarily ideal, is useful as a starting point. The second set of concepts describes the presentation layer and the navigational metaphors through which these different resource types are offered to the user. The third concept concerns searching. Quickly locating information on a specific topic in genetics and genomics is a ‘‘needle in a haystack’’ problem. Efficient searching for features such as genes, or for information about a complex concept such as a specific disease is a fundamental skill which all biologists are likely to find useful.

4.2.1

SPECIFIC RESOURCE TYPES

Genomic and genetic resources applicable to cytokine research can be classified into broad classes: 4.2.1.1

Sequence

The physical arrangement of nucleotides, one after another, like beads on a string along a single chromosome strand, is termed a sequence. Chromosomes may comprise hundreds of millions of nucleotides, but sequences are usually obtained in relatively short fragments of a few hundred nucleotides each. If multiple sequence fragments from an organism overlap, it may be possible to combine them into a larger sequence fragment in a process termed assembly. When enough sequence fragments can be unambiguously assembled, a whole chromosome can be completely characterized. This linear arrangement lends itself to mapping onto a linear coordinate system. Nucleotides are conventionally counted starting from the distal end or telomere of the short arm of each chromosome. The position of any specific nucleotide base can then be uniquely identified in chromosome absolute coordinates. Given this coordinate system, it is possible to uniquely map any genomic feature such as a polymorphism or a gene. An international consortium contributes to and maintains a shared database of nucleotide sequences called GenBank,1 which currently contains sequences from more than 130 000 organisms. Many genomes, including human, have been completely assembled. Release 149 (August 2005) passed a major milestone in terms of volume, exceeding 100 Gigabases of total sequence.2 All of this data is freely downloadable, requiring roughly 195 Gb of uncompressed storage for the sequence and annotation. This is twice the size of the February 2004 release,3 and the count of nucleotides in GenBank appears to be growing exponentially.4 Presenting so much data in a simple way is a substantial technical and ergonomic challenge. 4.2.1.2

Annotation and Mapping

Establishing the sequence of nucleotides is important, but is only a preliminary step. There are many larger, more complex, and interesting biological features such as common genetic variations including single nucleotide polymorphisms (SNPs), regions which encode proteins (genes), regions of low complexity, and regulatory elements involved in the control of gene expression. Identifying the genomic coordinates of individual features is sometimes termed mapping and information describing genomic features which exist in a given sequence is usually referred to as annotation. Many of the genomes in GenBank have been annotated with the position and layout of genes and other important higher level features. This is equivalent to saying that many features have been mapped onto GenBank reference sequences. Since there are many types of annotation and since many annotations are related (e.g. common variation in relation to coding regions of genes), it is very useful to be able to

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combine multiple annotations onto a given piece of sequence. Most of the resources described in this chapter provide specialized viewers which allow annotations to be superimposed on the basic, linear genomic scaffold. 4.2.1.3

Protein Structure and Function

The proteins encoded in genes are of fundamental biological importance, so numerous specialized bioinformatic resources containing physical, chemical, physiological, and other biological data on proteins are available. Some of these focus on amino acid sequence, others on function and on structure. Again, it is often very useful if this detail can be seen in the genomic context, particularly if the potential effects of genetic variation on protein regulation, structure, and function is of interest, as is the case with cytokine genetics. 4.2.1.4

Literature

While it may seem odd to consider published literature as a genomic resource, it is arguably a fundamental ingredient for good science. The best-known repository of peer reviewed literature is the NLM PubMed database. A less widely appreciated and more specialized human genetic resource is the NLM Online Mendelian Inheritance in Man (OMIM) database. OMIM is an unusual bioinformatic resource, because each entry is maintained by a team of content experts who regularly update the material to keep the database as current as possible. OMIM is the online version of the text book originally published as Mendelian Inheritance in Man, and now includes information on complex diseases such as asthma and diabetes, as well as the rarer Mendelian disorders which were the original focus. OMIM references are given as direct hyperlinks into PubMed, making it very convenient to quickly locate relevant published research.

4.2.2 NAVIGATION

AND

PRESENTATION METAPHORS

The explosive growth of the internet is at least partially attributable to the widespread adoption of a remarkably simple idea — the hyperlink. A hyperlink is a unique internet address (more formally, a uniform resource locator or URL) attached to an image or text link. When selected with a mouse click, the hyperlink instructs the browser to download and display the content hosted at that web address, effectively linking the two documents. Originally introduced by Tim Berners-Lee and colleagues at CERN in 1990 to help make complex documentation more easy to navigate, the hyperlink now forms a basic metaphor for the internet as we know it. An ordinary web browser on an internet connected computer gives access to all of the world’s major genomic internet resources, including relevant documentation and user tutorials to help users learn to use them efficiently. 4.2.2.1

Navigation and Content Control

There are three fundamental control conventions which are widely used in bioinformatic resources. Navigating a linear genomic sequence is fundamental to most of the bioinformatic resources described below and this is often controlled using a hyperlinked arrow pointing to the left and right at the start and end of the displayed sequence respectively. This directional model is an easy to grasp navigational metaphor for shifting the field of view along the sequence. Zooming the scale of view in to see finer features or zooming out to expand the length of sequence to see more of the local context, are also widely used navigational metaphors, often available through appropriately hyper-linked plus (zoom in — more detail) and minus (zoom out — more context) signs. When there are many optional annotation elements available for display, check boxes or select lists controlling which annotations are displayed, and in how much detail, are widely

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used metaphors, giving the user control over the amount of additional detail visible within a region to suit the task at hand. 4.2.2.2

Presentation Metaphors

Once these basic navigational and control elements are understood, the idea of a specialized genomic browser, controlled through readily available web browser software, becomes a remarkably flexible and powerful metaphor. Potentially overwhelming complexity can be easily controlled to suit the user’s needs with just a few mouse clicks, permitting an almost infinite number of possible configurations to be offered through a relatively simple, widely available interface between the user and the resource.

4.2.3

SIMPLE TEXT SEARCH NAVIGATION

AND

DIRECT SEQUENCE

Searching a vast repository of data by locating all the text in which there is a partial match to a user supplied text search term (such as a gene name ‘‘IL10’’ or a disease name like ‘‘asthma’’) is a simple, powerful and useful strategy. Although lacking in specificity, it is usually a very good starting place. The addition of Boolean logic can then be used to narrow the results (e.g. ‘‘asthma’’ AND ‘‘SNP’’) to the intersection of two sets of results. All of the resources described below offer a prominent ‘‘search bar’’ where the user can enter one or more words as search terms, and a ‘‘search’’ button which will initiate the search, returning all matches in some navigable form to the user. The default Boolean connector for multiple terms is usually AND, so the resulting search will generally be narrower (by intersection) for each additional search term. The specific genome browsers described below also offer a direct sequence navigation method which is a specialized version of a text search — direct navigation to a specific genomic location or region by nominating the chromosome and the range of linear coordinates — for example when using the May 2004 build of the human genome, ‘‘chr1:203,329,342–203,334,205’’ entered into the UCSC browser search bar will navigate directly to the IL10 gene. Note that the actual linear coordinates of any specific feature may change between builds, as the accuracy of the finished assembly improves over time.

4.2.4

LEARNING HOW

TO

USE RESOURCES

The major resources described here have extensive documentation for users available on-line. In many cases, help is available within each specific context. In other cases, there are tutorials which step through specific tasks, guides which summarize the basic features and operation, frequently asked questions (FAQ) which provide answers to the sorts of questions new and experienced users tend to ask, and other types of self-study material. There is always an email address available for help, but this should only be used as a last resort, since the resource is almost always limited because it is expensive to maintain. Users should make every effort to figure things out by using the on-line resources wherever possible, asking more experienced colleagues for help, or attending formal teaching sessions if these are available.

4.3 4.3.1

INTEGRATIVE BIOINFORMATIC RESOURCES UCSC BIOINFORMATICS (GOLDEN PATH) — http://genome.ucsc.edu

The Genome Bioinformatics Group of the University of California, Santa Cruz maintain the UCSC assembly and an extremely easy-to-use and configurable genome and annotation

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browser, sometimes known as the Golden Path. It is an excellent gateway for many tasks and is relatively easy to learn to navigate. The default display is generally useful but most of the power and flexibility of the browser is revealed by learning how to configure the display by changing the default tracks and their level of detail. 4.3.1.1

Learning to Use It

The UCSC home page has a link labeled FAQ (Frequently Asked Questions) at the far right of the horizontal navigation bar near the top of the screen. This links to an introductory overview describing the main features of the browser and a long list of annotation track descriptions. Far more extensive learning support materials are available from the Training link toward the end of the vertical navigation bar on the right side of the home page. These materials include a 3 hour slide presentation, a pre-recorded tutorial (requires Flash browser plug-in), and information about regional live training sessions. When using the browser, all the available annotation tracks are grouped into classes below the main browser section, and each track has a name label which is a hyperlink to a brief explanatory page describing the annotation and the levels of detail available. When annotation track settings are changed, the browser must be ‘‘refreshed’’ before the new settings will appear. 4.3.1.2

Resources

There are multiple assemblies of multiple organisms available for browsing and these are selected from the initial Genome Browser screen. For example, the default settings are to the latest available human assembly, but this can be changed to an earlier assembly or to another organism using the drop down lists. Once a genome and region are selected, the window showing the current genomic context also displays multiple user-selected annotations. A series of options below the main window control this annotation display, both in terms of scope and detail. The UCSC browser uses the term tracks for different types of annotation. For example, SNPs are displayed as annotation in the main window, with a detail level selected using a drop down list in the Variation section of track categories. Setting this level to hide causes no SNPs to be displayed; full displays each one individually as a hyperlink to a detail record and dbSNP, the main NCBI (see below) SNP database repository. The UCSC genome browser allows users to publish their own annotation tracks for features they have a particular interest in. In addition, UCSC offer a variety of other valuable tools, including a genome search engine optimized for relatively short sequences (Blat) and electronic PCR for locating the genomic region amplified by a pair of primers. 4.3.1.3

Navigation Tips

The main genome browser is available from the UCSC home page by selecting it from the link labeled Genome Browser toward the top of the right-sided vertical navigation bar. This opens a page which allows the default genome to be changed and to specify a specific region or feature. Some examples of specifying a region or feature are listed below the search bar. Opening a browser screen at a specific feature or genomic location is very easy — for example, it is possible to navigate directly to a gene by typing the HUGO symbol for the gene (e.g. TLR10) into a text box. This often leads to more than one match, typically when there are multiple isoforms or multiple sequences for the same gene. Selecting the most appropriate match will open a genome browser page. More ambiguous searches (e.g., try interleukin) will return a page showing a very long list all of the potential matches to that text term, each of which is a hyperlink to one specific match. Selecting any single

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feature (such as a gene) on the browser display leads to a page on that feature with many additional details and links to offsite resources. While viewing any specific region, the user can interactively control the position (left and right arrows will move the browser window in the 50 and 30 directions respectively) and scale (the window zoom level can be set explicitly or choosing the various zoom scale factors). Additional genomic features or annotations can be included or excluded from the view by selecting from the long and initially bewildering list of potential annotation tracks or features listed below the main browser window. Tracks include phylogenetic conservation, low complexity regions, genes, gene expression, and SNPs. Users can add external annotation sources and even share their own specialized annotations. After changing the track set-up, selecting the refresh button will display the new configuration. 4.3.1.4

Typical Uses

Quickly identifying tissues in which a gene is up- or down-regulated is sometimes helpful in planning research. While viewing a gene such as IL10, scroll down to the Expression and regulation section of the annotation track list. Choose full from the GNF Atlas 2 track and then select the refresh button. The browser will display a long list of tissues with colored bars indicating expression levels in that tissue. Finding neighboring genes is easily accomplished using the zoom facility. While viewing IL10, repeatedly zooming out until the genomic display shows about 200 kb total (note the size label on the position line above the browser window as the zoom buttons are clicked) reveals IL19 to be the nearest gene 30 (the genome is usually displayed with the 30 direction on the left with increasing linear coordinates) to IL10.

4.3.2

NCBI — http://www.ncbi.nlm.nih.gov

The National Center for Biotechnology Information (NCBI) web site integrates a wide range of important, individual databases. Although many of these have their own specialized web interfaces, they are merged into a consistent framework through a unified user interface and search engine. The page which appears when a web browser is directed to the internet address above (http://www.ncbi.nlm.nih.gov) offers a wide range of links, including, most importantly for first time visitors and near the left side of the page at present, an Education link which leads to courses, and free user self-instruction guides. This same page permits site-wide searches. Visitors perform a simple text match search of all NCBI databases by typing a search term into the search bar toward the top of the page, and activating the button labeled ‘‘Go’’. The search engine is an integrative gateway through which all major NCBI bioinformatic resources can be accessed quickly and easily. Less experienced visitors can find their way with a simple text search, while more experienced users can quickly access specific information using more sophisticated search strategies and techniques. Entrez is an alternative, less cluttered interface for more experienced users (http://www.ncbi.nlm.nih.gov/gquery/gquery.fcgi). 4.3.2.1

Learning to Use It

There is a link to ‘‘Education’’ toward the bottom of the navigation bar at the right side of the main page (http://www.ncbi.nlm.nih.gov/Education/). This page contains a large number of resources, designed to help users make better uses of the NCBI data and tools. The Entrez and PubMed tutorials are very good places to start.

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Resources

There is very little widely applicable data missing from the NCBI site, so it is a very useful resource for every day tasks in cytokine genetics. The peer-reviewed literature databases PubMed and PubMed Central (the free access citations) are available through the NCBI web site. It also offers genomes from a growing variety of organisms and a wide array of annotations, all integrated through a single search engine. 4.3.2.3

Navigation Tips

A simple partial match text search is described in more detail below. Most search and results pages also offer lists of potentially useful and important links (including help and tutorials) on the navigation bar on the left side of the browser screen. Links to major NCBI resources are arranged horizontally, near the top of the page where the search bar is located. Note that the default NCBI page has All Databases showing in the resource selector box to the left of the text search term entry box. A search will match the text term against all major NCBI resources. When a more specific search is required, select a specialized database. When a full search is performed, a summary of the matching text ‘‘hits’’ is presented in a neatly organized results page. The search result page offers direct links to each resource where the appropriate result set will be displayed in a specific way to suit each specific resource. 4.3.2.4

Typical Uses

The main NCBI search page is a very good place to start for almost any genetic research project. A simple text search for ‘‘IL10’’ for example, will result in an Entrez page, where the search result summary is shown in groups of related NCBI resources. The first two links at the top left are to PubMed and PubMedCentral. PubMed is the central literature database and PubMedCentral is a smaller collection of freely accessible literature, where the entire published article is available at no cost. One interesting link is labelled SNP, a link into dbSNP which contains information about single nucleotide polymorphisms which are found in the gene IL10. An alternative resource for SNP related data is described below.

4.3.3 ENSEMBL – http://ensembl.org Ensembl is a web-based genome and annotation browser for genomes, jointly maintained by the European Molecular Biology Laboratory and the Sanger Institute. The Ensembl interface is extensive and complex, but a simple exact match text search bar is immediately available from the top of the main Ensembl page at http://www.ensembl.org. There are an enormous and growing number of annotation sources available. Users can share their own annotations using the Distributed Annotation System (DAS — see http://biodas.org/). In the Ensembl browser, Features and DAS tracks are the equivalent of the annotation tracks available in the UCSC browser — they can be turned on and off to suit the task and context. 4.3.3.1

Learning to Use It

The main page has a section entitled ‘‘Help and Documentation’’ with links to guided tours, tutorials, and worked examples. Help is available for the deeper layers of complexity from the relevant pages using the ‘‘Help’’ button. The May 2004 edition of Genome Research (Genome Research 14(5): 925–995) included a number of papers on Ensembl which are available on-line from the home page under the Help and Documentation section. Detailed and context specific help are available from Help links on nearly every Ensembl screen. Often, when the mouse pointer is over a displayed feature, it will indicate a link by changing

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from a pointer to a hand — clicking these links will display a small pop-up window, usually with links to more details about the feature. 4.3.3.2

Resources

At the time of writing, 18 complete or partial genomes are available in the Ensembl browser, either individually or, in some situations, for comparison. The browser integrates most of the same data as is available from the UCSC or NCBI browsers. It includes a genome assembly for each genome, with a wide range of annotations, many from the same sources as the other browsers, but in a different way which may or may not suit different researchers and different tasks. 4.3.3.3

Navigation Tips

From the home page, select the Human link under the Species list on the right side of the screen. The page has a text search (try IL10) and a direct chromosome/position navigation option (both have ‘‘Lookup’’ buttons to perform the appropriate operation after text has been entered). The most important tip for using the Ensembl browser is that in the genome browser (Contig) mode, annotations are available from a series of drop-down lists (small downward pointing arrows indicate where these are) on the bar near the top of the ‘‘Detailed View’’ section of the screen. Clicking on any of the labels will drop down a series of checkboxes — selected checkbox items will be added to the browser view. For example, to view the SNP annotations, click the ‘‘Features’’ section of the bar and select the ‘‘SNPs’’ checkbox and click the ‘‘Refresh’’ button to redraw the browser screen (or click the ‘‘Close Menu’’ tag at the end of the drop-down list). A SNP track will now be added to the browser. Selecting any individual SNP will pop open a detail window for that SNP. 4.3.3.4

Typical Uses

The Genetic Association Database is a human curated source of published papers on human gene disease association (http://geneticassociationdb.nih.gov). The entire database is available as a DAS (see above) track which means that the GAD is effectively integrated as an annotation to any Ensembl browser window. From the main Ensembl page, try a simple text search for IL10. Select the Gene page for IL10, and check the GAS DAS box found midway down the page on the left side — a list of papers which refer to association between IL10 and human disease appears, with each paper linked directly into PubMed. Although the GAD is as yet far from complete, this is a very useful tool for reviewing a cytokine and is conveniently accessed through the Ensembl Gene page when needed. Note that any researcher can submit papers for inclusion in the GAD — clearly it will become more useful as more scientists contribute references they are familiar with to the resource.

4.3.4

SNPper – http://snpper.chip.org

SNPper is a specialized web-accessible bioinformatic resource which integrates some of the same data as the three genome browsers described above, but with very specialized and focussed functions. One major design goal was to support candidate gene-based SNP studies. In order to do this, it offers a gene-centric view of dbSNP, integrated with the UCSC genome assembly, together with many highly-specialized features, many of which make picking and managing a set of SNP for genotyping in a disease association study much easier than relying on multiple individual bioinformatic resources. SNPper is also a very handy tool for quickly finding all you need to know about a SNP given a reference SNP (rs) number (or a TSC SNP identifier), or for finding all the known SNPs in a particular gene. This information is

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available directly from the NCBI browser through dbSNP, but SNPper presents it in a way which suits many genomic research tasks. Note that SNPper is free, but requires a login for access to an individual storage space for saved search results. You can use SNPper as a guest user (look at the note on the main SNPper page), but if you make use of it regularly, registering is free and allows you to save your work for later re-use. It also helps the maintainer (Alberto Riva) to demonstrate that SNPper is a useful resource when it comes to grant funding or to notify users of upgrades. 4.3.4.1

Learning to Use It

SNPper has integrated help links on every page which lead to pithy but useful hints, and there is an ‘‘instructions’’ page linked from the main page (after login) which provides some general guidance, including a link to some papers on SNPper, one of which is a good starting point5 for understanding how it works. In general, SNPper is relatively easy to use, but it is far more specialized and does not have the same extensive documentation, tutorials, or user guides which some other, larger, and better–funded resources offer. ‘‘Try it and see’’ is the best way to learn how to use it, after first reading the help pages of course. Generally, SNPper does simple text searches to navigate to specific SNPs or to all the SNPs in and near a gene. Once a specific SNP or gene is found using a simple text search, SNPper displays links directly to additional details from other primary resource databases, including PubMed, LocusLink and OMIM. Having them all on one screen is very helpful for quickly assembling the basics for any specific gene and its SNPs. 4.3.4.2

Resources

SNPper integrates the most recent UCSC genome assembly with the release of dbSNP which UCSC integrated at the time. Because of its reliance on the UCSC, SNPper is sometimes a little out of date compared to the most recent dbSNP release, but this is a minor inconvenience compared to the benefits. SNPper also offers direct links to many of the primary resources such as SWISSProt and GenBank so they appear to be integrated seamlessly. 4.3.4.3

Navigation Tips

There are two main search methods. If you have a specific gene in mind such as IL10, then the Gene based view (find a gene by name, symbol, accession number, or position) will show all of the SNPs in dbSNP within the region of a gene. If you have a specific SNP in mind, then the SNP based view (find SNPs by name, position, or properties) will be more useful. These two views are available from the main SNPper page after log-in. To learn about all of the available SNPs in a specific candidate gene, use the gene view. To look up details for an rs number or The SNP Consortium (TSC) id from a manuscript or other source, use the SNP view. The gene view has several search options, depending on which text search box you use. The first searches HUGO symbols (e.g. IL10), the second searches part of a gene product name (e.g. interleukin), and the third searches common and widely used database identifiers (GenBank mRNA accession number, LocusLink, OMIM, Unigene, or Swissprot). 4.3.4.4

Typical Uses

Finding all known SNPs in a gene is a common task. A simple text search for gene names is available. Enter IL10 into the first search box since it is an official HUGO gene symbol, and select the ‘‘Find’’ button. Three matches were displayed at the time of writing from a simple

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text search — IL10, and its receptors, IL10RA, and IL10RB. Select IL10 to see the SNPper gene page for that gene. There is a lot of information here, behind a lot of web links, but it is powerful and easy to use once you have taken a minute to identify the main functional groupings. The top half of the screen contains database identifiers as links into their primary databases, for a wide range of fundamental gene annotation. Try each of these links in turn for your favorite cytokine, to see where each one goes. The left side of the lower half is the gene layout that shows SNPs in genomic context. The main resource for SNPs is on the right side where there are links for managing the gene’s entire collection of SNPs in a special web managed format — the SNPset. The SNPset deserves some experimentation because it can be very useful, particularly for designing SNP– based experiments such as disease association studies. Registered users (free!) can save and restore private SNPsets of their own. SNPsets are special containers for SNPs. They can have filters set, so only certain kinds of SNPs are visible, such as ‘‘validated and non-synonymous’’. Filter controls are accessed by selecting the ‘‘refine this SNPset’’ link for a gene. Finally, SNPsets can be downloaded in FASTA format for import into local software for genotyping primer design, for example.

4.4

CONCLUSION

In this chapter, some conventions including navigation and nomenclature, have been presented, which may be useful in working with web-accessible bioinformatic resources for genetic and genomic data, were presented. Four integrative bioinformatic resources were briefly introduced. The reader may find these to be useful starting points for the many tasks a modern biologist faces when working with genetic and genomic issues. It is hoped that this brief introduction will help readers become more familiar with some of the newer integrative bioinformatic tools, which can be used for genetic aspects of cytokine and other research. There are many more tools available.6 No single one of them is perfect for all tasks for all users, so trying them all at least once for some specific task is a clarifying experience. To learn which of the many available tools works best for you, try testing them with a favorite gene. It is not possible to harm the underlying resources by just clicking on links and trying things out. Tutorial and help links are often very useful places to explore when you first encounter a new resource. Experimentation is probably one of the best ways of learning what you need to know to make best use of these rich resources.

ACKNOWLEDGMENTS Support for this work by NIH grants U01 HL065899, U54 LM008748, R01 HG003646, and a grant from the Donald W. Reynolds Foundation, is gratefully acknowledged.

REFERENCES 1. Benson, D. A. et al., GenBank, Nucleic Acids Research, 33, D34-8, 2005. 2. NCBI, Genetic Sequence Data Bank Distribution Release Notes, ftp://ftp.ncbi.nih.gov/genbank/ gbrel.txt, Release 149.0:1; 2005. 3. National Center for Biotechnology Information, GenBank statistics, 2004. 4. National Center for Biotechnology Information, GenBank Flat File Release 142.0, 2004. 5. Riva, A. and Kohane, I. S., A SNP-centric database for the investigation of the human genome, BMC Bioinformatics, 5, 33, 2004. 6. Bateman, A., Editorial: Database issue, Nucleic Acids Research, 33, W1, 2005.

5

Cytokine Gene Nucleotide Sequence Alignments Jeffrey Bidwell

CONTENTS 5.1

Introduction and Relevance of Cytokine Gene Nucleotide Sequence Alignments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.2 User-Generated Cytokine Gene Nucleotide Sequence Alignments . . . . . . . . . . . . . . . . . . 74 5.2.1 MAP (http://genome.cs.mtu.edu/map.html) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 5.2.2 Multalin (http://prodes.toulouse.inra.fr/multalin/multalin.html) . . . . . . . . . . . . 74 5.2.3 BLAST (http://www.ncbi.nlm.nih.gov/BLAST/) . . . . . . . . . . . . . . . . . . . . . . . . . . 75 5.2.4 SNP BLAST (http://www.ncbi.nlm.nih.gov/SNP/snp_ blastByOrg.cgi) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 5.3 Pre-Generated Cytokine Gene Nucleotide Sequence Alignments . . . . . . . . . . . . . . . . . . 77 5.3.1 UCSC Genome Bioinformatics (http://genome.cse.ucsc.edu/) . . . . . . . . . . . . . . 77 5.3.2 dbCFC (http://cytokine.medic.kumamoto-u.ac.jp/CFC/index.htmlWelcome) . . . . . . . . 77 5.3.3 Human and Mouse Cytokine Nucleotide Sequence Alignments (http://www.bris.ac.uk/cellmolmed/services/CGR/cytokine.htm) . . . . . . . . . . . . 79 5.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

5.1 INTRODUCTION AND RELEVANCE OF CYTOKINE GENE NUCLEOTIDE SEQUENCE ALIGNMENTS Predisposition towards a TH1 or TH2 type cytokine response is thought to be influenced, at least in part, by inherited combinations of single nucleotide polymorphisms (SNPs) and polymorphic haplotypes within key cytokine genes. One explanation of how genotype affects phenotype in this way is that SNPs within the promoter or other regulatory sequences of certain cytokine genes influence up-regulation or down-regulation of transcription, and thus protein levels. Genetic polymorphism has been identified within virtually all cytokine, cytokine receptor, and receptor antagonist genes. Some of the polymorphisms have been uncovered by alignment of overlapping contiguous sequences and other sequenced clones as part of the human genome project (see http://genome.cse.ucsc.edu/ and http://www. ensembl.org/index.html). More recently, attempts have been made by individual groups and by organized collaborations to validate the occurrence and frequency of these SNPs, and to search for others within a variety of ethnic groups (see http://snpper.chip.org/bio/ snpper-enter/). It is becoming clear that the combinatorial arrangements of SNPs within a gene (haplotypes) and within adjacent genes (extended haplotypes) may provide more

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appropriate predictors of genotype–phenotype correlations in population genetics, gene expression, and disease association. As a corollary, there are now several ongoing large-scale projects generating genome-wide haplotype and extended haplotype data (see http:// www.hapmap.org/, http://pga.gs.washington.edu/finished_genes.html and http://www.niehs. nih.gov/envgenom/snpsdb.htm). Nucleotide sequence alignments have been and continue to be useful in mapping the extent of cytokine polymorphisms, and in providing a reference framework against which new SNP data may be conveniently compared. This chapter introduces some of the more useful software and data repositories which permit easy acquisition of user-generated or pre-generated cytokine gene nucleotide sequence alignments.

5.2

USER-GENERATED CYTOKINE GENE NUCLEOTIDE SEQUENCE ALIGNMENTS

There is a considerable choice of programs which facilitate user-generated nucleotide sequence alignments. URLs which provide links to some of these programs include:


http://bioinformatics.ca/bioinformatics_resources/links/?subcategory_id¼







120 http://www.swbic.org/links/1.9.1.2.php http://zlab.bu.edu/zlab/links.shtml http://pbil.univ-lyon1.fr/alignment.html http://www.ume.maine.edu/dnaseq/helpfullinks.htm http://www.public.iastate.edu/pedro/rt_1.html http://lepo.it.da.ut.ee/mremm/kurs/multali.htm

The speed, accuracy and capabilities of these programs vary and users would be advised to experiment with several. Four of the web-based programs which appear to be fast, accurate and which provide good output are as follows.

5.2.1

MAP (http://genome.cs.mtu.edu/ map.html)

This accepts user input in FASTA format. Figure 5.1 shows an example of the alignment output from MAP, comparing three complementary DNA (cDNA) and one genomic DNA (gDNA) sequences of interleukin 4. The analysis took 35 seconds. GT-AG splice donor/ acceptor sites were predicted accurately using default settings. The output can be copied from the web page or E-mailed to the user.

5.2.2

Multalin (http://prodes.toulouse.inra.fr/ multalin/multalin.html)

This accepts user input in FASTA format, pasted from the clipboard or as a file. Figure 5.2 shows an example of the alignment output from Multalin, comparing the same three cDNA and one gDNA sequences of interleukin 4 (IL4) as in Figure 5.1. The analysis took 29 seconds. GT-AG splice donor/acceptor sites were predicted accurately, using a gap opening penalty value of 5. The output can be copied from the web page or E-mailed to the user. New sequences can be added to the alignment. There are a variety of text, file, or image outputs.

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FIGURE 5.1 Alignment of IL4 sequences using MAP.

FIGURE 5.2 Alignment of IL4 sequences using Multalin.

5.2.3 BLAST (http://www.ncbi.nlm.nih.gov/ BLAST/) Nucleotide–nucleotide BLAST (BLASTn) is the NCBI alignment program useful for aligning sequences less than 3000 base pairs. Multiple pairwise alignments are automatically generated by searching the appropriate genome database. The advantage of BLAST is that all sequence homologs are aligned, the disadvantage being that only pairwise alignments, not a single multiple alignment, are generated. Figure 5.3A shows the results of a BLAST search for homologs of the IL4 cDNA clone M13982. Individual pairwise alignments are accessed by clicking on the appropriate BLAST hit (as exemplified in Figure 5.3B).

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FIGURE 5.3 (A) BLAST search for homologs of the IL4 cDNA clone M13982; (B) Pairwise alignment of M13982 with BC066278 IL4 cDNA clones.

5.2.4

SNP BLAST (http://www.ncbi.nlm. nih.gov/SNP/snp_blastByOrg.cgi)

SNP BLAST generates pairwise alignments of a nucleotide sequence with homologous sequences in the NCBI dbSNP database. This is extremely useful for indicating sites of known polymorphism within target genes. The output is similar to that for BLAST (Figure 5.4A and 5.4B).

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FIGURE 5.4 (A) SNP BLAST search for dbSNP homologs of the IL4 cDNA clone M13982, showing 11 hits; (B) Details of the 11 SNP BLAST hits (see Figure 5.4A) and links to dbSNP entries.

5.3 PRE-GENERATED CYTOKINE GENE NUCLEOTIDE SEQUENCE ALIGNMENTS 5.3.1 UCSC GENOME BIOINFORMATICS (http://genome.cse.UCSC.edu/) This site contains the reference sequence and working draft assemblies for a large collection of genomes, and is a major source of information gathered from the human genome project. Search results for a specific gene include an alignment of human mRNAs submitted to GenBank, with the gDNA, together with an alignment with non-human RefSeq genes. The zoom feature permits alignment at whole gene level (Figure 5.5A) down to codon and nucleotide level (Figure 5.5B). Individual pairwise alignments of mRNA with gDNA are easily accessed (Figure 5.5C), though multiple alignments cannot be generated at nucleotide level.

5.3.2 dbCFC (http:// cytokine.medic.kumamoto-u.ac.jp/CFC/ index.htmlWelcome) The Cytokine Family cDNA Database (dbCFC) provides information on cDNA, EST, contig/gene, and protein records of certain cytokines and growth factors, collated from

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FIGURE 5.5 (A) Alignment at gene level of human IL4 gDNA with GenBank human and non-human mRNAs. Location of SNPs is also shown; (B) Alignment at codon and nucleotide level of human IL4 gDNA with GenBank human and non-human mRNAs. Location of a SNP is also shown; (C) Pairwise alignment at nucleotide level of human IL4 cDNA (M13982) with gDNA.

Cytokine Gene Nucleotide Sequence Alignments

79

FIGURE 5.5 Continued.

several public databases including NCBI GenBank, Swiss-Prot, UniGene, TIGR (The Institute for Genomic Research) Gene Indices, Ensembl, Entrez Gene, Human Genome Database (GDB), Mouse Genome Informatics (MGI), and Rat Genome Database (RGD). Genes covered include IL6, TGFB family, TNFSF and TNFRSF families, chemokines and their receptors, FGF/HBGF family, LIF, OSM, MDK, PTN, and NGF.

5.3.3 HUMAN AND MOUSE CYTOKINE NUCLEOTIDE SEQUENCE ALIGNMENTS (http:// www.bris.ac.uk/cellmolmed/ services/CGR/cytokine.htm) Pre-generated cytokine nucleotide sequence alignments are available for viewing and download for a number of key human and mouse cytokine and cytokine receptor genes. These alignments were generated interactively using the MACAW (Multiple Alignment Construction & Analysis Workbench) computer application, available from http:// www.ibiblio.org/pub/academic/biology/molbio/ncbi/macaw/. MACAW permits multiple alignments and has relatively sophisticated manual alignment editing controls, though the raw sequence data cannot be edited. New sequences can be pasted from the clipboard in a relatively crude format, since MACAW filters out non-IUPAC nucleotide characters. Alignments can be exported in text format for annotation. There are a number of output options. Figure 5.6A shows the schematic alignment generated by MACAW of TNFSF1 (formerly TNFb/LTa) and TNFSF2 (formerly TNFa) gDNA (upper 11 clones) and cDNA (lower 6 clones). A portion of the equivalent annotated text file for this alignment is shown in Figure 5.6B.

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Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 5.6 (A) Schematic view of MACAW-generated alignment of TNFSF1 and TNFSF2 cDNA and gDNA clones; (B) Portion of the annotated text file from a MACAW-generated alignment of TNFSF1 and TNFSF2 cDNA and gDNA clones. Exon-intron boundaries, amino acid sequence, transcription factor binding sites, and other sequence features are shown.

5.4

CONCLUSIONS

The plethora of information relating to cytokine gene polymorphism and nucleotide sequences is now of a nature which would have been beyond belief only a few years ago. Sequence alignment data generated by the Human Genome Project was a necessary jump-start for the population-based polymorphism studies detailed in the Introduction to this chapter. What is now clear from these ongoing studies is that cytokine and cytokine receptor genes are highly polymorphic, despite their generally highly conserved coding region nucleotide sequences. The challenge confronting us now is to understand the correlation between cytokine genotype and phenotype, to encompass the effects of polymorphism on gene expression and association with human diseases.1–3 The software applications discussed in this chapter are some of the principal tools by which this polymorphism may be conveniently revealed by nucleotide sequence alignment.

Cytokine Gene Nucleotide Sequence Alignments

81

REFERENCES 1. Bidwell, J. L. et al., Cytokine gene polymorphism in human disease: on-line databases, Genes Immun., 1, 3, 1999. 2. Bidwell, J. L. et al., Cytokine gene polymorphism in human disease: on-line databases, Supplement 1, Genes Immun., 2, 61, 2001. 3. Haukim, N., et al., Cytokine gene polymorphism in human disease: on-line databases, Supplement 2, Genes Immun., 3, 313, 2002.

6

SNP Genotyping Techniques Pui-Yan Kwok

CONTENTS 6.1 6.2 6.3

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Basic SNP Genotyping Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Examples of Genotyping Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 6.3.1 Large-Scale Genotyping Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 6.3.1.1 Random Whole Genome Markers on Microarrays . . . . . . . . . . . . . . . . 85 6.3.1.2 Long-Range Resequencing of Unique Sequences on Microarrays . . 86 6.3.1.3 Targeted SNPs with Highly Multiplexed Assays on Microarrays . . 87 6.3.2 Medium-Scale Genotyping Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 6.3.2.1 Multiplex PCR and Primer Extension with Fluorescence Detection on Tag Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 6.3.2.2 Multiplex PCR with Primer Extension Detected by Mass Spectrometry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 6.3.2.3 Multiplex Ligation Detected by Capillary Electrophoresis of Mobility Tags . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 6.3.3 Single-Plex Genotyping Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 6.3.3.1 Allele-Specific Hybridization with Probe Cleavage . . . . . . . . . . . . . . . . 89 6.3.3.2 Kinetic PCR with Melting Curve Analysis . . . . . . . . . . . . . . . . . . . . . . . . 89 6.3.3.3 Allele-Specific Invasive Probe Cleavage . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 6.3.3.4 Primer Extension with Fluorescence Polarization Detection . . . . . . . . 90 6.4 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

6.1 INTRODUCTION The completion of the human genome sequencing project,1,2 the completion of the international haplotype mapping project (HapMap Project),3 and the maturation of the use of microarray technology have created an environment where ultra-high throughput single nucleotide polymorphism (SNP) genotyping is now possible.4 Because the high throughput genotyping methods rely on performing thousands of assays in multiplex, having the complete human genome sequence allows one to design probes that are unique in the genome and sets of probes that are not likely to interact with each other. The HapMap Project has contributed to the discovery of over 10 million SNPs in the human genome and has characterized some 3 million SNPs in four populations in Africa, Asia, and Europe. Knowing exactly where the SNPs are in the genome, whether they are common SNPs, and if they are in linkage disequilibrium with their neighbors makes it possible to identify the set of SNPs most useful for a particular project. The use of microarray technology in nucleic acid analysis has matured to the point where the quality of the microarrays is extremely high, the 83

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hybridization protocols are very robust, and the image analysis algorithms are highly sophisticated.5 Leveraging the informational and technological advances in genomics, several commercial concerns have been able to produce reliable and cost-effective large-scale SNP genotyping platforms for genetic association studies that require thousands of SNPs to be typed on thousands of DNA samples. Despite the advances made in the large-scale genotyping front, however, the cost of highly flexible methods suitable for studies requiring moderate throughput SNP genotyping (tens to hundreds of markers on a few hundred samples) remains relatively high. Nevertheless, the good news is that there are reliable genotyping methods that meet the needs of every genetic study using SNP markers. In this chapter, the most commonly used SNP genotyping techniques will be described together with a commentary on their strengths and weaknesses. As this field is moving extremely fast and the companies are continually improving their platforms, the readers are referred to the manufacturers for the latest version of each technology.

6.2

BASIC SNP GENOTYPING PRINCIPLES

There are four general mechanisms for allelic discrimination currently in use: allele-specific hybridization, allele-specific nucleotide incorporation, allele-specific oligonucleotide ligation, and allele-specific invasive cleavage. All four mechanisms are reliable under the right conditions and they can be used in combination for better assay performance. As these mechanisms have been extensively reviewed previously, only a brief description is presented here.6 With the hybridization approach, two allele-specific probes are designed to hybridize to the target sequence only when they match perfectly. Under optimized assay conditions, the one-base mismatch destabilizes the hybridization sufficiently to prevent the allelic probe from annealing to the target sequence. Because no enzymes are involved in allelic discrimination, hybridization is the simplest mechanism for genotyping. The challenge lies in probe design to ensure uniqueness of the probes in the genome and robust allelic discrimination. With ever more sophisticated probe design algorithms and the availability of the human genome sequence, allele-specific probes can be designed with high success rate. Primer extension is a very robust allelic discrimination mechanism. There are two major variations in the primer extension approach based on the ability of DNA polymerase to incorporate specific deoxyribose nucleosides complementary to the sequence of the template DNA. First is a sequencing (allele-specific nucleotide incorporation) approach where the identity of the polymorphic base in the target DNA is determined by the particular nucleotide incorporated in the reaction. Second is an allele-specific primer extension approach where the DNA polymerase is used to amplify the target DNA only if the 30 -end of the PCR primers are perfectly complementary to the target DNA sequence. DNA ligase is highly specific in repairing nicks in the DNA molecule. When two adjacent oligonucleotides are annealed to a DNA template, they are ligated together only if the oligonucleotides perfectly match the template at the junction. Allele-specific oligonucleotides can therefore be made to interrogate the nature of the base at the polymorphic site. One can infer the allele(s) present in the target DNA by determining whether ligation has occurred or not. Structure-specific enzymes cleave a complex formed by the hybridization of overlapping oligonucleotide probes. When probes are designed such that the polymorphic site is at the point of overlap, the correct overlapping structure is formed only with the allele-specific probe but not with the probe with a one-base mismatch. Elevated temperature and an excess

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of the allele-specific probe enable multiple probes to be cleaved for each target sequence present in an isothermal reaction. Determining whether the cleavage event has occurred or not allows one to infer the identity of the base present in the target DNA. Visualization of the allelic discrimination reaction is currently based on various fluorescence detection techniques such as fluorescence intensity, fluorescence resonance energy transfer, and fluorescence polarization. In addition, mass spectrometry is also used to identify the product of the allelic discrimination reaction. Fluorescence detection methods, especially those based on CCD imaging, can perform the detection step for numerous reactions at the same time whereas the mass spectrometry based methods require serial detection of reactions one at a time. In all the genotyping methods, however, detection is never the bottleneck because the time it takes for capture is usually a fraction of the total reaction time. Microarrays are used extensively to achieve highly paralleled genotyping reactions. In some cases, the microarrays are made up of marker specific oligonucleotides and the allelic discrimination reaction is done on the support. In other cases, generic oligonucleotides are placed on the array and they are used to capture complementary sequence tags conjugated to marker specific probes. In the former strategy, the oligonucleotide arrays act as a collection of reactors where the target DNA molecules find their counterparts and the allelic discrimination step for numerous markers proceeds in parallel. In the latter, the arrayed oligonucleotides are used to sort the products of the allelic discrimination reactions (also done in parallel) performed in homogeneous solution. In both cases, the identity of an oligonucleotide on a latex bead or at a particular location on the microarray is known and the genotypes are inferred by determining which immobilized oligonucleotide is associated with a positive signal. The major advantage of performing genotyping reactions on solid supports is that many markers can be interrogated at the same time. Besides savings in time and reagents, performing numerous reactions in parallel also decreases the probability of sample/results mix-ups.

6.3 EXAMPLES OF GENOTYPING METHODS Table 6.1 lists the many those engaged in genetic for their studies based on typed, and the amount of

commercially available SNP genotyping methods available for research. Investigators can select the method most appropriate the number of markers to be used, the number of samples to be funding available to them.

6.3.1 LARGE-SCALE GENOTYPING METHODS 6.3.1.1

Random Whole Genome Markers on Microarrays

A great example of how knowledge of the human genome sequence has changed the SNP genotyping field is found in the Affymetrix GeneChip Human Mapping Arrays.4 Based on bioinformatic predictions of which SNPs are found within small restriction fragments that can be amplified by routine PCR, oligonucleotide probes are arrayed on the GeneChip at high density to determine, by allele-specific hybridization, the alleles present for 450 000 SNPs per array. At the time of this writing, a two-chip set of arrays had just been commercialized to type 4500 000 SNPs. The major advantage of this approach is the fact that one can produce
16 million genotypes per day when the 500 000 SNP arrays are used. Other advantages include the ease of operation (seven standard steps of complete restriction digest of genomic DNA, ligation of a common linker, genome complexity reduction and

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Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 6.1 Comparison of Genotyping Methods Degree of Multiplexing

Method Affymetrix SNP Chip

ParAllele MIP AssayÕ

Up to 250 K per array Up to 300 K per array Up to 250 K per array Up to 10 000

Illumina GoldenGateÕ

Up to 1536

Beckman SNPStreamÕ

Up to 48

Sequenom MassArrayÕ

Up to 25

ABI SNPLexÕ

Up to 48

ABI TaqManÕ

Single

Third Wave InvaderÕ

Single

Roche Kinetic PCRÕ

Single

Perkin-Elmer AcycloPrime-FPÕ

Single

Perlegen whole genome arrays Illumina InfiniumÕ

Assay Design

Cost of Assay Development

Fixed by vendor

Extremely high

Low

Very low

Fixed by vendor

Extremely high

Low

Very low

Fixed by vendor

Extremely high

Low

Very low

Possible to customize Possible to customize Possible to customize Possible to customize Possible to customize Possible to customize Possible to customize Possible to customize Possible to customize

High

Low

Low

High

Low

Low

Moderate

Low

Moderately low

Moderate

Low

Moderately low

Moderate

Low

Moderately low

Moderate

High

Low

Moderately high Moderately high Low

Moderately high

Low

Low

Moderately high

Moderate

Operating Cost

Cost per Genotype

High

amplification using a universal primer, fragmentation and labeling of the amplified DNA, hybridization and washing, imaging of the array, automated data analysis); small amount of DNA needed (250 ng per array); the cost of oligo synthesis on the arrays is pretty much the same regardless of the oligo density; and low cost per genotype (51 cent US). There are some disadvantages. The main drawback is that the markers are not uniformly distributed across the genome. In addition, because of the requirement that the SNPs have to be found within small restriction fragments and that the SNPs must be found in DNA sequence unique in the sizeable fraction of the genome amplified, many SNPs one would like to type will not be found among the set of SNPs assayed on the arrays. 6.3.1.2

Long-Range Resequencing of Unique Sequences on Microarrays

Another example of intensive use of human genome sequence information for SNP genotyping is a strategy taken by the company Perlegen.7 Here, they design long PCR assays to cover as much of the genome as possible, fragment the long PCR products, and hybridize the pooled PCR product fragments to a chip containing the unique sequences surrounding all the SNPs found within the long PCR products.8 In the current version, they are able to type almost 5 million SNPs found in the public databases. The advantages of the method include the comprehensive nature of the strategy and the 51 cent US per genotype cost. The disadvantages are that thousands of long PCR assays have to be run for each sample and the need for specialized chips and equipment.

SNP Genotyping Techniques

6.3.1.3

87

Targeted SNPs with Highly Multiplexed Assays on Microarrays

Three different SNP genotyping strategies are used by Illumina and ParAllele to take advantage of generic sequence tag array concept where thousands of assays are sorted on the microarray after the reactions are completed in liquid phase. In these approaches, probes specific to all SNP are built to include a tag sequence complementary to those found on the microarrays. These approaches allow one to select specific SNPs for each assay and can accommodate thousands of SNPs in each reaction. 6.3.1.3.1

Primer Extension with Long Probes

A new assay being developed by Illumina aims to genotype 100 000 SNPs in one experiment, with plans to develop assays for 250 000 SNPs in one experiment.9 It starts with whole genome amplification of the genomic DNA to provide enough copies of DNA template for this reaction.10 Two long allele-specific probes (
50-mers), tailed with ‘‘tag’’ sequences for subsequent hybridization to the microarray features, are then designed for each SNP to provide the specificity needed in the face of whole genome complexity found in the target DNA. Primer extension occurs only when perfect complementary between the probe and target DNA is found. Because such long probes are used, very stringent annealing conditions can be used in the primer extension reaction to ensure both sensitivity and specificity. Some ten thousand SNPs can be typed at the same time with this approach. The microarrays are formed by self-assembly of thousands of latex beads conjugated with tag sequences when they are deposited onto glass slides full of tiny wells (BeadChips). The advantages of this system include: ability to target specific SNPs in the genome to assay; redundancy in the number of beads bearing the same tag on the array increases the confidence in genotype calls; no need for ligation or PCR steps; small starting genomic DNA sample; and low cost per genotype. The main disadvantage is the high initial cost and time needed to build the repertoire of allele-specific probes and conjugating them onto latex beads. The system is therefore best suited for a more or less static set of SNPs to be used in initial whole genome searches for association. 6.3.1.3.2

Gap-Filled Ligation with Molecular Inversion Probes

Another system based on the ‘‘tag array’’ concept is developed by ParAllele.11,12 In this approach, a set of ‘‘molecular inversion probes’’ are designed to hybridize to the DNA sequence flanking the SNPs. The 50 - and 30 -sequences annealed to the target DNA are part of a longer probe with universal PCR priming sequence and a unique tag sequence. The allelic base is brought in by DNA polymerase and the ends of the probe are closed by DNA ligase to form a circular product. Cleavage of the circular probe in the linker inverts the probe to yield the template for universal PCR amplification of the probe. The resultant products, each bearing a tag sequence, are then hybridized to a microarray containing oligos complementary to the tag sequences. The advantages of this system include: the intra-molecular ligation reaction is very specific and robust and allows for multiplexing to 410 000 assays; only one probe is needed for each SNP and the assay development cost is therefore less costly; the use of a universal PCR primer set keeps the protocol simple; and the cost per genotype is low. The disadvantages include the need to perform four separate reactions in the polymerase gap-fill reaction; the DNA sample required (
2 g) is high; the reliance on Affymetrix chips for imaging keeps the number of samples processed per experiment somewhat lower than other systems. 6.3.1.3.3

Allele-Specific Primer Extension with Ligation

The third system based on the ‘‘tag array’’ concept is from Illumina.13,14 In the ‘‘Golden Gate assay,’’ allele-specific probes are extended when annealed to the correct DNA target to fill

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Cytokine Gene Polymorphisms in Multifactorial Conditions

a small gap consisting of several bases to meet a common reporter probe downstream. The extended allele-specific probes are then ligated to the reporter probe. Each probe is tailed with one of three universal PCR priming sequences and the reporter probe is also tailed with a SNP-specific tag. The ligated products are then amplified with labeled PCR primers to form fluorescent PCR products for hybridization to latex beads bearing oligos complementary to the tag sequences. The beads are found on tips of fiberoptic bundles with tiny wells at the tips of the fibers. The advantage of this system is once again the number of assays one can do in each multiplex experiment. The cost of probe production is high but, once amortized over many samples, the cost per genotype is down to the 5 cents US range. The disadvantage of the method is the multiplex limitation of about 1500 SNPs in each experiment. Because the large-scale genotyping methods by definition have to perform thousands of allelic discrimination reactions on genomic DNA at the same time, long probes (typically with a combined probe length of 450 bases per allele) are needed to ensure high specificity. In addition, if the SNPs are part of duplicated regions in the genome, assays cannot be designed for them. Even with the significant savings in personnel cost, the cost of the microarray and probe manufacturing is so high that only multiplexing above 1000 SNPs for studies with several thousand samples makes the cost per genotype competitive.

6.3.2

MEDIUM-SCALE GENOTYPING METHODS

For many applications, the number of SNPs needed is relatively small and the number of samples is also in the hundreds rather than thousands. In this situation, moderately multiplexed methods (10- to 50-plex) with low-cost probes are desirable. In general, primer extension assays based on the ‘‘sequencing’’ approach is most suitable for this level of throughput although a ligation based method is also designed to fill this need. Here, Beckman Coulter, Sequenom, and Applied Biosystems have developed robust methods. 6.3.2.1

Multiplex PCR and Primer Extension with Fluorescence Detection on Tag Arrays

The Beckman Coulter approach is based on multiplex PCR followed by a primer extension reaction that incorporates the allelic nucleotide labeled with a fluorescent dye onto a SNP primer that is tailed with a tag sequence.15 The primer extension reaction products are then captured onto micotiter plates with oligos complementary to the tag sequences printed on the bottom of the wells. The reactions can be done at 12- to 48-plex at relatively low cost per genotype. The advantage is the flexibility of the reaction and low assay development cost. The disadvantage is the uncertainty surrounding multiplex PCR optimization. With good primer design algorithms, robust designs are becoming routine. 6.3.2.2

Multiplex PCR with Primer Extension Detected by Mass Spectrometry

The Sequenom approach is also based on the primer extension reaction with multiplex PCR. Instead of separating the primer extension products by hybridization to ‘‘tag arrays’’, the products are resolved by mass spectrometry based on the oligo lengths and the nucleotide incorporated.16,17 The advantage of the system is that a physical property of the oligo, namely mass, is used for genotype determination. It is very accurate and robust. The drawback is that the mass spectrum is quite limited so it is unlikely to achieve assay designs of 425-plex. 6.3.2.3

Multiplex Ligation Detected by Capillary Electrophoresis of Mobility Tags

The Applied Biosystem approach is based on multiplex ligation reaction followed by creation of DNA fragments corresponding to ligation products with different mobilities when they undergo capillary electrophoresis.18 Because the ligation reaction is very specific, the

SNP Genotyping Techniques

89

limitation to multiplexing is due to the small number of mobility-shifting molecules available for use in the automatic DNA sequencer. The advantage of the system is the availability of the instrument in many laboratories. The disadvantages include the large number of steps required in the protocol and the relatively costly probes needed for the method.

6.3.3 SINGLE-PLEX GENOTYPING METHODS Although there are many single-plex SNP genotyping methods available, four are currently commercially available and widely used. They are all homogeneous reactions that are very flexible and not labor intensive. However, the lack of multiplexing keeps the operating cost of these assays relatively high. 6.3.3.1

Allele-Specific Hybridization with Probe Cleavage

The TaqManÕ (Applied Biosystems, Foster City, California) assay is based on allele-specific hybridization with the readout of probe cleavage when the probe is fully annealed to the target DNA during PCR amplification.19 This is a closed-tube assay that has the advantage of simple reaction set up and minimal chance for cross contamination. In addition, this assay is quantitative and is therefore useful in determining the concentration of unknown DNA or RNA samples. The main disadvantage of the assay is the high cost of assay design. Unless the cost of the expensive probes is amortized over thousands of samples, the assay development cost pushes this assay beyond the resources available to most studies. To counter this problem, the company has developed thousands of assays up front and makes the reagents available to researchers as aliquots. 6.3.3.2

Kinetic PCR with Melting Curve Analysis

Another closed-tube assay is the Tm-shift assay developed by Roche Molecular Systems.20 In this assay, the two allele-specific PCR primers are tailed with different number of GC nucleotides so that the resultant PCR products have different melting profiles. Since SYBR-Green only fluoresces when it is intercalated into double-stranded DNA, the melting curves of the allele-specific PCR products can be determined by monitoring SYBR-Green fluorescence during heating and cooling of the reaction mixture. The genotype of each sample can be determined by the presence of products of particular melting profiles. The major advantage of the method is the low cost of assay development since the primers are inexpensive, PCR-grade oligonucleotides. The disadvantage of the method is the need to optimize allele-specific PCR assays. With improved computer assisted design, this assay will become more robust. 6.3.3.3

Allele-Specific Invasive Probe Cleavage

A third closed-tube assay is the InvaderÕ (Third Wave Technologies, Madison, Wisconsin) assay.21,22 In this assay, the invasive cleavage reaction cleaves the allele-specific ‘‘flap probe’’ hybridized to the SNP site. Using different synthetic sequences built into the allele-specific ‘‘flap probes,’’ the cleaved ‘‘flap’’ becomes the invader probe in a secondary reaction. The reporter dye on the ‘‘flap probe’’ in the secondary reaction is quenched by another dye but fluoresces when the probe is cleaved. The advantage of this method is that it is an isothermal reaction and does not require PCR amplification. However, in practice, a few rounds of PCR amplification prior to the Invader reaction increase the robustness of the assay tremendously. The assay suffers from the need for multiple high-quality probes, making it a relatively expensive technique.

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Cytokine Gene Polymorphisms in Multifactorial Conditions

6.3.3.4

Primer Extension with Fluorescence Polarization Detection

The assay with the lowest assay development cost is the primer extension assay based on fluorescence polarization detection commercialized by PerkinElmer.23–25 In this assay, a SNP region is amplified by PCR and a SNP primer is used to guide the incorporation of dye-labeled terminators complementary to the target DNA sequence. Because fluorescence polarization of a dye molecule is proportional to its size, the free dye-terminators have low polarization values while the incorporated dyes have high polarization values. Since the free and bound dyes have different physical properties, there is no need for purification or separation of the products before the detection step. The advantages of the assay include the low equipment cost, extremely low assay development cost, and high flexibility in assay design. The disadvantages include the need for multiple steps, the relatively high reagents cost, and its being more labor intensive than the closed-tube assays.

6.4

FUTURE DIRECTIONS

There are now good choices for SNP genotyping techniques to meet the needs of most studies. However, the medium-to large-scale genotyping methods are still expensive when the number of samples to be typed is small. As the cost of probe synthesis continues to drop and the reaction volume shrinks, the day will come when the cost per genotype is 50.1 cent US regardless of the sample size one needs to study. Of course, when the $1000 US whole genome sequencing methods become a reality, SNP genotyping is no longer an issue and will become a footnote in the history of molecular genetics.26 Given the speed of innovation seen in the field, that day will come sooner than one expects.

REFERENCES 1. Lander, E. S. et al., Initial sequencing and analysis of the human genome, Nature, 409, 860, 2001. 2. International Human Genome Sequencing Consortium, Finishing the euchromatic sequence of the human genome, Nature, 431, 931, 2004. 3. The international hapmap consortium, a haplotype map of the human genome, 437, Nature, 437, 1299, 2005. 4. Matsuzaki, H. et al., Genotyping over 100 000 SNPs on a pair of oligonucleotide arrays, Nat. Methods, 1, 109, 2004. 5. Di, X. et al., Dynamic model based algorithms for screening and genotyping over 100 K SNPs on oligonucleotide microarrays, Bioinformatics, 21, 1958, 2005. 6. Kwok, P.-Y., Methods for genotyping single nucleotide polymorphisms, Ann. Rev. Genomics and Hum. Genet., 2, 235, 2001. 7. Hinds, D. A. et al., Whole-genome patterns of common DNA variation in three human populations, Science, 307, 1072, 2005. 8. Patil, N. et al., Blocks of limited haplotype diversity revealed by high-resolution scanning of human chromosome 21, Science, 294, 1719, 2001. 9. Gunderson, K. L. et al., A genome-wide scalable SNP genotyping assay using microarray technology, Nat. Genet., 37, 549, 2005. 10. Barker, D. L., Two methods of whole-genome amplification enable accurate genotyping across a 2320-SNP linkage panel, Genome Res., 14, 901, 2004. 11. Hardenbol, P. et al., Multiplexed genotyping with sequence-tagged molecular inversion probes, Nat. Biotechnol., 21, 673, 2003. 12. Hardenbol, P. et al., Highly multiplexed molecular inversion probe genotyping: over 10 000 targeted SNPs genotyped in a single tube assay, Genome Res., 15, 269, 2005.

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13. Oliphant, A., BeadArray technology: enabling an accurate, cost-effective approach to high-throughput genotyping, Biotechniques, Suppl:56, 2002. 14. Murray, S. S. et al., A highly informative SNP linkage panel for human genetic studies, Nat. Methods, 1, 113, 2004. 15. Bell, P. A. et al., SNPstream UHT: ultra-high throughput SNP genotyping for pharmacogenomics and drug discovery, Biotechniques, Suppl:70, 2002. 16. Buetow, K. H. et al., High-throughput development and characterization of a genomewide collection of gene-based single nucleotide polymorphism markers by chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, Proc. Natl. Acad. Sci. USA, 98, 581, 2001. 17. Nelson, M. R. et al., Large-scale validation of single nucleotide polymorphisms in gene regions, Genome Res., 14, 1664, 2004. 18. De la Vega, F. M. et al., Assessment of two flexible and compatible SNP genotyping platforms: TaqMan SNP genotyping assays and the SNPlex genotyping system, Mutat. Res., 573, 111, 2005. 19. Livak, K. J., SNP genotyping by the 50 -nuclease reaction, Methods Mol. Biol., 212, 129, 2003. 20. Germer, S. and Higuchi, R., Homogeneous allele-specific PCR in SNP genotyping, Methods Mol. Biol., 212, 197, 2003. 21. Hall, J. G. et al., Sensitive detection of DNA polymorphisms by the serial invasive signal amplification reaction, Proc. Natl. Acad. Sci. USA, 97, 8272, 2000. 22. Lyamichev, V. and Neri, B., Invader assay for SNP genotyping, Methods Mol. Biol., 212, 229, 2003. 23. Chen, X., Levine, L. and Kwok, P.-Y., Fluorescence polarization in homogeneous nucleic acid analysis, Genome Res., 9, 492, 1999. 24. Hsu, T. M. et al., A universal SNP genotyping assay with fluorescence polarization detection, BioTechniques, 31:560, 2001. 25. Xiao, M., et al., Role of excess inorganic pyrophosphate in primer-extension genotyping assays, Genome Res., 14, 1749, 2004. 26. Collins, F. S. et al., A vision for the future of genomics research, Nature, 422, 835, 2003.

Part B Cytokine Gene Polymorphisms

7

The IL1 Cluster Tanja Pessi, Carita Eklund, Annika Raitala, and Mikko Hurme

CONTENTS 7.1 The IL1 Gene Cluster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 7.2 Structure of IL1 Gene Cluster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 7.3 IL-1 Family Proteins: Synthesis and Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 7.4 Expression of IL1 Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 7.5 Main Functions of IL1 Family Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 7.6 Polymorphism in IL1 Cluster Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 7.7 Effect of Gene Polymorphisms on IL-1 and IL-1Ra Protein Levels . . . . . . . . . . . . . . 100 7.8 Disease Associations of Single Marker Polymorphism . . . . . . . . . . . . . . . . . . . . . . . . . . 101 7.9 Haplotypes and Linkage Disequilibrium within IL1 Cluster . . . . . . . . . . . . . . . . . . . . 101 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

7.1 THE IL1 GENE CLUSTER The main cytokines participating in the regulation of the inflammatory response are IL-1a, IL-1b, IL-1 receptor antagonist (IL-1Ra), IL6, IL10, and tumor necrosis factor (TNF)-a. Functionally they can be divided into pro-inflammatory (IL-1a, IL-1b, IL-6, TNF-a) and anti-inflammatory (IL-1Ra, IL-10) molecules. The IL1 gene cluster contains genes coding for both anti- and pro-inflammatory cytokines, including IL-1a, (IL-1F1), IL-1b (IL-1F2), IL-1Ra (IL-1F3) and more recently found members of IL-1 family: IL-1F5– IL-1F10.1 Pro-inflammatory cytokines like IL-1a and IL-1b are involved in the enhancement of inflammation and host defence. Anti-inflammatory IL-1Ra counteracts the function of IL-1a and IL-1b. These three members of the family are structurally related to one another and bind to IL-1 receptors (IL-1R) on cells.2 Most IL-1 family cytokines are expressed in monocytes, macrophages, and keratinocytes. All genes in the IL1 cluster are polymorphic and several of these polymorphisms have been shown to be associated with either susceptibility to or severity of inflammatory conditions and diseases.

7.2 STRUCTURE OF IL1 GENE CLUSTER The IL1 gene cluster is located on chromosome 2q14.2. The gene order within the cluster from centromere to telomere is IL1A–IL1B–IL1F7–IL1F9–IL1F6–IL1F8–IL1F5–IL1F10– IL1RN, of which only IL1A, IL1B, and IL1F8 are transcribed towards the centromere (Figure 7.1). The region has been estimated to be 360 kb. IL-18 (IL-1F4) can also be considered as a member of the IL-1 family since its gene structure and predicted tertiary protein structure are very similar to those of IL-1b and IL-1Ra. IL-18 binds to its own receptor, and unlike the other IL1 family genes, its gene is located on chromosome 11q. One additional gene, LOC442042, lies between IL1F9 and IL1F6, but its function is unknown. 95

96

Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 7.1 Map of the IL1 gene cluster. Scale bars in kb are provided above the data to aid alignments. The used contigs were from www.ncbi.nlm.nih.gov (NC_000002, NM_000575, NM_000576, NM_000577, AF186094, AF201831, AF201832, AF201833, AF200492, AF334755). The arrows under the gene symbol indicate the direction of transcription. X, LOC150468; Y, LOC442042; Z, LOC23550. Exon–intron organization of the IL1A, IL1B, and IL1RN genes are indicated in the lower part of the diagram. Exons are shown as vertical lines or boxes. Exon–intron size rations and genomic sizes of genes (IL1A, IL1B, and IL1RN) are not shown to scale. The most studied polymorpic sites in the IL1A, IL1B, and IL1RN genes are indicated.

7.3

IL-1 FAMILY PROTEINS: SYNTHESIS AND STRUCTURE

Both IL-1a and IL-1b are synthesized as precursor proteins. Due to the absence of a leader peptide, the pro form of IL-1a (31 kDa)/IL-1b (31 kDa) remains in the cytosol. Processing the pro-form into the mature form requires assistance of a cysteine protease called calpain (IL-1a), or a proteolytic cleavage with IL-1 converting enzyme (IL-1b). After processing, a mature protein is released into the extracellular compartment. IL-1a is mainly found in the cytosol and on the plasma membranes of cells whereas IL-1b plasma levels are detectable in plasma.2 IL-1a and IL-1b are 24% homologous at the amino acid levels. Both IL-1a and IL-1b recognize the same receptor IL-1RI. The synthesis and structure of IL-1a and IL-1b have been described in detail in previous reviews.2,3 At least three additional intracellular isoforms of IL-1Ra (icIL-1Ra) and one secreted form of IL-1Ra (sIL-1Ra) have been described to date. An 18 kDa form of IL-1Ra, termed IL-1RaI, is created by an alternative transcriptional splice mechanism from an upstream exon. Although icIL-1RaI is synthesized in the cytoplasm of keratinocytes and other epithelial cells, it may under certain conditions be released from these cells.4 The predicted 25 kDa protein, termed icIL-1RaII, has never been found in human cells and this mRNA may not be translated in vivo. A 15 kDa isoform of IL-1Ra, termed icIL-1RaIII, may be created both by an alternative transcriptional splicing and by alternative translational initiation.5 Both sIL-1Ra and icIL-1RaI bind equally well to IL-1RI, but icIL-1RaIII exhibits weak receptor binding.2 The synthesis and structure of IL-1Ra have been described in detail in previous reviews.2,3 IL-1F6, IL1-F7, IL1-F8, and IL1-F9 are quite homologous to each other at the amino acid level (45% to 57% homology). The amino acid sequence and inferred tertiary structure of IL-1F56 and IL-1F107 are similar to those of IL1Ra (52% and 37%, respectively). IL-1F5–IL-1F9 do not have a classical leader sequence (as does sIL-1Ra), nor do they have a distinct pro-form (as do IL-1a and IL-1b). IL-1F7, however, contains a propeptide sequence. IL-1F10 binds to the soluble IL-1R1 in contrast to the IL-1F5–IL-1F9.

The IL1 Cluster

97

Two alternatively spliced transcript variants encoding the IL-1F5,6, 8 IL-1F8,9 and IL1-F1010 protein have been reported.6,8 IL-1F7 has five different splice variants (IL-1F7a–e).11

7.4 EXPRESSION OF IL1 GENES Various cell types and tissues express IL1 family genes (Table 7.1). Key findings include the demonstration that nearly all cell types that express IL1a and IL1b also produce IL-1Ra.2 The expression of IL1Ra isoforms in different cell types varies: sIL1Ra is secreted from monocytes, macrophages, and neutrophils, icIL1RaI is found inside keratinocytes, epithelial cells, monocytes, tissue macrophages, fibroblasts, and endothelial cells. icIL1RaII has never been found in human cells, and icIL1RaIII is found in monocytes, macrophages, neutrophils, and hepatocytes.5

7.5 MAIN FUNCTIONS OF IL1 FAMILY GENES IL-1a and IL-1b are expressed in and affect nearly every cell type, and their biological effects result from their ability to modulate gene expression in their target cells. The following names of IL-1 describe the major biological roles of IL-1: endogenous pyrogen, leukocyte endogenous mediator, lymphocyte-activating factor, B cell activating factor, osteoclast activating factor, epidermal cell derived thymocyte activating factor, hemapoietin-1, and mononuclear cell factor.2 In addition, IL1b has recently been found to be essential for in vivo invasiveness and angiogenesis of different types of tumor cells,12 to promote oligodendrocyte death through glutamate excitotoxicity,13 and to mediate the inflammatory pain hypersensitivity through COX-2 induction in the central nervous system.14 Intracellular IL-1a precursor, in turn, was recently suggested to be an intracrine proinflammatory activator of transcription.15 Because this effect was not affected by extracellular inhibitors, Werman et al.15 suggested that reduction of the intracellular functions of IL-1a might be beneficial in some inflammatory conditions. IL-1Ra acts as an antagonist to IL-1RI thereby blocking the biological responses of the agonists, IL-1a, and IL-1b. It has been suggested that the antagonistic effect of IL1Ra depends on its isoforms.5 The biological effects of IL-1a, IL-1b and IL-1Ra have been described in detail in previous reviews.2,3,5 It has been suggested that IL-1F5 has antagonistic effects. IL-1F5 is a highly specific antagonist to IL1F6 and inhibits the activity of IL-1F9. However, IL-1F5 has only a weak antagonistic effect on IL-1a and IL-1b because of its similarity to IL-1b.8 Debet et al. showed that IL-1F5 does not induce the production of IFN-g or inhibit the IL-18-induced production of IFN-g.6 The cytokine induction profiles for IL-1F6, IL-1F8, and IL-1F9 are very similar to each other and to that of IL-1b. They all induce the production of IL-6, IL-8, and granulocyte-macrophage colony-stimulating factor.9 It is now known that IL-1F6, IL-1F8, and IL-1F9 are all capable of enhancing immune responses and inducing inflammation. However, the specific information about the function of these cytokines is still limited. Expression profiles provide hints of the potential roles of IL-1F6, IL-1F8 and IL-1F9 in disease pathogenesis and in the defence against pathogens.9 IL-1F7 is expressed at low levels constitutively. It is suggested that IL-1F7 plays its greatest role during acute immune response requiring rapid up-regulation.16 IL-1F7 has been shown to have anti-tumor effects; it may promote the development of the antitumor response through enhanced IL-12 production.16 IL-F7 appears to mediate a mixture of IL-12- and IL-18-like effects, i.e. properties similar to IL-18, whose anti-tumor activity

Monocytes, alveolar and synovial macrophages, keratinocytes, Langerhans cells, endothelial cells, mast cells, chondrocytes, stimulated B and T cells, NK cells, eosinophils, fibroblasts Monocytes, alveolar and synovial macrophages, keratinocytes, Langerhans cells, endothelial cells, mast cells, chondrocytes, stimulated B and T cells, NK cells, eosinophils, fibroblasts Monocytes, alveolar and synovial macrophages, neutrophils, keratinocytes, chondrocytes, fibroblasts, endothelial cells, epithelial cells Placenta, uterus, skin, brain, heart, kidney, lung, monocytes, B cells, dendritic cells, Langerhans cells, keratinocytes, psoriatic skin Spleen, lymph node, tonsil, leukocytes, bone marrow, fetal brain, esophageal squamous epithelium, psoriatic skin, keratinocytes, Langerhans cells, monocytes, B cells, T cells Lymph node, thymus, bone marrow, lung, testis, placenta, uterus, skin colon, NK cells, monocytes, stimulated B cells, keratinocytes Bone marrow, tonsil, heart, placenta, lung, testis, colon, monocytes, B cells Placenta, stimulated keratinocytes, epithelial cells, esophageal squamous epithelium, psoriatic skin Basal epithelia of skin, proliferating B cells of tonsils

Expression

96 (
21127 to þ9035) 14 (
248 to þ6766) 26 (
259 to þ2665)

57 (þ1 to þ5796)

4 (þ1 to þ2172)

55 (
76 to þ5225)

172 (
87 to þ15816)

62 (
511 to þ5969)

69 (
1659 to þ9111)

Number of SNPs (Gene Region)*

Abbreviations: FIL-1, family of IL-1; IL, interleukin; IL-1L1, IL1 like 1; IL-1H, IL-1 homolog; IL-1R1, IL-1 type I receptor; IL-1Ra, IL1 receptor antagonist; IL-1RP, IL-1 related protein. *Gene region determined as in NCBI SNP database.

IL-1F7 (FIL-1z, IL-1H4, IL-1RP1, IL-1H) IL-1F8 (FIL-1Z, IL-1H2) IL-1F9 (IL-1H1, IL-1RP2, IL-1e) IL-1F10 (IL-1Hy2, FKSG75)

IL-1F5 (IL-1Hy1, FIL-1d, IL-1H3, IL-1RP3, IL-1L1, IL-1d) IL-1F6 (FIL-1e)

IL-1Ra (IL-1F3)

IL-1b (IL-1F2)

IL-1a (IL-1F1)

Protein (Alternative) Names

TABLE 7.1 IL-1 Family Proteins and Their Expression Profiles as Well as Number of Known SNPs in the IL1 Cluster Genes1–3

98 Cytokine Gene Polymorphisms in Multifactorial Conditions

The IL1 Cluster

99

depends on IL-12 activity. It also possibly inhibits the biological activity of IL-18 by binding to IL-18BP.16 IL-1F10 binds to sIL-1RI, suggesting its role in regulating IL-1R function.10 The expression in a variety of immune tissues and similarity to IL-1Ra implies a role of IL-1F10 in the inflammatory response.7 However, the functional significance of IL-1F10 on immune responses is still unclear.

7.6 POLYMORPHISM IN IL1 CLUSTER GENES All IL1 cluster genes are polymorphic. There are about 1500 SNPs within the IL1 cluster area (www.ncbi.nlm.nih.gov; www.appliedbiosystem.com/SNPbrowser). The region also contains a number of multiallelic markers, e.g. microsatellite markers 222/223, gz5/gz6 (in IL1A), gaat.p33330 (in IL1F9), Y31 (in IL1F8), and VNTR (in IL1A and IL1RN).17,18 Table 7.1 lists the number of SNPs of IL1 cluster genes reported on NCBI-website to date (http://www.ncbi.nlm.nih.gov). This chapter focuses on the most studied polymorphisms in the IL1A, IL1B, and IL1RN gene regions. More extensive information about other polymorphisms in IL1 cluster genes can be found at NCBI-website (http://www.ncbi.nlm. nih.gov), in the HapMap database (http://www.hapmap.org), and in the SeattleSNP database (http://pga.gs.washington.edu). The IL1A gene is 10 206 bp long and consists of seven exons and six introns. There are no apparent TATA box motifs in the gene promoter area. According to the NCBI database to date, the total amount of SNPs in IL1A is 69 (Table 7.1). The most studied polymorphisms in the IL1A gene are rs17561 (at position þ4845), rs18000587 (at position
889), VNTR, dinucleotide, and (TTCA) repeats in intron 6. Other studied SNPs in IL1A are rs1894399 (at position þ1893), rs2071373 (þ1986), rs3783543 (þ5418), rs2071375 (þ6630), rs2071376 (þ6673), and rs1304037 (þ10897). In healthy Caucasians IL1A SNP þ4845 is in 100% linkage disequilibrium at least with IL1A SNP
889, IL1A SNP þ1893, IL1A SNP þ1986, IL1A SNP þ5418, and IL1A SNP þ10897 (Figure 7.2).19 The single G to T base exchange polymorphism (IL1A SNP þ4845) causes an amino acid substitution of alanine to serine.20 The frequency of allele G of IL1A SNP þ4845 is 0.64 and allele T is 0.36 in the healthy Caucasian population.21 IL1A SNP
889 (C4T) is in the promoter region between the activation protein 2 binding site and the glucocorticoid responsive element. IL1A VNTR consists of 5, 8, 9, 12, 15 or 18 tandem repeats (46 bp). Each of the repeat sequences contains binding sites for transcription factor SP1, an imperfect copy of a viral enhancer element as well as an inverse and complementary sequence of a glucocorticoid-responsive element.22 The IL1B gene, like IL1A, has seven exons and six introns. The promoter region of IL1B contains a clear TATA box. IL1B regulatory regions can be found distributed over several thousand base pairs upstream and a few base pairs downstream from the transcriptional start site. The most studied SNPs in the IL1B gene are rs1143634 (at position þ3954), rs1143627 (at position
31) and rs16944 (at position
511). IL1B SNP
31, a TATA box polymorphism, is in 100% linkage disequilibrium in Caucasian population with IL1B SNP-511. ILB SNP þ3954 is located in exon 5. The base exchange (T4C) does not cause an amino acid change. The frequency of allele T is 0.73 and allele C is 0.27 in the healthy Caucasian population.23 The IL1RN gene consists of six exons, of which four to six are used when alternative forms of IL-1Ra are formed. These forms are achieved by alternative splicing and variable promoter usage. The most intensively studied polymorphisms of IL1RN are a penta-allelic 86-bp tandem repeat (VNTR) in intron 2 of the sIL1Ra gene (or in intron 3 of the extended gene containing the additional 50 exon encoding icIL1RaI) and rs419598 (at position

100

Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 7.2 Pairwise linkage disequilibrium represented as D0 in healthy Caucasians, MAF  0.2.19 SNPs [rs18000587 (at position
889), rs1894399 (þ1893), rs2071373 (þ1986), rs17561 (þ4845), and rs3783543 (þ5418)] form a haplotype block. The block was determined using the HaploViewprogram.39

þ2018 in exon 2 of the sIL1Ra gene). The synonymous SNP at þ2018 is in 100% linkage disequilibrium in the Caucasian population with IL1RN VNTR. IL1RN VNTR consists of two to six 86 bp tandem repeats. The most common allele has been termed allele one (4 repeats), allele two has 2 repeats, allele three 5 repeats, allele four 3 repeats, and allele five 6 repeats. The frequency of allele 1 is 0.74 and of allele 2 is 0.21 in healthy Caucasian population.24

7.7

EFFECT OF GENE POLYMORPHISMS ON IL-1 AND IL-1Ra PROTEIN LEVELS

Several studies have shown that both the IL1RN VNTR and the IL1B SNPþ3954 have biological relevance with regard to regulation of the production of IL-1b and IL-1Ra. In vitro studies have indicated that IL1RN*2 is associated with increased production of sIL-1Ra protein in monocytes.23,25,26 In umbilical vein and coronary artery endothelial cells the same allele has been shown to be associated with low production of sIL-1Ra.4 In vitro studies have shown that IL1RN*2 is associated with high production of sIL-1Ra but also with reduced expression of the intracellular levels of icIL-1RaI mRNA.25, 27 According to these studies the impact of IL1RN VNTR depends on the mRNA splice variants measured. However, contradictory results have been reported. IL1RN*2 was associated with reduced levels of IL-1Ra protein and IL1RN mRNA in colonic mucosa in patients with ulcerative colitis and healthy controls.28,29 The polymorphisms of IL1B SNP-511 and IL1B SNPþ3954 also participate in the regulation of IL1Ra in vivo production and show a cooperative effect with IL1RN*2.23 It seems that complex relationships may exist between the IL1RN*2 variant and other

The IL1 Cluster

101

polymorphisms in IL1RN or within neighboring genes. These complex relations could affect the absolute levels of IL-1Ra protein. There is contradictory data regarding the functional effects of IL1RN*2, IL1B SNPþ3954, and IL1B SNP-511 on IL-1b production. Both high30 and low27 IL-1b production in mononuclear cell cultures have been observed in IL1RN*2 carriers. Similarly, allele C of IL1B SNPþ3954 is associated with high levels31 as well as slightly lower levels30 of IL-1b production. Likewise, variation in the results concerning alleles of IL1B SNP-511 on IL-1b production has also been reported.30,32,33 The discrepancies observed may be attributable to differences in methodology and variation in the cell samples. IL1RN*2 is also associated with low levels of IL-1a production.25 The rare allele combination of IL1A SNP-889 allele T and IL1B SNP-511 allele T is associated with high levels of IL-1b production in healthy individuals.33 In patients with severe periodontal disease, IL1A SNP-889 allele T has been linked to high levels of IL-1a measured in gingival crevicular fluid.34 The 4 bp deletion allele in intron 6 of IL1A, TN7(delTTCA)A, is associated with high amount of IL1a protein synthesized in mitogen-stimulated lymphocytes from healthy subjects in vitro.35 The protein levels of IL-1 may be affected by IL-1Ra production or protein interaction. To avoid this problem Kimura et al.36 performed an allelic specific transcript quantification assay for IL1B SNP-31 and IL1B SNPþ3954. They showed that expression of allele T of IL1B SNP-31, which is in almost 100% LD with IL1B SNP-511, was 2.2 times higher than that of allele C, whereas the IL1B SNPþ3954 polymorphism did not affect the transcription levels of IL-1b. Taken together, these data suggest that it is difficult to evaluate the effect of a single marker polymorphism on an accurate amount of protein levels.

7.8 DISEASE ASSOCIATIONS OF SINGLE MARKER POLYMORPHISM IL-1 has an important proinflammatory role in many human diseases. The balance between IL-1 and IL-1Ra has been shown to be important in the phenotypic expression of diseases like arthritis, inflammatory bowel disease, granulomatous and fibrotic lung disorders, kidney, liver and pancreas diseases, graft-versus-host disease, leukemia, cancer, osteoporosis, diabetes as well as diseases of the central nervous system, and infectious and arterial diseases. Examples of positive disease associations of single marker polymorphisms in the IL1 gene cluster are presented in Table 7.2. The most studied polymorphism is IL1RN VNTR. In many cases, IL1RN*2 is associated with a variety of inflammatory disease in case-control studies. Earlier data suggests that subjects carrying the IL1RN*2 have decreased production of icIL1Ra1 with or without increased IL-1b production. The imbalance between both may predispose to a variety of human diseases, especially diseases that are manifest in cells of epithelial or endothelial cell origin (see above).

7.9 HAPLOTYPES AND LINKAGE DISEQUILIBRIUM WITHIN IL1 CLUSTER The results of single marker association should be interpreted with caution. The biological effect of one single marker may, for instance, be due to linkage disequilibrium with a functional polymorphism within the same gene or in neighboring genes. Haplotype association studies can help to avoid the pitfalls of single marker analysis. Likewise, associations arising from haplotype analysis may be stronger than those seen with individual SNP, which could imply that polymorphic sites act in combination. Some information on linkage disequilibrium (LD) within IL1 cluster genes is presented here. More information

59 (severe) þ 18 (mild) 102 þ 46 90 þ 40 90 þ 261 52 þ 47 131* 188 þ 482 188 þ 115 151 þ 247 151 þ 247 245 þ 405 151 þ 247 556 þ 827 14 þ 20 55*þ 85 312 þ 171 128 þ 125** 95 þ 96** 179 þ 99 179 þ 99 20 þ 380 366 þ 429 366 þ 429 158 þ 261 52 þ 200 52 þ 200 43 þ 98 105 þ 91 167 þ 400 167 þ 400 78 þ 261 96 þ 132 96 þ 132

IL1RN VNTR49 IL1RN VNTR50 IL1RN VNTR51 IL1RN VNTR52 IL1B SNPþ395453 IL1RN VNTR54 IL1B SNPþ395455 IL1RN VNTR56 IL1RN VNTR21 IL1A SNPþ484521 IL1B SNP-51157 IL1B SNPþ395421 IL1RN VNTR58 IL1B SNP-51159 IL1RN VNTR60 IL1B SNPþ395461 IL1RN VNTR62 IL1B SNPþ395463 IL1RN VNTR64 IL1 B SNPþ395464 IL1 B SNP-51165 IL1RN VNTR66 IL1B SNPþ395466 IL1RN VNTR67 IL1RN VNTR68 IL1B SNP-51168 IL1RN VNTR69 IL1RN VNTR70 IL1RN VNTR71 IL1B SNP-51171 IL1RN VNTR72 IL1B SNP-51173 IL1B SNPþ395473

Acute graft-versus-host disease Alcoholic hepatic fibrosis Alcoholism Alopecia areata

Inflammatory bowel disease

Henoch–Scho¨nlein Idiopathic recurrent miscarriage IgA nephropathy

Grave’s disease Hepatitis C virus–induced cirrhosis

Epstein–Barr virus infection Gastric cancer

Duodenal ulcer disease

Diabetic nephropathy

Diabetes

Coronary atherosclerosis

Alopecia areata (patchy) Alzheimer’s disease Ankylosing spondylitis Atopic diseases

Study Size Patients vs. Controls

Associated Polymorphism

Disease

TABLE 7.2 Examples of Positive Disease Associations of Polymorphisms in IL1 Gene Cluster

Allele 2 Allele 1 Allele 1 Allele 2 Heterozygote Allele 1 Allele T Allele 2 Allele 2 Allele G Heterozygote Allele C Allele 2 Allele C Genotype a1a1 Allele T Allele 2 Allele T Allele 2 Allele T Allele T Allele 2 Allele T Allele 2 Allele 2 Allele T Allele 2 Allele 2 Allele 2 Allele T Allele 2 Allele T Allele C

Risk Allele/Genotype

Protection Susceptibility Susceptibility Severity Severity Susceptibility Delay of onset Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Protection Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Progression Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Susceptibility Severity Susceptibility

Type of Association

102 Cytokine Gene Polymorphisms in Multifactorial Conditions

IL1RN VNTR74 IL1RN VNTR75 IL1RN VNTR76 IL1A SNPþ484577 IL1B SNPþ395477 IL1RN VNTR78 IL1B SNPþ395478 IL1B SNPþ395479 IL1A SNPþ484580 IL1RN VNTR81 IL1B SNP-51182 IL1RN VNTR83 IL1A SNPþ484584 IL1B SNPþ395484 IL1RN VNTR85 IL1RN VNTR86 IL1RN VNTR87 IL1RN VNTR87 IL1RN VNTR88 IL1B SNP-51188 IL1RN VNTR89 IL1RN VNTR90 IL1RN VNTR91 IL1RN VNTR92 IL1RN VNTR93 IL1B SNP-51194 IL1B SNPþ395494 IL1A SNP-88995 IL1A SNPþ484595 IL1RN VNTR26 IL1B SNPþ395426 IL1RN VNTR96 IL1RN VNTR97 185 þ 168 250 þ 471 78 þ 261 188 (mild) þ 188 (controls) 188 (mild) þ 188 (severe) 148 þ 98 148 þ 98 107 þ 82 35 þ 208 389 þ 389 52 þ 73 47 þ 97 44 þ 46*** 44 þ 46*** 92 þ 79 133 þ 112 191 þ 331 80 þ 331 87 þ 400 87 þ 400 67 þ 104 154 þ 202 93 þ 261 36 þ 100 81 þ 261 114 þ 392 114 þ 392 60 þ 70 60 þ 70 89 þ 114 89 þ 114 68 þ 228 68 þ 343 Allele 2 Allele 1 Allele 2 Allele T Heterozygote Allele 2 Allele C Allele T Allele G Allele 1 Allele C Allele 1 Allele 2 Allele 2 Allele 2 Allele 2 Allele 2 Allele 2 Allele 2 Allele T Allele 2 Allele 2 Allele 2 Allele 2 Allele 2 Allele C Allele T Allele C Allele G Allele 2 Allele C Allele 2 Allele 2

Susceptibility Susceptibility Severity Susceptibility Severity Severity Severity Susceptibility Susceptibility Susceptibility Susceptibility Protection Severity Severity Susceptibility Susceptibility Severity þ susceptibility Susceptibility Susceptibility Susceptibility Protection Severity Susceptibility Severity Severity Protection Protection Susceptibility þ severity Susceptibility þ severity Susceptibility Susceptibility Protection Susceptibility þ severity

*Parent–offspring trios; ** Diabetic patients with or without nephropathy; *** Controls: healthy to mild disease, patients: moderate to severe disease; PTCA (percutaneous transluminal coronary angioplasty); atopic diseases (atopic eczema, allergic rhinoconjunctivitis, and bronchial asthma); IL1A SNP-889 (rs18000587), IL1A SNPþ4845 (rs17561), IL1B SNP
511 (rs16944), IL1B SNPþ3954 (rs1143634).

Vulvar carcinogenesis Vulvar vestibulitis

Tuberculosis

Systemic sclerosis

Restenosis, protection after PTCA Rheumatoid arthritis Sepsis Sjo¨gren’s syndrome Systemic lupus erythematosus

Puumala hantavirus infection

Polymyalgia rheumatica Pre-eclampsia Psoriasis, early onset late onset

Myasthenia gravis Nasal polyposis Osteoporosis Parkinson’s disease Periodontitis

Multiple sclerosis

Juvenile chronic arthritis Juvenile idiopathic inflammatory myopathies Lichen sclerosus Malaria

The IL1 Cluster 103

104

Cytokine Gene Polymorphisms in Multifactorial Conditions

on LD and haplotypes within IL1 cluster is found in databases (http://www.hapmap.org/; http://pga.gs.washington.edu). The intragenic LD is usually high. For example, the LD between several polymorphic markers within the IL1A and IL1RN genes is very strong.37,38 Figure 7.2 shows the linkage disequilibrium values (D0 ) in IL1A between 8 SNPs (
889, þ1893, þ1986, þ4845, þ5418, þ6630, þ6673, and þ10 897) in healthy Caucasians. Haplotypes of these SNPs were inferred using the Haploview program.39 The three most common haplotypes were CGCGTGCA, TATTCAAG, and CGTGCGAA. The total frequency of these haplotypes was close to 90% among healthy Caucasians.19 The haplotypes for African American and European American mixed populations can be found in the SeattleSNP database for all IL1 cluster genes, except IL1F8 (http://pga.gs.washington.edu). LD varies within the 360-kb region of the IL1 gene cluster. It has been shown that at distances over 50 kb there is generally a good correlation between LD and physical distance. However, at distances less than 50 kb this relationship breaks down.18 Linkage disequilibrium has been shown to decrease within IL1A between intron 5 and intron 619 and in IL1B between IL1B SNPþ3954 and IL1B SNP
31, spanning a distance of 4.2 kb.36,38 In the case of IL1B, the weak intragenic LD is due to the reduction in the power when disequilibrium is in the negative direction but it may also reflect the age of the polymorphisms.41,42 Also linkage decreases in a large approximately 300 kb intergenic region between IL1A and IL1RN.40 LD differs between populations. It is a generally accepted observation that younger populations (Caucasians) have greater LD over the same genomic regions compared to an older population (Africans). Specifically, at 350 kb Caucasians had levels of LD comparable to those observed in African Americans at 50 kb.43,44 Among Caucasians LD is preserved relatively high from IL1F10 exon 4 to the IL1RN 30 flanking region (area of 60 kb) and from IL1A to 30 end of IL1RN (350 kb), while among African Americans, following a 37 kb region of LD, a dramatic drop occurs between the IL1RN promoter and intron icIL1RaI long (an inter-SNP distance of 6 kb).40 This finding may reflect inherent variability in measures of LD at shorter genomic intervals.42 It has been hypothesized that mutation, genetic drift, gene conversion, and admixture may play a greater role at a shorter distance than recombination in larger genomic segments.18,43 In multifactorial diseases, the relevance of single markers is usually ambiguous, since they might belong to disease-associated haplotypes, and may also interact with other gene polymorphisms. The IL1 cluster is linked to multifactorial diseases such as asthma,45 atopy,21 ankylosing spondylitis,46,47 knee osteoarthritis,48 and end-stage renal disease.35,40 These studies 21,40,45–48 show that haplotypes in the IL1 cluster increase the disease risk but they do not exclude the possibility that the results of IL1 cluster genes may also be due to LD with neighboring loci.

REFERENCES 1. Dunn, E. et al., Annotating genes with potential roles in the immune system: six new members of the IL-1 family. Trends Immunol., 22, 533, 2001. 2. Dinarello, C. A., Biologic basis for interleukin-1 in disease. Blood, 87, 2095, 1996. 3. Dinarello, C. A., The interleukin-1 family: 10 years of discovery. Faseb J., 8, 1314, 1994. 4. Dewberry, R. et al., Interleukin-1 receptor antagonist expression in human endothelial cells and atherosclerosis. Arterioscler. Thromb. Vasc. Biol., 20, 2394, 2000. 5. Arend, W. P., The balance between IL-1 and IL-1Ra in disease. Cytokine Growth Factor Rev., 13, 323, 2002.

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6. Debets, R. et al., Two novel IL-1 family members, IL-1 delta and IL-1 epsilon, function as an antagonist and agonist of NF-kappa B activation through the orphan IL-1 receptor-related protein 2. J. Immunol., 167, 1440, 2001. 7. Bensen, J. T. et al., Identification of a novel human cytokine gene in the interleukin gene cluster on chromosome 2q12–14. J. Interferon Cytokine Res., 21, 899, 2001. 8. Mulero, J. J. et al., IL1HY1: A novel interleukin-1 receptor antagonist gene. Biochem. Biophys. Res. Commun., 263, 702, 1999. 9. Towne, J. E. et al., Interleukin (IL)-1F6, IL-1F8, and IL-1F9 signal through IL-1Rrp2 and IL-1RAcP to activate the pathway leading to NF-kappaB and MAPKs. J. Biol. Chem., 279, 13677, 2004. 10. Lin, H. et al., Cloning and characterization of IL-1HY2, a novel interleukin-1 family member. J. Biol. Chem., 276, 20597, 2001. 11. Kumar, S. et al., Identification and initial characterization of four novel members of the interleukin-1 family. J. Biol. Chem., 275, 10308, 2000. 12. Voronov, E. et al., IL-1 is required for tumor invasiveness and angiogenesis. Proc. Natl. Acad. Sci. USA., 100, 2645, 2003. 13. Takahashi, J. L. et al., Interleukin-1beta promotes oligodendrocyte death through glutamate excitotoxicity. Ann. Neurol., 53, 588, 2003. 14. Samad, T. A. et al., Interleukin-1beta-mediated induction of Cox-2 in the CNS contributes to inflammatory pain hypersensitivity. Nature, 410, 471, 2001. 15. Werman, A. et al., The precursor form of IL-1alpha is an intracrine proinflammatory activator of transcription. Proc. Natl. Acad. Sci. USA., 101, 2434, 2004. 16. Gao, W. et al., Innate immunity mediated by the cytokine IL-1 homologue 4 (IL-1H4/IL-1F7) induces IL-12-dependent adaptive and profound antitumor immunity. J. Immunol., 170, 107, 2003. 17. Nicklin, M. J. et al., A sequence-based map of the nine genes of the human interleukin-1 cluster. Genomics, 79, 718, 2002. 18. Cox, A. et al., An analysis of linkage disequilibrium in the interleukin-1 gene cluster, using a novel grouping method for multiallelic markers. Am. J. Hum. Genet., 62, 1180, 1998. 19. Pessi, T., unpublished data, 2005. 20. van den Velden, P. A. and Reitsma, P. H., Amino acid dimorphism in IL1A is detectable by PCR amplification. Hum. Mol. Genet., 2, 1753, 1993. 21. Pessi, T. et al., Common IL-1 complex haplotype is associated with an increased risk of atopy. J. Med. Genet., 40, e66, 2003. 22. Bailly, S., di Giovine, F. S. and Duff, G. W., Polymorphic tandem repeat region in interleukin-1 alpha intron 6. Hum. Genet., 91, 85, 1993. 23. Hurme, M. and Santtila, S., IL-1 receptor antagonist (IL-1Ra) plasma levels are co-ordinately regulated by both IL-1Ra and IL-1beta genes. Eur. J. Immunol., 28, 2598, 1998. 24. Tarlow, J. K. et al., Polymorphism in human IL-1 receptor antagonist gene intron 2 is caused by variable numbers of an 86-bp tandem repeat. Hum. Genet., 91, 403, 1993. 25. Danis, V. A. et al., Cytokine production by normal human monocytes: inter-subject variation and relationship to an IL-1 receptor antagonist (IL-1Ra) gene polymorphism. Clin. Exp. Immunol., 99, 303, 1995. 26. Wilkinson, R. J. et al., Influence of polymorphism in the genes for the interleukin (IL)-1 receptor antagonist and IL-1beta on tuberculosis. J. Exp. Med., 189, 1863, 1999. 27. Vamvakopoulos, J., Green, C., and Metcalfe, S., Genetic control of IL-1beta bioactivity through differential regulation of the IL-1 receptor antagonist. Eur. J. Immunol., 32, 2988, 2002. 28. Carter, M. J. et al., Functional correlates of the interleukin-1 receptor antagonist gene polymorphism in the colonic mucosa in ulcerative colitis. Genes Immun., 5, 8, 2004. 29. Tountas, N. A. et al., Functional and ethnic association of allele 2 of the interleukin-1 receptor antagonist gene in ulcerative colitis. Gastroenterology, 117, 806, 1999. 30. Santtila, S., Savinainen, K., and Hurme, M., Presence of the IL-1RA allele 2 (IL1RN*2) is associated with enhanced IL-1beta production in vitro. Scand. J. Immunol., 47, 195, 1998. 31. Pociot, F. et al., A TaqI polymorphism in the human interleukin-1 beta (IL-1beta) gene correlates with IL-1beta secretion in vitro. Eur. J. Clin. Invest., 22, 396, 1992.

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32. Hwang, I. R. et al., Effect of interleukin 1 polymorphisms on gastric mucosal interleukin-1 beta production in Helicobacter pylori infection. Gastroenterology, 123, 1793, 2002. 33. Hulkkonen, J., Laippala, P. and Hurme, M., A rare allele combination of the interleukin-1 gene complex is associated with high interleukin-1 beta plasma levels in healthy individuals. Eur. Cytokine Netw., 11, 251, 2000. 34. Shirodaria, S. et al., Polymorphisms in the IL-1A gene are correlated with levels of interleukin-1 alpha protein in gingival crevicular fluid of teeth with severe periodontal disease. J. Dent. Res., 79, 1864, 2000. 35. Bensen, J. T. et al., Association of an IL-1A 30 UTR polymorphism with end-stage renal disease and IL-1 alpha expression. Kidney Int., 63, 1211, 2003. 36. Kimura, R. et al., Cis-acting effect of the IL1B C-31T polymorphism on IL-1 beta mRNA expression. Genes Immun., 5, 572, 2004. 37. Clay, F. E. et al., Novel interleukin-1 receptor antagonist exon polymorphisms and their use in allele-specific mRNA assessment. Hum. Genet., 97, 723, 1996. 38. Guasch, J. F., Bertina, R. M. and Reitsma, P. H. Five novel intragenic dimorphisms in the human interleukin-1 genes combine to high informativity. Cytokine, 8, 598, 1996. 39. Barrett, J. C. et al., Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics, 21, 263, 2005. 40. Bensen, J. T. et al., Nucleotide variation, haplotype structure, and association with end-stage renal disease of the human interleukin-1 gene cluster. Genomics, 82, 194, 2003. 41. Thompson, E. A. et al., The detection of linkage disequilibrium between closely linked markers: RFLPs at the AI-CIII apolipoprotein genes. Am. J. Hum. Genet., 42, 113, 1988. 42. Jorde, L. B. et al., Linkage disequilibrium predicts physical distance in the adenomatous polyposis coli region. Am. J. Hum. Genet., 54, 884, 1994. 43. Pritchard, J. K., and Przeworski, M., Linkage disequilibrium in humans: models and data. Am. J. Hum. Genet., 69, 1, 2001. 44. Jorde, L. B. et al., Gene mapping in isolated populations: new roles for old friends? Hum. Hered., 50, 57, 2000. 45. Gohlke, H. et al., Association of the interleukin-1 receptor antagonist gene with asthma. Am. J. Respir. Crit. Care Med., 169, 1217, 2004. 46. Maksymowych, W. P. et al., High-throughput single-nucleotide polymorphism analysis of the IL1RN locus in patients with ankylosing spondylitis by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry. Arthritis Rheum., 48, 2011, 2003. 47. Timms, A. E. et al., The interleukin 1 gene cluster contains a major susceptibility locus for ankylosing spondylitis. Am. J. Hum. Genet., 75, 587, 2004. 48. Loughlin, J. et al., Association of the interleukin-1 gene cluster on chromosome 2q13 with knee osteoarthritis. Arthritis Rheum., 46, 1519, 2002. 49. Cullup, H. et al., Donor interleukin 1 receptor antagonist genotype associated with acute graft-versus-host disease in human leucocyte antigen-matched sibling allogeneic transplants. Br. J. Haematol., 113, 807, 2001. 50. Takamatsu, M. et al., Correlation of a polymorphism in the interleukin-1 receptor antagonist gene with hepatic fibrosis in Japanese alcoholics. Alcohol Clin. Exp. Res., 22, 141S, 1998. 51. Pastor, I. J. et al., Polymorphism in the interleukin-1 receptor antagonist gene is associated with alcoholism in Spanish men. Alcohol Clin. Exp. Res., 24, 1479, 2000. 52. Tarlow, J. K. et al., Severity of alopecia areata is associated with a polymorphism in the interleukin-1 receptor antagonist gene. J. Invest. Dermatol., 103, 387, 1994. 53. Galbraith, G. M. et al., Contribution of interleukin 1beta and KM loci to alopecia areata. Hum. Hered., 49, 85, 1999. 54. Barahamani, N. et al., Interleukin-1 receptor antagonist allele 2 and familial alopecia areata. J. Invest. Dermatol., 118, 335, 2002. 55. Sciacca, F. L. et al., Interleukin-1B polymorphism is associated with age at onset of Alzheimer’s disease. Neurobiol. Aging, 24, 927, 2003. 56. McGarry, F. et al., A polymorphism within the interleukin 1 receptor antagonist (IL-1Ra) gene is associated with ankylosing spondylitis. Rheumatology (Oxford), 40, 1359, 2001.

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57. Karjalainen, J. et al., The IL-1beta genotype carries asthma susceptibility only in men. J. Allergy Clin. Immunol., 109, 514, 2002. 58. Francis, S. E. et al., Interleukin-1 receptor antagonist gene polymorphism and coronary artery disease. Circulation, 99, 861, 1999. 59. Lehtimaki, T. et al., Interleukin-1B genotype modulates the improvement of coronary artery reactivity by lipid-lowering therapy with pravastatin: a placebo-controlled positron emission tomography study in young healthy men. Pharmacogenetics, 13, 633, 2003. 60. Pociot, F. et al., Genetic susceptibility markers in Danish patients with type 1 (insulindependent) diabetes–evidence for polygenicity in man. Danish Study Group of Diabetes in Childhood. Autoimmunity, 19, 169, 1994. 61. Krikovsky, D. et al., Genetic polymorphism of interleukin-1beta is associated with risk of type 1 diabetes mellitus in children. Eur. J. Pediatr., 161, 507, 2002. 62. Blakemore, A. I. et al., Interleukin-1 receptor antagonist allele (IL1RN*2) associated with nephropathy in diabetes mellitus. Hum. Genet., 97, 369, 1996. 63. Loughrey, B. V. et al., An interluekin 1B allele, which correlates with a high secretor phenotype, is associated with diabetic nephropathy. Cytokine, 10, 984, 1998. 64. Garcia-Gonzalez, M. A. et al., The polymorphic IL-1B and IL-1RN genes in the aetiopathogenesis of peptic ulcer. Clin. Exp. Immunol., 125, 368, 2001. 65. Hurme, M. and Helminen, M., Polymorphism of the IL-1 gene complex in Epstein-Barr virus seronegative and seropositive adult blood donors. Scand. J. Immunol., 48, 219, 1998. 66. El-Omar, E. M. et al., Interleukin-1 polymorphisms associated with increased risk of gastric cancer. Nature, 404, 398, 2000. 67. Blakemore, A. I. et al., Association of Graves’ disease with an allele of the interleukin-1 receptor antagonist gene. J. Clin. Endocrinol Metab., 80, 111, 1995. 68. Bahr, M. J. et al., Cytokine gene polymorphisms and the susceptibility to liver cirrhosis in patients with chronic hepatitis C. Liver Int., 23, 420, 2003. 69. Liu, Z. H. et al., Interleukin-1 receptor antagonist allele: is it a genetic link between Henoch-Schonlein nephritis and IgA nephropathy? Kidney Int., 51, 1938, 1997. 70. Unfried, G. et al., Interleukin 1 receptor antagonist polymorphism in women with idiopathic recurrent miscarriage. Fertil Steril., 75, 683, 2001. 71. Syrjanen, J. et al., Polymorphism of the cytokine genes and IgA nephropathy. Kidney Int., 61, 1079, 2002. 72. Mansfield, J. C. et al., Novel genetic association between ulcerative colitis and the anti-inflammatory cytokine interleukin-1 receptor antagonist. Gastroenterology, 106, 637, 1994. 73. Nemetz, A. et al., IL1B gene polymorphisms influence the course and severity of inflammatory bowel disease. Immunogenetics, 49, 527, 1999. 74. Vencovsky, J. et al., Higher frequency of allele 2 of the interleukin-1 receptor antagonist gene in patients with juvenile idiopathic arthritis. Arthritis Rheum. 44, 2387, 2001. 75. Rider, L. G. et al., Polymorphisms in the IL-1 receptor antagonist gene VNTR are possible risk factors for juvenile idiopathic inflammatory myopathies. Clin. Exp. Immunol., 121, 47, 2000. 76. Clay, F. E. et al., Interleukin 1 receptor antagonist gene polymorphism association with lichen sclerosus. Hum. Genet., 94, 407, 1994. 77. Walley, A. J. et al., Interleukin-1 gene cluster polymorphisms and susceptibility to clinical malaria in a Gambian case-control study. Eur. J. Hum. Genet., 12, 132, 2004. 78. Schrijver, H. M. et al., Association of interleukin-1beta and interleukin-1 receptor antagonist genes with disease severity in MS. Neurology, 52, 595, 1999. 79. Huang, D. et al., Polymorphisms in IL-1beta and IL-1 receptor antagonist genes are associated with myasthenia gravis. J. Neuroimmunol., 81, 76, 1998. 80. Karjalainen, J. et al., The IL1A genotype is associated with nasal polyposis in asthmatic adults. Allergy, 58, 393, 2003. 81. Langdahl, B. L. et al., Osteoporotic fractures are associated with an 86-base pair repeat polymorphism in the interleukin-1–receptor antagonist gene but not with polymorphisms in the interleukin-1beta gene. J. Bone Miner. Res., 15, 402, 2000.

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82. Mattila, K. M. et al., Association of an interleukin 1B gene polymorphism (
511) with Parkinson’s disease in Finnish patients. J. Med. Genet., 39, 400, 2002. 83. Tai, H. et al., Association of interleukin-1 receptor antagonist gene polymorphisms with early onset periodontitis in Japanese. J. Clin. Periodontol., 29, 882, 2002. 84. McDevitt, M. J. et al., Interleukin-1 genetic association with periodontitis in clinical practice. J. Periodontol., 71, 156, 2000. 85. Boiardi, L. et al., Interleukin-1 cluster and tumor necrosis factor-alpha gene polymorphisms in polymyalgia rheumatica. Clin. Exp. Rheumatol., 18, 675, 2000. 86. Faisel, F. et al., Polymorphism in the interleukin 1 receptor antagonist gene in women with preeclampsia. J. Reprod. Immunol., 60, 61, 2003. 87. Tarlow, J. K. et al., Association between interleukin-1 receptor antagonist (IL-1ra) gene polymorphism and early and late-onset psoriasis. Br. J. Dermatol., 136, 147, 1997. 88. Makela, S. et al., Polymorphism of the cytokine genes in hospitalized patients with Puumala hantavirus infection. Nephrol. Dial. Transplant., 16, 1368, 2001. 89. Francis, S. E. et al., Interleukin 1 receptor antagonist gene polymorphism and restenosis after coronary angioplasty. Heart, 86, 336, 2001. 90. Cvetkovic, J. T. et al., Susceptibility for and clinical manifestations of rheumatoid arthritis are associated with polymorphisms of the TNF-alpha, IL-1beta, and IL-1Ra genes. J. Rheumatol., 29, 212, 2002. 91. Fang, X. M. et al., Comparison of two polymorphisms of the interleukin-1 gene family: interleukin-1 receptor antagonist polymorphism contributes to susceptibility to severe sepsis. Crit. Care Med., 27, 1330, 1999. 92. Perrier, S. et al., IL-1 receptor antagonist (IL-1RA) gene polymorphism in Sjogren’s syndrome and rheumatoid arthritis. Clin. Immunol. Immunopathol., 87, 309, 1998. 93. Blakemore, A. I. et al., Interleukin-1 receptor antagonist gene polymorphism as a disease severity factor in systemic lupus erythematosus. Arthritis Rheum., 37, 1380, 1994. 94. Camargo, J. F. et al., Interleukin-1beta polymorphisms in Colombian patients with autoimmune rheumatic diseases. Genes Immun., 5, 609, 2004. 95. Kawaguchi, Y. et al., Association of IL1A gene polymorphisms with susceptibility to and severity of systemic sclerosis in the Japanese population. Arthritis Rheum., 48, 186, 2003. 96. Grimm, C. et al., A polymorphism of the interleukin-1 receptor antagonist plays a prominent role within the interleukin-1 gene cluster in vulvar carcinogenesis. Gynecol. Oncol., 92, 936, 2004. 97. Jeremias, J., Ledger, W. J., and Witkin, S. S., Interleukin 1 receptor antagonist gene polymorphism in women with vulvar vestibulitis. Am. J. Obstet. Gynecol., 182, 283, 2000.

8

IL-2 Biology and Polymorphisms in Multifactorial Conditions Fuencisla Matesanz, Marı´a Fedetz, and Antonio Alcina

CONTENTS 8.1 8.2

IL-2 as a Bi-Functional Cytokine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mouse IL-2 Polymorphisms and Autoimmune Diseases . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1 Mouse IL-2 Allotypes and Autoimmune Pathology . . . . . . . . . . . . . . . . . . . . . . 8.2.2 Molecular Mechanisms Involving a Mouse IL-2 Allotype in Autoimmunity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Human IL2/IL2R Polymorphisms in Multifactorial Conditions . . . . . . . . . . . . . . . . . . 8.3.1 Human IL2 Polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.1.1 The 330 Promoter (rs2069762) SNP: Effect on IL-2 Expression 8.3.1.2 The 330 (rs2069762) SNP and Disease Association Studies . . . . 8.3.2 Human IL2 Receptor Alpha Gene Polymorphisms (hIL2RA) . . . . . . . . . . . . 8.3.3 Human IL2 Receptor Beta Gene Polymorphisms (hIL2RB) . . . . . . . . . . . . . . 8.3.4 IL2 Receptor Gamma Chain Gene Polymorphisms (hIL2RG). . . . . . . . . . . . 8.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

109 110 110 111 111 111 112 114 115 115 115 115 116

8.1 IL-2 AS A BI-FUNCTIONAL CYTOKINE Interleukin 2 (IL-2) is involved in the expansion of the immune system as a potent T cell growth factor and on the other hand is also a major contraction factor implicated in apoptosis or activation-induced cell death (AICD) by FAS- and tumor necrosis factor (TNF)-dependent pathways.1 The activity of IL-2 is essential for the generation, expansion, survival, and functioning of CD4þ CD25þ regulatory T cells (Treg).2–4 It is known that impaired production of Treg cells is sufficient to account for the unexpected lethal autoimmunity that is associated with IL-2-, IL-2Ra- and IL-2Rb-deficient mice.3,5 Treg cells have emerged as one of the major populations that suppress TCR-induced proliferation of CD4 and CD8 T cells in vitro and in vivo and have been shown to prevent autoimmune diseases, allograft rejection, and to down-regulate immune responses against antigens and pathogens.6–8 In vitro studies have shown that Treg cells fail to proliferate when stimulated via their TCR even in the presence of a co-stimulatory signal by anti-CD28 due to a failure to transcribe their IL2 gene. Therefore, they need exogenous IL-2 (paracrine), although about ten-fold higher concentrations of IL-2 are required to generate a level of proliferation equivalent to that seen with CD4þCD25
T cells and higher level for induction of suppressor activity. When the suppressive activities of cells grown in the presence of different cytokines are compared, only cells grown in the presence of IL-2 and IL-4 were potent suppressor cells. Nevertheless, promotion of T cell proliferation and activation of several effector cells is the rational base for the pharmacological utilization of IL-2 in cancer patients, especially those with metastatic melanoma, acute myelogenous leukaemia, 109

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or metastatic renal-cell carcinoma, as well as in renal and heart transplant recipients. IL-2 is used, in addition, to boost immunity in individuals infected with HIV and in patients with AIDS.

8.2 8.2.1

MOUSE IL-2 POLYMORPHISMS AND AUTOIMMUNE DISEASES MOUSE IL-2 ALLOTYPES PATHOLOGY

AND

AUTOIMMUNE

The original IL-2 sequence of the mouse was obtained from cDNA clones by two laboratories from B10Br,9 and from C57BL/610 mice. The genomic sequence was obtained from the BALB/C6 mouse strain.11 These three sequences were identical in the coding region. Later, a new IL-2 sequence obtained from RF/J strain of mice12 showed several nucleotide differences, all of them within the first exon of the IL-2 gene, encoding extensive polymorphism at the amino-terminal region. Finally, six different IL-2 sequences were obtained from different mouse strains.13,14 As can be seen in Figure 8.1, apart from punctual codon changes, major differences include an expanding CAG codon (translated into glutamine) and the presence of the tetrapeptide P–T–S–S, repeated 1, 2, or 3.5 times, which is also present once in human IL-2 and includes an O-glycosylation site. Purified recombinant IL-2 proteins showed differences in growth-inducing activity on peripheral blood lymphocytes and the human T cell line Kit-225.14 No differences were observed in proliferative stimulation of CTLL-2 cells compared with a commercial IL-2 control except for the RF IL-2 which was less active.20 The RF IL-2 allotype is also found in autoimmune-prone NOD,15 MRL and SJL/J mice and is different from the ones found in non-autoimmune strains such as in C57BL/6, BALB/c, FVB/N, Spretus (SPRET/Ei), Cast, and Mus musculus (CZECHII/Ei). This autoimmune-associated allotype differs from the C57BL/6 allele by a single base change (T to C) that results in a serine-to-proline substitution in the sixth amino acid residue of the mature protein, as well as a duplication of a 12-bp segment of DNA that results in a 4-amino acid insertion, and a compensatory 12-bp deletion that results in a deletion of four glutamines from a stretch of 12 consecutive glutamines. These results raised the possibility that different alleles may have differences in biological activity that may determine susceptibility or resistance to disease. In mouse genetic analyses, a number of quantitative trait loci (QTL) controlling susceptibility to autoimmune ovarian dysgenesis (Aod), insulin-dependent diabetes (Idd) and experimental autoimmune encephalomyelitis (EAE), have been identified in susceptible strains of mice. One of the strongest non-MHC

FIGURE 8.1 Amino acid sequence comparison of several mouse-strain specific IL-2 allotypes. Alignment of amino acid sequences coded for by the 1st exon, including the signal peptide and the amino terminus of the mature protein separated with an asterisk. The sequences coded for by the other exons were identical among mouse strains (data not shown). For comparison, the sequences of human, porcine, and ovine IL-2 are also represented.

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susceptibility loci for type 1 diabetes, Idd3, has been shown to be due to the IL2 gene16,17 and co-localizes with the eae3 and Aod2 locus.18 The identification of a narrowly defined locus that has effects in both EAE and diabetes may indicate that there are individual genes that contribute to the susceptibility to several autoimmune diseases.

8.2.2 MOLECULAR MECHANISMS INVOLVING A MOUSE IL-2 ALLOTYPE IN AUTOIMMUNITY Two major factors have been considered to drive association one of the mouse IL-2 allotypes with several autoimmune manifestations and diseases: (1) Potential differential glycosylation at the tetrapeptide repeats in the amino terminus of IL-2 molecule;19 (2) Biological hypo-activity.20,21 1. Differential IL-2 glycosylation between resistant and susceptible strains of mice may account for the effect of IL-2 in IDDM, EAE, and D3Tx-induced autoimmunity in susceptible strains of mice. Mouse strains carrying an Idd3 susceptibility IL-2 allotype have a proline at position 6 of the mature IL-2 protein, whereas strains carrying an Idd3-protective allele have a serine.19 The electrophoretic migration of these IL-2 allotypes yields two distinct patterns, consistent with differences in glycosylation, that correlate with diabetes-resistance and susceptibility. These findings suggest that IL-2 variants may be functionally different. It is conceivable that glycosylation may affect the half-life of the molecule leading to a functional deficiency in circulating IL-2 or to the binding to other molecules as heparin sulfate. 2. The MRL mouse strain, like other autoimmune strains, NOD and SJL, has a hypoactive variant of the IL-2 gene, corresponding with the RF allotype in Figure 8.1, which is around five- to tenfold less active in supporting growth of the IL-2 dependent cell line, CTLL-2.20,21 Furthermore, poor TCR-mediated activation and resistance to AICD are common features of these autoimmune strains.22 Compared to FVB/N T cells (non-autoimmune), MRL T cells underexpressed procaspase-3 but over-expressed FLIPL. In addition, up-regulation of Bcl-xL, IL-2, and CD25 was diminished in MRL cells, suggesting inadequate T cell activation. Wild-type murine recombinant (mr)IL-2 added during the activation restored MRL apoptosis to the level of FVB/N.21 Supplementation with mrIL-2 influenced not only the resistance to AICD but also various parameters associated with activation, including CD25 expression, the up-regulation of Bcl-xL, and down-regulation of FLIPL, and increased expression of procaspase-3. Therefore, defective MRL T cell activation, in part due to hypo-active IL-2, underlies the impaired apoptosis of this strain and predisposition to develop autoimmune disease.

8.3 HUMAN IL2/IL2R POLYMORPHISMS IN MULTIFACTORIAL CONDITIONS (FIGURE 8.2) 8.3.1 HUMAN IL2 POLYMORPHISMS Unlike mouse, human IL-2 protein is not polymorphic or at least polymorphic variants have not been found to date. Evidence for different biological activities of IL-2 alleles has been presented in mice,14,20,21 but not in humans. Impaired T cell production of IL-2 is a characteristic of the pathogenesis underlying systemic lupus erythematosus (SLE)23

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Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 8.2 Schematic representation of the localization of human IL2 and IL2R polymorphisms. Vertical boxes crossing the long horizontal line represent exons. Scale bars and the number of SNPs found in these genes according to ‘‘NCBI SNP Human Genome’’ database are shown. Vertical fine bars represent position of polymorphisms that have been used in genetic studies, most of them indicated with the reference SNP cluster number ‘‘rs.’’ Polymorphisms with an asterisk indicated amino acid changes.

and juvenile chronic arthritis.24 Decreased IL-2 production by SLE T cells is the result of transcriptional repression of the IL-2 gene by decreased expression of the enhancers NF-kappa B and AP1 and the increased expression of the transcriptional repressor CREM.25 The IL2 gene maps to chromosome 4q26–q27. It contains 16 polymorphic (CA)n(CT)m mixed repeats located in the 30 flanking coding region of the gene (Figure 8.2).26,27 One SNP is located at the first exon (referred as rs2069760) at the þ114 position counted from the codon start site (css)28,29 and, because it does not change the amino acid sequence, does not modify any post-translational regulation. This first exon polymorphism has been very useful to quantify mRNA production from heterozygous samples and, hence, to quantify allelic expression and to determine the effects of other polymorphisms in the same DNA strand. Several SNPs at the 50 flanking coding region of the gene have been reported: the
330 SNP28 (rs2069762) has been the most extensively studied including its association with a panel of multifactorial conditions (see Table 8.1),30,31 and the
475 (rs2067006) and
631 (rs2069760) SNPs in multiple sclerosis (MS).32 8.3.1.1

The
330 Promoter (rs2069762) SNP: Effect on IL-2 Expression

Two groups have studied the effect of the
330 polymorphism in the IL-2 expression using different approaches. In one study,33 the G/G group produced over three times

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IL-2 Biology and Polymorphisms in Multifactorial Conditions

TABLE 8.1 Disease Association Studies with IL2/IL2R Polymorphisms Polymorphism/Disease

Association

IL2, (CA)n (CT)m 30 Flanking Coding Region Repeat Early-onset pauciarticular64,65 juvenile chronic arthritis Inflammatory bowel disease66 Rheumatoid arthritis67 Multiple sclerosis68,69 Ulcerative colitis66 Multiple sclerosis47

Type of Study/Noa

No No No No Weak No

CC/120:500 F/198 F/89 CC/183:275 F/34; CC/147:95

IL2, rs2069763 1st Exon Polymorphisma Multiple sclerosis (South Spain)30 Multiple sclerosis (Japan)43

No No

CC/173:153 CC/113:118

IL2, 50 Promoter Region Polymorphismsb rs2069762 Multiple sclerosis (South Spain)30 rs2069762 Multiple sclerosis (Japan)43 rs2069760 Multiple sclerosis32 rs2069762 Rheumatoid arthritis31 rs2069762 PsoriasisUn rs2069762 Acute kidney rejection39 rs2069762 Cardiac allograph outcome39 rs2069762 Heart transplantation70 rs2069762 Severe periodontitis71

Yes No No No No Yes No No Yes

CC/173:153 CC/113:118 CC/127:98 CC/131:157 CC/93:125 CC/63:43 CC/67:42 CC/301:93 CC/38:31 þ 44

IL2RA Several SNPs Diabetes type 151

Yes

F/725; CC/7457

IL2RB, (GT)n Repeat at 5 Promoter Region Multiple sclerosis47 Multiple sclerosis69 Schizophrenia57 Schizophrenia (Japanese pop)56

No No No No

CC/287:216 CC/358:395 CC/42:47 CC/54:54; F/6

IL2RG Polymorphisms Several SNPs SCID59,72

Yes

0

a

Type of study/no: CC, case-control; F, multicase families/number of cases. Un, unpublished.

b

the amount of IL-2 protein than their T/T and T/G counterparts (equal amounts). In the second study,34 two different approaches were used. IL2 promoter (500 nucleotide fragment)–luciferase constructs, transfected in the Jurkat cell line, were shown to produce twofold higher levels of luciferase expression from the
330 G allele compared with the T allele. This is in partial agreement with Hoffmann’s work.33 However, analysis of the transcriptional effect of this polymorphism in PMA-ionomycin activated lymphocytes showed that the G allele was related to lower expression of IL2 mRNA as measured by reverse transcription and real time PCR relative to a housekeeping gene. In fact, in this study, the ‘‘high IL-2 producer’’ was associated with GT and TT genotypes (in similar amounts). This is in contradiction with data obtained in the transfected Jurkat cells34 as well as Hoffmann’s work,33 in which GT and TT genotypes were identified as the ‘‘low IL-2 producer’’ (in equal amounts). Several important differences exist in the experimental approaches of these two studies33,34 but it is unlikely that these system

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factors can explain these differences. Neither study shows allele dosage effects, that is, heterozygotes for the
330 SNP allele do not seem to be the ‘‘intermediate producer’’ between that of both homozygotes. Therefore, the mechanisms underlying these findings are at this moment speculative. These could include, first of all, the fact that mouse and human IL-2 are monoallelically transcribed in a stochastic manner in some T cells and bi-allelically transcribed in others.29,35–37 Thus, cells expressing the IL-2 gene may do so from 0, 1 or 2 alleles. Another possibility is the existence of other polymorphisms affecting the outcome of IL-2 production in these cells.

8.3.1.2

The
330 (rs2069762) SNP and Disease Association Studies

Indirect corroboration of the association of the
330 G/G genotype with a ‘‘low IL-2 producer’’ phenotype, in agreement with Matesanz’s work,34 is derived from the observation that this genotype is absent or present at very low frequency in Black-American individuals, in whom renal transplant is more likely to suffer acute rejection, and who display a poorer prognosis for long-term graft survival than caucasians.38 Also, the finding of association of T/T but not T/G genotype with acute kidney rejection was unexpected considering that both genotypes were shown to be associated with equal (low) in vitro IL-2 production in Hoffmann’s work33 and with the higher producers in Matesanz’s studies.34 One possible explanation is that in vivo, under conditions of allostimulation and immunosupression, the influence of the T/T and T/G genotypes on IL-2 production could be different from that observed in vitro. On the other hand, the association could also be related to another polymorphism, in linkage disequilibrium with IL2
330T.39 There is also support for Hoffmann’s work33 in another study.40 As mentioned above, the monoallelic expression of IL-2 may allow heterozygotes to express both variants with probably a variable biological activity in different T-cells, whereas homozygotes do not have the advantage of diploidy.41 It is also surprising that while this polymorphism appears to be implicated in acute kidney transplant rejection it was not associated with acute cardiac transplant rejection nor with graft survival.39 Association was found between the
330 IL2 gene promoter polymorphism, GT and TT genotypes, and secondary progressive multiple sclerosis (SP-MS), and a tendency for association was seen with RR-MS in a sample group from the south of Spain.30 These genotypes were also associated with the ‘‘high producer’’ phenotype,34 suggesting that the expansive and activating function of IL-2 is implicated in the inflammatory process that takes place in the MS plaques. In addition, a genetic effect of IL2 in MS may also be related to the hypothesis of the infectious agent as an exogenous cofactor in the aetiology of the disease. Using the same samples of the Spanish study, no association with MS was found for the
176 IL-6 promoter polymorphisms (rs1800795).42 Another study43 reproduced Matesanz’s work in a Japanese population resulting in no significant differences in allele distribution, suggesting that this IL2 gene polymorphism does not influence the susceptibility to MS in this group. The inconsistency of these two studies may be due, in part, to differences in the polymorphism background of different ethnic groups. Racial and ethnic differences may affect not only susceptibility, but also the phenotypic expression of MS, including clinical manifestations, site of lesions, disease course and prognosis. In fact, striking differences were evident in the distribution of the
330 SNP genotypes between different populations, especially between Blacks and both Whites and Asians. Whites showed a T/G allelic distribution of 74%/26% whereas Afro-Americans had a distribution of 94%/6%.30,41,43,70 This difference may contribute to the apparent influence of ethnicity on allograft outcome or to the association with pathology.38,44,45

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8.3.2 HUMAN IL2 RECEPTOR ALPHA GENE POLYMORPHISMS (hIL2RA) A soluble form of hIL-2R alpha (sIL2Ra) chain can be detected in blood. Although sIL-2Ra may not have a physiological role, its presence at high levels has been correlated with a number of disease states, including some forms of leukaemia, certain viral infections, and autoimmune disorders.46,47 However, the observed increase of IL-2R and IL-2 production in MS and other diseases may be explained by a higher number of IL-2 and IL-2R expressing cells rather than a higher level of IL-2 and IL-2R production per cell. The IL2RA/CD25 gene is located on chromosome 10p15, a region which has shown linkage to MS,48 IDDM49 and adult-onset glaucoma.50 The IL2RA/(CD25) gene has been associated with type 1 diabetes (T1D) in a tag-SNP approach with a large number of samples of T1D.51 In one report, a patient with a genetic mutation in the CD25 gene that leads to a lack of CD25 expression had anaemia, lymphadenopathy, and multi-organ inflammatory infiltrates,52 similar to the symptoms of IL-2- and IL-2R-deficient mice.3

8.3.3 HUMAN IL2 RECEPTOR BETA GENE POLYMORPHISMS (hIL2RB) The IL2RB gene is located at chromosome position 22q11.2–q12. The promoter region of the gene lacks a TATA box element but contains a GT(n) dinucleotide repeat polymorphism 215 base pairs upstream from the first transcription initiation site, whose alleles may regulate its expression (Figure 8.2).53,54 Eight GT dinucleotide repeats have been reported that can generate 15 different alleles in Caucasians. Whether these polymorphisms have any biologic importance is unknown, although they have been variably identified in association with certain chronic disease states27 (Table 8.1). An extreme case of severe combined immunodeficiency (SCID) caused by lack of NK cells in the peripheral circulation has been associated with a reduced expression of the IL-2R/IL-15R beta chain.55 It is possible, but as yet unknown, that there is some genetic defect in regulatory regions. This symptom contrasts with that observed in mice lacking expression of IL-2R beta.3 IL2R beta has also been considered a good candidate gene for schizophrenia (Table 8.1), based on linkage analysis in multicase families. However, recent studies do not support an association between schizophrenia and the IL2RB gene locus.56,57

8.3.4 IL2 RECEPTOR GAMMA CHAIN GENE POLYMORPHISMS (hIL2RG) The IL2RG gene is localized on human chromosome Xq13, which is the general region previously determined to contain the locus for X-linked severe combined immunodeficiency (XSCID),58 a syndrome of profoundly impaired cellular and humoral immunity. XSCID constitutes a disorder of the immune system caused by mutations in the gene encoding the common gamma chain (gc), which is necessary for lymphocyte development and function. In humans, two thirds of patients with SCID express abnormal gamma c chains in their lymphocytes.59

8.4 CONCLUDING REMARKS Assuming that the essential characteristic of the autoimmunity-associated mouse IL-2 allotype is its hypo-activity and that this is the cause of diminished cell activation and cell death predisposing these strains to develop autoimmune disease,21 we may translate this concept to the human IL-2/IL-2R system and its polymorphisms. In humans, since no

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Cytokine Gene Polymorphisms in Multifactorial Conditions

IL-2 protein variants have been found that are associated with differential activity, we have to rely on the level of protein expression. In this respect several recent findings may be relevant: (1) Mouse and human IL-2 are mono-allelically transcribed in a stochastic manner in some T cells, and bi-allelically transcribed in others.29,36,45 Thus, cells expressing IL-2 genes may do so from 0, 1, or 2 alleles. Furthermore, it seems clear that the
330 hIL2 promoter polymorphisms differentially affect the amount of IL-2 production, adding to the above-mentioned mechanism of regulation of expression more factors that may control the amount of IL-2 produced by a single cell in a given situation. These types of regulation could account for the wide variety of different combinations of cytokine genes expressed in individual T cells and therefore play a role in the generation of T cells with a range of potentially different effector functions. (2) The association of the
330 GT and TT IL2 genotypes with MS and with the ‘‘high IL-2 producer’’ phenotype,30,34 may be related to the pro-inflammatory activity of this cytokine and its role in immune responses against infectious agents. (3) IL-2 functioning, not only as a growth factor, has been shown to be very dependent on the concentrations used in each system. For instance, there is a strong correlation between the rate of IL-2 production and the protection efficiency of mouse S91 melanoma cell vaccines.60 The best immunization is achieved with vaccines producing intermediate IL-2 levels while no protection was achieved with reduced or high production levels of IL-2. In comparison, granulocyte-macrophage colony-stimulating factor (GM-CSF) as immunomodulator induces substantial immunization even at a moderate level of secretion and protects all animals at the maximum obtainable level of secretion. (4) Cytokine agonist or antagonist therapy is already a reality in an IL-2/IL-2R system,61 but in multifactorial conditions or diseases first the optimal timing of action62 and the concentration at which IL-2 may be pathogenic has to be precisely defined. The IL2/IL2R functional polymorphisms can provide clues as to whether a specific condition is being affected by a ‘‘high or low’’ IL-2 level as has already been analyzed for IL-4.63 This may indicate whether the pathogenic effect could be based either on the pro-inflammatory activity of IL-2, or on a low control of self tolerance.

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11. Fuse, A. et al., Organization and structure of the mouse interleukin-2 gene, Nucleic Acids Res. 12, 9323, 1984. 12. Matesanz, F., Alcina, A., and Pellicer, A., A new cDNA sequence for the murine interleukin-2 gene, Biochim. Biophys. Acta, 1132, 335, 1992. 13. Matesanz, F., Alcina, A., and Pellicer, A., Existence of at least five interleukin-2 molecules in different mouse strains, Immunogenetics, 38, 300, 1993. 14. Matesanz, F. and Alcina A., Glutamine and tetrapeptide repeat variations affect the biological activity of different mouse interleukin-2 alleles, Eur. J. Immunol., 26, 1675, 1996. 15. Ghosh, S. et al., Polygenic control of autoimmune diabetes in nonobese diabetic mice, Nat. Genet., 4, 404, 1993. 16. Ikegami, H. et al., Genetic dissection of type 1 diabetes susceptibility gene, Idd3, by ancestral haplotype congenic mapping, Ann. N.Y. Acad. Sci., 958, 325, 2002. 17. Encinas, J. A. et al., QTL influencing autoimmune diabetes and encephalomyelitis map to a 0.15-cM region containing IL2, Nat. Genet., 21, 158, 1999. 18. Roper, R. J. et al., Interacting quantitative trait loci control loss of peripheral tolerance and susceptibility to autoimmune ovarian dysgenesis after day 3 thymectomy in mice, J. Immunol., 169, 1640, 2002. 19. Podolin, P. L. et al., Differential glycosylation of interleukin 2, the molecular basis for the NOD Idd3 type 1 diabetes gene?, Cytokine, 12, 477, 2000. 20. Matesanz, F. and Alcina, A., High expression in bacteria and purification of polymorphic mouse interleukin 2 molecules, Cytokine, 10, 249, 1998. 21. Choi, Y., Simon-Stoos, K., and Puck, J. M., Hypo-active variant of IL-2 and associated decreased T cell activation contribute to impaired apoptosis in autoimmune prone MRL mice, Eur. J. Immunol., 32, 677, 2002. 22. Zipris, D. et al., Defective thymic T cell activation by concanavalin A and antiCD3 in autoimmune nonobese diabetic mice. Evidence for thymic T cell anergy that correlates with the onset of insulitis, J. Immunol., 146, 3763, 1991. 23. Crispin, J. C. and Alcocer-Varela, J., Interleukin-2 and systemic lupus erythematosus – fifteen years later, Lupus, 7, 214, 1998. 24. Kutukculer, N., Caglayan, S., and Aydogdu, F., Study of pro-inflammatory (TNF-alpha, IL-1alpha, IL-6) and T-cell-derived (IL-2, IL-4) cytokines in plasma and synovial fluid of patients with juvenile chronic arthritis: correlations with clinical and laboratory parameters, Clin. Rheumatol., 17, 288, 1998. 25. Tenbrock, K. and Tsokos, G. C.,Transcriptional regulation of interleukin 2 in SLE T cells, Int. Rev. Immunol., 23, 333, 2004. 26. Epplen, C., Dinucleotide repeat polymorphism in the IL2 and IL5RA genes, Hum. Mol. Genet., 3, 679, 1994. 27. Khani-Hanjani, A. et al., Identification of four novel dinucleotide repeat polymorphisms in the IL-2 and IL-2beta receptor genes, Hum. Immunol., 62, 368, 2001. 28. John, S. et al., Two novel biallelic polymorphisms in the IL-2 gene, Eur. J. Immunogenet., 25, 419, 1998. 29. Matesanz, F. et al., Allelic selection of human IL-2 gene, Eur. J. Immunol., 30, 35, 2000. 30. Matesanz, F. et al., Allelic expression and interleukin-2 polymorphisms in multiple sclerosis, J. Neuroimmunol., 119, 101, 2001. 31. Fedetz, M. et al., Lack of association between -384 and 114 IL-2 gene polymorphisms and rheumatoid arthritis, J. Rheumatol., 30, 435, 2003. 32. Fedetz, M. et al., Analysis of -631 and -475 interleukin-2 promoter single nucleotide polymorphisms in multiple sclerosis, Eur. J. Immunogenet., 29, 389, 2002. 33. Hoffmann, S. C. et al., Association of cytokine polymorphic inheritance and in vitro cytokine production in anti-CD3/CD28-stimulated peripheral blood lymphocytes, Transplantation, 72, 1444, 2001. 34. Matesanz. F., Effects of the multiple sclerosis associated -330 promoter polymorphism in IL2 allelic expression, J. Neuroimmunol., 148, 212, 2004. 35. Hollander, G. A. et al., Monoallelic expression of the interleukin-2 locus, Science, 279, 2118, 1998.

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36. Hollander, G. A., On the stochastic regulation of interleukin-2 transcription, Semin. Immunol., 11, 357, 1999. 37. Rhoades, K. L. et al., Allele-specific expression patterns of interleukin-2 and Pax-5 revealed by a sensitive single-cell RT-PCR analysis, Curr. Biol., 10, 789, 2000. 38. Isaacs, R. B., Racial disparities in renal transplant outcomes, Am. J. Kidney Dis., 34, 706, 1999. 39. Morgun, A. et al., Interleukin-2 gene polymorphism is associated with renal but not cardiac transplant outcome, Transplant. Proc., 35, 1344, 2003. 40. MacMillan, M. L. et al., High-producer interleukin-2 genotype increases risk for acute graft-versus-host disease after unrelated donor bone marrow transplantation, Transplantation, 76, 1758, 2003. 41. Nieters, A., Brems, S., and Becker, N., Cross-sectional study on cytokine polymorphisms, cytokine production after T-cell stimulation and clinical parameters in a random sample of a German population, Hum. Genet., 108, 241, 2001. 42. Fedetz, M. et al., The -174/-597 promoter polymorphisms in the interleukin-6 gene are not associated with susceptibility to multiple sclerosis, J. Neurol. Sci., 190, 69, 2001. 43. Kikuchi, S. et al., An assessment of the association between IL-2 gene polymorphisms and Japanese patients with multiple sclerosis, J. Neurol. Sci., 205, 47, 2002. 44. Reynard, M. P., Turner, D., and Navarrete, C. V., Allele frequencies of polymorphisms of the tumour necrosis factor-alpha, interleukin-10, interferon-gamma and interleukin-2 genes in a North European Caucasoid group from the UK, Eur. J. Immunogenet., 27, 241, 2000. 45. Cox, E. D. et al., Cytokine polymorphic analyses indicate ethnic differences in the allelic distribution of interleukin-2 and interleukin-6, Transplantation, 72, 720, 2001. 46. Fernandez-Botran, R., Chilton, P. M., and Ma, Y., Soluble cytokine receptors: their roles in immunoregulation, disease, and therapy, Adv. Immunol., 63, 336, 1996. 47. McDonnell, G. V. et al., An evaluation of interleukin genes fails to identify clear susceptibility loci for multiple sclerosis, J. Neurol. Sci., 176, 4, 2000. 48. Akesson, E. et al., Refining the linkage analysis on chromosome 10 in 449 sib-pairs with multiple sclerosis, J. Neuroimmunol., 143, 31, 2003. 49. Reed, P. et al., Evidence for a type 1 diabetes susceptibility locus (IDDM10) on human chromosome 10p11–q11, Hum. Mol. Genet., 6, 1011, 1997. 50. Sarfarazi, M. et al., Localization of the fourth locus (GLC1E) for adult-onset primary openangle glaucoma to the 10p15–p14 region, Am. J. Hum. Genet., 62, 641, 1998. 51. Vella, A. et al., Localization of a Type 1 Diabetes Locus in the IL2RA/CD25 Region by Use of Tag Single-Nucleotide Polymorphisms, Am. J. Hum. Genet., 76, 773, 2005. 52. Sharfe, N., Dadi, H. K., Shahar, M., and Roifman, C. M., Human immune disorder arising from mutation of the alpha chain of the interleukin-2 receptor, Proc. Natl. Acad. Sci. USA, 94, 3168, 1997. 53. Shibuya, H. et al., The human interleukin-2 receptor beta-chain gene: genomic organization, promoter analysis and chromosomal assignment, Nucleic Acids Res., 18, 3697, 1990. 54. Brewster, E. S., Brennan, M. B., and Vissing, H., Dinucleotide repeat polymorphism in the IL-2R beta gene. Nucleic. Acids Res., 19, 4022, 1991. 55. Gilmour, K. C. et al., Defective expression of the interleukin-2/interleukin-15 receptor beta subunit leads to a natural killer cell-deficient form of severe combined immunodeficiency, Blood, 98, 877, 2001. 56. Tatsumi, M. et al., Genes for interleukin-2 receptor beta chain, interleukin-1 beta, and schizophrenia: no evidence for the association or linkage, Am. J. Med. Genet., 74, 338, 1997. 57. Nimgaonkar V. L. et al., Association study of schizophrenia and the IL-2 receptor beta chain gene, Am. J. Med. Genet., 60, 448, 1995. 58. De Saint Basile, G. et al., Close linkage of the locus for X chromosome-linked severe combined immunodeficiency to polymorphic DNA markers in Xq11–q13, Proc. Natl. Acad. Sci. USA, 84, 7576, 1987. 59. Fugmann, S. D. et al., Mutations in the gene for the common gamma chain (gammac) in X-linked severe combined immunodeficiency, Hum. Genet., 103, 730, 1998. 60. Schmidt, W. et al., Cancer vaccines: the interleukin 2 dosage effect, Proc. Natl. Acad. Sci. USA, 92, 4711, 1995.

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61. Waldmann, T. A., The meandering 45-year odyssey of a clinical immunologist, Annu. Rev. Immunol., 21, 1, 2003. 62. Blattman, J. N. et al., Therapeutic use of IL-2 to enhance antiviral T-cell responses in vivo, Nat. Med., 9, 540, 2003. 63. Vandenbroeck, K. and Goris, A., Cytokine gene polymorphisms in multifactorial diseases: gateways to novel targets for immunotherapy?, Trends. Pharmacol. Sci., 24, 284, 2003. 64. Bidwell, J. et al., Cytokine gene polymorphism in human disease: on-line databases, Genes Immun., 1, 13, 1999. 65. Epplen, C. et al., Immunoprinting excludes many potential susceptibility genes as predisposing to early onset pauciarticular juvenile chronic arthritis except HLA class II and TNF, Eur. J. Immunogenet., 22, 311, 1995. 66. Parkes, M., Satsangi, J., and Jewell, D., Contribution of the IL-2 and IL-10 genes to inflammatory bowel disease (IBD) susceptibility, Clin. Exp. Immunol., 113, 28, 1998. 67. Gomolka, M. et al., Immunoprinting: various genes are associated with increased risk to develop rheumatoid arthritis in different groups of adult patients, J. Mol. Med., 73, 19, 1995. 68. He, B. et al., Linkage and association analysis of genes encoding cytokines and myelin proteins in multiple sclerosis, J. Neuroimmunol., 86, 13, 1998. 69. Epplen, C., Genetic predisposition to multiple sclerosis as revealed by immunoprinting, Ann. Neurol., 41, 34, 1997. 70. Holweg, C. T. et al., Recipient gene polymorphisms in the Th-1 cytokines IL-2 and IFN-gamma in relation to acute rejection and graft vascular disease after clinical heart transplantation, Transpl. Immunol., 1, 121, 2003. 71. Scarel-Caminaga, R. M. et al., Investigation of an IL-2 polymorphism in patients with different levels of chronic periodontitis, J. Clin. Periodontol., 29, 587, 2002. 72. O’Marcaigh, A. S. et al., Maternal mosaicism for a novel interleukin-2 receptor gamma-chain mutation causing X-linked severe combined immunodeficiency in a Navajo kindred, J. Clin. Immunol., 17, 29, 1997.

9

The Chromosome 5q23.1–q31.1 Cluster of Cytokines Tarja Laitinen

CONTENTS 9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Genomic Orientation and Evolution of the Cytokine Cluster . . . . . . . . . . . . . . . . . . . . 9.3 Functions of the Cytokines Encoded by the Gene Cluster on Chromosome 5q . . 9.4 Common Variants of the Cytokine Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Linkage and Association Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

121 122 123 124 125 130 130

9.1 INTRODUCTION The T helper type 2 (Th2) cytokines, primarily Interleukins-4, -5, and -13, control the major components that characterize an asthmatic immune response, including IgE isotype switching, mucus production, and the recruitment and activation of eosinophils. The population of Th2 cells is expanded in the airways of asthmatic subjects, and presence of these cells correlates with bronchial hyper-reactivity and airway eosinophilia, both in man and in experimental mouse models. Based on epidemiological studies, genetic factors are known to strongly influence susceptibility to allergic conditions. The genes encoding IL4, IL5, and IL13 are located as a tight cluster on the long arm of chromosome 5 in bands q23.1–q31.1. The cluster has shown to be developed most likely due to gene duplications; it is highly polymorphic, evolutionary ancient, and well conserved indicating its distinctive role in immune responses. Because of these discoveries the cytokine cluster has become one of the first and most extensively studied genomic regions as a susceptibility locus for asthma and other atopy related traits. Since Marsh and colleagues (1994)1 reported linkage between the chromosome five cytokine cluster and serum immunoglobulin E level as a marker of an atopic constitution, tens of publications have been published on genetic variants of these cytokine genes and their potential role in explaining individuals’ risk to develop different immune-mediated diseases. While our knowledge on the physical orientation of the genes and genetic markers, haplotype structures and their frequencies in different ethnic groups have increased, the informativeness of publications has improved accordingly. In the earliest studies, genetic analyses were performed using linkage approaches based on microsatellite markers. Microsatellite markers (di-, tri-, and tetranucleotide repeats varying in size) are highly polymorphic, located usually outside coding sequences, and rarely considered to be functional. In these studies, however, the physical distances and the order of the microsatellite markers were based on approximations from several genetic maps and often 121

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somewhat ambiguous harming multipoint linkage analyses. Since the complete human DNA sequence has become available in 2003, high-throughput sequencing projects have increased the density of single nucleotide polymorphism (SNP) maps and enhanced the development of the technologies for SNP genotyping. Furthermore, international collaborations, such as the Hapmap Project (http://www.hapmap.org/index.html.en), have released valuable information on haplotype structures across the human genome and the catalog of SNPs that can recognize these conserved haplotype blocks, generally of 20 to 60 kb in size. These blocks may contain a large number of SNPs, but a few SNPs are enough to uniquely identify the haplotypes in a block (called haplotype tagging SNPs). Together with the growing recognition of the limitations of linkage analysis in complex human diseases, this has shifted emphasis away from linkage analysis and microsatellite markers towards SNP genotyping and analytical strategies based on allele and haplotype association analyses. Compared to microsatellite markers, SNPs are less polymorphic, but more stable and robust to genotype, and they can be found also in the coding regions of a gene. Changes in the analysis methods have also shifted the focus from family-based studies to extremely large, well-defined population-based case-control cohorts in attempts to uncover ancient, shared haplotype blocks carrying the disease-causing SNPs which are therefore found more frequently among the patients than controls.

9.2

GENOMIC ORIENTATION AND EVOLUTION OF THE CYTOKINE CLUSTER

Based on the latest gene annotations (http://genome.ucsc.edu/cgi-bin/hgGateway), five human cytokine genes IL3, colony stimulating factor-2 (CSF2), IL5, IL13, and IL4 are located close to each other within a 622 kb genomic region on chromosome five (Figure 9.1). Especially IL5, IL13, and IL4 are in an immediate neighborhood to each other within a 200 kb region. However, genes such as interleukin-9 (IL9), monocyte differentiation antigen CD14, and beta-2-adrenergic receptor (ADRB2) that have been sometimes connected to the region, especially in asthma-related traits, are located several megabases downstream of the gene cluster (Figure 9.1). Ten additional genes have been annotated in between the cytokine genes. None of those represent sequence homologs of the cytokines and the functions of most of these genes are to a lesser extent understood than those of the cytokines.

FIGURE 9.1 Genomic orientation of the chromosome 5q cytokine gene cluster including the IL9, CD14, and ADRB2 genes.

The Chromosome 5q23.1–q31.1 Cluster of Cytokines

123

The chromosome 5q cytokine genes are believed to have arisen as a result of duplication events from a common ancestor. IL3, CSF2, IL5, IL4, and IL13 genes are all composed of four exons of conserved size and the exons are interrupted by introns in the same phases, with the exception of IL3 in which exon 3 is split into two segments. In addition, the expression of the IL5, IL4, and IL13 genes is regulated coordinately by several long-range regulatory elements. The cytokine proteins all share the four alphahelical bundle structure. The receptors of these cytokines are heterodimers each possessing a unique alpha unit, but the same beta subunits are shared by IL-5, IL-3, and CSF-2, and by IL-13, and IL-4, respectively. Similar grouping of Th2 cytokine genes has been found also in other species. In all mammals the orthologous locus is recognized. In the mouse this highly conserved locus is found on chromosome 11 which shows sequence homology not only in the coding regions but also in promoter regions.2 Lately the identification of the corresponding region in chicken, the first non-mammalian organism, showed that the gene cluster is very old, at least 300 million year.3 Contrary to some other cytokine genes cloned previously in chicken this locus showed a high level of sequence identity. This is a somewhat surprising observation, since, compared to mammals, chicken lacks the central components of the Th2 type response such as classic eosinophils and immunoglobulin class E.

9.3 FUNCTIONS OF THE CYTOKINES ENCODED BY THE GENE CLUSTER ON CHROMOSOME 5q A complex network of immune responses in which the cytokines have a central role maintains immunological homeostasis. Humanized monoclonal antibodies used as therapeutic agents for blocking specific cytokine responses have opened up a fascinating field of new therapeutic opportunities for treatment of chronic inflammatory diseases. Based on in vitro and in vivo studies in man and experimental sensitization models of mice IL-5, IL-4, IL-13, and IL-9 have become the prime candidates.4,5 IL5 encodes a 134 amino acid cytokine that acts a main regulator of eosinopoiesis, eosinophil maturation, and activation. In humans IL-5 is a very selective cytokine, since the expression of the IL-5 receptor is restricted to eosinophils and basophils. There is experimental evidence that anti-IL5 can inhibit infiltration of eosinophils into the lung.6 In addition, IL-5 knockout mice do not respond to an allergic challenge with blood or tissue eosinophilia and they do not show bronchial hyper-reactivity to cholinergic challenge.7 IL13 encodes a 132 amino acid immunoregulatory cytokine produced primarily by activated Th2 cells. This cytokine is found to be critical to the pathogenesis of asthma related traits based on human studies and in vivo experimental models.8 In IL-13 transgenic mouse it has also been demonstrated that in addition to eosinophil-, macrophage-, and lymphocyterich pulmonary inflammation, the cytokine is involved with airway remodeling such as development of bronchial circulation neovascularization and pulmonary fibrosis. IL4 encodes a 153 amino acid pleiotropic cytokine produced by activated T cells and is essential in the differentiation of T cells into Th2 cytokine-producing cells. Anti-IL-4 antibodies in mice inhibit the development of allergen-specific IgE response, and reduce eosinophilic inflammation and airway reactivity. These results have been confirmed by using IL-4 knockout mice. The IL-4 receptor can also bind IL-13, which may explain many overlapping functions of these cytokines. The signal transducer and activator of transcription, STAT6, has been shown to play a central role in mediating the immune regulatory signal of this cytokine. Other cytokines (IL3, CSF2, and IL9) of the 5q cluster control cell growth, differentiation, and apoptosis of a variety of hematopoietic cells. IL-9 expression is increased

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Cytokine Gene Polymorphisms in Multifactorial Conditions

significantly in asthmatic lung and genetic studies on a mouse model of asthma demonstrated that this cytokine is a determining factor in the pathogenesis of bronchial hyperresponsiveness.

9.4

COMMON VARIANTS OF THE CYTOKINE GENES

Numerous common single nucleotide polymorphisms have been described in the 5q cytokine cluster (http://snpper.chip.org), most of these in non-coding regions of the genes. These inherited variants may alter the function of a gene by several mechanisms. SNPs that cause an amino acid change in the encoded proteins are the most obvious candidates for a functional effect; however, such SNPs are rare (Table 9.1). Even one amino acid change in the active site of a protein can dramatically alter the three-dimensional structure and binding properties of the molecule. SNPs in 50 and 30 non-coding regions of the gene and promotor regions can have an effect on expression of the gene and stability of the messenger RNA. The biological role of intronic SNPs has been more difficult to explain. Lately it has been suggested that altered splicing due to intronic variation might be one of the major mechanisms in complex disorders explaining genetic susceptibility. The latest studies on sequence variation in the genomic region covering the IL13 and IL4 genes have revealed strong linkage disequilibrium especially across the IL4 gene, consistent haplotype structures, but divergent haplotype frequencies in four study populations.9 When fourteen SNPs were used in genotyping, the three most common haplotypes explained 94% of all variation found in the IL4 gene locus among

TABLE 9.1 Common Allelic Variants of the 5q Cytokine Cluster Genes That Cause an Amino Acid Change in the Encoded Protein and Reported Associations in These Genes to Immune Mediated Diseases Gene

Amino Acid Changing Variants

Reported Associations

IL3

R15H, P27S

No associations for the gene reported

CSF2

T115I, I117T

Association to I117T reported (Table 9.3)

IL5

–

No associations for the gene reported

IL13

R130Q (named also R110Q, R129Q, R144Q)

Several positive associations reported (Table 9.2 and Table 9.3) Located in exon 4 of the gene Located in alpha helix D of the protein (region that interacts with the receptors IL4Ra and IL13Ra) In vitro assays show increased activity in STAT6 phosphorylation CD23 expression IgE switching in B-cells compared to the major allele24 Haplotype distribution across the gene reported in four ethnic groups9

IL4

–

Both positive association and lack of association reported especially for the promoter
590C/T polymorphism (Table 9.3) Haplotype distribution across the gene reported in four different ethnic groups9

IL9

T117M

No associations found for gene in asthma or high serum total IgE45,46

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125

FIGURE 9.2 Pairwise LD statistics D’ for pairs of common SNPs in genomic regions containing IL13 and IL4 in the European population.9 Positions of the markers are given according to the numbering in GeneBank entry AC004039 and the three most common haplotypes with frequencies are shown.

Europeans (Figure 9.2). Among Japanese, haplotype diversity was at the same level, but it was much greater among African Americans and Sub-Saharan Africans. Among these populations the three most common haplotypes explained 42% and 23% of haplotype diversity, respectively. Also the majority of the most common haplotypes were different to those seen among the Europeans or Japanese. For IL13 linkage disequilibrium is evident, though it is weaker than for IL4. Among the Europeans the three most common haplotypes explain 72% of all variation in the gene locus using the eight markers shown in Figure 9.2.9

9.5 LINKAGE AND ASSOCIATION RESULTS Several studies have been performed to establish linkage between the chromosome 5q cytokine cluster and different atopic conditions. Study designs vary greatly in pedigree structures, age range of the probands, and ethnicity of the study populations. Clinical phenotypes such as asthma, allergic rhinitis, and atopic dermatitis and quantitative measurements such as blood eosinophil level, bronchial hyper-reactivity, serum total and allergen specific IgE levels, and skin prick test reactivity as markers of atopic conditions have been applied in the analyses. The heterogeneity in the study designs makes it rather difficult to compare the results. Studies have shown either suggestive linkage or no evidence of linkage. In case of no linkage very few research groups have explored the power to exclude linkage. The Consortium On Asthma Genetics has published one of the largest studies by combining several Caucasian data sets (1037 families).10

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Cytokine Gene Polymorphisms in Multifactorial Conditions

The retrospective collaboration reported suggestive linkage (LOD score of 2.6) for asthma, which in spite of the large study cohort, remained weaker than the linkage reported in inflammatory bowel disease (non-parametric LOD score of 3.9 described as the IBD5 locus). The linkage in inflammatory bowel diseases was later confirmed by LD mapping.11 A common haplotype spanning 250 kb showed strong association (P 5 2  10
7) with the disease. The haplotype harvested the cytokine cluster and contained multiple SNPs showing equivalent association and, therefore, the causal mutation remained unknown. Linkage as an analysis method does not allow us to separate the genetic influences between the genes within the cluster. That can be done only using allele or haplotype association analysis with dense marker maps. However, systematic and information-rich analyses covering all common haplotypes of the locus or even a single gene has not yet been published. Instead of testing all common variants of the gene, published association studies so far have relied on the detection of a few polymorphisms in cytokine genes. Focus has often been on the coding sequences when the SNPs have been screened and tested for association to one or more phenotypic traits. The most robust association to atopic conditions so far has been described for the IL13 gene. Especially the non-synonymous SNP causing an amino acid change from arginine (R) to glutamine (Q) (named in the literature as R110Q, R129Q, R144Q, or R130Q) has shown association in several studies among patients with different ethnic backgrounds and different atopic conditions or quantitative traits (Table 9.2).12–20 Also some promoter and 30 non-coding regions end SNPs in IL13 (most likely at least partially in linkage disequilibrium with R130Q) have shown association to asthma related traits16,19,21–23 (Table 9.3). When human IL13 is compared to mouse il13, the sequence homology is high; not only in the exons but also in the 50 flanking region that contains several transcription factor consensus sequences. This might suggest that these highly conserved regions may be highly relevant to gene expression regulation and that any genetic variance found is therefore functionally important.2 Understanding the biological mechanism underlying the association is important to support the genetic findings. R130Q is of particular interest since it obviously changes the functional properties of the protein. The replacement of the amino acid alters the distribution of charges in alpha helix D of the protein. This region is critical for the interactions of IL13 with its receptors. Based on in vitro studies with primary human cells IL13*130Q was more active in inducing STAT6 phosphorylation, CD23 expression on monocytes, and hydrocortisone dependent IgE switching in B-cells compared to that of IL13*130R.24 All the other associations reported for the single genetic variants in the cytokine cluster are still much more inconsistent25–49 (Table 9.3). Rather small sample sizes with limited power to prove or disprove genetic association increase the risk of false positive and negative associations. The risk of false positive associations due to multiple testing becomes even greater when several related phenotypes are analyzed simultaneously. IL4 promoter variant
590C/T has been studied by several groups in different allergic conditions, but the results have remained inconclusive.21,25–39 Even though the great majority of the 5q cytokine cluster association studies have been conducted with relevance to atopic conditions, also Th1-driven chronic inflammatory diseases such as inflammatory bowel disease,11 type 1 diabetes,40,41 multiple sclerosis,42–44 and juvenile idiopathic arthritis,20 have been studied. Contrary to inflammatory bowel disease, the reported associations are rather weak and many of those yet unreplicated. For example in type 1 diabetes, a large case-control study41 could not confirm the association to IL4 or IL13 reported previously.40 In multiple sclerosis several markers have been genotyped across the IL4 gene.44 Haplotype analysis strengthened the allele associations suggesting potentially a true association; however, this was not found in all studies published. Taken together these

High risk families Recruited based asthma

Canadian: Caucasian and Asian ancestry German German

High risk families

AD ¼ atopic dermatitis. *Haplotype analysis decreased the P values.

Heinzmann et al. 200320

P ¼ 0.04

188 cases þ 87 controls

168 cases þ 99 controls 278 cases þ 270 controls

304 cases

P ¼ 0.007

666 cases

US: Caucasian ancestry Chinese

Recruited based on asthma, family-based association study, children Recruited based on allergic rhinitis, adults

P ¼ 0.006 P ¼ 0.04

RR 1.9, P ¼ 0.05* RR 2.5, P ¼ 0.01

P ¼ 0.02

185 cases þ 102 controls

Japanese

Kauppi et al. 200115 Tsunemi et al. 200216 DeMeo et al. 200218 Wang et al. 200317 He et al. 200319

100 cases þ 100 controls

Japanese

OR 2.3, 95% CI 1.3–4.0, P ¼ 0.003 OR 1.8, 95% CI1.1–2.9, P ¼ 0.01 P ¼ 0.02

OR 2.4, 95% CI 1.4–4.2, P ¼ 0.003 OR 1.8, 95% CI 1.1–3.0, P ¼ 0.03 P ¼ 0.000 002

Statistical Significance

324 cases þ 358 controls

Recruited based on asthma, probands young adults

Heinzmann et al. 200014

cases cases cases cases þ 150 controls

286 592 521 150

US German German British

187 cases þ 98 controls

100 cases þ 101 controls

No. of Patients

Finnish

Unselected population sample, probands children

Graves et al. 200013

German

Nationality

Families recruited based on asthma, family-based association study, probands adults Recruited based on AD, age 11–61 yrs

Unselected population sample, probands children

Study Population

Liu et al. 200012

Study

Serum IgE, Mean age of 15 yr Bronchial asthma, age 5–18 yrs

Atopy at the age of 2 yr AD at the age of 2 yr

Combination of several allergy phenotypes by genotype IgE by genotype

AD

IgE

Asthma

Severe asthma

IgE by genotype

AD diagnosed at the age of 4 yr

IgE at the age of 7 yrs

Phenotype and Age

TABLE 9.2 Characteristics of the Studies Showing an Association between the R130Q Polymorphism in IL-13 and Atopy-Related Traits

The Chromosome 5q23.1–q31.1 Cluster of Cytokines 127

Phenotype Type 1 diabetes Type 1 diabetes Type 1 diabetes Type 1 diabetes Type 1 diabetes Type 1 diabetes Type 1 diabetes Type 1 diabetes Type 1 diabetes Type 1 diabetes Multiple sclerosis Multiple sclerosis Multiple sclerosis Multiple sclerosis Multiple sclerosis Multiple sclerosis Multiple sclerosis Multiple sclerosis Juvenile idiopathic artritis Atopic asthma Atopic asthma Asthma

Variant

50 – 524T/C 50 – 1512A/C 50 – 1112C/T þ1923C/T R110Q 50 – 524T/C 50 – 1512A/C 50 – 1112C/T þ1923C/T R110Q 50 – 1024C/T Intron 3 (709) VNTR polymorphism2 50 – 523C/T1,2 Exon1 (33C/T)1,2 Intron2 (1344TGn)1,2 Exon 3 (150)1,2 Intron 3 (709) VNTR polymorphism1,2 Intron 3 (2580C/A)1 R110Q Ile117Thr Ile117Thr Ile117Thr

Gene

IL4 IL13 IL13 IL13 IL13 IL4 IL13 IL13 IL13 IL13 IL13 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL13 CSF2 CSF2 CSF2

No Yes No No No No No No No No No Yes No No No No Yes No No Yes No Yes

Association Filipinos Filipinos Filipinos Filipinos Filipinos British British British British British Danish Caucasian US, ethnicity US, ethnicity US, ethnicity US, ethnicity US, ethnicity US, ethnicity German Swiss Icelandic Hutterites

matched matched matched matched matched matched

Population

controls controls controls controls controls controls

90/94 90/94 90/94 90/94 90/94 1557/1622 1578/1655 1583/1660 1559/1624 1559/1653 198/162 146/256 122/244 122/244 122/244 122/244 122/244 122/244 86/270 135/157 94/94 66/372

No. Cases/Controls

40 40 40 40 40 41 41 41 41 41 42 43 44 44 44 44 44 44 20 47 21 48

Reference

TABLE 9.3 Studied Polymorphisms and Reported Associations of the Chromosome 5q23.1–q31.1 Cytokine Gene Cluster in Multiple Immune Mediated Conditions

128 Cytokine Gene Polymorphisms in Multifactorial Conditions

2

1

Ile117Thr 545G/A 3606T/C
590C/T
590C/T
590C/T
590C/T1
590C/T
590C/T
590C/T
590C/T
590C/T
590C/T
590C/T
590C/T
590C/T þ33C/T þ33C/T
1112C/T
1112C/T
1112C/T
1112C/T

Atopic dermatitis Asthma Atopic dermatitis Total serum IgE Specific IgE Atopic dermatitis Asthma FEV1 Asthma Asthma Asthma Asthma Atopic asthma Atopic dermatitis Atopic dermatitis Atopic dermatitis Total IgE Atopic dermatitis Atopic asthma Atopic asthma Asthma Atopic dermatitis

Haplotype analysis strengthened the association. The markers are named according to their position on GenBank accession M23442.

CSF2M CSF2 CSF2 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL4 IL13 IL13 IL13 IL13

Yes Yes Yes Yes Yes Yes Yes Yes No Yes No Yes No No No Yes Yes No Yes No Yes No

Canadian Canadian Canadian American Australian Japanese Japanese Caucasian Hutterites Canadian Japanese Canadian Icelandic Australian Japanese German Japanese Australian Dutch Icelandic Dutch Japanese Unspecified Unspecified Unspecified 44 Unspecified 88/215 97/215 682 71 11/269 100/100 157/90/143 94/94 101 302/122 60/40 120 101 101/107 94/94 184/184 185/102 49 49 49 26 27 28 29,30 31 32 33 34 35 21 36 37 38 39 36 22 21 23 16

The Chromosome 5q23.1–q31.1 Cluster of Cytokines 129

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Cytokine Gene Polymorphisms in Multifactorial Conditions

observations will benefit greatly by studies done with a carefully selected set of haplotype tagging SNPs and in large, epidemiologically presentative cohorts before any final conclusions are made.

9.6

CONCLUSIONS

Genetic studies offer a way of improving our understanding of pathogenesis of a disease with the goal of improving preventive strategies, diagnostic tools, and therapies. The chromosome 5q cytokine cluster is a highly conserved and old genomic region that contains the main Th2 cytokine genes, which are of interest especially in allergic diseases. The latest IL4 and IL13 haplotype studies in populations of different ethnicities have shown that during human evolution the region has been under strong selection pressure. This may suggest that the carriers of distinct variants of the genes may have differences in their immune responses that are genetically controlled. So far, in the IL13 gene, haplotypes carrying the R130Q polymorphism have emerged as of particular interest. A better understanding of haplotype blocks across the chromosome 5q cytokine cluster will, however, generate a third wave of haplotype association studies. Knowing the SNPs that tag the common haplotypes will reduce the number of SNPs required to examine the region whilst retaining full information. Another interesting piece of information that might influence interpretation of association results in the near future is the increasing evidence of unequal expression of allelic transcripts of a gene.50 This becomes of importance when results of heterozygous individuals are analyzed, since a recognized susceptibility allele can be either the only active allele, or the silent allele that does not have an effect to begin with on the phenotype. Variations in allelic expression can be caused by genomic imprinting, X-chromosome inactivation, but also other, still unknown, mechanisms may exist. A better understanding of these mechanisms that sometimes can be tissue-specific, will most likely help to distinguish true from false associations.

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34. Takabayashi, A. et al., Childhood atopic asthma: positive association with a polymorphism of IL-4 receptor alpha gene but not with that of IL-4 promoter or Fc epsilon receptor I beta gene. Exp. Clin. Immunogenet., 17, 63, 2000. 35. Sandford, A. J. et al., Polymorphisms in the IL4, IL4RA, and FCERIB genes and asthma severity. J. Allergy Clin Immunol., 106, 135, 2000. 36. Elliott, K. et al., The
590C/T and
34C/T interleukin-4 promoter polymorphisms are not associated with atopic eczema in childhood. J. Allergy Clin. Immunol., 108, 285, 2001. 37. Tanaka, K. et al., Lack of association between atopic eczema and the genetic variants of interleukin-4 and the interleukin-4 receptor alpha chain gene: heterogeneity of genetic backgrounds on immunoglobulin E production in atopic eczema patients. Clin. Exp. Allergy, 31, 1522, 2001. 38. Novak, N. et al., Dichotomic nature of atopic dermatitis reflected by combined analysis of monocyte immunophenotyping and single nucleotide polymorphisms of the interleukin-4/ interleukin-13 receptor gene: the dichotomy of extrinsic and intrinsic atopic dermatitis. J. Invest. Dermatol., 119, 870, 2002. 39. Suzuki, I et al., Association between a Cþ33T polymorphism in the IL-4 promoter region and total serum IgE levels. Clin Exp Allergy, 30, 1746, 2000. 40. Bugawan, T. L. et al., Association and interaction of the IL4R, IL4, and IL13 loci with type 1 diabetes among Filipinos. Am. J. Hum. Genet., 72, 1505, 2003. 41. Maier, L. M. et al., No evidence of association or interaction between the IL4RA, IL4, and IL13 genes in type 1 diabetes. Am. J. Hum. Genet., 76, 517, 2005. 42. Hummelshoj, T. et al., Association between an interleukin-13 promoter polymorphism and atopy. Eur. J. Immunogenet., 30, 355, 2003. 43. Vandenbroeck, K. et al., Occurrence and clinical relevance of an interleukin-4 gene polymorphism in patients with multiple sclerosis. J. Neuroimmunol., 76, 189, 1997. 44. Kantarci, O. H. et al., A population-based study of IL4 polymorphisms in multiple sclerosis. J Neuroimmunol., 137, 134, 2003. 45. Waldman, I. D. and Robinson, B. F. Meta-analysis of sib pair linkage studies of asthma and the interleukin-9 gene (IL9). Genet. Epidemiol., 2 (Suppl. 1), S109, 2001. 46. Laitinen, T. et al., Genetic control of serum IgE levels and asthma: linkage and linkage disequilibrium studies in an isolated population. Hum. Mol. Genet., 6, 2069, 1997. 47. Rohrbach, M. et al., A variant in the gene for GM-CSF, I117T, is associated with atopic asthma in a Swiss population of asthmatic children. J. Allergy Clin. Immunol. 104, 247, 1999. 48. Bourgain, C. et al., Novel case-control test in a founder population identifies P-selectin as an atopy-susceptibility locus. Am. J. Hum. Genet., 73, 612, 2003. 49. He, J. Q. et al., Polymorphisms of the GM-CSF genes and the development of atopic diseases in at-risk children. Chest, 123(3 Suppl.), 438S, 2003. 50. Pastinen, T. and Hudson, T. J. Cis-acting regulatory variation in the human genome. Science, 306, 647, 2004.

10

IL10 Ross Lazarus

CONTENTS 10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Genetic Variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 Genetic Variation and IL-10 Expression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 Disease Association Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 IL10 Resequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.6 IL10 Variation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 SNP Location and Unambiguous Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.8 IL10 Pairwise Linkage Disequilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 IL10 Haplotypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.10 Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowlegments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

133 134 134 134 137 137 138 139 139 139 142 142

10.1 INTRODUCTION Initially referred to as cytokine synthesis inhibitory factor (CSIF),1 Interleukin-10 (IL10) is an immuno-modulatory cytokine with an important role as a down-regulator of allergic inflammation and cellular immunity. IL-10 appears to inhibit both lymphocyte replication and secretion of pro-inflammatory TH1 cytokines, including other members of the Interleukin family (specifically IL1, IL6, IL8, and IL12), and inhibition of secretion of tumor necrosis factor a (TNF), by activated macrophages.2 IL-10 is produced by a broad range of cells including dendritic cells, B cells, CD4þ and CD8þ T cells, macrophages, and antigenpresenting cells stimulated by bacterial pathogens. Regulatory T cells (tregs) are CD4þ T cells that inhibit immune responses. Two broad types have been described – naturally occurring tregs and IL-10 secreting tregs, which appear to function independently, although the precise details of their interactions are not yet fully understood.3 IL-10 secreting tregs are increased by antigen administration induced anergy and tolerance in-vivo,3 suggesting a role in the development of peripheral tolerance. There is a delicate balance between efficient eradication of potential pathogens and damage to health. Mechanisms to limit normal immune responses are needed because healthy immune responses to pathogens include inflammatory and even auto-immune pathologies which can potentially damage healthy tissue. IL-10 appears to play a key role in mechanisms limiting this collateral damage from the normal immune responses necessary for the effective eradication of potential pathogens. The IL-10 protein (Swiss-Prot P22301) is a Class 2 a-helical cytokine containing 178 amino acids. IL-10 has evolutionarily conserved cysteines in disulfide bonds.4 It has been noted to have structural similarities to the BCRF1 protein from Epstein–Barr virus,5 which inhibits the synthesis of gamma-interferon.6 133

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Cytokine Gene Polymorphisms in Multifactorial Conditions

10.2 GENETIC VARIATION IL10 genetic variation is common and important in humans. Although not as rich in variation as many of the pathogen associated molecular pattern recognition genes such as TLR4 and the other human TOLL-like receptors,7 there are about 14 reasonably common (45%) single nucleotide polymorphisms (SNP) in IL10, described below. At least some of this variation appears to be functional, because there is good evidence that circulating human IL-10 levels vary in association with specific SNP genotypes. In addition, a wide variety of diseases in which inflammation plays an important role have been shown to have significant statistical associations with patterns of IL10 human genetic variation. These are briefly described below, together with a comprehensive catalogue of SNPs, patterns of linkage disequilibrium (LD) and common haplotypes discovered in three distinct population samples. Differences in these patterns illustrate the importance of considering population history when trying to understand the genetic architecture of the IL10 gene or studying genetic effects on disease.

10.3 GENETIC VARIATION AND IL-10 EXPRESSION There is good evidence that both IL-10 production and circulating IL-10 levels are substantially affected by polymorphisms in the 50 (upstream) region near the start of the first IL10 exon. Three polymorphisms in this region appear to change regulatory elements so that specific 3 locus haplotypes appear to influence transcription of the gene,8,9 and thus detectable circulating and tissue levels of the cytokine. This suggests a possible functional explanation for variability in gene expression accompanying genetic variation upstream of the coding region of the gene.

10.4 DISEASE ASSOCIATION STUDIES IL10 has been mapped to human chromosome 1, between 1q31 and 1q32,10 and has five exons (see Figure 10.1). As much as three-quarters of inter-individual variability in IL10 production is thought to be associated with genetic variation.9 Given this large genetic component to IL-10 circulating blood levels, and the fundamental importance of cytokine regulation in immune and inflammatory processes, it is hardly surprising that many studies have tested and most, but not all, have found association between various IL10 polymorphisms and risk of diseases associated with disordered immunity and

FIGURE 10.1 IL10 Genomic context and gene structure. Images from http://genome.ucsc.edu/ – the UCSC Golden Path genome browser.

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IL10

inflammation, including asthma, cancer, infection, systemic lupus erythematosis, and rheumatoid arthritis. A summary of published reports on IL10 in humans is shown in Table 10.1, where a study is shown as positive if the authors claimed statistical significance for their results. In most cases, authors used the conventional p-value cutoff of 0.05 or less to indicate statistical significance. It should be pointed out that in many studies large numbers of hypotheses were tested. Measures to control Type I statistical error over a large number of statistical tests are readily available and are necessary to guard against false positive findings. Unfortunately, in many cases in Table 10.1, these measures were not applied, so some of these tests were undoubtedly significant purely by chance alone.

TABLE 10.1 Published IL10 Disease Association Studies Phenotype Alzheimer’s disease Asthma – IgE, eosinophil count Asthma Asthma/eosinophilia Asthma Asthma Asthma Cancer: Cervical Cancer: Colorectal Cancer: Gastric carcinoma Cancer: Gastric carcinoma Cancer: Gastric carcinoma Cancer: Nasopharyngeal Cancer: Non-Hodgkin’s lymphoma Cancer: Skin squamous cell Cancer: Small cell lung cancer Coeliac disease CVD CVD CVD CVD (CAD/MI) Epidermodysplasia verruciformis Graft: Graft versus host disease Graft: Graft versus host disease Graft: Graft versus host disease Graft: Graft versus host disease Human longevity IL10 Production after surgery Increased IL10 production Increased IL10 production Infection: Epstein–Barr virus Infection: Epstein–Barr virus Infection: Hepatitis C Infection: Hepatitis C Infection Hepatitis C Infection: Herpes zoster Infection: Parvovirus B19

Reference

Study Size 29

Positive

PubMed ID

Scassellati 2004 Karjalainen 200330 Lim 199831 Immervoll 200132 Hakonarson 200133 Lyons 200434 Chatterjee35 Stanczuk 200136 Macarthur 200537 Wu 200338 Wu 200239 Sicinschi 200540 Pratesi 200541 Breen 200342

Case ¼ 215, control ¼ 153 Cases ¼ 245, controls ¼ 405 Cases ¼ 193, controls ¼ 241 97 multiplex families Cases ¼ 94, controls ¼ 94 518 trios Cases ¼ 272, controls ¼ 307 Cases ¼ 77, controls ¼ 69 Cases ¼ 264, controls ¼ 408 Cases ¼ 220, controls ¼ 230 Cases ¼ 120, controls ¼ 220 Cases ¼ 183, controls ¼ 377 Cases ¼ 89, controls ¼ 130 n ¼ 1157

Y N Y Y N Y Y Y N Y Y Y N Y

14746878 12534553 9672280 11668616 11739132 14748015 16008678 11745479 16030091 12594817 11756988 16114018 16059673 14597210

Alamartine 200343 Shih 200544 Lio 200545 Bijlsma 200146 Chou 200347 Hirashiki 200348 Koch 200149 de Oliveira 200313 Asderakis 200150 Kogler 200251 Lin 200352 Middleton 199853 Wang 200154 Galley 200355 Suarez 200326 Kilpinen 200225 Helminen 199956 Helminen 200157 Barrett 200358 Knapp 200359 Oleksyk 200560 Haanpaa 200261 Kerr 200362

Cases ¼ 70, controls ¼ 70 Cases ¼ 154, controls ¼ 205 Cases ¼ 110, controls ¼ 220 n ¼ 70 Cases ¼ 100, controls ¼ 103 Cases ¼ 1011, controls ¼ 650 Cases ¼ 998/793, controls ¼ 340 Cases ¼ 22, controls ¼ 27 n ¼ 88 n ¼ 115 n ¼ 993 n ¼ 49 Cases ¼ 250, controls ¼ 400 n ¼ 150 n ¼ 183 n ¼ 400 Cases ¼ 36, controls ¼ 72 n ¼ 116 n ¼ 158 n ¼ 659 AA cases ¼ 91, controls ¼ 183 Cases ¼ 60, controls ¼ 400 Cases ¼ 36, controls ¼ 330

Y Y N N N N N Y Y N Y Y N Y Y Y Y Y N Y Y Y N

12535204 16122836 15979955 11260510 12578333 14563588 11689215 14512909 11292301 12438965 14657427 9808588 11640949 12925485 12640314 11956022 10395868 11517440 12938195 12942209 15815689 11928840 14514772 (continued )

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Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 10.1 Continued Phenotype Infection: Periodontitis Infection: Pneumococcus Infection: Pneumonia Infection: RSV Inflammatory bowel disease/UC Inflammatory bowel disease/CD Longevity Osteoarthritis Psoriasis Psoriasis, familial early onset Reactive arthritis Recurrent pregnancy loss Rheumatic cardiac disease Rheumatoid arthritis Rheumatoid arthritis Rheumatoid arthritis Schizophrenia Sjogrens syndrome Spontaneous preterm birth Sudden infant death syndrome Suppression of contact sensitivity Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Systemic lupus erythematosus Total serum IgE Type 1 diabetes Type 1 diabetes Type 1 diabetes Wegener’s granulomatosis

Reference

Study Size

Positive

PubMed ID

Berglundh 200363 Schaaf 200364 Gallagher 200365 Hoebee 200466 Tagore 199967 Fernandez 200568 Lio 200269 Riyazi 200570 Reich 199971 Hensen 200372 Kaluza 200173 Daher 200374 Chou 200575 Crawley 19998 Huizinga 200012 Lard 200376 Chiavetto 200277 Hulkkonen 200178 Kalish 200479 Summers 200080 Allen 199881 Gibson 200182 D’Alfonso 200283 D’Alfonso 200084 Crawley 19998 Eskdale 199785 Guseva 200386 Lazarus 199787 Mehrian 199888 Mok 199889 Nakashima 199990 Nath 200591 Hobbs 199892 Ide 200393 Ide 200294 Tegoshi 200495 Zhou 200296

Cases ¼ 60, controls ¼ 39 Cases ¼ 69, controls ¼ 50 Case ¼ 93, controls ¼ 90 Cases ¼ 207, controls ¼ 407 Cases ¼ 81, controls ¼ 330 Cases ¼ 228, controls ¼ 572 Cases ¼ 190, controls ¼ 260 n ¼ 172 Cases ¼ 151, controls ¼ 123 137 trios Cases ¼ 85, controls ¼ 62 Cases ¼ 48, controls ¼ 108 Cases ¼ 115, controls ¼ 163 Cases ¼ 274, controls ¼ 435 Cases ¼ 7, controls ¼ 6 Cases ¼ 283, controls ¼ 1220 Cases ¼ 106, controls ¼143 Cases ¼ 62, controls ¼ 400 n ¼ 73 Cases ¼ 23, controls ¼ 330 n ¼ 42 Cases ¼ 60, controls ¼ 64 Cases ¼ 205, controls ¼ 631 Cases ¼ 172, controls ¼ 172 Cases ¼ 120, controls¼ 274 Cases ¼ 56, controls ¼ 102 Cases ¼ 49, controls ¼ 81 Cases ¼ 76, controls ¼ 119 Cases ¼ 158, controls ¼ 223 Cases ¼ 88, controls ¼ 83 Cases ¼ 109, controls ¼ 102 Meta-analysis, 16 studies 30 multiplex familes Cases ¼ 352, controls ¼ 107 Cases ¼ 128, controls ¼ 107 Cases ¼ 207, controls ¼ 160 Cases ¼36, controls ¼ 109

Y Y Y Y Y Y Y N Y Y Y Y N Y Y Y Y Y N Y N Y Y Y N Y Y Y Y N N Y Y N Y N Y

12631183 12746253 12554901 14722888 10551422 16043989 11857058 16078336 10469306 12932247 11352256 12609526 16043936 10366102 11085795 12847677 11922883 11212157 15042002 11163082 9767235 11238636 12486603 10643707 10513824 9234486 12847896 9415634 9550468 9627019 10556270 16133175 9847292 14679088 12121678 11821159 11838849

Abbreviation: AA, African-Americans. Note that the PubMed ID can be used as a search term, to quickly and accurately locate the article on the internet at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db ¼ PubMed.

A large variety of both common (e.g. cardio-vascular disease) and rare (e.g. epidermodysplasia verruciformis) diseases have been studied, united primarily by their inflammatory manifestations or basis, and many of them are positive. This may be partly explained by publication bias favoring publication of positive studies in the literature, with many negative studies never seeing the light of day. For any given disease susceptibility locus allele frequency and penetrance, statistical power to detect a true effect in a genetic association study depends on the sample size.11 Table 10.1 shows numerous studies with tiny samples, such as the comparison between groups of seven and six patients with specific subphenotypes studied by Huizinga,12 or the 22 cases of the rare disease epidermodysplasia verruciformis and 27 controls reported by

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de Oliveira.13 These have such poor statistical power that they are unlikely to detect a moderately large effect size.11 In addition, the quality of many of the studies leaves much to be desired in terms of design, control selection and statistical genetics. Important differences in human genetic characteristics and in disease risk associated with population history are well recognized.14 As a result, case-control and cohort based genedisease association studies may be confounded by differences in the proportion of different populations among diseased and control subjects. Despite all these potential deficiencies and caveats, it is clear from Table 10.1 that genetic variations in the genomic region around IL10 are frequently found to be associated with disease risk for a very wide range of disorders potentially related to the control of inflammation.

10.5 IL10 RESEQUENCING As part of the work of the Innate Immunity Program in Genomic Applications (IIPGA – see http://innateimmunity.net), the genomic region encoding the IL10 gene was resequenced in 71 individuals – 23 CEPH (European Americans), 24 African American samples, and 24 DNA samples from individuals of self-identified Hispanic ethnicity. All of the methods, primers and details have been previously published,15 and all of the primary data and a wide range of reports and images are freely available for download and viewing at the web site, for this gene and more than 80 others, including a variety of cytokines and their receptors.

10.6 IL10 VARIATION With 48 chromosomes in a sample, the sequencing had a power of 85% or more to detect at least one allele of any real SNPs with minor allele frequency (MAF) of 0.04 or greater in each sample, but rarer markers may have been missed. Note that not all SNPs were found in all samples. Table 10.2 shows the 28 SNPs detected in the 71 subjects. Sixteen SNPs had a frequency of
2% and 14 SNPs had a frequency of
5%. None of the SNPs caused changes in encoded amino acid sequence. Of the SNPs shown in Table 10.2, the first nine are in the 50 (upstream) or promoter region of the IL10 gene and the last six are in the 30 flank. Six SNP (3835 to 4751 in Table 10.1) are in the fifth IL10 exon. All of the others are located in introns. Flanks for each marker are available from the IIPGA website for designing primers for assays. Twelve of the SNPs shown in Table 10.2 were restricted to subjects from a single population sample; six SNPs were only observed in the African American sample, four in the Hispanic American sample and two in the European American sample. All of these population-specific SNPs had a frequency 55% in the population in which it was found. Two SNPs (886 and 2483; see Table 10.2) were detected only in European American and Hispanic American samples, but were not detected in any African American subjects. All of the SNPs shown in Table 10.2 were in Hardy–Weinberg (HW) equilibrium among the African American and European samples. Among the Hispanic American sample, four SNPs (854, 627, 1135, and 1547) were not in HW equilibrium (P50.02 before correction for multiple tests, see the IIPGA web site for details). Using an appropriate method to ensure a false discovery rate of 0.05 over multiple tests,16 none of these Hardy– Weinberg test p-values were significant, suggesting that they were a chance finding, since 28 tests were performed in each of three samples. All of the SNPs occurring with 45% frequency in the three samples combined were detected in subjects from all three

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Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 10.2 SNPs and their Allele Frequencies by Population Sample Offset

Allele1

Afr. Amer.

European

Hispanic

Tot. Pop

Allele 2

dbSNP ID

1791 1524 21387 21117 886 2854 2627 464 919 1135 1547 1668 1703 1812 2483 2664 3835 3916 3990 4144 4251 4751 4949 5333 5466 5470 5876 6474

C C G A G C C G G G C A G G T A T T A A A A T G C G C C

0.979 0.958 0.583 0.595 1.000 0.457 0.500 0.958 0.435 0.524 0.521 0.958 1.000 0.957 1.000 1.000 1.000 0.646 0.979 1.000 0.854 0.974 0.630 0.979 1.000 0.646 0.913 1.000

1.000 1.000 0.522 0.500 0.935 0.761 0.773 1.000 0.717 0.789 0.775 0.719 0.969 0.833 0.921 1.000 1.000 0.522 1.000 0.978 0.804 1.000 0.545 1.000 1.000 0.545 0.783 1.000

1.000 1.000 0.688 0.674 0.958 0.583 0.583 1.000 0.568 0.579 0.646 0.896 1.000 0.896 0.929 0.957 0.978 0.674 1.000 1.000 0.896 1.000 0.674 1.000 0.958 0.674 0.886 0.978

0.994 0.983 0.589 0.582 0.972 0.640 0.665 0.983 0.615 0.675 0.690 0.886 0.994 0.852 0.963 0.988 0.994 0.607 0.994 0.994 0.861 0.993 0.605 0.994 0.989 0.609 0.829 0.994

A T A G A T A T T A T T A T C G C C G T G G C A T A T G

rs5743623 rs5743624 rs1800893 rs1800896 rs1800894 rs1800871 rs1800872 rs3024489 rs1518110 rs1518111 rs1554286 rs3024492 rs3024507 rs3024493 rs3024509 rs5743627 rs5743628 rs3024496 rs3024497 rs3024510 rs3024498 rs3024499 rs3024500 rs3024501 rs574363 rs3024502 rs3024505 –

Note that the 14 SNPs with a rare allele frequency of 5% or more are shown in bold face.

population samples. Linkage disequilibrium and haplotype analysis was restricted to these 14 cosmopolitan (i.e. seen in all three samples) SNPs. It is also important to note that very large samples or extreme effect sizes are needed to obtain adequate statistical power for less common polymorphisms.11

10.7 SNP LOCATION AND UNAMBIGUOUS IDENTIFICATION One frustration in reviewing the literature on SNPs and disease is that SNPs are not always identified unambiguously. When first discovered, SNPs do not have unambiguous identifiers, and specifying the genomic location accurately requires care and diligence. Most researchers will deposit novel SNPs in the major public databases eventually, so that identifiers become available. When this happens, the SNP flanks are used to place it correctly on the genome at a specific position in a curated reference sequence. Use of dbSNP reference SNP (rs) numbers is recommended as a way of avoiding any ambiguity about which SNP is being studied. For example, a recent publication17 describes genotypes for an IL10 SNP identified using the gene relative coordinates of 1082. This is the most recent in a very long series of publications (e.g. Turner,18 Donger,19 D’Alphonso20) attributing that designation to an important SNP. In the literature, this notation is typically used to refer to the genomic position located 1082 nucleotides upstream of the first nucleotide in the triplet (ATG) which

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139

signals the start of translation of the transcribed messenger RNA strand into the gene protein. In the case of IL10, there is a 30 base untranslated region at the start of the transcript, so the designation might be meant to indicate 1082 nucleotides 50 of the start of the transcript. Although this particular site has been repeatedly reported as harboring a common SNP, there does not appear to be a common variant at the stated position in the resequencing performed by our group or by the only other group (Seattle SNPs) who are known to have resequenced IL10, and this difference does not seem to be explained by the UTR. Fortunately, the authors provided the forward (50 -ccaactggctccccttaccttctac-30 ) and reverse 0 (5 -caggattccatggaggctgg-30 ) primers, so it is possible to use the UCSC in-silico PCR utility (http://genome.ucsc.edu/) to learn that these primers will amplify a region on chr1:203335229– 203335394. This region appears to be centered on rs1800896, a SNP discovered in the resequencing performed by the IIPGA, which is probably more correctly placed at –1117 nucleotides from the site of the start of IL10 translation. The 30 base 50 untranslated region (UTR) does not explain a 35 base-pairs difference in coordinates. The initial location may have been correct in the human genome data available at that time, subsequently improved through better bioinformatics and larger quantities of high-quality sequence. It is not clear why the same gene-relative location continues to be reported in multiple studies, considering that accurate resequenced data and dbSNP identifiers were published in 2002.15 It is certainly the case that the use of dbSNP rs numbers helps to minimize uncertainty or ambiguity and makes comparability between reports easier and more reliable.

10.8 IL10 PAIRWISE LINKAGE DISEQUILIBRIUM Figures 10.2A–C show the pattern of pairwise LD among SNPs with frequency
10% in the three samples. While the African American sample had more SNPs overall, there were fewer common SNPs (n ¼ 11) compared to the Hispanic and European American samples (n ¼ 14) so the images are not directly comparable. LD in common SNPs is very similar between European and Hispanic American samples with a relatively strong block of LD in the region of the promoter and first exon.

10.9 IL10 HAPLOTYPES Haplotypes were inferred using Bayesian methods21 implemented in the Phase21 package for the 14 common SNPs. Each subject gives rise to two inferred haplotypes corresponding to the two copies of the IL10 gene. Table 10.3 shows the frequency of haplotypes by population group, excluding the four haplotypes encountered only once in the entire sample. The haplotype frequencies are significantly different in the three population samples (Fisher’s Exact test, P ¼ 0.0000001). The order of alleles within each haplotype shown in Table 10.3 correspond to the order of the 14 common SNPs shown in bold in Table 10.2 (1387, 1117, 854, 627, 919, 1135, 1547, 1668, 1812, 3916, 4251, 4949, 5470, and 5876). Overall, the most frequent haplotype was the most common in all three samples. Haplotype distributions were similar between European American and Hispanic Americans with both groups sharing the same haplotype as their second most common and only one haplotype seen in European Americans being absent from the Hispanic American sample. Four of the haplotypes observed more than once among the African American group were only seen in that sample.

10.10 SUMMARY High levels of variation are found in non-adaptive immunity pathogen-associated molecular pattern (PAMP) receptor genes, such as the TOLL-like receptors, perhaps related

140

Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 10.2 Pairwise linkage disequilibrium as r2 for SNP with MAF
0.1. (A) European Americans; (B) Hispanic Americans; (C) African Americans.

141

IL10

FIGURE 10.2 Continued.

TABLE 10.3 Haplotypes Observed More Than Once in Any Single Population Sample

rs1518111

rs1554286

rs3024492

rs3024493

rs3024496

rs3024498

rs3024500

rs3024502

rs3024505

A C C C C A C C C C C

T G G G G T G T T G T

A G G G G A G A G G A

T C C C C C C T C C C

A A A A T A A A T A T

G G T G G G G G G G G

T T C C C T C T C T C

A A A A G A G A G A G

T T C C C T C T C T C

G G A A A G A G A G A

C C T C C C C C C C C

10 13 10 3 7 1 0 0 0 0 2

17 13 4 5 5 3 0 0 0 0 0

18 4 3 6 0 1 5 4 2 2 0

Total

rs1518110

T C C C C T C T C C C

AA

rs1800872

A A G G G A G A G G G

HA

rs1800871

G G A A A G A G A A A

EA

rs1800896

Sample Counts**

rs1800893

Haplotype*

45 30 17 14 12 5 5 4 2 2 2

*Haplotypes inferred using Phase for the 14 SNP
10% in at least one of the samples. ** EA ¼ European American (CEPH) (n ¼ 23), HA ¼ Hispanic American (n ¼ 24), AA ¼ African American (n ¼ 24). Note that only haplotypes seen twice or more are shown, so four haplotypes, each seen only once, are omitted. Equal population frequency, p ¼ 0.000 000 1 using Fisher’s Exact test.

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Cytokine Gene Polymorphisms in Multifactorial Conditions

to the need for diversity, in order for a species to cope with rapidly changing proteins and nucleotide fragments from viral, bacterial, and other pathogens.7 In contrast, with about 1 SNP every 400 bases, IL10 is much less polymorphic than the TLRs and there are no common SNP which cause an amino-acid substitution in the protein. Variation in IL-10 protein structure may be disadvantageous and not well tolerated, in contrast to receptor structures. A greater number of population-specific polymorphisms were identified in the African American sample (n ¼ 6), compared to the European American (n ¼ 2) and Hispanic American (n ¼ 4) samples (Table 10.2), as has been reported from other multi-population comparisons in other human genes.22–24 As expected, these population-specific SNPs tended to have a low frequency, whereas more common SNPs were more likely to be common to all three ethnic groups.24 Three IL10 SNP in the 50 region have been repeatedly reported with designations 1082, 819, and 592. Based on reported genotypes, these are likely to be rs1800896 (1117), rs1800871 (854), and rs1800872 (627) respectively (Table 10.2). Assuming that the SNP often designated at –1082 is really rs1800896, it has previously been shown to be associated with differences in IL10 production in vitro,18 and in vivo.25,26 One case-control study has been reported in which a specific haplotype (ATA at 1117, 854, and 627 respectively) based on the SNPs described by Turner18 were found to be associated with severe asthma.27 Given its central role in the down regulation of cytokine mediated inflammatory processes, genetic variation in IL10 is of current interest as a source of new approaches to the prevention and management of asthma.28 In addition, since IL10 plays a key role in the regulation of immune and inflammatory responses, these polymorphisms may be of importance in a wide range of other human diseases. Although a relatively large number of haplotypes were detected, four of these accounted for more than 80% of all haplotypes in the three populations sampled. The African American sample had a relatively large number of population specific haplotypes and a distinct distribution pattern of shared haplotypes compared with the Hispanic American and European American samples. Note that these haplotypes were inferred using 14 SNPs with frequency
10% in any one sample, and that all of these SNP were detected in all three populations, so the explanation for the distinct haplotype pattern in the African American sample is not simply related to the presence of African American population-specific SNPs. The number of subjects sampled from each population was relatively small, so the differences in patterns of linkage disequilibrium, SNPs, and haplotypes are imprecise at best. However, they appear to be consistent with findings from large multi-population, multi-gene surveys,22,24 and may have important implications for the design and analysis of disease association studies of IL10 polymorphisms.

ACKNOWLEDGMENTS Support for this work through NIH grants U01 HL065899, R01 HG003646 and a grant from the Donald W. Reynolds Foundation, is gratefully acknowledged.

REFERENCES 1. Fiorentino, D. F. et al., Two types of mouse T helper cell. IV. Th2 clones secrete a factor that inhibits cytokine production by Th1 clones, Journal of Experimental Medicine, 170, 2081–2095, 1989. 2. de Waal Malefyt, R. et al., Interleukin 10 (IL-10) inhibits cytokine synthesis by human monocytes: an autoregulatory role of IL-10 produced by monocytes, Journal of Experimental Medicine, 174, 1209–1220, 1991.

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3. O’Garra, A. and Vieira, P., Regulatory T cells and mechanisms of immune system control, Nature Medicine, 10, 801–805, 2004. 4. Zdanov, A. et al., Crystal structure of interleukin-10 reveals the functional dimer with an unexpected topological similarity to interferon gamma, Structure, 3, 591–601, 1995. 5. Pestka, S. et al., Interleukin-10 and related cytokines and receptors, Annual Reviews in Immunology, 22, 929–979, 2004. 6. Hsu, D. H. et al., In Science, Vol. 250; pp 830–832, 1990. 7. Lazarus, R. et al., Single nucleotide polymorphisms in innate immunity genes: abundant variation and potential role in complex human disease, Immunological Reviews, 190, 9–25, 2002. 8. Crawley, E. et al., Polymorphic haplotypes of the interleukin-10 50 flanking region determine variable interleukin-10 transcription and are associated with particular phenotypes of juvenile rheumatoid arthritis, Arthritis Rheum., 42, 1101–1108, 1999. 9. Westendorp, R. G. J. et al., Genetic influence on cytokine production and fatal meningococcal disease, Lancet, 349, 170–173, 1997. 10. Eskdale, J. et al., Mapping of the human IL10 gene and further characterization of the 50 flanking sequence, Immunogenetics, 46, 120–128, 1997. 11. Purcell, S. et al., Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits, Bioinformatics, 19, 149–150, 2003. 12. Huizinga, T. W. et al., Are differences in interleukin 10 production associated with joint damage?, Rheumatology (Oxford), 39, 1180–1188, 2000. 13. de Oliveira, W. R. et al., Polymorphisms of the interleukin 10 gene promoter in patients from Brazil with epidermodysplasia verruciformis, J. Am. Acad. Dermatol., 49, 639–643, 2003. 14. Reich, D. E. et al., Linkage disequilibrium in the human genome, Nature, 411, 199–204, 2001. 15. Lazarus, R. et al., Single nucleotide polymorphisms in the Interleukin 10 gene: Differences in frequencies, linkage disequilibrium patterns and haplotypes in three US ethnic groups, Genomics, 80, 223–228, 2002. 16. Benjamini, Y. and Yekutieli, D., The control of the false discovery rate in multiple testing under dependency, The Journal of Statistics, 29, 1165–1188, 2001. 17. Shin, H. D. et al., Common interleukin 10 polymorphism associated with decreased risk of tuberculosis, Exp. Mol. Med., 37, 128–132, 2005. 18. Turner, D. M. et al., An investigation of polymorphisms in the Interleukin-10 promoter, European Journal of Immunogenetics, 24, 1–8, 1997. 19. Donger, C. et al., New polymorphisms in the interleukin-10 gene – relationships to myocardial infarction, European Journal of Clinical Investigation, 31, 9–14, 2001. 20. D’Alfonso, S. et al., New polymorphisms in the IL-10 promoter region, Genes and Immunity, 1, 231–233, 2001. 21. Stephens, M. and Li, M., 1.0 ed., Department of Statistics, University of Washington, http:// www.assertion.net/software/: Seattle 2001. 22. Halushka, M. K. et al., Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis, Nature Genetics, 22, 239–247, 1999. 23. Cargill, M. et al., Characterization of single nucleotide polymorphisms in coding regions of human genes, Nature Genetics, 22, 231–238, 1999. 24. Goddard, K. et al., Linkage disequilibrium and allele frequency distributions for 114 singlenucleotide polymorphisms in five populations, American Journal of Human Genetics, 66, 216–234, 2000. 25. Kilpinen, S. et al., The combination of the interleukin-1alpha (IL-1alpha-889) genotype and the interleukin-10 (IL-10 ATA) haplotype is associated with increased interleukin-10 (IL-10) plasma levels in healthy individuals, Eur. Cytokine. Netw., 13, 66–71, 2002. 26. Suarez, A. et al., Interindividual variations in constitutive interleukin-10 messenger RNA and protein levels and their association with genetic polymorphisms, Transplantation, 75, 711–717, 2003. 27. Lim, S. et al., Haplotype associated with low Interleukin 10 production in patients with severe asthma, Lancet, 352, 113, 1998. 28. Stirling, R. G. and Chung, K. F., New immunological approaches and cytokine targets in asthma and allergy, European Respiratory Journal, 16, 1158–1174, 2000.

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29. Scassellati, C. et al., Promoter haplotypes of interleukin-10 gene and sporadic Alzheimer’s disease, Neurosci. Lett., 356, 119–122, 2004. 30. Karjalainen, J. et al., Interleukin-10 gene promoter region polymorphism is associated with eosinophil count and circulating immunoglobulin E in adult asthma, Clin. Exp. Allergy, 33, 78–83, 2003. 31. Lim, S. et al., Haplotype associated with low interleukin-10 production in patients with severe asthma, Lancet, 352, 113, 1998. 32. Immervoll, T. et al., Fine mapping and single nucleotide polymorphism association results of candidate genes for asthma and related phenotypes, Hum. Mutat., 18, 327–336, 2001. 33. Hakonarson, H. et al., Allelic frequencies and patterns of single-nucleotide polymorphisms in candidate genes for asthma and atopy in Iceland, Am. J. Respir. Crit. Care Med., 164, 2036–2044, 2001. 34. Lyons, H. et al., IL10 gene polymorphisms are associated with asthma phenotypes in children, Genetic Epidemiology, 26, 155–165, 2004. 35. Chatterjee, R. et al., Interleukin-10 promoter polymorphisms and atopic asthma in North Indians, Clin. Exp. Allergy, 35, 914–919, 2005. 36. Stanczuk, G. A. et al., Cancer of the uterine cervix may be significantly associated with a gene polymorphism coding for increased IL-10 production, Int. J. Cancer, 94, 792–794, 2001. 37. Macarthur, M. et al., The role of cytokine gene polymorphisms in colorectal cancer and their interaction with aspirin use in the northeast of Scotland, Cancer Epidemiol. Biomarkers Prev., 14, 1613–1618, 2005. 38. Wu, M. S. et al., Interleukin-10 genotypes associate with the risk of gastric carcinoma in Taiwanese Chinese, Int. J. Cancer, 104, 617–623, 2003. 39. Wu, M. S. et al., Tumor necrosis factor-alpha and interleukin-10 promoter polymorphisms in Epstein-Barr virus-associated gastric carcinoma, J. Infect. Dis., 185, 106–109, 2002. 40. Sicinschi, L. A. et al., Gastric cancer risk in a Mexican population: Role of Helicobacter pylori CagA positive infection and polymorphisms in interleukin-1 and -10 genes, Int. J. Cancer, 2005. 41. Pratesi, C. et al., Interleukin-10 and interleukin-18 promoter polymorphisms in an Italian cohort of patients with undifferentiated carcinoma of nasopharyngeal type, Cancer Immunol. Immunother., 2005. 42. Breen, E. C. et al., Non-Hodgkin’s B cell lymphoma in persons with acquired immunodeficiency syndrome is associated with increased serum levels of IL10, or the IL10 promoter -592 C/C genotype, Clin. Immunol., 109, 119–129, 2003. 43. Alamartine, E. et al., Interleukin-10 promoter polymorphisms and susceptibility to skin squamous cell carcinoma after renal transplantation, J. Invest. Dermatol., 120, 99–103, 2003. 44. Shih, C. M. et al., The involvement of genetic polymorphism of IL-10 promoter in non-small cell lung cancer, Lung Cancer, 2005. 45. Lio, D. et al., TNFalpha, IFNgamma and IL-10 gene polymorphisms in a sample of Sicilian patients with coeliac disease, Dig. Liver. Dis., 2005. 46. Bijlsma, F. J. et al., No association between IL-10 promoter gene polymorphism and heart failure or rejection following cardiac transplantation, Tissue Antigens, 57, 151–153, 2001. 47. Chou, H. T. et al., Lack of association of genetic polymorphisms in the interleukin-1beta, interleukin-1 receptor antagonist, interleukin-4 and interleukin-10 genes with mitral valve prolapse in Taiwan Chinese, J. Heart. Valve Dis., 12, 38–44, 2003. 48. Hirashiki, A. et al., Association of gene polymorphisms with coronary artery disease in low- or high-risk subjects defined by conventional risk factors, J. Am. Coll. Cardiol., 42, 1429–1437, 2003. 49. Koch, W. et al., Interleukin-10 and tumor necrosis factor gene polymorphisms and risk of coronary artery disease and myocardial infarction, Atherosclerosis, 159, 137–144, 2001. 50. Asderakis, A. et al., Association of polymorphisms in the human interferon-gamma and interleukin-10 gene with acute and chronic kidney transplant outcome: the cytokine effect on transplantation, Transplantation, 71, 674–677, 2001. 51. Kogler, G. et al., Recipient cytokine genotypes for TNF-alpha and IL-10 and the minor histocompatibility antigens HY and CD31 codon 125 are not associated with occurrence or

IL10

52.

53. 54.

55. 56. 57. 58.

59. 60. 61. 62. 63. 64.

65. 66.

67. 68. 69. 70. 71.

72. 73.

74.

145 severity of acute GVHD in unrelated cord blood transplantation: a retrospective analysis, Transplantation, 74, 1167–1175, 2002. Lin, M. T. et al., Relation of an interleukin-10 promoter polymorphism to graft-versus-host disease and survival after hematopoietic-cell transplantation, N. Engl. J. Med., 349, 2201–2210, 2003. Middleton, P. G. et al., Cytokine gene polymorphisms associating with severe acute graftversus-host disease in HLA-identical sibling transplants, Blood, 92, 3943–3948, 1998. Wang, X. Y. et al., Lack of association between human longevity and polymorphisms of IL-1 cluster, IL-6, IL-10 and TNF-alpha genes in Finnish nonagenarians, Mech. Ageing. Dev., 123, 29–38, 2001. Galley, H. F. et al., Genotype and interleukin-10 responses after cardiopulmonary bypass, Br. J. Anaesth., 91, 424–426, 2003. Helminen, M. et al., Polymorphism of the interleukin-10 gene is associated with susceptibility to Epstein-Barr virus infection, J. Infect Dis., 180, 496–499, 1999. Helminen, M. E. et al., Susceptibility to primary Epstein–Barr virus infection is associated with interleukin-10 gene promoter polymorphism, J. Infect. Dis., 184, 777–780, 2001. Barrett, S. et al., Polymorphisms in tumour necrosis factor-alpha, transforming growth factor-beta, interleukin-10, interleukin-6, interferon-gamma, and outcome of hepatitis C virus infection, J. Med. Virol., 71, 212–218, 2003. Knapp, S. et al., Interleukin-10 promoter polymorphisms and the outcome of hepatitis C virus infection, Immunogenetics, 55, 362–369, 2003. Oleksyk, T. K. et al., Single nucleotide polymorphisms and haplotypes in the IL10 region associated with HCV clearance, Genes and Immunity, 6, 347–357, 2005. Haanpaa, M. et al., Polymorphism of the IL-10 gene is associated with susceptibility to herpes zoster, Scand. J. Infect. Dis., 34, 112–114, 2002. Kerr, J. R. et al., Cytokine gene polymorphisms associated with symptomatic parvovirus B19 infection, J. Clin. Pathol., 56, 725–727, 2003. Berglundh, T. et al., Association of the -1087 IL 10 gene polymorphism with severe chronic periodontitis in Swedish Caucasians, J. Clin. Periodontol., 30, 249–254, 2003. Schaaf, B. M. et al., Pneumococcal septic shock is associated with the interleukin10-1082 gene promoter polymorphism, Am. J. Respir. Crit. Care Med., 168, 476–480, 2003. Gallagher, P. M. et al., Association of IL-10 polymorphism with severity of illness in community acquired pneumonia, Thorax, 58, 154–156, 2003. Hoebee, B. et al., Influence of promoter variants of interleukin-10, interleukin-9, and tumor necrosis factor-alpha genes on respiratory syncytial virus bronchiolitis, J. Infect. Dis., 189, 239–247, 2004. Tagore, A. et al., Interleukin-10 (IL-10) genotypes in inflammatory bowel disease, Tissue Antigens, 54, 386–390, 1999. Fernandez, L. et al., Interleukin-10 polymorphisms in Spanish patients with IBD, Inflamm. Bowel. Dis., 11, 739–743, 2005. Lio, D. et al., Gender-specific association between -1082 IL-10 promoter polymorphism and longevity, Genes Immun., 3, 30–33, 2002. Riyazi, N. et al., The role of interleukin 10 promoter polymorphisms in the susceptibility of distal interphalangeal osteoarthritis, J. Rheumatol., 32, 1571–1575, 2005. Reich, K. et al., Combined analysis of polymorphisms of the tumor necrosis factor-alpha and interleukin-10 promoter regions and polymorphic xenobiotic metabolizing enzymes in psoriasis, J. Invest. Dermatol., 113, 214–220, 1999. Hensen, P. et al., Interleukin-10 promoter polymorphism IL10.G and familial early onset psoriasis, Br. J. Dermatol., 149, 381–385, 2003. Kaluza, W. et al., IL10.G microsatellites mark promoter haplotypes associated with protection against the development of reactive arthritis in Finnish patients, Arthritis Rheum., 44, 1209–1214, 2001. Daher, S. et al., Associations between cytokine gene polymorphisms and recurrent pregnancy loss, J. Reprod. Immunol., 58, 69–77, 2003.

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75. Chou, H. T. et al., Lack of association of genetic polymorphisms in the interleukin-1 Beta, interleukin-1 receptor antagonist, interleukin-4, and interleukin-10 genes with risk of rheumatic heart disease in Taiwan chinese, Int. Heart J., 46, 397–406, 2005. 76. Lard, L. R. et al., Association of the -2849 interleukin-10 promoter polymorphism with autoantibody production and joint destruction in rheumatoid arthritis, Arthritis Rheum., 48, 1841–1848, 2003. 77. Chiavetto, L. B. et al., Association between promoter polymorphic haplotypes of interleukin-10 gene and schizophrenia, Biol. Psychiatry., 51, 480–484, 2002. 78. Hulkkonen, J. et al., Genetic association between interleukin-10 promoter region polymorphisms and primary Sjogren’s syndrome, Arthritis Rheum., 44, 176–179, 2001. 79. Kalish, R. B. et al., Interleukin-4 and 10 gene polymorphisms and spontaneous preterm birth in multifetal gestations, Am. J. Obstet. Gynecol., 190, 702–706, 2004. 80. Summers, A. M. et al., Association of IL-10 genotype with sudden infant death syndrome, Hum. Immunol., 61, 1270–1273, 2000. 81. Allen, M. H. et al., Ultraviolet B induced suppression of induction of contact sensitivity in human skin is not associated with tumour necrosis factor-alpha-308 or interleukin-10 genetic polymorphisms, Br. J. Dermatol., 139, 225–229, 1998. 82. Gibson, A. W. et al., Novel single nucleotide polymorphisms in the distal IL-10 promoter affect IL-10 production and enhance the risk of systemic lupus erythematosus, J. Immunol., 166, 3915–3922, 2001. 83. D’Alfonso, S. et al., Association tests with systemic lupus erythematosus (SLE) of IL10 markers indicate a direct involvement of a CA repeat in the 50 regulatory region, Genes Immun., 3, 454–463, 2002. 84. D’Alfonso, S. et al., Systemic lupus erythematosus candidate genes in the Italian population: evidence for a significant association with interleukin-10, Arthritis Rheum., 43, 120–128, 2000. 85. Eskdale, J. et al., Association between polymorphisms at the human IL-10 locus and systemic lupus erythematosus, Tissue Antigens, 49, 635–639, 1997. 86. Guseva, I. A. et al., [Polymorphism of Fc gamma RIIIA-158F/V gene and promoter region of IL-10 gene in systemic lupus erythematosus in Kazakhs], Ter Arkh, 75, 36–41, 2003. 87. Lazarus, M. et al., Genetic variation in the interleukin 10 gene promoter and systemic lupus erythematosus, J. Rheumatol., 24, 2314–2317, 1997. 88. Mehrian, R. et al., Synergistic effect between IL-10 and bcl-2 genotypes in determining susceptibility to systemic lupus erythematosus, Arthritis Rheum., 41, 596–602, 1998. 89. Mok, C. C. et al., Interleukin-10 promoter polymorphisms in Southern Chinese patients with systemic lupus erythematosus, Arthritis Rheum., 41, 1090–1095, 1998. 90. Nakashima, H. et al., Polymorphisms within the interleukin-10 receptor cDNA gene (IL10R) in Japanese patients with systemic lupus erythematosus, Rheumatology (Oxford), 38, 1142–1144, 1999. 91. Nath, S. K. et al., Polymorphisms of complement receptor 1 and interleukin-10 genes and systemic lupus erythematosus: a meta-analysis, Hum. Genet., 1–10, 2005. 92. Hobbs, K. et al., Interleukin-10 and transforming growth factor-beta promoter polymorphisms in allergies and asthma, Am. J. Respir. Crit. Care Med., 158, 1958–1962, 1998. 93. Ide, A. et al., Interleukin-10 gene promoter region polymorphisms in patients with type 1 diabetes and autoimmune thyroid disease, Ann. NY. Acad. Sci., 1005, 344–347, 2003. 94. Ide, A. et al., Genetic association between interleukin-10 gene promoter region polymorphisms and type 1 diabetes age-at-onset, Hum. Immunol., 63, 690–695, 2002. 95. Tegoshi, H. et al., Polymorphisms of interferon-gamma gene CA-repeat and interleukin-10 promoter region (-592A/C) in Japanese type I diabetes, Hum. Immunol., 63, 121–128, 2002. 96. Zhou, Y. et al., Novel genetic association of Wegener’s granulomatosis with the interleukin 10 gene, J. Rheumatol., 29, 317–320, 2002.

11

The IL19 Subfamily of Cytokines Sulev Ko˜ks, Ku¨lli Kingo, Eero Vasar, and Helgi Silm

CONTENTS 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Molecular Biology of Cytokines Belonging to the IL-19 Subfamily . . . . . . . . . . . . 11.3 Functions of IL-19 Family Cytokines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 Molecular Genetic Studies on the IL19 Subfamily . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

147 147 148 150 153

11.1 INTRODUCTION Interleukin-19, interleukin-20, and interleukin-24 belong to the interleukin-10 family of cytokines, which comprises a series of herpesviral and poxviral members and human cellular paralogs of IL-10 (IL-19, IL-20, IL-22, IL-24, and IL-26).1 Human cellular IL-10-related cytokines form additionally two subfamilies of more closely-related ligands based on receptor-chain sharing between these cytokines — IL-10 subfamily and IL-19 subfamily. The IL-10 subfamily contains IL-10 itself (see Chapter 10), IL-22, and IL-26 (see Chapter 12), while the IL-19 subfamily contains IL-19, IL-20, and IL-24 and is discussed in this chapter.2 IL-19 and IL-20 were identified recently by a sequence database search aimed at finding potential IL-10 homologs.3,4 IL-24 was primarily cloned by subtraction hybridization in 1995 and first named mda-7 (melanoma differentiation-associated protein 7), but its homology with IL-10 as well as its cytokine-like features were not originally reported.5 The members of the IL-19 subfamily share limited primary sequence, structural homologies and receptor subunits. Although the exact biological functions of the IL-19, IL-20, and IL-24 are still unknown, they possess pleiotropic cell-specific activities, and are clearly involved in the regulation of inflammatory responses in various tissues.

11.2 MOLECULAR BIOLOGY OF CYTOKINES BELONGING TO THE IL-19 SUBFAMILY The IL19, IL20, and IL24 genes together with the IL10 gene locate in an IL10 gene cluster in a 200 kb region of chromosome 1 within the locus q31–32. The genes encoding members of the IL-19 subfamily (IL-19, IL-20, and IL-24) have similar structural features. All three genes are positioned in a head-to-tail direction and are oriented toward the telomere on chromosome 1 (Figure 11.1). The IL20 gene consists of five exons and four introns. The genes that encode IL-19 and IL-24 have additional exons positioned upstream of their first coding exons, and therefore the exons that encode the 50 -UTRs of the IL19 and IL24 mRNAs are alternatively spliced.3,6,7 The IL19 and IL24 genes are composed of seven exons and six introns. The lengths of the respective exons are virtually identical between members of the IL19 subfamily, although intron sizes vary substantially. The junctions between the exons 147

148

Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 11.1 Genomic locus containing IL10, IL19, IL20, and IL24 genes. Coding regions (CDS) and mRNAs of respective genes are also shown in the illustration.

and introns of the IL19, IL20, and IL24 genes conform to standard motifs (GT/AG rule). The genomic locus containing the IL10, IL19, IL20, and IL24 genes is shown in Figure 11.1. The extent of amino acid homology between the members of the IL-19 subfamily is not extensive (in the 30–45% range), but all three cytokines — IL-19, IL-20, and IL-24 — are members of the class of long helical cytokines.4,8,9 Three-dimensional structures of IL-19 and IL-20 are very similar. The molecules of IL-19 and IL-20 are monomers made up of seven amphipathic helices, forming a seven-helix bundle with an extensive internal hydrophobic core.8 IL-24 can exist as both monomer and dimer depending on the reduction state of the disulfide pair.9 Additionally all three cytokines have N-terminal signal peptides that are classically present in secreted molecules. IL-20 is found preferentially expressed in monocytes.10 Its main targets are keratinocytes where IL-20 binds type I IL-20R (IL-20Ra and IL-20Rb) and type II IL-20R (IL-20Rb and IL-22R) complexes.11 IL-19 has been detected in immune cells, such as LPS- or GM-CSFactivated and resting monocytes, and at lower level in resting and stimulated B cells.3,10 This cytokine binds to the type I IL-20R complex.11 IL-24 expression is detected in some cultured melanocytes and in peripheral blood mononuclear cells (PBMC) by ConA stimulation.5,12 In blood, the cytokine IL-24 is expressed mainly in monocytes. IL-24 is up-regulated by LPS stimulation in monocytes and by anti-CD3 monoclonal antibody activation in T cells.10 IL24 binds to type I and type II IL-20 receptor complexes.11,12 Binding of the members of the IL-19 subfamily to the IL-20 receptor complexes activates STAT signalling pathway in cytokine responsive cells.13 Pletnev et al. have verified that IL-20Rb represents a high-affinity receptor for the members of IL-19 subfamily, whereas IL-20Ra is a low-affinity receptor.14

11.3 FUNCTIONS OF IL-19 FAMILY CYTOKINES Cytokine IL-19 acts as a pro-inflammatory cytokine or modulator of the inflammatory response. IL-19 induces cell apoptosis, production of cytokines IL-6, TNF-a, and reactive oxygen species in monocytes.6 Moreover, IL-19 induces IL-4, IL-5, IL-10, and IL-13

The IL19 Subfamily of Cytokines

149

production by Th2 cells and inhibits IFN-g production by Th1 cells.15 Similarly, Gallagher et al. have established that IL-19 up-regulates IL-4 and down-regulates IFN-g in whole blood PBMC culture.2 The fact that IL-19 shares the same receptor complex with IL-20 (type I IL-20R that is composed from IL-20Ra and IL-20Rb subunits) indicates that IL-19 may have partially overlapping biological activities with IL-20. IL-19 is markedly elevated in psoriatic lesions and is strongly suppressed by administration of IL-4 during the improvement of psoriasis.16 Romer et al. have confirmed the pathogenic role of IL-19 in psoriasis demonstrating the higher expression of IL-19 in involved psoriatic skin in contrast to uninvolved psoriatic skin.17 Moreover, IL-19 may contribute to the pathogenesis of asthma. The excessive production of IL-4, IL-5, and IL-13 by Th2 cells has been established in asthma. Recently an increased level of serum IL-19 in the group of asthmatic patients compared with controls was found, whereby the level of IL-19 correlated with the levels of IL-4 and IL-13.15 Based on the expression pattern of IL-20 and of its receptor, one of the major physiological functions of the IL-20 signalling pathway is related to epidermal functions. Two lines of evidence suggest the role of IL-20 in the pathogenesis of psoriasis. The first one is that the over-expression of IL-20 induces skin lesions on transgenic mice similar to skin changes observed in psoriasis. Histological analysis of the skin of IL-20 transgenic mice shows hyperkeratosis, thickened epidermis, and proliferation in the suprabasal layer resembling human psoriatic abnormalities.4 These changes in the skin appear to be caused by circulating IL-20, because even mice expressing the transgene construct in other tissues (liver) were similarly affected with similar skin changes. Microarray and RT-PCR analyses in HaCaT-cells have demonstrated that expression patterns of several genes involved in inflammation are increased in response to IL-20 and therefore this cytokine may modulate the inflammatory response in the skin.4,18 The second line of evidence implicating the role of IL-20 and its receptor in the pathogenesis of psoriasis is that both IL-20 and its receptor subunits (IL-20Ra and IL-20Rb) are markedly up-regulated in human psoriatic skin compared to normal skin.4,17 The up-regulation of both IL-20 receptor subunit mRNAs is detected in keratinocytes as well as in endothelial cells and immune cells. These are the main cell types, which interact in the pathogenesis of psoriasis. IL-20 may also play a part in inflammatory conditions in the brain. Hosoi et al. have demonstrated that bacterial endotoxin induces IL-20 expression in glial cells.19 The expression of IL-20 is regulated by a negative feedback loop mediated through glycocorticoids in the brain. Moreover, systemic application of LPS induces STAT3 activation in the brain during peripheral inflammation and is probably involved in the activation of the HPA axis. For that reason the central IL-20 may affect CNS function during inflammation. IL-24/mda-7 can function either through its cell-surface receptors as a classical cytokine, or intracellulary as a cytotoxic agent to certain cancer cells.12,20 Treatment of PBMC with IL-24 results in the induction of IL-6, IFN-g, TNF-a, IL-1b, IL12, and GM-CSF and therefore IL-24 may also be a member of a complex cascade of cytokines involved in inflammation.21 Moreover, IL24 mRNA is inducible by pro-inflammatory cytokines such as IL-1b. The overexpression of IL24 mRNA by IL-1b is established in human chondrocytes.22 While IL-1b plays a central role in the inflammation and connective tissue destruction that are observed both in rheumatoid arthritis and osteoarthritis, the cytokine IL-24 may also contribute to inflammation and cartilage destruction in arthritis. The finding that IL-24 binds to IL-20 receptor complexes (type I IL-20R and type II IL-20R that is composed from IL-20Rb and IL-22R subunits) indicates that, similarly to IL-20, IL-24 may also be involved in the function of the epidermis. The rat ortholog of the human IL24 gene named as c49a has been found in fibroblast-like cells during the

150

Cytokine Gene Polymorphisms in Multifactorial Conditions

healing process of skin wound.23 The elevated expression of the c49a gene before and during the proliferation phase of repair suggests that c49a might promote cellular proliferation. Moreover, the expression of IL24 mRNA is found in mononuclear cells located in the papillae and in the dense inflammatory areas in the subpapillary dermis in psoriatic lesions.17 IL-24 is a potent growth-suppressor in cancer cells of diverse origin, including glioblastoma, osteosarcoma, and cancers of breast, cervix, ovary, colon, prostate, lung, and nasopharynx.24–27 IL-24 induces also growth arrest and induction of terminal differentiation in human melanoma cells and expression of IL-24 inversely correlates with melanoma progression.5,28,29 In contrast, IL-24 has a negligible effect on growth and does not induce apoptosis in normal epithelial and fibroblast cells.30,31 The exact mechanism of how IL-24 induces apoptosis of various tumor cells is not fully understood, but the involvement of Bax, dsRNA-dependent protein kinase (PRK), and GADD (family of growth arrest and DNA damage) proteins have been reported.32–34 It is also unclear why IL-24 induces apoptosis only in tumor cells. The apoptotic (tumor-suppressive) effect of IL-24 may also depend on IL-24 receptor activation. As IL-10 predominates and IL-24 is suppressed in metastatic tumors, the antitumor immune response may be ineffective to melanoma.21 In addition, it is established that IL-24 suppresses tumor angiogenesis in a receptor-dependent manner, by activating STAT3 in endothelial cell and by blocking cell differentiation.35,36 On the other hand, Aggarwal et al. (2004) have verified that IL-24 may have antiapoptotic activity. Namely, stable transfection of HEK-293 (human embryonic kidney) cells with IL24 potentiates TNF-induced NF-B activation and NF-B regulated gene expression (cyclin D1 and cyclooxygenase-2).37 Therefore, IL-24 is able to abolish TNF-induced apoptosis and could initiate survival signalling.

11.4 MOLECULAR GENETIC STUDIES ON THE IL19 SUBFAMILY The expression of the cytokines IL-19, IL-20, and IL-24 is primarily regulated by transcription factors. Gallagher et al. (2004) sequenced the genomic fragment containing the human IL19 gene and discovered the polymorphic repeat sequence.2 Additionally they identified 22 potentially informative SNPs for genetic analysis studies; eight of them occur in the 50 flanking region, 50 UTR, and intron-1. Computer analysis confirmed that SNPs in noncoding regions are able to create or destroy putative transcription factor binding sites of IL19 gene.2 There is no information about the transcription factor binding sites in the IL20 gene. Analyses of the 50 -upstream nucleotide sequence of the IL24 gene revealed the presence of TATA elements that regulate promoter activity of the IL24 gene. The expression of IL24 gene was mainly regulated by two transcription factors — AP-1 and C/EBP.38 The relevance of IL10 polymorphisms has been demonstrated by their involvement in determining susceptibility to and/or severity for a number of immune-inflammatory, malignant and infectious diseases.39–42 Although descriptions of SNPs of IL19, IL20, and IL24 genes are accessible in the NCBI dbSNP database (www.ncbi.nlm.nih.gov/SNP/), polymorphisms of these genes have been investigated only in psoriasis and HCV infection at the present time. According to the dbSNP database the IL19 cytokine cluster contains 238 SNPs of which most locate in intergenic areas. The IL19 genomic region contains 70 SNPs, one is non-synonymous (rs2243191 C to T transition, and causes substitution of Ser to Phe in position 175). IL20 has 18 SNPs in the genomic region from which one is synonymous. IL24 contains 47 SNPs, three locate in the coding region and all are non-synonymous SNPs (rs1150258 C to T His/Tyr in position 124, rs3093431 G to A causing Arg/His in position 125 and rs3093446 C to G leading to Leu/Val replacement in position 131). We analyzed recently 16 SNPs in IL19 cluster and their impact in genetic risk for psoriasis (details of SNPs are

151

The IL19 Subfamily of Cytokines

TABLE 11.1 Single Nucleotide Polymorphisms in IL19 Cytokine Cluster Analyzed in Patients with Plaque-Type Psoriasis Gene

SNP ID

Position from ATG

Alleles

Minor allele freq

Coding/non-coding (c/nc)

IL19

rs2243158 rs2243168 rs2073186 rs2243174 rs2243188 rs2243191 rs2243193 rs2981572 rs2981573 rs2232360 rs1518108 rs3762344 rs291111 rs1150253 rs1150256 rs1150258

35402 37149 38386 39245 42232 43717 43985 1053 1380 1462 3978 2506 1652 418 1956 3728

G/C A/T C/T A/G C/A C/T G/A T/G A/G A/G T/C G/A T/C A/G A/G C/T

0.1 0.08 0.27 0.23 0.26 0.26 0.27 0.29 0.24 0.25 0.46 0.49 0.03 0.42 0.48 0.49

nc nc nc nc nc c (175 Ser/Phe) nc nc nc nc nc nc nc nc nc c (124 His/Tyr)

IL20

IL24

in Table 11.1). Two non-synonymous SNPs leading to amino acid exchange were also included in our study. In the individual evaluation of SNPs of IL19, IL20, and IL24 genes in a sample of unrelated Caucasian psoriasis patients IL19 SNP rs2243188, IL20 SNPs rs2981572 and rs1518108 had significant association with psoriasis.43,44 In a sample of unrelated patients with HCV infection, the SNPs in IL19 rs2243191, IL20 rs1400986, rs3024517, and rs2232360 had significant associations with HCV clearance in African Americans while no significant associations were observed for alleles in European Americans.45 The block-like distribution of LD has been demonstrated in different cytokine clusters.46,47 In our original study we showed block-like structure of LD formed by the genes IL19, IL20, and IL24.48 We identified the existence of two haplotype blocks with a recombination site between SNPs rs2232360 and rs1518108 within the 67264 bp fragment of human chromosome 1 locus q32 in the region of IL19, IL20, and IL24 genes in Caucasians (Figure 11.2). The first haplotype block (30 kb) includes five SNPs across the IL19 gene (rs2073186, rs 2243174, rs2243188, rs2243191, rs2243193) and three SNPs from the IL20 gene (rs2981572, rs2981573, rs2232360). The second haplotype block (31 kb) includes one SNP from the IL20 gene (rs1518108) and four SNPs across the IL24 gene (rs3762344, rs1150253, rs1150256, rs1150258). Out of all the possible haplotypes five common haplotypes (frequency
1%) were observed within both blocks (Figure 11.3).44,48 Similar haplotype block structure encompassing the IL19 and IL20 genes was also established in African Americans and European Americans.45 There were six common haplotypes within the IL19/IL20 haplotype block in groups of European Americans and African Americans.45 However, African Americans have lower LD between polymorphisms of the IL19 and IL20 genes compared with European Americans. The importance of examining haplotypes of gene clusters has clearly been demonstrated in several studies.49–52 The IL20 haplotype GAA (OR 2.341) and the extended IL19/IL20 haplotype CACCGGAA (OR 2.548) were found to be related to increased risk for plaquetype psoriasis, while the IL20/IL24 extended haplotype CAAAC was associated with

152

Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 11.2 Haplotype blocks within the IL19, IL20, and IL24 genes of human chromosome 1q32.

FIGURE 11.3 Common haplotypes with frequency
1%, formed by SNPs in IL19, IL20, and IL24 genes.

a significant protective effect against plaque-type psoriasis (OR 0.154).43,44,48 Protective effects against psoriasis were also observed with the extended haplotype TGGGT (OR 0.591) and with the extended haplotype CGAGT (OR 0.457).48 Thus, haplotype analysis suggests that cytokines in the IL-19 family could have distinctive roles in the development of psoriasis.

The IL19 Subfamily of Cytokines

153

In particular, IL19 and IL20 genes are related to increased susceptibility, whereas the IL24 gene seems to carry a protective effect in the case of psoriasis. However, as the protective haplotype forms between SNPs in IL24 as well as SNPs in the 30 UTR of the IL20 gene, it is still difficult to say which of these two cytokines, if any, is actually primarily responsible for the protective action. In fact, neither IL24 SNPs when analyzed individually nor the haplotype covering the IL24 locus showed a strong protective impact.48 Extending the haplotype to include 30 UTR SNP in the IL20 gene turned the association into a significantly protective one. SNPs in the 30 UTR could have functional impact in regulatory sequences. Impact of the IL-19 family of cytokines in modulation of inflammation is not restricted only to psoriasis. In a recent study their impact in hepatitis C infection was shown. Two haplotypes in the IL19/IL20 region in African Americans were significantly associated with HCV clearance; i.e. the depleted haplotype (OR 0.56–0.59) and the enriched haplotype (OR 1.93–2.7).45 In conclusion, two haplotype blocks within the region of the IL19 subfamily of genes on human chromosome 1q32 have been identified. In addition, the significant genetic influence of IL19 subfamily cytokines on the development of plaque-type psoriasis and HCV clearance have been verified. Family-based studies and association studies of different populations are required to confirm the impact of the genes of the IL19 subfamily in the genetic predisposition for plaque-type psoriasis and HCV infection. Moreover, functional relevance of analyzed polymorphisms should be investigated in further studies. It also remains as a major issue to determine the importance of the genes of the IL19 subfamily in the pathogenesis of different malignant tumors.

REFERENCES 1. Fickenscher, H. et al., The interleukin-10 family of cytokines, Trends Immunol., 23, 89, 2002. 2. Gallagher, G. et al., Human interleukin-19 and its receptor: a potential role in the induction of Th2 responses, Int. Immunopharmacol, 4, 615, 2004. 3. Gallagher, G. et al., Cloning, expression and initial characterization of interleukin-19 (IL-19), a novel homologue of human interleukin-10 (IL-10), Genes Immun., 1, 442, 2000. 4. Blumberg, H. et al., Interleukin 20: discovery, receptor identification, and role in epidermal function, Cell, 104, 9, 2001. 5. Jiang, H. et al., Subtraction hybridization identifies a novel melanoma differentiation associated gene, mda-7, modulated during human melanoma differentiation, growth and progression, Oncogene, 11, 2477, 1995. 6. Liao, Y. C. et al., IL-19 induces production of IL-6 and TNF-alpha and results in cell apoptosis through TNF-alpha, J. Immunol., 169, 4288, 2002. 7. Kotenko, S. V., The family of IL-10-related cytokines and their receptors: related, but to what extent? Cytokine Growth Factor Rev., 13, 223, 2002. 8. Chang, C. et al., Crystal structure of interleukin-19 defines a new subfamily of helical cytokines, J. Biol. Chem., 278, 3308, 2003. 9. Chada, S. et al., MDA-7/IL-24 is a unique cytokine–tumor suppressor in the IL-10 family, Int. Immunopharmacol., 4, 649, 2004. 10. Wolk, K. et al., Cutting edge: immune cells as sources and targets of the IL-10 family members? J. Immunol., 168, 5397, 2002. 11. Dumoutier, L. et al., Cutting edge: STAT activation by IL-19, IL-20 and mda-7 through IL-20 receptor complexes of two types, J. Immunol., 167, 3545, 2001. 12. Wang, M. et al., Interleukin 24 (MDA-7/MOB-5) signals through two heterodimeric receptors, IL-22R1/IL-20R2 and IL-20R1/IL-20R2, J. Biol. Chem., 277, 7341, 2002. 13. Parrish-Novak, J. et al., Interleukins 19, 20, and 24 signal through two distinct receptor complexes. Differences in receptor-ligand interactions mediate unique biological functions, J. Biol. Chem., 277, 47517, 2002.

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Cytokine Gene Polymorphisms in Multifactorial Conditions

14. Pletnev, S. et al., Characterization of the recombinant extracellular domains of human interleukin-20 receptors and their complexes with interleukin-19 and interleukin-20, Biochemistry, 42, 12617, 2003. 15. Liao, S. C. et al., IL-19 induced Th2 cytokines and was up-regulated in asthma patients, J. Immunol., 173, 6712, 2004. 16. Ghoreschi, K. et al., Interleukin-4 therapy of psoriasis induces Th2 responses and improves human autoimmune disease, Nat. Med., 9, 40, 2003. 17. Romer, J. et al., Epidermal overexpression of interleukin-19 and -20 mRNA in psoriatic skin disappears after short-term treatment with cyclosporine a or calcipotriol, J. Invest. Dermatol., 121, 1306, 2003. 18. Rich, B. E., IL-20: a new target for the treatment of inflammatory skin disease, Expert. Opin. Ther. Targets., 7, 165, 2003. 19. Hosoi, T. et al., Bacterial endotoxin induces IL-20 expression in the glial cells, Brain Res. Mol. Brain. Res., 130, 23, 2004. 20. Sauane, M. et al., Mda-7/IL-24 induces apoptosis of diverse cancer cell lines through JAK/ STAT-independent pathways, J. Cell. Physiol., 196, 334, 2003. 21. Caudell, E. G. et al., The protein product of the tumor suppressor gene, melanoma differentiation-associated gene 7, exhibits immunostimulatory activity and is designated IL-24, J. Immunol., 168, 6041, 2002. 22. Vincenti, M. P. and Brinckerhoff, C. E., Early response genes induced in chondrocytes stimulated with the inflammatory cytokine interleukin-1beta, Arthritis Res., 3, 381, 2001. 23. Soo, C. et al., Cutaneous rat wounds express c49a, a novel gene with homology to the human melanoma differentiation associated gene, mda-7, J. Cell Biochem., 74, 1, 1999. 24. Yacoub, A. et al., Melanoma differentiation-associated 7 (interleukin 24) inhibits growth and enhances radiosensitivity of glioma cells in vitro and in vivo, Clin. Cancer Res., 9, 3272, 2003. 25. Huang, E. Y. et al., Genomic structure, chromosomal localization and expression profile of a novel melanoma differentiation associated (mda-7) gene with cancer specific growth suppressing and apoptosis inducing properties, Oncogene, 20, 7051, 2001. 26. Su, Z. Z. et al., The cancer growth suppressor gene mda-7 selectively induces apoptosis in human breast cancer cells and inhibits tumor growth in nude mice, Proc. Natl. Acad. Sci. USA, 95, 14400, 1998. 27. Leath, C. A., 3rd et al., Infectivity enhanced adenoviral-mediated mda-7/IL-24 gene therapy for ovarian carcinoma, Gynecol. Oncol., 94, 352, 2004. 28. Ekmekcioglu, S. et al., Down-regulated melanoma differentiation associated gene (mda-7) expression in human melanomas, Int. J. Cancer, 94, 54, 2001. 29. Ellerhorst, J. A. et al., Loss of MDA-7 expression with progression of melanoma, J. Clin. Oncol., 20, 1069, 2002. 30. Jiang, H. et al., The melanoma differentiation associated gene mda-7 suppresses cancer cell growth, Proc. Natl. Acad. Sci. USA, 93, 9160, 1996. 31. Saeki, T. et al., Tumor-suppressive effects by adenovirus-mediated mda-7 gene transfer in nonsmall cell lung cancer cell in vitro, Gene Ther., 7, 2051, 2000. 32. Cao, X. X. et al., Adenoviral transfer of mda-7 leads to BAX up-regulation and apoptosis in mesothelioma cells, and is abrogated by over-expression of BCL-XL, Mol. Med., 8, 869, 2002. 33. Pataer, A. et al., Adenoviral transfer of the melanoma differentiation-associated gene 7 (mda7) induces apoptosis of lung cancer cells via up-regulation of the double-stranded RNA-dependent protein kinase (PKR), Cancer Res., 62, 2239, 2002. 34. Sarkar, D. et al., mda-7 (IL-24) Mediates selective apoptosis in human melanoma cells by inducing the coordinated overexpression of the GADD family of genes by means of p38 MAPK, Proc. Natl. Acad. Sci. USA, 99, 10054, 2002. 35. Saeki, T. et al., Inhibition of human lung cancer growth following adenovirus-mediated mda-7 gene expression in vivo, Oncogene, 21, 4558, 2002. 36. Ramesh, R. et al., Melanoma differentiation-associated gene 7/interleukin (IL)-24 is a novel ligand that regulates angiogenesis via the IL-22 receptor, Cancer Res., 63, 5105, 2003. 37. Aggarwal, S. et al., Melanoma differentiation-associated gene-7/IL-24 gene enhances NF-kappa B activation and suppresses apoptosis induced by TNF, J. Immunol., 173, 4368, 2004.

The IL19 Subfamily of Cytokines

155

38. Madireddi, M. T., Dent, P., and Fisher, P. B., Regulation of mda-7 gene expression during human melanoma differentiation, Oncogene, 19, 1362, 2000. 39. Crawley, E. et al., Polymorphic haplotypes of the interleukin-10 50 flanking region determine variable interleukin-10 transcription and are associated with particular phenotypes of juvenile rheumatoid arthritis, Arthritis Rheum., 42, 1101, 1999. 40. Lim, S. et al., Haplotype associated with low interleukin-10 production in patients with severe asthma, Lancet, 352, 113, 1998. 41. Howell, W. M. et al., IL-10 promoter polymorphisms influence tumor development in cutaneous malignant melanoma, Genes Immun., 2, 25, 2001. 42. Shin, H. D. et al., Genetic restriction of HIV-1 pathogenesis to AIDS by promoter alleles of IL10, Proc. Natl. Acad. Sci. USA, 97, 14467, 2000. 43. Kingo, K. et al., Polymorphisms in the interleukin-20 gene: relationships to plaque-type psoriasis, Genes Immun., 5, 117, 2004. 44. Ko˜ks, S. et al., Combined haplotype analysis of the interleukin-19 and -20 genes: relationship to plaque-type psoriasis, Genes Immun., 5, 662, 2004. 45. Oleksyk, T. K. et al., Single nucleotide polymorphisms and haplotypes in the IL10 region associated with HCV clearance, Genes Immun., 2005. 46. Hafler, D. A. and Jager, P. L., Opinion: Applying a new generation of genetic maps to understand human inflammatory disease, Nat. Rev. Immunol., 5, 83, 2005. 47. Rioux, J. D. et al., Genomewide search in Canadian families with inflammatory bowel disease reveals two novel susceptibility loci, Am. J. Hum. Genet, 66, 1863, 2000. 48. Ko˜ks, S. et al., Possible relations between the polymorphisms of the cytokines IL-19, IL-20 and IL-24 and plaque-type psoriasis, Genes Immun., 6, 407, 2005. 49. Carlson, C. S. et al., Mapping complex disease loci in whole-genome association studies, Nature, 429, 446, 2004. 50. Crawford, D. C. and Nickerson, D. A., Definition and clinical importance of haplotypes, Annu. Rev. Med., 56, 303, 2005. 51. Smith, A. J. et al., Extended haplotypes and linkage disequilibrium in the IL1R1-IL1A-IL1BIL1RN gene cluster: association with knee osteoarthritis, Genes Immun., 5, 451, 2004. 52. Undlien, D. E., Lie, B. A., and Thorsby, E., HLA complex genes in type 1 diabetes and other autoimmune diseases. Which genes are involved? Trends Genet., 17, 93, 2001.

12

The IFNG–IL26–IL22 Cytokine Gene Cluster Koen Vandenbroeck and An Goris

CONTENTS 12.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 Haplotype Structure of the IFNG–IL26–IL22 Cytokine Cluster . . . . . . . . . . . . . . . . 12.3 Functional Analysis of Allelic Variation in Intron 1 of IFNG . . . . . . . . . . . . . . . . . . 12.4 IFNG Disease Association Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 IL26 and IL22 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 IFNGR1 and IFNGR2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

157 158 160 160 167 168 168 169

12.1 INTRODUCTION Interferon-g (IFN-g; gene symbol IFNG) is a key modulator of innate and adaptive immune responses and is therefore involved in host protection against viral, bacterial and parasitic infections. The cytokine is known to polarize the acquired immune response toward a Th1 profile (see Chapter 1 for review of the biology of IFN-g). A variety of IFNG or IFNGR gene targeting models have been utilized in attempts to define the multifaceted, and often seemingly contradictory (i.e. disease-promoting or -limiting) effects of this cytokine in autoimmune diseases such as rheumatoid arthritis (RA), multiple sclerosis (MS), diabetes, lupus and inflammatory bowel disease (IBD). Equally, systemic administration of IFN-g or IFN-g-antagonists in experimental animal models pronouncedly affects predisposition to, or recovery from, autoimmune conditions or fungal, bacterial, helminth, or protozoal infections. IFNG has been mapped to human chromosome 12q15, a region showing linkage to MS, RA, IBD, asthma and Type I and II diabetes in a number of genome-wide screens (summarized in Ref. 1). Thus, it is precisely such positional evidence, in combination with the finding of IFN-g being crucially involved in phenotypic expression or modulation of so wide an array of multifactorial conditions, that has made IFNG a prime target of numerous candidate gene studies on complex diseases and conditions. Recent progress in the sequencing of the human genome has uncovered the presence of the genes of two other cytokines, i.e. interleukin-26 (IL-26; previously named AK-155) and IL-22, in close vicinity to IFNG. IL-26 was originally identified in herpes virus saimiritransformed T cells.2 IL-22 is mainly produced by activated Th1-cells, and is thought not to be directly involved in communication between immune cells, but to enhance the innate, non-specific immunity of tissues.3 The chromosomal intimacy of IFNG, IL22, and IL26 is underscored by structural similarities between the genes and proteins. IFN-g, IL-26, and IL-22 are class II a-helical cytokines.4 On the amino acid level, IFN-g, IL-26, and IL-22 show 157

158

Cytokine Gene Polymorphisms in Multifactorial Conditions

a certain degree of similarity within helices C and F which is likely reminiscent of a protein fold or folding pathway conserved in the family of IL-10-related cytokines.5 The discovery of a CA dinucleotide repeat nucleotide polymorphism in the first intron of IFNG in 1993 kicked off an ever-expanding series of disease-association studies, which have been complemented only more recently with SNP and haplotype screens that also include the IL26 and IL22 gene regions.6 The majority of association data published in journals cited by Medline refer therefore to IFNG. Not a single nonsynonymous coding SNP has ever been reported in IFNG. However, though data are still scarce with regard to IL26 and IL22, the influence of allelic variation in intronic/promoter regions of IFNG on gene expression is increasingly being defined. Also, notions on linkage disequilibrium in the IFNG–IL26–IL22 gene cluster and SNP haplotype frequencies and distributions will be of benefit in constructing a more complete model for describing the genetics of the 12q15 cytokine cluster. We will conclude this chapter with a brief overview of studies on the IFNGR1 and IFNGR2 genes.

12.2 HAPLOTYPE STRUCTURE OF THE IFNG–IL26–IL22 CYTOKINE CLUSTER Analysis of data from the HapMap project (Public data release #16, August 2005) reveals the presence of a 79-kb haplotype block surrounding IFNG, succeeded in telomeric direction by a putative recombination hot spot and a 19- kb haplotype block spanning 90% of IL26 (Figure 12.1). The situation around IL22 is as yet less clear. Table 12.1 provides an overview

FIGURE 12.1 Linkage disequilibrium in the IFNG/IL26/IL22 region. Top: Overview of the position and transcription direction of IFNG, IL26 and IL22 genes on chromosome 12 and the position of HapMap SNPs in the region. Bottom: extent of linkage disequilibrium in the European population based on HapMap data and visualized with Haploview: squares indicate pairwise D0 values between SNPs, with dark shades corresponding to high linkage disequilibrium, and outlined areas specify haplotype blocks.

159

The IFNG–IL26–IL22 Cytokine Gene Cluster

TABLE 12.1 Common IFNG Haplotypes and Haplotype Tagging SNPs in European Population Haplotype

H1 H2 H3 H4 H5 H6

rs2430561 Intron 1

(CA)n Intron 1

rs1861493 Intron 3

rs2069716 Intron 3

rs2069733 Intron 3

rs2069718 Intron 3

rs2069727 30 region

T T A A A A

12 12 Non-12 Non-12 Non-12 Non-12

T T C T T C

A G A A A A

G G – G G G

C C T C T T

G G A A A A

Freq

ca. ca. ca. ca. ca. ca.

30–35% 10% 20% 10% 10% 5%

Note: Based on HapMap, and Refs 7 and 8.

FIGURE 12.2 Overview of IFNG (ca. 8 kb) with main regulatory regions and main polymorphic variations present in European population. Black boxes represent the four exons in the gene, transcriptional direction left to right (filled: coding, open: non-coding). Black lines indicate SNPs with their respective dbSNP numbers. Dotted black lines correspond to CG methylation sites. The four gray areas correspond to transcription regulatory sites; (1) the distal promoter adjacent to rs2069707 contains a NFkB binding site þ C3-enhancer region; (2) the proximal promoter immediately upstream from the transcription initiation site contains a C3-enhancer region, silencer element binding YY-1 and AP-2-like repressor, AP-1-like binding motif conferring inducibility by TNF-a, proximal and distal core promoter protein-binding elements, and TATAA box; (3) C3-enhancer region in first intron; (4) adjacent and overlapping recognition sites for transcription activating factors STAT-1, -4, -5 and -6 and NFkB binding site, adjacent to rs2430561 and (CA)n in first intron.

of common haplotypes and haplotype tagging SNPs in the IFNG region in the European population, based on current HapMap and literature data.7,8 According to these sources, four-to six common haplotypes capture 485% of variation in the 79- kb IFNG haplotype block. It is of relevance to note that three markers, i.e. rs2430561 (intron 1; position þ874), rs2069727 (30 UTR), and the intron 1 (CA)n repeat (position þ875) are very strongly correlated and tag therefore the same haplotypes H1&H2 (T – CA12 – G) and H3 to H6 (A – non-CA12 – A), as was reported before (for position of polymorphisms in IFNG see Figure 12.2).9 H1 and H2 have a common haplotype background, differ from one another only by rs2069716 (intron 3), and account together for about 40% of all haplotypes. Disease association or allelic expression studies utilizing any of these three markers can therefore be compared straightforwardly (see below). Haplotypes H3 and H6 have also a common background and are divided only by rs2069733 (intron 3). Data on African and Asian populations are as yet scarce. In the African population, Koch et al.8 described eight IFNG haplotypes with frequencies 44%. The IFNG CA12 allele is less frequent, and the CA15 allele

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Cytokine Gene Polymorphisms in Multifactorial Conditions

(rare in Europeans1) is more frequent than in Europeans. Also, both haplotype composition and frequencies differ from Europeans; there is for example no perfect correlation between rs2430561 and the (CA)n repeat whereas (CA)n is in strong LD with rs2069718 in intron 3.8 At any rate, these inter-population disparities offer possibilities for fine-mapping studies to distinguish between these markers.

12.3 FUNCTIONAL ANALYSIS OF ALLELIC VARIATION IN INTRON 1 OF IFNG Data on allelic effects of IFN-g expression taken from a total of 16 published studies are summarized in Table 12.2.10–25 All studies scrutinized either the intron-1 T/A SNP rs2430561 or the adjacent (CA)n microsatellite polymorphism (Figure 12.2). Since, as demonstrated above, the alleles of both these polymorphisms segregate perfectly (CA12 – T versus nonCA12 – A) and tag the same haplotypes, direct comparisons are possible. Using a total of fifteen different assays IFN-g mRNA or protein levels were measured. In eight of these studies no association was found between IFNG polymorphisms and IFN-g expression levels.15–21,25 In five assays, CA12 or T homozygotes expressed 1.5–3 times more IFN-g, or had a higher number of IFN-g producing T cells, than did CA13 or A homozygotes.10–13,25 The remaining two assays point in the same direction, in that non-carriers of the CA13 allele (who are enriched for CA12 homozygotes) had a higher IFN-g expression level or percentage of IFN-gþ T cells than CA13 homozygotes.14 In two further studies, rather than IFN-g expression levels, IFN-g-induced, indirect effects were quantified and found to correlate to IFNG genotype. Raitala et al. (2005) found the T allele to be associated with increased indoleamine-pyrrole 2,3-dioxygenase (IDO) activity, an enzyme that is upregulated by IFN-g during the inflammatory response and transforms tryptophan into kynurenine.23 Thus, the higher IDO activity seen in T homozygotes should correlate to higher IFN-g levels. Development of lymphoproliferative disease (LPD) in mice after injection with PBLs from human Epstein–Barr virus positive donors is a model for post-transplantation lymphoproliferative disorder. Cytolytic T lymphocyte (CTL) is crucial for protection against LPD and IFN-g is important in this function. Among donors with rapid LPD response, AA and AT individuals were over-and TT individuals under-represented.24 The mechanism seems to be related to TGF-b succeeding in inhibiting to some extent CTL activity of AA and AT PBLs, but not TT PBLs, with EBV. Since IFN-g and TGF-b are antagonistic and counter-regulatory, this would fit with the notion of TT being a high-producer IFN-g genotype.24 Taken together, functional data from seven published studies seem to coincide and to indicate that the shared haplotype background of haplotypes H1 & H2 (Table 12.1) is associated with a ‘‘high IFN-g producer’’ phenotype.10–14,23,24 Only one study points in the opposite direction.22 The remainder are neutral.15–21 Further research is, indeed, needed to fine-map the functional polymorphisms on these haplotypes, to clarify under which precise natural conditions a higher IFN-g expression level is induced from H1 and/or H2, and which transcription sites and factors are differentially involved in the segregation of high- and lowexpression haplotypes. For now, however, these data can give a clue as to how IFNG alleles and haplotypes associated with diseases might operate, and whether this conforms to established immunological or biological models of IFN-g action.

12.4 IFNG DISEASE ASSOCIATION STUDIES Table 12.3 summarizes genetic associations between individual markers within the IFNG region and autoimmune or inflammatory diseases (MS, RA, SLE, Graves’ disease, Type I

161

The IFNG–IL26–IL22 Cytokine Gene Cluster

TABLE 12.2 Functional Analysis of Allelic Variation in Intron 1 of IFNG Assay

mRNA levels in PBMCa Protein levels (ELISA) from cultured PBMC

Inducer (time)

Refs

– ConAc (18 h)

nsb ns

17 18

PHAd, IL-1be, LPSf (18 h)

T homozygotes 4A homozygotes ns ns ns CA12 homozygotes 4CA12 heterozygotes 4non-carriers CA12 T homozygotes 4A homozygotes ns

12

PHA (48 h) PHA (48 h) ConA (48 h) PHA, ConA (48 h)

ConA (48h), anti
CD3 þ anti
CD28 (72 h) ConA (48 h) PHA (72 h)

PPDg antigen (96 h)

Intracellular IFN-g expression levels

Genotype effect of intron 1 (CA)n microsatellite or þ874 T/A SNP rs2430561

PHA, malaria antigen (120 h) PMAh þ ionomycin (4 h)

15 16 19 10

11 25

Non-carriers CA13 4CA13 heterozygotes 4CA13 homozygotes T homozygotes, TA heterozygotes 4A homozygotes ns ns

14

13

20 21

% Whole blood cells positive for intracellular IFN-g

PMA þ ionomycin (4 h)

Non-carriers CA13 4CA13 heterozygotes 4CA13 homozygotes

14

Total number of IFN-g producing T cells

Hepatitis C antigen (48 h)

25

In vitro expression of reporter constructs

PMA (6 h)

T homozygotes, TA heterozygotes 4A homozygotes CA15 4 CA13 4 CA12

IDO activityi

–

23

LPDj development upon injection of PBL in mice

–

T homozygotes 4A carriers, in females only A homozygotes, TA heterozygotes 4T homozygotes

Inhibition of CTLk activity by TGF-b

–

A homozygotes, TA heterozygotes 4T homozygotes

24

a

PBMC, peripheral blood mononuclear cells; ns, non-significant; c ConA, concanavalin A; d PHA, phytohaemagglutinin; e IL-1b, interleukin-1b; f LPS, lipopolysaccharide; g PPD, M. tuberculosis purified protein derivative; h PMA, phorbol myristate acetate; i IDO, indoleamine-pyrrole 2,3-dioxygenase; j LPD, lymphoproliferative disease; k CTL, cytolytic T lymphocyte. b

22

24

208/196 120 trios 72/85 174/95 220/266 509/193 103/103 251/198 350/395 130/102 417/276 59/79/129 82/102 162/133

Belgian French Finnish Swedish Nordic Dutch French N Irish German Czech British Spanish Spanish Japanese

American Finnish Danish Japanese Japanese

Multiple sclerosis Multiple sclerosis Multiple sclerosis Multiple sclerosis Multiple sclerosis Multiple sclerosis Rheumatoid arthritis Rheumatoid arthritis Rheumatoid arthritis Juvenile idiopathic arthritis Juvenile idiopathic arthritis Giant cell arteritis/ polymyalgia rheumatica Giant cell arteritis Graves’ disease

Systemic lupus erythematosus Type I diabetes Type I diabetes Type I diabetes Type I diabetes 207/160

136/99 168/110 266/195

432/205

N. Irish

Multiple sclerosis

N patients/ N controlsa

131 trios 165/54 305/367 141/144 221/442

Population

Autoimmune or Inflammatory Diseases Multiple sclerosis Sardinian Multiple sclerosis Swedish Multiple sclerosis German Multiple sclerosis Italian Multiple sclerosis American

Condition

AAO 5 10 AAO 5 25

Antithyrotropin receptor antibody negative within 3 years

Male

Male

Male HLA DR3/4


Subgroup

TABLE 12.3 Genetic Associations between IFNG Polymorphisms and Multifactorial Diseases

NS 0.039 NS 0.039 (0.0006) 0.08 (0.01)

NS NS (0.0035)

NS 0.007 NS NS NS NS NS NS NS NS NS NS

NA (0.019)

0.02 (0.001) 0.047 NS NS NA (0.044)

P condition (P subgroup)

12CA and 15CA (
), 13CA (þ) 12CA carrier (þ)

12CA (þ)

15CA (þ)

12CA (
)

Carrier rs2069727*A (þ) Carrier rs2069727*A (þ)

13CA(þ) 12CA(þ)

Effectb

18 41 41 42 43

39 40

28 29 30 31 17 32 33 34 35 36 37 38

28

1,26,27 1 1 1 28

Refs

162 Cytokine Gene Polymorphisms in Multifactorial Conditions

Scarring trachoma Leprosy Brucellosis Severe hepatic fibrosis in schistosomiasis 651/651 98/96 83/101 104

676/459

Gambian Gambian Brazilian Spain Sudan

45/97 113/307 313/235 131 families 514/913 385/451 190/135 77/58 85 158 207

96/61 193/92 220 trios 330/499 106 trios 84/77 83 families 42/73 140/73 2591

125/100 26/85 158/218 184/115 73/157 36/61

Sicilian Spanish S. African colored S. African colored Malawi Hong-Kong Colombian Israeli British Irish German

Japanese Canadian Spanish Spanish Finnish British Russian American American German

IgA nephropathy Inflammatory bowel disease Coeliac disease Coeliac disease Coeliac disease Psoriasis Viliuisk encephalomyelitis Alcoholic chronic pancreatitis Pancreatitis Restenosis after coronary stent

Infectious Disorders Tuberculosis Tuberculosis Tuberculosis Tuberculosis Tuberculosis Tuberculosis Tuberculosis Chronic hepatitis B infection Chronic hepatitis C severity Hepatitis C infection outcome Severity of inflammation in Helicobacter pylori infection Malaria

UK German Japanese Japanese British Japanese

Intermediate uveitis Allergy/hay fever Asthma Asthma Idiopathic pulmonary fibrosis Lupus nephritis

Severe malaria anemia

WHO Class V vs. IV

0.04 0.01 0.023 0.035

NS (0.035)

0.02 0.0017 0.0055 0.005 NS 50.001 NS 0.003 NS NS NS

50.01 NS 0.02 NS NS NS NS NS NS NS

0.004 OR 4.1 (1.6 – 10.4)c 0.0018 NS NS NA (0.035)

rs2069718*C/C (þ) Rare alleles grouped rs2430561*A/A (þ) rs1861494*A/A (þ) rs2069720*G/G (
)

rs2069728*C (þ)

rs2430561*A/A (þ)

rs2430561*A/A (þ)

rs2430561*T/T (
) rs2430561*A/A (þ) rs2430561*A (þ) rs2430561*A (þ)

12CA (þ)

13CA (þ)

13CA/13CA (þ)

rs2430561*T (þ) 13CA/13CA (þ) rare alleles

(Continued )

66 67 68 69

8

58 13 59 59 60 61 62 63 25 64 65

49 50 51 51 52 53 54 56 55 57

44 45 46 47 48 14

The IFNG–IL26–IL22 Cytokine Gene Cluster 163

Fibrosis after lung transplant Bronchiolitis obliterans after lung transplant Rejection after renal transplant Rejection after renal transplant Rejection after renal transplant Rejection after renal transplant Chronic allograft nephropathy Rejection after liver transplant Rejection after liver transplant Rejection after heart transplant Rejection after heart transplant Rejection after heart transplant Rejection after heart transplant Coronary vasculopathy after heart transplant Graft-versus-host disease after bone marrow transplantation Graft-versus-host disease after bone marrow transplantation Graft-versus-host disease after bone marrow transplantation

Transplant Complications

Severe sepsis after trauma AIDS risk/progression

Condition

TABLE 12.3 Continued

93 88 120 82 118 244 68 89 93 95 71 301 134 donors/ 144 recipients 80 100 160

American British American British Canadian American Israeli UK American American Colombian Dutch British

French Polish

British

82

61 337/470

N patients/ N controlsa

British

American French

Population

Severe acute form

Rejection within 3 months

Subgroup

0.02

NS

NS (0.02)

0.008 NS NS NS NS NS NS NS

13CA/13CA (þ)

13CA/13CA (þ)

87

86

85

77 78 79 80 81 82 83 84

76

NS (OR 2.6 [1.6-6.0])c

74

73

72

71

70 7

Refs

75

donor rs2430561*T (þ)

rs2430561*T/T (þ)

12CA (þ)

12CA (þ)

Effectb

NS

NS

NS

0.002

50.005

0.045 NS

P condition (P subgroup)

164 Cytokine Gene Polymorphisms in Multifactorial Conditions

Italian N. Irish Sardinia Argentinian Cypriotic Brazilian Italian Arabic

Other Longevity Longevity Longevity Recurrent pregnancy loss Pregnancy loss Recurrent pregnancy loss Aplastic anaemia Hypertension 174/248 93/100 112/137 41/54 69/69 48/108 67/100 81/93

199/225 115/90 111/213 340/314 265/308

250/250 48/188 127 169/261

223/267 54/144 185/176 369/123

Female

Early vs late onset

Male 6–20 yrs old

High-grade squamous intra-epithelial lesion

NS (0.02) NS NS 0.01 NS NS 0.004 NS

NS NS NS NS (0.039) NS

NS NS 0.02 (0.005) NS

0.004 0.001 0.048 NA (50.005)

12CA (þ)

rs2430561*T/A (þ)

rs2430561*T/T (
)

13CA (
)

12CA carriage (
)

rs2430561*T/T (þ) 12CA (þ) 13CA (þ) 12CA and 14CA (þ), 13CA and 18CA (
)

100 101 102 103 104 105 106 107

95 96 97 98 99

91 92 93 94

88 22 89 90

a Number of individuals included in the study: cases/controls, trios or multiplex families for case-control studies; or individuals followed up for cohort studies (e.g. number of transplant patients observed for occurrence of rejection or non-rejection). b (þ), allele frequency, carriage, or genotype is increased in patients compared to controls; (
), allele frequency, carriage, or genotype is decreased in patients compared to controls. c P values not available, OR [95% CI]. d Kidney angiomyolipomas in tuberous sclerosis-2 patients. Abbreviations: AAO, age at onset; NA, not applicable; NS, not significant.

Japanese Italian Italian Japanese Swedish

Chinese Japanese American/Polish British

Iranian Indian Japan Taiwanese

Neurological Disorders Alzheimer disease Alzheimer disease Alzheimer disease Parkinson disease Parkinson disease

Hepatocellular carcinoma Hepatocellular carcinoma KAMLs in TSC2d Cutaneous malignant melanoma

Cancer Breast cancer Breast cancer Endometriosis Cervical carcinogenesis

The IFNG–IL26–IL22 Cytokine Gene Cluster 165

166

Cytokine Gene Polymorphisms in Multifactorial Conditions

diabetes, allergy, asthma, uveitis, IgA nephropathy, and celiac disease), infectious disorders (tuberculosis, HBV infection, HEV infection, malaria, scarring trachoma, leprosy, brucellosis, AIDS), transplant complications, cancer, neurological disorders, and longevity.1,7,8,13,14,17,18,22,25–107 Probably the most striking genetic association, both in terms of significance and number of reproduced independent observations, is that found with susceptibility to tuberculosis (TB).13,58–62 Identical patterns of allelic association were observed in ethnically unrelated populations from Sicilian, Spanish, colored South African, and Hong-Kong Chinese origin.13,58,59,61 With the exception of two negative studies in the Malawi and Columbian population,60,62 either the A allele or A/A genotype of the IFNG intron-1 rs2430561 SNP were reproducibly increased in TB patients, or the T/T genotype was decreased (which is similar given the binary nature of this and most SNPs), compared to controls. Taken together with the functional data highlighted above, it therefore appears that ‘‘high-producer’’ IFNG alleles protect, and ‘‘low-producer’’ IFNG alleles predispose to TB. This is in line with accepted notions on IFN-g effects in mycobacterial infection; e.g. individuals with inherited complete or partial IFN-g receptor deficiency are known to be highly susceptible to disseminated atypical mycobacterial infection.108 The extent of association between polymorphisms in IFNG and a variety of other complex diseases is more ambiguous. Either association data extracted from independent studies on the same disorder tend to be conflicting, or reported disease associations have not yet been reproduced. The study size in many reports is relatively small jeopardizing detection with sufficient power of any relatively weak but genuine genetic effects. A few published studies have been excluded from this compilation because of questionable allele calling, implementation of genotyping techniques, or interpretation of genotyping data. The distinctive distribution patterns of the (CA)n polymorphism between European and some Asian populations may also hamper meaningful comparison in the absence of more than fragmentary haplotype information. CA13 homozygosity or carriage was reported to be associated with a higher risk to contract the Th2-type conditions allergy/hay fever, SLE class V nephritis, or IgA nephropathy; all of which are associations that could be anticipated from known immunological concepts and by applying the dichotomous high–low IFN-g producer haplotype model.14,45,49 The rs2430561*T and CA12 alleles were increased in Iranian and Indian breast cancer patients, respectively.22,88 A large number of studies have explored association between IFNG polymorphisms and transplant (kidney, liver, heart) rejection.73–83 Even if no clear association pattern has emerged, it should be noticed that power of the individual studies was generally limited due to small sample sizes. A meta-analysis of the in total more than 1000 individuals involved would probably facilitate to draw more solid conclusions. Interestingly, in one of the largest studies performed, indications were found for a role of the donor rather than recipient IFNG genotype in transplant rejection (donor ‘‘high IFN-g producer’’ allele rs2430561*T associated with recipient biopsy-proven chronic allograft nephropathy).77 Also, IFNG genotype was found to be associated with certain inflammatory processes, e.g. fibrosis71 or bronchiolitis obliterans,72 occurring after lung transplantation. Given the intricate effects of IFN-g in MS (see Chapter 20), not unexpectedly IFNG polymorphisms have been scrutinized intensively.1,17,26–32 Though data have been conflicting, a highly similar pattern of association has emerged from a subset of independent studies that warrants some in-depth discussion. In the most comprehensive study on the subject to date, carriage of the rs2069727*A allele was found to be reproducibly associated with susceptibility to MS in men, but not women, who were recruited from either USA (Olmsted County) or Northern Irish populations (ORs of 2.58 and 2.37, respectively).28 A similar,

The IFNG–IL26–IL22 Cytokine Gene Cluster

167

though not significant trend was seen in Belgian men with MS (OR of 1.5).28 The results of this study reinforce earlier findings of association of the IFNG CA13 allele with MS in male Sardinians not carrying HLA-DR3/4 alleles.1,26–27 It is as yet unclear why this finding has not been reproduced in the other published studies. Disease and/or genetic heterogeneity, insufficient power to detect this relatively weak effect, population stratification, or, simply omission of gender stratification are all factors that may jointly or individually account for this failure. In two separate studies on Nordic and Dutch patients, gender stratification was performed but did not force out a significant male-specific association with MS.17,32 In a French study, the CA12 allele was significantly under-transmitted to MS patients in a set of trio families, but gender stratification was not reported.29 Nevertheless, whichever the functional mechanisms underlying the gender-specific association, the data obtained from the Sardinian, Northern Irish, American, and French studies point in the same, and somewhat unexpected, direction, i.e. that of the ‘‘low-producer’’ IFNG haplotype being associated with predisposition to MS.1,26–29 Notwithstanding the fact that both beneficial and detrimental effects can be attributed to IFN-g in MS and CNS inflammation (see Chapter 20), the overall consensus is that IFN-g acts predominantly through a pro-inflammatory modus operandi and, hence, promotes disease. With regard to its role in immune defence against infectious disease, the situation is more clear-cut: IFN-g is generally considered a protective factor. In this review, the most frequently confirmed genetic association arising from comparison of all available literature data is that between ‘‘low-producer’’ (or ‘‘highproducer’’) IFNG alleles and susceptibility (or protection against) to TB infection.13,58,59,61 The ‘‘low-producer’’ rs2430561*A/A genotype was also associated with increased risk for chronic hepatitis B virus infection and brucellosis, suggesting that IFNG polymorphisms could influence susceptibility to a range of infectious agents.63,68 While MS is a complex predisposing genetic trait, onset of disease is thought to require a provoking environmental insult in genetically susceptible individuals.109 This insult is thought to be infectious and could be of viral, bacterial, or mycobacterial origin.110 Could the association of lowproducer IFNG alleles with susceptibility to MS, therefore, be indirect; i.e. due to enhanced vulnerability of individuals carrying such alleles to certain infectious agents capable of inciting onset of MS? Future analysis of the three-way interaction between MS, IFNG genotype and evidence for exposure to infectious pathogens may provide a clue. At any rate, the results from current genetic association studies seem to point in the direction that, more than to provide flexibility in the regulation of inflammation, allelic variation in IFNG may have arisen as a determinant of plasticity in protection against infectious diseases.

12.5 IL26 AND IL22 The D12S2511 and D12S2510 microsatellite polymorphisms were identified in the 3rd intron and 30 UTR, respectively, of IL26.111 In a set of 184 Sardinian trio MS families, transmission of neither the individual markers nor their haplotypes was distorted.111 In a case-control study on rheumatoid arthritis in Northern Ireland, marker D12S2510 was significantly associated with RA in women (P ¼ 0.008) but not in men (P ¼ 0.99).34 Fivemarker haplotypes constructed from the markers rs2227478, rs2227485, rs2227491, rs1012356, and rs2227507, all of which are located in IL22, were found to be associated with severe malaria in 676 cases and 459 controls from the Gambia region.8 The A–G–T– A–T haplotype 3 was associated with protection against severe malaria (P ¼ 0.004), while the G–G–C–T–T haplotype 4 was associated with susceptibility (P ¼ 0.006).8

168

Cytokine Gene Polymorphisms in Multifactorial Conditions

12.6 IFNGR1 AND IFNGR2 The IFN-g receptor is a member of the Class II family of cytokine receptors and is composed of two chains IFN-g R1 and IFN-g R2, the genes of which are located on distinct chromosomes. IFNGR1 is located on chromosome 6q and contains two nonsynonymous SNPs: 14 V/M (rs11575936) and 467 L/P (rs1887415). IFNGR2 is located on chromosome 21q, in a region of strong LD that covers most of the gene, if not the entire gene, in European, Asian, and African populations (75- kb block). Five common haplotypes occur in Europeans (4 htSNPs), versus seven in Africans (5 htSNPs), and haplotypes differ strongly between both European and African ethnic groups. Seven nonsynonymous coding polymorphisms are known: 58 T/R (rs17879783 ¼ rs4986958); 64 Q/R (rs17879493 ¼ rs9808753), 147 E/K(rs17878639), 182 K/E (rs17878711), 191 S/C (rs17880298 ¼ rs11910627), 260 V/G (rs1064579), and 322 D/E (rs1802585). The pioneering work of Newport and colleagues (1996) led to the identification of a point mutation at nucleotide 395 of the IFNGR1 gene that introduces a stop codon and yields a truncated protein that lacks the transmembrane and cytoplasmic domains and is not expressed on the cell surface.112 This mutation was found to be the cause of severe mycobacterial infections in a group of children. A few well-performed, more recent studies leave little doubt regarding a role for more subtle IFNGR1 and R2 polymorphisms in modulation of susceptibility to certain infectious diseases. A genome-wide linkage analysis among Senegalese siblings uncovered linkage between IFNGR1 and Helicobacter pylori-reactive IgG (LOD 3.1).113 This result was reinforced by the finding of association between three IFNGR1 SNPs and high H. pylorireactive IgG levels.113 In both case-control and family TDT designs, Gambian heterozygotes for an IFNGR1 SNP at position
56 were protected against cerebral malaria (OR of 0.54) as well as against death due to cerebral malaria (OR of 0.22), presumably through a mechanism involving a heterozygote advantage such as that seen with hemoglobin S.114 Ethnic variability in incidence and clinical phenotypes are associated with Leishmania donovani infection in Sudan. Mohamed et al. showed that a (CA)n polymorphism in the 6th intron of IFNGR1 was specifically linked and associated (TDT; P ¼ 0.007) with the clinical phenotype post Kala-azar dermal leishmaniasis, but not with visceral leishmaniasis.115 In a smaller study, the microsatellite D6S471, located near IFNGR1, was also found to be associated with infection following major trauma.116 With regard to autoimmune diseases data are in shorter supply. The IFNGR1 14 V/M variant was reported to be associated with SLE in Japan.117 In an extensive cohort of MS patients, the IFNGR2 64*R allele was found to be associated with a progressive disease onset, but not with susceptibility to MS per se.32

12.7 CONCLUDING REMARKS Functional studies seem to demonstrate that IFNG genotype can influence expression levels of this cytokine. The functional polymorphism or combination of polymorphisms, as well as the precise biological conditions under which this genetic control of expression is seen, remain thus far elusive. Indications are also emerging that polymorphic variations in the genes of the IFNG pathway (IFNG, IFNGR) can influence susceptibility to certain disorders. This has been demonstrated most convincingly for infectious diseases. The lack of clarity with regard to autoimmune diseases, transplant complications, and other non-infectious disorders, may be reminiscent of much more subtle or subgroup effects, in need of much larger sample sizes in order to be realistically verifiable. A case in point is the association between IFNG polymorphisms and male sex seen in susceptibility to MS,26–28 kidney angiomyolipomas in TSC2 patients,93 and as part of a larger

The IFNG–IL26–IL22 Cytokine Gene Cluster

169

haplotype in susceptibility to RA (Ref. 34 and unpublished data). Transcription of IFN-g is known to be influenced by sex hormones,118–123 and some effects of IFN-g deficiency in mice differ between male and female ifng
/
mice.124–125 These observations could indicate that this gender–gene interaction is biologically and genetically meaningful. Fail-safe assessment of the genetic contribution of IFNG to sexual dimorphism in susceptibility to autoimmune diseases is, however, still to be performed. Sharing between research groups, or public access, of raw genotyping data, implementation of meta-analytical approaches, and large collaborative studies may be the way forward to assure sufficient power to reliably address potential roles of IFNG, and other cytokine genes, as modifiers of susceptibility or disease aspects of patient subgroups.

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42. Awata, T. et al., Association of polymorphism in the interferon gamma gene with IDDM, Diabetologia, 37, 1159, 1994. 43. Tegoshi, H. et al., Polymorphisms of interferon-gamma gene CA-repeat and interleukin-10 promoter region (
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65. Rad, R. et al., Cytokine gene polymorphisms influence mucosal cytokine expression, gastric inflammation, and host specific colonisation during Helicobacter pylori infection, Gut, 53, 1082, 2004. 66. Natividad, A. et al., Risk of trachomatous scarring and trichiasis in Gambians varies with SNP haplotypes at the interferon-gamma and interleukin-10 loci, Genes Immun., 6, 332, 2005. 67. Reynard, M. P. et al., Allele frequencies for an interferon-gamma microsatellite in a population of Brazilian leprosy patients, Eur. J. Immunogenet., 30, 149, 2003. 68. Bravo, M. J. et al., Polymorphisms of the interferon gamma and interleukin 10 genes in human brucellosis, Eur. J. Immunogenet., 30, 433, 2003. 69. Chevillard, C. et al., IFN-gamma polymorphisms (IFN-gamma þ2109 and IFN-gamma þ3810) are associated with severe hepatic fibrosis in human hepatic schistosomiasis (Schistosoma mansoni), J. Immunol., 171, 5596, 2003. 70. Stassen, N. A. et al., Interferon-gamma gene polymorphisms and the development of sepsis in patients with trauma, Surgery, 132, 289, 2002. 71. Awad, M. et al., CA repeat allele polymorphism in the first intron of the human interferongamma gene is associated with lung allograft fibrosis, Hum. Immunol., 60, 343, 1999. 72. Lu, K. C. et al., Interleukin-6 and interferon-gamma gene polymorphisms in the development of bronchiolitis obliterans syndrome after lung transplantation, Transplantation, 74, 1297, 2002. 73. Asderakis, A. et al., Association of polymorphisms in the human interferon-gamma and interleukin-10 gene with acute and chronic kidney transplant outcome: the cytokine effect on transplantation, Transplantation, 71, 674, 2001. 74. Hahn, A. B. et al., TNF-alpha, IL-6, IFN-gamma, and IL-10 gene expression polymorphisms and the IL-4 receptor alpha-chain variant Q576R: effects on renal allograft outcome, Transplantation, 72, 660, 2001. 75. Pelletier, R. et al., Evidence for a genetic predisposition towards acute rejection after kidney and simultaneous kidney-pancreas transplantation, Transplantation, 70, 674, 2000. 76. Tinckam, K. et al., The relative importance of cytokine gene polymorphisms in the development of early and late acute rejection and six-month renal allograft pathology, Transplantation, 79, 836, 2005. 77. Hoffmann, S. et al., Donor genomics influence graft events: the effect of donor polymorphisms on acute rejection and chronic allograft nephropathy, Kidney Int., 66, 1686, 2004. 78. Tambur, A. R. et al., Role of cytokine gene polymorphism in hepatitis C recurrence and allograft rejection among liver transplant recipients, Transplantation, 71, 1475, 2001. 79. Warle´, M. C. et al., Cytokine gene polymorphisms and acute human liver graft rejection, Liver Transpl., 8, 603, 2002. 80. Awad, M. R. et al., The effect of cytokine gene polymorphisms on pediatric heart allograft outcome, J. Heart Lung Transplant., 20, 625, 2001. 81. Gourley, I. S. et al., The effect of recipient cytokine gene polymorphism on cardiac transplantation outcome, Hum. Immunol., 65, 248, 2004. 82. Plaza, D. M. et al., Cytokine gene polymorphisms in heart transplantation: association of low IL-10 production genotype with Quilty effect, J. Heart Lung Transplant., 22, 851, 2003. 83. Holweg, C. T. et al., Recipient gene polymorphisms in the Th-1 cytokines IL-2 and IFN-gamma in relation to acute rejection and graft vascular disease after clinical heart transplantation, Transpl. Immunol., 11, 121, 2003. 84. Densem, C. G. et al., Influence of IFN-gamma polymorphism on the development of coronary vasculopathy after cardiac transplantation, Ann. Thorac. Surg., 77, 875, 2004. 85. Cavet, J. et al., Interferon-gamma and interleukin-6 gene polymorphisms associate with graft-versus-host disease in HLA-matched sibling bone marrow transplantation, Blood, 98, 1594, 2001. 86. Socie, G. et al., Both genetic and clinical factors predict the development of graft-versus-host disease after allogeneic hematopoietic stem cell transplantation, Transplantation, 72, 699, 2001. 87. Bogunia-Kubik, K. et al., Recipient interferon-gamma 3/3 genotype contributes to the development of chronic graft-versus-host disease after allogeneic hematopoietic stem cell transplantation, Haematologica, 90, 425, 2005.

The IFNG–IL26–IL22 Cytokine Gene Cluster

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88. Kamali-Sarvestani, E. et al., Polymorphism in the genes of alpha and beta tumor necrosis factors (TNF-alpha and TNF-beta) and gamma interferon (IFN-gamma) among Iranian women with breast cancer, Cancer Lett., 223, 113, 2005. 89. Kitawaki, J. et al., Interferon-gamma gene dinucleotide (CA) repeat and interleukin-4 promoter region (
590C/T) polymorphisms in Japanese patients with endometriosis, Hum. Reprod., 19, 1765, 2004. 90. Lai, H. C. et al., Genetic polymorphism of the interferon-gamma gene in cervical carcinogenesis, Int. J. Cancer, 113, 712, 2005. 91. Nieters, A. et al., Effect of cytokine genotypes on the hepatitis B virus-hepatocellular carcinoma association, Cancer, 103, 740, 2005. 92. Migita, K. et al. Cytokine gene polymorphisms in Japanese patients with hepatitis B virus infection–association between TGF-beta1 polymorphisms and hepatocellular carcinoma, J. Hepatol., 42, 505, 2005. 93. Dabora, S. L. et al., Association between a high-expressing interferon-gamma allele and a lower frequency of kidney angiomyolipomas in TSC2 patients, Am. J. Hum. Genet., 71, 750, 2002. 94. Howell, W. M. et al., Cytokine gene single nucleotide polymorphisms and susceptibility to and prognosis in cutaneous malignant melanoma, Eur. J. Immunogenet., 30, 409, 2003. 95. Oda, M. et al., Dinucleotide repeat polymorphism in interferon-gamma gene is not associated with sporadic Alzheimer’s disease, Am. J. Med. Genet. B Neuropsychiatr. Genet., 124, 48, 2004. 96. Galimberti, L. et al., þ874(T!A) single nucleotide gene polymorphism does not represent a risk factor for Alzheimer’s disease, Immun. Ageing, 1, 6, 2004. 97. Scola, L. et al., Allele frequencies of þ874T!A single nucleotide polymorphism at the first intron of IFN-gamma gene in Alzheimer’s disease patients, Aging Clin. Exp. Res., 15, 292, 2003. 98. Mizuta, I. et al., Relation between the high production related allele of the interferon-gamma (IFN-gamma) gene and age at onset of idiopathic Parkinson’s disease in Japan, J. Neurol. Neurosurg. Psychiatry, 71, 818, 2001. 99. Hakansson, A. et al., Investigation of genes coding for inflammatory components in Parkinson’s disease, Mov. Disord., 20, 569, 2005. 100. Lio, D. et al., Allele frequencies of þ874T!A single nucleotide polymorphism at the first intron of interferon-gamma gene in a group of Italian centenarians, Exp. Gerontol., 37, 315, 2002. 101. Ross, O. A. et al., Study of age-association with cytokine gene polymorphisms in an aged Irish population, Mech. Ageing Dev., 124, 199, 2003. 102. Pes, G. M. et al., Association between longevity and cytokine gene polymorphisms. A study in Sardinian centenarians, Aging Clin. Exp. Res., 16, 244, 2004. 103. Prigoshin, N. et al., Cytokine gene polymorphisms in recurrent pregnancy loss of unknown cause, Am. J. Reprod. Immunol., 52, 36, 2004. 104. Costeas, P. A. et al., Th2/Th3 cytokine genotypes are associated with pregnancy loss, Hum. Immunol., 65, 135, 2004. 105. Daher, S. et al., Associations between cytokine gene polymorphisms and recurrent pregnancy loss, J. Reprod. Immunol., 58, 69, 2003. 106. Dufour, C. et al., Homozygosis for (12) CA repeats in the first intron of the human IFNgamma gene is significantly associated with the risk of aplastic anaemia in Caucasian population, Br. J. Haematol., 126, 682, 2004. 107. Frossard, P. M. et al., A study of five human cytokine genes in human essential hypertension, Mol. Immunol., 38, 969, 2002. 108. Casanova, J. L., and Abel, L. The human model: a genetic dissection of immunity to infection in natural conditions, Nat. Rev. Immunol., 4, 55, 2004. 109. Sospedra, M., and Martin, R., Immunology of multiple sclerosis, Annu. Rev. Immunol., 23, 683, 2005. 110. Salvetti, M. et al., The immune response to mycobacterial 70-kDa heat shock proteins frequently involves autoreactive T cells and is quantitatively disregulated in multiple sclerosis, J. Neuroimmunol., 65, 143, 1996.

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111. Goris, A., Marrosu, M. G., and Vandenbroeck, K., Novel polymorphisms in the IL-10 related AK155 gene (chromosome 12q15), Genes Immun., 2, 284, 2001. 112. Newport, M. J. et al., A mutation in the interferon-gamma-receptor gene and susceptibility to mycobacterial infection, N. Eng. J. Med., 26, 335, 1996. 113. Thye, T. et al., Genomewide linkage analysis identifies polymorphism in the human interferongamma receptor affecting Helicobacter pylori infection, Am. J. Hum. Genet., 72, 448, 2003. 114. Koch, O. et al., IFNGR1 gene promoter polymorphisms and susceptibility to cerebral malaria, J. Infect. Dis., 185, 1684, 2002. 115. Mohamed, S. et al., Genetic susceptibility to visceral leishmaniasis in The Sudan: linkage and association with IL4 and IFNGR1, Genes Immun., 4, 351, 2003. 116. Davis, E. G. et al., Microsatellite marker of interferon-gamma receptor 1 gene correlates with infection following major trauma, Surgery, 128, 301, 2000. 117. Tanaka, Y. et al., Association of the interferon-gamma receptor variant (Val14Met) with systemic lupus erythematosus, Immunogenet., 49, 266, 1999. 118. Fox, H. S., Bond, B. L., and Parslow, T. G., Estrogen regulates the IFN-g promoter, J. Immunol., 146, 4362, 1991. 119. Correale, J., Arias, M., and Gilmore, W., Steroid hormone regulation of cytokine secretion by proteolipid protein-specific CD4þ T cell clones isolated from multiple sclerosis patients and normal control subjects, J. Immunol., 161, 3365, 1998. 120. Karpuzoglu-Sahin, E., Hissong, S., and Ansar Ahmed, S., Interferon-g levels are upregulated by 17-b-estradiol and diethylstilbestrol, J. Reprod. Immunol., 52, 113, 2001. 121. Karpuzoglu-Sahin, E. et al., Effects of long-term estrogen treatment on IFN-g, IL-2 and IL-4 gene expression and protein synthesis in spleen and thymus of normal C57BL/6 mice, Cytokine, 14, 208, 2001. 122. Maret, A. et al., Estradiol enhances primary antigen-specific CD4 T cell responses and Th1 development in vivo. Essential role of estrogen receptor a expression in hematopoietic cells, Eur. J. Immunol., 33, 512, 2003. 123. Bebo, B. F. Jr., Schuster, J. C., Vandenbark, A. A., and Offner, H., Androgens alter the cytokine profile and reduce encephalitogenicity of myelin-reactive T cells, J. Immunol., 1 62, 35, 1999. 124. Whitman, S. C., Ravisankar, P., and Daugherty, A. IFN-g deficiency exerts gender-specific effects on atherogenesis in apolipoprotein E-/- mice, J. Interferon Cytokine Res., 22, 661, 2002. 125. Han, X. et al., Gender influences herpes simplex virus type 1 infection in normal and gamma interferon-mutant mice, J. Virol., 75, 3048, 2001.

13

TNF Polymorphisms and Disease Reginald M. Gorczynski and Ivo Boudakov

CONTENTS

13.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.1.1 General Background on TNF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.1.2 The TNF:TNFR Superfamily . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.1.3 Role of TNF-a and TNFR in Human Diseases . . . . . . . . . . . . . . . . . . . . . . . . 13.1.3.1 Role in Infection and Inflammation . . . . . . . . . . . . . . . . . . . . . . . . . . 13.1.3.2 Role in Malignancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.1.3.3 Role in Lymphoid Organ Development . . . . . . . . . . . . . . . . . . . . . . 13.1.3.4 Role in Hematopoiesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.1.4 Structure-Function Analysis of TNF-a:TNF-aR Interactions . . . . . . . . . . 13.2 Polymorphisms in TNF/TNFRs and Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2.1 General. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2.2 Infectious Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2.3 Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2.4 Autoimmune Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2.5 Transplantation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2.6 TNF Polymorphisms and Other Clinical Disorders . . . . . . . . . . . . . . . . . . . . 13.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3.1 Methodological Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3.2 Complexity Associated with Ethnic/Racial Differences in SNP Frequencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3.3 Is Disease Association with TNF-a SNPS a Reflection of Linkage with HLA Genes? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.4 Possibilities for the Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

175 176 176 178 178 178 178 178 179 179 179 180 180 181 182 183 184 184 185 185 185 186

13.1 INTRODUCTION There is a growing interest in the likelihood that cytokine gene polymorphisms, identified by SNP and haplotype analysis, are associated with disease, particularly for those cytokines (e.g. TNF-a) implicated in both non-specific inflammatory reactions, as well as in acquired immune-mediated reactivity. The discussion below briefly overviews the biology of TNF:TNFR interactions in order to consider biological mechanism(s) which underly the association of TNF:TNFR with disease. Subsequently the evidence for a role for TNF-a polymorphisms in the regulation of disorders as broad as autoimmune diseases, infection, malignancy, and transplantation is discussed, along with more recent data suggesting a linkage with susceptibility to cardiovascular disease, schizophrenia, and even longevity per se. 175

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13.1.1 GENERAL BACKGROUND

Cytokine Gene Polymorphisms in Multifactorial Conditions

ON

TNF

TNF-a has been known for some time to be a major mediator of inflammatory diseases and of organ-specific autoimmune diseases.1 One mechanism whereby inflammatory processes are induced by TNF-a, at least in the brain, resides in the crucial role played in regulating lymphocyte trafficking following control of chemokine expression.2 A wealth of literature suggests a role for anti-TNF-a or the decoy receptor (TNFR linked to an immunoglobulin Fc region) in suppression of autoimmunity.3 Given the evolutionary importance of this inflammatory pathway, perturbation of TNF-a-induced inflammation, as expected, produces undesired side-effects.4 Although TNF-a and TNF-b (lymphotoxin) share sequence homology (
30%), and can compete for binding to TNFRs, the discussion that follows is restricted, with few exceptions, to a review of TNF-a alone.5 Under some circumstances TNF-a is an anti- rather than pro-inflammatory molecule. In the non obese diabetic mouse model (NOD) of type-1 diabetes, adult expression of TNF-a abrogates disease, and does not elicit disease as had been anticipated.6 The advent of disease in neonatal animals occurred concomitant with a diminution in CD4þCD25þ Treg in the thymus and spleen, an effect reversed by anti-TNF-a.7 Since TNF-a regulates levels of RANK (receptor activator of NFkB) and RANK:TRANCE (TNF-related activation induced cytokine) interactions also influence development of CD4þCD25þ Treg, these data offer at least one plausible mechanism whereby TNF-a may modulate autoimmune disease.8 An alternate hypothesis, consistent with the known role of many members of the extended superfamily of TNF, TNFRs, is that TNF-a induces anti-inflammatory effects following apoptosis of autoreactive T lymphocytes.9 At least in patients with Crohn’s disease, TNF-a neutralization increased the number of apoptotic cells in the gut mucosa.10 TNF-a may also produce paradoxical anti-inflammatory effects in other ways — dendritic cells incubated with TNF-a in vitro show augmented induction of IL-10 producing Treg cells.11

13.1.2 THE TNF:TNFR SUPERFAMILY (SEE FIGURE 13.1A–FIGURE 13.C) Both ligand and counter-ligand belong to a large extended family of molecules (19 identified members for the TNF family; 29 for the TNFR family), with significant functional overlap. Most of the TNF family members exist as transmembrane molecules, exerting their action locally (perhaps accounting for the harmful effects mediated when, under non-homeostatic conditions, members (e.g. TNF-a) are released in soluble form). TNFR family members all express repeats of a cysteine-rich domain in their extracellular region (CRDs in Figure 13.1B and Figure 13.1 C), and are otherwise subdivided into two categories, those with and those without an intracellular death domain (implicated in mediating apoptotic signals — see Figure 13.1B). An additional region in the extracellular domain of TNFR1 and TNFR2 (PLAD in Figure 13.1B and Figure 13.1C) mediates ligand-independent oligomerization (to trimers) which is required for generation of a TNF-a binding complex to mediate TNF-a signaling. While expression of TNFR2 is limited to immune cells and endothelial cells, and has been implicated in delivery of signals by membrane-expressed TNFa, expression of TNFR1 is ubiquitous, accounting for the relative nonspecific effects mediated by soluble TNF-a.12 Other data suggests significant interaction between the receptors in signal generation.13 Following binding of TNF-a to TNFR1 and/or TNFR2, intracellular signaling occurs through pathways involving NFkB, JUN N-terminal kinase (JNK), p42/p44 mitogenactivated protein kinase (MAPK), and p38 MAPK. TRAFFs (TNFR-associated factors) link the cell surface receptors with downstream kinase cascades, resulting in activation of NFkB and AP1 (see Figure 13.1C for location of TRAF binding domain in TNFR2). Knockout

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177

FIGURE 13.1 Panel A: Genomic organization, transcribed mRNA, and translational products of human TNF-a and TNF-b. Also shown are essential structural features of the TNF molecule, and the location of a number of SNPs documented to have a relationship with human disease (see text for more details). Panel B: Genomic organization, transcribed mRNA, and translational product of human TNF receptor 1 (TNFR1). Also shown are essential structural features of the TNFR1 molecule, including the PLAD, CRDs, TM and cytoplasmic domains, and the location of SNPs documented to have a relationship with human disease. Panel C: Genomic organization, transcribed mRNA, and translational product of human TNF receptor 2 (TNFR2), showing essential structural features as in Panel B (for TNFR1). Once again the location of a number of SNPs documented to have a relationship with human disease is shown (see text for more details).

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mice lacking TRAFF2 and TRAFF5 showed reduced TNF-a-induced NFkB induction, and increased susceptibility to TNF-a-induced cytotoxicity.14 After binding of TNF-a, TNFR1 translocates to lipid rafts where it associates with TRADD (TNFR-associated death domain), TRAF2 and a serine-threonine kinase receptor-interacting protein (RIP), forming a large signaling complex. This is followed by ubiquitinylation of TNFR1, loss of NFkB signaling, and apoptosis. Binding of TNF-a to TNFR2 induces independent ubiquitinylation of TRAF2, accounting for some at least of the ‘‘cross-talk’’ between TNFR1 and TNFR2.15 A number of members of the TNF and TNFR family provide co-stimulatory signals for T cell activation. Included amongst these are TNF:TNFR homologs OX40L and OX40, 4-1BBL and 4-1BB, CD70 and CD27, and CD30L and CD30. In all cases the TNF homologs are only induced on APCs after activation, coinciding with peak expression of their ligands (TNFR homologs) on T cells.16 All function in co-stimulation through activation of the NFkB pathway (and ultimately JNK/AP1) and thus there is the potential for ‘‘interference’’ in signaling from these members following activation via TNF:TNFR1 (TNFR2) themselves, and vice versa.

13.1.3 ROLE OF TNF-a AND TNFR IN HUMAN DISEASES 13.1.3.1

Role in Infection and Inflammation

Evidence for a crucial role for TNF-a comes from data using anti-TNF-a and TNFR decoys in treatment of human autoimmune diseases (above). While the inflammatory pathology is ameliorated, increased susceptibility (e.g. to TB) is noted.17 Similar increased susceptibility of TNF or TNFR KO mice to infection with Listeria has been observed.18 Even chronic cardiac disease (heart failure) has been linked to inflammatory pathology associated with elevations in TNF-a levels.19 13.1.3.2

Role in Malignancy

Although first discovered by virtue of its toxicity to tumor cells, TNF-a itself has limited use clinically in cancer therapy, because of systemic toxicity. Efficacy of intravenous therapy in isolated limb perfusion is described, both for soft tissue sarcomas and melanomas.20 13.1.3.3

Role in Lymphoid Organ Development

Amplification of apoptotic machinery can cause the destruction of tissues and loss of these signals causes hyperproliferation. A role for TNF-a in regulation of the morphogenesis of secondary lymphoid organs is known.21 Apoptotic signals do not require protein synthesis, while anti-apoptotic signals do, following activation of NFkB dependent pathways. Amongst the NFkB regulated proteins which control apoptosis are TRAF-1, inhibitor of apoptosis 1 (IAP1) and IAP2, and BCL-XL (which blocks release of cytochrome c from mitochondria, thus inhibiting caspase-9 activation). 13.1.3.4

Role in Hematopoiesis

As expected from the myeloid/lymphoid restricted expression of TNFR2, TNF-a has profound effects on hematopoiesis. TNF-a promotes B cell proliferation,22 which may account for the role of TNF homologs in development of autoimmunity.23 TNF-a (and members of the extended family) also plays a key role in regulation of the balance between osteoclastogenesis and osteoblastogenesis, perhaps secondary to modulation of NFkB dependent signaling.24

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13.1.4 STRUCTURE-FUNCTION ANALYSIS TNF-a:TNF-aR INTERACTIONS

OF

What are the relevant domains in both ligand:receptor structure which are key for functional activity, and what regulatory elements for both TNF and TNFRs lie in the 50 noncoding (promoter) region of these genes? The TNF-a structure (233aa) is a type-II transmembrane molecule, with an extracellular COOH-terminus, and an intracellular NH2 terminus. There is an important TNF-receptor binding domain in the extracellular region, a key transmembrane region (aa 36–56), and a recognition site for members of the ADAM family of proteinases (aa 76–77) which can cleave the molecule from the cell surface, releasing soluble TNF-a. The two TNFRs are type-1 transmembrane molecules, with an intracellular COOH-terminus and an extracellular NH2 terminus. TNFR1 (455aa) has a unique and important death-domain feature (aa 356–441), lacking in TNFR2 (461aa). Both TNFRs have four conserved cysteine-rich domains in the extracellular region (in TNFR1, from aa 43–196, and in TNFR2, from aa 39–201), and transmembrane domains (TNFR1 aa 212–234; TNFR2 aa 258–287). In addition, both TNFRs contain a PLAD domain in the NH2-terminus which regulates ligandindependent assembly of the trimer, the functional receptor moiety,25 as well as an independent ligand-binding domain. There is a TRAF1/2 binding domain in the intracellular domain (aa 384–424) of TNFR2.26

13.2 POLYMORPHISMS IN TNF/TNFRs AND DISEASE All numbers refer to nt position; also in Table 13.1 are shown positions with respect to the transcriptional start site, computed from the Ensembl database.

13.2.1 GENERAL Much of the literature for TNF-a has concentrated on analysis of polymorphisms contained within the promoter region, and investigation of whether these have functional effects on TABLE 13.1 Summary of Different SNPs for Cytokines/Receptors (http://www.ensembl.org) Gene

cDNA Position

SNP ID (rs number)

Alleles

Gene

cDNA Position

SNP ID (rs number)

Alleles

TNF-a

1031

rs1799964

T/C

TNF-R1

863 857

rs1800630 rs1799724

A/C T/C

609 580 383 þ226

rs4149570 rs4149621 rs2234649 rs767455

T/G A/G A/C T/C

TNF-R2 376 308

rs1800750 rs1800629

A/G A/G

þ168 þ543 þ587

A/G T/C T/G

244 238 þ489

rs673 rs361525 rs1800610

A/G A/G T/C

þ694 þ1466 þ1493 þ1663

rs17880314 rs2275415 rs17883437 (rs1061622) rs5746026 rs1061624 rs3397 rs5746065

A/G A/G T/C A/C

þ691 þ851

rs1799769 rs3093662

-/G A/G

þ252

rs909253

T/C

TNF-b

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Cytokine Gene Polymorphisms in Multifactorial Conditions

TNF-a transcription and/or influence disease susceptibility. Several studies report generally negative findings, leading authors to conclude that polymorphism at this locus is functionally silent and exists only because of linkage disequilibrium with selectable HLA alleles.27 However, more detailed critique of the available data suggests that polymorphism in the TNF-a promoter is not randomly distributed and likely has some functional and selectable effect.

13.2.2 INFECTIOUS DISEASES Recognition of association between SNPs and disease, even SNPs in the (presumed) promoter region of the gene, does not imply that we necessarily understand the mechanism of this association. Thus a wealth of data exists linking TNF-a promoter SNPs (376, 308, 244, and 238) and disease. However, linker scanning mutational analysis of this region, using reporter constructs transfected into various cell lines, gave conflicting data concerning the role these regions played in regulation of promoter activity.28 In other studies a region containing disease-associated SNPs in the TNF-a promoter (863 and 857) appeared to regulate allele-specific binding of OCT-1. 29 Ubalee et al.30 investigated evidence that polymorphism in the 50 promoter region of the TNF-a gene affected the course of falciparum malaria in patients with cerebral malaria. Two hundred and forty three (243) Myanmar patients with falciparum malaria were studied, 200 with no complications and 43 with cerebral malaria. Five biallelic polymorphic sites were analyzed, at 238, 308, 857, 863, and 1031. Of seven possible alleles identified, only one was associated with cerebral malaria in the two populations, with no linkage disequilibrium with any alleles of HLA-B or HLA-DRB1. Craandijk examined similar polymorphisms (G to A transitions) in the promoter region (at 238, 308, and 376), as well as one on the first intron (þ489), in the context of susceptibility to periodontitis.31 No evidence suggested a polymorphism controlling susceptibility to, or severity of, disease. de Jong et al.32 stimulated whole blood cultures with endotoxin and showed that alleles of a TNF-a microsatellite and the various TNF polymorphisms were not related to TNF production. In contrast, Aguillon et al.33 concluded that the G to A transition at 308, generating TNF alleles 1 and 2 respectively, was associated with elevated TNF-a production (from TNF2), which they suggest may help explain the linkage with susceptibility to autoimmune disorders (below), and increased susceptibility to septic shock/mortality in the context of infection (and/or inflammation). Similarly Soga et al.34 independently concluded that in Japanese populations (where SNPs at 1031, 863, and 857 occur more frequently), all were linked with severe periodontitis. Yee et al. were unable to find a correlation between TNF-a promoter polymorphisms at 308 or 238 in response to antiviral therapy in hepatitis C patients, although there was a correlation with polymorphisms for the IL-10 gene.35 More recently Goyal et al.36 reported an association of TNF-b polymorphisms, but not TNF-a polymorphisms (i.e. 308) with disease severity in HepC infected patients. The Soga data concur with previous observations indicating a lack of evidence for a role for polymorphisms at 308 or 238 in TNF regulation. Nevertheless, Peters et al.37 documented significant methodologic issues associated with genotyping populations in many of the studies reported to date, and suggest that at least some of the controversy may reflect misclassification.38

13.2.3 CANCER A review by Jang et al.39 concluded that the 238 G to A promoter polymorphism discussed above in the context of infectious disease was associated with a decreased

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susceptibility to cancers. Their study included 169 patients with gastric cancer, uterine cervical cancer, colorectal cancer, or renal cell carcinoma and 92 healthy controls. The TNF-238A allele was less frequent in the cancer group than in the control group (odds ratio for cancer in subjects with the TNF-238A allele was 0.25 (95% CI, 0.10–0.64)). However, analysis of colorectal malignancy,40 prostate cancer,41 melanoma,42 and bladder cancer43 failed to find evidence for an association between these promoter polymorphisms and susceptibility to disease. As an example, McCarron et al. showed an association of polymorphisms in VEGF, IL-1b, and IL-10 genes in prostate cancer susceptibility, possibly reflecting a role in altered angiogenesis rather than inflammation, but no evidence for TNF 308 involvement was observed. Similar conclusions were reached by Tsai for transitional cell carcinoma of the bladder.43 Howell et al. studied patients with cutaneous malignant melanoma where increased expression of TNF-a upregulated by UV exposure may contribute to tumor escape from the immune response,42 and studied SNPs in both the TNF-a promoter and TNF-b for association with susceptibility to disease, or with other known prognostic indicators (e.g. initial tumor growth phase, Breslow thickness, mitotic count in vertical growth phase tumors). Analysis of data from 146 patients and 220 controls, typed for TNF-a 376, 308 and 238, and TNF-b þ 252 SNPs by PCR, showed that only the TNF-a -238 GG (P ¼ 0.05) and GA (P ¼ 0.03) genotypes showed a small (albeit significant) association with melanoma, while TNF-b þ 252 AA was associated with a higher mitotic count in vertical growth phase tumors (P ¼ 0.02). The TNF-a 238 and TNF-b þ 252 SNPs showed linkage disequilibrium with HLA-DQB1*0303 and *0301 alleles, both of which have independently been variably implicated in susceptibility and/or prognosis of this disease. In contrast to these negative findings, Park et al.44 investigated polymorphisms in both TNF-a and TNF-b in peripheral leucocytes in 95 breast cancer patients and 190 healthy controls, including the TNF-a promoter polymorphisms 1031 (T/C), 863 (C/A), 857 (C/ T), and 308 (G/A), and an SNP in the first intron of TNF-b (G/A). The TNF-b*G/TNF-b *G homozygote genotype (23.2% vs. 5.8%, P ¼ 0.001) predominated in patients, while the TNF-b*A/TNF-b*A homozygote genotype was less frequent in patients (34.7% vs. 46.3%, P ¼ 0.041), in each case when compared with healthy control subjects. No association of disease was seen with SNPs in the TNF-a promoter. There was a significant difference in pathology among tumor stages for the 857 SNP in TNF-a. The authors concluded that TNF-b has both tumorigenic and anti-tumorigenic capabilities depending on the genotype, with TNF-b*G/TNF-b*G genotype at increased risk for breast cancer, while the TNF-b*A/ TNF-b*A produced increased resistance to breast cancer (OR ¼ 5.3395%; CI: 2.33–12.19). The data were taken to imply that the TNF-b*G allele led to a function important in tumorigenesis or activation of dormant tumor cells, while the TNF-b*A allele induced a function(s) leading to the inhibition of tumorigenesis. Neben et al.45 examined evidence for promoter polymorphisms regulating response to treatment in 81 patients with refractory and relapsed multiple myeloma who were treated with Thalidomide. Their data suggested that regulatory polymorphisms of the TNF-a gene promoter could affect TNF-a production and predict outcome after Thalidomide therapy, particularly in myeloma patients who are genetically defined as ‘‘high TNF-a producers.’’

13.2.4 AUTOIMMUNE DISEASE TNFR2 SNP gene polymorphisms (within the cysteine-rich domain coding region of TNFR2) have been identified in Japanese patients with lupus erythematosus.46 Three additional SNPs within the coding sequence (cSNPs), as well as several variations within the promoter, introns, and 30 -untranslated region (30 UTR), were also identified. More studies have focused on arthritis (both adult and juvenile onset) to explore evidence for contributions of TNF and

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TNFR polymorphism to disease status, measuring disease severity by radiological erosions, rheumatoid nodules, biopsy, rheumatoid factor, or TNF-a mRNA in peripheral blood mononuclear cells (PBMC) and synovium of healthy individuals and patients following stimulation with LPS, PMA, and anti-CD3 and anti-CD28 monoclonal antibodies.47 No evidence was found for a difference in the contribution of distinct TNF alleles in healthy individuals and RA patients, and comparison of SNPs in the TNF promoter 1031, 863, 857, and 308 in these populations argued against their functional relevance in the regulation of transcription. This conclusion was in contrast to that reached by Aguillon and co-workers discussed earlier,33 and Ozen et al.,48 who studied JRA in Turkish and Czechoslovakian patients, and reported that while the G to A 238 polymorphism did not have an effect on patient outcome in either group, the G to A 308 polymorphism was associated with a poor outcome in the Turkish group (P ¼ 0.005) with no association in the Czech patients. Nishibu et al.49 reported a lack of association of SNPS in the TNF promoter (238A and 308A) in Japanese patients with various forms of psoriasis vulgaris, psoriatic arthritis, and generalized pustular psoriasis. Witte et al.50 examined polymorphisms in asthmatic populations and found that TNF-a (A at –308), but not TNF-b SNPs, were associated with asthma (OR 1.86, P ¼ 0.04). A recent study51 of 490 overweight subjects, analyzing whether TNF-a (308) and IL-6 (174, C to G) promoter polymorphisms might help predict the conversion from impaired glucose tolerance to type 2 diabetes in a Finnish population, concluded that the 308A allele of the TNF-a gene was associated with nearly a two-fold higher risk for type 2 diabetes compared with the 308G allele (odds ratio 1.80, 95% CI 1.05–3.09; P ¼ 0.034). Risk was compounded in subjects with both the A allele of the TNF-a gene and the C-174C genotype of the IL-6 gene (CI 1.02–4.85, P ¼ 0.045). Bouqbis et al.52 studying a Moroccan population with type 1 (not II) diabetes concluded that both the TNF-a 307 and the TN-b þ252 SNPs were associated with protection from disease. A number of investigations addressed the issue of the role of SNPs in defining risk/ outcome for inflammatory bowel diseases. Sashio et al. investigated polymorphisms in both TNF and TNFR in ulcerative colitis (UC, 106 patients) and Crohn’s disease (CD, 124 patients).53 Two SNPs of the TNF-a gene promoter, 308 and 238; one SNP of the TNFR1 gene, codon 12 in exon 1 (þ 226: CCA/CCG, Figure 13.1A); and two SNPs of the TNFR2 gene (see Figure 13.1C: 1466 A/G and 1493 C/T) were studied. The carrier frequency for haplotype AG (308 A, 238 G) was different between UC patients and the controls (OR ¼ 4.76, P 5 0.01). There was also a significant difference in carrier frequency for haplotype AT (1466 A, 1493 T) of the TNFR2 gene between CD patients and the controls (OR ¼ 2.13, P 5 0.05), with this difference being expanded in patients with more severe disease (internal and external fistula; OR ¼ 4.8, P 5 0.01), and/or who responded poorly to management (nutritional therapy, medical therapy, and surgical therapy: OR ¼ 9.24, P 5 0.001). Louis et al.54 found that the 308 TNF-a promoter allele (TNF2) was associated with steroid-dependent Crohn’s disease, and to a lesser extent, fistulizing and colonic disease, possibly secondary to a more intense TNF-a -driven inflammatory reaction at the mucosal level.

13.2.5 TRANSPLANTATION Analysis of cytokine gene polymorphisms and the incidence and severity of acute rejection in the first six months following renal transplantation55 showed that recipient TNF-a high producer and IL-10 high producer genotypes were significantly associated with multiple rejection episodes in HLA-DR mismatched transplants (P ¼ 0.0047 and P ¼ 0.045, respectively), while only the TNF-a high producer genotype was associated with steroidresistant rejection (P ¼ 0.025). Analysis of the cytokines together revealed that the TNF-a

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high/IL-10 high producer genotype had the worst prognosis, while the compound TNF-a low/IL-10 low producer genotype was protective. Similar studies to these were performed independently by Fernandes et al.56 in orthotopic liver transplant patients, showing that acute cellular rejection was associated with the TNF-a 308 A/A genotype (P 5 0.02), with increased TNF-a production from cells of rejecting patients in an allele-specific fashion.56 An interesting analysis, combining some of the information on the role of polymorphisms in infectious disease and in transplantation, was performed by Rosen et al.,57 assessing the combined incidence of hepatitis C virus-related histologic recurrence, allograft injury, and cytokine gene polymorphisms. The authors hypothesized that the allograft plays a significant role in determining timing and severity of hepatitis C virus recurrence, and that genetic polymorphisms (308, 238) of the TNF-a locus would also be associated with a variable severity of HepC recurrence. Restriction fragment length analysis for four polymorphic loci within the TNF-b gene were assessed. The relative prevalence of polymorphisms in the population under study corresponded to distributions previously reported in normal control populations. However, the interval to histologic recurrence was significantly shorter and the severity of hepatitis C allograft hepatitis was significantly greater in patients with one or two TNF2 alleles (308 A). In addition, at the last follow-up biopsy, 5 of 9 (56%) patients with a TNF2 donor liver showed a severe histological activity index as compared to 2 of 22 (9%) of patients receiving a donor liver homozygous for the TNF1 allele (P ¼ 0.01). The authors reported no correlation between rejection rates and the presence of any TNF-a or TNF-b alleles, and donor liver TNF-b polymorphisms were not correlated with severity of HCV recurrence. Thus it seems that the donor TNF-a308 promoter genotype influences the inflammatory response to hepatitis C reinfection of the graft thus contributing to accelerated graft injury. Finally, Ishikawa et al. amongst others reported on the effect of polymorphisms in TNF-a and/or TNFR2 on the outcome in unrelated bone marrow transplantation.58,59 TNF-a promoter polymorphisms (1031 (T/C); 863 (C/A); 857 (C/T), and 308 (G/A)) and a nonsynonymous SNP in TNFR2 (196M/196R) were assessed. Effects attributable to associations with the HLA mismatching effect due to linkage disequilibirium of TNF-a with HLA loci were excluded. Transplantation from TNFR2-196R-positive donors showed a higher incidence of severe GVHD (P 5 0.05) and tendency for a lower relapse rate than transplantation from TNFR2-196M homozygous donors. When the recipient was TNFR2196R no effect was observed for GVHD but the relapse rate increased (P 5 0.025).

13.2.6 TNF POLYMORPHISMS CLINICAL DISORDERS

AND

OTHER

There are multiple other disorders whose pathophysiology and etiology is ill-understood, but for which there is evidence of an immuno-inflammatory component to the disease. Mutations in the extracellular domain of the 55-kD tumor-necrosis factor TNFR1 have been described to define a periodic-fever syndrome, TRAPS (TNF receptor-associated periodic syndrome), characterized by attacks of fever, sterile peritonitis, arthralgia, myalgia, skin rash, and/or conjunctivitis; some patients also develop systemic amyloidosis.60 Six diseaseassociated TNFR1 mutations are described, five of which disrupt individual extracellular cysteines involved in disulfide bonds in the so-called cysteine-rich domain of the molecule (see schematic outline in Figure 13.1A). Four other mutations have subsequently been reported (Figure 13.1). Provocative data suggest an association between TNF-a polymorphisms (308) and schizophrenia.61,62 Initial observations which formed the background to these studies suggested a dysregulation of the inflammatory response (abnormal levels of proinflammatory cytokines and their receptors in peripheral blood and cerebrospinal fluid)

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in schizophrenic patients vs. controls. TNF-a has been reported to exert both neurotrophic and neurotoxic effects, and to influence neural cell growth and proliferation, and the TNFA gene locus is closely associated with a region (6p21.1–21.3) contributing to genetic susceptibility to schizophrenia. Both studies reported an association of the 308 gene polymorphism (TNF2) in schizophrenic patients (but not the 1031, 863, or 857 genotype), consistent with a potential role of TNF-a as a candidate gene for susceptibility to schizophrenia. Alvarez et al.63 reported on the role of TNF-a and TNF-b polymorphisms and susceptibility to Alzheimer’s disease in keeping with a role for inflammation in this chronic CNS pathology. Carriers of TNF-a 308A had a mean age at onset 3 years younger than non-carriers of this allele (P ¼ 0.019). Hohjoh et al.64 examined TNF promoter SNPs in 49 narcoleptic patients, all positive for DRBI*1501 (the human class II haplotype linked with narcolepsy), and 111 healthy controls. The frequency of 857T was increased in patients compared with controls (P ¼ 0.0068), with 857T mainly associated with DRB1 alleles other than DRB1*1501; hence, the increased frequency of 857T in the patients was not caused by linkage disequilibrium with DRB1*1501. Several other studies are worthy of brief mention before concluding this section. Despite the evidence for a role for TNF polymorphisms in regulating hepatic pathology in hepatitis C patients, and following transplantation (above) Ladero et al. found no association between SNPs at positions 238, 308, and 376 (TNF-a) or positions 597, 824, and 1087 (IL-10) in patients with chronic inflammatory alcoholic liver disease.65 In addition, and consistent with the proposed role of TNF-a as a potential osteoporotic factor because of its stimulatory effects on cells of the osteoclast lineage and its association with bone loss associated with oestrogen deficiency, Ota et al. investigated the relationship of TNF-a SNPs (1031C, 863A, and 857T) in a Japanese population assayed for bone loss. A significant correlation was seen for SNP 1031 and decreased bone mineral density, suggesting that TNF-a may play a role in pathogenesis of osteoporosis.66 Confirming long-standing speculation for a role for inflammatory processes in the cardiovascular disease associated with hyperlipidemia (the most commonly inherited hyperlipidemia in man, present in
10% of all infarct survivors), Geurts et al.67 described a role for polymorphisms in exon 6 of TNFR2 as an important modifier of the effects of hyperlipidemia in familial combined disease. In 85 hyperlipidemic subjects, an association was seen between soluble TNFR2 plasma concentrations and the 196 M allele. O’Keefe et al. explored the role of TNF SNPs in helping explain the heterogeneity in clinical outcome (risk of development of sepsis syndrome) in trauma patients using multivariate analysis.68 Once again there was a remarkable correlation between expression of the 308 SNP (TNF2) and adjusted odds ratio of significant disease/death from sepsis. Finally, an interesting report from Lio et al.69 recently reported that both TNF-a SNP (308) and IL-10 SNP (1082) showed independent association with longevity in an aging cohort, consistent with evidence for inflammatory mediators in aging processes.

13.3 DISCUSSION Controversies concerning a role for TNF/TNFR SNPs in regulation of clinical disease include a variety of issues which are discussed below.

13.3.1 METHODOLOGICAL ISSUES Peters et al.37 suggested that haplotype misclassification could explain some of the conflicting data. Juszczynski et al.70 discuss this in detail in relation to comparison of two of the more popular techniques, allele-specific polymerase chain reaction (ASPCR) and automated

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sequencing (ASEQ). When applied to TNF 308 genotyping, a number of studies show that ASPCR sensitivity and specificity is dependent on numerous PCR parameters, with mismatches occurring to a degree of 4%. In the direct comparison reported, for a total of 204 DNA samples, duplicate examination by the ASPCR and ASEQ revealed concordant results in 96.5% and mismatches in 3.5% of genotypes. ASEQ was more accurate than ASPCR for the TNF 308 genotyping, and was recommended by these authors as a ‘‘gold standard’’ benchmark for other SNP assays. The majority of the reports cited in the discussion above have used ASPCR technology.

13.3.2 COMPLEXITY ASSOCIATED WITH ETHNIC/ RACIAL DIFFERENCES IN SNP FREQUENCIES The representation of TNF-a SNPs in different populations reflects evolutionary history.71 Thus the 244 SNP and the 857 SNPs are the first markers of a sub-Saharan Africanderived extended haplotype and an Amerindian HLA haplotype, respectively. Hassan and co-workers examined SNP allelic frequencies among Caucasian and African American women for TNF-a (308), TGF-b1, IL-10 (1082A/G, 819T/C, 592A/C), IL-6, and IFN-g. Importantly, in the context of the current (and preceding) discussion, this group reported that SNP allelic and genotypic frequencies for TNF-a and IL-10 (and TGF-b1) did not differ between the Caucasian and African American women.72 In contrast Bridges et al. performed SNP genotyping for TNFR genes in African Americans with rheumatoid arthritis (RA), healthy African Americans, and healthy Caucasians, including analysis of the TNFR2 SNP (196 G/T) which influences susceptibility to familial RA in Caucasians, and three SNPs in the 50 flanking region of the TNFR1 gene (609G/T, 580A/G, and 383A/C).73 While there were no differences in TNFR1 allele frequencies between African Americans with RA and healthy African Americans the allele frequencies were very different between the ethnic groups; i.e. healthy African Americans and healthy Caucasians.

13.3.3 IS DISEASE ASSOCIATION WITH TNF-a SNPS A REFLECTION OF LINKAGE WITH HLA GENES? In humans the TNF-a gene is located at the telomeric end of the class III region, within the highly polymorphic major histocompatibility complex (MHC) region on chromosome 6p21.3. Many of the TNF SNP polymorphisms have been found to be in linkage disequilibrium with HLA class I and class II alleles. As but one example of the complexity of this issue, consider a recent study by Low and colleagues,74 examining HLA linkage of two polymorphisms in the TNFA gene, TNF-a þ 489 and þ 691. This group studied the association of these two TNF alleles with HLA-DR, -DQ and -B alleles in more than 200 healthy individuals in England. The frequencies of the uncommon alleles were 0.08 (þ 489A) and 0.05 (þ 691Gdel). The þ 489A allele was associated with carriage of DRB1*1104, DQB1*0301, B18 and B35. The þ 691Gdel allele was associated with carriage of DRB1*13 *11, DQB1*0301 and B44. The probable linkage disequilibrium between these TNF alleles thus inevitably complicates studies aimed at determining the role of these loci in the genetic background of the diseases which show genetic associations with MHC haplotypes.

13.4 POSSIBILITIES FOR THE FUTURE This review began with a discussion of what is known about the biology of TNF-a (and TNFR), and used this as a model framework to examine disease association patterns which could be understood within the context of TNF biology. Just as microarray and proteomics technology have revolutionized the search for unexpected associations of

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molecules with disease, so too genetic analysis of common but complex (multi-factorial) diseases has been revolutionized by the application of large-scale single nucleotide polymorphism (SNP) typing.75 Future studies analyzing SNP disease association will depend upon not merely data gathering, but more sophistication in data mining and analysis. Nevertheless, this field will likely play an important and growing part in enhancing our future molecular understanding of the pathophysiology of multifactorial medical entities.

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67. Geurts, J. M. et al., Identification of TNFRSF1B as a novel modifier gene in familial combined hyperlipidemia, Hum. Mol. Genet., 9, 2067, 2000. 68. O’Keefe, G. E., Hybki, D. L., and Munford, R. S., The G !A single nucleotide polymorphism at the 308 position in the tumor necrosis factor-alpha promoter increases the risk for severe sepsis after trauma, J. Trauma, 52, 817, 2002. 69. Lio, D. et al., Inflammation, genetics, and longevity: further studies on the protective effects in men of IL-10 1082 promoter SNP and its interaction with TNF-alpha 308 promoter SNP, J. Med. Genet., 40, 296, 2003. 70. Juszczynski, P. et al., Comparison study for genotyping of a single-nucleotide polymorphism in the tumor necrosis factor promoter gene, Diagn. Mol. Pathol., 11, 228, 2002. 71. Baena, A. et al., TNF-alpha promoter single nucleotide polymorphisms are markers of human ancestry, Genes Immun., 3, 482, 2002. 72. Hassan, M. I. et al., Racial differences in selected cytokine allelic and genotypic frequencies among healthy, pregnant women in North Carolina, Cytokine, 21, 10, 2003. 73. Bridges, S. L., Jr. et al., Single-nucleotide polymorphisms in tumor necrosis factor receptor genes: definition of novel haplotypes and racial/ethnic differences, Arthritis Rheum., 46, 2045, 2002. 74. Low, A. S., et al., TNF þ489 polymorphism does not contribute to susceptibility to rheumatoid arthritis, Clin. Exp. Rheumatol., 20, 829, 2002. 75. Zee, R. Y. et al., Multi-locus interactions predict risk for post-PTCA restenosis: an approach to the genetic analysis of common complex disease, Pharmacogenomics J., 2, 197, 2002.

14

Macrophage Migration Inhibitory Factor (MIF ) Zaynab Alourfi, David W. Ray, and Rachelle Donn

CONTENTS 14.1 14.2 14.3

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MIF Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MIF Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3.1 MIF as a Pro-Inflammatory Cytokine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3.2 MIF as a Hormone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3.3 MIF as an Enzyme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.4 Regulation of MIF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.5 Mechanism of MIF Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 MIF and Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6.1 MIF and Arthritis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6.2 MIF and Chronic Colitis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6.3 MIF and Sarcoidosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6.4 MIF and Psoriasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6.5 MIF and Tumors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6.6 MIF and Liver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7 The MIF Gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7.1 Polymorphisms of the Human MIF Gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7.2 Genetic Polymorphisms in MIF and Association with Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7.3 Promoter Activity of MIF and the Significance of the Known Polymorphic Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.7.4 MIF and Glucocorticoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.8 Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

191 192 192 192 193 193 194 194 194 194 195 195 195 195 195 197 197 198 199 200 200 201

14.1 INTRODUCTION Macrophage migration inhibitory factor (MIF) was originally described as the first T-cell derived cytokine, which inhibits the migration of macrophages from capillaries.1,2 Subsequently, after cloning in 1989,3 it was discovered to be expressed in most tissues, suggesting that it has a widespread role beyond the immune system.4 MIF has unusual biological properties. First, it is a pleiotropic factor with pro-inflammatory, hormonal, and enzymatic activities.5,6 Second, MIF is able to counter-regulate the immunosuppressive and anti-inflammatory effects of glucocorticoid (GC).7–11 Finally, MIF was reported to be induced by low concentrations of GC in a murine cell line,7 which is unusual for a proinflammatory cytokine. However, this observation has proved controversial with a recent 191

192

Cytokine Gene Polymorphisms in Multifactorial Conditions

report not supporting this in the same murine cell line. MIF was found to be suppressed with high concentrations of GCs, with no induction at low concentrations in two different cell lines.12

14.2 MIF PROTEIN The MIF protein is small with no significant sequence homology to any other protein. Its primary sequence consists of 115 amino acids, with a predicted molecular mass of 12.5 kDa based on the cDNA sequence which was originally cloned in 1989 from a T lymphoblast cell line.3 The structure of MIF protein was determined by X-ray crystallography in 1996.13 It exists as a trimer, with each monomer consisting of two anti-parallel a helices and six b strands. a helices with b strands wrap around to form a barrel structure containing a solventaccessible channel. The inner surface of the channel has a positive potential, suggesting that it might interact with negatively-charged moieties; however, its precise role in MIF function has yet to be elucidated.8

14.3 MIF FUNCTIONS MIF is a pleiotropic factor. It was originally defined as an activated T lymphocyte and macrophage derived cytokine.14 Furthermore, MIF was reported to be a pituitary hormone potentiating lethal endotoxemia15 and also to be a catalytic enzyme.16

14.3.1 MIF

AS A

PRO-INFLAMMATORY CYTOKINE

T lymphocytes were considered to be the source of MIF and monocytes/macrophages the targets of its migration inhibitory effect. However, it was found that monocytes/ macrophages also produce MIF in response to endo-and exotoxins (lipopolysaccharide (LPS), toxic shock syndrome toxin-1, and streptococcal pyrogenic exotoxin), malaria pigment (hemozoin), or cytokines (TNF-a and IFN-g). MIF modulates the expression of proinflammatory mediators by macrophages and is an important component of T lymphocyte activation.17 MIF activates macrophages and enhances their tumoricidal and parasiticidalactivities.18 MIF induces the pro-inflammatory action of macrophages, promotes TNF-a secretion, and mediates IFN-g-induced production of nitric oxide (NO), phagocytosis, and intracellular killing.19 In addition, MIF is involved in delayed-type hypersensitivity. Rocklin et al. studied MIF production and skin test response to streptokinase streptodornase (SK-SD), and candida in patients with congenital thymic aplasia and patients with X-linked agammaglobulinemia. They found that the former group did not produce MIF and the skin test was negative, implying a T lymphocyte source of MIF.20 Injection of recombinant murine MIF (rMIF) with LPS into mice was reported to potentiate LPS lethality, while MIF alone produced the endotoxemia symptoms without lethality in the dose range studied. Further evidence for a role of MIF was gained by administration of anti-MIF serum which protected mice and raised survival to 100%.15 Bozza et al. used MIF deficient mice (MIF
/
), which were completely healthy but did not produce MIF, MIF
/
, MIF
/þ, and MIFþ/þ (wild-type mice) were injected with LPS intraperitoneally.21 Although MIF-deficient mice showed mild features of endotoxemia, they were remarkably resistant to the lethal effects of LPS. Cytokine levels were measured in MIF
/
and wild-type mice 90 min after LPS injection. IL-6 and IL-10 levels were similar, but plasma levels of TNFa in MIF
/
mice were 50% less than in wild-type mice. This reduction in TNFa production, apparently due to lack of MIF activity, could be the cause

Macrophage Migration Inhibitory Factor (MIF )

193

of resistance to LPS. Another contribution may be the absence of the counter-regulatory effects of MIF on stress induced concentrations of glucocorticoids. The same group studied the role of MIF in host defense to Gram-negative bacteria by introducing P. aeruginosa intratracheally into MIF
/
and wild-type mice. Then, the mice were killed either immediately or at 6 and 24 hours to investigate lung clearance of P. aeruginosa. The MIF
/
mice efficiently cleared bacteria from the lungs 24 hours after infection.21 Taken together these studies suggest a critical role for MIF in the inflammatory response. Therefore, neutralization or counteraction of MIF might have potential therapeutic implications. However, Honma et al.22 found that there was no important difference in immune response and susceptibility to LPS-induced shock between administration of LPS to MIFdeficient mice and that of normal mice, when maintained under specific pathogen-free conditions. They also found that the production of TNF-a was essentially the same. This obviously contradicts the earlier report of Bozza et al.21 and their suggestion that MIF is involved in TNF-a production.

14.3.2 MIF

AS A

HORMONE

MIF is reported to be secreted by immune and endocrine cells. It modulates glucocorticoid action and functions locally on autocrine and paracrine hormonal action regulation.23 Bernhagen et al.15 found that the pituitary is an important source of MIF that appears in serum after LPS administration. They did their experiments on normal, hypophysectomized and T-cell deficient mice. They estimated the content of stored MIF within a single pituitary to be about 40 ng which is approximately 0.05% of total pituitary protein. Immuno-electron microscopy studies of the anterior pituitary co-localizes MIF to granules containing adrenocorticotrophic hormone (ACTH) and thyroid-stimulating hormone (TSH).24 It was found that adrenalectomy in rats was associated with increased serum MIF levels and increased pituitary MIF levels which was consistent with the pituitary being the principal source of this increase.19 MIF was surprisingly found to be released when macrophages were treated with low concentration (10
16 M) of dexamethasone, the synthetic glucocorticoid, peaked at between 10
14 to 10
12 M Dex, and decreased at 10
8 to 10
6 M Dex.7 However, recently Alourfi et al. reported that GCs either inhibited MIF secretion, or were without effect.12 Additional endocrine actions of MIF have been reported. Insulin-secreting cells in the endocrine pancreas produce MIF which potentiates glucose-induced insulin secretion,23 and in the testis Leydig cells secrete MIF which, in paracrine activity, affects Sertoli cell regulation and decreases the inhibin production.25

14.3.3 MIF

AS AN

ENZYME

MIF and Rat D-dopachrome tautomerase (DDT), a protein involved in melanin synthesis, have significant similarity in protein sequence.26 Both proteins can catalyze the isomerization of D-dopachrome.27 MIF is structurally related to some small isomerases in bacteria28 such as 4-oxalocrotonate tautomerase, 5-carboxy methyl-2-hydroxy muconate.29 MIF also has phenylpyruvate tautomerase and thiol protein oxidoreductase activities, and it was also demonstrated to have the ability to metabolize several catecholamines , and thus may play an important protective role in neural tissues.30 Site-directed mutagenesis studies showed that the N-terminal proline of MIF is involved in the catalytic function of MIF. The precise connection between the enzymatic and biological activities of MIF is questionable.31 D-dopachrome and its tautomerized product bear significant structure similarities to acetaminophen and some of its active metabolites,

194

Cytokine Gene Polymorphisms in Multifactorial Conditions

which irreversibly inhibit both the enzymatic and in vitro biological activity of MIF. This makes the therapeutic potential of pharmacological inhibitors of MIF higher.

14.4 REGULATION OF MIF MIF regulation appears to be cell-type specific: 1. Monocytes/macrophages: LPS and TNFa stimulate MIF mRNA and protein expression. Staphylococal toxic shock syndrome toxin 1 (TSST-1) and the streptococal pyrogenic exotoxin A induce MIF secretion.32 2. Insulin-secreting beta cells: Glucose stimulates MIF production in a time and concentration dependent manner.33 3. The pituitary: LPS induces MIF production15 and corticotropin releasing factor (CRF) stimulates corticotroph cells to produce MIF.34 This effect is mediated by the cyclic adenosine 30 ,50 monophosphate responsive element-binding protein (CREB).

14.5 MECHANISM OF MIF ACTION The cytokine activities of MIF may be mediated by transcription factor Jab1-dependent pathways. MIF binds directly to Jab1 both in vitro and in vivo, leading to inhibition of AP-1 activity of TNF and ultraviolet stress-induced AP-1 transcription activity inducing P27 Kip1 levels.35 MIF can act directly on T cells. There is no specific MIF receptor known, but MIF can act on T cells via the T cell receptor (TCR).36 Anti-MIF mAb (monoclonal antibody) inhibited antigen-specific responses of both IFN-g and IL4 producing T cells, but there was no inhibition on NK-T cell responses. In response to LPS in MIF knockout mice there is a significant reduction, compared with controls, in the activity of NF-kB and the production of TNF-a. This reduction relates to a down-regulation of Toll-like receptor-4 (TLR-4), the signal-transducing molecule of the lipopolysaccharide receptor complex, and is associated with decreased activity of transcription factor PU.1, which is required for optimal expression of the TLR-4 gene in myeloid cells.37 Mitchell et al.38 studied the role of MIF in proliferation and intracellular signaling in the NIH/3T3 fibroblast cell line. They found that MIF-stimulated cell proliferation was associated with the activation of the P44/P42 extracellular signal-regulated (ERK) mitogenactivated protein kinases (MAP). This was dependent on protein kinase A activity. In addition, MIF regulates cytosolic phospholipase A2 activity via a protein kinase A and ERK dependent pathway. MIF-deficient mice are resistant to endotoxic shock, possibly explained by the ability of MIF to sustain activated macrophage function,17 by inhibiting tumor suppressor gene product p53-dependent apoptosis in these cells.

14.6 MIF AND DISEASE Elevated MIF levels have been documented in many diseases suggesting that MIF may have important roles in their pathogenesis. The initial observations of MIF in clinical diseases were made by Cohen et al.39 who found that compared to controls, MIF activity was detectable in the serum of patients with various lymphoproliferative disorders such as chronic lymphotic leukemia, myoloma, Hodgkin’s disease, and non-Hodgkin’s lymphoma.

Macrophage Migration Inhibitory Factor (MIF )

14.6.1 MIF

AND

195

ARTHRITIS

Increased MIF levels had been reported in the serum, synovial fluid, and within the inflamed synovia in human rheumatoid arthritis (RA).9 Evidence for a role of MIF in RA emerges from the correlation of synovial MIF concentration with RA activity.40 Raised MIF protein levels had also been described in sera and synovial fluid from children with JIA.41 In addition, a critical role of MIF in the development of RA was demonstrated in animal studies. Immunoneutralization of MIF with anti-MIF monoclonal antibody (mAb) delayed onset of collagen-induced arthritis in mice42 and inhibited the clinical and histological features of adjuvant-induced arthritis in rats.43 It also ameliorated antigeninduced arthritis.44 MIF induced the proliferation of fibroblast-like synoviocytes (FLS). FLS are important in the pathogenesis of RA and its hyperplasia is essential to evaluate joint destruction.45 Many studies have been carried out to investigate the association between MIF polymorphisms and JIA,46–49 or RA,50 or adult inflammatory polyarthritis51 (Table 14.1).

14.6.2 MIF

AND

CHRONIC COLITIS

Serum MIF concentration in patients with Crohn’s disease was six-fold higher than that in controls.52 Treating the disease with anti-TNF (Infliximab) was associated with a significant decrease in MIF levels. In further work the same investigators studied the role of MIF in experimental colitis. They found that MIF-deficient mice failed to develop the disease, but reconstitution of those mice with wild-type innate immune cells (CD45RBhi A TH1 cells) restored colitis susceptibility. Anti-MIF treatment prevented the progression and severity of murine colitis.52

14.6.3 MIF

AND

SARCOIDOSIS

In one study 60% of sarcoidosis patients were found to have a raised bioactive MIF concentration in the circulation.53 In a Spanish population the MIF-173*C polymorphism was reported to be positively associated with sarcoidosis.54

14.6.4 MIF

AND

PSORIASIS

Serum MIF levels in psoriasis patients were found to be significantly higher than those in controls. After dermal glucocorticoid treatment, serum MIF levels were decreased with the improvement of the clinical symptoms.55 In addition the spontaneous MIF release into culture media by peripheral blood mononuclear cells (PBMC) from psoriatic patients was significantly higher than that of controls. The CATT-7-MIF-173*C haplotype was found to be positively associated with chronic psoriasis.56

14.6.5 MIF

AND

TUMORS

Serum MIF concentration has been found to be elevated in patients with tumors such as prostate cancer,57 melanoma,58 lung cancer59 and uveal melanoma.60 MIF has the capacity to inhibit P53 activity, and to prevent the lysis of tumor cells by natural killer (NK) cells.60 It was reported that melanoma cells produced and secreted more MIF than melanocytes. In addition, MIF enhanced melanoma cells in a dose-dependent manner. This might implicate the role of MIF in metastasis.58 Prostate adenocarcinoma cell line DU-145 cells produce and secrete more MIF than normal cells.61

43 79

57.3 59.6

32.7 75.9

Sarcoidosis (NW Spain, 28) Control (NW Spain, 122)

Atopy (Japan, 349) Non-atopic (Japan, 235)

Alopecia areata (Japan) Age at onset 5 20 yr (n ¼ 55) Age at onset  20 yr (n ¼ 58)

5.6 33.0 32.3 6.8 0 0.8

7.7 5.4 1.7

17.24 13.90

50

68

78

66

1 5,X refers to
794 CATT alleles 5, 6, 7, or 8. The table shows the frequency data (%) for the MIF polymorphisms positively associated with disease loci.

JIA (UK, 321 TDT families)

56

6.7 14.6 12.7

11.6 7.2

6.6 19.7 17.8

Psoriasis (UK, 228) Controls (UK, 401)

5.8 0.3 0.4

51

5.7 11.7 14.9

54

46

Ref

12.2 4.1

5.5 or 5.X1 39.1 31.7

5.5 15.2 19.1

CATT7-MIF-173*C

Inflammatory polyarthritis (UK, 438) Controls (UK, 343)

90 10

12.7 1.7

9.2 3.4

11 1

3.2 0.8

CC

-794 CATT

47

54.6 22.4

33.5 37.0

46 29

31.6 20.8

GC

MIF-173

Transmitted 38 times: non transmitted 21 times; P ¼ 0.0016

Ulcerative colitis (Japan) MIF-173*CC (n ¼ 10): Pancolitis (9) Other (1) Rheumatoid arthritis (USA) Mild (41) Severe (25)

65.2 78.4

GG

Juvenile Idiopathic Arthritis (JIA) (UK, 526) Control (UK, 259)

Disease (Population, n)

TABLE 14.1 MIF Gene Polymorphisms and Disease

196 Cytokine Gene Polymorphisms in Multifactorial Conditions

Macrophage Migration Inhibitory Factor (MIF )

14.6.6 MIF

AND

197

LIVER

MIF serum levels were increased in hepatocellular carcinoma and liver cirrhosis when compared to normal controls and those with gastro-intestinal cancer. However, MIF secretion by peripheral blood mononuclear cells (PBMC) from patients with hepatocellular carcinoma and normal controls was approximately the same. This suggested that the source of MIF was mainly the hepatocytes. Elevated serum MIF concentrations in liver cirrhosis, which is a pre-cancerous state, might partly suggest a facilitatory role for MIF in development of cancer.62

14.7 THE MIF GENE The genomic organization of the human MIF gene was first reported by Paralkar and Wistow in 1994.4 MIF is a remarkably small gene and comprises three exons of 205, 173, and 183 base pairs (bp), separated by two introns of 189 and 95 bps (EMBL ID: HSMIF http://www.ebi.ac.uk/htbin/emblfetch?L19686). Only a single functional MIF gene exists in humans (chrom 22q11.2), unlike in mice, where several processed (intronless) pseudogenes have been described.63–65 The clones sequenced by Paralkar and Wistow identified 250 bp of 30 untranslated region (30 UTR) and 1 kb of 50 flanking region. Primer extension and 50 rapid amplification of cDNA ends (RACE) were used to map the transcription start site, and this identified a single site 97 bp upstream from the initiator methionine, in a TATA-less promoter.4 These approaches cannot exclude the presence of additional transcription start sites, and the anatomy of the MIF promoter, consisting of abundant GC content, and no TATA box, would suggest the presence of multiple transcription start sites. However, analysis of mRNA harvested from multiple tissues, heart, brain, placenta, lung, liver, skeletal muscle, kidney, and pancreas, by northern analysis identified a single transcript (of approx 800 nucleotides).

14.7.1 POLYMORPHISMS

OF THE

HUMAN MIF GENE

The presence of raised MIF protein concentrations within the serum, plasma, or tissue in several divergent diseases suggests a role for MIF in pathogenesis.8 The increased expression of MIF in these sites could be consequential, rather than causative. In an attempt to address this conundrum, sequence variation of the MIF gene has been determined. The identification of any polymorphic variants of MIF would allow future comparisons of specific combinations of these genetic changes (or genotypes) with diseased and nondiseased individuals to be undertaken. If a genetic basis to altered endogenous MIF protein production were found to underlie the disease states this would be important evidence for a central contributory role of MIF in the pathogenesis of the disease. Donn et al.48 used denaturing high performance liquid chromatography (dHPLC, Wave, Transgenomic) to look for variation across the whole of the MIF gene and 1 Kb of the 50 flanking region. This screen was performed in 32 healthy, normal UK caucasian individuals and in 96 children with juvenile idiopathic arthritis (JIA), a chronic inflammatory disease in which raised MIF protein concentrations had been described. Four polymorphic positions were found. These were all seen both in the healthy volunteers and subjects with JIA. The CATT repeat element, originally documented by Paralkar and Wistow,4 was found to be polymorphic with 5–8 existing alleles. The 8 allele repeat is found at only very low allele frequency in UK caucasians. Also, within the 50 flanking region a single nucleotide polymorphism (SNP) at nucleotide position
173(G to C) (relative to HSMIF) was seen. Two intronic polymorphisms at nucleotide positions þ254 (T to C) and at þ656 (C to G) were

198

Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 14.1 Schematic representation of the MIF gene (three exons and two introns) with the 50 flanking region. The sites of four polymorphisms, i.e. three SNPs and one microsatellite CATT repeat, are indicated, þ1 ¼ transcription start site.

also identified. These polymorphic positions are shown in Figure 14.1 (amended from review). Baugh et al.,50 having sequenced the 50 flanking region of MIF in six normal individuals and six rheumatoid arthritis patients, also described the tetranucleotide CATT repeat element which begins at position
794.

14.7.2 GENETIC POLYMORPHISMS IN MIF AND ASSOCIATION WITH DISEASE (TABLE 14.1) Following the description of genetic polymorphisms in MIF a limited number of disease association studies have been described. Baugh et al.50 showed that the short CATT repeat (CATT5) was associated with less-severe rheumatoid arthritis in a cohort of hospital derived patients from Wichita, U.S.A. Barton et al.51 found an association between a specific MIF promoter haplotype composed of CATT7-MIF-173*C and susceptibility to adult inflammatory polyarthritis. The majority of this cohort developed RA. When outcome measures of disease severity were considered however, no association with MIF polymorphisms was seen. These differences may be explained by variation in case ascertainment, but taken together a pathogenic role for MIF is supported. The same promoter haplotype (CATT7-MIF-173*C) has been shown to be both linked and associated with JIA. JIA is the commonest chronic arthritis to commence before the age of 16 years. It encompasses seven clinically distinct subgroups, all of which share the feature of chronic synovitis. The MIF-173*C-CATT7 haplotype was found to confer increased risk to all JIA subgroups. The CATT7-MIF-173*C haplotype has also been found to be a susceptibility factor for the development of psoriasis in a UK caucasian population.47 Hizawa et al.66 studied the MIF-173G/C and the CATT repeat elements in a large Japanese cohort (n ¼ 584) for the possible association of MIF promoter polymorphisms with the development of atopy and asthma. Individuals homozygous for CATT7-MIF-173*C (MIF-173*CC) were at almost four times increased risk of atopy compared to MIF-173*GG homozygotes. Similarly,
794 CATT5 non-carriers were at 3.5 fold increased risk of atopy when compared to CATT5/CATT5 homozygotes. Haplotype analysis showed the MIF173*G-CATT5 haplotype to be significantly associated with a lower risk of atopy and the MIF-173*C-CATT7 haplotype to be positively associated with an increased risk of atopy. Whilst significant associations of MIF polymorphisms and atopy were identified, no association of MIF and asthma was seen. In vivo and in vitro models have shown the importance of MIF in the development of chronic colitis, both Crohn’s disease52 and ulcerative colitis.67 Nohara et al.68 considered the importance of the MIF-173G/C polymorphism as a susceptibility factor for ulcerative colitis in a Japanese population. The study compared MIF-173 genotype frequencies between

199

Macrophage Migration Inhibitory Factor (MIF )

221 patients with UC and 438 healthy controls. No significant differences in genotype distribution between the cases and the controls was seen. However, a highly-significant association of the MIF-173*CC genotype and the extent of ulcerative colitis was found. Nine out of ten (90%) patients with pancolitis had the MIF-173*CC genotype compared with only 96/211 (45%) of patients with more restricted distal or left-sided colon disease. Therefore, individuals with the MIF-173*CC genotype were almost 11 times more likely to suffer from an extended pancolitis form of UC. This study implicates MIF gene polymorphisms as important in the severity of UC disease. Whilst these findings are based on relatively small numbers, were these findings to be replicated this could potentially translate to a screening test for the development of pancolitis at disease presentation. The MIF-173*C polymorphism has also been shown to be positively associated with sarcoidosis in biopsy proven erythema nodosum in a Spanish population. No association between MIF
173G/C and giant cell arteritis, however, was observed by this study in the same Spanish population.69 The clinical relevance of the MIF -173*C promoter polymorphism has been further explored by De Benedetti et al.70, who found it to be predictive of disease outcome in patients with systemic onset juvenile idiopathic arthritis, a particularly severe onset type of JIA. Specifically, they found that carriage of the MIF-173*C polymorphism was correlated with raised serum and synovial fluid levels of MIF protein, and to be predictive of the duration of response to intra-articular injection of triamcinolone hexacetonide (TXA). Those individuals with a mutant allele at
173 (MIF-173*C) relapsed more quickly than individuals with the MIF-173 GG wild-type genotype. This effect has now also been demonstrated for the response to intra-articular TXA injection in patients with an oligo-articular phenotype ( 4 joints affected at presentation), the commonest presentation of JIA. Again, the duration of clinical response to the steroid treatment (months with no clinical evidence of synovitis) was significantly shorter in patients carrying a MIF-173*C allele (median 6 months; range 1–39) than in the MIF-173*GG homozygotes (median 9 months, range 2–62). So far only a limited number of genetic studies have been undertaken for the MIF gene locus. The ones that have been (as summarized in Table 14.1) are largely supportive of the importance of MIF as a driving entity in the pathogenesis of a wide range of inflammatory conditions.

14.7.3 PROMOTER ACTIVITY OF MIF AND SIGNIFICANCE OF THE KNOWN POLYMORPHIC VARIANTS

THE

To date a small number of different groups, in several cell lines, have confirmed the putative promoter identified by Paralkar and Wistow.4 Baugh et al.50 described variation in reporter gene luciferase activity for the different CATT alleles, with the CATT5 allele shown to have the lowest level of basal and stimulated MIF promoter activity in human lung epithelial (A549) and fibroblast cell lines. Hizawa et al.66 looked at three haplotypic constructs (CATT5-MIF-173*G, CATT6-MIF-173*G and CATT7-MIF-173*C) in A549 cells and found the CATT7-MIF-173*C haplotype to have lower promoter activity as determined by dual luciferase assays, than either the CATT5-MIF-173*G or CATT6-MIF-173*G, which themselves did not differ significantly in promoter activity. Donn et al.46,47 have shown that the MIF-173G/C polymorphism regulates promoter activity and that higher reporter gene luciferase activity is found for the MIF-173*C allele in the human T lymphoblast cell line (CEMC7A), whilst in human lung epithelial cells (A549s) MIF-173*G allele has higher luciferase promoter activity. Functional interaction between the CATT repeats and the
173 SNP has also been observed. Constructs of MIF-173*C with CATT5, 6 and 7 length repeats and similarly, a series of constructs with MIF-173*G together with CATT5, 6 and 7 length

200

Cytokine Gene Polymorphisms in Multifactorial Conditions

repeats were studied and a cell type specific difference found. In the CEMC7A cell line increasing CATT repeat with the MIF-173*C polymorphism significantly increased the luciferase promoter activity. No effect of CATT repeat length with the MIF-173*G was seen. In the A549 cells again increasing CATT repeat length significantly increased luciferase activity of the MIF-173*C constructs. However, increasing CATT repeat length reduced the luciferase activity of the MIF-173*G constructs. This work suggests that different transcription factors occurring within different cell types by binding to the CATT and MIF173*G/C polymorphic sites, alter MIF promoter activity. Such cell type-specific interactions with naturally occurring gene promoter polymorphisms are well described, for example in prolactin,71 IL-10,72 and IL-6,73 and likely reflect the differential expression of transcription factors and co-factors between cell types. It is increasingly recognized that important gene regulatory elements can map at distant sites both 50 and 30 to the coding region of the gene. Furthermore, the chromatin environment of different cell types could dramatically influence the amount of MIF protein produced. It will therefore be necessary to look comprehensively at the genomic region surrounding MIF for such regulatory sites and to study them within a native chromatin environment.

14.7.4 MIF

AND

GLUCOCORTICOIDS

MIF has a special relationship with GCs as mentioned above. Therefore, GCs regulation of MIF reporter gene activity of all haplotypic constructs MIF CATT(5
7)-173*C/G-luc was investigated in the same two human cell lines CEMC7A and A549. Clear evidence was found of dose-dependent dexamethasone inhibition of MIF promoter activity. There was detectable repression at 10
8 M Dex, and 50% inhibition at 10
6 M Dex. No differences, however, were found between the different MIF promoter haplotypes examined. Importantly, there was no suggestion of an induction in MIF promoter activity at low concentrations of Dex. In contrast to the inhibition of MIF promoter function seen in CEM C7A cells there was no inhibition seen in A549 cells.12 Dex suppressed MIF promoter activity in dose-dependent manner (up to 50% with 10
6 M), and this suppression was the same with the all different MIF promoter haplotypes examined in CEMC7A cells. This effect was abolished by Mifepristone (RU486), a GC antagonist. Therefore it can be assumed that Dex is acting through the conventional GR.12 Most pro-inflammatory cytokines lack consensus binding sites for the GC reporter, and the activated GR inhibits such genes by interacting with DNA-bound NFkB, or AP-1 transcription factors.74–76 The MIF promoter, which is rich in G and C nucleotides, lacks a consensus GR binding site. Bioinformatic analysis shows that the MIF promoter does contain a number of putative NFkB and AP-1 binding sites. Therefore, it would appear to be paradoxical that the MIF gene would be upregulated by activated GR. In addition, induction of the MIF promoter with Dex is expected to be at higher concentration than is needed for inhibition.77

14.8 SUMMARY In summary, MIF has a number of unusual biological properties. It is expressed at sites of inflammation, and increased concentrations are found in serum in inflammatory disease. A direct pro-inflammatory role for MIF has been proposed, that acts augmenting TNF-a secretion, and limiting the anti-inflammatory actions of glucocorticoids. Genetic polymophisms in the MIF gene are functional, influencing MIF promoter activity, and the same polymorphisms are associated both with serum MIF concentrations and susceptibility to diverse Th1-mediated inflammatory diseases. Unusually, a high affinity receptor for MIF remains to be found, and how MIF exerts its effects remains largely uncertain. There is evidence for an intracellular role of MIF, but it is not clear if this results from internalization

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of circulating MIF, or by direct action through an intracrine mechanism. Therefore much remains to be learned about both how MIF production is regulated, and how MIF works in vivo.

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41.

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173 polymorphism of the macrophage migration inhibitory factor gene in systemic-onset juvenile idiopathic arthritis, Arthritis Rheum., 48, 1398, 2003. Baugh, J. A., Chitnis, S., Donnelly, S. C., Monteiro, J., Lin, X., Plant, B. J., et al., A functional promoter polymorphism in the macrophage migration inhibitory factor (MIF) gene associated with disease severity in rheumatoid arthritis, Genes Immun., 3, 170, 2002. Barton, A., Lamb, R., Symmons, D., Silman, A., Thomson, W., Worthington, J. et al., Macrophage migration inhibitory factor (MIF) gene polymorphism is associated with susceptibility to but not severity of inflammatory polyarthritis, Genes Immun., 4, 487, 2003. de Jong, Y. P., Abadia-Molina, A. C., Satoskar, A. R., Clarke, K., Rietdijk, S. T., Faubion, W. A. et al., Development of chronic colitis is dependent on the cytokine MIF, Nat. Immunol., 2, 1061, 2001. Yoshida, T., Siltzbach, L. E., Masih, N., and Cohen, S., Serum-migration inhibitory activity in patients with sarcoidosis, Clin. Immunol. Immunopathol., 13, 39, 1979. Amoli, M. M., Donn, R. P., Thomson, W., Hajeer, A. H., Garcia-Porrua, C., Lueiro, M. et al., Macrophage migration inhibitory factor gene polymorphism is associated with sarcoidosis in biopsy proven erythema nodosum, J. Rheumatol., 29, 1671, 2002. Shimizu, T., Nishihira, J., Mizue, Y., Nakamura, H., Abe, R., Watanabe, H. et al., High macrophage migration inhibitory factor (MIF) serum levels associated with extended psoriasis, J. Invest. Dermatol., 116, 989, 2001. Donn, R. P., Plant, D., Jury, F., Richards, H. L., Worthington, J., Ray, D. W. et al., Macrophage migration inhibitory factor gene polymorphism is associated with psoriasis, J. Invest. Dermatol., 123, 484, 2004. Meyer-Siegler, K., and Hudson, P. B., Enhanced expression of macrophage migration inhibitory factor in prostatic adenocarcinoma metastases, Urology, 48, 448, 1996.

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15

Polymorphisms of Chemokines and Their Receptors Be´ne´dicte Puissant, Christophe Combadie`re, and Elise Lavergne

CONTENTS 15.1 15.2

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Polymorphisms of Chemokines and Their Receptors . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.1 CCR5/CCL5 Axis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.1.1 CCR5D32 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.1.2 Other CCR5 Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.1.3 CCL5 Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.2 CCR2/CCL2 Axis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.2.1 CCR2 Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.2.2 CCL2 Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.3 CX3CR1/CX3CL1 Axis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.3.1 CX3CR1 Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.3.2 CX3CR1 Gene Promoter Polymorphisms . . . . . . . . . . . . . . . . . . . . 15.2.4 CXCR4/CXCL12 Axis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.4.1 CXCR4 Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.4.2 CXCL12 Variants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3 Disease Associations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.1 Infectious Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.2 Autoimmune Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.3 Cardiovascular Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.4 Transplantation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.5 Neurodegenerative Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.6 Allergy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.7 Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

207 208 208 209 209 209 210 210 210 210 211 211 211 211 212 212 212 213 213 214 215 215 215 216 216

15.1 INTRODUCTION Leukocyte recruitment is a multistep process involving several protein families, including adhesion molecules (such as selectins and integrins), matrix metalloproteinases, and chemotactic factors. The latter include the chemokines, a family of structurally-related chemotactic cytokines that direct the migration of leukocytes throughout the body, under both physiological and pathological conditions.1 Successful trafficking of the appropriate leukocyte population to restricted sites depends on local secretion of chemokine repertoires and on the programmed expression of chemokine receptors on leukocytes. 207

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Chemokines are composed of single polypeptide chains, 70–100 amino acids in length, with 20–95% sequence similarity. The number and spacing of the conserved cysteines distinguish four chemokine subfamilies: in CC chemokines the first two cysteines are adjacent; in CXC chemokines, they are separated by one amino acid; CX3C chemokines have three intervening amino acids; and C chemokines lack one of the two canonical cysteine bridges.2 Based on this structural framework, a new nomenclature currently lists about 50 chemokines (http://cytokine.medic.kumamoto-u.ac.jp/CFC/CK/Chemokine.html). Many CXC chemokine genes are located on human chromosome 4q12–21, while most CC chemokine genes are on chromosome 17q11–21. Generally, chemokines exert their biological functions by binding and activating seven-transmembrane-domain G protein-coupled receptors on their target cells. Eighteen chemokine receptors have so far been cloned. Unlike chemokines with their structurally determined classification, chemokine receptors are grouped into four families based on their chemokine subclass specificity and thus their triggering of intracellular signals that initiate cell-specific functional programs including adhesion, chemotaxis, degranulation, cytokine secretion, and survival. The genes encoding most human CC chemokine receptors have been mapped to a cluster on chromosome 3p21 while those encoding CXC chemokine receptors are more dispersed. Chemokines were first recognized for their central role in recruitment of a wide spectrum of leukocytes to inflammatory sites. Promising investigations are intensely searching for therapeutic tools that interfere with their action.3 Drugs targeting them are among the most promising new anti-inflammatory treatments because they may be more selective than current anti-inflammatory drugs and less harmful than immunosuppressants. It is not surprising that pathogens exploit chemokine receptors, given the latter’s role in host defense. Lentivirus infections are most thoroughly documented, especially HIV and SIV, which can infect their target cells by binding to CD4 molecules and a co-receptor (in humans, mainly CCR5 and CXCR4).4–7 Genetic disorders have often highlighted the role of specific molecules in pathologic processes and have sometimes led to the identification of new therapeutic targets. The best example of genetic validation of a chemokine-related therapeutic target is probably the discovery of a CCR5 null allele that protects against HIV infection. Since then, numerous chemokine and receptor variants have been described and associated with disease states. Many of these reports, however, contradict one another. We will review the main associations of chemokines and their receptors with diseases, in humans and in ‘‘knockout’’ animal models.

15.2 POLYMORPHISMS OF CHEMOKINES AND THEIR RECEPTORS 15.2.1 CCR5/CCL5 AXIS CCR5 is expressed on various hematopoietic (including lymphocytes, macrophages, and granulocytes) and non-hematopoietic cells.8–11 It binds to many chemokines, including CCL3, CCL4, and CCL5. CCR5 also binds to HIV-1 envelope protein GP120, which perverts it from its original functions to obtain viral access to immune system cells including macrophages and CD4 T cells.4,6,12 Genetic approaches confirm its physiopathological relevance: individuals carrying a rare CCR5 allele called CCR5D32 are almost totally resistant to HIV-1 infection (see Chapter 27). Its role in HIV infection has led to intense scrutiny of both the receptor and its ligand, and different variants have been described. Interestingly, CCR5-deficient (CCR5
/
) mice show altered T cell activity, impaired macrophage function, and fewer infiltrating leukocytes on infection than wild-type mice, and their susceptibility to numerous pathogen changes.13–21 Met-CCL5, a CCR5 antagonist,

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impairs host defense by altering T cell recruitment22 and cytokine response.23 Taken together, these results suggest that CCR5, by regulating T cell polarization, activation, and differentiation, is important in both pathogen clearance and immune control. 15.2.1.1

CCR5D32

CCR5D32, the most frequent human CCR5 coding sequence mutation, is a deletion of 32 base pairs between nucleotides 554 to 585, which causes a frame shift after amino acid 184.22,24 The CCR5D32 variant lacks the three last transmembrane domains. Homozygous CCR5D32 subjects do not express membrane CCR5 and heterozygous subjects express much less than those without the polymorphism.25,26 Irrespective of the CCR5D32 genotype, however, membrane CCR5 expression varies greatly between individuals, perhaps due to differences in its promoter region. CCR5D32 allelic frequency varies substantially by geographic origin and ranges from 1% to more than 15% among whites.27 Its high frequency in Europe suggests that at one time it conferred some advantage that led to its selection. It appears likely that another pathogen contributed to the origin and the spread of this allele, for the hypothetical infectious agent causing this selection must have preceded HIV entry into the human population by many centuries. The identification of CCR5D32 in 2900-year-old skeletal remains from Germany and Italy suggests that this mutation was prevalent among prehistoric Europeans.28 Bubonic plague does not appear to be the agent responsible for this selection, because CCR5D32 allele frequency in victims of the 14th century plague pandemic in northern Germany does not differ from that in a historic control group,28 nor does CCR5 deficiency in mice protect against experimental infection or death by Yersinia pestis.29,30 A more likely hypothesis is smallpox.31 Individuals homozygous for CCR5D32 ‘‘can live normally’’ and, unlike CCR5-deficient mice, do not appear to have defective T-cell responses. The redundancy, at least partial, of CCR5 chemokine receptor function may explain this discrepancy. Thus, the role CCR5 plays in leukocyte trafficking and immunity during infection remains to be determined. 15.2.1.2

Other CCR5 Variants

At least twenty other single nucleotide polymorphisms (SNP) have been described in the CCR5 coding region32 (see Ref. 33 for review). Most of these mutations have an allele frequency below 1% and they bind CCL3 with functional responses similar to the frequent allele. The CCR5–C101X mutation has a stop-codon before the third transmembrane domain that prevents receptor expression at the cell membrane.32 The CCR5 gene promoter is highly polymorphic, and four haplotypes appear to account for over 90% of those observed.34 More specifically, CCR5–303A (which McDermott called
59029A) shows more promoter activity than 303G and lower macrophage membrane expression; it is associated with lower rates of in vitro HIV replication and higher chemokine production.35 15.2.1.3

CCL5 Variants

Eight SNPs have been described in the CCL5 gene (also known as RANTES for regulated on activation, normal T cell expressed and secreted), five in the promoter (
471C/T,
403G/A, 105C/T,
109T/C, and
28C/G), two in the first intron (In1.1T/C and In1.2G/A) and one in the 30 untranslated region (30 222T/C).36,37 Allele frequency of
403A ranges from 18% to 36% among European Americans, African Americans, and Asians. The
28G allele is infrequent in whites, but has a frequency of 13% among Asians. The other two promoter alleles are rare:
105T and
109C. Of the two intronic SNPs, In1.1C is frequent in all three groups (ranging from 15% to 35%), whereas In1.2A is found only among African Americans, and at a low frequency there (5%). One study reports that both the
28G

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Cytokine Gene Polymorphisms in Multifactorial Conditions

and
403A variants increase CCL5 transcription, while In1.1C down-regulates gene transcription.36

15.2.2 CCR2/CCL2 AXIS The chemokine receptor CCR2 is expressed on monocytes, B and T cells, and natural killer cells.38–41 Its most common ligand, CCL2, is also known as monocyte chemotactic protein-1 (MCP-1) and is produced by monocytes, lymphocytes, endothelial cells, fibroblasts, and neurons.38,42 CCR2 responds to a number of other CC chemokines including CCL7, CCL8, and CCL13.43–45 Two alternatively spliced CCR2 isoforms, CCR2A and CCR2B, differ only in their C-terminal cytoplasmic tails: CCR2A traffics to the cell surface while CCR2B is localized in the cytoplasm.46 CCR2
/
and CCL2
/
mice develop normally, have no hematopoietic abnormalities, but have significant defects in both delayed-type hypersensitivity responses and Th1-type cytokine production.47,48 Other impairments in CCR2
/
mice involve monocyte trafficking to inflammation sites and IFN-g production.47 Specifically, mortality from M. tuberculosis49,50 and from coronavirus mouse hepatitis virus infection51 increases, associated in both cases with defective peripheral blood mononuclear cell migration. These findings have some implications for the development of human therapy because CCR2 antagonists can increase susceptibility to intracellular pathogens. 15.2.2.1

CCR2 Variants

Eight SNPs with frequencies ranging from 5% to 20% have been described in the CCR2 gene, two in the promoter, one in the first exon (190G/A, i.e., 64V/I), one in the second exon and four in the 30 untranslated region.52 The most frequent SNP is also the most extensively explored: CCR2-V64I. The CCR2-64I allele is distributed in populations throughout the world at a frequency around 10–20% in most.53 This substitution in the first transmembrane domain increases the half-life of CCR2A but is not associated with altered membrane CCR2 expression or defective CCL2 binding.46 CXCR4 can also dimerize with CCR2-64I but not with the wild type and may help prevent HIV infection.54 Linkage disequilibrium between CCR2-64I and polymorphisms in the CCR5 gene makes it difficult to interpret the genetic effects of CCR2.55 15.2.2.2

CCL2 Variants

Two SNPs are reported to affect the distal regulatory region of the CCL2 promoter:
2518 A/G (also designated
2578) and
2076 T/A transitions.56 Because cells obtained from GG or AG individuals produce more CCL2 than those isolated from AA individuals,
2518 A/G seems to influence transcriptional activity.56–60 One study reports a contrary result in a group of lupus nephritis patients.61 This polymorphism may determine the severity of organ inflammation in diseases where tissue leukocyte infiltration depends on CCL2.

15.2.3 CX3CR1/CX3CL1 AXIS CX3CR1, the only member of its CX3C chemokine receptor family, is expressed on monocytes, subpopulations of both CD4þ and CD8þ cytotoxic T lymphocytes, dendritic cells, and natural killer cells.62,63 Its unique ligand, CX3CL1 (or fractalkine), is characterized by a mucin-like stalk, a transmembrane domain, and a cytoplasmic tail allowing the molecule to exist in both soluble and membrane-anchored forms. Membrane-bound CX3CL1 directly mediates strong and rapid adhesion of CX3CR1-expressing leukocytes, and soluble CX3CL1 has classic leukocyte chemotactic activity.64 CX3CR1 and CX3CL1 participate in inflammatory response and appear in particular to be linked to Th1 adaptive immune

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211

responses.65 Besides its role in immune cell migration, CX3CR1 has a unique role in microglia chemotaxis and communication with neurons in the brain.66 CX3CR1 and CX3CL1 knockout mice show no developmental defects or exacerbated immune impairment.67,68 Profiles of CX3CL1
/
mice differ from classic hematologic profiles only in that fewer monocytes express the cell surface marker F4/80. 15.2.3.1

CX3CR1 Variants

Four nonsynonymous SNPs on the CX3CR1 coding region have been identified, all in transmembrane domains.69 The SNPs in positions 57 and 122 are each rare (1%). The other two, resulting in allelic variants V249I and T280M respectively, are frequent in white populations (about 25% and 13%, respectively). V249 T280 is the most common haplotype in all ethnic groups: the V249 M280 allele was only observed recently, in a Japanese study.70 These two polymorphisms induce changes located in the sixth and seventh transmembrane domains, respectively, and may therefore directly affect receptor function. Two major studies investigated the functional effect of these mutations.71,72 The first reported that in vitro CX3CR1–M280 cell response to CX3CL1 was globally impaired, in its ligand binding, calcium response, and adhesive and chemotactic functions.71 In the second study, however, both CX3CR1 variants responded similarly to soluble CX3CL1, but the cells expressing I249 M280 were captured in larger numbers in response to immobilized CX3CL1. These conflicting results may be due to subtle differences in manipulation conditions or cell-line features. But it may be interesting to consider these sets of data to reflect two different CX3CR1 functional states. 15.2.3.2

CX3CR1 Gene Promoter Polymorphisms

Eight SNPs located within the first putative promoter and one within the first exon of the gene have been described.73 Linkage disequilibrium is reported between the SNPs in the coding and promoter regions, and further experiments should investigate the impact of these different haplotypes on the biological implications of this receptor.

15.2.4 CXCR4/CXCL12 AXIS CXCR4 and its ligand CXCL12, also named stromal cell-derived factor-1 (SDF-1), are widely expressed in tissue, including lymphatic, thymus, brain, spleen, stomach, small intestine, and adrenal gland tissues.74 The embryonic lethality of CXCR4 and CXCL12 knockout mice demonstrates the fundamental role of this dyad in fetal development, organogenesis,75 hematopoiesis, B-cell lymphopoiesis and myelopoiesis,76 hematopoietic stem cell mobilization,77 and angiogenesis.78 15.2.4.1

CXCR4 Variants

Because of their key role in many physiological processes,79 CXCR4 and CXCL12 are highly conserved in humans and other species and seem not to tolerate alterations. Two mutations described in the CXCR4 coding region in white HIVþ non-progressors were each unique to two patients.80 Three other polymorphisms have been associated with WHIM (warts, hypogammaglobulinemia, recurrent bacterial infections, and myelokathexis) syndrome: a two base pair deletion at positions 1016–1017 and two mutations leading to premature stop codons (R334X and E343X). All three mutations result in truncation of cytoplasmic tail residues that are involved in receptor function regulation.81 Seven more SNPs have been identified in a Chinese Han population.82

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15.2.4.2

Cytokine Gene Polymorphisms in Multifactorial Conditions

CXCL12 Variants

CXCL12 exists in two subtypes, CXCL12-a and CXCL12-b, which arise by alternative splicing of a single gene and differ by four additional amino acid residues in CXCL12-b.83 Only one mutation is known in this gene, located in the 30 untranslated region of CXCL12-b and abbreviated CXCL12-30 A (
801 G/A).84 CXCL12-30 A is found in all world populations, in whites (20%), Hispanics (16%), African Americans (6%), Asians (26%), and Oceanians (71%).53 The effect of this mutation on CXCL12 function and mRNA and protein expression remains unclear: the CXCL12-30 A mutation is not correlated with CXCL12 mRNA levels,85,86 but CXCL12-30 A homozygosity is associated with low plasma CXCL12 levels.87

15.3 DISEASE ASSOCIATIONS 15.3.1 INFECTIOUS DISEASES In addition to their role in HIV infection, discussed in detail in Chapter 27, polymorphisms of chemokines and their receptors also play a role in hepatitis C viral (HCV) infection, where they have been studied extensively. CCR5D32 is not associated with susceptibility to HCV infection, stage of fibrosis, or response to therapy.88–92 Although other studies report that CCR5D32 is associated with increased HCV viral load93 and lower hepatic inflammatory scores,94,95 these discrepancies may reflect significant differences in the selection criteria for cases and controls (such as HIV infection or hemophilia). The CCL5403A allele is correlated with less severe inflammation94 in HCV-infected patients, while both the CCL53’222C and CCL5 Int 1.1 alleles occur more frequently in HCV-infected patients unresponsive to antiviral treatment.96 The latter allele down-regulates CCL5 transcriptional activity in vitro and is associated with diminished T helper 1 lymphocyte response in these patients. The CCR5-G59029A allele is also marginally associated with sustained response to interferon therapy in HCV-infected patients.90 One study reports a similar frequency of CCL2 genotypes in HCV patients and controls but more advanced fibrosis and severe inflammation associated with the mutated allele.58 The failure of another study97 to confirm this may be due to differences in fibrosis scoring. Mascheretti et al. report a lower CCR2-64I allele frequency in HCV-infected patients who spontaneously cleared the virus than in other patients,89 but according to Promrat et al. the CCR2 polymorphism is not associated with clinical HCV outcome.90 The CXCL12/CXCR4 pathway plays an important role in recruitment and retention of immune cells in the liver during chronic HCV and hepatitis B virus (HBV) infections,98 although the CXCL12- 30 A mutation does not affect the course of HCV or HIV/HCV infections.99 The impact of polymorphisms of chemokines and their receptors on HCV infection remains unclear for many reasons, including co-infections in patients with HIV, the low allelic frequency of CCR2-64I, linkage disequilibrium between the CCR2 and CCR5 polymorphisms, and other confounding factors. Explorations of the influence of CCR5D32 on immunity to common herpes virus infections in humans suggest that CCR5 variations do not modulate humoral immunity to varicella zoster virus, Epstein–Barr virus, cytomegalovirus, or herpes simplex virus (HSV) type 1 or 2.100,101 Experiments in mice models, however, indicate that CCR5 is important in both viral clearance and immune response control during HSV-2 infection.23 According to a recent study, CX3CR1 is a key mediator of dendrite formation on mucosal dendritic cells and thus controls clearance of entero-invasive pathogens.102 The impact of its polymorphisms on commensal and pathogenic microbial infections has not yet been studied, however. A CXCR4 frameshift mutation (1016–1017delCT) and two

Polymorphisms of Chemokines and Their Receptors

213

nonsense mutations (R334X and E343X) are reported in separate families with WHIM syndrome, an immunodeficiency disease characterized by neutropenia, hypergammaglobulinemia and extensive papilloma virus infection.81 Neutrophils and T cells from WHIM patients with truncated or wild-type CXCR4 show sustained CXCR4 activity and increased migration in response to CXCL12.103,104 Truncation appears to decrease internalization of mutated CXCR4;105 for the wild-type receptor a genetic anomaly may target an effector that interacts with the CXCR4/CXCL12 axis.104

15.3.2 AUTOIMMUNE DISEASES Studies report increased expression of CCR5 in peripheral lymphocytes and increased levels of CCL5 in cerebrospinal fluid and in demyelinating brain lesions of multiple sclerosis (MS) patients.106,107 The association of the CCR5D32 allele with MS remains controversial. Two studies report no association between allele frequency and MS,108,109 although age at onset was approximately 3 years later in patients with the allele.109 Other studies, however, find the allele to have a protective110 or an adverse111,112 impact. MS is associated with the two CCL5 alleles known to increase CCL5 gene expression: the
403A allele is significantly more frequent in MS patients than controls, and the
28G allele is associated with both early onset and longer survival.113 Several studies in mice suggest that CCR2 and its ligands play a role in MS pathogenesis; notably, CCR2
/
mice do not develop clinical experimental autoimmune encephalitis.114,115 CCR2/CCL2 polymorphisms, however, do not appear to be associated with MS,109,116 although one Japanese study reports that the CCR2-64I allele is protective.117 Although the frequency of rheumatoid arthritis (RA) is not associated with CCR5D32,118,119 its severity is.118–120 The frequencies of the CCL2
2518G and CCR2-64I polymorphisms are similar in patients with RA and controls.121–123 The CCR5D32 and CCR2-64I alleles are also not associated with systemic lupus erythematosus (SLE),124 myasthenia gravis,125 insulin-dependent diabetes mellitus (IDDM),126,127 or Addison’s disease.128 Children with IDDM have a significantly higher frequency of the CCR2-64I allele than controls,129 and CCR5-G59029 is more frequent in IDDM patients with microvascular complications than in patients with uncomplicated disease.127 Most studies conclude that distribution of the CCL2
2518 genotype is not correlated with sarcoidosis52,130–132 or SLE.57,61,133–135 This genotype is, however, associated with the occurrence of attacks of lupus nephritis,57 arthritis,135 and vasculitis,136 and may predispose patients to systemic sclerosis.137 The CXCL12 gene is located on chromosome 10q11.1, near the type-1 diabetes susceptibility locus IDDM10, and this ligand is reported to play an important role in the onset of diabetes in NOD mice.138 The CXCL12-30 A variant may modulate mononuclear cell infiltration of the pancreatic islet, a critical step in the pathogenesis of type 1 diabetes. Although this variant does not seem to influence IDDM susceptibility in French or Japanese populations,139–142 it is associated with the early onset of type 1 diabetes in patients with the HLA type at high risk for it.139,140 The CXCL12-30 A allele is not associated with SLE susceptibility.135

15.3.3 CARDIOVASCULAR DISEASES Several epidemiologic studies report CCR5 and CCL5 variants (CCR5D32 and CCL5-403A) are associated with a reduced risk of early myocardial infarction (MI)143 and severe coronary artery diseases (CAD).144–146 The CCL5 In1.1T/C polymorphism is associated with a significant increase in cardiovascular events in patients with type 2 diabetes and end-stage renal disease.146 Blockading CCR5 (and CCR1) with Met-CCL5 reduces atherosclerotic plaque formation in hypercholesterolemic mice.147 Two epidemiologic studies have failed

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Cytokine Gene Polymorphisms in Multifactorial Conditions

to confirm this suggested positive effect,148,149 and experiments in an atherosclerosis-prone mice model show that CCR5 deficiency does not affect the size of atherosclerotic lesions.150 The role of the CCR2/CCL2 axis in atherogenesis is well established in this murine model: those crossed with CCR2
/
mice have fewer and less severe atherosclerotic lesions.151,152 Moreover, blocking CCL2 controls plaque formation and improves the survival rate in mice with MI.153,154 The effect of the CCR2-64I allele in MI is ambiguous: although the first study reports that CCR2-64I is associated with a reduced risk of MI,144 subsequent studies find instead that it predisposes its carriers to MI.155,156 Increased risk of brain infarction, however, has a dominant borderline association with the CCR2-64I allele.157 These results are ambiguous, probably because of this allele’s low frequency and linkage disequilibrium with the CCR5 gene promoter region. CCL2
2578G is associated with a reduced risk of severe CAD144 but not with risk of brain infarction.157CX3CL1 and CX3CR1 are also compelling candidates for a crucial role in atherosclerosis. In proatherogenic murine models, the area of atherosclerotic lesions is dramatically lower in mice deficient for this receptor and ligand than in controls and contains significantly fewer macrophages.158–160 Several separate epidemiologic studies associate the CX3CR1 variants I249 and M280 with reduced CAD risk.71,149,157,161 The I249 allele is consistently associated with fewer CX3CL1 binding sites and lower CX3CL1 binding affinity to peripheral blood mononuclear cells.71,161 Moreover, endothelium-dependent vasodilatation, tested by intracoronary administration of acetylcholine, is higher in patients with the I249 allele.149 In contrast, a recent study reports these alleles have no significant effect on the onset of CAD but that in patients with CAD the I249 allele is associated with more frequent acute coronary syndromes and enhanced inflammatory response.162 The M280 allele appears to be an independent risk factor for internal carotid artery occlusive disease, and the I249 allele is more frequent in cases of hard plaque.163 Neither allele is associated with atherosclerosisrelated peripheral arterial disease.164 A case-control study reports that the rarer CX3CR1 alleles are an independent risk factor for brain infarction and confirms earlier accounts of a dominant protective association between the I249 allele and cardiovascular history.157 A study of a Japanese cohort, however, does not confirm the association of CX3CR1 polymorphisms with ischemic stroke.70 The lower frequencies of these rare alleles in Japanese than white populations may have influenced the results. Interestingly, in a murine model of stroke, mice deficient for CX3CL1 have smaller infarctions and lower mortality.165

15.3.4 TRANSPLANTATION Chemokines play a role in leukocyte migration in transplanted tissues and in transplantation injury.166 Clinical therapies targeting chemokines and their receptors are therefore being studied.167 CCR5 is involved in cardiac allograft rejection in mice: enhanced survival is observed in CCR5-deficient mice.168 In humans, CCL5 and CCR5 expression are correlated with the presence, grade, and timing of acute cardiac rejection.169,170 An initial study reports longer survival after renal transplants among recipients homozygous for the CCR5D32 allele,171 but subsequent studies of renal,172 cardiac,173 and liver transplantation174 fail to confirm this. Studies of CCR5-59029A are also ambiguous, showing a reduced incidence of acute renal transplant rejection in homozygous patients172 but no beneficial effect in liver transplantation recipients.175 The mononuclear cells infiltrating kidney grafts express CCL2 and CCR2.176,177 In mice, lack of CCR2 significantly prolongs islet allograft survival, reduces generation of CD8þ alloreactive T cells, increases Th2 response,122,178 but only marginally extends heart allograft survival.178 In humans, neither CCR2-64I genotype influences the risk of acute rejection or graft survival in liver allograft recipients,174 nor does CCL2
2518G modify susceptibility to acute allograft rejection in orthotopic liver transplantation.179

Polymorphisms of Chemokines and Their Receptors

215

Another study reports a significantly reduced risk of acute kidney transplant rejection in recipients carrying the CCR2-64I allele,172 and an elevated risk of premature kidney graft failure in carriers of the CCL2 –2518G allele.180 In liver transplantation, CXCL12-30 A is associated with higher mortality but not with the risk of acute rejection or graft survival.174 The CXCR4 mRNA-expressing leukocyte count rises in human renal allograft rejection, however, which suggests a relation between the receptor and this rejection.181 CX3CR1 polymorphisms are not associated with the incidence of renal transplantation rejection,172 but blocking CX3CR1 function delays the onset and improves the course of lupus nephritis,182 reduces proteinuria in glomerulonephritis,183 and prolongs cardiac allograft survival.184

15.3.5 NEURODEGENERATIVE DISORDERS Although chemokines and their receptors are up-regulated in CNS-resident cells and this up-regulation is linked to the pathological changes that characterize Parkinson’s disease and late onset Alzheimer’s disease,185 no association is so far reported between CCR5/CCL5 alleles and either Parkinson’s186 or Alzheimer’s disease.59,187,188 One study shows the mutated allele of the CCL2 gene to be significantly more common in subjects with Alzheimer than in controls.189 Two recent studies indicate that CX3CR1 M280 alleles are associated with an enhanced risk of age-related macular degeneration.190 CX3CR1 transcripts are detected only in the maculae of normal eyes bearing the TT or TM genotype and of diseased eyes with the TT genotype. Reduced CX3CR1-induced cellular activities, caused by sequence variation and/or lower CX3CR1 expression, may contribute to this disease.

15.3.6 ALLERGY Reports about the effect of CCR5D32 allele in asthma or atopy in both children191,192 and adults193–196 conflict. This discordance highlights once again the importance of the constitution of the study population, its genetic background and exposure to environmental factors. CCR5 knockout mice have less severe fungal asthma; neutralization of CCL5 further reduces asthma severity and allergic airway inflammation.197,198 Numerous studies point to the possible involvement of the CCL5 polymorphism in asthma. The CCL5 gene lies on chromosome 17q11.2–q12, a region linked to atopy.199 Moreover, the lungs of patients with asthma express elevated levels of CCL5.200,201 Many studies report an association between the CCL5 promoter polymorphism and increased susceptibility to asthma and atopy, and frequency of the
403A and
28G alleles is higher in patients with allergic rhinitis.202 The
403A allele is associated with elevated serum levels of CCL5 in Japanese patients with atopic dermatitis203 and with susceptibility to atopic dermatis and asthma.204–206 Studies of Hungarian children207 and Chinese and Japanese populations208,209 do not confirm this association, however.

15.3.7 CANCER Chemokines play a role in tumor biology, acting on physiopathological processes including antitumor immune response, metastasis, and angiogenesis.210 Malignant cells express CXCR4, which confers an invasive phenotype in vivo.211 The CXCR4 and CXCL12 axis is especially important in breast cancer,212,213 and CXCR4 expression is associated with poor overall survival and high metastasis rates in different types of cancer.214–222 The relation between CXCR4/CXCL12 polymorphisms and cancer, however, remains poorly understood. CXCL12-30 A allelic frequency is associated with the onset of breast cancer.223

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Both heterozygous and homozygous CXCL12-30 A genotypes are associated with increased susceptibility to breast cancer and to lung carcinoma in an Iranian population.224,225 CXCL12-30 A is also associated with increased susceptibility to non-Hodgkin lymphoma in AIDS patients.226 The percentage of CXCL12-30 A carriers is significantly higher among patients with lymphoma than with lymphoid leukemia.227 The CX3CR1 polymorphism is not associated with hepatocellular carcinoma.228

15.4 CONCLUDING REMARKS The study of polymorphisms of chemokines and their receptors has already proved fruitful. While CCR5 D32 and its relation to HIV is probably the best example of function validation, it is highly unusual for a genetic alteration to block expression of a chemokine completely and for a disease to rely almost wholly on one single path for host invasion. It is obvious from the data collected in this review that other disease settings are much more complex. This is due in part to the redundant nature of chemokines and their receptors: not only can a chemokine recognize several chemokine receptors, but a receptor may bind multiple chemokines. Cells crawl in a ‘‘chemokine soup’’ which confers strength and selectivity on the recruitment. Furthermore, chemokine functions may be altered by other sets of proteins such as proteases and cytokines that can toggle chemokine functions on and off. It is thus not surprising that the clinical impact of subtle variations in the sequence of chemokines and their receptors or in their expression is difficult to address individually with epidemiologic approaches. A more global approach using novel high-throughput technologies and generating determination of several hundred SNPs would be suitable for defining patients’ disease susceptibility, severity, and treatment efficacy. This would however require larger cohorts with standardized laboratory, clinical, and demographic characteristics.

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403 G !A promoter RANTES polymorphism with atopic asthma, Genes Immun., 6, 24, 2005. 207. Kozma, G. T. et al., Lack of association between atopic eczema/dermatitis syndrome and polymorphisms in the promoter region of RANTES and regulatory region of MCP-1, Allergy, 57, 160, 2002. 208. Yao, T. C. et al., The RANTES promoter polymorphism: a genetic risk factor for nearfatal asthma in Chinese children, J. Allergy Clin. Immunol., 111, 1285, 2003. 209. Hizawa, N. et al., A functional polymorphism in the RANTES gene promoter is associated with the development of late-onset asthma, Am. J. Respir. Crit. Care Med., 166, 686, 2002. 210. Balkwill, F., Cancer and the chemokine network, Nat. Rev. Cancer, 4, 540, 2004. 211. Balkwill, F., The significance of cancer cell expression of the chemokine receptor CXCR4, Semin. Cancer Biol., 14, 171, 2004.

Polymorphisms of Chemokines and Their Receptors

225

212. Muller, A. et al., Involvement of chemokine receptors in breast cancer metastasis, Nature, 410, 50, 2001. 213. Murphy, P. M., Chemokines and the molecular basis of cancer metastasis, N. Engl. J. Med., 345, 833, 2001. 214. Scala, S. et al., Expression of CXCR4 predicts poor prognosis in patients with malignant melanoma, Clin. Cancer Res., 11, 1835, 2005. 215. Longo-Imedio, M. I. et al., Clinical significance of CXCR3 and CXCR4 expression in primary melanoma, Int. J. Cancer, 2005. 216. Wang, N. et al., Expression of chemokine receptor CXCR4 in nasopharyngeal carcinoma: pattern of expression and correlation with clinical outcome, J. Transl. Med., 3, 26, 2005. 217. Schimanski, C. C. et al., Effect of chemokine receptors CXCR4 and CCR7 on the metastatic behavior of human colorectal cancer, Clin. Cancer Res., 11, 1743, 2005. 218. Kim, J. et al., Chemokine receptor CXCR4 expression in colorectal cancer patients increases the risk for recurrence and for poor survival, J. Clin. Oncol., 23, 2744, 2005. 219. Laverdiere, C. et al., Messenger RNA expression levels of CXCR4 correlate with metastatic behavior and outcome in patients with osteosarcoma, Clin. Cancer Res., 11, 2561, 2005. 220. Retz, M. M. et al., CXCR4 expression reflects tumor progression and regulates motility of bladder cancer cells, Int. J. Cancer, 114, 182, 2005. 221. Darash-Yahana, M. et al., Role of high expression levels of CXCR4 in tumor growth, vascularization, and metastasis, Faseb J., 18, 1240, 2004. 222. Schmid, B. C. et al., CXCR4 is expressed in ductal carcinoma in situ of the breast and in atypical ductal hyperplasia, Breast Cancer Res. Treat., 84, 247, 2004. 223. Zafiropoulos, A. et al., Significant involvement of CCR2-64I and CXCL12-3a in the development of sporadic breast cancer, J. Med. Genet., 41, e59, 2004. 224. Razmkhah, M. et al., Stromal cell-derived factor-1 (SDF-1) gene and susceptibility of Iranian patients with lung cancer, Lung Cancer, 49, 311, 2005. 225. Razmkhah, M. et al., Stromal cell-derived factor-1 (SDF-1) alleles and susceptibility to breast carcinoma, Cancer Lett., 225, 261, 2005. 226. Rabkin, C. S. et al., Chemokine and chemokine receptor gene variants and risk of non-Hodgkin’s lymphoma in human immunodeficiency virus-1-infected individuals, Blood, 93, 1838, 1999. 227. de Oliveira Cavassin, G. G. et al., Molecular investigation of the stromal cell-derived factor-1 chemokine in lymphoid leukemia and lymphoma patients from Brazil, Blood Cells Mol. Dis., 33, 90, 2004. 228. Muhlbauer, M. et al., Lack of association between the functional CX3CR1 polymorphism V249I and hepatocellular carcinoma, Oncol. Rep., 13, 957, 2005.

Part C Polymorphic Cytokine Networks in Multifactorial Conditions

16

Asthma and Atopy Jussi Karjalainen, Miia Virta, Kati A˚djers, and Mikko Hurme

CONTENTS 16.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.2 Definitions and Phenotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.3 Genetics of Asthma and Atopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.4 Mechanisms of Atopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.5 Cytokines in Asthma and Atopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

229 230 231 232 233 238 238

16.1 INTRODUCTION Atopic eczema, hay fever (allergic rhinitis), and asthma are often considered to be part of a common syndrome of atopic diseases.1 The prevalence of asthma has increased dramatically since the early 1980s and this is thought to be caused largely by environmental factors such as improved hygiene, more indoor activities, and fewer childhood infections.2 Asthma is now one of the most common chronic diseases in both children and adults. Clearly, asthma exacts a heavy toll in both its costs to society and its effect on the individual. Adults with asthma are troubled not only by the symptoms themselves, but by limitation of their daily activities (occupational, social, and physical), sleep impairment, and emotional problems such as anxiety and frustration.3 Moreover, although allergic rhinitis is not usually a severe disease, it significantly impairs patients’ quality of life.4 Similarly, these disorders interfere greatly with the daily lives of numerous children and their families. Both genetic and environmental factors contribute to the inception and evolution of asthma and atopy. To comprehend the pathogenetic mechanisms underlying these disorders, it is essential to identify factors which initiate, intensify, and modulate the inflammatory response of the airway and to determine how these immunological and biological processes produce the characteristic airway abnormalities.5 Therefore, the role of different cytokines and genetic variation among genes coding for cytokines is of particular interest. The generally accepted conception is that environmental factors are important for the development of asthma, but the individual must be genetically predisposed to respond to environmental influences.6 Multiple chromosomal regions and polymorphisms of several candidate genes have already been linked to or associated with asthma and atopy.7 However, these studies pose considerable challenges by reason of phenocopies (identical phenotypes may be attributable to different constellations of genes), the large number of genes involved, the effects of any particular gene being possibly fairly modest, and the unknown model of inheritance. The alleles which influence these phenotypes are not necessarily fully penetrant, which means that a proportion of the carriers of a susceptibility allele will not express the phenotype.8 229

230

Cytokine Gene Polymorphisms in Multifactorial Conditions

16.2 DEFINITIONS AND PHENOTYPING Phenotyping of study subjects is a matter of utmost importance in genetic studies on complex diseases such as asthma and atopy. Different phenotyping standards, including parameters for bronchial challenge data, normal values for lung function tests, and cutoff values for IgE are all factors that may skew the outcome.9 For instance both epidemiological and experimental data support the view that age at onset of asthma is an important phenotyping factor. When dealing with this issue, it must be borne in mind that the clinical context of phenotyping varies between physicians in pediatric and pulmonary medicine. The lack of a defined and specific asthma phenotype has been considered a major hurdle in reliably detecting asthma-associated genes.10 Consequently, much emphasis has been placed on surrogate markers of the disease, especially measures of bronchial hyperresponsiveness and atopy, although these are not specific to asthma.11 Moreover, genetic studies on atopy have varied greatly in the approach adopted to determine the atopic state, and these differences have contributed to the difficulties in developing a unified view of the subject. Here we give an overview on some of the most widely used asthma and atopy related phenotypes. Asthma: The definition of asthma has changed in recent decades with increasing understanding of the immunological mechanisms underlying the disorder. Until the 1980s its basic characteristics were considered to be bronchospasm, edema, and hypersecretion, while the more recent definition by the Global Strategy for Asthma Management and Prevention Report states that: Asthma is a chronic inflammatory disease of the airways in which many cell types play a role, in particular mast cells, eosinophils, and T lymphocytes. In susceptible individuals the inflammation causes recurrent episodes of wheezing, breathlessness, chest tightness, and cough particularly at night and/or early morning. These symptoms are usually associated with widespread but variable airflow obstruction that is at least partly reversible either spontaneously or with treatment. The inflammation also causes an associated increase in airway responsiveness to a variety of stimuli.

The role of airway inflammation is thus highlighted.12 Various methods have been used to define asthma in epidemiological studies. No generally applicable golden standard has been presented which would apply in both grouplevel epidemiology and individual-level clinical practice.13 Most epidemiological studies have used symptom questionnaires and history of physician-diagnosed asthma alone or together with observed bronchial hyper-responsiveness (BHR). Given the variable course of asthma and the different demands imposed by study design it is obvious that no single definition of asthma will be applicable to all studies.14 Total serum IgE: A high serum immunoglobulin E (IgE) level is one of the most frequently applied surrogate markers in asthma research. Ever since its discovery IgE has been connected with asthma.15 Burrows and his group studied IgE in a population cohort from Arizona. They found that age, gender, and smoking significantly affect serum IgE levels.16 Whether the subject is allergic or not the age- and gender-standardized IgE levels are associated with asthma.17,18 Moreover, in a prospective setting the age- and genderstandardized IgE levels have been identified as independent risk factors for asthma in both young adults and the elderly.19,20 In a longitudinal study IgE levels were seen to remain relatively unchanged after 35 years of age, while in younger age groups a slight decreasing tendency was found.21 Eosinophils: Most allergic and non-allergic asthmatics have bronchial eosinophilia and there is a significant association between eosinophil activation and asthma severity.

Asthma and Atopy

231

There is evidence that the number of eosinophils is increased in asthma as a consequence of reduced apoptosis.22 Peripheral blood eosinophilia is also frequently found in asthma and correlations have been observed between eosinophil levels and severity of symptoms, degree of airflow limitation, and bronchial hyper-responsiveness.23–25 Ideally, eosinophils should be measured from the airways, but peripheral blood measurements are often used in asthma surveys as being less time- and labor-consuming than alternative methods.26,27 Bronchial challenges: Challenge tests are also used in the characterization of asthmatic subjects. Bronchial hyper-responsiveness is defined as increased responsiveness or reactivity of the bronchi to various physical, chemical and pharmacological stimuli, manifested as airway narrowing.28 Tests for bronchial hyper-responsiveness, usually histamine or methacholine challenges, are used in clinical practice both as a part of asthma diagnosis and in the follow-up of the efficacy of treatment.29–32 Some researchers have proposed that in epidemiological studies asthma should be defined on the basis of asthma symptoms together with bronchial hyper-responsiveness.13 Atopy: The finding of IgE prepared the theoretical basis for a scientific definition of atopy.15,33 In 1975 the following proposal was made: that form of immunological reactivity of the subject in which reaginic antibody, now identifiable as IgE antibody, is readily produced in response to ordinary exposure to common allergens of the subjects’ environment.34

This does not imply the presence of symptoms; it is simply a description of the immunologic reactivity of the subject. The presence of specific IgE is usually studied by either skin prick test or serum assay. Recently the European Academy of Allergology and Clinical Immunology published a position statement on the revised nomenclature for allergy. The following proposal for a definition of atopy was offered: Atopy is a personal or familial tendency to produce IgE antibodies in response to low dose of allergens, usually proteins, and to develop typical symptoms such as asthma, rhinoconjunctivitis, or eczema/dermatitis.1

16.3 GENETICS OF ASTHMA AND ATOPY Allergic disorders have long been known to cluster in families.35 Preliminary evidence for a genetic effect on atopy and asthma has been obtained from twin studies. When aggregation of asthma cases in the Finnish adult twin cohort was studied, it was found that the concordance was higher among monozygotic than dizygotic twins. This led to an estimate of heritability (that proportion of aetiology attributable to genetic factors) of 36%.36 In the case of young twin cohorts even higher estimates (60–87%) for asthma heritability have been reported.37–39 Among the phenotypes associated with asthma, the total serum IgE level evinces marked heritability in different populations,40,41 whereas the specificity of the IgE response is mainly determined by environmental factors.41,42 Furthermore, a 3- to 5-fold genetic effect has also been demonstrated by comparing the relative risk of asthma in the siblings of the proband to the relative risk in the general population.10,39,43 The role of cytokine genes in asthma has been studied by using the candidate gene approach. On the other hand, at least 11 genome wide screenings have been reported for asthma and associated phenotypes.7

232

Cytokine Gene Polymorphisms in Multifactorial Conditions

16.4 MECHANISMS OF ATOPY The basic chain of events in immediate allergic reaction has been described as follows: Allergens are taken up by dendritic cells and presented to cells. In the absence of childhood microbial exposure, the balance between T helper 1 (TH1) and T helper 2 (TH2) cells is altered. TH2 cells encourage the production of IgE by B cells. Allergen-specific IgE then binds to the highaffinity receptor for IgE (FceRI) on mast cells. Allergen exposure induces cross-linking of receptor-bound IgE with subsequent mast cell degranulation and the release of pro-inflammatory molecules.7

However, TH2 driven reactions do not sufficiently explain the whole spectrum of atopy and asthma. Many patients with atopic disorders have no allergen specific IgE and their total serum IgE is within normal limits. The recent identification of four new genes affecting asthma susceptibility has shed some light on this picture.44–47 All four genes code for proteins which seem to have their role in other than acquired immunity. Although their functions are still largely unknown, it seems that they all play a part in the maintenance of the epithelial barrier or that they may be involved in the first lines of response when this barrier is breached.7 The first cell type encountering an invading microbe or allergen is the antigen presenting cell (including cells of monocyte/macrophage lineage and dendritic cells). This contact induces an inflammatory response mediated by pro-inflammatory cytokines (e.g., interleukins (IL)-1, -6, -12, -18, and tumor necrosis factor (TNF)) and subsequently controlled by the negative feedback mechanisms of the anti-inflammatory cytokines (e.g., IL-1 receptor antagonist (IL-1Ra), transforming growth factor b (TGF-b), and IL-l0). TH1 – TH2: The balance between the two T helper cell subsets, TH1 and TH2, has a crucial role in the pathogenesis of the IgE mediated atopic diseases. In atopic individuals the TH2 activity (i.e., production of the TH2 cytokines such as IL-4, IL-5, IL-13) is clearly increased.48 The most important inducers of the production of IgE are IL-4 and IL-13. In contrast, in healthy non-atopic individuals IL-12 from the antigen presenting cells generates and maintains the TH1 mediated response. IFN-g produced by activated TH1 cells together IL-18 from macrophages suppresses IgE production. There is evidence that both genetic and environmental factors have an influence on the differentiation of the TH subsets and it is also likely that this differentiation starts in early childhood. Contacts with microbial antigens during childhood direct TH cells in the TH1 direction, and, conversely, in their absence TH cells differentiate more to TH2 cells (the hygiene hypothesis).49 This immune deviation theory has been widely accepted but there also seem to be other factors involved. Absence of adequate microbial exposure in infancy leads to reduced activity of regulatory T cells instead of mere TH2 deviation.50 These hypotheses may explain the increase of atopic diseases observed in developed countries in recent decades. However, the molecular and cellular mechanisms of the TH cell differentiation in vivo are still largely unknown. Exposure to dogs and cats in the first year of life reduced the risk of allergies later in life in a recent prospective study.51 We could observe the same effect in our cohort of asthmatics and atopics, but when this finding was correlated to the genotype of the inflammatory cytokines, it was observed that this effect was stronger in individuals with the IL1A þ 4845 G/G genotype.52 Thus, this would mean that the high atopy risk genotype is also associated with the protective effect of allergen priming in childhood. It could be hypothesized that the nature of the inflammatory response of these persons favors TH1 differentiation when a strong allergen is present, and in its absence their immune system develops markedly in the TH2 direction leading to a high risk of atopy. It should be noted, however, that there is so far no evidence that this regulatory pathway really leads

Asthma and Atopy

233

to a shift in he TH1/TH2 balance — the role of other regulatory T cell subsets remains to be established.

16.5 CYTOKINES IN ASTHMA AND ATOPY Cytokines are signalling proteins in cell–cell communication. They act on target cells to give the impulse for a wide array of cellular functions inc1uding activation, proliferation, chemotaxis, immunomodulation, release of other cytokines or mediators, growth and cell differentation, and apoptosis. Usually thay have an effect on adjacent cells and therefore function in paracrine fashion. Moreover, they often act at a distance (endocrine function) or have an effect on the cell of origin (autocrine function). It is important to understand that individual cytokines are always parts of a complex network. Each cytokine has many overlapping functions, each function being potentially mediated by more than one cytokine. The existing knowledge of cytokines and their interactions is based on simplistic models. In future, the major challenge will be to understand biology at the system level. Recent progress in molecular biology and the computational sciences has made possible a new multidisciplinary field of research called systems biology.53 However, for the time being all new data on cytokines must be placed in the context of a network whose functioning is not yet fully understood. It has now been demonstrated that most of the cytokine genes are polymorphic.54 The pathologies of atopic diseases are influenced by the profiles of cytokine production. Interindividual differences in cytokine profiles appear to be due, at least in part, to allelic polymorphism within regulatory or coding regions of cytokine gene. Table 16.1 summarizes repeated findings on cytokine gene polymorphism in asthma and atopy. The total number of studies on this subject is much higher and new studies are published monthly. The discrepancies seen between different association studies vary and may be related to differences in allele and haplotype frequencies between different study populations, Type I errors, and differences in phenotyping. There is also clear publication bias in favor of reporting positive association results.9 It is now evident that asthma and atopy are caused by multiple interacting genes. This is a challenge to researchers since the individual genes each have their own ways of affecting the net outcome and many of them may be dependent on environmental influences. The first attempts to tackle this problem are haplotyping and gene–gene interaction studies. The published studies in this field are summarized in Table 16.2. Here we describe the role and function of some key cytokines in which polymorphisms occur that have been shown to be associated with asthma and atopy related traits (Table 16.1). Interleukin-l (IL-l) represents a group of proteins that are closely involved in the enhancement of inflammation and host defense. The three best known proteins within this group of proteins are IL-1a, IL-1b, and IL-1 receptor antagonist (IL-1ra), this latter being an antagonist which has no agonist activity compared with the first two family members.55 The balance between agonists and antagonists in the IL-l system is likely to have profound effects on the pathogenesis of inflammatory diseases.56 The IL-1 cluster is described in detail in Chapter 7. IL-4 promotes immunoglobulin synthesis by B cells and plays a central role in immunoglobulin class switching of activated B lymphocytes to the synthesis of IgG4 and IgE. IL-4 promotes the development of TH2 cells and inhibits the development of TH1 cells.57 Moreover, IL-4 increases expression of MCH class II molecules and adhesion molecules as VCAM-1, affects cytokine release (e.g., TNF, IL-1, IL-8, IL-12, INF-g) and macrophage colony formation. IL-4 is a key cytokine in allergic inflammation since in IL-4 knock-out

IL4RA Ile50Val

Repeat in intron 2 CA repeat in intron 2 Two-locus haplotypes (IL4RP2del/IL4 þ 33 C4T/ IL4
598 C4T/SNP1–4) Haplotype (12 SNPs)


33 C4T (
34)

Yes No Yes – – –

–

–

– – –

– Yes – – No Yes – No – – –

Yes – Yes

IL1RN VNTR VNTR Haplotype (six tagging SNPs)

– –

– –

BHR

Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes

Yes –

IL1B
511 C4T
511 C4T

IL4
590 C4T (
589)

– –

Asthma

IL1A þ4845 G4T þ4845 G4T

Cytokine Gene Polymorphism

Yes Yes Yes

–

– – No – – – – – – – –

No – –

– –

Yes –

SPT and/or Specific IgE

Yes Yes Yes

Yes

No No – Yes Yes No Yes Yes – No –

No – –

– –

– –

Total IgE

– – –

–

– – Yes – – – – – – – –

No Yes –

– Yes

– Yes

Rhinitis

480 890 480

478

521 1544 908 1120 478 1544 1120 478 305 299 476

500 450 744

650 450

650 450

Study Population (Persons)

TABLE 16.1 An Overview of Repeated Findings on Cytokine Gene Polymorphisms and Asthma or Atopy

6.30 (3.66–10.45)*,** – 6.30 (3.36–10.45)*,**

–

– – 2.5 (1.2–5.2) – – – – – – – –

5.71 (1.63–19.8) 2.7 (1.2–6.0) –

2.70 (1.40–5.19)y 2.9 (1.5–5.4)

0.58 (0.38–0.88)y 2.8 (1.5–5.1)

OR (95% CI)

Japanese Japanese Japanese

White

Japanese children Caucasian families White children German children White Caucasian families German children White Tunisian children Northern Indian Japanese families

Japanese adults Finnish adults German, Swedish and Italian families

Finnish adults Finnish adults

Finnish adults Finnish adults

Material

81 82 83

77

73 74 75 76 77 74 76 77 78 79 80

71 69 72

70 69

68 69

Ref.

234 Cytokine Gene Polymorphisms in Multifactorial Conditions

Arg130Gln (þ2044)

Arg110Gln

IL13
1111 C4T (
1112,
1024,
1055)

–

–

– –

IL12B Promoter microinsertion Promoter microinsertion Haplotype (4237/6402)

– – – –

No No

Yes No Yes

IL10
571 C4A
571 C4A
1082 G4A/
819 C4T/
592 C4A
1082 G4A/
819 C4T/
592 C4A

– Yes – – – –

– No Yes No

Val75Arg576 148 A4G/1432 T4C/1652 A4G Haplotype (6 SNPs) Haplotype (6 SNPs) Haplotype (12 SNPs)

Ser478Pro

Cys406Arg

Gln576Arg

– No – – – – – No – Yes – – – – –

Yes Yes – Yes Yes –

– No – Yes – – No No – Yes Yes No – Yes Yes

Glu375Ala

– Yes

– Yes Yes No No –

No No –

– – – –

No No Yes – – No – No No Yes – No No – –

Yes –

– No – No No Yes

– Yes –

Yes Yes – Yes

Yes Yes – – Yes Yes Yes Yes Yes Yes – Yes Yes – Yes

– No

– – – – – –

–

–

– No – –

– – – – – – – – – – – No – – –

682 908

208 368 342 890 591 1399

844 484 2366

144 144 436 650

158 401 60 265 1544 158 682 401 158 401 265 1120 158 694 682

– –

– – 2.14 2.31 (1.33–4.00) – –

4.6 (2.1–11.2) – –

– – –

– – – – – – – – – – – 1.60 (1.08–2.37) – – –

88 75

98 99 100 82 101 102

95 96 97

91 92 93 94

84 85 86 87 74 84 88 85 84 85 87 89 84 90 88

(Continued )

Dutch Dutch, Caucasian Scandinavian, Caucasian Japanese and British adults German children American and German children Finnish families White children

Australian children Australian White

Families American families White adults Finnish adults

German adults Dutch families American American adults Caucasian families German adults Finnish families Dutch families German adults Dutch families American adults German children German adults Hutterite families Finnish families

Asthma and Atopy 235

No Yes Yes

Yes Yes No

Yes Yes Yes Yes

– – –

– – No

–

– –

– –

–

– Yes Yes

–

–

BHR

–

Yes

Asthma

– – –

– – Yes

No

– –

– –

Yes

Yes

Yes

SPT and/or Specific IgE

Yes – No

No – Yes

No – No No

No Yes

–

Yes

–

Total IgE

No – –

– – –

–

– -

– –

No

Yes

–

Rhinitis

144 335 697

413 124 600

413 124 721 476

376 193

644

105

591

Study Population (Persons)

BHR ¼ bronchial hyperresponsiveness, SPT ¼ skin prick test. Criterion for positive association ¼ P 5 0.05. *Asthma. **Children. ***Female. yMale. yyIgE.

TGFB
509 C4T

TNFB LTANcoI


1031 C4T/
863 C4A/
857 C4T

TNFA
308 G4A

IFNG CA–repeat (intron 1)

IL18
137 G4C

IL15 Haplotype (5 SNPs)

Cytokine Gene Polymorphism

TABLE 16.1 Continued

– – 2.98 (1.45–6.25)

– 4.89 (1.30–18.35)* 2.24 (1.29–3.90)***

– 5.23 (1.69–16.20)* 0.37 (0.21–0.64) –

– –

–

3.65 (1.54–8.63)yy

–

OR (95% CI)

American families Caucasian adults White adults

Australian families Australian children Italian families

Australian families Australian children Korean adults Japanese families

Japanese children Indian

German children and young adults German adults

German

Material

92 113 114

108 109 112

108 109 110 111

106 107

105

104

103

Ref.

236 Cytokine Gene Polymorphisms in Multifactorial Conditions

237

Asthma and Atopy

TABLE 16.2 Gene–Gene Effects of Cytokines Cytokine Gene Polymorphisms IL1A 4845 G4T IL4RA 22446 T4C IL1A 4845 G4T IL1B þ3945 C4T IL1RN VNTR IL1A 4845 G4T IL1B
511 C4T IL1RN VNTR IL4 RP2 del IL13 þ 2044 G4A IL4 þ 33 C4T IL13 þ 2044 G4A IL4
590 C4T IL4RA Arg 551Gln IL4
590 C4T IL13
1512 A4C IL4
590 C4T IL13 þ 2044 G4A IL4RA Ser478Pro IL13 –1111 C4T IL10
571 C4A TGFb
509 C4T IL13 Arg130Gln IL4
589 C4T IL13
1055 C4T IL13 Arg130Gln TNFa
308 G4A LTa-NcoI 1 4 2 TNFa
308 G4A LTa-NcoI 1 4 2 TNFa
308 G4A LTa
NcoI 1 4 2 TNFa
308 G4A LTa-NcoI 1 4 2 TNFb 252 A4G, 318 G4C TNFa
1031 T4C,
863 C4A,
857 C4T,
308 G4A,
238 G4A

Asthma SPT and/or Total Rhinitis Specific IgE IgE

Study Population

Number

OR (95% CI)

Ref.

115

No

Yes

–

–

Finnish adults

650

2.32 (1.47–3.67)

–

Yes

–

–

Finnish adults

405

4.07 (1.720–9.630) 116

–

–

–

Yes

Finnish adults

405

3.04 (1.53–6.03)

69

Yes

–

–

–

Japanese families

476

–

80

Yes

–

–

–

Japanese families

476

–

80

Yes

–

–

–

Korean children

356

3.70 (1.07–12.78)

Yes

–

–

–

Japanese families

476

–

80

Yes

–

–

–

Japanese families

476

–

80

Yes

–

Yes

–

Dutch families

401

4.87*

85

–

–

Yes

–

American families

144

–

92

No

Yes

–

No

908

–

75

–

–

Yes

–

White, Asian, and other children German children

1314

–

118

Yes

–

No

–

Australian families

413

–

108

Yes

–

–

–

Australian children

124

–

109

No

Yes

Yes

–

Italian families

600

–

112

Yes

No

No

–

Taiwanese children

329

2.59 (1.10–6.10)

119

–

–

Yes

–

Korean adults

721

–

110

117

BHR ¼ bronchial hyper-responsiveness, SPT ¼ skin prick test. Criterion for positive association ¼ P 5 0.05. *Asthma.

mice sensitization and development of bronchial hyper-responsiveness do not occur in experimental models.58 Similar results have been found by blocking IL-4 receptors. Gene coding for IL-4 (together with IL5, IL9, and IL3) is located in cytokine gene cluster in chromosome 5q31 as described in Chapter 9. IL-10 is a pleiotropic cytokine with a broad spectrum of immunosuppressive and antiinflammatory effects. Atopic individuals have lower levels of IL-10 and in the skin test the wheal-size is negatively correlated with the amount of allergen-stimulated IL-10.59,60 In addition to this, treatment of atopic children with probiotic bacteria, which is known to alleviate atopic symptoms, elevates blood IL-l0 levels.61

238

Cytokine Gene Polymorphisms in Multifactorial Conditions

IL-12 is a key cytokine in initiating and driving TH1-mediated immune responses as well as innate immunity. It may play an important role in inhibiting inappropriate IgE synthesis and allergic inflammation. The production of IL-12 and IL-12 induced INF-g release is reduced in whole blood cultures from patients with allergic asthma compared with normal subjects.62 IL-13 shares many of its functions with IL-4. This is a potent modulator of human monocyte and B cell function. There is an increased expression of IL-13 mRNA in the airway mucosa of asthmatics and a significant correlation has been found between the levels of IL-13 and eosinophil counts.63 IL-15 stimulates proliferation of T cells and lymphokine activated NK cells. When it is produced at the site of allergic inflammation may participate in recruiting and activating eosinophils by inducing IL-5 production from T cells.64 IL-18 is an important regulator of the innate and the acquired immune system.65 It has been regarded as a pro-inflammatory cytokine because of its potent interferongamma-inducing activity. Human IL-18 is an inflammatory cytokine that plays a role in atopic diseases, such as atopic eczema (AE), by enhancing IL-4 and IL-13 production and stimulating the synthesis of IgE. IFN-g is produced only by T cells and NK cells. It has extensive and diverse immunoregulatory effects on various cells. The production of IFN-g is reduced in T cells in asthmatic patients and this correlates with disease severity.66 TNF-a is a pro-inflammatory cytokine that has been implicated in the modulation of inflammation in various diseases, including asthma. It is one of the cytokines which up-regulate adhesion molecules and also increase the affinity of adhesion molecules both on eosinophils and endothelial cells. Moreover, TNF-a acts as an eosinophil chemotactic factor, attracting the cells to the inflammatory focus in the tissue.64 TGF-b is known to mediate pleiotropic functions both inside and outside the immune system. Recent progress in this field underlines the role of TGF-beta in regulatory T cells, where it participates in both suppression and differentiation. In addition, recent information highlights the role of TGF-beta in repair responses that lead to matrix deposition and tissue remodeling.67

16.6 CONCLUSION So far, the most plausible results have been seen in studies concerning genes coding for IL-1 family, IL-4 and its receptor, IL-10, and IL-13. However, new results are published monthly and we must be ready to change our views. Studying functionally relevant cytokine gene polymorphisms has offered a new possibility to study the role of these cytokines in humans. In the future, studying gene–gene and gene–environment interactions will give us better possibility to understand the mechanisms behind these complex diseases.

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17

Common Rheumatic Diseases Rachael Kilding and Anthony G. Wilson

CONTENTS 17.1 17.2

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rheumatoid Arthritis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.2.1 Tumor Necrosis Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.2.2 Interleukin-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.2.3 Interleukin-6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.2.4 Interleukin-10. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3 Spondylo-Arthropathies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3.1 Tumor Necrosis Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3.2 Interleukin-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3.3 Interleukin-6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3.4 Interleukin-10. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.4 Osteoarthritis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.5 Cytokine Pharmacogenetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.5.1 Tumor Necrosis Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.5.2 Interleukin-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

245 246 246 247 248 248 249 249 250 250 250 250 251 251 252 252 252

17.1 INTRODUCTION The autoimmune rheumatic diseases include rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and Sjogrens’ syndrome. The aetiology of these diseases is multifactorial but each has a significant genetic component and, in common with other autoimmune diseases, a significant proportion arises from the major histocompatibility complex (MHC) at 6p21.3. Rheumatoid arthritis for example has a genetic contribution of 30–50% with around one-third arising from the MHC. Most studies have implicated a group of alleles encoding a similar amino acid sequence in the peptide binding groove of DRB1 termed the shared epitope (SE). Furthermore, severity is associated with SE genotypes with DRB1*0401 homozygosity increasing the risk of developing aggressive, systemic disease. The overall genetic contribution to SLE is stronger than that for RA (s 20 and 8, respectively) and includes a complex MHC contribution involving the complement cluster, DRB1 and the telomeric class III region. Recently progress has been made in mapping non-MHC susceptibility genes with a non-synonomous SNP in the gene encoding a protein tyrosine phosphatase (PTPN22) protein tyrosine phosphatase being implicated in susceptibility to both SLE and RA.1,2

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17.2 RHEUMATOID ARTHRITIS (TABLE 17.1) Rheumatoid arthritis is a heterogeneous complex inflammatory disorder with a prevalence of approximately 1%. It primarily affects synovial joints but is a systemic disease frequently manifesting extra-articular features. The characteristic pathology in RA is increased thickness of the synovial lining layer containing macrophages and fibroblast-like synoviocytes, while the sub-lining infiltration is composed of inflammatory cells including T and B cells and macrophages, blood vessels and fibroblasts. A complex interplay of inflammatory mediators including cytokines and chemokines have been implicated in the development and maintenance of the chronic inflammation and tissue destruction typical of RA.

17.2.1 TUMOR NECROSIS FACTOR This cytokine has been identified as a pivotal mediator of chronic inflammatory joint disease in RA. It is produced mainly by monocytes and macrophages but also by T and B cells and fibroblasts. The TNF gene (TNFA) is situated
900 kb telomeric of HLA-DRB1 in the telomeric class III region of the MHC. It is a small gene, 3 kb in length encoding four exons. Several polymorphisms have been described within the region containing TNFA including five microsatellite markers and a large number of promoter SNPs. The 308G/A polymorphism has been most intensively studied.3 Carriage of TNF308A has been

TABLE 17.1 Cytokine Genetics in RA Reference DRB1 Independent TNF Region Association 16 17 18 19 20 IL1 25 26 27 IL6 31

Comments

Telomeric class III association (Japan) Telomeric class III association (Dutch) Telomeric class III association (British) Association with 497 Kb region including TNF on 8.1 haplotype (U.S.) British DRB1*04 case control study showing DRB1 independent genetic effect detected at TNF locus Association of IL1B marker with erosive RA European family study revealing linkage of IL1 locus and interaction with DRB1 British family study reporting linkage with erosive RA only in SEve families

35 36

British case control study describing association of 174G with s-JIA TDT study describes association of 174G with s-JIA No evidence of IL6 (622 or 174) alleles with RA

IL10 46 47 26 44

Genetic associations with RA in three U.K./U.S. populations Association with IgA RF levels and RA severity Interaction with DRB1 in predisposing to severe disease Haplotype association with oligoarticular JIA

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associated with increased susceptibility to or worse outcome from a range of diseases including septic shock,4 cerebral malaria,5 and mucocutaneous leishmaniasis.6 Correlations of alleles of TNF promoter SNPs with gene expression have been reported and add to the attractiveness of this cytokine as a susceptibility gene for RA.3,7 Two major problems arise in studies of MHC genetics: the strong linkage disquilibrium that exists across this region and the high gene density, particularly in the central class III region containing TNF. The early studies typed DRB1 and one or more TNF locus markers and were able to examine if any associations of the latter regions were primary or simply the result of LD with shared SE. However, they were not able to determine the exact location of the effect detected at TNF because of the small number of markers typed. More recently, studies have included larger sets of markers in the telomeric class III region. These involved case-control studies on different ethnic groups and described DRB1-independent associations with both disease susceptibility8–12 and with severity of radiological damage.13 These findings were supported by several small family-based studies.14,15 More recently larger more powerful studies have been published. A Japanese group typed five TNF promoter SNPs and 18 microsatellites spanning the MHC in 248 controls and 120 patients and found evidence of an additional genetic effect in the telomeric class III region close to TNF.16 A Dutch group examined similar numbers and typed six microsatellites around the junction of the class III and I regions and reported evidence of a DRB1independent genetic effect derived from the A1-B8-DR3 (8.1) haplotype.17 Two large familybased studies have most clearly demonstrated that the MHC association with RA is polygenic. A study of 164 British RA families found over-transmission of several SNPs in the telomeric class III region after conditioning on the SE.18 A study of U.S. RA families reported two non-DRB1 effects, one in the central MHC within a 497 kb region on a segment of the 8.1 ancestral haplotype and another in a 697 kb interval in the class I region on a subset of DRB1*0404 haplotypes.19 A large case-control study examined TNF locus haplotypes in DRB1*0401 and *0404 matched cases and controls and detected significant differences.20 The telomeric class III region is particularly gene dense and there are a large number of genes with putative roles on the immune or inflammatory reactions. Other than TNF, a gene of particular interest encodes a putative member of the IkB family of proteins. The similarity is based on the presence of two ankyrin repeat sequences in the IkB-like (IkBL) gene although members of the IkB family generally have six repeats. A case-control study from Japan reported the association of the IkBL-62 marker with RA, speculating that this polymorphism may alter a motif for the transcriptional repressor dEF1.21 However DRB1 genotypes were not determined and so the association could be the result of LD with SE alleles. Indeed, subsequent studies have not replicated this finding.18

17.2.2 INTERLEUKIN-1 The potent pro-inflammatory cytokine IL-1 undoubtedly plays a central role in RA, in particular in inducing cartilage damage and bone erosion. The IL-1 system comprises two agonists, IL-1a and b and the IL-1 receptor antagonist (IL-1ra). The three genes lie on the long arm of chromosome 2 within a 430 kb interval.22 Similar to TNF, IL-1 is primarily produced by stimulated monocytes, macrophages, and some specialized synovial cells.23 The IL-1 locus has been genetically associated with susceptibility to or outcome from a wide range of infectious and inflammatory neoplastic diseases, including chronic inflammatory diseases such as ulcerative colitis, meningococcal disease and tuberculosis, and gastric cancer.24 Most of the reported studies in RA have typed one or a combination of four SNPs in the cluster, IL1B (511 and þ3954), IL1A (þ4845), IL1RN (þ2018), or an intronic VNTR in IL1RN. A prospective cohort study of 108 Caucasian RA patients and 128 Caucasian

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Cytokine Gene Polymorphisms in Multifactorial Conditions

controls did not find evidence of association with the IL1 locus. However, a combination of DRB1 SE and IL1 alleles were associated with poorer prognosis suggesting an epistatic interaction.25 Similar results were reported in a family-based association study of 90 European RA families comprising 107 sibling pairs.26 However, a study of 195 British multiplex RA families that were typed at HLA-DRB1 and five microsatellite markers and four SNPs in the IL1 cluster detected evidence for linkage of the IL1 cluster with erosive x-ray damage but only in SE negative families.27 There studies suggest that the IL1 cluster contributes to RA via an epistatic mechanism with DRB1 alleles, although the exact nature of this interaction is at present unclear.

17.2.3 INTERLEUKIN-6 The IL6 gene is 5 kb in length, contains five exons and is located at 7p15.3. In RA, IL-6 has been implicated in T-cell and osteoclast activation, autoantibody production, and release of inflammatory mediators.28 IL-6 is produced by lymphocytes, monocytes, fibroblasts, synoviocytes and endothelial cells and has both pro-inflammatory and anti-inflammatory properties in vivo.29,30 A large number of SNPs have been identified in this locus although most studies have examined the 174G/C marker as it has been shown to have effects on gene expression.31 Serum IL-6 levels correlate with acute phase biomarkers including erythrocyte sedimentation rate and platelet count.32 Patients with systemic onset juvenile idiopathic arthritis (s-JIA) show elevated serum and synovial levels of IL-6 with fluctuations paralleling the typical fever pattern.33,34 Interestingly the 174G allele has been associated with the development of s-JIA in both a large case control31 and a family-based association study.35 These results are biologically plausible in view of reporter gene experiments showing the 174C allele to be a weaker transcriptional activator than the common allele.35 There is no evidence however implicating this polymorphism in the pathogenesis of rheumatoid arthritis.36 Further studies involving a more comprehensive IL6 haplotype analysis are required to confidently exclude an effect from this locus.

17.2.4 INTERLEUKIN-10 The IL10 gene is 5 kb in length, encodes five exons and is located at 1q31-32. It is a Th2 cyotokine secreted mainly by monocytes, macrophages, and lymphocytes and inhibits synthesis of pro-inflammatory cytokines including TNF, IL-1, and IL-6. It is also involved in activation of B-cells and autoantibody production.37 Lower levels of IL-10 mRNA in synovial tissue have been correlated with erosive disease, supporting a role for IL-10 production in modulating joint damage.38 Studies of twins and families have shown that approximately 75% of the population variation in IL-10 production is genetically determined.39 The IL10 locus is highly polymorphic, the 50 flanking region contains at least two microsatellites between 4000 and 1100 (IL-10.G and IL-10.R) and three SNPs lying within transcription factor-binding sites or regulatory regions: 1087 G/A, 824 C/T, and 597 C/A.40–42 The SNPs are in strong linkage disequilibrium resulting in three predominant haplotypes: GCC, ACC, and ATA.43 Variation in LPS induced IL-10 secretion has been shown to correlate with both individual SNPs44 and promoter haplotypes.45 Under-representation of low IL-10 associated genotypes have been reported in RA.46 Low IL-10 producer haplotypes have also been associated with higher levels of IgA rheumatoid factors and more severe RA.47 A linkage study involving 107 European RA sibling pairs reported evidence of an interaction between IL10 and the MHC, particularly in families with more erosive disease.26 Association of SNP haplotypes has also been described

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in s-JIA.44 In summary there is substantial evidence implicating low production alleles of IL10, particularly with severity of RA.

17.3 SPONDYLO-ARTHROPATHIES (TABLE 17.2) The seronegative spondylo-arthropathies are a group of disorders characterized by chronic inflammation primarily involving the enthesis, the insertion of tendon into bone, although synovitis is also a common manifestation. The group consists of several related diseases: ankylosing spondylitis, reactive arthritis, arthritis associated with inflammatory bowel disease, some forms of psoriatic arthritis, and undifferentiated forms. Classically there is inflammation of the axial skeleton with sacro-iliitis and spondylitis, peripheral large joint asymmetrical arthropathy, and ensethitis. In addition extra-articular involvement including ocular, cardiovascular, pulmonary, and gastrointestinal systems may occur. The importance of genetic factors is supported by familial clustering and twin studies which have suggested heritability to be 490% for the disease prototype, ankylosing spondylitis.48 The major susceptibility gene is HLA-B2749 which accounts for between 16 and 50% of the total genetic contribution; although present in 495% of AS patients, less than 5% of B27 carriers develop AS suggesting that other genes are involved.50

17.3.1 TUMOR NECROSIS FACTOR Serum levels of TNF in AS are significantly higher than those in patients with noninflammatory back pain51 and TNF mRNA is highly expressed at sites of new bone formation in AS sacro-iliac joint biopsies.52 The dramatic clinical response of AS to inhibitors of TNF further suggests a key role of this cytokine.53 The proximity of the TNF and HLA-B loci complicates genetic studies of the TNF locus. To overcome this problem several groups have performed case-control studies using B27þve or ve populations. The first large study examined a Southern German population

TABLE 17.2 Cytokine Genetics in Ankylosing Spondylitis Reference HLA-B27 Independent TNF Associations 54

Comments

56

Protective effect of TNF –238 and 308 alleles in B27þve patients (Germany) Protective effect of –308 but not –238 alleles in B27þve patients (Scotland) No evidence significant TNF effect (Spanish)

IL1 61 62 63 64

Linkage detected in two large family sets Association detected in TDT study Case control association of IL1RN Case control association of IL1RN

IL6 66

No association in small Spanish case control study

IL10 67

No association in large Finnish family study

55

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Cytokine Gene Polymorphisms in Multifactorial Conditions

and revealed a protective effect of TNF-238A and TNF-308A carriage in B27þve individuals only.54 Subsequently, the finding for 308A was replicated in a separate Southern German cohort55 and a Scottish study but was not replicated in several other populations.56 A Spanish study reported association of TNF-238A with AS in B27 negative patients only.57 Psoriasis is common skin condition affecting around 3% of Britons. Inflammatory arthritis occurs in up to 20% of patients with psoriasis and can take several forms including an asymmetric oligo-arthritis, a sero-negative RA-like form or an AS-like spondyloarthropathy. To date several studies have examined the role of the MHC in psoriatic arthritis and as with many other studies of this region have not conclusively implicated the TNF locus as an independent susceptibility factor.58–60 Larger more detailed genetic studies in the different forms of psoriatic arthritis are required.

17.3.2 INTERLEUKIN-1 Convincing evidence of a role of the IL1 locus in AS has emerged in both family-based and case-control studies. A whole genome scan of two large family sets revealed linkage of this region with AS.61 A subsequent family-based study confirmed association and overtransmission of IL1 cluster SNPs and haplotypes in AS.62 Two large case-control association studies have both confirmed IL1 locus association with AS and found evidence that the effect arises from polymorphism wihin the IL1RN gene.63,64 To date two studies have examined IL1 genetics in psoriatic arthritis; an association with the IL1A-889C allele was reported.65 However, another study did not find association with the IL1Bþ3953 SNP.60

17.3.3 INTERLEUKIN-6 Few studies have examined the role of the IL6 locus in the genetic background of the spondylo-arthropathies. A relatively small Spanish study did not find association of the 174 marker with AS66 and a relatively large Irish study did not find association of this marker with psoriatic arthritis.60 However, to confidently exclude a contribution from this locus will require more powerful studies.

17.3.4 INTERLEUKIN-10 A study of 182 Finnish AS families typed two microsatellites and three SNPs in the IL10 promoter and reported a relatively weak association with age at onset and disease severity suggesting a minor role in these manifestations.67 Reactive arthritis is a related condition which is precipitated by an infective episode most frequently gastrointestinal or urinary. A Finnish study reported a significant decrease in frequency of several alleles of an IL10 promoter microsatellite suggesting a strong protective effect against the development of reactive arthritis.68 A study of psoriatic arthritis did not detect association of IL10 promoter SNPs with clinical parameters such as age at onset, pattern of arthritis or progression of joint damage.60

17.4 OSTEOARTHRITIS (TABLE 17.3) Osteoarthritis (OA) is the commonest joint disease and is characterized by cartilage loss and periarticular bony sclerosis. It most commonly affects the finger joints, the neck and lumbar spine, hips and knees, although any joint can be involved. The aetiology is multifactorial with a complex mix of genetic and environmental factors contributing at

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TABLE 17.3 Cytokine Genetics in Osteoarthritis Reference

Comments

IL-1 69 70 71 72

Genomic scan Finnish study (27 families) describing linkage to region containing the IL1 cluster Large case control study showing association of IL1RN with knee but not hip disease Small U.S. case control study describing association of erosive hand disease with IL1B alleles Large Dutch study revealing association with hip disease.

different joints, for example knee joint OA is strongly correlated with body mass index, particularly in females, but hip OA is not. There is a very strong genetic component to hand OA but occupation can also have a significant impact on risk. There is accumulating evidence of an important genetic contribution of the IL1 locus in OA. A Finnish study performed a genome scan of families with OA of the distal interphalangeal joints of the fingers and reported independent linkages with the IL1 and IL1R loci on 2q.69 A large study compared eight IL1 locus marker genotypes between in 557 OA cases and 557 age matched controls and found an association with knee but not hip OA; this was supported by an affected sibling pair analysis that found linkage of the cluster with knee but not hip OA;70 Other studies have also confirmed IL1 locus associations with OA in different joint groups.71,72

17.5 CYTOKINE PHARMACOGENETICS (TABLE 17.4) The advent of cytokine-based treatments has significantly improved the treatment of patients with aggressive inflammatory joint diseases unresponsive to conventional treatments such as weekly methotrexate (MTX). The more widespread use of these agents has been limited by the much higher yearly cost of treatment (MTX £220 v anti-TNF £8000). Although most patients have a significant clinical benefit from these new treatments a significant proportion (30–35%) of patients continue to have active disease although recent evidence suggests that this group may still be protected from ongoing joint damage.73 In view of the high cost and increasing number of cytokine inhibitors available there is a particular need to use these medications as effectively as possible. One possible method is to use genetic markers in cytokine genes as biomarkers for response and there is some evidence supporting this strategy in the treatment of Crohn’s disease74 and hepatitis C.75

17.5.1 TUMOR NECROSIS FACTOR Three inhibitors of this cytokine are currently widely used: Infliximab (chimeric murinehuman anti-TNF monoclonal antibody), Etanercept (soluble TNFRII:Fc fusion protein), and Adalimumab (fully human anti-TNF antibody). After 6 months of treatment all have been shown to be effective at reducing disease activity and retarding radiological progression of RA.76–78 Two relatively small studies have examined the association in RA of TNF polymorphisms with response to Infliximab; a mini-haplotype composed of alleles of two microsatellites was increased in responders compared with non-responders after 3 months of treatment.79 Another study examined association of TNF-308 alleles with response after 22 weeks of treatment and reported a significantly higher frequency of G/G genotype in better responders.80 It is not clear if these studies detected the same effect as different markers were typed in these studies. Furthermore they were both relatively small (78 and 59 patients

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Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 17.4 Cytokine Pharmacogenetics in Rheumatic Disease Reference TNF 79 80 IL1 82

Comments

Association of TNF alleles with response to Infliximab treatment of RA Small association study revealing association of 308A allele with response to Infliximab treatment of RA Large study revealing strong association of IL1A (þ4845) with response to IL1 treatment of RA

respectively). Additional more powerful studies are therefore required to ascertain the usefulness of TNF genetics in predicting response to each of the three inhibitors.

17.5.2 INTERLEUKIN-1 A recombinant IL-1ra molecule is licensed for the treatment of RA although it is much less widely used than any of the three TNF inhibitors.81 A remarkably strong association to response with 150 mg/day of IL-1ra was detected in patients carrying the rare allele at IL1Aþ4845 with an odds ratio for response of 4.85.82 The numbers studied were relatively large and it will be important to examine the utility of this marker in predicting response when additional and more effective inhibitors of IL-1 become available.

17.6 CONCLUSIONS There is a large body of evidence implicating cytokine genetics in the pathogenesis of a range of inflammatory and noninflammatory joint diseases. Further studies are required to confirm some of these associations and to characterize these genetic effects. The use of cytokine pharmacogenetics is particularly exciting in view of the economic importance of individualizing these treatments based on genetic prediction of likelihood of response.

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18

Systemic Lupus Erythematosus Sandra D’Alfonso

CONTENTS 18.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.2 Polymorphisms in Cytokine and Cytokine Receptor Genes . . . . . . . . . . . . . . . . . . . . 18.3 Association Studies with Polymorphisms in the TNF Genes . . . . . . . . . . . . . . . . . . . . 18.4 Association Studies with IL10 Polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.5 Future Directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

257 258 268 269 271 271

18.1 INTRODUCTION Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by autoantibody production and immune complex formation whose deposition causes chronic inflammatory lesions in different organs.1,2 Mechanisms that contribute to the formation of auto-antibodies and immune complexes include loss of tolerance to nuclear antigens and other components of one’s own body, decreased clearance of immune complexes, and abnormal B- and T-cell activation.2 The disease is characterized by a combination of different clinical and immunological symptoms reported in Table 18.1. According to the 1997 Revised American College of Rheumatology (ACR) Criteria for Classification of SLE,3 an individual with any four of the different clinical and laboratory criteria reported in Table 18.1 is diagnosed as having SLE. Consequently, individuals affected with SLE have different disease phenotypes with clinical manifestations including mucocutaneous, renal, cardiovascular, gastrointestinal, hepatic, pleural, pulmonary, articular, splenic, lymph node, hematological, and central nervous system involvement. The pattern of SLE related autoantibodies is also very wide including mainly those relating to nuclear components, such as DNA, RNA, histones and non-histones proteins, and cell surface and subcellular molecules particularly of lymphohematopoietic cells. The SLE prevalence is about 1/2000 in Caucasoid populations with a female to male ratio of about 9:1.4 The disease is three-fold more frequent in African-Americans.4 Similar to many other autoimmune diseases, SLE is characterized by a multifactorial etiology and shows a complex pattern of inheritance that is consistent with the involvement of multiple susceptibility genes as well as environmental risk factors. A genetic component is suggested by classical epidemiological data: in first-degree relatives of SLE patients, the risk of SLE is about 20 times higher than in the general population. Concordance rates within pairs of monozygote twins range from 24 to 58% as compared with 3 to 10% for dizygote twins.4,5 Genes mapping in the major histocompatibility region (HLA) were extensively investigated for SLE association since 1971. Many studies have shown that SLE is associated with HLA-DR3 and DR2 class II alleles, particularly in Caucasoid individuals.6,7 In African Americans only the association with DR2 was reported.6,7 However, the risk conferred by 257

258

Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 18.1 Revised Criteria* of the American Rheumatism Association for the Classification of Systemic Lupus Erythematosus (SLE) 1. 2. 3. 4. 5. 6. 7. 8. 9.

Malar rash Discoid rash Photosensitivity Oral ulcers Arthritis Serositis: (a) pleuritis, or (b) pericarditis Renal disorder: (a) proteinuria 40.5 g/24 h or 3þ, persistently, or (b) cellular casts Neurological disorder: (a) seizures or (b) psychosis (having excluded other causes, e.g. drugs) Hematologic disorder: (a) hemolytic anaemia or (b) leucopenia of 54.0
109/1 on two or more occasions (c) lymphopenia of 51.5
109/1 on two or more occasions (d) thrombocytopenia 5100
109/110. 10. Immunologic disorders: (a) positive LE cell or (b) raised anti-native DNA antibody binding or (c) anti-Sm (Smith antigen) antibody or (d) false positive serologic test for syphilis, present for at least 6 months 11. Antinuclear antibody in raised titre *Hochberg, 1997 (3).

these alleles is relatively small (1.8–3.2) as compared with other autoimmune diseases. This can be due to a limited role of these alleles in the development of SLE and/or to a primary association with other genes in linkage disequilibrium with DR. Among these, genes encoding the complement components are particularly interesting based on the observation that defects leading to deficiency of complement components are often detected in SLE patients.8,9 In particular HLA-DR3 is part of the A1-B8-DR3 haplotype which carries the null allele C4AQ0 for the C4A complement component. Thus, the C4 gene is a strong candidate for the primary association in this haplotype. Several genome wide linkage studies identified different regions which likely harbor genes implicated in SLE susceptibility. Among these, 1q23, 1q41, 2q37, 4p16-13, 6p21 (HLA region), 11p13, 12q24 and 16q13 met the threshold of genome-wide significance.10,11 The identification of SLE susceptibility genes mapping in the linkage regions (positional candidate genes) as well as genes in other regions selected for their function (functional candidate genes) has been pursued by several groups in the last decade.10,11

18.2 POLYMORPHISMS IN CYTOKINE AND CYTOKINE RECEPTOR GENES Given the autoimmune nature of SLE, genes encoding cytokines and their receptors are particularly attractive functional candidates for several reasons: 1. The pattern of cytokine expression in SLE patients is different from healthy individuals.12 In particular an imbalance between Th1 and Th2 cytokine production is considered to play an important role in the development of SLE. In SLE, Th2 responses tend to predominate over Th1 responses, as shown by the increased production of IL-10 and IL-6 and decreased production of IL-2, IL-12, and IFNg.12–15 The IL-2 expression dysregulation was recently shown to be mediated by the increased expression of a cAMP response element modulator (CREM) consequential to the presence of anti-TCR/CD3 antibodies in SLE sera.16 CREM binds to the IL-2 gene promoter and represses its transcription.

Systemic Lupus Erythematosus

259

Ca2þ/calmodulin-dependent kinase IV (CaMKIV) was found to be increased in the nucleus of SLE T cells and to be involved in the over-expression of CREM and its binding to the IL-2 promoter.16 Decreased IL-2 production contributes to an increased rate of infections17 and decreased ability to generate a proper activationinduced cell death, allowing B cell-helping subsets to survive longer.18 2. The application of DNA microarray technology, allowing to test the expression profile of thousand of genes genome wide, has confirmed a dysregulation of inflammatory cytokines, chemokines and their receptors in the peripheral blood mononuclear cells from SLE patients as well as in the target organs (reviewed in Ref. 19). Interestingly, these studies also identified a dysregulated expression of groups of genes related to particular cytokine pathways. Among these, several IFN-inducible genes and genes belonging to the TNF and TNF receptor pathways are upregulated in SLE patients.19,20 3. In mice, transgenic overexpression of cytokines such as IL-4, IFNg, or gene targeting of cytokines such as IL-2 and its receptors (IL-2Ra and IL-2Rb) and TGFb1 lead to the development of an autoimmune condition resembling SLE (reviewed in Ref. 21). Altogether these data suggest that polymorphisms in genes coding for cytokines and their receptors that the influence the level of expression or the biological activity of these molecules22 may contribute to SLE susceptibility. About 80 papers have been published in journals cited by Medline on the genetic association of SLE with polymorphisms in genes encoding for cytokines (Table 18.2) and their receptors (Table 18.3). To date, a total of 27 genes have been studied. Published results (cited by Medline in June 2005) for each of these genes listed in order of chromosome number are summarized in Table 18.2 and Table 18.3. For each study the number of tested individuals, the population, and the strength of association (P value and OR) are indicated. The majority of these association studies were performed by the population-based casecontrol approach. For each gene biallelic markers (SNPs ¼ single nucleotide polymorphisms) localized in the coding and regulatory region or simple tandem repeat markers in the gene or in its vicinity were analyzed. The presence of an association would indicate either that the tested polymorphism itself contributes to disease susceptibility or that it is in linkage disequilibrium with the deleterious allele. The following general conclusions can be drawn from these studies. 1. A significant association with SLE was reported for polymorphisms in the OPN (Osteopontin), IL1A, IL4R, and IFNGR1 genes. For most of these genes the positive result was detected only in one study and has not been further tested, with the exception of OPN for which the association was confirmed in two independent studies. Interestingly the association with OPN concerns two regulatory polymorphisms at the 50 and 30 end of the gene, respectively. The effects of the two SNPs were independent of each other and the risk associated to a double dose of susceptibility alleles at both SNPs (O.R. 3.8, 95% CI 2.0–7.4) was higher than that conferred by each of them separately (Table 18.2).23 2. Apart from these promising results, in general association studies have met with only modest success in identifying disease-causing genes in SLE. Most studies failed to detect a significant difference in frequency distribution between patients and controls. In some cases a positive association with the disease was reported in a group of patients but it was not confirmed in an independent study. For example the IL1RN*2 allele of VNTR in the interleukin-1 receptor antagonist was originally found to be associated in a U.K. population.24 This result was

Location

1q31–q32

Function

Interleukin 10

Gene

IL10

8571C/T 8531G/A 7400del (GGA) 6752A/T 6208G/C 5402C/G 3533A/T 2726C/A 2739A/G 1349G/A 1082G/A 851G/A 657G/A

99/95

554/708

1082G T–C–A–T–A haplotype (ht1)

–2726A/A3

64/60

3575T/A 2849G/A 2726C/A 1130/G/A 1082A/G 819T/C 592A/C 1082A/G 1082A/G 3575T/A 2849G/A 2726C/A3 1082A/G 819T/C 592A/C 180/163

1087A

Associated allele

26/26

N1

1082A/G

Polymorphism

TABLE 18.2 Summary of Genetic Association Studies of Cytokine Polymorphisms with SLE

2.5 (1.2–5.4)

Ns 50.05 0.009

Ns

0.3 (0.1–0.9)

OR (95%CI)

0.025

P value

ht1 negative serositis (0.0001)

1087A cardiovascular disease (50.05)

Association with Disease Features2

Italian

Dutch Vietnamese Hong Kong Chinese

African American

Swedish

Population

51

78 79 55

57

52

Ref.

260 Cytokine Gene Polymorphisms in Multifactorial Conditions

IL10.G IL10.R IL10.G IL10.R

IL10.G IL10.G

217/173

IL10.G

158/220 56/102

IL10.G

554/708

0.003 (overall) 0.0001 (overall) 0.028 (overall) 0.025 (overall)

Ns

92/162

IL10.G IL10.R IL10.G

ns

Ns

120/147

1082A/G 819T/C 592A/C 1082A/G 819T/C 592A/C

A–T–A haplotype neuropsychiatric manifestations (0.02, OR ¼ 1.8)

G–C–C haplotype anti-Ro autoantibodies (0.005)

Ns

76/119

A–T–A haplotype nephritis (50.001)

1082A/G 819T/C 592A/C

50.05 Ns

627A

88/83

49/81

1082A/G 819T/C 592A/C

592C/A þ1553C/T (intron 3) þ2487C/T (intron 3) þ3895T/C (30 UTR) þ4230A/G (30 UTR) 657G/A

58

60 61

Hong Kong Chinese Mexican American U.K. Italian

(Continued )

59

54

81

53

56

80

Dutch

U.K.

U.K.

Kazakh (Russian) Chinese

Systemic Lupus Erythematosus 261

1q41

2q13

2q13

2q13

Transforming growth factor beta-2

Interleukin1beta

Interleukin-1 alpha

Interleukin-1 receptor antagonist

TGFB2

IL1B

IL1A

IL1Ra

Location

Function

Gene

TABLE 18.2 Continued

330/368

IL10.G

230/275

93/127 91/189

86bpVNTR 86bpVNTR 86bpVNTR

230/275

86bpVNTR

889C/T þ4845C/T

52/103

0.017 African American Ns

230/275

Promoter Exon 5

Ns

IL1RN*2

889CC genotype

Ns Ns 0.01

Ns

0.001 African American 0.005 Caucasoids

0.006

103/106

0.01

2.9

3.1

2.4

ns

ns 0.001 arthritis

Australian Korean Swedish

87 88 25

85

85

U.S.A.

U.S.A.

86

85

U.S.A.

Taiwan Chinese

84

83

82

63

62

Ref.

Japanese

Colombia

Spanish Turkish UK

German

Population

Ns

511C/T 31T/ þ3877A/ 511C/T þ3953C/T 511T

IL10.G14, IL10.G15 antiSm antibodies (50.05)

Association with disease features2

Mexican American

0.6 (0.3–0.9) 0.4(0.2–0.7)

OR (95%CI)

Ns

Ns

P value

114/392 þ3953T haplotype 511C/þ 3953T

Associated allele

511C/T þ3953C/T

4bp insertion in 50 UTR

210/158

N1

IL10.G IL10.R

Polymorphism

262 Cytokine Gene Polymorphisms in Multifactorial Conditions

4q13– q21

4q21– q25

5q31.1– q33.1 5q31

6p21.3

Interleukin-8

Osteopontin

Interleukin 12B

Interleukin-4

Tumor necrosis factor alpha

IL8

OPN

IL12B

IL4

TNF

52/103 89/88 143/200 196/218

86bpVNTR 86bpVNTR 86bpVNTR 86bpVNTR

308G/A 238G/A

100/430

50/100

590T/C

308A

559/603

30 UTR promoter 91/163

156G þ1239C

394/479

1748A/G 616G/T 443T/C 156G/GG 66T/G þ1083A/G (30 UTR) þ1239A/C (30 UTR)

590T/C intron3 VNTR

þ1239C

81/79

IL1RN*2

IL1RN*2

IL1RN*2

þ1239A/C

845T/C 738T/A 353A/T

81/261

86bpVNTR

0.0001

Ns

Ns

0.0060 0.00094

0.001

0.05 Ns Ns 50.05

0.032

2.3 (1.6–3.3)

2.3 (1.4–4.0) 1.6 (1.2–2.1)

1.6

2.63

1.5 (1.1–2.5)

4

Colombian

Japanese

95, 96

94

93

(Continued )

Taiwan Chinese

Discoid rash intron3 VNTR RP1 allele (0.029) 590T (0.04)

92

23

Italian

Spanish

91

90

U.S.A.

U.S.A.

26 61 89 27

24

Taiwan Chinese Italian Swedish Japanese

U.K.

Nephritis (ns)

þ1239C Renal insufficiency (0.043) 156G Lymphadenopathy (pc ¼ 0.046)

845C Severe nephritis in African American (50.05)

IL1RN*2 Photosensitivity (0.02)

ns

IL1RN*2 photosensitivity (0.006) Discoid skin lesions (0.005)

Systemic Lupus Erythematosus 263

LTA

Gene Location

6p21.3

Function

Lymphotoxin alpha (TNF beta)

TABLE 18.2 Continued

308A 238A 238AG

91/253 51/55

308G/A 238G/A 308A/G 238A/G 1031T/C 863A/C 857C/T 308G/A 238G/A 308A/G

NcoI first intron NcoI first intron

308A/G 308A/G 308A/G 308A/G 238A/G 308A/G 238A/G 308A/G 308A/G

308A

230/276

308G/A 238G/A

TNF2 TNF2/TNF2 genotype

97/281

308A

308A

308A

51/80

81/168

123/199

105/115 100/107 49/49

88/64 308A

308A

70/59

308G/A

91 trios

Associated allele

N1

Polymorphism

P 5 0.01

0.05

ns7 ns

ns Increased (ns) ns ns7 ns ns

0.0052

0.03 0.02 ns (TDT)

50.05

0.047

P value

1.98

1.704 TNF2/TNF2 Nephritis (0.035)9

ns

Northern Chinese Han Korean

U.K. Australian

African American Han Chinese Taiwan Chinese Taiwan Chinese U.K. and South Africa (white) Italian

4.4 (1.5–13.3)5

ns

Mexican Mestizo U.S.A.

2.7 (1.3–5.8)5 4.776 3.62

Malaysian Chinese

U.S.A. (Caucasoid and African American) Dutch

Neurologic involvement (0.004) anti-La antibodies (0.03)

2.2 (1.0–4.8)4

Population

1.3 (0.6–2.8)5 (only for Caucasoids)

Association with disease features2

OR (95%CI)

108

107

105 106

104

100 101 102 103

39

99

98

37,38

75

97

Ref.

264 Cytokine Gene Polymorphisms in Multifactorial Conditions

7p21

9p21

9p22

9p22

12q14

Interleukin-6

Interferon beta 1

Interferon alpha21

Interferon alpha6

Interferon gamma

IFNB1

IFNA21

IFNA6

IFNG

IL6

ns

ns

589/37711

2093G/A 91/136

ns

(CA)n intron1

ns

A488A 589/37711

ns

589/37711

þ607C/T

1976T/C

ns ns

589/37711 589/37711

152C/G Y947Y

589/37711

ns

589/37711

U.S.A.

117

116

116

116

116

116 116

116

115

114

(Continued )

Swedish/Finnish

Swedish/Finnish

Swedish/Finnish

Swedish/Finnish

Swedish/Finnish Swedish/Finnish

Swedish/Finnish

Danish

ns

872A/G

U.S.A. (Caucasoid and African American)

50.006

AT Minisatellite overall distribution and short allele 792bp

146/139

Minisatellite 30 flanking region 62G/C 174G/C MspI and BglII RFLP

113

German

ns

104

37

112

111

110

109

Italian

211/200

174G Discoid skin lesion ( pc ¼ 0.034)

ns

German

174G/C

123/199 ns

Dutch

a2

ns5

91/253

Danish

50.0510

TNF1

1.9610

P 5 0.002

TNF1

173/192

Canadians

ns

Japanese

91/91

TNF2 Proteinuria 50.05

NcoI first intron NcoI first intron NcoI first intron TNFa microsatellite TNFa microsatellite

ns

74/74

NcoI first intron

Systemic Lupus Erythematosus 265

17q11.2–q21.1

19q13.1

Monocyte chemoattractant protein 1

Transforming growth factor beta-1

MCP1

TGFB1

988C/A, 800G/A, 509C/T, Leu10/Pro10 Arg25/Pro25 915G/C ns

230/158

ns

ns ns

0.0002

P value

ns

AA genotype

Associated allele

138/182

276/194

2518G/A 2518G/A

509C/T

134/118

N1

2518A/G

Polymorphism

0.3 (0.2–0.6)

OR (95%CI)

ns

AG genotype cutaneous vasculitis (p ¼ 0.008)

AA genotype nephritis (p 5 0.0001 protective)

Association with disease features2

German

Taiwanese

U.S.A.

Korean Spanish

U.S.A.

Population

123

122

121

119 120

118

Ref.

Genes are listed in order of chromosome number. 1 Number of SLE patients/number of controls. 2 Allele -or genotype, or haplotype-, disease feature, (p value). 3 Named 2763 in Ref. 55 and Ref. 57. 4 No stratification for HLA-DR alleles was performed. 5 After stratification for HLA-DR3. 6 DRB1 alleles showed a similar distribution among patients and controls. 7 308A allele significantly ( p ¼ 0.04) increased before the stratification for HLA-DR3. 8 After stratification for HLA-DR15 (which is significantly increased in SLE and showed a significant linkage disequilibrium with TNF2 allele) the increase of TNF2/TNF2 genotype was significant only in DR15 positive individuals. 9 After stratification for DR15 which showed a significant linkage disequilibrium with TNF2 allele. 10 The effect was indistinguishable from HLA-DR3 haplotype. 11 A sample of Swedish (480 SLE patients and 256 controls) and of Finnish (109 SLE patients and 121 controls) were separately analyzed TDT: transmission disequilibrium test. pc: p value corrected for the number of comparisons; ns: not significant.

Location

Function

Gene

TABLE 18.2 Continued

266 Cytokine Gene Polymorphisms in Multifactorial Conditions

11q23 19p13.1

21q22.11

21q22.11 21q22.11

Interleukin 10 receptor

Interleukin 12 receptor, beta 1

Interferon alpha receptor1

Interferon alpha receptor2

Interferon gamma receptor 2

IL10R

IL12RB1

IFNAR1

IFNAR2

IFNGR2

Val114Met

Gln64Arg

IVSG/A 4723T/C

641A/G, 1094T/C 1132G/C V18338L IVSG/A IVSA/G

Val 50Ile Gln551Arg

110/110

0.016

ns ns ns ns ns ns

589/3773 589/3773 589/3773 589/3773 589/3773 96/91

ns

0.0057 0.037 ns

Ile50 Arg551

559/603

109/102

50/100

ns

ns

350/330

104/86

ns (TDT) ns ns ns ns

0.033

P value

ns

Met114

196R

Associated Allele

101/105

202/231 139/137

91 trios

105/99

N1

1.9 (1.2–3.3) 2.3 (1.1–4.7)

3.60 (1.2–12.7)

1.8 (1.01–3.2)

OR (95%CI)

Nephritis (ns)

Nephritis (ns)

ns

ns

Association with Disease Features2

Genes are listed in order of chromosome number. 1 Number of SLE patients/number of controls. 2 Allele (or haplotype), disease feature, p value. 3 A sample of Swedish (480 SLE patients and 256 controls) and of Finnish (109 SLE patients and 121 controls) were separately analyzed. TDT: Transmission Disequilibrium Test; ns: not significant.

6q23–q24 16p11.2– 12.1

Interferon gamma receptor 1

Interleukin 4 receptor

IFNGR1

1486T/C 1237C/T þ1174A/G þ2848G/A

3p21.3

Toll-like receptor 9

TLR9

IL4R

M196R E232K K56 K P181P M196R M196R M196R M196R P181P E232K K56K 1666G/A 1693T/C (30 UTR) (CA)n (IVS4)

Polymorphism

1p36.3– p36.2

Location

Tumor necrosis factor receptor type II

Function

TNFRII

Gene

TABLE 18.3 Summary of Genetic Association Studies of Cytokine Receptor Polymorphisms with SLE

131

116 116 133

Japanese

116 116 116

92

132

94

Swedish/Finnish Swedish/Finnish

Swedish/Finnish Swedish/Finnish Swedish/Finnish

Spanish

Japanese

Japanese

Japanese

61 130

Italian

129

125 79 126 127 128

124

Ref.

Korean

U.S.A. (Caucasoid)

U.S.A. Vietnamese Spanish, U.K. Korean Japanese

Japanese

Population

Systemic Lupus Erythematosus 267

268

Cytokine Gene Polymorphisms in Multifactorial Conditions

confirmed in a Swedish25 and in two Oriental samples.26,27 However, at least another five reports failed to replicate this finding (Table 18.2). For this kind of result a meta-analysis is strongly recommended. Using this approach, a significant association with SLE susceptibility was demonstrated for three genes showing conflicting results in different studies, namely FCGRIIA (R131H, OR ¼ 1.30 CI: 1.10–1.52; Ref. 28), CTLA4 (exon 1 þ49A/G, OR ¼ 1.29 CI: 1.03–1.62; Ref. 29), and MBL (variant alleles at codon 52, 54, 57, OR ¼ 1.62 CI: 1.3–2.0; Ref. 30). 3. Some positive associations were only found when subdividing the patients according to the clinical and immunological features suggesting that there might be a genetic influence on the disease phenotype and that genes different from those involved in SLE susceptibility may influence the severity of the disease, as demonstrated for murine lupus models.21,31 This analysis requires to perform several comparisons. Therefore the p values should be corrected for the number of comparisons. Since this is often not done, conclusions need particular caution. 4. In most studies few variants have been analyzed without any information of the LD extension across the candidate locus region. Since LD distribution is highly variable throughout the genome and can vary even across very small physical distances, multiple polymorphisms within each of the candidate genes should be tested to ensure that any true effect is identified.

The overall failure to find positive associations can be explained by many reasons including the difficulty in selecting from among the many possibile candidate genes, the presence of clinical and genetic heterogeneity, the modest effect likely to be contributed by each disease gene, the limited number of tested markers, and their uncertain probability of being in linkage disequilibrium with the causal variation. The lack of replication also arises from the small size of most tested samples and the consequent lack of the statistical power to detect modest gene effects. This problem is even greater when patient samples are further subdivided in smaller groups taking into account clinical and genetic heterogeneity. For two genes the number of published papers were particularly large, namely TNF and IL10. Details regarding these genes are reported below

18.3 ASSOCIATION STUDIES WITH POLYMORPHISMS IN THE TNF GENES Cytokines belonging to the TNF family are pluripotent molecules involved in the regulation of inflammation and apoptosis. In particular, TNF alpha enhances class I MHC expression on activated T cells, promotes IL-2 dependent T cell proliferation, and is a cofactor in B cell proliferation and immunoglobulin production.12,32,33 Levels of TNF are increased in SLE patients compared with controls and strongly correlate with parameters of disease activity.34–36 A cluster of three different TNF genes maps in the HLA central region, namely LTB, TNF, LTA coding for lymphotoxin beta, TNF alpha, and TNF beta (or lymphotoxin alpha), respectively. Both the biological effects and the localization in the HLA region were encouraging factors for undertaking studies to test the association of polymorphisms in these genes with SLE susceptibility. In fact, although SLE is known to be positively associated with certain HLA-DR alleles, it is not clear whether the MHC genes are the predisposing genes of the disease rather than markers for other closely linked gene(s). This is a general problem for HLA associated diseases, but it is particular evident for SLE since the strength of association of the classically HLA-DR alleles (DR3 and DR2) with SLE is much lower than

Systemic Lupus Erythematosus

269

with other autoimmune diseases, suggesting that the primarily associated sequence variations may be located in other genes of the HLA region. The majority of the association studies were focused on two SNPs, namely the 308A/G in the TNF promoter and the NcoI-RFLP in the first intron of LTA. The TNF promoter variation was particularly promising since some papers reported its association with TNF alpha production.22 However, this association was not replicated in other studies.22 In spite of the promising expectations, the majority of the studies did not find a significant association; when an association was detected, it was not independent of DR alleles (Table 18.2). On the contrary, three papers37–39 reported a significant association of the 308 A allele in the TNF promoter region, independently of DR3. This allele is part of the HLA B8-DR3 haplotype but in these studies its involvement was not secondary to linkage disequilibrium with DR3. In particular, 308A synergizes with DR3 in Caucasoids.37,38 Moreover 308A is associated with SLE in African Americans39 a population showing no association with DR3. The importance of TNF genes in SLE pathogenesis is also suggested by murine lupus models.40 Three different H-2-congenic (NZB
NZW) F1 mice bearing distinct alleles at class II and TNF-alpha regions were analyzed. Among these, only one (NZB
NZW) F1 produced a markedly lower level of TNF-alpha, due to a sequence variation in the TNF-alpha gene. Compared to these mice, in the other two strains the disease was milder and the onset of renal disease was significantly delayed demonstrating that TNF-alpha polymorphism acts to modulate an initial process of the renal disease.40

18.4 ASSOCIATION STUDIES WITH IL10 POLYMORPHISMS Many lines of evidence suggest that IL10 is a strong candidate gene for SLE susceptibility. IL-10 is an important immunoregulatory cytokine influencing many aspects of the immune response. It suppresses type 1 T helper lymphocytes by decreasing IL-2 and interferon-g production.41,42 It also inhibits certain functions of activated macrophages by downregulating major histocompatibility complex (MHC) class II and B7 expression43 and by inhibiting production of pro-inflammatory cytokines such as TNFa, IL-1, IL-6, IL-8, and IL-12.41,44 Contrary to its T cell and macrophage inhibitory actions, IL-10 has a potent stimulatory effect on B lymphocytes, leading to their proliferation and differentiation.45 Since SLE is characterized by impaired T cell responses and dysregulation of B cell activation leading to B cell hyperactivity and production of autoantibodies,2,46 IL-10 production may contribute to the disease by a direct effect on B cell survival and on autoantibody production.47 Moreover, B cells and monocytes of SLE patients produce an increased amount of IL-10 compared with non-affected individuals.48,49 Besides its functional relevance, IL10 is an attractive positional candidate gene since it maps in 1q32, in a region homologous to a murine SLE susceptibility region (reviewed in Ref. 50). In humans different genome screens reported evidence of linkage with SLE in the 1q41–44 region spanning 30 cM and located 16 cM telomeric to IL10 (reviewed in Refs. 10, 11, and 50). Different polymorphisms were identified both in the 50 flanking region and in the transcribed region of the IL10 gene including several SNPs and two microsatellites at position 4000 (IL10.R) and 1100 (IL10.G) (reviewed in Ref. 51). No significant association with SLE susceptibility was reported for IL10 SNPs in Caucasoid populations (Table 18.2) although a role in the clinical phenotype was suggested in Caucasoids52–54 as well as Orientals.55,56 Conversely, the SNP at position 2726, was found to be associated with SLE susceptibility in a group of African American patients57 and the T–C–A–T–A haplotype (involving promoter SNPs at position 3575, 2726, 1082, 819, and 592) was significantly associated in a large population of Hong Kong Chinese.55

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One of the two microsatellites, IL10.G, was shown to be associated with SLE by four independent studies in four different populations (U.K., Italian, Mexican American, Chinese),58–61 although this was not supported by two more recent works.62,63 In each of the four reports showing a significant association of IL10.G microsatellite with SLE, alleles with a higher number of repeats (22, 23, 25, and 28 repeats respectively) were involved while a negative association was observed with the shorter, (CA)21, allele in three of these studies59–61 (Table 18.4). One possibility is that the association with the disease is not with single alleles but with the length of the repeated sequence. Therefore we re-analyzed the six IL10.G-SLE association studies considering the IL10.G microsatellite as a biallelic marker consisting of a ‘‘long allele’’ (IL10.G-L, including all the alleles containing 421 CA repeats) and a ‘‘short allele’’ (IL10.G-S, including (CA)21 and alleles with 521 CA repeats). A significant positive association with the L allele was observed by combining the data of the six studies. These data suggest that the presence of a large stretch of CA repeats in the IL10 promoter is associated with SLE susceptibility. There are several examples in the literature showing a direct correlation of the promoter transcriptional activity with the number of repeats of a microsatellite.64–68 The number of tandem repeats

TABLE 18.4 A Summary of Association Studies of IL10.G Microsatellite with SLE Population

U.K. Mexican American Italian Chinese

Repeat Number of the Individual Allele that is Significantly: Increased Allele (P)

Decreased Allele (P)

(CA)253 (0.053) (CA)225 (3.9
106) (CA)237 (0.05) (CA)289 (0.02) (CA)1610 (0.02)

(CA)214 (0.019) (CA)216 (0.00047) (CA)218 (0.0139)

Association with the ‘‘Long Allele’’

1

Controls2

P

OR (95% CI)

0.55 (56)

0.43 (102)

0.033

1.70 (1.04–2.78)

60

0.61 (158)

0.45 (220)

0.00001

1.93 (1.42–2.61

59

0.69 (217)

0.56 (173)

0.012

1.46 (1.08–1.98)

51,61

0.39 (550)

0.38 (689)

ns

58

0.50 (330)

0.53 (368)

ns

63

0.52 (210)

0.54 (158)

ns

62

0.49 (1521)

0.45 (1710)

0.001

All IL10.G alleles with 4 21 (CA) repeats. Frequency (number of tested individuals). Nomenclature reported in the original papers: 3 (IL10.G13). 4 (IL10.G9). 5 (IL10127). 6 (IL10125). 7 (IL10.G-140bp). 8 (IL10.G-136bp). 9 (IL10.G16). 10 (IL10.G4). ns: not significant. 2

Ref.

SLE2

Mexican American German All

1

1.18 (1.07–1.30)

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271

has been shown to influence the transcription rate either by a direct interaction with a transcription factor69,70 or by affecting spacing between flanking regions.71 Thus, it is tempting to speculate that a long IL10.G allele is responsible for a high IL-10 production, a typical aspect of SLE pathogenesis. This hypothesis is in agreement with previously reported data72 showing that cells of individuals carrying the longest analyzed IL10.G allele (containing 26 CA repeats) produced the highest amount of IL-10 upon induction with LPS whereas the lowest production was observed for cells of individuals carrying the shortest analyzed IL10.G allele (containing 19 CA repeats). Moreover, cells of individuals carrying IL10.G-S produced a mean amount of IL-10 lower than individuals with the IL10.G-L alleles.72

18.5 FUTURE DIRECTIONS So far, the association results reported for SLE and in general for complex diseases have identified susceptibility genes each conferring a small OR. It is possible that different low effect factors synergize and their combination confers a higher risk for the development of the disease. Accordingly, several studies aimed at testing the interaction of different polymorphisms in the susceptibility of complex diseases were recently reported. By using this approach, two papers59,73 report a synergistic effect between susceptibility alleles of IL-10 and the bcl-2 genes in determining SLE susceptibility. Alone, the presence of alleles of each of these genes was associated with a moderate increase in SLE risk, while the occurrence of these alleles together increased the odds of developing SLE by more than 40-fold59 and 3-fold.73 However, a third report did not confirm these data.74 Two further examples concern an interaction between genes in the HLA region and genes of the IL1 family.25,75 In one report IL1RN*2 and HLA-DR3 separately increased the SLE risk moderately. The occurrence of IL1RN*2 and HLA-DR3 together increased the risk to develop SLE by seven fold.25 In a second report a strong association (OR ¼ 8.0, p 5 0.00001) for the combined ‘‘HLA-DR3, TNF-alpha 308A, IL-1alpha 889C/C’’ genotype was observed.75 Even though these examples are very promising, they need confirming in larger samples since this kind of study loses power by grouping individuals in many different subsets according to their different possible genotype combinations. Another promising approach is the association analysis with a large number of polymorphisms with high throughput typing systems. The choice of the markers is a crucial point which strongly influences the success of detecting an association. The possibility of testing many different markers in different genes, for many samples and with a reasonable cost and time, would improve the power to detect sequence variations involved in the susceptibility to complex diseases. The recent development of efficient genotyping methods based on microarray technology and the availability of a large collection of single-nucleotide polymorphisms opens the possibility of performing genome wide association studies. A few applications of these innovative approaches were recently reported.76,77

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122. Lu, L. Y. et al., Single-nucleotide polymorphisms of transforming growth factor-beta1 gene in Taiwanese patients with systemic lupus erythematosus, Microbiol. Immunol. Infect., 37, 145, 2004. 123. Schotte, H. et al., The transforming growth factor-beta1 gene polymorphism (G915C) is not associated with systemic lupus erythematosus, Lupus, 12, 86, 2003. 124. Morita, C. et al., Association of tumor necrosis factor receptor type II polymorphism 196R with systemic lupus erythematosus in the Japanese: molecular and functional analysis, Arthritis Rheum., 44, 2819, 2001. 125. Tsuchiya, N. et al., Analysis of the association of HLA-DRB1, TNFalpha promoter and TNFR2 (TNFRSF1B) polymorphisms with SLE using transmission disequilibrium test, Genes Immun., 2, 317, 2001. 126. Al-Ansari, A. S. et al., Tumor necrosis factor receptor II (TNFRII) exon 6 polymorphism in systemic lupus erythematosus, Tissue Antigens, 55, 97, 2000. 127. Lee, E. B. et al., Tumor necrosis factor receptor 2 polymorphism in systemic lupus erythematosus: no association with disease, Hum. Immunol., 62, 1148, 2001. 128. Tsuchiya, N. et al., New single nucleotide polymorphisms in the coding region of human TNFR2: association with systemic lupus erythematosus, Genes Immun., 1, 501, 2000. 129. Sullivan, K. E. et al., A TNFR2 30 flanking region polymorphism in systemic lupus erythematosus, Genes, 1, 225, 2000. 130. Hur, J. W. et al., Association study of Toll-like receptor 9 gene polymorphism in Korean patients with systemic lupus erythematosus, Tissue Antigens, 65, 266, 2005. 131. Tanaka, Y. et al., Association of the interferon-gamma receptor variant (Val14Met) with systemic lupus erythematosus, Immunogenetics, 49, 266, 1999. 132. Nakashima, H. et al., Polymorphisms within the interleukin-10 receptor cDNA gene (IL10R) in Japanese patients with systemic lupus erythematosus, Rheumatology, 38, 1142, 1999. 133. Nakashima, H. et al., The combination of polymorphisms within interferon-gamma receptor 1 and receptor 2 associated with the risk of systemic lupus erythematosus, FEBS Lett., 453, 187, 1999.

19

Sjo¨gren’s Syndrome Marja Pertovaara

CONTENTS 19.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.2 Interleukin-10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.3 Tumour Necrosis Factor a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.4 Tumour Necrosis Factor b . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 Interleukin-6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.6 Interleukin-1 Complex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.7 Transforming Growth Factor b1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.8 Interferon-g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 Interleukin-4 Receptor a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.10 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

279 279 283 284 284 284 285 285 285 285 286 286

19.1 INTRODUCTION Sjo¨gren’s syndrome (SS) is a chronic autoimmune rheumatic disease characterized by dry eyes and mouth (keratoconjunctivitis sicca and xerostomia). Extraglandular manifestations, including dermatological, gastrointestinal, musculoskeletal, neurological, renal, respiratory, and vascular symptoms, are possible and abundant autoantibody production is a characteristic feature of the condition. Histologically, lymphocyte and plasma cell infiltration is observed in the affected organs.1 An increased risk of non-Hodgkin lymphoma has been related to SS.2 SS is divided into primary (pSS) and secondary (sSS) forms, the latter presenting in association with other autoimmune connective tissue diseases, most typically rheumatoid arthritis. An interaction between environmental and genetic factors is thought to play a role in the pathogenesis of pSS.3 Several cytokines have been proposed to be involved in the process, including the pro-inflammatory cytokines interleukin-1a and b (IL-1a and IL-1b), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-a), interferon gamma (IFN-g) and the anti-inflammatory cytokines interleukin-10 (IL-10), IL-1 receptor-a (IL-1Ra) and transforming growth factor-b1 (TGF-b1). Primary SS, like many other autoimmune diseases, is a multifactorial and probably also multigenic disorder. There is a strong human leukocyte antigen (HLA) gene association in patients with pSS, but non-HLA genes, including cytokine genes, also have raised interest as potential effectors in susceptibility to and severity of the condition.4 A summary of studies concerned with cytokine gene polymorphisms in pSS is presented in Table 19.1.

19.2 INTERLEUKIN-10 Five studies have dealt with the issue of the genetic polymorphism of IL-10 in pSS patients, and in four of them5–8 an association between IL10 genetics and pSS was observed. 279

TNF-a

IL-10

Cytokine

A allele increased, OR 2.71 (CI 1.32–5.58, P ¼ 0.006)


308 G/A SNP

65 pSS patients 66 controls

No pSS patients with joint symptoms or anti-SSA antibodies: a10 allele increased compared with controls No

No a2 allele increased in DRB1*0301-positive pSS patients vs. DRB1*0301-positive controls, OR 5.63, P 5 0.02

No in allele or genotype frequencies GCC haplotype carrier rate increased, OR 2.25 (CI 1.26–4.02, Pcorr ¼ 0.036)

a1–a14 microsatellite


1082 G/A SNP
819 C/T SNP
592 C/A SNP

129 pSS patients 96 controls

ACC haplotype carrier rate decreased

49 pSS patients 148 controls


1082 G/A SNP
819 C/T SNP
592 C/A SNP

47 pSS patients 107 controls

IL10.G9 allele increased in high IL-10 producers

a1–a13 microsatellite

IL10.G, IL10.R microsatellite

39 pSS patients 15 controls

GCC haplotype increased ACC haplotype decreased GCC/ATA genotype increased ACC/ACC genotype decreased

35 pSS patients 146 controls


1082 G/A SNP
819 C/T SNP
592 C/A SNP

63 pSS patients 150 controls

GCC-carriers: P-IL-10 increased

GCC haplotype increased, OR 1.90 (CI 0.955–3.62, P 5 0.05) ACC haplotype decreased, OR 0.443 (CI 0.257–0.764, P 5 0.05) GCC/ATA genotype increased, OR 2.19 (CI 1.19–4.03, P 5 0.05)

a1–a13 microsatellite


1082 G/A SNP
819 C/T SNP
592 C/A SNP

62 pSS patients 400 controls

No

Association/Main Finding

42 pSS patients 152 controls


1082 G/A SNP
819 C/T SNP
592 C/A SNP

Polymorphism

108 pSS patients 165 controls

Patients/Controls

TABLE 19.1 Summary of Studies Dealing with Cytokine Gene Polymorphisms in Primary Sjo¨gren’s Syndrome

12

16

15

14

7

8

11

6

5

9

Reference

280 Cytokine Gene Polymorphisms in Multifactorial Conditions

TGF-b1

25 SS patients 32 controls
509 C/T SNP

No

No

No No

þ915 C/G SNP

IL1B
511 C/T SNP IL1B þ3953 C/T SNP

69 pSS patients 392 controls

CC genotype decreased vs. SLE patients TT genotype decreased vs. SLE patients AA genotype decreased vs. healthy controls No

No C allele increased in SSB-positive pSS patients vs. SSA- and SSB-negative pSS patients, OR 2.63 (CI 1.37–5.03, Pcorr ¼ 0.024)


511 C/T SNP
31 C/T SNP þ3877 A/G SNP þ3953 C/T SNP

IL1B IL1B IL1B IL1B

101 SS patients (43 pSS, 58 sSS) 103 SLE patients 106 controls

pSS patients with Raynaud’s symptom: Haplotype IL1a-889T, IL1b þ 3953C, IL1RN1 increased Haplotype IL1a-889C, IL1b þ 3953T, IL1RN1 decreased

No in allele or genotype frequencies No in allele or genotype frequencies No; no difference between definite or possible pSS

No; all pSS patients vs. controls IL1RN*2 carriage rate increased in definite pSS vs. possible pSS or vs. healthy controls, OR 2.38 (CI 1–5.8, P ¼ 0.04)

þ869 C/T SNP

IL1A
889 C/T SNP IL1B þ3953 C/T SNP Intron 2 IL1RN 86-bp VNTR

65 pSS patients 180 controls

129 pSS patients 96 controls

Intron 2 IL1RN 86-bp VNTR

36 pSS patients (16 definite pSS, 20 possible pSS) 100 controls

No


174 G/C SNP

129 pSS patients 96 controls

IL-1 complex

No GG genotype vs. CC genotype: P-IL-6 increased


174 G/C SNP

61 pSS patients 400 controls

No

IL-6

Intron 1 Nco I RFLP

19 pSS patients 131 controls

A allele increased, OR 2.9 (CI 1.90–4.57, P 5 0.0001) A allele decreased, OR 0.03 (CI 0–0.46, P 5 0.0001)


308 G/A SNP
238 G/A SNP

67 pSS patients 430 controls

TNF-b

A allele increased, OR 2.86 (CI 1.64–5.12, Pcorr ¼ 0.00028) GA genotype increased, OR 3.16 (CI 1.60–6.45, Pcorr ¼ 0.0012)


308 G/A SNP

129 pSS patients 96 controls

(Continued )

24

7

23

22

21

20

7

19

17

13

7

Sjo¨gren’s Syndrome 281

45 pSS patients 74 controls

IL-4 receptor a þ1748 A/G SNP

þ874 A/T SNP

Polymorphism

G allele increased, RR 2.6, P ¼ 0.035

No

Association/Main Finding

25

7

Reference

Abbreviations used in the Table: IL ¼ interleukin; pSS ¼ primary Sjo¨gren’s syndrome; SNP ¼ single-nucleotide polymorphism; OR ¼ odds ratio; CI ¼ 95% confidence interval; Pcorr ¼ P value with Bonferroni correction; TNF ¼ tumor necrosis factor; RFLP ¼ restriction fraction length polymorphism; VNTR ¼ variable number of tandem repeats; sSS ¼ secondary Sjo¨gren’s syndrome; TGF ¼ transforming growth factor; IFN ¼ interferon; RR ¼ risk ratio.

129 pSS patients 96 controls

Patients/Controls

IFN-c

Cytokine

TABLE 19.1 Continued

282 Cytokine Gene Polymorphisms in Multifactorial Conditions

Sjo¨gren’s Syndrome

283

No association was noted in one report.9 In three of the studies the GCC haplotype carrier state (G at position
1082, C at
819, and C at
592 of the IL10 gene) was increased5–7 and in three of them the ACC haplotype carrier rate decreased in patients with pSS compared with control subjects.5,6,8 Rischmueller and co-workers9 reported no association between IL10 gene polymorphism and pSS in 108 Australian patients; GCC, ACC and ATA haplotype frequencies in their pSS patient cohort and control subjects did not differ. In contrast, we found the GCC haplotype to be more prevalent with an odds ratio (OR) of 1.90 and the ACC haplotype less prevalent (OR 0.443) in pSS patients compared with healthy controls.5 The frequency of the GCC/ATA genotype was elevated in pSS patients (OR 2.19).5 The increased frequency of IL10 GCC haplotype in patients with pSS has subsequently been ascertained in two other cohorts.6,7 Font and colleagues found the GCC haplotype carrier rate, mainly related to a higher frequency of the heterozygote genotype GCC/ATA, significantly increased in 63 Spanish pSS patients.6 The frequency of the IL10 ACC haplotype and the ACC/ACC genotype was decreased in patients with pSS.6 Moreover, in a French study involving 129 patients with pSS, the IL10 haplotype GCC carrier rate was higher in pSS patients than in controls, although the IL10 allele and genotype frequencies were not significantly different.7 The IL10 GCC haplotype was not associated with levels of serum immunoglobulins or secretion of autoantibodies in any of the five studies.5–9 The GCC haplotype carriers had higher plasma IL-10 concentrations than non-carriers in one study,5 but the GCC haplotype carrier state was not associated with clinical features or autoantibody production in pSS.5 In one study the presence of the GCC haplotype was found to lead to an earlier onset of pSS.6 In accordance with results obtained by Hulkkonen and colleagues5 and Font and colleagues6 in Japanese SS patients the ACC haplotype carrier rate was also significantly decreased compared with control subjects, but the GCC haplotype carrier rate was not increased.8 However, the overall haplotype and genotype frequencies also in Japanese control subjects differed from those in Caucasian subjects, i.e. the frequency of the GCC haplotype was lower and that of the ATA haplotype higher compared with Caucasians. The IL10 gene polymorphism affected the age of onset of pSS, carriers of the protective haplotype ACC having the highest age at onset.8 Moreover, the frequency of the protective ACC haplotype was decreased, although not significantly, in patients with high IgG levels.8 In addition, an IL10 microsatellite polymorphism, which is known to be in linkage disequilibrium with the
1082,
819, and
592 SNPs,10 was seen to be associated with serum IL-10 levels in pSS patients in one study.11 No comparison of IL10 microsatellite polymorphism was made between pSS patients and controls in this study. pSS patients producing high levels of IL-10 carried the IL10.G9 allele more frequently than those with low levels of IL-10.11 IL-10 levels also correlated positively with titers of IgA-RF, anti-SSAand anti-SSB antibodies, as well as with focus score in labial salivary gland biopsies.11

19.3 TUMOUR NECROSIS FACTOR a The genetic polymorphism of TNFA
308 (G/A) in pSS patients has been investigated in three separate studies, with parallel results.7,12,13 The rarer A allele of TNFA
308 (TNF2) was found to be more prevalent in patients with pSS than in healthy controls in all studies and was associated with anti-SSB antibodies in two of the cohorts.7,12 In the Finnish study,12 the carriers of TNF2 had more frequently and in significantly higher titers anti-SSA and anti-SSB antibodies and higher plasma IgG concentrations than the others, but Gottenberg and co-workers7 found even that the association of TNF2 was restricted only

284

Cytokine Gene Polymorphisms in Multifactorial Conditions

to pSS patients with anti-SSB antibodies. They suggested that the genetic predisposition to pSS might to a great extent concern the pattern of autoantibody diversification. There was a trend towards an association of TNF2 with renal manifestations (proteinuria and distal renal tubular acidosis) in pSS in one study but the number of patients was too limited to yield conclusive evidence.12 There is a strong linkage disequilibrium between TNFA and HLA DR3 in Caucasian subjects and the TNF2 carriers also had significantly more often the HLA DR 3 genotype in the Finnish study; the independent effect of TNF2 on susceptibility to pSS could therefore not be evaluated.12 TNF2 and HLA-DRB1*03 did not independently affect disease susceptibility or anti-SSB antibody secretion in the French study.7 The polymorphism of TNFA at
238 (G/A) was investigated in one study in Colombian pSS patients, the G/A heterozygosity being found to be a protective factor for pSS and the haplotype TNFA
308A–238G a risk factor (OR 3.6).13 No differences in allelic frequencies between TNF microsatellites in pSS patients and controls have been observed.14–16 The TNF a2 allele was more frequent in DRB1*0301-positive pSS patients than in DRB1*0301-positive control subjects.14 In another study an association was noted between TNF a10 allele and joint symptoms or anti-SSA-antibodies in pSS patients.15

19.4 TUMOUR NECROSIS FACTOR b The frequency of a 5.5 kb fragment representing NcoI RFLP polymorphism of TNFA was found to be increased, albeit not significantly, in patients with pSS.17 However, later on this polymorphism was located at the first intron of the TNFB gene and the fragment identified as the TNFB*1 allele.18

19.5 INTERLEUKIN-6 The polymorphism of the IL6 gene at position
174 (G/C) does not predispose to pSS based on results of two separate studies.7,19 In Finnish Caucasian patients circulating IL-6 concentrations were found to be associated with certain clinical features of pSS; i.e. the severity of the histological findings in labial salivary gland biopsies, the number of diagnostic criteria for pSS, the presence of such extraglandular manifestations as pulmonary fibrosis or alveolitis, or peripheral neurological symptoms and the presence of an associated celiac disease.19 Plasma levels of IL-6 were genetically regulated in patients with pSS but not in healthy controls. Plasma IL-6 levels were higher in pSS patients with the G/G genotype than in those with G/C or C/C.19 No association was found between IL6 polymorphism and the clinical presentation in French pSS patients.7

19.6 INTERLEUKIN-1 COMPLEX Four studies with somewhat conflicting results have addressed the issue of IL1 complex gene polymorphism and pSS.20–23 The IL1RN*2 allele was found to be more prevalent in definite (n ¼ 16) than in possible pSS (n ¼ 20) or healthy controls in a cohort of 36 pSS patients,20 but the difference between all pSS patients (definite and possible) and healthy controls was not significant. Interpretation of the results must take into account the fact that the patient number in this study and, particularly in the subgroups, was very small. In another study involving 65 Finnish Caucasian patients with pSS,21 IL1 gene family (IL1A, IL1B, IL1RN) genotypes or their haplotypes were found not to predispose patients to pSS. No difference emerged between IL1RN*2 allele distribution in definite or possible pSS.

Sjo¨gren’s Syndrome

285

In contrast, the IL1 complex haplotypes were found to be associated with Raynaud’s phenomenon in pSS. The frequency of a haplotype consisting of IL1A
889 allele T, IL1B þ3953 allele C and ILIRN*1 VNTR was increased and that of haplotype IL1A
889 allele C, IL1B þ3953 allele T, ILIRN*1 VNTR decreased in a subgroup of pSS patients with Raynaud’s phenomenon. In Colombian pSS patients no association was observed between IL1B
511 or þ3953 polymorphism and pSS.23 In Japanese patients with SS (including both pSS and sSS patients) allele frequencies of the IL1B gene at positions
511,
31,
3877 and þ3953 did not differ from those in healthy controls or SLE patients.23 The genotypes CC and TT at positions
511 and
31, respectively, were significantly less frequent in SS patients than in patients with SLE, and the genotype AA at position
3877 was significantly less frequent in pSS patients than in healthy controls.22

19.7 TRANSFORMING GROWTH FACTOR b1 The genetic polymorphism of TGF-b1 has not been found to predispose to the development of pSS,7,24 but it has proved to be associated with anti-SSB antibody production in pSS.7 The frequency of allele C at þ869 (codon 10) of TGFB1 was increased in a subgroup of pSS patients with anti-SSB antibodies. The polymorphism of the TGFB1 gene at þ915 (codon 25) was not associated with susceptibility to pSS or to antibody secretion.7

19.8 INTERFERON-c The polymorphism of IFNG at þ874 has been investigated in one study in patients with pSS and no association with susceptibility or clinical presentation of pSS was found.7

19.9 INTERLEUKIN-4 RECEPTOR a The genetic polymorphism of the IL-4 receptor a was associated with susceptibility to pSS in one study,25 in which a Q576R (gln576arg) polymorphism resulting from a þ1748 A/G SNP was investigated. Carriers of the G allele (coding for arginine) at IL4RA þ1748 were found to have a 2.6 risk ratio for pSS compared to AA (coding for glycine) homozygotes.

19.10 CONCLUSIONS Most of the data concerning the significance of various cytokine gene polymorphisms in susceptibility to pSS are still disputable, either by reason of conflicting findings or lack of confirmation. However, it can be stated that the genetics of IL6 does not predispose to pSS7,19 but is possibly associated with the clinical presentation of the disease and regulates the inducible levels of serum IL-6 in pSS.19 TNFA genetics seems to affect susceptibility to pSS, but this effect is probably mediated via the extended HLA haplotype.7,12 The role of IL1 complex genes in pSS remains unclear, as the data from different studies are conflicting.20–23 However, there is evidence from four independent studies pointing to a role of IL10 genetics in susceptibility to pSS.5–8 It is difficult to establish the mechanism by which the polymorphism of IL10 predisposes to pSS. IL-10 is a potent anti-inflammatory mediator which down-regulates the production of pro-inflammatory cytokines and cell-mediated immune responses, but is also involved in the activation of B-cells and cytotoxic T-lymphocytes.26 T-cell-mediated immune responses play a decisive role in organ destruction in pSS, but B-cell hyperreactivity and autoantibody formation are likewise important in the

286

Cytokine Gene Polymorphisms in Multifactorial Conditions

pathogenesis of pSS.3 As it is the haplotype with high IL-10-producing capability (GCC) that is associated with an increased risk of pSS, it may be concluded that the antiinflammatory effect of IL-10 is either not sufficient or does not play a role in inhibiting the autoimmune reaction in pSS. A likely biological explanation for the effect of IL10 genetics on susceptibility to pSS would thus be activation of B-lymphocytes and induction of immunoglobulin synthesis and autoantibody production. However, there is no direct evidence for such a chain of events, as the IL10 GCC haplotype was not associated with serum immunoglobulin concentrations or autoantibody production in any of the studies.5–9 In one study, however, high levels of IL-10 were associated with the IL10 microsatellite polymorphism (IL10.G9 allele), and IL-10 levels correlated positively with titers of IgA-RF, anti-SSA- and anti-SSB antibodies,11 and in another the protective IL10 haplotype (ACC) was associated with low IgG levels.8 There are also other cytokines, e.g. IL-619 affecting B-cell hyperreactivity, and other non-HLA genetic factors, e.g. immunoglobulin gene polymorphism,27 affecting immunoglobulin and autoantibody production in pSS. It is therefore possible that a combination of cytokine and other genetic polymorphisms results in a predisposition to pSS, to B-cell hyperreactivity and to increased immunoglobulin and autoantibody production in pSS. Regarding IL10 gene polymorphism and predisposition to pSS it is, furthermore, of interest that high IL-10 levels and IL10 genetics have recently been reported to predispose to non-Hodgkin’s lymphoma,28,29 which is precisely the lymphoma type the risk of which has been found to be 44-fold in patients with SS compared with age- and sex-matched controls.2

ACKNOWLEDGMENTS The author wishes to thank Professor Mikko Hurme for valuable discussions regarding the manuscript, and the Medical Research Fund of Tampere University Hospital, Tampere, Finland, for grant support.

REFERENCES 1. Fox, R. I., Stern, M., and Michelson, P., Update in Sjo¨gren syndrome, Curr. Opin. Rheumatol., 12, 391, 2000. 2. Kassan, S. S. et al., Increased risk of lymphoma in Sjo¨gren’s syndrome, Ann. Intern. Med., 89, 888, 1978. 3. Jonsson, R., Gordon, T. P., and Konttinen, Y. T., Recent advances in understanding molecular mechanisms in the pathogenesis and antibody profile of Sjo¨gren’s syndrome, Curr. Rheumatol. Rep., 5, 311, 2003. 4. Sawalha, A. H. et al., The genetics of primary Sjo¨gren’s syndrome, Curr. Rheumatol. Rep., 5, 324, 2003. 5. Hulkkonen, J. et al., Genetic associations between IL-10 promoter region polymorphism and primary Sjo¨gren’s syndrome, Arthritis Rheum., 44, 176, 2001a. 6. Font, J. et al., The role of interleukin-10 promoter polymorphism in the expression of primary Sjo¨gren’s syndrome, Rheumatology, 41, 1025, 2002. 7. Gottenberg, J. E. et al., Association of transforming growth factor b1 and tumor necrosis factor a polymorphisms with anti-SSB/La antibody secretion in patients with primary Sjo¨gren’s syndrome, Arthritis Rheum., 50, 570, 2004. 8. Origuchi, T. et al., Correlation between interleukin 10 gene promoter region polymorphisms and clinical manifestations in Japanese patients with primary Sjo¨gren’s syndrome, Ann. Rheum. Dis., 62, 1117, 2003.

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9. Rischmueller, M. et al., Polymorphisms of the interleukin10 gene promoter are not associated with anti-Ro autoantibodies in primary Sjo¨gren’s syndrome, J. Rheumatol., 27, 2945, 2000. Correction in: J. Rheumatol., 44, 176, 2000. 10. Eskdale, J. et al., Microsatellite alleles and single nucleotide polymorphisms combine to form four major haplotype families at the human interleukin-10 (IL-10) locus, Genes Immun., 1, 151, 1999. 11. Anaya, J.-M. et al., Interleukin-10 (IL-10) influences autoimmune responses in primary Sjo¨gren’s syndrome and is linked to IL-10 gene polymorphism, J. Rheumatol., 29, 1874, 2002. 12. Pertovaara, M. et al., Polymorphism of the tumour necrosis factor a gene at position
308 and renal manifestations of primary Sjo¨gren’s syndrome, Rheumatology, 43, 106, 2004a. 13. Correa, P. A. et al., Autoimmunity and tuberculosis. Opposite association with TNF polymorphism, J. Rheumatol., 32, 219, 2005. 14. Jean, S. et al., DRB1*15 and DRB1*03 extended haplotype interaction in primary Sjo¨gren’s syndrome genetic susceptibility, Clin. Exp. Rheumatol., 16, 725, 1998. 15. Guggenbuhl, P. et al., Analysis of TNF alpha microsatellites in 35 patients with primary Sjo¨gren’s syndrome, Joint Bone Spine, 67, 290, 2000. 16. Hadj Kacem, H. et al., HLA-DQB 1 CAR1/CAR2, TNFa IR2/IR4 and CTLA-4 polymorphisms in Tunisian patients with rheumatoid arthritis and Sjo¨gren’s syndrome, Rheumatology, 40, 1370, 2001. 17. Fugger, L. et al., NcoI restriction fragment length polymorphism (RFLP) of the tumor necrosis factor (TNF-alpha) region in four autoimmune diseases, Tissue Antigens, 34, 17, 1989. 18. Messer, G. et al., Polymorphic structure of the tumor necrosis factor (TNF) locus: an NcoI polymorphism in the first intron of the human TNF-beta gene correlates with a variant amino acid in position 26 and a reduced level of TNF-beta production, J. Exp. Med., 173, 209, 1991. 19. Hulkkonen, J. et al., Elevated interleukin-6 plasma levels are regulated by the promoter region polymorphism of IL-6 gene in primary Sjo¨gren’s syndrome (pSS) and correlate with clinical manifestations of the disease, Rheumatology, 40, 656, 2001b. 20. Perrier, S. et al., IL-1 receptor antagonist (IL-1RA) gene polymorphism in Sjo¨gren’s syndrome and rheumatoid arthritis, Clin. Immunol. Immunopathol., 87, 309, 1998. 21. Hulkkonen, J. et al., IL-1 gene family haplotypes and Raynaud’s phenomenon in primary Sjo¨gren’s syndrome, Rheumatology, 41, 1206, 2002. 22. Muraki, Y. et al., Polymorphisms of IL-1b gene in Japanese patients with Sjo¨gren’s syndrome and systemic lupus erythematosus, J. Rheumatol., 31, 720, 2004. 23. Camargo, J. F. et al., Interleukin-1 beta polymorphisms in Columbian patients with autoimmune rheumatic diseases, Genes Immun., 5, 609, 2004. 24. Caserta, T. M. et al., Genotypic analysis of the TGF beta
509 allele in patients with systemic lupus erythematosus and Sjo¨gren’s syndrome, Ann. Genet., 47, 359, 2004. 25. Youn J. et al., Association of the interleukin-4 receptor a variant Q576R with Th1/Th2 imbalance of connective tissue disease, Immunogenetics, 51, 743, 2000. 26. Moore, K. W. et al., Interleukin-10 and interleukin-10 receptor, Annu. Rev. Immunol., 19, 683, 2001. 27. Pertovaara, M. et al., Immunoglobulin KM and GM gene polymorphisms modify the clinical presentation of primary Sjo¨gren’s syndrome, J. Rheumatol., 31, 2175, 2004b. 28. Breen, E. C. et al., Non-Hodgkin’s B cell lymphoma in persons with acquired immunodeficiency syndrome is associated with increased serum levels of IL10, or the IL10 promoter
592 C/C genotype, Clinical Immunology, 109, 119, 2003. 29. Lech-Maranda, E. et al., Interleukin-10 gene promoter polymorphisms influence the clinical outcome of diffuse large B-cell lymphoma, Blood, 103, 3259, 2004.

20

Multiple Sclerosis Orhun H. Kantarci and Brian G. Weinshenker

CONTENTS 20.1 20.2 20.3

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Role of Genetics in the Etiology of and Phenotypic Variability in MS . . . . . . . . . . The Autoimmune Hypothesis, Th1/Th2 Cell Bias and Role of Cytokines in MS Pathogenesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.4 Establishing the Role of Cytokine Polymorphisms in MS . . . . . . . . . . . . . . . . . . . . . . 20.5 Examples of Genetic Studies on Cytokines in MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.5.1 Interferon-g. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.5.2 Interleukin-12. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.5.3 Tumor Necrosis Factor a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.5.4 Interleukin-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.5.5 Interleukin-4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.5.6 Interleukin-10. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.6 Targeting Cytokine Networks for Treatment in MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.6.1 Interferon Experience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.6.2 Cytokine Blockade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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20.1 INTRODUCTION Multiple sclerosis (MS) is the prototypic idiopathic inflammatory demyelinating disease (IIDD) of the central nervous system (CNS) (Table 20.1).1 The clinical manifestations, prognosis and pathological features vary, both amongst entities within the broad spectrum of demyelinating disease and amongst subtypes of MS.2 MS is usually classified based on the temporal course of disease; the most common form is characterized by an initial relapsing–remitting course that ultimately evolves into a progressive disease. A variety of neurological functions are affected during these relapses depending on the location of the lesion. During and between clinical relapses, magnetic resonance imaging reveals CNS white matter lesions of different stages, most evolving without symptoms. While relapses and new inflammatory lesions detected on MRI become less frequent, and even scarce over time, an insidious course of worsening neurological function ensues characterized by prominent progressive axonal loss (secondary-progressive MS). Progressive axonal dropout apparently begins at a very early stage, when the clinical disease is still regarded as relapsing remitting. About 15% of cases, despite occasional relapses, remain disability-free (benign MS). Some cases present with insidious neurological dysfunction, most commonly as a myelopathy from onset without any clinical symptoms of acute relapses (primary progressive MS).

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TABLE 20.1 Clinical Spectrum of Idiopathic Inflammatory Demyelinating Diseases Extent of CNS Involvement

Disease Course

Restricted or Focal Monophasic


Monofocal IIDDs (isolated optic neuritis,




Relapsing-remitting





Chronic progressive





transverse myelitis, isolated brainstem events.) Monophasic neuromyelitis optica (Devic’s disease) Balo’s concentric sclerosis Recurrent monofocal IIDDs (e.g. recurrent optic neuritis; recurrent transverse myelitis) Relapsing neuromyelitis optica Primary progressive MS

Diffuse or Multifocal


Acute disseminated encephalomyelitis (ADEM)


Fulminant MS (Marburg’s variant)


Relapsing-remitting MS


Secondary progressive MS

IIDD ¼ idiopathic inflammatory demyelinating disease

20.2 ROLE OF GENETICS IN THE ETIOLOGY OF AND PHENOTYPIC VARIABILITY IN MS The etiology of MS is ‘‘complex’’ with strong evidence in support of both genetic and environmental factors.3 The arguments in support of environmental and genetic factors are presented in Table 20.2. Concordance studies among affected relative pairs suggest that phenotypic heterogeneity in this disorder as well as differences in individual susceptibility to CNS demyelinating disease may have a genetic basis; members of relative pairs have greater similarity of clinical course and rate of worsening of disability than would be expected considering the spectrum of the disease in familial cases of MS.4 How these genetic and environmental factors exert their biological effects so as to account for the clinicopathological heterogeneity in MS is not well defined. Most susceptibility loci, except perhaps the major histocompatibility complex, contribute only a small effect. Meta-analysis of whole genome linkage studies in MS has shown that only the HLA region on chromosome 6p21 has a well established role in determining MS susceptibility, supporting the previously well defined HLA DRB1*1501, DQ1* 0602 association with MS. Four other regions (Chromosomes 11ptr, 16p13, 17q21 and 22q13) have been identified as promising but not proven MS susceptibility loci.5 Association studies are powerful methods to uncover relatively small effects of allelic variants on complex traits such as MS.6 Association studies are conducted as either hypothesis-independent whole genome studies, as are many linkage studies for complex diseases, or hypothesis-driven candidate gene-based studies. Both of these approaches have limitations. Whole genome association studies are mainly limited by the sample size necessary to study sufficient number of markers to construct the haplotype blocks through a given genome to have power to uncover all small effects, particularly when corrections are performed for false positive chance discovery. Given the limited degree of linkage disequilibrium in the outbred population, unless one studies markers very close to the ‘‘causative allele,’’ one may miss a critical gene association. A candidate gene, while much easier to study by saturated markers, is limited by the reliability of the choice of candidate gene, which in turn is dependent on the degree of understanding of the biology of the disease that is necessary to identify the likely candidate. Therefore, homogeneity of the

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TABLE 20.2 ‘‘Complex’’ Etiology of MS Support for Genetic Basis of MS 1. Excess occurrence in Northern Europeans relative to indigenous populations from the same geographic location127 2. Familial aggregation: 20–40 times more common in 1st degree relatives with rapid drop off with degree of relatedness128 3. No excess of MS in adopted relatives of patients with MS128 4. Excess concordance in monozygotic versus dizygotic twins129 5. Widely confirmed HLA DRB1* 1501, DQ1* 0602 association with susceptibility to MS130

Support for Environmental Basis of MS 1. Variation in incidence and prevalence according to geography127 2. Mutable risk of developing MS with migration from both low to high as well as high to low prevalence areas127 3. Presence of rare clusters and epidemics of MS (Faroe Islands and Iceland post WWII)127 4. Incomplete concordance in MZ twins (no greater than 30%) even when past major period of risk of developing MS129 5. Evidence for association of decreased sunlight exposure, low vitamin D levels, Epstein Bar virus exposure and smoking with MS131

definition of the disease is critical. In the case of MS, it is likely that diverse diseases unified by the occurrence of inflammatory demyelination and axonal loss are classified as MS, making homogeneity a major concern. Only one whole genome association study in MS has been successfully completed7 but innumerable candidate gene studies have been reported.

20.3 THE AUTOIMMUNE HYPOTHESIS, Th1/Th2 CELL BIAS AND ROLE OF CYTOKINES IN MS PATHOGENESIS (FIGURE 20.1) It is widely suspected that MS is an autoimmune disease, although direct evidence supporting this theory is lacking. It is universally accepted that the disease is largely immunemediated. The major arguments in favor of MS being an autoimmune disease are the clinical and pathological analogies with experimental autoimmune encephalomyelitis (EAE), the association with major histocompatibility haplotypes and the presence of oligoclonal bands in CSF, suggesting clonal B cell proliferation in the central nervous system. There is also evidence for clonal expansion of T cells in the blood as well. Both in MS and in EAE, autoreactive T cells have escaped several levels of negative selection. In response to an unknown insult, these autoreactive T cells become activated, ‘‘traffic’’ into the CNS facilitated by adhesion molecules and chemokines followed by a Th1 type cell response which appears to dominate over a Th2 response. This process leads to a cascade of events resulting in inflammatory-demyelination.8,9 Activation of autoreactive T cells may occur within the CNS as well as in the ‘‘periphery’’ (i.e. outside the blood brain barrier) (Figure 20.1). Binding of cytokines to their respective receptors on the T cell membranes plays a pivotal role in conditioning naı¨ ve T cells towards a Th1 or Th2 response. Th1 versus Th2 bias is influenced heavily by the cytokine production profiles of individual cells. For example, binding of IL-12 to its receptor on the T cell membrane activates the cytoplasmic Jak 2 – Stat 4 phosphorylation cascade. Active Stat 4 induces IFNg production leading to a Th1 type cell response. On the other hand, IL-4 results in a cascade wherein Jak 1, 2, 3 is phosphorylated, IL-4 is activated by Stat 6, and IL-5 and IL-10 are produced, thereby inducing a Th2 response. A somewhat simplified concept of MS suggests that

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FIGURE 20.1 Schematic of interaction of cytokines that determine Th1–Th2 bias in autoimmunity and the overall contribution of this bias in determining the balance between demyelination and remyelination. Solid arrows represent change of state while dashed arrows represent effector functions of cytokines. Beginning at the bottom of the figure, CD4 T cells interact with antigen presented in the context of the class II major histocompatibility complex; depending on costimulatory factors expressed on the surface of the macrophage, T cell activation or anergy/tolerance ensue. Insets define the two major mechanisms of inducing tolerance for autoreactive T cells: activation induced apoptosis mediated by IL2 and clonal anergy through B7–CTLA4 interaction rather than B7–CD28 interaction. Furthermore, the cytokine milieu influences whether a Th1 or Th2 response occurs. Activated T cells are able to enter the CNS, where they are restimulated by professional antigen presenting cells of the CNS, especially microglia. Activated T cells orchestrate the inflammatory process by activating or regulating it, in part mediated via competing action of cytokines and by production of chemokines that attract specific cell populations. Additional effector mechanisms are mediated by CD8 cells that dominate the inflammatory cell infiltrate in MS. The cycle of myelin destruction and repair determines the extent of axonal injury that leads to the permanent neurological impairments that occur in patients with MS.

pro-inflammatory cytokines such as TNFa and IFNg are detrimental while immunoregulatory cytokines such as IL-4 and IL-10 are favorable (Figure 20.1). These observations are supported by multiple studies in the animal models and in patients with MS.10 The Th1/Th2 paradigm (Th1 cells detrimental and Th2 favorable) is likely stage dependent and target specific. Cytokines may not contribute at all or may contribute only to a minor degree at some stages of MS. They may have opposing effects on the overall disease course depending on their target; for example, TNFa may be toxic to oligodendrocytes with a consequent detrimental effect on MS, yet may enhance apoptosis of

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activated lymphocytes which may yield favorable effects. Oligodendrocyte damage may occur by mechanisms that are not entirely dependent on the Th1/Th2 paradigm such as complement and cytotoxic T cell mediated injury (Figure 20.1). Coincident with ongoing detrimental inflammation, spontaneous remyelination occurs and aspects of the inflammatory response related to cytokines may facilitate remyelination through activation of oligodendrocyte precursors and astrocytes.2,11 IL-1b knock-out mice fail to remyelinate completely.12 TGFb induces microglia to secrete hepatocyte growth factor (HGF) leading to chemotaxis of oligodendrocyte precursors.13 Inhibition of spontaneous remyelination may be as important as the inflammatory-demyelinating effects of cytokines. Polyclonal human immunoglobulins or specific human monoclonal antibodies can accelerate the rate of CNS remyelination.14 Thus, the ‘‘Th1 favorable/Th2 unfavorable’’ paradigm is a starting point in the understanding of inflammation in MS but an oversimplified one. Although the determinants of whether a pro-inflammatory or anti-inflammatory/ immunoregulatory immune response will be mounted in a given individual are unknown, cytokines and chemokines seem to mold, or at least reflect the nature of the cellular immune response active at a given time. Therefore, cytokines have been attractive candidate genes with the assumption that polymorphisms that alter cytokine expression levels may collectively or individually condition an immune response to a common insult differently in different individuals. Manipulation of the cytokine milieu has therapeutic implications both in MS and other autoimmune disorders.15

20.4 ESTABLISHING THE ROLE OF CYTOKINE POLYMORPHISMS IN MS A number of difficulties arise when attempting to interpret how cytokines influence MS. Cytokine expression is often very dynamic and transient; cytokines exert their effects close to the target cells or tissues and measurement of systemic levels may be unrevealing; expression is often influenced by the prevailing milieu and stimuli to the immune system, and a steady state rarely exists. The downstream effects of a cytokine may be dependent on interaction of multiple cytokines and multiple cytokines may serve a similar function. Therefore it may be difficult to extrapolate results from in vitro expression studies with a controlled environment to disease processes. Cytokine polymorphisms may modify susceptibility to MS, the course of established MS or both.4 Crude measures of susceptibility or ultimate disease-related disability may be not sufficiently sensitive to detect the effect of the cytokine. The ultimate effect of a cytokine polymorphism may depend on the effect of a cytokine on an entire effector pathway rather than its effect on expression of the individual cytokine; therefore multiple polymorphisms in effector molecules downstream or upstream of a given cytokine may act in conjunction, making it difficult to establish an association between a specific cytokine polymorphism and an endpoint, particularly one as complex as a clinical phenotype. Most studies to date have utilized gross clinical outcome measures such as presence or absence of disease, disease course and disease severity (see examples below). However, it is likely that intermediate outcome measures such as MRI effects, particularly repeated measures such as frequency of new lesions, and pathologic studies, including immunopathological detection of cytokine expression, may be more sensitive to the potential effects of genomic variation in cytokines. However, pathological databases to address these issues are very rare, while data on more distant clinical outcomes are routinely collected by clinical investigators evaluating patients with MS, which explains in large part why such disease outcomes as classification disease stage (relapsing remitting versus progressive) and scores on disability scales indexed to time are the predominant endpoints considered by those investigating the

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contribution of cytokines in MS. Considering possible stage-dependent effects of cytokines, patients in later stages of MS with lesser or no evidence of ongoing inflammation may be less informative for study. Another potential confounding factor is differential expression of cytokines between men and women, that may interact with the disease process and possibly genotype.16,17

20.5 EXAMPLES OF GENETIC STUDIES ON CYTOKINES IN MS A variety of cytokines have been studied in association with MS predominantly within the context of ‘‘Th1 favorable/Th2 unfavorable’’ paradigm, a hypothesis largely derived by extrapolation from studies in EAE. Several cytokines believed to play key roles in generating or mediating the effects of the Th1/Th2 dichotomy have been studied as candidate genes in MS. Replication of findings among investigators has been problematic. This is likely explained by the multitude of biological contributions to the clinical endpoints as described above, which may lead to false negative results, as well as due to the large number of inherent comparisons of genotype data with the clinical outcome data with its consequent tendency for generating false positive results. We will discuss several examples of key cytokines pertinent to the Th1/Th2 paradigm. A few cytokines still hold promise as candidate genes for MS.

20.5.1 INTERFERON GAMMA Interferon-gamma (IFNg) is secreted primarily by naı¨ ve T and Th-1 cells. IFNg stimulates Th-1 clonal expansion and inhibits Th-2 expansion therefore playing a pivotal role in autoimmunity and MS.8,9 IFNg expression is increased in EAE in parallel to disease severity.18,19 Transgenic mice overexpressing IFNg in the central nervous system under the control of an oligodendrocyte-specific promoter develop extensive primary demyelination compared to wild type mice.20,21 IFNg may exert deleterious effects directly on myelinating cells but also through MHC expression and activation of macrophages and microglia.22 IFNg also induces dendritic retraction and inhibits synapse formation.23 However, whether the increased IFNg expression is a deleterious or a disease limiting response in EAE is unclear. IFNg receptor knockout mice are more susceptible to EAE than wild-type mice and develop a progressive form of EAE.24–26 The paradoxical roles of IFNg may be due to the regulator functions of IFNg on T cell proliferation and apoptosis.27,28 Upstream control of IFNg production via STAT4 and STAT6 seem to have a direct role in induction or resistance in EAE, respectively.29 The study of IFNg illustrates the multifaceted effects of a cytokine on the pathogenesis of EAE. MS is an even more complex disease than EAE which is an imperfect model of MS (Figure 20.1). Nevertheless, similar to EAE, IFNg expression increases in the two weeks preceding attacks of MS and treatment with exogenous IFNg is deleterious to patients with MS.30–32 Low levels of IFNg expression by lymphocytes at the initiation of treatment with IFNb, a standard relapse-preventative treatment for MS, predicts a favorable response to treatment.33 IFNg expression is higher in individuals who are HLA 1, 2 or 6 positive but lower in individuals who are HLA DR 3, 4, 5, or 7 positive.34 There are gender differences in Th1/Th2 bias in MS and this seems to be reflected in the relevant cytokine productions (i.e. IFNg and IL-5). Women with MS have higher IFNg expression yet lower IL-5 response in response to PLP stimulation than men with MS and women controls, suggesting a skew toward Th1 response in women with MS.17 We and others have recently shown that several polymorphisms of IFNG and the haplotypes formed between them are associated with susceptibility to MS possibly in a gender dependent fashion.16,35–37 The specific

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polymorphism of IFNG that is associated with decreased risk of MS in men is also associated with increased expression of IFNg.38–40 Others have not confirmed an association between IFNG polymorphisms and MS in other populations.41–44 IFNg likely has a dual role in activation and regulation of immune response in EAE and MS. Evidence is insufficient regarding disease stage dependence of this process to reach final conclusions about whether IFNg contributes to the excess of women compared to men with MS. Study of IFNG polymorphisms and their effects on IFNg expression may better clarify the role of this cytokine on disease susceptibility.

20.5.2 INTERLEUKIN 12 (IL-12) IL-12, like IFNg, stimulates differentiation and proliferation of Th1 cells. IL-12 levels increase prior to relapses in EAE.45 This, however, is true only for the p40 subunit of the IL-12 heterodimer produced by monocytes and dendritic cells.46 IL-12 deficient mice are resistant to induction of EAE, while EAE resistant mice strains can be made susceptible by transfer of IL-12-treated lymphocytes.47 Exogenous IL-12 induces relapses in EAE.48 Despite similarities to actions of IFNg, IL-12 levels seem to correlate more closely with a detrimental immune response in EAE, independent of IFNg.49 In MS, IL-12 p40 subunit is expressed in plaques. and mRNA expression in unstimulated peripheral blood mononuclear cells is higher in patients with bout-onset disease course than controls.50,51 Despite initial reports that a 30 polymorphism may be associated with decreased risk of MS in two separate population-association studies, a recent family association study using transmission disequilibrium testing has refuted this association.52–54 However, larger studies in well-characterized populations are needed before a definite conclusion can be reached. Whether the observed increase in IL-12 expression in MS is determined by polymorphisms or mutations of IL12 is not known.

20.5.3 TUMOR NECROSIS FACTOR ALPHA (TNFa) TNFa is an acute phase reactant produced by several types of mononuclear cells including activated T cells, natural killer cells, B cells, and other antigen presenting cells in the CNS as well as astrocytes. Although TNFa is generally accepted to be associated with a Th1 type cell response it is responsible for induction of a multitude of immune cells, cytokine, and chemokine production. Increased TNFa expression is associated with an unfavorable disease course in EAE; exogenous TNFa augments the immune response, increasing the severity of cellular infiltration of the CNS and prolonging the course of EAE.55,56 TNFa induces oligodendrocyte apoptosis in the CNS.57 Paradoxically, homologous disruption of TNFA in mice leads to a higher mortality and more severe inflammatory demyelination in MOG-induced EAE, compared to mice with native TNFA.58 The effects of TNFa may depend in part on the differential sensitivity of TNFa receptors to TNFa, which may lead to differential effects on CNS inflammation.10 TNFR1 is a death receptor for T cells and knockout of this receptor leads to milder EAE while TNFR2 knockout leads to more severe EAE compared to mice with native receptors.59 TNFa may have a dual role in EAE pathogenesis by inducing a protracted inflammation that is beneficial and by inducing oligodendrocyte apoptosis which is detrimental. TNFa expression is increased in MS lesions, precedes attacks of MS and correlates with MRI activity as well as disease course in MS.31,60–64 TNFa production may be higher in individuals carrying the major histocompatibility complex MHC alleles HLADR2 or HLADR3.34,65 Given the high degree of linkage disequilibrium in the MHC locus that harbors the DR-DQ haplotype as well as TNFA, it is possible that this stratification is not due to a functional relationship but rather due to polymorphisms of TNFA that are

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in linkage disequilibrium with HLADR locus. Associations between polymorphisms of TNFA and MS have yielded conflicting results.66 Positive associations were suggested in some studies.67–71 However, several studies have refuted these associations.72–77 Furthermore the TNFA polymorphisms that were previously associated with MS are not associated with TNFa production except in one study where homozygosity for 308 promoter single nucleotide polymorphism was associated with spontaneous expression of TNFa.66,67,78,79 Currently there is no consensus that TNFA polymorphisms are associated with MS.

20.5.4 INTERLEUKIN 1 (IL-1) IL-1 is produced predominantly by mononuclear cells and is up-regulated in the CNS during induction of EAE. Increased expression of IL-1b in the CNS is toxic to neurons possibly through induction of increased nitric oxide production.10,80 IL-1b induces oligodendrocyte apoptosis only in the presence of astrocytes and microglia, likely by impairing glutamate uptake by astrocytes leading to glutamate toxicity.81 On the other hand IL-1b also seems to have a dual effect during the immune response; by stimulating nerve growth factors (e.g. IGF1), IL-1b may facilitate oligodendrocyte regeneration and remyelination.12,82 IL-1 receptor antagonist (IL-1ra) opposes the effects of IL-1b. IL1B and IL1RN are in linkage disequilibrium over an extraordinary distance of 360 kb.83 IL1B polymorphisms have been associated with disease severity in MS despite a lack of association with susceptibility to disease.83,84 However, a recent study failed to support these associations.85 The IL1B allele associated with higher IL-1b expression in LPS stimulated monocyte cultures was associated with a favorable course of MS (disability indexed to time).83,86 On the other hand the IL-1RN allele associated with relatively high expression from stimulated monocytes in vitro was associated with an unfavorable course in MS.87–90 Families with a higher IL-1b/IL-1ra expression ratios in endotoxin stimulated whole blood analyzed by ELISA have a higher chance of having other members with relapsing-remitting MS independent of the IL1B or IL1RN polymorphisms associated with disease severity.91 IL-1b/IL-1ra expression ratio is significantly lower in patients with primary progressive MS than in those with relapsing-remitting MS.92 Associations between IL-1B and MS remain to be clarified both from the standpoint of whether there is an association of genotype or with levels of expression. Lack of consensus may arise from multifaceted effects of IL-1b which may be dependent on the stage of the disease.

20.5.5 INTERLEUKIN 4 (IL-4) IL-4 is produced predominantly by Th2 cells. Through its receptor and the downstream JAK1,2,3-STAT6 pathway, IL-4 induces IL-4, IL-5, and IL-10 expression amplifying the Th2 bias of the immune response. IL-4 inhibits Th1 cell activation. Endogenous IL-4 production confers resistance to EAE, while neutralization of endogenous IL-4 overcomes resistance to EAE.93,94 IL-4 knockout leads to a more severe EAE phenotype in C57BL/6 and BALB/c mice but transgenic over-expression does not reduce disease severity while in the same system transgenic over-expression of IL-10 confers complete resistance to EAE.95,96 Exogenous IL-4 inhibits the synthesis of IFNg and reduces severity of EAE.97,98 In MS, IL-4 expression is increased in active lesions.63 Treatment with cyclophosphamide increases expression of IL-4.99 Several polymorphisms of IL4 have been studied in association with MS. Allele-2 of a variable number tandem repeat in intron-3 has been associated with older age at onset in MS.100 We recently found a similar trend but also showed that allele-1 may be associated

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with more severe disease.101 However, we also found that two haplotypes including three other polymorphisms spanning IL4 are associated with increased susceptibility to MS independent of the allelic status of the intron-3 polymorphism, suggesting that intron-3 polymorphism only acts as a marker. Further studies are needed to confirm the associations observed in MS. The functional effects of the polymorphisms considered are unknown.

20.5.6 INTERLEUKIN 10 (IL-10) IL-10 is predominantly expressed by Th2 cells but also by monocytes, macrophages, and B cells. IL-10 inhibits MHC expression by antigen presenting cells and co-stimulatory molecule expression by T cells, thereby inhibiting T cell proliferation, and inhibiting IL-1 and TNFa production by macrophages. Following PLP immunization IL-10 expression is sustained during the evolution of EAE.102 Over-expression of human IL-10 is associated with resistance to EAE and exogenous IL-10 reduces severity in EAE by suppressing MHC-II upregulation.103,104 IL-10 knockout mice develop more severe EAE than wildtype mice and exhibit no spontaneous recovery, while IL-4 deficient mice, despite having more severe disease, are able to recover spontaneously.96,105 IL-10 levels are higher in PLP stimulated T cell clones collected during remissions of MS compared to T cell clones collected during acute relapses of MS.106 Serial IL-10 mRNA levels measured in unstimulated peripheral mononuclear cells are lower during exacerbations compared to remission periods in relapsing-remitting MS and are consistently low during secondary progressive phase in MS.51,107 Three haplotypes formed by three promotor polymorphisms of IL10 are associated with IL-10 expression.108 In one study the two non-GCC haplotypes were associated with relatively better response to IFNb treatment as measured by reduction of enhancing MRI lesion load within the first 6 months.109 The promoter polymorphisms may be associated with disease course and severity in MS but not with susceptibility to MS.108,110–114 Despite encouraging data suggesting an association of IL-10 promoter polymorphisms and disease phenotype in MS, the results are conflicting. Further correlation with expression studies and confirmation in other populations with sufficient sample size and power are needed to clarify these associations.

20.6 TARGETING CYTOKINE NETWORKS FOR TREATMENT IN MS Understanding the contributions of individual cytokines to MS pathogenesis, both at a genetic susceptibility level and at a functional level, will further enhance development of disease-specific and stage-specific treatment strategies in MS. Given the roles of cytokines in shifting the immune response in a disease activity dependent manner and redundancies in certain pathways even within the extremely simplified Th1/Th2 paradigm of EAE and MS pathogenesis, it is difficult to imagine that enhancing or inhibiting the expression or function of a single cytokine will result in a measurable effect without having catastrophic effects. Arbitrary classifications as good or bad likely underestimate the fact that depending on the stage of MS, activation of an otherwise detrimental cytokine response may be favorable. Nevertheless, several advances in our understanding of MS pathogenesis have evolved from bold trials of cytokine based therapies, some of which are discussed below.

20.6.1 INTERFERON EXPERIENCE A trial of IFNg to treat MS led to a significant increase in exacerbations compared to pretrial period and was associated with increased circulating monocytes with MHC class II expression.30,115 This experience helped establish the role of detrimental Th1 response

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during periods of increased activity in MS. This experience is one of many observations that paved the way to development of IFNb as a standard treatment modality in MS; one key action of the drug is to down-regulate IFNg-producing cells.33 However, the complexity of the cytokine network is illustrated by the fact that IFNb also suppresses IL-4-producing T cells, which, based on experience in EAE, should also suppress a beneficial response induced by Th2 cells.116 INFb treatment is partially effective in preventing MS relapses; the extent to which treatment with this cytokine-based treatment will prevent long-term disability in MS is yet to be established. Whether this is due to a relatively non-specific antiproliferative effect of IFNb on T cells is unknown. Individual clinical responses to IFNb vary. Cytokine and cytokine receptor responses of individuals to IFNb also vary. Higher levels of soluble tumor necrosis factor 1 and 2 measured serially over the course of a 15 month period of treatment with IFNb-1b correlates with good MRI response.117 Baseline levels of IL-12p35 mRNA in unstimulated whole blood from relapsing remitting patients is lower in non-responders versus responders to IFNb-1b treatment.118 It is possible that a genetic cytokine profile that determines differential response to IFNb exists. Two studies did not find an association between interferon receptor polymorphisms and treatment response in MS.119,120 A recent study of 100 Interferon Stimulated Response Element-containing genes suggested that IFNAR1, LMP7, CTSS and MXA promoter polymorphisms may be involved in response to treatment with INFb.121 This area needs to be further investigated to possibly help with better selection of individuals for this treatment.

20.6.2 CYTOKINE BLOCKADE Assuming that TNFa production by Th1 cells is a key element in MS pathogenesis and based on encouraging data from EAE, a recombinant TNFa blocker, Lenercept, was evaluated in MS. Patients who received Lenercept experienced an increased number of exacerbations.122 Similar products, Etanercept and Infliximab, have been tried in rheumatoid arthritis and Crohn’s disease and some patients receiving these treatments experienced inflammatory-demyelination in the CNS.123,124 TGFb2 has been associated with remissions in multiple sclerosis but was also shown to ameliorate EAE. With the assumption that exogenous TGFb2 could also ameliorate MS exacerbations a phase-1 trial was conducted in secondary progressive MS.125 Unfortunately, almost half of the patients suffered from a reversible decline in glomerular filtration rate while no effect on clinical course was established. The failure of treatment, however, could have resulted from the fact that treated patients were already in a stage of their disease where axonal degeneration, rather than inflammation, was the predominant mechanism of their clinical decline. These experiences underscore the fact that individual targeting of cytokines, which have multifaceted, stage-dependent effects on MS pathogenesis is likely to encounter significant problems, albeit promising due to successes in other autoimmune diseases outside the CNS such as rheumatoid arthritis and Crohn’s disease.126 Several issues, including the immune privileged nature of the CNS and complexity of the immune response in MS compared to other systemic autoimmune disorders may play a role in these problems. However, combined approaches using a ‘‘soup’’ of cytokines to ‘‘tame’’ the immune response in a stage dependent fashion to prevent injury from individual MS exacerbations may be a more feasible, albeit very complex approach. To be successful in treatment of MS, further understanding of the role of cytokine profiles during different stages of MS pathogenesis is necessary. It is likely that patients respond to similar immune insults by different cellular and humoral immune profiles due to inherent genetic factors and different environmental preconditioning of their immune systems. Therefore, elucidating these

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profiles and targeting individuals based on these profiles (pharmacogenomics) remains an elusive but promising future task. Progress to this goal will advance in parallel with advances in technology and biology.

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47. Segal, B. M. and Shevach, E. M., IL-12 unmasks latent autoimmune disease in resistant mice, J. Experimental Medicine, 184, 771, 1996. 48. Smith, T. et al., Interleukin-12 induces relapse in experimental allergic encephalomyelitis in the Lewis rat, Am. J. Pathol., 150, 1909, 1997. 49. Leonard, J. P. et al., Prevention of experimental autoimmune encephalomyelitis by antibodies against interleukin 12, J. Experimental Medicine, 181, 381, 1995. 50. Windhagen, A. et al., Expression of costimulatory molecules B7–1 (CD80), B7–2 (CD86), and interleukin 12 cytokine in multiple sclerosis lesions, J. Experimental Medicine, 182, 1985, 1995. 51. van Boxel-Dezaire, A. H. et al., Decreased interleukin-10 and increased interleukin-12p40 mRNA are associated with disease activity and characterize different disease stages in multiple sclerosis [see comment], Ann. Neurol., 45, 695–703, 1999. 52. Alloza, I. et al., Interleukin-12 p40 polymorphism and susceptibility to multiple sclerosis [comment], Ann. Neurol., 52, 524, 2002. 53. Hall, M. A. et al., Genetic polymorphism of IL-12 p40 gene in immune-mediated disease, Genes and Immunity, 1, 219, 2000. 54. van Veen, T. et al., Interleukin-12p40 genotype plays a role in the susceptibility to multiple sclerosis [see comment], Ann. Neurol., 50, 275, 2001. 55. Issazadeh, S. et al., Cytokine production in the central nervous system of Lewis rats with experimental autoimmune encephalomyelitis: dynamics of mRNA expression for interleukin-10, interleukin-12, cytolysin, tumor necrosis factor alpha and tumor necrosis factor beta, J. Neuroimmunol., 61, 205, 1995. 56. Kuroda, Y. and Shimamoto, Y., Human tumor necrosis factor-alpha augments experimental allergic encephalomyelitis in rats, J. Neuroimmunol., 34, 159, 1991. 57. Akassoglou, K. et al., Oligodendrocyte apoptosis and primary demyelination induced by local TNF/p55TNF receptor signaling in the central nervous system of transgenic mice: models for multiple sclerosis with primary oligodendrogliopathy, Am. J. Pathol., 153, 801, 1998. 58. Liu, J. et al., TNF is a potent anti-inflammatory cytokine in autoimmune-mediated demyelination, Nature Medicine, 4, 78, 1998. 59. Bachmann, R. et al., Impairment of TNF-receptor-1 signaling but not fas signaling diminishes T-cell apoptosis in myelin oligodendrocyte glycoprotein peptide-induced chronic demyelinating autoimmune encephalomyelitis in mice, Am. J. Pathol., 154, 1417, 1999. 60. Selmaj, K. et al., Identification of lymphotoxin and tumor necrosis factor in multiple sclerosis lesions, J. Clin. Invest., 87, 949, 1991. 61. Andrews, T. et al., TNFalpha potentiates IFNgamma-induced cell death in oligodendrocyte progenitors, J. Neurosci. Res., 54, 574, 1998. 62. van Oosten, B. W. et al., Increased production of tumor necrosis factor alpha, and not of interferon gamma, preceding disease activity in patients with multiple sclerosis, Arch. Neurol., 55, 793, 1998. 63. Cannella, B. and Raine, C. S., The adhesion molecule and cytokine profile of multiple sclerosis lesions [see comment], Ann. Neurol., 37, 424, 1995. 64. Spuler, S. et al., Multiple sclerosis: prospective analysis of TNF-alpha and 55 kDa TNF receptor in CSF and serum in correlation with clinical and MRI activity, J. Neuroimmunol., 66, 57, 1996. 65. Zipp, F. et al., Genetic control of multiple sclerosis: increased production of lymphotoxin and tumor necrosis factor-alpha by HLA-DR2þ T cells [see comment], Ann. Neurol., 38, 723, 1995. 66. Bayley, J. P. et al., Is there a future for TNF promoter polymorphisms?, Genes and Immunity, 5, 315, 2004. 67. Huizinga, T. W. et al., TNF-alpha promoter polymorphisms, production and susceptibility to multiple sclerosis in different groups of patients, J. Neuroimmunol., 72, 149, 1997. 68. Drulovic, J. et al., Decreased frequency of the tumor necrosis factor alpha 308 allele in Serbian patients with multiple sclerosis, Eur. Neurol., 50, 25, 2003. 69. Wirz, S. A. et al., High frequency of TNF alleles 238A and 376A in individuals from northern Sardinia, Cytokine, 26, 149, 2004.

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70. Martinez, A. et al., TNF 376A marks susceptibility to MS in the Spanish population: A replication study, Neurology, 62, 809, 2004. 71. Fernandez-Arquero, M. et al., Primary association of a TNF gene polymorphism with susceptibility to multiple sclerosis, Neurology, 53, 1361, 1999. 72. Weinshenker, B. G. et al., Genetic variation in the tumor necrosis factor alpha gene and the outcome of multiple sclerosis, Neurology, 49, 378, 1997. 73. Wingerchuk, D. et al., A population-based case-control study of the tumor necrosis factor alpha 308 polymorphism in multiple sclerosis, Neurology, 49, 626, 1997. 74. Lucotte, G. et al., TNF-alpha polymorphisms in multiple sclerosis: no association with 238 and 308 promoter alleles, but the microsatellite allele a11 is associated with the disease in French patients, Multiple Sclerosis, 6, 78, 2000. 75. Fugger, L. et al., Tumor necrosis factor alpha gene polymorphism in multiple sclerosis and optic neuritis, J. Neuroimmunol., 27, 85, 1990. 76. He, B. et al., Tumor necrosis factor alpha 308 alleles in multiple sclerosis and optic neuritis, J. Neuroimmunol., 63, 143, 1995. 77. Duvefelt, K. et al., A NOTCH4 association with multiple sclerosis is secondary to HLA-DR*1501, Tissue Antigens, 63, 13, 2004. 78. Armstrong, M. A. et al., Relationship between tumor necrosis factor-alpha (TNFalpha) production and a specific multiple sclerosis (MS) associated TNF gene haplotype, Multiple Sclerosis, 5, 165, 1999. 79. Braun, N. et al., Gene polymorphism at position 308 of the tumor-necrosis-factor-alpha (TNF-alpha) in multiple sclerosis and it’s influence on the regulation of TNF-alpha production, Neurosci. Lett., 215, 75, 1996. 80. Downen, M. et al., Neuronal death in cytokine-activated primary human brain cell culture: role of tumor necrosis factor-alpha, GLIA, 28, 114, 1999. 81. Takahashi, J. L. et al., Interleukin-1beta promotes oligodendrocyte death through glutamate excitotoxicity, Ann. Neurol., 53, 588, 2003. 82. Carlson, N. G. et al., Inflammatory cytokines IL-1 alpha, IL-1 beta, IL-6, and TNF-alpha impart neuroprotection to an excitotoxin through distinct pathways, J. Immunol., 163, 3963, 1999. 83. Kantarci, O. H. et al., Association of two variants in IL-1beta and IL-1 receptor antagonist genes with multiple sclerosis, J. Neuroimmunol., 106(1–2), 220, 2000. 84. Schrijver, H. M. et al., Association of interleukin-1beta and interleukin-1 receptor antagonist genes with disease severity in MS, Neurology, 52, 595, 1999. 85. Hooper-van Veen, T. et al., The interleukin-1 gene family in multiple sclerosis susceptibility and disease course, Multiple Sclerosis, 9, 535, 2003. 86. Pociot, F. et al., A TaqI polymorphism in the human interleukin-1 beta (IL-1 beta) gene correlates with IL-1 beta secretion in vitro, Eur. J. Clin. Invest., 22, 396, 1992. 87. de la Concha, E. G. et al., Combined effect of HLA-DRB1*1501 and interleukin-1 receptor antagonist gene allele 2 in susceptibility to relapsing/remitting multiple sclerosis, J. Neuroimmunol., 80, 172, 1997. 88. Sciacca, F. L. et al., Relevance of interleukin 1 receptor antagonist intron 2 polymorphism in Italian MS patients, Neurology, 52, 1896, 1999. 89. Feakes, R. et al., Interleukin 1 receptor antagonist (IL-1ra) in multiple sclerosis, J. Neuroimmunol., 105, 96, 2000. 90. Danis, V. A. et al., Cytokine production by normal human monocytes: inter-subject variation and relationship to an IL-1 receptor antagonist (IL-1Ra) gene polymorphism, Clin. and Experimental Immunol., 99, 303, 1995. 91. de Jong, B. A. et al., Production of IL-1beta and IL-1Ra as risk factors for susceptibility and progression of relapse-onset multiple sclerosis, J. Neuroimmunol., 126, 172, 2002. 92. Schrijver, H. M. et al., Interleukin (IL)-1 gene polymorphisms: relevance of disease severity associated alleles with IL-1beta and IL-1ra production in multiple sclerosis, Mediators of Inflammation, 12, 89, 2003. 93. Karpus, W. J. et al., CD4þ suppressor cells of autoimmune encephalomyelitis respond to T cell receptor-associated determinants on effector cells by interleukin-4 secretion, Eur. J. Immunol., 22, 1757, 1992.

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94. Constantinescu, C. S. et al., Modulation of susceptibility and resistance to an autoimmune model of multiple sclerosis in prototypically susceptible and resistant strains by neutralization of interleukin-12 and interleukin-4, respectively, Clin. Immunol., 98, 23, 2001. 95. Falcone, M. et al., A critical role for IL-4 in regulating disease severity in experimental allergic encephalomyelitis as demonstrated in IL-4-deficient C57BL/6 mice and BALB/c mice, J. Immunol., 160, 4822, 1998. 96. Bettelli, E. et al., IL-10 is critical in the regulation of autoimmune encephalomyelitis as demonstrated by studies of IL-10- and IL-4-deficient and transgenic mice, J. Immunol., 161, 3299, 1998. 97. Peleman, R. et al., Recombinant interleukin 4 suppresses the production of interferon gamma by human mononuclear cells, J. Experimental Medicine, 170, 1751, 1989. 98. Racke, M. K. et al., Cytokine-induced immune deviation as a therapy for inflammatory autoimmune disease, J. Experimental Medicine, 180, 1961, 1994. 99. Smith, D. R. et al., Immune deviation following pulse cyclophosphamide/methylprednisolone treatment of multiple sclerosis: increased interleukin-4 production and associated eosinophilia, Ann. Neurol., 42, 313, 1997. 100. Vandenbroeck, K. et al., Occurrence and clinical relevance of an interleukin-4 gene polymorphism in patients with multiple sclerosis, J. Neuroimmunol., 76, 189, 1997. 101. Kantarci, O. H. et al., A population-based study of IL4 polymorphisms in multiple sclerosis, J. Neuroimmunol., 137(1–2), 134, 2003. 102. Begolka, W. S. et al., Differential expression of inflammatory cytokines parallels progression of central nervous system pathology in two clinically distinct models of multiple sclerosis, J. Immunol., 161, 4437, 1998. 103. Cua, D. J. et al., Transgenic interleukin 10 prevents induction of experimental autoimmune encephalomyelitis, J. Experimental Medicine, 189, 1005, 1999. 104. Rott, O. et al., Interleukin-10 prevents experimental allergic encephalomyelitis in rats, Eur. J. Immunol., 24, 1434–40, 1994. 105. Samoilova, E. B. et al., Acceleration of experimental autoimmune encephalomyelitis in interleukin-10-deficient mice: roles of interleukin-10 in disease progression and recovery, Cellular Immunology, 188, 118, 1998. 106. Correale, J. et al., Patterns of cytokine secretion by autoreactive proteolipid protein-specific T cell clones during the course of multiple sclerosis, J. Immunol., 154, 2959, 1995. 107. Rieckmann, P. et al., Cytokine mRNA levels in mononuclear blood cells from patients with multiple sclerosis, Neurology, 44, 1523, 1994. 108. de Jong, B. A. et al., Frequency of functional interleukin-10 promoter polymorphism is different between relapse-onset and primary progressive multiple sclerosis, Human Immunol., 63, 281, 2002. 109. Wergeland, S. et al., IL-10 promoter haplotype influence on interferon treatment response in multiple sclerosis, Eur. J. Neurol., 12, 171, 2005. 110. Luomala, M. et al., Promoter polymorphism of IL-10 and severity of multiple sclerosis, Acta Neurol. Scand., 108, 396, 2003. 111. Myhr, K. M. et al., Interleukin-10 promoter polymorphisms in patients with multiple sclerosis, J. Neurol. Sci., 202, 93, 2002. 112. Almeras, L. et al., Interleukin-10 promoter polymorphism in multiple sclerosis: association with disease progression, Eur. Cytokine Network, 13, 200, 2002. 113. He, B. et al., Linkage and association analysis of genes encoding cytokines and myelin proteins in multiple sclerosis, J. Neuroimmunol., 86, 13, 1998. 114. Martinez Doncel, A. et al., Interleukin-10 polymorphisms in Spanish multiple sclerosis patients, J. Neuroimmunol., 131, 168, 2002. 115. Panitch, H. S. et al., Exacerbations of multiple sclerosis in patients treated with gamma interferon, Lancet, 1, 893, 1987. 116. Furlan, R. et al., Interferon-beta treatment in multiple sclerosis patients decreases the number of circulating T cells producing interferon-gamma and interleukin-4, J. Neuroimmunol., 111, 86–92, 2000.

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117. Laske, C. et al., Induction of sTNF-R1 and sTNF-R2 by interferon beta-1b in correlation with clinical and MRI activity, Acta Neurol. Scand., 103, 105, 2001. 118. van Boxel-Dezaire, A. H. et al., Contrasting responses to interferon beta-1b treatment in relapsing-remitting multiple sclerosis: does baseline interleukin-12p35 messenger RNA predict the efficacy of treatment?, Ann. Neurol., 48, 313, 2000. 119. Sriram, U. et al., Pharmacogenomic analysis of interferon receptor polymorphisms in multiple sclerosis, Genes and Immunity, 4, 147, 2003. 120. Leyva, L. et al., IFNAR1 and IFNAR2 polymorphisms confer susceptibility to multiple sclerosis but not to interferon-beta treatment response, J. Neuroimmunol., 163, 165, 2005. 121. Cunningham, S. et al., Pharmacogenomics of responsiveness to IFN-treatment in multiple sclerosis: A genetic screen of 100 Type I IFN-inducible genes, Clin. Pharmacol. Therapeutics (in press). 122. The Lenercept Multiple Sclerosis Study Group and The University of British Columbia MS/MRI Analysis Group (anonymous), TNF neutralization in MS: results of a randomized, placebo-controlled multicenter study. The Lenercept Multiple Sclerosis Study Group and The University of British Columbia MS/MRI Analysis Group [see comment], Neurology, 53, 457, 1999. 123. Mohan, N. et al., Demyelination occurring during anti-tumor necrosis factor alpha therapy for inflammatory arthritides [see comment], Arthritis and Rheumatism, 44, 2862, 2001. 124. Sicotte, N. L. and Voskuhl, R. R., Onset of multiple sclerosis associated with anti-TNF therapy, Neurology, 57, 1885, 2001. 125. Calabresi, P. A. et al., Phase 1 trial of transforming growth factor beta 2 in chronic progressive MS, Neurology, 51, 289, 1998. 126. Atzeni, F. et al., Potential off-label use of infliximab in autoimmune and nonautoimmune diseases: a review, Autoimmun. Rev., 4, 144, 2005. 127. Weinshenker, B. G., Epidemiology of multiple sclerosis, Neurol. Clin., 14, 291, 1996. 128. Ebers, G. C. et al., A genetic basis for familial aggregation in multiple sclerosis. Canadian Collaborative Study Group [see comment], Nature, 377, 150, 1995. 129. Sadovnick, A. D. et al., A population-based study of multiple sclerosis in twins: update, Ann. Neurol., 33, 281, 1993. 130. Oksenberg, J. R. and Hauser, S. L., Genetics of multiple sclerosis, Neurol. Clin., 23, 61–75, 2005. 131. Marrie, R. A., Environmental risk factors in multiple sclerosis aetiology, Lancet Neurology, 3, 709, 2004.

21

Type 1 and 2 Diabetes Regine Bergholdt and Flemming Pociot

CONTENTS 21.1 21.2 21.3 21.4 21.5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Type 1 Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Type 2 Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anti-Inflammatory Agents in the Treatment of Diabetes . . . . . . . . . . . . . . . . . . . . . . Genetic Aspects of the Inflammatory Model for the Pathogenesis of T1D and T2D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.6 Cytokine Gene Polymorphisms in Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.7 Future Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

305 306 308 310 310 310 313 313

21.1 INTRODUCTION Diabetes is an increasing worldwide health problem. It is estimated that the prevalence of diabetes doubles every 15 years and that by year 2010 there will be more than 220 million people affected with diabetes.1 Diabetes mellitus represents a heterogeneous group of disorders. Some distinct diabetic phenotypes can be identified in terms of specific etiology and/or pathogenesis, but in many cases overlapping phenotypes make etiological and pathogenic classification difficult. Type 1 (insulin-dependent) diabetes mellitus (T1D) [MIM #222100] develops as the result of pancreatic b-cell destruction and is characterized by absolute insulin deficiency, an abrupt onset of symptoms, proneness to ketosis, and dependency on exogenous insulin to sustain life. It is the most common form of diabetes among children and young adults in populations of European origin, where the prevalence is approximately 0.4%. Type 2 diabetes mellitus (T2D) [MIM #125853] is the result of insufficient insulin production to maintain normoglycemia in the face of insulin resistance and may develop gradually over years. T2D comprises 85–90% of all diabetes, and also an increasing incidence of T2D is seen in children and adolescents. T1D and T2D are generally considered to be two distinct diseases in terms of etiology, genetics and pathogenesis. Increasing evidence, however, links T1D and T2D,2–5 and there is accumulating evidence that inflammatory mediators are of importance in the pathogenesis of both diseases. In both T1D and T2D b-cell loss may be a consequence of apoptosis and necrosis induced by inflammatory mediators. In T1D, b-cell destruction is a result of an immune-mediated reaction towards the b-cell. Pro-inflammatory cytokines are released during inflammation of the pancreatic islet and in synergy they lead to induction of apoptosis and necrosis of b-cells.6 In T2D, b-cell deficit and increased b-cell apoptosis have also been reported.7 Cytokines induce also insulin resistance in peripheral tissues,8–10 and elevated circulating levels of pro-inflammatory cytokines in recent onset T2D subjects have been reported.11–13 In addition, hyperglycemia in T2D patients is accompanied by increased levels of pro-inflammatory cytokines.11 Thus, cytokines produced locally as part of the 305

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FIGURE 21.1 Important pathways changed in expression profiling studies after cytokine-exposure of beta-cells. Cytokine receptor binding and activation of the cytokine-signaling pathways influence several different pathways demonstrating that the energy generation, insulin production/b-cell function and cellular defense are decreased, whereas the nitrite oxide (NO) production, cytokine-signaling, apoptosis and cellular repair are increased.

autoimmune infiltrate of the pancreatic islets in T1D or expressed in b-cells and/or at high levels in circulation in T2D may be a common pathogenetic denominator in b-cell failure of the two diseases (Figure 21.1). It is well documented that cytokine production and action are under genetic influence and thus it can be expected that cytokine gene polymorphisms may contribute to both T1D and T2D risk.

21.2 TYPE 1 DIABETES In the past 20 years, in vitro and animal studies have underlined the importance of inflammatory mediators in the pathogenesis of T1D.14–16 Pro-inflammatory cytokines are present early in the inflammatory infiltrate of the pancreatic islets in animal models of human T1D, and antagonists of pro-inflammatory cytokines prevent diabetes development in such models.14 Combinations of the pro-inflammatory cytokines, IL-1b, IFN-g, TNF-a, and IL-6, are synergistically cytotoxic to b-cells in rodent islets by inducing a mixture of b-cell necrosis and apoptosis in human islets mainly by inducing b-cell apoptosis. Thus immune-mediated T1D can be considered an inflammatory disease of the pancreatic islet.17 Based on the above observation(s), an inflammatory model for the pathogenesis of T1D has been suggested as depicted in Figure 21.2. The model suggests that environmental factors, e.g. in the form of common viruses, induce a MHC Class I restricted presentation of b-cell antigen. This antigen is recognized by CD8þ T cells that cause a limited MHC Class I restricted b-cell damage, either via cytotoxic cytokines as secreted IFN-g and/or

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FIGURE 21.2 The inflammatory model for the pathogenesis of T1D. For explanation see text.

TNF-a or the perforin/granzyme system. b-cell components, such as insulin or GAD (glutamic acic decarboxylase), possibly in forms modified by cytokine-induced reactive oxygen species that are more immunogenic, are released.18 These modified peptides/proteins are taken up by dendritic cells in the islets and transported to regional pancreatic lymph nodes, where the antigens are processed and presented to CD4þ T cells. Following clonal expansion, the CD4þ T cells home to the islets. The activated CD4þ T cells will recruit and activate specific as well as non-specific inflammatory cells that then build up the inflammatory insulitis infiltrate. The effector phase of the b-cell destruction is mediated by cytokines via induction of pro-apoptotic signaling selectively in b-cells and/or by inducing b-cell expression of Fas, marking the b-cells for MHC Class II non-restricted CD4þ T cell mediated killing via interaction between the Fas ligand on CD4þ T cells and Fas on the b-cells. The form of b-cell death induced by cytokines is mostly apoptotic, but also necrotic cell death is observed in rodent b-cells upon cytokine exposure.14 The signaling pathways elicited by receptor binding of IL-1b, TNF-a, and IFN-g are complex and not completely understood. Although certain signaling elements may be shared to some extent, these cytokines utilize discrete signal transduction pathways. IL-1b, TNF-a, and IFN-g bind to their respective receptors on the cell surface leading to induction of several, but distinct, signaling cascades resulting in activation of various transcription factors, thereby leading to altered gene-expression. The signaling pathways for IL-1b include activation of mitogenactivated protein kinases (MAPK)19,20 and activation of the transcription factor NFkB.21,22 The latter pathway is in addition commonly utilized by TNF-a.23 IFN-g signaling involves, first and foremost, induction of Janus tyrosine kinases (JAK) leading to activation of signal transducers and activators of transcription-1 (STAT-1).24 NFkB, STAT-1, and other cytokine induced transcription factors, induce alterations in the regulation of several genes and consequently protein expression. Possibly, as a result of its degree of specialization, the differentiated b-cell is highly susceptible to deleterious signaling by IL-1b, TNF-a,

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and IFN-g. The action or impact of the individual signaling elements and resulting response have been dissected to some extent and have provided valuable information about the complex mechanisms underlying cytokine mediated b-cell destruction (i.e. aspects of T1D at the molecular level).

21.3 TYPE 2 DIABETES Since it was first proposed that inflammation and activated innate immunity might play a role in the pathogenesis of T2D,25 several studies have addressed the role of markers of inflammation, e.g. cytokines, in the development of T2D.26 Markers of inflammation are associated with T2D and features of the metabolic syndrome in cross-sectional studies. In several studies, IL-6 and TNF-a are positively correlated with measures of insulin resistance and/or plasma insulin concentrations, body mass index (BMI), and circulating triglycerides.27–29 Circulating levels of cytokines also predict the development of T2D. This has been consistently shown in several ethnic and different risk groups.13,30–32 Most studies have shown that IL-6 is elevated and in the prospective, population-based EPIC-Postdam study, IL-6 was shown to be an independent predictor of T2D after adjustment for age, gender, BMI, WHR (waist–hip ratio), sports, smoke status, social status, alcohol consumption, and HbA1c.13 Interestingly, a significant interaction between IL-6 and IL-1b was shown to predict the highest risk.13 Circulating pro-inflammatory cytokines released from adipose tissue, inflammatory cells, working muscles, and even b-cells have numerous actions of potential relevance for T2D pathogenesis (Figure 21.3). The ability of cytokines to induce insulin resistance in peripheral tissues is well established and appears, at least in part, to be mediated through disruption of insulin signaling through the insulin receptor/IRS (insulin receptor substrate) pathway. The two major pro-inflammatory cytokines, implicated in T2D pathogenesis/ insulin resistance, are TNF-a and IL-6. It has also been suggested that anti-inflammatory cytokines as IL-4 and IL-10 might prevent or delay onset of T2D.33,34 Cytokines may also play a role in the pathogenesis of T2D by direct effects on the b cell. Most individuals with T2D, whether obese or lean, show a net decrease in b-cell mass.7 Chronic elevated glucose concentrations may lead to induction of IL-1b within the islets,5 thus paralleling the scenario discussed above in relation to T1D pathogenesis. TNF-a, IL-1b, IL-6, and IFN-g can induce b-cell apoptosis through induction of signaling pathways that activate, e.g. NFkB.35 However, they may also activate signaling pathways that trigger increased degradation of insulin receptor substrate (IRS)-2 (Figure 21.4). Both IRS-1 and IRS-2 are expressed in pancreatic b-cells. However, IRS-1 is not involved in the control of b-cell mass,36 but instead appears to function in cellular Caþþ homeostasis.37 In contrast, IRS-2 plays a critical role in regulation of b-cell growth.36,38,39 IL-6 and IFN-g activate the JAK/STAT signaling pathway, which leads to increased expression of SOCS-1 and SOCS-3 proteins (suppressors of cytokine signaling). These SOCS proteins will inhibit JAK/STAT signaling by binding to the cytokine receptors. SOCS-1 and SOCS-3 also bind to the C-terminus of IRS molecules leading to their ubiquitination and subsequent degradation.40,41 Thus, it is conceivable that, for example, IL-6 may cause b-cell apoptosis by decreasing b-cell IRS-2 levels through a similar mechanism. IL-1b and TNF-a promote activation of the protein kinase IkK. IkK phosphorylates the cytosolic inhibitory protein IkB, resulting in release and activation of NFkB.35 IkK also phosphorylates IRS molecules leading to their degradation42 and ultimately b-cell apoptosis (Figure 21.4). A decrease in IRS-2 expression causes insulin resistance in insulin-responsive tissues.36,39,43 Thus, there are parallels between the molecular mechanisms that control insulin sensitivity and those that promote b-cell survival. If these mechanisms go awry, then the balance between insulin

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FIGURE 21.3 Potential relevance of pro-inflammatory cytokines in T2D. Nutrients may promote pro-inflammatory cytokines acting directly on b-cells, e.g. glucose, which in itself induce production of IL-1b from b-cells, and furthermore via increased free fatty acids stimulation of cytokines as TNF-a and IL-6, and the hormone leptin from adipocytes. These substances may also activate the innate immune system, of which effector molecules as C-reactive protein (CRP), plasminogen activator inhibitor (PAI), fibrinogen etc. may have an effect on b-cells as well. As mentioned in the text IL-6 production from muscle and liver probably is important in processes leading to b-cell apoptosis, whereas the exact role of autoimmunity is not clear.

FIGURE 21.4 Cytokine-induced signaling pathways in the b-cell that may lead to increased apoptosis in T2D pathogenesis. For explanation see text.

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Cytokine Gene Polymorphisms in Multifactorial Conditions

resistance and compensatory b-cell mass will become ever more disrupted, accelerating the onset of T2D.

21.4 ANTI-INFLAMMATORY AGENTS IN THE TREATMENT OF DIABETES To further support a role of cytokines in the pathogenesis of diabetes an effect on the molecular processes leading to both T1D and T2D should be expected following treatment with anti-inflammatory agents. Indeed, observations already in the 19th century indicated that high doses of salicylates were able to lower glycosuria in diabetic patients.44 Based on the model of T1D pathogenesis presented in this chapter, the most obvious strategy for intervention includes immunosuppression. Agents such as cyclosporine45 are able to arrest the development of the disease, but carry too many demonstrable and theoretical side effects to be useful as lifelong therapy. Less potent immunosuppression regimens have not consistently shown to be effective in T1D. Interestingly, several drugs used in the treatment of T2D patients have, in addition to their primary therapeutic target, anti-inflammatory properties. Statins have a cholesterol independent anti-inflammatory effect.46 Glitazones (PPARg agonists) are also antiinflammatory by inhibiting cytokine production and macrophage activation.47,48 Cytokine effects on peripheral tissues are also countered by PPARg agonists. Thus the beneficial effects of these drugs in T2D treatment may in part be due to their anti-inflammatory properties.

21.5 GENETIC ASPECTS OF THE INFLAMMATORY MODEL FOR THE PATHOGENESIS OF T1D AND T2D Both T1D and T2D are considered complex genetic diseases where several genes together with unknown environmental factors determine disease risk. It can be suspected that several of the events outlined in the models above for both T1D and T2D are under genetic control. Here we will focus only on the contribution of polymorphisms in cytokine genes presumed to directly influence the pathogenetic process as shown in the models (Figure 21.2 and Figure 21.3). In Table 21.1, the reported T1D and T2D associated candidate gene polymorphisms are listed, as well as their chromosomal position.49–109 For some of the polymorphisms a functional effect has been demonstrated, e.g. a correlation between specific alleles and the expression level of the transcript and/or protein or to promoter activity, suggesting a functional significance (see Table 21.1). The basis of most of these polymorphisms are dealt with in separate chapters of this volume.

21.6 CYTOKINE GENE POLYMORPHISMS IN DIABETES Specific alleles of the interleukin-1b gene, IL1B, the interleukin-1 receptor antagonist gene, IL1RN, and the interleukin-1 receptor type 1 gene, IL1RI, polymorphisms are significantly associated with T1D,49,51,54,55,57 and it has been examined whether diseaseassociated alleles have quantitative consequences for the synthesis and secretion of the peptides. Assessment of composite haplotypes of IL1A, IL1B and IL1RI seems to give the best prediction,110–113 an approach also used in studies of the IL-1 gene cluster in other diseases, e.g. peridontitis114–117 and gastric cancer.118 For the IL1B þ 3954 C/T polymorphism a clear allele-dosage effect of the T1D associated T allele has been demonstrated in LPS stimulated monocytes, with higher IL-1b secretion when this allele

12q14 6p21.3

5q31.1-q33.1 7p21 1q31-q32

16p12.1-p11.2

11q22.2-q22.3

IFNG TNFA

IL12B IL6 IL10

IL4R

IL18

Yes Yes Yes Yes/No Yes/No

Pos.þ375 A/C Pos.þ389 G/T Pos.
3223 C/T Pos.
607 C/A Pos.
137 G/C

Yes/No Yes/No (Yes) Yes/No Yes Yes Yes Yes

Pos.
308 A/G Pos.
238 G/A Pos.
863 C/A Pos.
174 G/C Pos.
598 A/G Pos.
634 C/G Pos.þ358 A/C Pos.
1082 G/A

6p21.3

7p21

1q21.3 1q31-q32

IL6

IL6R IL10

Association

Yes Yes Yes/No Yes Yes Yes/No Yes Yes/No Yes/No Yes/No Yes

Pos.þ3954 C/T Pos.
511 C/T Intron 2, 86 bp repeat 50 UTR (PstI) 50 UTR (HinfI) Intron 1, CA-repeat Microsatellite Pos.
308 A/G Pos.þ1159 C/A (30 UTR) Pos.
174 G/C Microsatellite (Pos.
1.1 kb)

Position in Gene

Association

Position in Gene

TNFA

Chr. Position

2q14.2 2q12

IL1RN IL1R1

T2D Gene

2q14

Chr. Position

IL1B

T1D Gene

A-allele associated with lower IL-10 production

G-allele assocates with higher IL-6 production

Allele dosage effect Allele dosage effect at transcriptional level A-allele decreased in 1.degree relatives of T2D, and associates with decreased expression and secretion Allele dosage effect

Functional Significance/Remarks

Opposite allele of that demonstrated associated to allergy and asthma

Allele dosage effect 2-allele: Increased in vitro expression Specific alleles correspond to different expression-levels Association independent of HLA demonstrated Conflicting Allele dosage effect Association of same allele as in studies of Multiple Sclerosis and Rheumatoid Arthritis

Allele dosage effect on LPS stimulation. T-allele: Increased production Effect on IL-1 secretion 2-allele: Increased expression, 1/1 genotype: Reduced expression

Functional Significance/Remarks

92,98–105 98,105 106 107–109 88

12,87–93 89,91,93–96 97

References

80,81 80,81 82 79,83–86 79,83–86

51–53 54–56 57 58–62 63–65 66–68 69–75 76,77 78,79

49,50

References

TABLE 21.1 Cytokine Gene Polymorphisms Associated to T1D and T2D, as Well as Their Chromosomal Position. For Some of the Polymorphisms a Functional Effect Has Been Demonstrated, e.g. a Correlation between Specific Alleles and the Expression Level of the Transcript and/or Protein or to Promoter Activity, Suggesting a Functional Significance

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Cytokine Gene Polymorphisms in Multifactorial Conditions

is present, and highest when present in duplicate.49 Similarly, T1D patients homozygous for the disease-associated allele of the IL1RN gene had lower circulating levels of IL-1RA,51 whereas increased IL-1RA levels have been found for the 2-allele.52,53 In the IL1RI gene, a polymorphism in the 50 UTR showed linkage to T1D and significant differences in IL-1RI plasma-levels correlated to genotype.57 These studies suggest genetic regulation of monokine antagonism in T1D. In both types of diabetes pro-inflammatory mediators are believed to be able to trigger a common pathway leading to b-cell apoptosis (see above and reviewed in Ref. 35). Individuals with elevated levels of IL-1b have, in a prospective study, been shown to be at increased risk of developing T2D.13 Furthermore, in human islets glucose-induced b-cell apoptosis has been demonstrated to be mediated by b-cell production and secretion of IL-1b.5 Surprisingly, there is, however, a pronounced lack of genetic studies evaluating T2D and genes in the IL-1 gene cluster. A few studies have evaluated and demonstrated association of polymorphisms of IL1B, IL1A, and IL1RN with sub-phenotypes as T2Dnephropathy and T2D with cardiovascular disease.119–121 Functional effects of some of the variants of the interferon-gamma gene, IFNG, and the tumor necrosis factor-alpha gene, TNFA, have been demonstrated (see Table 21.1). Regarding TNFA polymorphisms, although different expressions of different genotypes have been observed,63,66,94,97,122 effects independent of HLA class II are difficult to demonstrate. However, data supports TNFA as important, genetically and functionally, in T1D as well as T2D. The promoter polymorphism at position
308 is the most extensively studied and established, in terms of functional significance and HLA-independent association (see Table 21.1). The significance of another cytokine gene, the IL12B gene in T1D, is not yet clear. Association has been shown in some T1D populations69 but not in several others70–75 suggesting genetic heterogeneity. Functional studies on IL12B variants have been conflicting as well.69,71,75,123 The significance of this cytokine gene has to our knowledge not been evaluated in T2D populations. The action of another cytokine gene, the interleukin-6 gene, IL6, via its receptor complex, is also believed to be under genetic control, and it is likely that variants in the genes encoding IL-6 and its receptor may regulate IL-6 action at different levels. Several studies have evaluated genetic variants in the human IL6 gene in T1D and T2D (Table 21.1). Findings have, however, been quite conflicting. In T1D the C allele of the most studied promoter SNP,
174 G/C, seems convincingly associated to T1D, at least in females.76 Others have, in smaller studies, demonstrated association to T1D in general,77 although others could not demonstrate association.124 Also findings in T2D have been contradictory, although several studies have reported an association of the
174 G-allele with T2D.98,103,104 Others have not been able to confirm this,101,105,125 and in addition, some have even demonstrated an association with T2D of the C-allele, although only in obese T2D.102,104 Data on other promoter polymorphisms of IL6 in T2D, some in LD with the
174 SNP, have also been inconsistent.98,105,106 In conclusion, genetic variance in the IL6 promoter region confer risk to T1D and T2D. However, data are differing and further studies are needed for clarification. Also data on the functional consequences of the
174 SNP are not simple to interpret. The postulated ‘‘high’’ and ‘‘low’’ producing alleles, corresponding to the
174 G and C-alleles, respectively, is probably too simple,76,98,99,103,126 and the level of IL-6 production is probably affected by many other factors. Regarding the IL6R gene, only variants in relation to T2D have been addressed. A coding SNP (þ358 A/C) in the IL6R gene shows association to T2D in several populations, although ethnic differences may be the case.107–109 Mechanisms of a possible functional significance of the SNP are not clear.107–109 Another coding SNP (þ385 G/A) showed association in a study of African Americans, but were not detected in other populations.108

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Genetic variants in other pro-inflammatory cytokines as interleukin-18, IL18, and tumor growth factor b, TGFB1, genes have also been observed, IL18 polymorphisms have demonstrated association to T1D, however, but not consistently reproduced.84–86 TGFB1 did not show independent association to T1D127 or T2D,88,128 but have been associated with nephropathy in both T1D and T2D.127,129 Also, genetic variation in anti-inflammatory cytokine genes and their possible associations to T1D and T2D are potentially interesting. Variants in the IL10, IL4, IL4R, and IL13 have been evaluated. Some variants in the IL4, IL4R, and IL10 have shown independent association, as shown in Table 21.1; some however, only when evaluating haplotypes of several polymorphisms (e.g. haplotypes of SNPs in IL4 and IL13,80 whereas others (IL10
819 C/T, and
592 C/A) only show association with sub-phenotypes, i.e. adult-onset T1D in Japan.130 Additionally, for several other cytokine polymorphisms, associations to sub-phenotypes, e.g. diabetes with specific complications or quantitative traits of especially T2D, i.e. insulin resistance, obesity, etc., have been demonstrated. From such studies it is not known whether an independent association to T1D and/or T2D exist. Examples are associations of TGFB1 (þ869 C/T) and IL1B (
511 C/T) with T2D-nephropathy,119,129 and association of TNFA (
863 C/A), in which the A allele is less frequent in first degree relatives of T2D.97 A thorough review of such associations is, however, outside the scope of this review. Cytokine gene polymorphisms are beyond doubt of importance in both T1D and T2D, by complex genetic control of the actions of cytokines in the pathogeneses of both T1D and T2D.

21.7 FUTURE PERSPECTIVES To fully understand the role of cytokines in the pathogenesis of diabetes and the genetic influence on this, it is relevant to further investigate the downstream signaling pathways. Genetic variation in transcription factors, signaling molecules, etc. (e.g. NFkB, SOCS-1, SOCS-3, IRS-2 genes), are likely to influence the net effect of cytokines on different target tissues. For example polymorphisms in the NF-kB gene have been associated with T1D131 and a comprehensive analysis of genetic variation in cytokines, cytokine receptors, and signaling molecules may be needed to provide the complete picture of the genetic aspects of inflammatory mediators in the pathogenesis of T1D and T2D. It is the hope that understanding the genetic basis of inflammation ultimately will contribute to the development of methods for enhancing b-cell function and survival in the context of both major forms of diabetes.

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50. Krikovsky, D., Vasarhelyi, B. A. T. et al., Genetic polymorphism of interleukin-1beta is associated with risk of type 1 diabetes mellitus in children, Eur. J. Pediatr., 2002, 161(9), 507–508. 51. Mandrup-Poulsen, T., Pociot, F., Molvig, J. et al., Monokine antagonism is reduced in patients with IDDM, Diabetes, 1994, 43(10), 1242–1247. 52. Danis, V. A., Millington, M., Hyland, V. J. et al., Cytokine production by normal human monocytes — inter-subject variation and relationship to an il-1 receptor antagonist (il-1ra) gene polymorphism, Clin. Exp. Immunol., 1995, 99(2), 303–310. 53. Hurme, M., and Santtila, S, IL-1 receptor antagonist (IL-1RA) plasma-levels are coordinately regulated by both IL-1RA and IL-1-beta genes, Eur. J. Immun., 1998, 28(8), 2598–2602. 54. Bergholdt, R., Karlsen, A. E., Johannesen, J. et al., Characterization of polymorphisms of an Interleukin-1 receptor-type-1 gene (IL1RI) promotor region (p2) and their relation to insulin-dependent diabetes-mellitus (IDDM), Cytokine, 1995, 7(7), 727–733. 55. Metcalfe, K. A., Hitman, G. A., Pociot, F. et al., An association between type-1 diabetes and the interleukin-1 receptor-type-1 gene, Human Immun., 1996, 51(1), 41–48. 56. Kristiansen, O. P., Pociot, F., Johannesen, J. et al., Linkage disequilibrium testing of four interleukin-1 gene-cluster polymorphisms in Danish multiplex families with insulindependent diabetes mellitus, Cytokine, 2000, 12(2), 171–175. 57. Bergholdt, R., Larsen, Z. M., Andersen, N. A. et al., Characterization of new polymorphisms in the 50 UTR of the human Interleukin-1 receptor type 1 (IL1R1) gene: linkage to Type 1 diabetes and correlation to IL-1RI plasma level, Genes and Immunity, 2000, 1(8), 495–500. 58. Awata, T., Matsumoto, C., Urakami, T. et al., Association of polymorphism in the interferon-gamma gene with iddm, Diabetolog, 1994, 37(11), 1159–1162. 59. Pociot, F., Veijola, R., Johannesen, J. et al., Analysis of an Interferon-gamma gene (IFNG) polymorphism in Danish and Finnish insulin-dependent diabetes-mellitus (IDDM) patients and control subjects, J. Interf. Cy., 1997, 17(2), 87–93. 60. Pravica, V., Asderakis, A., Perrey, C. et al., In vitro production of IFN-gamma correlates with CA repeat polymorphism in the human IFN-gamma gene, Eur. J. Immunogenet., 1999, 26(1), 1–3. 61. Jahromi, M., Millward, A., and Demaine, A., A CA repeat polymorphism of the IFN-gamma gene is associated with susceptibility to type 1 diabetes, J. Interf. Cy., 2000, 20(2), 187–190. 62. Tegoshi, H., Hasegawa, G., Obayashi, H. et al., Polymorphisms of interferon-gamma gene CA-repeat and interleukin-10 promoter region (
592A/C) in Japanese type I diabetes, Human Immun., 2002, 63(2), 121–128. 63. Pociot, F., Briant, L., Jongeneel, C. et al., Association of tumor necrosis factor (TNF) and class II major histocompatibility complex alleles with the secretion of TNF-alpha and TNF-beta by human mononuclear cells: a possible link to insulin-dependent diabetes mellitus. Eur. J. Immun., 1993, 23(1), 224–231. 64. Obayashi, H., Nakamura, N., Fukui, M. et al., Influence of TNF microsatellite polymorphisms (TNFa) on age-at-onset of insulin-dependent diabetes mellitus, Human Immun., 1999, 60(10), 974–978. 65. Obayashi, H., Hasegawa, G., Fukui, M. et al., Tumor necrosis factor microsatellite polymorphism influences the development of insulin dependency in adult-onset diabetes patients with the DRB1*1502-DQB1*0601 allele and anti-glutamic acid decarboxylase antibodies, J. Clin. Endocrinol. Metab., 2000, 85(9), 3348–3351. 66. Pociot, F., Wilson, A. G., Nerup, J. et al., No independent association between a tumor necrosis factor-alpha promotor region polymorphism and insulin-dependent diabetes mellitus, Eur. J. Immun., 1993, 23(11), 3050–3053. 67. Shbaklo, H., Azar, S. T., Terwedow, H. et al., No association between the
1031 polymorphism in the TNF-alpha promoter region and type 1 diabetes, Human Immun., 2003, 64(6), 633–638. 68. Bouqbis, L., Akhayat, O., Garchon, H. et al., TNFA-TNFB haplotypes modify susceptibility to type I diabetes mellitus independently of HLA class II in a Moroccan population, Tissue Antigens, 2003, 61(1), 72–79. 69. Morahan, G., Huang, D. X., Ymer, S. I. et al., Linkage disequilibrium of a type 1 diabetes susceptibility locus with a regulatory IL12B allele, Nature Genet., 2001, 27(2), 218–221.

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70. Johansson, S., Lie, B. A., Thorsby, E. et al., The polymorphism in the 30 untranslated region of IL12B has a negligible effect on the susceptibility to develop type 1 diabetes in Norway, Immunogenetics, 2001, 53(7), 603–605. 71. Dahlman, I., Eaves, I., Kosoy, R. et al., Parameters for reliable results in genetic association studies in common disease, Nature Genet., 2002, 30(2), 149–150. 72. Davoodi-Semiromi, A., Yang, J. J., and She J. X., IL-12p40 is associated with type 1 diabetes in Caucasian-American families, Diabetes, 2002, 51(7), 2334–2336. 73. McCormack, R. M., Maxwell, A. P., Carson, D. J. et al., The IL12B 30 untranslated region DNA polymorphism is not associated with early-onset type 1 diabetes, Genes and Immunity, 2002, 3(7), 433–435. 74. Nistico, L., Giorgi, G., Giordano, M. et al., IL12B polymorphism and type 1 diabetes in the Italian population — A case-control study, Diabetes, 2002, 51(5), 1649–1650. 75. Bergholdt, R., Ghandil, P., Johannesen, J. et al., Genetic and functional evaluation of an interleukin-12 polymorphism (IDDM18) in families with type 1 diabetes, J. Med. Genet., 2004, 41(4), e39. 76. Kristiansen, O. P., Nolsøe, R. L., Larsen, L. et al., Association of a functional 17beta-estradiol sensitive IL6-174G/C promoter polymorphism with early-onset type 1 diabetes in females, Hum. Mol. Gen., 2003, 12(10), 1101–1110. 77. Jahromi, M. M., Millward, B. A., and Demaine, A. G., A polymorphism in the promoter region of the gene for interleukin-6 is associated with susceptibility to type 1 diabetes mellitus, J. Interf. Cy., 2000, 20(10), 885–888. 78. Urcelay, E., Santiago, J., de la Calle, H. et al., Interleukin-10 polymorphisms in Spanish type 1 diabetes patients, Genes and Immunity, 2004, 5(4), 306–309. 79. Ide, A., Kawasaki, E., Abiru, N. et al., Interleukin-10 gene promoter region polymorphisms in patients with type 1 diabetes and autoimmune thyroid disease, Ann. N. Y. Acad. Sci., 2003, 1005, 344–347. 80. Bugawan, T., Mirel, D., Valdes, A. et al., Association and interaction of the IL4R, IL4, and IL13 loci with type 1 diabetes among Filipinos, Am. J. Hum. Genet., 2003, 72(6), 1505–1514. 81. Mirel, D., Valdes, A., Lazzeroni, L. et al., Association of IL4R haplotypes with type 1 diabetes, Diabetes, 2002, 51(11), 3336–3341. 82. Maier, L., Twells, R., Howson, J. et al., Testing the possible negative association of type 1 diabetes and atopic disease by analysis of the interleukin 4 receptor gene, Genes and Immunity, 2003, 4(7), 469–475. 83. Kretowski, A., Mironczuk, K., Karpinska, A., et al., Interleukin-18 promoter polymorphisms in type 1 diabetes, Diabetes, 2002, 51(11), 3347–3349. 84. Martin, R., Savage, D., Carson, D. et al., Interleukin 18 promoter polymorphisms are not strongly associated with type I diabetes in a UK population, Genes and Immunity, 2005, 6(2), 171–174. 85. Ide, A., Kawasaki, E., Abiru, N. et al., Association between IL-18 gene promoter polymorphisms and CTLA-4 gene 49A/G polymorphism in Japanese patients with type 1 diabetes, J. Autoimmun., 2004, 22(1), 73–78. 86. Novota, P., Kolostova, K., Pinterova, D. et al., Interleukin IL-18 gene promoter polymorphisms in adult patients with type 1 diabetes mellitus and latent autoimmune diabetes in adults, Immunol. Lett., 2005, 96(2), 247–251. 87. Heijmans, B., Westendorp, R., Droog, S. et al., Association of the tumour necrosis factor alpha
308G/A polymorphism with the risk of diabetes in an elderly population-based cohort, Genes and Immunity, 2002, 3(4), 225–228. 88. Tsiavou, A., Hatziagelaki, E., Chaidaroglou, A. et al., TNF-alpha, TGF-beta1, IL-10, IL-6, gene polymorphisms in latent autoimmune diabetes of adults (LADA) and type 2 diabetes mellitus, J. Clin. Immunol., 2004, 24(6), 591–599. 89. Hayakawa, T., Nagai, Y., Taniguchi, M. et al., Tumor necrosis factor-beta gene NcoI polymorphism decreases insulin resistance in Japanese men, Metabolism, 2000, 49(11), 1506–1509. 90. Dalziel, B., Gosby, A., Richman, R. et al., Association of the TNF-alpha
308 G/A promoter polymorphism with insulin resistance in obesity, Obes Res., 2002, 10(5), 401–407.

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91. Shiau, M., Wu, C., Huang, C. et al., TNF-alpha polymorphisms and type 2 diabetes mellitus in Taiwanese patients, Tissue Antigens, 2003, 61(5), 393–397. 92. Kubaszek, A., Pihlajamaki, J., Punnonen, K. et al., The C-174G promoter polymorphism of the IL-6 gene affects energy expenditure and insulin sensitivity, Diabetes, 2003, 52(2), 558–561. 93. Rasmussen, S., Urhammer, S., Jensen, J. et al., The -238 and -308 G!A polymorphisms of the tumor necrosis factor alpha gene promoter are not associated with features of the insulin resistance syndrome or altered birth weight in Danish Caucasians, J. Clin. Endocrinol. Metab., 2000, 85(4), 1731–1734. 94. Schulz, S., Schagdarsurengin, U., Suss, T. et al., Relation between the tumor necrosis factor-alpha (TNF-alpha) gene and protein expression, and clinical, biochemical, and genetic markers: age, body mass index and uric acid are independent predictors for an elevated TNF-alpha plasma level in a complex risk model, Eur. Cytokine. Netw., 2004, 15(2), 105–111. 95. Koch, M., Rett, K., Volk, A. et al., The tumour necrosis factor alpha
238 G!A and
308 G!A promoter polymorphisms are not associated with insulin sensitivity and insulin secretion in young healthy relatives of Type II diabetic patients, Diabetolog, 2000, 43(2), 181–184. 96. Day, C., Grove, J., Daly, A. et al., Tumour necrosis factor-alpha gene promoter polymorphism and decreased insulin resistance, Diabetolog, 1998, 41(4), 430–434. 97. Costa, A., Fernandez-Real, J., Vendrell, J. et al., Lower rate of tumor necrosis factor-alpha
863A allele and higher concentration of tumor necrosis factor-alpha receptor 2 in first-degree relatives of subjects with type 2 diabetes, Metabolism, 2003, 52(8), 1068–1071. 98. Illig, T., Bongardt, F., Schopfer, A. et al., Significant association of the interleukin-6 gene polymorphisms C-174G and A-598G with type 2 diabetes, J. Clin. Endocrinol. Metab., 2004, 89(10), 5053–5058. 99. Bennermo, M., Held, C., Stemme, S. et al., Genetic predisposition of the interleukin-6 response to inflammation: implications for a variety of major diseases?, Clin. Chem., 2004, 50(11), 2136–2140. 100. Fernandez-Real, J., Broch, M., Vendrell, J. et al., Interleukin-6 gene polymorphism and insulin sensitivity, Diabetes, 2000, 49(3), 517–520. 101. Hayakawa, T., Takamura, T., Hisada, A. et al., IL-6 gene polymorphism
174G/C does not contribute substantially to hyperlipidaemia and Type II diabetes mellitus in Japanese men. Diabetolog, 2002, 45(3), 453–454. 102. Mohlig, M., Boeing, H., Spranger, J. et al., Body mass index and C-174G interleukin-6 promoter polymorphism interact in predicting type 2 diabetes, J. Clin. Endocrinol. Metab., 2004, 89(4), 1885–1890. 103. Vozarova, B., Fernandez-Real, J., Knowler, W. et al., The interleukin-6 (-174) G/C promoter polymorphism is associated with type-2 diabetes mellitus in Native Americans and Caucasians, Hum Genet., 2003, 112(4), 409–413. 104. Stephens, J., Hurel, S., Cooper, J. et al., A common functional variant in the interleukin-6 gene is associated with increased body mass index in subjects with type 2 diabetes mellitus, Mol. Genet. Metab., 2004, 82(2), 180–186. 105. Hamid, Y., Rose, C., Urhammer, S. et al., Variations of the interleukin-6 promoter are associated with features of the metabolic syndrome in Caucasian Danes, Diabetolog, 2005, 48(2), 251–260. 106. Kitamura, A., Hasegawa, G., Obayashi, H. et al., Interleukin-6 polymorphism (-634C/G) in the promotor region and the progression of diabetic nephropathy in type 2 diabetes, Diabet. Med., 2002, 19(12), 1000–1005. 107. Hamid, Y., Urhammer, S., Jensen, D. et al., Variation in the interleukin-6 receptor gene associates with type 2 diabetes in Danish whites, Diabetes, 2004, 53(12), 3342–3345. 108. Wang, H., Zhang, Z., Chu, W. et al., Molecular screening and association analyses of the interleukin 6 receptor gene variants with type 2 diabetes, diabetic nephropathy, and insulin sensitivity, J. Clin. Endocrinol. Metab., 2005, 90(2), 1123–1129. 109. Wolford, J., Colligan, P., Gruber, J. et al., Variants in the interleukin 6 receptor gene are associated with obesity in Pima Indians, Mol. Genet. Metab., 2003, 80(3), 338–343.

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110. Katila, H., Hanninen, K., and Hurme, M., Polymorphisms of the interleukin-1 gene complex in schizophrenia, Mol. Psychiatr., 1999, 4(2), 179–181. 111. Joos, L., McIntyre, L., Ruan, J. et al., Association of IL-1 beta and IL-1 receptor antagonist haplotypes with rate of decline in lung function in smokers, Thorax, 2001, 56(11), 863–866. 112. Boiardi, L., Salvarani, C., Timms, J. et al., Interleukin-1 cluster and tumor necrosis factor-alpha gene polymorphisms in polymyalgia rheumatica, Clin. Exp. Rheumatol., 2000, 18(6), 675–681. 113. Feakes, R., Sawcer, S., Broadley, S. et al., Interleukin 1 receptor antagonist (IL-1ra) in multiple sclerosis, J. Neuroimmunol., 2000, 105(1), 96–101. 114. Diehl, S., Wang, Y., Brooks, C. et al., Linkage disequilibrium of interleukin-1 genetic polymorphisms with early-onset periodontitis, J. Periodont., 1999, 70(4), 418–430. 115. Lang, N., Tonetti, M., Suter, J. et al., Effect of interleukin-1 gene polymorphisms on gingival inflammation assessed by bleeding on probing in a periodontal maintenance population, J. Periodont. Res., 2000, 35(2), 102–107. 116. McDevitt, M., Wang, H., Knobelman, C. et al., Interleukin-1 genetic association with periodontitis in clinical practice, J. Periodont., 2000, 71(2), 156–163. 117. Papapanou, P., Neiderud, A., Sandros, J. et al., Interleukin-1 gene polymorphism and periodontal status — A case-control study, J. Clin. Periodontol., 2001, 28(5), 389–396. 118. El-Omar, E., Carrington, M., Chow, W. et al., Interleukin-1 polymorphisms associated with increased risk of gastric cancer, Nature, 2000, 404(6776), 398–402. 119. Lee, S., Ihm, C., Sohn, S. et al., Polymorphisms in interleukin-1 beta and Interleukin-1 receptor antagonist genes are associated with kidney failure in Korean patients with type 2 diabetes mellitus, Am. J. Nephrol., 2004, 24(4), 410–414. 120. Bensen, J., Langefeld, C., Li, L. et al., Association of an IL-1A 30 UTR polymorphism with end-stage renal disease and IL-1 alpha expression, Kidney Int., 2003, 63(4), 1211–1219. 121. Marculescu, R., Endler, G., Schillinger, M. et al., Interleukin-1 receptor antagonist genotype is associated with coronary atherosclerosis in patients with type 2 diabetes, Diabetes, 2002, 51(12), 3582–3585. 122. Pociot, F., Molvig, J., Wogensen, L. et al., A tumour necrosis factor beta gene polymorphism in relation to monokine secretion and insulin-dependent diabetes mellitus, Scand. J. Immunol., 1991, 33(1), 37–49. 123. Seegers, D., Zwiers, A., Strober, W. et al., A TaqI polymorphism in the 30 UTR of the IL-12 p40 gene correlates with increased IL-12 secretion, Genes and Immunity, 2002, 3(7), 419–423. 124. Eerligh, P., Koeleman, B., Dudbridge, F. et al., Functional genetic polymorphisms in cytokines and metabolic genes as additional genetic markers for susceptibility to develop type 1 diabetes, Genes and Immunity, 2004, 5(1), 36–40. 125. Chang, Y., Huang, C., and Shiau, M., The C-174G promoter polymorphism of the interleukin-6 (IL-6) gene that affects insulin sensitivity in Caucasians is not involved in the pathogenesis of Taiwanese type 2 diabetes mellitus, Eur. Cytokine Netw., 2004, 15(2), 117–119. 126. Terry, C., Loukaci, V., and Green, F., Cooperative influence of genetic polymorphisms on interleukin 6 transcriptional regulation, J. Biol. Chem., 2000, 275(24), 18138–18144. 127. Pociot, F., Hansen, P., Karlsen, A. et al., TGF-beta1 gene mutations in insulin-dependent diabetes mellitus and diabetic nephropathy, J. Am. Soc. Nephrol., 1998, 9(12), 2302–2307. 128. Rosmond, R., Chagnon, M., Bouchard, C. et al., Increased abdominal obesity, insulin and glucose levels in nondiabetic subjects with a T29C polymorphism of the transforming growth factor-beta1 gene, Horm. Res., 2003, 59(4), 191–194. 129. Wong, T., Poon, P., Chow, K. et al., Association of transforming growth factor-beta (TGF-beta) T869C (Leu 10Pro) gene polymorphisms with type 2 diabetic nephropathy in Chinese, Kidney Int., 2003, 63(5), 1831–1835. 130. Ide, A., Kawasaki, E., Abiru, N. et al., Genetic association between interleukin-10 gene promoter region polymorphisms and type 1 diabetes age-at-onset, Human Immun., 2002, 63(8), 690–695. 131. Hegazy, D., O’Reilly, D., Yang, B. et al., NFkappaB polymorphisms and susceptibility to type 1 diabetes, 2001, 2(6), 304–308.

22

Psoriasis Sulev Ko˜ks, Ku¨lli Kingo, Eero Vasar, and Helgi Silm

CONTENTS 22.1 22.2 22.3 22.4 22.5 22.6 22.7

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tumor Necrosis Factor Gene Cluster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interferon Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interleukin-1 Family Cluster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interleukin-12 Family. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interleukin-10 Gene Cluster. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Macrophage Migration Inhibitory Factor and Vascular Endothelial Growth Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.8 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

321 323 328 328 329 330 330 331 331

22.1 INTRODUCTION Psoriasis (OMIM 177900) is a common inflammatory skin disorder of unknown etiology.1 Estimates of the prevalence of psoriasis range from 0.4 to 4.7% with rates varying between countries and races.2 The disease is more common in Caucasians and in people living in colder climates. Psoriasis is supposed to be a T cell-mediated autoimmune disease with similarities to other complex autoimmune disorders such as rheumatoid arthritis, Crohn’s disease, and diabetes. Psoriasis resembles other autoimmune disorders by several criteria: distinct role of genetic and environmental factors, variable age of onset, the great variability of the tissue reaction with different degrees of activity and frequency of relapses. Primarily taken as skin disorder, it is now known that psoriasis is a chronic systemic disorder affecting other organs as well. Five to 42% of patients with psoriasis have psoriatic arthritis that is usually seronegative for rheumatoid factor and is presented in several characteristic forms: oligoarticular disease, distal interphalangeal arthritis, arthritis mutilans, and spondylitis or sacroilitis.3 Ten to 30% of patients with psoriasis have nail changes: pitted nails, onycholysis, subungual hyperkeratosis, and discoloration of the nail plate.4 Patients with more severe skin eruption and long-standing disease are more likely to have nail changes and psoriatic arthritis than those with less severe or recent-onset disease. Family studies have suggested that psoriasis has a complex mode of inheritance involving the interaction of multiple genes in combination with environmental factors. Concordance rate in monozygotic twins is substantial — from 35 to 70%.5 Independent genome-wide linkage scans have suggested the involvement of large numbers of chromosomal regions in the development of psoriasis. Replication has only been achieved for a limited number of regions, including chromosomes 1q21, 3q21, 4q34, 6p21, 17q25, and 19p13.6–8 The highest risk to susceptibility to psoriasis has been reported for a region located on the short arm of chromosome 6. The susceptibility region on chromosome 6 321

322

Cytokine Gene Polymorphisms in Multifactorial Conditions

(PSORS1 — psoriasis susceptibility 1) has been refined to an approximately
300 kb region around the HLA-C gene, and contains several candidate genes including HLA-C, octamer transcription factor-3 (OTF3), transcription factor-19 (TCF19), corneodesmosin (CDSN), and a-helix coiled-coil rod homolog (HCR) genes.9–13 The HLA association of psoriasis affirms a pathogenetic link to the immune system and suggests that the pathogenic process is driven by autoantigens that may be presented by HLA-Cw6 in those patients who carry this allele. The exact cause of psoriasis remains unknown, but one unifying hypothesis of disease pathophysiology is the cytokine network model. In this model either an exogenously derived stimulus such as trauma, or an endogenous stimulus such as HIV-1, neuropeptides, or medications, is portrayed as triggering a plexus of cellular events by inciting a cascade of cytokines. This model features central pathogenetic roles for TNF-a derived from dendritic APCs and IFN-g produced by activated T helper 1/T cytotoxic 1 (Th1/Tc1)-type lymphocytes. These cytokines stimulate inflammation in the Type 1 pathway increasing transcription of other T-helper 1 genes and enhance the production of pro-inflammatory cytokines by keratinocytes, dendritic cells (DCs) and T-cells. The expression of a large number of IFN-related genes, that account 45% of total genes up-regulated in psoriatic lesions, explains the main cellular features of psoriasis, including T-cell activation, DC activation, leukocyte trafficking, vasodilatation, and abnormal keratinocyte differentiation and proliferation.14 Many of the IFN-induced genes overlap with genes regulated by TNF-a activation sequence elements that improve the synergy between these two cytokines and support also the key role of TNF-a in the induction and maintenance of psoriasis. Moreover, neutralization of TNF-a bioactivity abolished the clinical manifestation of psoriasis.15,16 Strong support for the cytokine network model is coming also from a recent study by Zhou et al.17 They compared gene expression profiles in biopsies from normal skin, involved and uninvolved psoriatic lesions by use of Affymetrix Gene Chips.17 This study identified 1338 genes with potential roles in the pathogenesis of psoriasis. Comparison of involved skin to normal skin samples revealed several genes related to immune response to be up-regulated. On the other hand, only genes responsible to epidermal differentiation were consistently altered in comparisons between involved vs. normal and uninvolved vs. normal skin. This finding supports the idea that inflammatory processes seem to be involved in the initiation and maintenance of psoriasis, whereas altered epidermal differentiation could have causative impact. Hence, initiation of psoriasis is associated with an over-expression of a large number of pro-inflammatory cytokines in psoriatic plaques, peripheral blood, and synovia of affected joints.18–20 Increased levels of pro-inflammatory cytokines in the peripheral blood indicates that generalized inflammation is present in psoriasis.21 In addition, several findings suggest that anti-inflammatory cytokines and their receptors (IL-1Ra, IL-10) also play a critical part in the disease pathogenesis. In the psoriatic skin the deficiency of IL-1Ra and the deficiency of IL-10 are established.22–24 Furthermore, therapeutic application of the anti-inflammatory cytokines IL-4 and IL-10 alleviates psoriasis significantly.25,26 The results from twin and family studies have demonstrated that
50 to 75% of the variation in cytokines production is genetically determined and polymorphisms of the cytokine genes regulate production for these cytokines.27 Gene polymorphisms that affect cytokine production may contribute to the disease-associated cytokine imbalance and influence susceptibility to psoriasis. In the following pages we try to overview the most important findings related to the impact of cytokine polymorphisms on the development of psoriasis. Table 22.1 summarizes main results of molecular genetic studies.

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323

22.2 TUMOR NECROSIS FACTOR GENE CLUSTER Tumour necrosis factor (TNF) gene cluster locates within the HLA class III region 250 kb centromeric from the HLA class genes on chromosome 6. The TNF locus is 12 kb in length and contains genes for three cytokines — TNF-a (gene TNFA), TNF-b (TNFB, LTA) and LTB (TNFC). As no studies on TNFC and psoriasis have been conducted presently, we will discuss only findings related to TNFA and TNFB genes. Several polymorphic areas including five microsatellites and several single nucleotide polymorphisms (SNPs) in promoter of the TNFA gene are described. Two G to A transitions at positions 308 and 238 are the most studied polymorphisms in patients with psoriasis. An increased carriage rate of the TNFA 238A allele in patients with plaque psoriasis has been established in Caucasian populations.28–31 Moreover, higher frequency of 238A SNP in TNFA gene seems to be associated with more aggressive form of psoriasis (early disease onset with positive family history) and joint involvement.28–30,32 Frequency of 308A allele is ambiguous — although in psoriatic patients it is usually unchanged, the lower frequency of the 308A allele in a subgroup of patients with more severe skin disease compared with healthy controls has been established.31 The trend towards decreased carriage of the A allele, although not significant, is seen also in studies by Reich et al. and by Hohler et al.32,33 Likewise, the lower frequency of the 308A allele in patients with PsA compared to healthy controls is observed. Described findings reflect potential protective effect of the 308A allele.31,33 However, in subgroup of PsA patients having more severe joint disease (deformities, erosions) frequency of 308A allele is higher.31,34 This is in contrast to studies in Asian populations that failed to demonstrate associations of the 238 and 308 promoter polymorphisms and psoriasis.35,36 In addition, a significant HLA class I independent increase of the TNFa6c1d3 microsatellite haplotype is found in the Caucasian group with PsA but not among patients with psoriasis.33 TNFA 238A genotype and TNFa6c1d3 microsatellite haplotype are both related to altered production of TNF-a cytokine and this could be one explanation for the associations.32,33,37 However, results of different studies are not consistent. Kaluza et al. have found that 238A allele has lower transcriptional activity and results in lower level of TNF-a secretion.37 Same group reported also that microsatellite TNFa6 was associated with decreased production of TNF-a.33 On the other hand, 238A allele was found to be associated with increased production of TNF-a in vitro.32 Therefore, biological impact of promoter polymorphisms in TNFA gene is still unclear. Taken together, even if TNFA gene is associated with psoriasis, its functional impact in psoriasis remains to be clarified. In the case of TNF-b the most frequently studied polymorphism in psoriasis patients is the NcoI polymorphism. This SNP (rs 909253) localizes at position 207 from ATG and is an A to G replacement (G nucleotide generates NcoI restriction site). NcoI restriction generates two types of products — A allele that is called B2 (782 bp band) and G allele that is called B1 (586 and 196 bp bands). Significant increase in B1 (G) allele has been found in psoriasis patients compared to healthy individuals.38 Additionally, a positive family history of psoriasis is associated with a higher B1 allele frequency in TNFB gene in Caucasian populations.38 However, in Korean psoriasis patients, frequencies of TNFB B1/B1 genotype and B1 allele are significantly lower.39 Positive association between PsA and TNFB polymorphism in position 252 is also described.34 Furthermore, an association between psoriatic arthritis and one of the microsatellite markers within the TNFB locus has been established in Caucasian population.40 Taken together, TNFB seems to have an impact on psoriasis susceptibility. However, as the number of studies is limited, it is too early for definite statements.

TNFA

Gene

308 G/A

238 G/A

Polymorphism Studied

A

S E Ps

A A A

Ps PASI 12 PsA

Caucasian

A

A

Type I Ps

Ps

Caucasian

GA

GG

Caucasian

Type I Ps

Caucasian

A

A

Type I Ps

Type I Ps 8

A

E Ps 8

A

A

E Ps

Type I Ps

A

Ps

Caucasian

Caucasian

A A

Associated allele/ Genotype/ Haplotype

J Ps PsA

Clinical Subgroup

Caucasian

Population/Ethnicity

0.009, 0.036* 0.51 (0.30–0.86) 0.0041, 0.1640* 0.42 (0.23–0.78) 0.0187, 0.5236* 0.37 (0.14–0.89)

0.041, 0.6* 0.5 (0.3–0.97)

0.0003, 0.0012* 3.21 (1.60–6.84)

2.74  108, 1.6  107* 0.12 2.64  107, 1.58  106* 7.73

0.0012, 0.017* 3.4 (1.6–7.2) 0.0046, 0.064* 4.1 (1.5–11)

59/135

152/135

239/135

100/123

239/135

99/123

67/56a

100/123

74/345

82/345

105/182a

156/345

231/345

1  106, 3  106* 3.24 (1.94–5.49) 1  107, 3  107* 4.02 (2.31–7.00) 2  108, 2  107* 6.78 (3.18–15.15) 9  108, 7  107* 5.35 (2.80–10.12) 0.0055, 0.0218* 2.77 (1.29–5.71)

Number of Patients/ Controls 60/99 62/99

P Value, Pc Value (*), OR (95% CI)

50.0001, 50.008* 50.0003, 50.03*

TABLE 22.1 Summary of the Main Findings from Cytokine Polymorphism Association Studies in Psoriasis

31

29

31

30

29

32

28

Reference

324 Cytokine Gene Polymorphisms in Multifactorial Conditions

TNFB

Caucasian

Caucasian

þ252 B1/B2

microsatellite markers

A B2 B2

E Ps nummular PsA with joint erosions PsA with progression of joint erosions

0.012, 0.024*

A

E Ps not-severe

TNFB123

0.0486

A

S E Ps

PsA

0.0017

A

0.002, 50.006* 1.9RR (1.3–2.9) 0.005, 0.03* 3.0RR (1.4–6.6) 0.006, 0.03* 1.9RR (1.2–3.1) 0.006, 0.03* 1.9RR (1.2–2.9) 0.004, 0.02* 2.0RR (1.3–3.1)

E Ps 9

GG

G

50.003, 50.006* 1.8RR 50.003, 50.006* 0.6RR 50.001, 50.002* 0.2RR

A

A

Ps

Korean patients

0.006 0.011 0.049

G G G

0.04 50.008* 5.3RR

0.0078

A

d4 TNFa6c1d3

50.0001

0.008* 2.7 (1.5–6.8)

A

G

E Ps

Ps F Ps Type I Ps

Caucasian

207 A/G

Type I Ps PsA

Caucasian

PsA with joint erosions PsA with progression of joint erosions

Caucasian

TNFa/TNFc/TNFd

PsA

Caucasian

120/94

147/389

60/125

64/125

56/125

45/19

(continued )

40

34

39

103/125

80/125

38

33

34

33

142/141

65/99 49/65c

147/389

65/99b

Psoriasis 325

rs2073186/ rs2243174/

Caucasian

rs2243188 C/A

IL19

F Ps

Caucasian

IL10.G

Caucasian

Caucasian

1082 G/A 1082/819/592

IL10

1053 T/G 3978 T/C 1053/1380/1462

Japanese Caucasian Caucasian

þ1188 A/C

IL12p40

IL20

F Ps Type I Ps

Caucasian

Ps L Ps S L Ps

Ps

IL10.G9

A A A TGATA

G T/C GAA

0.029 50.02 50.05 0.05 0.58 (0.335–1.00)

50.05 50.05 50.01 2.341 (1.346–4.074)

0.022

0.0069 0.0028

254/148 74/148 153/148 74/148

254/148

137 trios

26/56e 24/31f

41/188d 0.002 2.445 (1.384–4.318)

IL10.G13 IL10.G13

65/148

0.03 1.637 (1.040–2.566)

31/330 147/148

143/100

140/100

Ps with extent ACC of eruption  10 Ps with persistent ATA eruption

0.035

0.014, 0.04* 1.65 (1.11–2.45) 0.009, 0.027* 2.06 (1.22–3.47)

75/345

231/345

Number of Patients/ Controls

0.02 0.04 1.463 (1.008–2.123)

A

CC

C

0.0135, 0.0268* 1.54 (1.09–2.19) 0.0071, 0.0419* 2.04 (1.19–3.53)

P Value, Pc Value (*), OR (95% CI)

GA PASI ACC

L Ps Ps with 20

Ps

PsA

CC

L Ps

889 C/T

CC

Associated allele/ Genotype/ Haplotype

Ps

IL1A

Clinical Subgroup

Caucasian

Population/Ethnicity

511 C/T

Polymorphism Studied

IL1B

Gene

TABLE 22.1 Continued

90

89

87

86

47 88

75

64

32

Reference

326 Cytokine Gene Polymorphisms in Multifactorial Conditions

þ405 G/C

Ps with onset between 20 and 40 years Ps with onset between 20 and 40 years Ps with PASI12

0.02 0.02 0.03 0.04

C CC

0.02

C CC

CC

Caucasian

460 C/T

0.024 1.52 (1.05–2.19) 0.013 1.67 (1.1–2.5) 0.008 1.69 (1.2–2.5)

72/102

56/102

56/102

228/401

254/148

66/148

254/148

97

94

91

*Corrected P value; RRRelative risk; aMale patients vs. male controls; bPsoriatic arthritis with TNFA 238Gþ haplotypes vs. healthy controls with TNFA 238Gþ haplotypes; c Psoriatic arthritis vs. psoriasis; dPersistent course of psoriasis vs. intermittent course of psoriasis; eFamilial psoriasis vs. sporadic psoriasis; fFamilial early onset psoriasis vs. sporadic early onset psoriasis. Abbreviations: (Ps) psoriasis, (PsA) psoriatic arthritis, (J Ps) juvenile onset psoriasis, (E Ps) early onset psoriasis, (E Ps 8) early onset psoriasis of male patients, (L Ps) late onset psoriasis, (F Ps) familial psoriasis, (Type I Ps) familial early onset psoriasis, (Type I Ps 8) familial early onset psoriasis of male patients, (S Ps) sporadic psoriasis, (S E Ps 8) sporadic early onset psoriasis of male patients, (E Ps 9) early onset psoriasis of female patients.

VEGF

CATT7-MIF173*C

C

CATT-MIF-173 haplotype

Ps

CGAGT

TGGGT

CATT7

Caucasian

173 G/C

MIF

0.000186 0.154 (0.059–0.411) 0.04 0.591 (0.356–0.981) 0.04 0.457 (0.215–0.974)

CAAAC

Ps

50.01 2.548 (1.379–4.706) 0.02 0.05 1.548 (1.007–2.380)

CACCGGAA

Ps with extent of G GGGT eruption  10

Ps

794 CATT repeat

Caucasian

rs1150253 rs3762344/ rs1150253/ rs1150256/ rs1150258 IL20/IL24 haplotype block

IL24

rs2243188/ rs2243191/ rs2243193 IL19/IL20 haplotype block

Psoriasis 327

328

Cytokine Gene Polymorphisms in Multifactorial Conditions

22.3 INTERFERON GENES Interferons (IFNs) form a large class of different cytokines — type I (IFN-a and IFN-b), type-II (IFN-g) and IFN-. The number of members in each class is quite different. There are 17 type I cytokines, one type II cytokine and three IFN- cytokines.41 Genes encoding different IFNs are locating in three clusters according to their subfamily. Interferon type I (IFNA, IFN1) cluster is in locus 9p22, interferon type II (IFNG, IFN2) (together with interleukin-22 and interleukin-26 genes) is in locus 12q14 and IFN- (IFNL; contains IL29 or IFNL1, IL28A or IFNL2, IL28B or IFNL3 genes) cluster is in 19q13 locus. According to present understanding on the pathogenesis of psoriasis, IFN-g has a central role in the induction of inflammation in psoriatic lesions and it is able to stimulate the proliferation of psoriatic keratinocytes.42,43 Therefore, IFNs (especially IFNG) are good candidates for molecular genetic studies to find genetic factors affecting development of psoriasis. IFNG gene contains a CA repeat microsatellite in the first intron [I1(761)*CAn].44 Alleles are numbered according to their size. Allele 1 corresponds to 11 repeats, allele 2 to 12 repeats, alleles 3–5 correspond to 13–15 repeats, respectively.45 Allele 2 or CA12 is associated with a higher production of IFN-g in vitro.45 Pravica et al. have shown that the I1(761)*CA12 allele is associated with increased production of IFN-g mainly in homozygotes, although a trend toward increased expression was observed in heterozygotes.45 Moreover, they have found that the SNP in position 874 T/A absolutely correlates perfectly with the presence or absence of allele 2 (CA12).46 This polymorphism coincides with the middle of NF-kB binding site and could account for the differences in the level of IFN-g production.46 Up to now there is only one report where association between IFNG polymorphisms and psoriasis has been studied.47 No association between polymorphism in the IFNG gene and susceptibility to plaque psoriasis was found. This study should be taken as preliminary, as sample size was too limited for definitive conclusions (84 patients). As IFN-g is related directly to the pathogenesis of psoriasis, it is surprising that SNPs in this genetic locus have not deserved enough attention. Other genes from IFN cluster have not been studied in patients with psoriasis.

22.4 INTERLEUKIN-1 FAMILY CLUSTERS Interleukin-1 (IL-1) is a cytokine with a variety of biological activities known to initiate and promote the host response to injury or infection. As a pro-inflammatory cytokine, IL-1 activates transcription factors NFkB and AP-1, which in turn induce genes involved in the initiation of immune and inflammatory responses.48,49 IL-1 activity resides on different structurally and functionally similar cytokines and they form interleukin-1 family of cytokines.50–52 Altogether, ten cytokines have been characterized to belong to the IL1 cytokine superfamily — IL1A, IL1B, IL1RN, IL18, IL1F5, IL1F6, IL1F7, IL1F8, IL1F9, and IL1F10.53 IL-1RN (also known as IL-1Ra) is endogenous antagonist for IL-1 activity. IL-1RN interacts with IL-1R1 receptor without inducing the activation of signalling cascade and by blocking receptor, prevents the binding of IL-1A and IL-1B.54 IL-1F5 and IL-1F6 belong to an independent signalling system, where IL-1F6 activates NFkB and IL-1F5 specifically and potently inhibits IL-1F6 action.55 IL-18 was identified as IFN-g inducing factor by T cells and natural killer cells.56 Other members of IL-1 family are not fully characterized yet, but it is suggested that IL-1F8, IL-1F9, and IL-1F10 may antagonize IL-1 actions and IL-1F7 is a potential agonist of IL-1.52 Genes encoding IL-1 family cytokines (except IL18) reside in one locus 2q14, and they form IL-1 cytokine cluster.53 The gene for IL-18 is located on the 11th chromosome, in band q22.2–q22.3.57 IL-1 family cytokines are thought to play a central role in inflammatory reactions of the skin as epidermal expression

Psoriasis

329

of IL-1 cytokines is clearly altered.58 Thus, genes for those cytokines could account for the genetic predisposition for psoriasis. In the IL1B gene there are two base-exchange polymorphisms at positions 511 C/T (AvaI polymorphism, rs16944) in the promoter region and at position 3953 C/T (TaqI polymorphism, rs1143634) in the fifth exon.59,60 The IL1RN gene has a penta-allelic polymorphism in intron 2 containing a variable number of an 86 tandem repeat sequence.61 The precise role of different polymorphisms in gene expression is not fully understood yet, but production of IL1B and IL1RN is regulated by different IL1B and IL1RN alleles.62,63 PBMCs from IL1B 511 C/C homozygotes are shown to have higher production of IL-1Ra compared to C/T or T/T genotypes.32 Interestingly, 511 C/C genotyopes are related to higher sensitivity to the anti-inflammatory action of IL-10.32 In the same study, 511 C/C genotype was described to be more frequent in patients with late onset psoriasis compared to controls. This finding supports the idea that imbalance between pro-inflammatory and anti-inflammatory cytokines is involved in the maintenance and activity of psoriasis. In another study linkage disequilibrium between IL1B 3953 and IL1A 889 C/T is described.64 Significantly higher frequency of C allele in 889 position of IL-1A gene in patients with psoriatic arthritis was found. These data indicate that polymorphisms of the IL1 gene cluster influence susceptibility to psoriasis.

22.5 INTERLEUKIN-12 FAMILY Interleukin-12 (IL-12) is a more novel cytokine cloned from B-cell lines. It has a broad array of potent biologic activities, acting on both T and NK cells. IL-12 is a disulfide-linked heterodimer composed of unrelated 40-kD (p40 or IL-12B) and 35-kD (p35 or IL-12A) subunits.65 Sequence alignment showed that p40 is a member of the cytokine receptor family related to IL-6R. On the other hand, sequence comparison showed that p35 is related to ligands of cytokine receptor family, most closely to IL-6. Interleukin-23 (IL-23A, p19) is a newly discovered heterodimeric cytokine in the IL-12 family and consists of p40 and p19 subunits.66 IL-12 family has two more heterodimeric members — interleukin-27 (p28 and EBI3 subunits) and p35-EBI3 complex.67,68 Subunits p40, p35, and p19 localize to different chromosomes — p35 is located on 3q12–q13.2, p40 on 5q31.1–q33.1 and p19 on 12q13.3. IL-12 is thought as being a link between innate and adaptive immunity. Moreover, IL-12 has been suggested to be a key cytokine in the development of psoriasis and p40 subunit antibody is a possible therapeutic option.69 Indeed, increased expression of p40 subunit (but not p35) in psoriatic lesion has been repeatedly shown.70,71 As p40 is a common subunit for IL-12 and IL-23 it was not possible to rule out the role of IL-23. In fact, the up-regulation of p19 (IL-23 specific subunit) and p40 in psoriatic skin lesions has been described.72 While p35 was unchanged, this finding confirms the importance of IL-23 in psoriasis. Recently, A/C polymorphism in 30 -UTR region of p40 gene in position 1188 (rs3212227 or rs17875322) has been described.73 C/C genotype is related to significantly reduced expression of p40.74 Frequency of A allele and A/A genotype was significantly increased in patients with psoriasis compared to control subjects.75 Another study on a smaller sample did not find any difference in distribution of 30 -UTR between psoriasis patients and controls.76 In this study authors also analyzed the production of IL-12p70 (p35 and p40 together) and p40 in whole blood. They did not find any correlation between 30 UTR SNP and IL-12 production level. However, blood cells from psoriasis patients were more susceptible to the LPS stimulation than control blood cells.76 Taken together, the role of the IL-12 family in psoriasis needs to be evaluated in further studies.

330

Cytokine Gene Polymorphisms in Multifactorial Conditions

22.6 INTERLEUKIN-10 GENE CLUSTER The IL10 gene cluster locates in a 200 kb region of chromosome 1 within the locus q31–32 and holds four genes: IL10, IL19, IL20, and IL24.77–80 Three SNPs at the promoter region of the IL10 gene — IL10 1082 G/A (rs1800896), IL10 819 C/T (rs1800871), and IL10 592 C/A (rs1800872) — are in complete linkage disequilibrium (LD). Generally three haplotypes exist in Caucasian populations (GCC, ACC, ATA).81 In addition, two microsatellites in the promoter area are also in LD with these three SNPs and altogether four common haplotypes exist depending on the variability of the R microsatellite.82 These haplotypes influence the expression level of IL-10, but findings from different studies are inconsistent. Some studies have found that G allele in position 1082 is related to higher and A allele to lower IL-10 expression.81,83,84 Other groups have described that 1082 A allele causes higher expression of IL-10.82,85 These different studies used different methods for IL-10 level analysis and this could be the reason for contradictory findings. An increased frequency of the heterozygous G/A genotype at position 1082 of the IL10 promoter has been described in the subset of patients with late onset of disease.47 Microsatellite G13 in the promoter region was associated with familial psoriasis.86 However, the trio-design study with 137 nuclear families did not confirm this finding.87 Contrarily, IL10.G9 allele was identified to be protective against familial type of disorder.87 Haplotype analysis of promoter SNPs in unrelated subjects showed no differences in the frequencies of haplotypes between healthy controls and patients. Nevertheless, the haplotype ATA determines clinical course of plaque psoriasis and the haplotype ACC influences severity of disease.88 Descriptions of SNPs of IL19, IL20, and IL24 genes are accessible in the public databases. Their influence on gene expression levels is unknown at present. Overrepresentation of minor G allele of IL20 promoter SNP (rs2981572) at position 1053 in patients with psoriasis has been reported.89 The frequency of genotype T/C at position 3978 (rs1518108) in 30 UTR region of IL20 gene was lower among psoriasis patients.89 In our original study we showed block-like structure of LD formed by genes IL19, IL20, and IL24. Moreover, we found extended haplotype (CACCGGAA) formed by eight SNPs in IL19 (rs2073186, rs2243174, rs2243188, rs2243191, rs2243193) and IL20 (rs2981572, rs2981573, rs2232360) genes to be a significant susceptibility factor for psoriasis.90 This association mainly reflects individual effect of allele G at position 1053 of the IL20 gene.90 There is a breakdown of LD at 30 UTR region of the IL20 gene and IL20 SNP 3978 (rs1518108) in 30 UTR is in linkage with SNPs of the IL24 gene. IL20/IL24 extended haplotypes (SNPs rs1518108, rs3762344, rs1150253, rs1150256, rs1150258) CAAAC, TGGGT, and CGAGT have been demonstrated to be protective against psoriasis. The strongest protective effect was found with CAAAC haplotype. This association was caused by individual effect of 3978 (rs1518108) SNP in the IL20 gene.91 Functional relevance of these findings is not established yet, but the IL10 cluster seems to have significant impact on susceptibility and clinical course of psoriasis.

22.7 MACROPHAGE MIGRATION INHIBITORY FACTOR AND VASCULAR ENDOTHELIAL GROWTH FACTOR Macrophage migration inhibitory factor (MIF) is a macrophage-derived cytokine and increased expression of MIF occurs in plaques of psoriasis and in sera from patients with psoriasis.92,93 The MIF gene maps to chromosome 22q11.2. Polymorphisms in positions 173 (SNP) and 794 (CATT repeat) have been described. Relation between chronic

Psoriasis

331

plaque psoriasis and carriage of the MIF 173C allele and MIF CATT7 allele has been established.94 Vascular endothelial growth factor (VEGF) is a mitogen primarily for vascular endothelial cells. Several studies have shown that VEGF expression is increased in psoriatic lesions and that serum levels of circulating VEGF protein are correlated with disease severity.95,96 Gene for VEGF locates in the 6p12 region, close to the PSORS1 locus (6p21). SNPs in positions 460 C/T (rs833061) and 405 G/C (rs2010963) have been studied in psoriasis patients.97 SNP 405 regulates production of VEGF in healthy subjects.98 Patients with severe plaque psoriasis, and those with onset of psoriasis between ages of 20 and 40 years showed significantly increased frequency of 405 C/C genotype and C allele.97 In the same group frequency of C/C genotype in position 460 was significantly reduced in patients with onset of psoriasis between 20 and 40.97

22.8 CONCLUDING REMARKS Current understanding on the pathogenesis of psoriasis relies on the cytokine network model. According to this model imbalance between pro-inflammatory and anti-inflammatory cytokines is crucial for the generation of psoriatic symptoms. The central role of cytokines TNF-a and IFN-g in pathogenesis of psoriasis is postulated. Associations between TNFA polymorphisms and psoriasis susceptibility and severity have been shown. Interestingly, polymorphisms in IFNG have not yet been studied in sufficient detail. Genetic analysis of other cytokines has revealed their role in modifying clinical course of psoriasis. Moreover, IL12B and IL20 genes have been found to be related to development of skin inflammation. Transgenic mice models have confirmed the possible role of these genes in psoriasis. Haplotype based association studies combined with functional analysis are necessary to clarify the role of cytokines in development of psoriasis.

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56. Okamura, H. et al., Cloning of a new cytokine that induces IFB-gamma production by T cells, Nature, 378, 88, 1995. 57. Nolan, K. F., Greaves, D. R., and Waldmann, H., The human interleukin 18 gene IL18 maps to 11q22.2–q22.3, closely linked to the DRD2 gene locus and distinct from mapped IDDM loci, Genomics, 51, 161, 1998. 58. Debets, R. et al., The IL-1 system in psoriatic skin: IL-1 antagonist sphere of influence in lesional psoriatic epidermis, J. Immunol., 158, 2955, 1997. 59. di Giovine, F. S. et al., Single base polymorphism at 511 in the human interleukin-1 beta gene (IL1 beta), Hum. Mol. Genet., 1, 450, 1992. 60. Pociot, F. et al., Genetic susceptibility markers in danish patients with type 1 (insulindependent) diabetes — evidence for polygenicity in man. Danish study group of diabetes in childhood, Autoimmunity, 19, 169, 1994. 61. Tarlow, J. K. et al., Association between interleukin-1 receptor antagonist (IL-1RA) gene polymorphism and early and late-onset psoriasis, Br. J. Dermatol., 136, 147, 1997. 62. Pociot, F. et al., A TaqI polymorphism in the human interleukin-1 beta (IL-1 beta) gene correlates with IL-1 beta secretion in vitro, Eur. J. Clin. Invest., 22, 396, 1992. 63. Hurme, M. and Santtila, S., IL-1 receptor antagonist (IL-1RA) plasma levels are co-ordinately regulated by both IL-1RA and IL-1beta genes, Eur. J. Immunol., 28, 2598, 1998. 64. Ravindran, J. S. et al., Interleukin 1alpha, interleukin 1beta and interleukin 1 receptor gene polymorphisms in psoriatic arthritis, Rheumatology (Oxford), 43, 22, 2004. 65. Wolf, S. F. et al., Cloning of cDNA for natural killer cell stimulatory factor, a heterodimeric cytokine with multiple biologic effects on T and natural killer cells, J. Immunol., 146, 3074, 1991. 66. Oppmann, B. et al., Novel p19 protein engages IL-12p40 to form a cytokine, IL-23, with biological activities similar as well as distinct from IL-12, Immunity, 13, 715, 2000. 67. Pf lanz, S. et al., IL-27, a heterodimeric cytokine composed of ebi3 and p28 protein, induces proliferation of naive cd4(þ) t cells, Immunity, 16, 779, 2002. 68. Watford, W. T. and O’Shea, J. J., Autoimmunity: A case of mistaken identity, Nature, 421, 706, 2003. 69. Nestle, F. O. and Conrad, C., The IL-12 family member p40 chain as a master switch and novel therapeutic target in psoriasis, J. Invest. Dermatol., 123, xiv–xv, 2004. 70. Yawalkar, N. et al., Expression of interleukin-12 is increased in psoriatic skin, J. Invest. Dermatol., 111, 1053, 1998. 71. Cheng, J. et al., A study on the expression of interleukin (IL)-10 and IL-12 p35, p40 mrna in the psoriatic lesions, J. Tongji Med. Univ., 21, 86, 2001. 72. Lee, E. et al., Increased expression of interleukin 23 p19 and p40 in lesional skin of patients with psoriasis vulgaris, J. Exp. Med., 199, 125, 2004. 73. Huang, D., Cancilla, M. R., and Morahan, G., Complete primary structure, chromosomal localisation, and definition of polymorphisms of the gene encoding the human interleukin-12 p40 subunit, Genes Immun., 1, 515, 2000. 74. Morahan, G., Huang, D., Ymer, S. I., Cancilla, M. R., Stephen, K., Dabadghao, P., Werther, G., Tait, B. D., Harrison, L. C., and Colman, P. G., Linkage disequilibrium of a type 1 diabetes susceptibility locus with a regulatory IL12b allele, Nat. Genet., 27 (2), 218, 2001. 75. Tsunemi, Y. et al., Interleukin-12 p40 gene (IL12b) 30 -untranslated region polymorphism is associated with susceptibility to atopic dermatitis and psoriasis vulgaris, J. Dermatol. Sci., 30, 161, 2002. 76. Litjens, N. H. et al., Psoriasis is not associated with IL-12p70/IL-12p40 production and IL12b promoter polymorphism, J. Invest. Dermatol., 122, 923, 2004. 77. Kim, J. M. et al., Structure of the mouse IL-10 gene and chromosomal localization of the mouse and human genes, J. Immunol., 148, 3618, 1992. 78. Gallagher, G. et al., Cloning, expression and initial characterization of interleukin-19 (IL-19), a novel homologue of human interleukin-10 (IL-10), Genes Immun., 1, 442, 2000. 79. Blumberg, H. et al., Interleukin 20: Discovery, receptor identification, and role in epidermal function, Cell, 104, 9, 2001.

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80. Jiang, H. et al., Subtraction hybridization identifies a novel melanoma differentiation associated gene, mda-7, modulated during human melanoma differentiation, growth and progression, Oncogene, 11, 2477, 1995. 81. Turner, D. M. et al., An investigation of polymorphism in the interleukin-10 gene promoter, Eur. J. Immunogenet., 24, 1, 1997. 82. Eskdale, J. et al., Microsatellite alleles and single nucleotide polymorphisms (SNP) combine to form four major haplotype families at the human interleukin-10 (IL-10) locus, Genes Immun., 1, 151, 1999. 83. Crawley, E. et al., Polymorphic haplotypes of the interleukin-10 50 flanking region determine variable interleukin-10 transcription and are associated with particular phenotypes of juvenile rheumatoid arthritis, Arthritis Rheum., 42, 1101, 1999. 84. Kingo, K. et al., Influence of genetic polymorphisms on interleukin-10 mRNA expression and psoriasis susceptibility, J. Dermatol. Sci., 37, 111, 2005. 85. Temple, S. E. et al., Alleles carried at positions 819 and 592 of the IL10 promoter affect transcription following stimulation of peripheral blood cells with streptococcus pneumoniae, Immunogenetics, 55, 629, 2003. 86. Asadullah, K. et al., Interleukin-10 promoter polymorphism in psoriasis, J. Invest. Dermatol., 116, 975, 2001. 87. Hensen, P. et al., Interleukin-10 promoter polymorphism IL10.G and familial early onset psoriasis, Br. J. Dermatol., 149, 381, 2003. 88. Kingo, K. et al., Il-10 promoter polymorphisms influence disease severity and course in psoriasis, Genes Immun., 4, 455, 2003. 89. Kingo, K. et al., Polymorphisms in the interleukin-20 gene: Relationships to plaque-type psoriasis, Genes Immun., 5, 117, 2004. 90. Ko˜ks, S. et al., Combined haplotype analysis of the interleukin-19 and -20 genes: Relationship to plaque-type psoriasis, Genes Immun., 5, 662, 2004. 91. Ko˜ks, S. et al., Possible relations between the polymorphisms of the cytokines IL-19, IL-20 and IL-24 and plaque-type psoriasis, Genes Immun., 6, 407, 2005. 92. Steinhoff, M. et al., Evidence for a role of macrophage migration inhibitory factor in psoriatic skin disease, Br. J. Dermatol., 141, 1061, 1999. 93. Shimizu, T. et al., High macrophage migration inhibitory factor (MIF) serum levels associated with extended psoriasis, J. Invest. Dermatol., 116, 989, 2001. 94. Donn, R. P. et al., Macrophage migration inhibitory factor gene polymorphism is associated with psoriasis, J. Invest. Dermatol., 123, 484, 2004. 95. Detmar, M. et al., Overexpression of vascular permeability factor/vascular endothelial growth factor and its receptors in psoriasis, J. Exp. Med., 180, 1141, 1994. 96. Nielsen, H. J. et al., Elevated plasma levels of vascular endothelial growth factor and plasminogen activator inhibitor-1 decrease during improvement of psoriasis, Inflamm. Res., 51, 563, 2002. 97. Young, H. S. et al., Single-nucleotide polymorphisms of vascular endothelial growth factor in psoriasis of early onset, J. Invest. Dermatol., 122, 209, 2004. 98. Watson, C. J. et al., Identification of polymorphisms within the vascular endothelial growth factor (VEGF) gene: Correlation with variation in VEGF protein production, Cytokine, 12, 1232, 2000.

23

Diseases of the Gastrointestinal Tract Thomas Ho¨hler

CONTENTS 23.1 23.2 23.3

Helicobacter Infection and Gastric Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chronic Inflammatory Bowel Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Liver Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3.1 Hepatitis B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3.2 Chronic HCV Infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.4 Future Directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

337 338 340 341 343 345 345

Cytokines are important mediators in infectious and inflammatory gastrointestinal diseases. Cytokines (interferon-a) or anti-cytokine antibodies (e.g. infliximab) are established therapies in gastrointestinal diseases as chronic viral hepatitis or Crohn’s disease. Here I will review the data on association of cytokine polymorphisms with gastrointestinal diseases.

23.1 HELICOBACTER INFECTION AND GASTRIC CANCER Infection with Helicobacter pylori occurs worldwide, but the prevalence varies greatly among countries and among population groups within the same country.1 The infection is acquired by oral ingestion of the bacterium and is mainly transmitted within families in early childhood. The infection almost always causes inflammation of the gastric mucosa, the distribution and severity of which varies widely and affects the clinical outcome. The gastric epithelium of H. pylori-infected persons has enhanced levels of interleukin-1b, interleukin-2, interleukin-6, interleukin-8, and tumor necrosis factor-a.2–5 Among these, interleukin-8, a potent neutrophil-activating chemokine expressed by gastric epithelial cells, apparently has a central role in initiating the inflammation.5 The clinical course of H. pylori infection is highly variable and is influenced by both microbial and host factors.1 Patients with antral-predominant gastritis, the most common form of H. pylori gastritis, are predisposed to duodenal ulcers, whereas patients with corpuspredominant gastritis and multifocal atrophy are more likely to have gastric ulcers, gastric atrophy, intestinal metaplasia, and ultimately gastric carcinoma. Duodenal ulceration and gastric cancer seem to be mutually exclusive outcomes of H. pylori infection that cannot be explained by differences in bacterial virulence factors alone, as virulent strains seem to be equally associated with both conditions.1 H. pylori-induced inflammation is mediated by a variety of pro- and anti-inflammatory cytokines that are upregulated in the presence of H. pylori lipopolysaccharide, urease, and toxins. One of the key cytokines that is increased in the gastric mucosa in this process 337

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Cytokine Gene Polymorphisms in Multifactorial Conditions

is interleukin-1 beta (IL-1b). This cytokine is important in initiating and amplifying the inflammatory responses against the bacterium and is also a potent inhibitor of gastric acid secretion. Three diallelic polymorphisms in IL1B gene have been reported, all representing C/T base transitions, at positions
511,
31, and þ3954 from the transcriptional start site.6,7 There are conflicting data regarding the functional effects of these polymorphisms on IL-1b production.6,7 The IL1RN gene has a penta-allelic 86-bp tandem repeat (VNTR) in intron 2, of which the less common allele 2 (IL1RN*2) is associated with a wide range of chronic inflammatory and autoimmune conditions.8 IL1RN*2 is associated with enhanced IL-1b production in vitro,9 but data regarding its effects on IL-1 receptor antagonist production are contradictory. Carriers of the IL1B-511T/T genotype and IL1RN*2 allele have higher IL-b levels compared to non-carriers.10 Higher Il-1b levels are associated with more pronounced inflammation in the antrum and corpus of the stomach and consequently decreased gastric acid production.10,11 Carriers of the IL1B-511T allele and IL1RN*2/*2 have been reported to be at increased risk of hypochlorhydria,12 atrophic gastritis,12 early13 and advanced gastric cancer.14-20 Carriers of the IL1RN*1/*2 genotype had higher gastric atrophy scores in Chinese patients.10 In Japanese patients IL-2 gene polymorphisms have been shown to increase the risk for gastric atrophy.21 A pro-inflammatory cytokine profile related to the presence of the IL1B-511T allele, the IL1RN*2/*2 genotype,15,16 the IL10 ATA/ATA,15 and the TNF308A15,16,18 genotypes increase the risk of noncardia gastric adenocarcinoma. However, these latter associations are less well established than the IL1B and IL1RN associations. A Chinese group recently reported a yet unconfirmed association of the
251 allele in the IL-8 promoter with an increased risk for gastric carcinoma.22 Gastroesophageal reflux disease (GERD) is a common disorder characterized by abnormal exposure of the esophageal mucosa to acid gastric contents. The incidence of GERD is increasing in Western countries. Patients colonized by virulent H. pylori strains expressing the cag pathogenicity island show more severe gastric inflammation but lower gastric acid output and protection against GERD. Interleukin-1b genotypes associated with higher IL-1b production and suppression of gastric acid secretion (interleukin IL1B-31C which is in nearly complete linkage disequilibrium with the
511T-polymorphism in European populations) and the IL1RN*2/*2 genotype have been shown to decrease the risk of reflux esophagitis.23 Chronic gastric inflammation caused by Helicobacter pylori infection can lead to gastric marginal zone lymphoma (GMZL). In the early phase of lymphoma, lymphocyte proliferation is driven by helicobacter antigens. However, host factors as certain cytokine polymorphisms significantly contribute to the risk to develop lymphoma. The IL1RN*2/2-, but not the IL1B-31 genotype, was significantly associated with risk of GMZL (odds ratio (OR), 5.51; 95% confidence interval (CI) 2.16–14.07).24 These results support the hypothesis that the risk of developing GMZL is influenced by inter-individual variation in the cellular inflammatory immune responses to H. pylori infection.

23.2 CHRONIC INFLAMMATORY BOWEL DISEASES Inflammatory bowel disease (IBD) comprises two major disorders: ulcerative colitis and Crohn’s disease. These disorders have distinct and overlapping pathologic and clinical characteristics and pathogenesis remains incompletely understood. For ulcerative colitis and Crohn’s disease the prevalence rates range between 50 to 80:100 000 in the countries of the Western hemisphere.25,26

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A number of observations suggest that genetic factors contribute to inflammatory bowel disease susceptibility. First-degree relatives of patients with IBD are 3 to 20 times more likely to develop IBD than the background population.27–29 A family history of CD is also associated with an earlier age of diagnosis in affected patients.30,31 Twin studies have shown substantially higher concordance rates for monozygotic compared to dizygotic twins indicating the importance of genetic factors for the development of IBD.32 Concordance rates have been consistently higher for Crohn’s disease than for ulcerative colitis suggesting a stronger genetic influence in CD. The specific gene(s) responsible for the inherited risk of IBD are not well-understood. Mutations within the NOD2 gene (also called IBD locus 1) present on chromosome 16 have been shown to confer susceptibility to Crohn’s disease.33,34 The wild-type NOD2 protein activates nuclear factor kappa B in response to a fragment of bacterial peptidoglycan; this process is deficient in patients with mutant forms of NOD2. Several studies have evaluated potential associations of IBD with major histocompatibility complex (MHC) loci.35,36 These studies have demonstrated that HLA-DR2 is associated with ulcerative colitis, particularly in the Japanese, and extraintestinal manifestations of CD are more commonly observed in patients with HLA-A2, HLA-DR1, and DQw5. The ability to delete or modify genes selectively (such as IL-2 and IL-10) in animal models has also contributed to the understanding of the genetic loci involved in IBD pathogenesis.37,38 These experiments have revealed several important observations: colitis is a non-specific phenotype that can result from alterations in a variety of genes. Most of these genes play a role in the mucosal immune system although some appear to affect the mucosal barrier epithelium. A single genetic alteration can be associated with a variable clinical presentation, depending upon the specific strain of mice used, suggesting that the actual phenotype results from interactions among multiple genetic loci. The lack of colitis observed in susceptible strains with genetic alterations when maintained in germ-free environments demonstrates that the genes confer disease susceptibility, but actual disease is dependent upon the presence of appropriate environmental factors.38,39 Cytokines like IL-1 and TNF-a play a key role in the regulation of inflammatory processes in the intestine. Other candidate genes associated with IBD include IL-4, IL-10, and interleukin 1 receptor antagonist. In murine studies, targeted deletion of an AU-rich region within the 30 -untranslated region of TNF results in increased transcript stability and translational efficiency, thereby resulting in increased overall expression of TNF.40 Particularly the efficacy of TNF-a antagonists in the treatment of Crohn’s disease is well recognized and raised the idea that TNF-a is the key cytokine in the development of CD. The TNF-genes are located within the major histocompatibility complex. A haplotype formed by alleles at five microsatellite loci in the TNF-region (the TNFa2b1c2d4e1 haplotype) has been associated with CD in one study (odds ratio 4.4, 95% confidence interval 1.3–16.1).41 A Japanese study reported associations between three SNPs in the TNF-a promoter region, including T to C at position
1031 (odds ratio 1.68, 95% confidence interval 1.18–2.39), C to A at nucleotide position
863 (odds ratio 1.72, 95% confidence interval 1.19–2.48), and C to T at position
857 (odds ratio 1.73, 95% confidence interval 1.23–2.43).42,43 A cosegregation of the
857C allele and Crohn’s disease has also been observed in a large Australian family study.44 The TNFA–1031C association has also been found in a TDT analysis of parents and affected offspring in the United Kingdom.43 In a Spanish study the TNF308 A/A genotype was associated with Crohn’s disease and certain disease features, no association was found for the
857 polymorphism.45 However, a recent Canadian study on TNF-a polymorphisms in Crohn’s disease was negative.46 A decreased ratio of mucosal interleukin-1 receptor antagonist to interleukin-1 production in inflammatory bowel disease patients suggests that there is insufficient production

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Cytokine Gene Polymorphisms in Multifactorial Conditions

of IL-1Ra to counterbalance the increased production of IL-1.47 A weak association of a VNTR polymorphism in the IL1RN gene has been reported in some studies, but this association has remained controversial.48–53 A study of patients and ethnically matched controls from two different centers in Los Angeles and one center in Italy found that the allele 2 of the IL1RN VNTR is associated with ulcerative colitis in Jewish Caucasians and Hispanics, but not in non-Jewish Caucasians.54 A recent Spanish study found no association between the IL1B–511 and the IL1RN VNTR polymorphisms and CD.45 A meta-analysis of eight IL1RN VNTR case-control association studies in North European Caucasian populations reported a minor association beetween allele 2 of the IL1RN VNTR and ulcerative colitis (odds ratio 1.2, 95% CI 1.04–1.45).55 Polymorphisms in other cytokine genes have been studied as well. However, the results of most of these studies have so far been unconfirmed and the functional consequences of the polymorphisms investigated are controversial. In German inflammatory bowel disease patients a significant association of the IL4–590T allele with Crohn’s disease has been found.56 A British study reported an association of Crohn’s with alleles resulting in high IL-4 transcription (
34 IL-4 promoter) and enhanced signalling activity (codon 576 IL-4 receptor) suggesting that IL-4 may have a role in the pathogenesis of Crohn’s disease.57 No associations have been observed for the IL-10 promoter polymorphisms in British and German patients.58,59 However, a recent Spanish study reported a significant association of the G14 microsatellites and the
1082 polymorphism with Crohn’s disease.60 IL-11 can downregulate LPS induced NFk-B activation and could thus counteract the effect of mutant NOD2 alleles that are associated with CD. In a German study a dinucleotide repeat in exon 4 of the IL11 gene showed a significant association with ulcerative colitis.61 No association was found between IL12B polymorphisms and Crohn’s disease in Dutch patients.62

23.3 LIVER DISEASES Chronic inflammation of the liver (chronic hepatitis) can be caused by different diseases which include among others viral agents (hepatitis B–D), autoimmune liver diseases (autoimmune hepatitis, primary biliary cirrhosis, primary sclerosing cholangitis), metabolic diseases (hemochromatosis, Wilson’s disease), and nutritive toxic liver damage (alcoholic and non-alcoholic steratohepatitis). Cytokine polymorphisms have been studied in all types of liver diseases. I will restrict this review to hepatitis B and C virus infection, since more than 90% of relevant papers deal with these two diseases in relation to outcome. Fibrosis is a wound healing response in damaged liver regions, which develops in almost all patients with chronic liver injury at variable rates depending in part upon the cause of liver disease and host factors.63–65 Progressive fibrosis will eventually result in liver cirrhosis with its sequelae portal hypertension, liver failure and hepatocellular carcinoma. Hepatocellular damage results in the recruitment of inflammatory cells and the activation of Kupffer cells and hepatic stellate cells (HSC), which amplify the inflammatory response. Factors involved in this early phase include the proapoptotic receptor Fas, accumulation of reactive oxygen species, and the release of pro-inflammatory (interleukin 1b (IL-1b) and tumor necrosis factor-a (TNF-a)) and/or anti-inflammatory (IL-10) cytokines.66,67 If the hepatic injury persists, activated hepatic stellate cells migrate and proliferate at the sites of tissue remodeling. As a consequence, a marked secretion of extracellular matrix proteins, mainly collagens, accumulates in the damaged tissue. ROS, growth factors, chemokines, and pro-fibrogenic cytokines (i.e., transforming growth factor (TGF-b), angiotensin II, and leptin) are involved in this latter phase.

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Fibrosis reflects a balance between matrix production and degradation. The degradation of extracellular matrix is a key event in hepatic fibrosis. Early disruption of the normal hepatic matrix by matrix proteases hastens its replacement by scar matrix, which has deleterious effects on cell function. The main cellular source of extracellular matrix in the liver is the hepatic stellate cell. The best-studied component of hepatic scar is collagen type I, the expression of which is regulated post-transcriptionally in hepatic stellate cells. The most potent stimulus for collagen I production is TGF-b. TGF-b also stimulates the production of other matrix components including cellular fibronectin and proteoglycans.66,68 Other factors that stimulate collagen I by activated stellate cells in culture include retinoids, angiotensin II,69 interleukin-1b, tumor necrosis factor, and acetaldehyde. However, none of these is as potent as TGFb1. Hepatic fibrosis can be viewed as a process in which multiple genes interact with environmental factors.64 Well-characterized causal agents of liver fibrosis include chronic viral hepatitis infection and alcohol abuse. However, not all patients exposed to a similar causal agent develop the same degree of liver fibrosis. For example, while viral factors (i.e., genotype or viral load) do not influence fibrosis progression in patients with hepatitis C virus infection, host factors (i.e., weight, age, or gender) seem to play an important role. Large-scale studies have allowed the identification of patients with rapid fibrosis progression per unit time (‘‘rapid fibrosers’’) and with slow fibrosis progression (‘‘slow fibrosers’’).70 The genetic determinants involved in this different individual behavior are largely unknown, but candidate genes have been identified. However, most association studies so far have yielded controversial results. During the last few years, numerous association studies focused on progression of liver fibrosis and/or development of cirrhosis in patients with different types of chronic liver diseases. Gene variations influencing the cause of prevalent liver diseases have been identified. Common methodologic limitations of genetic epidemiologic studies, which may explain these divergent results are as follows: (1) a low sample size leading to a lack of statistical power; (2) recruitment of patients from single institutions (mainly tertiary hospitals), where individuals suffer from more advanced diseases compared with primary centers (as a consequence, some ‘‘alleles’’ associated with bad prognosis could be, in fact, associated with an increased susceptibility to the disease); (3) no rigorous validation of the molecular biology techniques; (4) study of only a single gene or unrelated genes; (5) no investigation of gene–environmental interactions; and (6) study of alleles with unclear functional significance.

23.3.1 HEPATITIS B HBV-infected subjects generally fall into one of the following clinical types: (1) asymptomatic HBV carriers and cryptic hepatitis; (2) acute hepatitis; (3) chronic hepatitis; (4) liver cirrhosis with or without decompensated liver failure; and (5) primary hepatocellular carcinoma associated with HBV infection.71,72 However the pattern and clinical outcome of the infection are highly variable and a strong genetic component is suspected to affect the individual susceptibility to HBV,72 although to date no single allele has been clearly associated with HBV persistence or disease severity. Several observations suggest that the course of HBV infection is influenced by genetic host factors.72,73 HBV is not cytopathic and liver injury is caused by the host immune attack against the virus. Infection with the same virus leads to variable disease courses in different individuals.74 So far, case control studies have reported associations of persistent HBV infection with MHC class II alleles72 and polymorphisms in cytokine genes. Tumor necrosis factor (TNF-a) is an important cytokine involved in non-cytotoxic antiviral mechanisms.75 Controversial results regarding the association of polymorphisms

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Cytokine Gene Polymorphisms in Multifactorial Conditions

in the TNF-a promoter region with the outcome of acute hepatitis B virus infection have been reported. Ho¨hler et al. found an association between the TNF-238A SNP and the development of chronic hepatitis in German patients.76 In a large Korean study the TNF-a promoter alleles associated with higher plasma levels, i.e. the presence of the
308A allele (TNFA-308A 308A/G or A/A) or the absence of the
863A (TNFA-863C or 863C/C) variant were strongly associated with the resolution of HBV infection. The promoter haplotypes (
1031T;
863C,
857C;
308G;
238G;
163G) and haplotype 2 (
1031C;
863A;
857C;
308G;
238G;
163G) were significantly associated with HBV clearance showing protective antibody production against, and persistence of HBV infection, respectively (P ¼ 0.003–0.02).77 However investigations in Japanese and Jewish patients with hepatitis B virus infection have reported conflicting results. Japanese patients with chronic hepatitis B virus infection showed no association with TNF-a promoter variation.78,79 There was however an association of the IL10
1082A/
819T/
592A promoter-haplotype with the asymptomatic carrier state in the Jewish patients.80 In Jewish patients an association of chronic hepatitis B with a polymorphism in the IFNG gene was reported (879 A/A genotype).79 No associations were found for IL6 and IL10 polymorphisms. Patients with chronic hepatitis B virus infection and cirrhosis of the liver have an annual risk of 3–5% to develop hepatocellular carcinoma. Several recent publications have suggested that the risk of liver cancer in chronic hepatitis B patients is related to the presence of certain cytokine polymorphisms. In a Chinese study the presence of the IL1RN*2 allele together with the IL1B-31 T/T genotype had an odds ratio of 5.76 (CI 1.79–18.53) for the development of hepatocellular carcinoma.81 In another Chinese population putative low activity genotypes of IFN-g, IL-12, and IL-18 were associated with a non-significant increase in the risk of hepatocellular carcinoma whereas low activity genotypes of genotypes of Th2 cytokines IL-4 and IL-10 lead to a reduced risk for liver cancer.82 A Japanese study reported a protective effect of the TGFB1 gene polymorphism þ29 C/C against liver cancer in chronic HBV carriers. No association was found for TNFA, IFNG, IL6, and IL10 polymorphisms.83 However, due to the heterogeneity of the studied populations, small sample sizes and ethnic differences, results of immunogenetic studies in hepatitis B virus infection so far have been conflicting. A more elegant and prospective way to study the immune response to the hepatitis B virus are hepatitis B antigen vaccination studies. Since gender, age, body mass index, smoking, mode of and age at infection significantly influence HBsAg responsiveness, a prospective study allows to control for these variables and to calculate the true contribution of genetic polymorphisms to anti-HBs responsiveness. In a large twin vaccination study individuals carrying the IL10
1082A/
819C/
592C haplotype had geometric mean titers twice as high as individuals without this haplotype.84 The influence of the IL10 ACC haplotype was as strong as that of age, gender or BMI. Comparison of dizygotic IL10 haplo-identical and haplotype different dizygotic twins allowed the estimation of the relative contribution of the IL10 ACC haplotype to the overall heritability of HBsAg responsiveness.84 Approximately 25% of heritability was determined by variability in the IL10 promoter, shown by higher intraclass correlations of IL10 haplotype-identical in comparison with IL10 haplotype-different dizygotic twins. The effect of the IL-10 promoter variability on HBsAg responsiveness was weaker than that of the MHC,73 which had been estimated to account for 40% of the genetic determination of vaccine response. Although the vaccination model is a simplification of the complex immune response during viral infections, these data underline the importance of IL10 promoter variability for humoral immune responses to HBsAg and they provide for the first time an estimate of

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the relative contribution of the cytokine promoter haplotypes to the overall heritability of immune responsiveness.84

23.3.2 CHRONIC HCV INFECTION Hepatitis C virus (HCV) infection causes a wide spectrum of liver disease ranging from acute and chronic hepatitis to cirrhosis and hepatocellular carcinoma.72 Acute hepatitis C virus infection progresses to chronic hepatitis in about 70–80% of infected patients. A number of studies have tried to identify polymorphisms in cytokine genes that influence development of chronic disease. The results of these studies have been controversial since adequate controls are hard to find (individuals exposed to hepatitis C that have recovered from infection) and some studies have used seronegative individuals as controls. In those studies using HCV antibody positive, RNA negative controls, no definite association with cytokine polymorphisms has been reported. A British study found no significant difference in genotype frequencies between HCV clearance and nonclearance groups for IL1B (
511 and þ3954), IL1A (þ4845), IL1RN (þ2018), IL6 (
174), or IL10 (
1082) SNP.85 A German study did not find an association between spontaneous recovery from hepatitis C virus infection and IL12B polymorphisms within the promoter region (4 bp insertion/deletion) and the 30 -UTR (1188-A/C).86 In contrast a British group recently reported an association of chronic infection with homozygosity for the 30 -UTR A allele of the IL12 gene (66% vs. 50%; 2 ¼ 4.12, p ¼ 0.04 with Yates correction). This allele has been associated with lower IL-12 production.87 In Afro-Americans the TNF-863C polymorphism has been associated with viral clearance.88 A British study reported an association of self-limiting infection with the IL10
592AA genotype (OR ¼ 2.05; P ¼ 0.028)89 which was not confirmed in two other studies in populations of similar ethnicity.90,91 An Irish study reported an association of persistent infection with a high IL-6 production profile (P ¼ 0.02). However, no associations were observed between polymorphisms of TNF-a, IL-10, or IFN-g and viral clearance or persistent infection.90 These negative results were confirmed in a British study that found no association of viral clearance with IL1A, IL1B and IL1RN, three polymorphic sites in the IL10 gene promoter (
1082,
819,
592) nor with two SNPs in the tumor necrosis factor-alpha promoter (
308,
238).91 The natural history of patients with chronic hepatitis C is characterized by a slow progression of liver fibrosis.72 Following infection, cirrhosis may develop after an average of 20 to 30 years. In some patients, the rate of fibrosis progression is much faster and cirrhosis develops after 10 to 15 years, whereas in others the rate of progression is negligible. The pathogenesis of HCV-induced liver fibrosis is poorly understood, reflecting in part the lack of a rodent model of persistent HCV infection. HCV escapes surveillance of HLA-IIdirected immune response and infects hepatocytes, causing oxidative stress and inducing the recruitment of inflammatory cells.67 Both factors lead to HSC activation and collagen deposition.64,66 Moreover, HCV proteins (i.e., core protein) stimulate secretion of profibrogenic cytokines by hepatocytes and can directly induce fibrogenic actions in HSCs. The answer to the question whether cytokine polymorphisms influence the disease progression and treatment outcome in hepatitis C virus infection remains controversial. Although factors such as duration of infection, gender, and alcohol consumption influence fibrosis progression none of the studies has incorporated them in a multiple regression analysis. Variations in genes encoding key cytokines involved in human fibrogenesis may regulate fibrosis progression. These cytokines include angiotensin II and TGF-b, which play an important role in experimental liver fibrosis.64 Polymorphisms in the angiotensinogen gene, the angiotensin II precursor, as well as the TGFB gene (slow fibrosis progression

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codon 10 Leu/Leu and 25 Arg/Pro fast fibrosis progression) influence fibrosis progression in HCV infection.92,93 Interestingly, patients having polymorphisms in both genes progress more rapidly than those having only one polymorphism. However, these TGF-b associations could not be confirmed in Japanese and Chinese patients.94 No influence on fibrosis progression could be shown for the interleukin IL1A(
889), IL1B(
511 and þ3954), IL-1RN (intron 2 VNTR), IL4 (intron 3 VNTR) and TNF-a(
308) loci 95 in German patients with hepatitis C virus infection. The IL10
1082A/A genotype and the ATA/ATA and ACC/ACC homozygous haplotypes were associated with rapid fibrosis progression in European patients.89 The treatment for patients with chronic hepatitis C has been rapidly evolving. With the standard treatment of pegylated interferon-a plus ribavirin sustained virological responses in more than 80% of patients with viral genotype 2 and 3 can be achieved. Treatment response depends on the viral genotype, viral load, the stage of liver disease, body mass index, coinfections with, for example, hepatitis B or human immunodeficiency virus, ethnicity (response lower in African-Americans), and the treatment regimen.96 None of the studies investigating the association of cytokine polymorphisms with treatment responses in chronic hepatitis C virus infection has included all of these factors in a multivariate analysis of the results. Therefore reported data are controversial and no clear picture has emerged. Most consistent data regarding treatment response have been reported for IL-10 promoter polymorphisms. In a small American study with 49 responders and 55 non responders to treatment with ribavirin and interferon carriage of the
592A or the
819T SNP was associated with sustained response (odds ratio OR ¼ 2.2; P ¼ 0.016).97 The haplotype consisting of the 108-bp IL10.R microsatellite and
3575T,
2763C,
1082A,
819T, and
592A was also associated with SR (OR ¼ 2.65; P ¼ 0.01). Stratification for viral genotype, baseline viral RNA concentration, and histologic status identified homozygosity for the haplotype as the principal determinant: all five homozygous individuals achieved SR (OR ¼ 13.7; P ¼ 0.025), whereas heterozygotes differed only slightly from wild-type carriers. In this study no association was found between treatment response and TNF- promoter SNPs
238G/A and
308G/A.97 The association of the IL10 promoter
592A and
819T alleles and the ATA haplotype with response to IFN-alpha therapy was also described in Australian patients (P ¼ 0.016).98 In addition, the author could show that following in vitro stimulation of peripheral blood mononuclear cells, the IL10 promoter haplotypes, GCC, ACC, and ATA, were associated with high, intermediate, and low IL-10 production, respectively. However, these results could not be confirmed among the participants of a large European multicenter study which reported an association of treatment response with the IL10 –1082 G/G genotype and the
1082G/
819C/
592C haplotype.89 Carriage of the TGFB þ 29C/C and the IL10
1082G/G genotypes was asssociated with treatment failure in American hepatitis C patients.99 In German HCV genotype1-infected patients with high baseline viremia the IL12B 30 -UTR 1188-C-allele was associated with significantly higher sustained virologic response (SVR) rates.86 No association with treatment response has been found for the IFN-g SNP at position 874 in Chinese patients100 and TNF-a promoter polymorphisms in various Chinese, Italian, and North-American patients.101–104 Once cirrhosis is established, patients with chronic hepatitis C infection have an annual risk of approximately 5% to develop hepatocellular carcinoma. The risk is highest in patients with high inflammatory activity. Two recent papers suggest that the risk for liver cancer in this patient group is influenced by cytokine polymorphisms. In a multivariate analysis in Japanese patients the IL1B-31T/T genotype, a-fetoprotein 420 mg/l, the presence of cirrhosis, male sex, and age 460 years were associated with the development of HCC at odds ratios of 3.73 (T/T vs. C/C), 4.12, 4.03, 3.89, and 3.27, respectively. The IL1B-31

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and -511 loci were in near complete linkage disequilibrium, and the IL1B-511/-31 haplotype C–T was significantly associated with the presence of HCC (odds ratio of 1.51, P ¼ 0.02).105 In the second Japanese study the IL1B-511 T/T genotype was found to be significant risk factors for the development of HCC.106

23.4 FUTURE DIRECTIONS The conflicting data from investigations in inflammatory bowel diseases and viral hepatitis, in particular, highlight the problems of association studies. For many of the investigated polymorphisms the functional implications are still unclear. The decision to study a certain cytokine polymorphism in a disease should ideally be based on functional data from animal or cell culture studies. The effects of most cytokine polymorphisms on disease susceptibility or treatment responses are weak. Consequently most of the studies in the past have been underpowered and remain unconfirmed. Future studies should use accepted phenotypes and disease outcomes. Data have to be stratified for confounding factors like age, sex, body mass index, ethnicity, and other environmental factors. Only with the incorporation of these changes in the study design will association studies contribute to our rapidly increasing knowledge in gastrointestinal diseases.

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16. El-Omar, E. M. et al., Increased risk of noncardia gastric cancer associated with proinflammatory cytokine gene polymorphisms, Gastroenterology, 124, 1193, 2003. 17. Zeng, Z. R. et al., Association of interleukin 1B gene polymorphism and gastric cancers in high and low prevalence regions in China, Gut, 52, 1684, 2003. 18. Rocha, G. A. et al., Combined inflammatory IL1b cluster/TNFA polymorphisms and H. pylori virulence markers in the risk of gastric carcinoma, Helicobacter, 8, 419, 2003. 19. Graziano, F. et al., Prognostic role of interleukin-1beta gene and interleukin-1 receptor antagonist gene polymorphisms in patients with advanced gastric cancer, J. Clin. Oncol., 23, 2339, 2005. 20. Ruzzo, A. et al., Interleukin 1B gene (IL-1B) and interleukin 1 receptor antagonist gene (IL-1RN) polymorphisms in Helicobacter pylori-negative gastric cancer of intestinal and diffuse histotype, Ann. Oncol., 16, 887, 2005. 21. Togawa, S. et al., Interleukin-2 gene polymorphisms associated with increased risk of gastric atrophy from Helicobacter pylori infection, Helicobacter, 101, 72, 2005. 22. Lee, W. P. et al., The
251T allele of the interleukin-8 promoter is associated with increased risk of gastric carcinoma featuring diffuse-type histopathology in Chinese population, Clin. Cancer Res., 11, 6431, 2005. 23. Queiroz, D. M. et al., IL1B and IL1RN polymorphic genes and Helicobacter pylori cagA strains decrease the risk of reflux esophagitis, Gastroenterology, 127, 73, 2004. 24. Rollinson, S. et al., Gastric marginal zone lymphoma is associated with polymorphisms in genes involved in inflammatory response and antioxidative capacity, Blood, 102, 1007, 2003. 25. Hiatt, R. A. et al., Epidemiology of inflammatory bowel disease in a defined northern California population, West J. Med., 149, 541, 1988. 26. Moum, B. et al., Incidence of Crohn’s disease in four counties in southeastern Norway, 1990–93. A prospective population-based study. The Inflammatory Bowel South-Eastern Norway (IBSEN) Study Group of Gastroenterologists, Scand. J. Gastroenterol., 31, 355, 1996. 27. Roth, M. P. et al., Familial empiric risk estimates of inflammatory bowel disease in Ashkenazi Jews, Gastroenterology, 96, 1016, 1989. 28. Monsen, U. et al., Prevalence of inflammatory bowel disease among relatives of patients with ulcerative colitis. Scand. J. Gastroenterol., 22, 214, 1987. 29. Fielding, J. F., The relative risk of inflammatory bowel disease among parents and siblings of Crohn’s disease patients, J. Clin. Gastroenterol., 8, 655, 1986. 30. Yang, H. et al., Familial empirical risks for inflammatory bowel disease: differences between Jews and non-Jews, Gut, 34,517, 1993. 31. Lee, J. C. et al., Inflammatory bowel disease in 67 families each with three or more affected first-degree relatives, Gastroenterology, 111, 587, 1996. 32. Thompson, N. P. et al., Genetics versus environment in inflammatory bowel disease: results of a British twin study, Br. Med. J., 312, 95, 1996. 33. Ogura, Y. et al., A frameshift mutation in NOD2 associated with susceptibility to Crohn’s disease, Nature, 411, 603, 2001. 34. Hugot, J. P. et al., Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn’s disease, Nature, 411, 599, 2001. 35. Mathew, C. G. et al., HLA and inflammatory bowel disease, Lancet, 348, 68, 1996. 36. Satsangi, J. et al., Contribution of genes of the major histocompatibility complex to susceptibility and disease phenotype in inflammatory bowel disease, Lancet, 347, 1212. 1996. 37. Morales, V. et al., Probing the gastrointestinal immune function using transgenic and knockout technology, Curr. Opin. Gastroenterol., 12, 577, 1996. 38. Contractor, N. V. et al., Lymphoid hyperplasia, autoimmunity, and compromised intestinal intraepithelial lymphocyte development in colitis-free gnotobiotic IL-2-deficient mice, J. Immunol., 160, 385, 1998. 39. Taurog, J. D. et al., The germfree state prevents development of gut and joint inflammatory disease in HLA-B27 transgenic rats, J. Exp. Med., 180, 2359, 1994. 40. Kontoyiannis, D. et al., Impaired on/off regulation of TNF biosynthesis in mice lacking TNF AU-rich elements: implications for joint and gut-associated immunopathologies, Immunity, 10, 387, 1999.

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41. Plevy, S. E. et al., Tumor necrosis factor microsatellites define a Crohn’s disease–associated haplotype on chromosome 6, Gastroenterology, 110, 1053, 1996. 42. Negoro, K., et al., Crohn’s disease is associated with novel polymorphisms in the 50 -flanking region of the tumor necrosis factor gene, Gastroenterology, 117, 1062, 1999. 43. Kinouchi, Y. et al., Transmisssion disequilibrium test confirms the association of the TNFa 1031C allele with Crohn’s disease, Gastroenterology, 120, 456, 2001. 44. O’Callaghan, N. J. et al., Association of TNF-alpha-857C with inflammatory bowel disease in the Australian population, Scand. J. Gastroenterol., 38, 533, 2003. 45. Ferreira, A. C. et al., NOD2/CARD15 and TNFA, but not IL1B and IL1RN, are associated with Crohn’s disease, Inflamm. Bowel Dis., 11, 331, 2005. 46. Zipperlen, K. et al., Association of TNF-alpha polymorphisms in Crohn disease, Hum. Immunol., 66, 56, 2005. 47. Casni-Raggi, V. et al., Mucosal imbalance of IL-1 and IL-1 receptor antagonist in inflammatory bowel disease. A novel mechanism of chronic intestinal inflammation, J. Immunol., 154, 2434, 1995. 48. Bioque G. et al., Allelic polymorphism in IL-1 beta and IL-1 receptor antagonist (IL-1Ra) genes in inflammatory bowel disease, Clin. Exp. Immunol., 102, 379, 1995. 49. Mansfield, J. C. et al., Novel genetic association between ulcerative colitis and the antiinflammatory cytokine interleukin-1 receptor antagonist, Gastroenterology, 106, 637, 1994. 50. Louis, E. et al., Cytokine polymorphisms and inflammatory bowel disease, Gut, 39, 705, 1996. 51. Heresbach, D. et al., Significance of interleukin-1beta and interleukin-1 receptor antagonist genetic polyymorphism in inflammmatory bowel diseases, Am. J. Gastroenterol., 92, 1164, 1997. 52. Hacker, U. T. et al., Inflammatory bowel disease: no association between allele combinations of the interleukin (IL)-1 beta and IL-1 receptor antagonist gene polymorphisms, Eur. J. Clin. Invest., 28, 214, 1998. 53. Papo, M. et al., Genetic heterogeneity within ulverative colitis determined by an interleukin-1 receptor antagonist gene polymorphism and antineutrophil cytoplamic antibodies. Eur. J. Gastroenterol. Hepatol., 11, 413, 1999. 54. Tountas, N. A. et al., Functional and ethnic association of allele 2 of the interleukin-1 receptor antagoniast gene in ulcerative colitis, Gastroenterology, 117, 806, 1999. 55. Carter, M. J. et al., Asssociation of the interleukin-1 receptor antagonist gene with ulcerative colitis in Northern European Caucasians, Gut, 48, 461, 2001. 56. Klein, W. et al., Interleukin-4 and interleukin-4 receptor gene polymorphisms in inflammatory bowel diseases, Genes Immun., 2, 287, 2001. 57. Aithal, G. P. et al., Association of single nucleotide polymorphisms in the interleukin-4 gene and interleukin-4 receptor gene with Crohn’s disease in a British population, Genes Immun., 2, 44, 2001 58. Klein, W. et al., The IL-10 gene is not involved in the predisposition to inflammatory bowel disease, Electrophoresis, 21, 3578, 2000. 59. Aithal, G. P. et al., Role of polymorphisms in the interleukin-10 gene in determining disease susceptibility and phenotype in inflammatory bowel disease, Dig. Dis. Sci., 46, 1520, 2001. 60. Fernandez, L. et al., Interleukin-10 polymorphisms in Spanish patients with IBD, Inflamm. Bowel Dis., 11, 739, 2005. 61. Klein, W. et al., A polymorphism in the IL11 gene is associated with ulcerative colitis, Genes Immun., 3, 494, 2002. 62. Zwiers, A. et al., Definition of polymorphisms and haplotypes in the interleukin-12B gene: association with IL-12 production but not with Crohn’s disease, Genes Immun., 5, 675, 2004. 63. Poynard, T. et al., A comparison of fibrosis progression in chronic liver diseases, J. Hepatol., 38, 257, 2003. 64. Bataller, R. et al., Genetic polymorphisms and the progression of liver fibrosis: A critical appraisal, Hepatology, 37, 493, 2003. 65. Hillebrandt, S. et al., Genome-wide analysis of hepatic fibrosis in inbred mice identifies the susceptibility locus Hfib1 on chromosome 15, Gastroenterology, 123, 2041, 2002. 66. Gressner, A. M. et al., The cell biology of liver fibrogenesis — an imbalance of proliferation, growth arrest and apoptosis of myofibroblasts, Cell Tissue Res., 292, 447, 1998.

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67. Pinzani, M. et al., Cytokine receptors and signaling in hepatic stellate cells, Semin. Liver Dis., 21, 397, 2001. 68. George, J. et al., Transforming growth factor-beta initiates wound repair in rat liver through induction of the EIIIA-fibronectin splice isoform, Am. J. Pathol., 156, 115, 2000. 69. Bataller, R. et al., NADPH oxidase signal transduces angiotensin II in hepatic stellate cells and is critical in hepatic fibrosis, J. Clin. Invest., 112, 1383, 2003. 70. Poynard, T. et al., Natural history of liver fibrosis progression in patients with chronic hepatitis C. The OBSVIRC, METAVIR, CLINIVIR, and DOSVIRC groups, Lancet, 22, 349, 825, 1997. 71. Lee, W. M., Hepatitis B virus infection, N. Engl. J. Med., 337, 1733, 1997. 72. Thio, C. L. et al., Chronic viral hepatitis and the human genome, Hepatology, 31, 819, 2000. 73. Hohler, T. et al., Differential genetic determination of immune responsiveness to hepatitis B surface antigen and to hepatitis A virus: a vaccination study in twins, Lancet, 360, 991, 2002. 74. Karayiannis, P. et al., Fulminant hepatitis associated with hepatitis B virus e antigen-negative infection: importance of host factors. Hepatology, 22, 1628, 1995. 75. Knight, J. C. et al., Inherited variability of tumor necrosis factor production and susceptibility to infectious disease, Proc. Assoc. Am. Physicians, 111, 290, 1999. 76. Hohler, T. et al., A tumor necrosis factor-alpha (TNF-alpha) promoter polymorphism is associated with chronic hepatitis B infection, Clin. Exp. Immunol., 111, 579, 1998. 77. Kim, Y. J. et al., Association of TNF-alpha promoter polymorphisms with the clearance of hepatitis B virus infection, Hum. Mol. Genet., 12, 2541, 2003. 78. Higuchi, T. et al., Polymorphism of the 50 flanking region of the human tumor necrosis factor (TNF)-alpha gene in Japanese, Tissue Antigens, 51, 605, 1998. 79. Ben-Ari, Z. et al., Cytokine gene polymorphisms in patients infected with hepatitis B virus, Am. J. Gastroenterol., 98, 144, 2003. 80. Miyazoe, S. et al., Influence of interleukin-10 gene promoter polymorphisms on disease progression in patients chronically infected with hepatitis B virus, Am. J. Gastroenterol., 97, 2086, 2002. 81. Chen, C. C. et al., Association of cytokine and DNA repair gene polymorphisms with hepatitis B-related hepatocellular carcinoma, Int. J. Epidemiol., 1, 1911, 2005. 82. Nieters, A. et al., Effect of cytokine genotypes on the hepatitis B virus-hepatocellular carcinoma association, Cancer, 103, 740, 2005. 83. Migita, K. et al., Cytokine gene polymorphisms in Japanese patients with hepatitis B virus infection — association between TGF-beta1 polymorphisms and hepatocellular carcinoma, J. Hepatol., 42, 505, 2005. 84. Hohler, T. et al., A functional polymorphism in the IL-10 promoter influences the response after vaccination with HBsAg and hepatitis A, Hepatology, 42, 72, 2005. 85. Minton, E. J. et al., Clearance of hepatitis C virus is not associated with single nucleotide polymorphisms in the IL-1, -6, or -10 genes, Hum. Immunol., 66, 127, 2005 86. Mueller, T. et al., Influence of interleukin 12B (IL12B) polymorphisms on spontaneous and treatment-induced recovery from hepatitis C virus infection, J. Hepatol., 41:652, 2004. 87. Houldsworth, A. et al., Polymorphisms in the IL-12B gene and outcome of HCV infection, J. Interferon Cytokine Res., 25, 271, 2005. 88. Thio, C. L. et al., An analysis of tumor necrosis factor alpha gene polymorphisms and haplotypes with natural clearance of hepatitis C virus infection, Genes Immun., 5, 294, 2004. 89. Knapp, S., et al., Interleukin-10 promoter polymorphisms and the outcome of hepatitis C virus infection, Immunogenetics, 55, 362, 2003. 90. Barrett, S. et al., Polymorphisms in tumor necrosis factor-alpha, transforming growth factor beta, interleukin-10, interleukin-6, interferon-gamma, and outcome of hepatitis C virus infection, J. Med. Virol., 71, 212, 2003. 91. Constantini, P. K. et al., Interleukin-1, interleukin-10 and tumor necrosis factor-alpha gene polymorphisms in hepatitis C virus infection: an investigation of the relationships with spontaneous viral clearance and response to alpha-interferon therapy, Liver, 22, 404, 2002. 92. Gewaltig, J. et al., Association of polymorphisms of the transforming growth factor-beta1 gene with the rate of progression of HCV-induced liver fibrosis, Clin. Chim. Acta, 316, 83, 2002.

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93. Wang, H. et al., Transforming growth factor-beta1 gene polymorphisms are associated with progression of liver fibrosis in Caucasians with chronic hepatitis C infection, World J. Gastroenterol., 11, 1929, 2005. 94. Suzuki, S. et al., Transforming growth factor-beta-1 genetic polymorphism in Japanese patients with chronic hepatitis C virus infection, J. Gastroenterol. Hepatol., 18, 1139, 2003. 95. Bahr, M. J. et al., Cytokine gene polymorphisms and the susceptibility to liver cirrhosis in patients with chronic hepatitis C, Liver Int., 23, 420, 2003. 96. Zeuzem, S., Heterogeneous virologic response rates to interferon-based therapy in patients with chronic hepatitis C: who responds less well?, Ann. Intern. Med., 140, 370, 2004. 97. Yee, L. J. et al., Interleukin 10 polymorphisms as predictors of sustained response in antiviral therapy for chronic hepatitis C infection, Hepatology, 33, 708, 2001. 98. Edwards-Smith, C. J. et al., Interleukin-10 promoter polymorphism predicts initial response of chronic hepatitis C to interferon alfa, Hepatology, 30, 526, 1999. 99. Vidigal, P. G. et al., Polymorphisms in the interleukin-10, tumor necrosis factor-alpha, and transforming growth factor-beta1 genes in chronic hepatitis C patients treated with interferon and ribavirin, J. Hepatol., 36, 271, 2002. 100. Dai, C. Y. et al., Polymorphisms in the interferon-gamma gene at position þ874 in patients with chronic hepatitis C treated with high-dose interferon-alpha and ribavirin, Antiviral Res., 67, 93, 2005. 101. Rosen, H. R. et al., Tumor necrosis factor genetic polymorphisms and response to antiviral therapy in patients with chronic hepatitis C, Am. J. Gastroenterol., 97, 714, 2002. 102. Yu, M. L. et al., Tumor necrosis factor alpha promoter polymorphisms at position
308 in Taiwanese chronic hepatitis C patients treated with interferon-alpha, Antiviral Res., 59, 35, 2003. 103. Schiemann, U. et al., Response to combination therapy with interferon alfa-2a and ribavirin in chronic hepatitis C according to a TNF-alpha promoter polymorphism, Digestion, 68, 1, 2003. 104. Airoldi, A. et al., Lack of a strong association between HLA class II, tumor necrosis factor and transporter associated with antigen processing gene polymorphisms and virological response to alpha-interferon treatment in patients with chronic hepatitis C, Eur. J. Immunogenet., 31, 259, 2004. 105. Wang, Y. et al., Interleukin-1beta gene polymorphisms associated with hepatocellular carcinoma in hepatitis C virus infection, Hepatology, 37, 65, 2003. 106. Tanaka, Y. et al., Impact of interleukin-1beta genetic polymorphisms on the development of hepatitis C virus-related hepatocellular carcinoma in Japan, J. Infect. Dis., 187, 1822, 2003.

24

Pulmonary Fibrosis Berran Yucesoy and Michael I. Luster

CONTENTS 24.1 24.2

Overview of Pulmonary Fibrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351 Cytokines, Metalloproteinases and Fibrogenic Mediators in Fibrotic Diseases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352 24.2.1 Inflammatory Cytokines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352 24.2.2 Th Cytokines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353 24.2.3 Metalloproteinases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354 24.2.4 Fibrogenic Mediators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354 24.3 Cytokine Gene Polymorphisms and Interstitial Lung Diseases . . . . . . . . . . . . . . . . . . 354 24.4 Gene-Gene and Gene-Environment Interactions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 24.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358

24.1 OVERVIEW OF PULMONARY FIBROSIS The pathogenesis of fibrotic diseases is similar regardless of whether the lung or extrapulmonary tissues are involved. The disease is characterized by chronic inflammation, excessive accumulation of matrix proteins and destruction of normal tissue structure.1,2 Although the etiology of pulmonary fibrotic diseases is diverse, the process universally involves an imbalance between matrix formation and degradation. Studies have shown that accumulation of matrix proteins, mainly produced by fibroblasts and myofibroblasts, is responsible for the alveolar wall damage and distortion of lung parenchyma. Three, sometimes overlapping, phases have been proposed in the development of pulmonary fibrosis including initial triggering events, the inflammatory response and the fibrotic response. A diverse group of insults including drugs (bleomycin, cisplatin), radiation, physical injury, or viral infections as well as collagen-vascular diseases, such as systemic sclerosis, may trigger the development of fibrosis.1,3 Regarding environmental factors, an elevated risk for idiopathic pulmonary fibrosis (IPF) occurs in subjects exposed to mineral dusts (e.g. silica or asbestos), metal or wood dust and tobacco smoking.4–6 The tissue response involves sequentially alveolar epithelial cell injury or activation, inflammation, proliferation, and differentiation of interstitial cells and collagen production. Chronic inflammation occurs following the initial injury and is characterized by activation of resident cells and inflammatory cell infiltration, interstitial edema and local cell proliferation.1,7 Cytokines, such as interleukin-1 (IL)-1, IL-4, IL-8 and tumor necrosis factor (TNF)-a, and growth factors, such as platelet-derived growth factor (PDGF) and transforming growth factor (TGF)-b1, are involved in the recruitment of inflammatory cells into the alveolar walls and spaces. A number of these mediators also play a role in the remodeling process through fibroblast proliferation and collagen synthesis. Therefore, the early and persistent expression of pro-inflammatory cytokines and subsequent presence of cell-surface adhesion molecules and chemotactic molecules are important in mediating 351

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FIGURE 24.1 Simplified scheme of the phases involved in the pathogenesis of pulmonary fibrosis. A diverse group of insults may trigger the initial lung injury followed by chronic inflammation. If inflammation is not resolved, fibrotic phase emerges with the overproduction of collagen and other matrix proteins, resulting in the development of fibrosis. In this pattern, genetic variations in related genes may influence susceptibility and modify progression or severity of disease.

fibrosis.2,3 Although this pathway is common for most interstitial lung diseases, IPF may develop in the absence of an inflammatory process.8,9 If inflammation is not resolved, fibroblasts migrate and proliferate in areas of acute injury and secrete an excessive amount of collagen and other matrix proteins. These proteins are deposited in the interstitial space and gradually cause irreversible pulmonary fibrosis.10–12 Fibroblasts also release proteases that degrade and remodel the matrix proteins.2 The aberrant tissue remodeling involves the families of matrix metalloproteinases (MMPs) and tissue inhibitor of metalloproteinases (TIMPs). The changes in the levels, activities and balance between MMPs and TIMPs play a significant role in the altered extracellular matrix (ECM) metabolism due to their capacity to cleave structural proteins such as collagens and elastin.13,14 Figure 24.1 shows the hypothetical scheme of the events in the pathogenesis of pulmonary fibrosis.

24.2 CYTOKINES, METALLOPROTEINASES AND FIBROGENIC MEDIATORS IN FIBROTIC DISEASES 24.2.1 INFLAMMATORY CYTOKINES The pathogenesis of pulmonary fibrosis appears to be driven by persistent inflammation where pro-inflammatory cytokines, such as TNFa, IL-1 and IL-6 play a central role. TNFa is one of the earliest cytokines implicated as its over-expression promotes fibroblast proliferation and collagen deposition.15 Administration of neutralizing antibodies to TNFa or soluble TNFa receptors prevent the development of silica or bleomycin-induced

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pulmonary fibrosis in mice.15,16 Furthermore, mice that over-express TNFa develop IPF-like fibrosis, while TNFa deficient mice resist bleomycin-induced fibrosis.17,18 TNFa also promotes matrix-degrading gelatinases and fibroblast migration which result in matrix-remodeling.19 Increased amounts of TNFa can be found in BALF of patients with IPF or asbestosis.20 Furthermore, polymorphisms at position
308 and
238 in the promoter region of the TNFa gene confer increased risk of developing pulmonary fibrosis.21–23 These genetic variants result in increased production of TNFa protein.24 The IL-1 family that includes IL-1a, IL-1b, and IL-1 receptor antagonist (RA), like TNFa, has pro-inflammatory and fibrogenic properties that contribute to the initial fibrotic process. Both IL-1a and IL-1b induce fibroblasts to produce additional cytokines such as IL-6, and collagens.25 Recently, it has been reported that transient expression of IL-1b can lead to progressive fibrosis, even after IL-1b levels have declined.26 IL-1Ra, a naturally occurring antagonist of the IL-1 receptor, can attenuate IL-1 signaling and help resolve inflammation after injury. Administration of IL-1Ra decreases lung fibrosis in mice exposed to bleomycin and silica.27 Significantly increased levels of IL-1Ra can be found in the BALF of patients with IPF and sarcoidosis.28,29 Two genetic variations of the IL-1Ra gene (IL-1RN) at position þ2018 and intron 2, which express variable numbers of tandem repeat [VNTR], have been associated with increased production of IL-1Ra and accelerated fibrosis.21,30 IL-6 has been shown to help mediate interstitial lung diseases either alone or in concert with TNFa.31 Although the contribution of IL-6 to fibrosis is not fully understood, it may stimulate fibroblast proliferation and ECM deposition.32 In animal models, overexpression of IL-6 showed a marked inflammatory response, but only weak signs of fibrosis.33,34 However, IL-6, together with TNFa, participates in fibrosis induced by bleomycin by stimulating expression of the pro-fibrotic chemokine macrophage inflammatory protein-1 alpha (MIP-1a).35 Furthermore, increased levels of IL-6 are found in BALF from patients with sarcoidosis.36 A polymorphism at position
174 in the promoter region of the IL-6 gene leads to reduced transcription of the gene and its presence is associated with IPF progression.22,37

24.2.2 Th CYTOKINES The imbalance between T helper 1 (Th1) and T helper 2 (Th2) cytokine responses is also important in the pathogenesis of fibrosis.7,8,38–40 Th1 and Th2 cytokines have the ability to influence either resolution or progression to end-stage fibrosis. While Th1 cytokines [interfeon-g (IFN-g), IL-2, IL-12, IL-18, TNFb] appear to be involved in the restoration of normal tissue structure by inhibiting fibrosis, Th2 cytokine response (IL-4, IL-5, IL-10, and IL-13) stimulate fibroblast activation, proliferation, and ultimately the deposition of ECM protein.38,41,42 In particular, IL-4 and IL-13 have been implicated in fibroblast proliferation and increased production of ECM, including type-I and type-III procollagens and fibronectin.43–45 IL-4 mRNA levels are increased in bleomycin-induced pulmonary fibrosis in mice while IL-13 expressing transgenic mice demonstrates airway epithelial cell hypertrophy and subepithelial airway fibrosis.42,45 IL-5 is also up-regulated at sites of active pulmonary fibrosis in mice treated with bleomycin.46 In addition, increased levels of IL-4, 5 and 13 are found in BAL fluid from patients with IPF.47 With regards to Th1 response, Th1 cytokines have a profound antifibrotic effect mediated primarily by IFN-g. The administration of IFN-g suppresses the proliferation of fibroblasts, production of ECM proteins, such as collagen and fibronectin, and downregulates TGF-b production.44,48,49 Clinical studies indicate that IFN-g is one of the more encouraging drugs for fibrosis treatment and patients with higher serum IFN-g levels respond better to corticosteroids.50 Treatment of IPF patients with IFN-g for

354

Cytokine Gene Polymorphisms in Multifactorial Conditions

a one-year period can provide substantial improvement in lung function.51 Furthermore, a variable length CA repeat polymorphism in the first intron of the IFN-g gene has been associated with pulmonary fibrosis.52,53 The other Th1 cytokines, IL-12 and IL-18, act synergistically to stimulate IFN-g induction in T cells.54

24.2.3 METALLOPROTEINASES Degradation of the ECM is mediated primarily by MMPs which are grouped based on their structure and activity into different subfamilies such as collagenases, gelatinases, and stromelysins.3,8 The TIMPs control ECM turnover with their MMP inhibitory actions. Disruption of the regulated balance between MMPs and TIMPs during normal tissue metabolism plays a crucial role in the formation of the ECM and remodeling.14,55–57 Increased expression of MMP-1, -2, -8 and -9 are found in experimental models of pulmonary fibrosis58,59 and in patients with IPF and sarcoidosis.60

24.2.4 FIBROGENIC MEDIATORS TGF-b is the most widely-studied cytokine in the context of fibrosis due to its pleiotropic activity in inflammatory/immune and structural cells, wound healing, and tissue remodeling.61,62 Both laboratory animal and human studies support a role for TGF-b in fibrosis. For example, TGF-b gene expression and protein production are increased in bleomycin, silica, asbestos, and radiation-induced pulmonary fibrosis in experimental animals.63–66 Increased TGFb1 production has also been demonstrated in patients with IPF and asbestosis.67,68 Among the three TGFb isoforms identified, TGFb1, -2 and -3, TGFb1 is the most potent promoter of ECM production, being involved in wound healing and tissue remodeling. Also, TGFb1 is a potent chemotactic and activating factor for monocytes and macrophages. Once activated, these cells, in turn, release additional cytokines, such as IL-1b, PDGF, fibroblast growth factor (FGF), TNFa and TGFb1.62 Other potentially fibrogenic molecules, such as TNFa and granulocyte-macrophage colony-stimulating factor (GM-CSF), may mediate their fibrogenic effect through up-regulation of TGF-b expression.69,70 Furthermore, gene polymorphisms influencing TGFb1 production at positions þ915, þ29, and
509 are associated with pulmonary fibrosis.71,72 Other profibrotic factors, such as PDGF, macrophage chemotactic protein (MCP-1), insulin-like growth factor (IGF-1), endothelin-1 (ET-1), MIP-1a and IL-8 also have been implicated in different stages of human and experimental pulmonary fibrosis. Table 24.1 provided a list of these mediators and their roles in fibrosis. Functional polymorphisms in genes which control these mediators have been associated with a variety of lung diseases. However, contributions of these genetic variations in pulmonary fibrosis are yet to be identified.

24.3 CYTOKINE GENE POLYMORPHISMS AND INTERSTITIAL LUNG DISEASES The genes that control expression of mediators of interstitial lung diseases are highly polymorphic and the role of these polymorphisms in other common diseases is receiving considerable attention. In this respect, epidemiological studies have identified associations between specific cytokine polymorphisms and common complex human diseases such as cardiovascular diseases, cancer, neurodegenerative diseases, periodontal disease and immunemediated diseases including allergic asthma and autoimmunity.73–78 Most genetic polymorphisms in genes for common diseases are not directly responsible for disease causation, rather they act as disease modifiers by influencing the severity or response to specific treatment regimens. This is particularly true for polymorphisms in cytokine genes. As has

355

Pulmonary Fibrosis

TABLE 24.1 Examples of Cytokines, Chemokines and Growth Factors That Play a Role in the Pathogenesis of Pulmonary Fibrosis Cytokines TNFa IL-1a and b IL-6 TGF-b IL-4 IL-10 IL-12 IL-13 IFN-g IL-8 MCP-1 and MIP-1 RANTES PDGF IGF-1 MMPs ET-1, CTGF

Their Role in the Pathogenesis of Pulmonary Fibrosis

Reference

Chronic inflammation, mitogenic and chemotactic for fibroblasts Chronic inflammation, fibroblast proliferation Regulates inflammatory response, stimulates fibroblast proliferation and ECM deposition Fibroblast proliferation, ECM production Fibroblast proliferation, collagen production, suppression of Th1 cytokines Suppresses pro-inflammatory cytokines and chemokines Skewing cytokine production toward Th1 Fibroblast activation, ECM production Inhibits fibroblasts proliferation and collagen synthesis Chemoattractant for neutrophils Mononuclear cell recruitment Eosinophil and lymphocyte chemoattractant Fibroblast proliferation, ECM synthesis Fibroblast proliferation ECM destruction Cell proliferation and matrix production

15,17 25 31–33 68,88 42,89 90,91 92 45 48,49 93 94,95 96 97,98 99 13,14 100,101

been suggested in the course of epidemiological studies with other chronic inflammatory diseases, genetic factors may also determine susceptibility or influence the clinical expression of pulmonary fibrosis. Table 24.2 provides a summary indicating where genetic variations have been implicated in the development or course of pulmonary fibrosis. The association between the TGFb1 þ915 (codon 25) single nucleotide polymorphism (SNP) and pre-transplant lung fibrosis was investigated in transplant patients.71 Stimulated lymphocytes containing the homozygous genotype (Arg/Arg) from control individuals displayed a higher production of the protein. The frequency of the minor variant was increased in patients displaying fibrosis, when compared to normal controls or patients with pre-transplant non-fibrotic pathology. The authors also found that this variation can predict the development of post-transplant lung fibrosis. Patients that developed allograftmediated fibrosis expressed the homozygous Arg/Arg, reflecting the high TGFb1 producer genotype. The presence of the Pro allele in codon 10 of the TGF-b1 gene has been associated with rapid deterioration in gas exchange in patients with IPF.72 Silicosis, an interstitial lung disease resulting from inhalation of crystalline silica, is characterized by chronic inflammation leading to severe pulmonary fibrotic changes. Laboratory animal and clinical studies have indicated that TNFa and IL-1 are important in regulating the development of silicotic lesions. In this respect, an association was found between disease severity and the functional polymorphism at position
238 of the TNFa gene (OR ¼ 4, CI; 2.4–6.8). Irrespective of disease severity, the other functional variants TNFa
308 and IL-1RA þ2018 conferred an increased risk for the presence of disease (OR ¼ 2.2, 95% CI; 1.4–3.6 and OR ¼ 2.1, 95% CI;1.3–3.5, respectively).79,80 In studies of South African miners, TNFa polymorphisms in positions
238,
308,
376 of the promoter region were associated with severe silicosis, providing confirmation to these associations ( p ¼ 0.022, 0.034, and 0.016, respectively).81 Coal worker’s pneumoconiosis (CWP) is characterized by chronic inflammation that usually leads to fibrosis. In a study investigating associations between TNFa gene

Sarcoidosis Silicosis

Lung allograft fibrosis

Idiopathic pulmonary fibrosis

TNFa
308 TNFa
308, TNFa
238 (severe) IL-1RN þ2018

TGFb1 codon 10 TNFa þ691g IL-1RN þ2018 TNFa
308 Co-carriage of the IL-6 intron 4 and the TNF-RII 1690 IFNg/CA repeat TGFb1 codon 25

Cystic fibrosis

Fibrosing alveolitis

TNFa
308

Gene/Polymorphism

Coal workers’ pneumoconiosis

Disease

Caucasian Caucasian Caucasian Caucasian Caucasian

325/164

Caucasian Caucasian Caucasian Caucasian Caucasian Caucasian Caucasian

Ethnicity

78/56 253 171/107 180/85 88/88 61/103 74/100 (IL-6) 74/192 (TNF-RII) 82/164 45/107 101/216 325/164

Sample Size (Case/Control)

TABLE 24.2 Examples of Associations between Cytokine Polymorphisms and Pulmonary Fibrotic Diseases

12 CA repeats þ915 Arg allele A-308 allele A-308 allele A-238 allele IL-1RN*2

A-308 allele A-308 allele TT genotype þ691 ins IL-1RN*2 A-308 allele 4 G and 1690 C alleles

Associated Variant

P 5 0.005 P 5 0.03 P 5 0.0078 P 5 0.01 P ¼ 0.04 P 5 0.01

P ¼ 0.04 P ¼ 0.003 P 5 0.02 P ¼ 0.008 P ¼ 0.03 P ¼ 0.022 P 5 0.00093

P Value

80

52 71 104 79

22

82 87 102 103 21

Reference

356 Cytokine Gene Polymorphisms in Multifactorial Conditions

Pulmonary Fibrosis

357

polymorphisms and development of CWP, the frequency of the TNFa
308 variant was significantly increased in miners with CWP (50%), as compared with miners without lung disease (25%) or non-miners (29%) (OR ¼ 3.0, 95% CI; 1.0–9.0).82 The TNFa
308 and lymphotoxin-a (LTA) NcoI polymorphisms were investigated in 253 coal miners exposed to low and high levels of coal dust and cigarette smoke. TNFa can alter the oxidant/ antioxidant balance in the lung by generating reactive oxygen species and modulating glutathione levels.83 The LTA gene is located in tandem with the TNFa gene on chromosome 6p21.31 and a functional polymorphism in LTA gene (NcoI ) was found to be associated with pulmonary fibrosis.84 Reactive oxygen species derived from coal dust and activated inflammatory cells are known to be important in CWP pathogenesis.85 In a study investigating the relationship between coal mine dust exposure and antioxidant enzyme activities, a strong association was found between catalase activity, cumulative dust exposure, and CWP severity.86 While the LTA NcoI polymorphism was associated with CWP prevalence in miners with low blood catalase activity ( p ¼ 0.05), the TNFa
308 SNP showed an interaction with erythrocyte GSH-Px activity in individuals with high occupational exposure ( p ¼ 0.003).87 This study showed that the TNFa
308 and the LTA NcoI polymorphisms, along with occupational exposure and intermediate response phenotypes, may play a role in the pathogenesis of CWP. Fibrosing alveolitis is characterized by persistent alveolar inflammation and interstitial pulmonary fibrosis. Occupations where workers are exposed to metals, wood dusts, or other chemicals can sometimes cause fibrosing alveolitis. The frequency of TNFa
308 and IL-1RN þ2018 variants were investigated in patients with fibrosing alveolitis and controls from the UK and Italy.21 The frequency of IL-1RN þ2018 was increased in subjects with the homozygous minor variant (OR ¼ 10.2, 95% CI; 1.3–81.4). Carriage of TNFa
308 variant was also associated with increased risk of fibrosing alveolitis (OR ¼ 2.5, 95% CI; 1.1–5.5). These data suggest that IL-1RN þ2018 and TNFa
308 minor variants might confer increased risk of developing fibrosing alveolitis.

24.4 GENE-GENE AND GENE-ENVIRONMENT INTERACTIONS As fibrotic lung diseases are complex, it is not surprising that several gene–gene interactions have been observed. While no significant associations were found in an IPF population with respect to LTA, TNF-receptor 2 (TNF-R2) or IL-6 gene polymorphisms, an increased frequency of individuals possessing both the IL-6 intron 4G and the TNF-R2 1690 C alleles has been observed22. In silicosis, the presence of both the IL-1a þ4845 and TNFa
238 variants was associated with an increased likelihood of severe disease.79 The frequency of TNFa
238 was associated with severe silicosis, but the magnitude of this effect was greater in those subjects without the IL-1a þ4845 variant. A second interaction was found between IL-1RA þ2018 and TNFa
308 variants. The proportion of moderate cases increased independently with the presence of either minor variant. For severe disease, however, both IL-1RA and TNFa
308 variants were present.79 Three-way interactions were identified between the proportion of cases in each possible gene–gene combination and two different categories of exposure (less than or equal to thirty years versus greater than thirty years). These analyses showed an increased prevalence of silicosis with increasing exposure, except in the case where both IL1a þ4845 and TNFa
308 variants were present. Nadif et al. (2003) showed an interaction of the TNFa
308 genotype and high coal dust exposure and GSH-Px activity ( p ¼ 0.003). They postulated that chronic oxidative stress resulting from high dust exposure may down regulate GSH-Px, while the highproducer TNFa genotype modulates GSH-Px activity through regulation of GSH levels.87

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Cytokine Gene Polymorphisms in Multifactorial Conditions

24.5 CONCLUSIONS With the identification of the DNA sequence of the human genome and increasing data on polymorphisms, genetic epidemiology offers a powerful approach to the identification of genetic variants that influence susceptibility to many common diseases. Although the pathogenesis of pulmonary fibrosis remains incompletely understood, identification and understanding the role of genetic risk factors helps provide novel insights into the pathophysiology of the disease and identify molecular regulators of inflammatory and fibrotic processes. The use of new high-throughput genotyping technology, statistical genetic methods and robust association study designs which considers population stratification, sample size, intermediate phenotypes, linkage disequilibrium, and gene–gene/gene– environment interactions, will help lead to a better understanding of fibrotic mechanisms in the lung and identification of high-risk groups. This information may also aid in the development of novel therapeutic targets at a molecular level.

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84. Yamaguchi, E., Itoh, A., Hizawa, N., and Kawakami, Y., The gene polymorphism of tumor necrosis factor-beta, but not that of tumor necrosis factor-alpha, is associated with the prognosis of sarcoidosis, Chest, 119, 753, 2001. 85. Schins, R. P. and Borm, P. J., Mechanisms and mediators in coal dust induced toxicity: a review, Ann. Occup. Hyg., 43, 7, 1999. 86. Nadif, R. et al., Relations between occupational exposure to coal mine dusts, erythrocyte catalase and Cuþþ/Znþþ superoxide dismutase activities, and the severity of coal workers’ pneumoconiosis, Occup. Environ. Med., 55, 533, 1998. 87. Nadif, R. et al., Effect of TNF and LTA polymorphisms on biological markers of response to oxidative stimuli in coal miners: a model of gene-environment interaction. Tumour necrosis factor and lymphotoxin alpha, J. Med. Genet., 40, 96, 2003. 88. Khalil, N., O’Connor, R. N., Flanders, K. C., and Unruh, H., TGF-beta 1, but not TGF-beta 2 or TGF-beta 3, is differentially present in epithelial cells of advanced pulmonary fibrosis: an immunohistochemical study, Am. J. Respir. Cell. Mol. Biol., 14, 131, 1996. 89. Gillery, P. et al., Interleukin-4 stimulates collagen gene expression in human fibroblast monolayer cultures. Potential role in fibrosis, FEBS Lett., 302, 231, 1992. 90. Martinez, J. A. et al., Increased expression of the interleukin-10 gene by alveolar macrophages in interstitial lung disease, Am. J. Physiol., 273, L676, 1997. 91. Huaux, F. et al., Role of interleukin-10 in the lung response to silica in mice, Am. J. Respir. Cell. Mol. Biol., 18, 51, 1998. 92. Trinchieri, G. and Gerosa, F., Immunoregulation by interleukin-12, J. Leukoc. Biol., 59, 505, 1996. 93. Carre, P. C. et al., Increased expression of the interleukin-8 gene by alveolar macrophages in idiopathic pulmonary fibrosis. A potential mechanism for the recruitment and activation of neutrophils in lung fibrosis, J. Clin. Invest., 88, 1802, 1991. 94. Hasegawa, M., Sato, S., and Takehara, K., Augmented production of chemokines (monocyte chemotactic protein-1 (MCP-1), macrophage inflammatory protein-1alpha (MIP-1alpha) and MIP-1beta) in patients with systemic sclerosis: MCP-1 and MIP-1alpha may be involved in the development of pulmonary fibrosis, Clin. Exp. Immunol., 117, 159, 1999. 95. Smith, R. E., Chemotactic cytokines mediate leukocyte recruitment in fibrotic lung disease, Biol. Signals, 5, 223, 1996. 96. Petrek, M. et al., The source and role of RANTES in interstitial lung disease, Eur. Respir. J., 10, 1207, 1997. 97. Antoniades, H. N. et al., Platelet-derived growth factor in idiopathic pulmonary fibrosis, J. Clin. Invest., 86, 1055, 1990. 98. Yi, E. S. et al., Platelet-derived growth factor causes pulmonary cell proliferation and collagen deposition in vivo, Am. J. Pathol., 149, 539, 1996. 99. Bloor, C. A. et al., Differential mRNA expression of insulin-like growth factor-1 splice variants in patients with idiopathic pulmonary fibrosis and pulmonary sarcoidosis, Am. J. Respir. Crit. Care Med., 164, 265, 2001. 100. Pan, L. H. et al., Type II alveolar epithelial cells and interstitial fibroblasts express connective tissue growth factor in IPF, Eur. Respir. J., 17, 1220, 2001. 101. Saleh, D. et al., Elevated expression of endothelin-1 and endothelin-converting enzyme-1 in idiopathic pulmonary fibrosis: possible involvement of proinflammatory cytokines, Am. J. Respir. Cell. Mol. Biol., 16, 187, 1997. 102. Arkwright, P. D. et al., TGF-beta(1) genotype and accelerated decline in lung function of patients with cystic fibrosis, Thorax, 55, 459, 2000. 103. Yarden, J. et al., Association of tumour necrosis factor alpha variants with the CF pulmonary phenotype, Thorax, 60, 320, 2005. 104. Seitzer, U. et al., Tumour necrosis factor alpha promoter gene polymorphism in sarcoidosis, Cytokine, 9, 787, 1997.

25

Atherosclerosis Giuseppina Candore, Sonya Vasto, Giuseppina Colonna-Romano, Domenico Lio, Marco Caruso, Irene Maeve Rea, and Calogero Caruso

CONTENTS 25.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.2 Chemokines: MCP-1, RANTES and EOTAXIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.3 Interleukin-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.4 Interleukin-6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.5 Interleukin-10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.6 Tumor Necrosis Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.7 Transforming Growth Factor-b1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.8 Interferon-g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.9 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

363 364 368 368 370 371 372 372 373 374 374

25.1 INTRODUCTION Atherosclerosis and its complications contribute to a large percentage of morbidity and mortality in older people. Cardiovascular disease is the leading worldwide cause of morbidity and death.1 However, our understanding of the pathogenetic mechanisms underlying atherosclerosis and its complications remain incomplete, since more than half of patients with atherosclerosis do not show classical risk factors, such as hypercholesterolemia, hypertension, smoking history, diabetes, obesity, or sedentary life style.1,2 On the other hand, atherosclerosis, formerly considered a lipid storage disease, is now known to involve an ongoing inflammatory response. Recent advances in basic science have established a fundamental role for innate immunity and inflammation in mediating all stages of this disease from initiation through progression and, ultimately, to the thrombotic complications. Clinical studies have shown that the emerging biology of inflammation in atherosclerosis applies directly to human patients. Elevation of markers of inflammation predicts outcomes of patients with acute coronary syndromes, independently of myocardial damage. In addition, low-grade chronic inflammation, as indicated by levels of the inflammatory marker reactive C protein (CRP) and pro-inflammatory cytokines, prospectively defines risk of atherosclerotic complications, thus adding to prognostic information provided by traditional risk factors. In fact, levels of CRP or IL-6 have been suggested to be significant predictive risk factors for future development of cardiovascular events.2–4 Furthermore, increased levels of serum IL-1b have been associated with high risk of congestive heart failure and angina pectoris5 and altered levels of IL-1b have been implicated in chronic inflammation related to high blood pressure.6 363

364

Cytokine Gene Polymorphisms in Multifactorial Conditions

In atherosclerosis, the initiating event is the accumulation of lipids in the vessel wall, which subsequently become modified by oxidation, glycation, and aggregation. Their subsequent association with proteoglycans or incorporation into immune complexes initiates and triggers an inflammatory process. Oxidized low-density lipoproteins (ox-LDL) are taken up by macrophages through scavenger receptors; the internalization leads to the formation of lipid peroxides and facilitates the accumulation of cholesterol esters. Further, other monocytes, attracted from the blood, differentiate into macrophages, take up modified ox-LDL and form lipid-laden foam cells, which initiate atherosclerotic plaque development. Later on, inflammatory mediators increase, other immune cells are attracted, and smooth muscle cells become activated and involved. More advanced stages of plaque development are characterized by increased deposition of extracellular lipid cores, fibrous material, and often necrosis. Subsequently, these macrophages are progressively activated, leading to the production of a wide range of cytokines and growth factors. Myocardial infarction (MI) may occur as a result of erosion or uneven thinning and rupture of the fibrous cap, often at the shoulders of the lesion where macrophages enter, accumulate and are activated, and where apoptosis may occur.7,8 Inflammation is a key component of atherosclerosis and genes coding for inflammatory or anti-inflammatory cytokines are, therefore, good candidates for the risk of atherosclerosis. Because genetic traits contribute significantly to the risk of coronary heart disease (CHD),9 a number of studies have now addressed the hypothesis that allelic variations in genes of innate immunity may increase the risk of disease.10,11 Differences in the genetic regulation of inflammatory processes might partially explain why some people, but not others, develop the disease and why some develop a greater inflammatory response than others. However, as discussed in the present review, there is considerable discrepancy in the various results obtained in the different populations studied. So, to gain an insight into the role of immunogenetics of inflammation in CHD and MI, we have included a Medline search of the literature published between 1996 and January 2005. We reviewed the existing literature linking CHD and MI using ‘‘myocardial infarction’’ (or coronary heart disease), polymorphism and the involved ‘‘cytokine’’ as key words (Table 25.1 and Table 25.2).

25.2 CHEMOKINES: MCP-1, RANTES AND EOTAXIN Chemokines are a group of inducible cytokines which promote cellular migration and activation.12 The level of chemokine expression, in response to the immune injury, regulates the degree of tissue leukocyte infiltration and so differences in chemokine expression could account, in part, for observed differences in the severity of organ inflammation. Chemokines have been associated with the inflammatory zone in human atherosclerotic plaque.13 A body of evidence suggests that interactions between cells, such as leukocytes and endothelial cells amplify chemokine release and contribute to the sustained chemokine generation noted in inflammatory conditions including atherosclerosis.14–16 Chemokines are usually classified into four groups based on the relative position of cysteine residues 17 (Table 25.1). The CC chemokines have been detected in human and animal experimentally-induced models of atherosclerotic plaques.13,18 In addition RANTES has been detected in atherosclerotic plaque and in atherosclerotic lesions associated with heart transplant chronic rejection and vasculopathy.19 So, atherosclerosis is associated with an increased expression of a number of chemokines, including MCP-1, MIP-1alpha/beta and RANTES and IL-8, both of which are presumed to be produced secondarily to activation of T cells.14,18,19 MCP-1, an ubiquitous chemokine found in many aspects of atherogenesis, has been found in intimal atherosclerotic lesions of cholesterol-fed rabbits,18 in arteries of primates

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Atherosclerosis

TABLE 25.1 Role of Selected Cytokines and Chemokines in Atherogenesis Category

Member

Source

Relevance in Atherosclerosis

CX3C-chemokine

FRACTALKINE, MIG (CXCL9),

Endothelial cells

Agonist for the chemotaxis and adhesion of monocytes and lymphocytes

CXC-chemokine

IP-10 (CXCL10), IL-8, SDF-1-BCA-1

Endothelial cells

Up-regulation of angiostatic factors and neutrophils and lymphocytes recruitment. IL-8 promotes endothelial cell prolifeation

C-chemokine

LYMPHOTACTIN

T-cell, B-cell, NK-cell

Chemotactic for lymphocytes but not for monocytes

Proinflammatory cytokines

IL-1a/b, IL-6, TNF-g

Mast cells, macrophages, T-cells, endothelium

IFN-g

T-cells, NK cells

Endothelial cells: activation, cytokine synthesis and permeability; Acute phase response (CRP) Macrophage activation, MHC II induction

IL-10

T- cells, monocyte, macrophages Platelets, endothelial, haematopoietic, and connective tissue cells

Anti-inflammatory cytokines

TGF-b

Inhibits cytokine synthesis (IL-2, IFN-g) Deposition of extracellular matrix protein and anti-inflammatory cytokine

For references see text.

fed a hypercholesterolemic diet,20 and in human atheromatous plaque.13 These studies indicate that the expression of MCP-1 in vascular smooth muscle cells is triggered in response to dietary hypercholesterolemia. Boring et al.14 dissecting out the MCP-1 response and using mice deficient in MCP-1 and MCP-1’s receptor, revealed an important role of MCP-1 in early recruitment of monocytes into the vessel wall after lipid deposition and lesion formation. This provided strong evidence for a direct effect of MCP-1 in macrophage recruitment in murine models of atherosclerosis. Subsequently, Aiello et al.21 noted that MCP-1 expression by macrophages progressed atherosclerosis by increasing ox-LDL accumulation while Desai et al.22 showed that the risk factor for atherosclerosis, homocysteine, induced MCP-1 nuclear translocation, transcription, and secretion in endothelial cells. Similarly, oxidized or modified lipoproteins induce chemokine production in vascular endothelium, in vitro.23 Interestingly, in view of the male/female difference in the incidence of CHD, Seli et al.24 showed that estrogens down regulate MCP-1 expression in smooth muscle cells endorsing its antiatherogenic effect. Only a few studies have evaluated any association between CHD and MCP-1 polymorphisms. Szalai et al.25 reported association between MCP-1
2518G/G single nucleotide polymorphism (SNP) and CHD in 318 patients (35–73 range of age) with signs of severe coronary atherosclerosis tested by coronary angiography (470% of stenosis in one or more coronary arteries and/or angina pectoris and electrocardiographic abnormalities). In the only other study, Simeoni et al.26 found no association between MCP-1 SNP
2518G/G and CHD in 2694 patients and 530 controls, though the disease progression in the coronary arteries may have been less severe. To our knowledge, no study on MCP-1 and MI has been performed to date.

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Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 25.2 Studies on Cytokine Gene Polymorphisms in Patients and Controls Gene Polymorphisms MCP-1 –2518A!G MCP-1 –2518A!G RANTES –403A!G EOTAXIN 23T!A IL-1-511 C!T IL-1-889 C!T IL-1 þ3593 C!T IL-1ra VNTR 2 IL-1ra VNTR 2 IL-1ra VNTR 2 IL-1-511 C!T IL-1ra VNTR 2 IL-1ra VNTR 2 IL-1b –511C!T IL-1b –511C!T IL-6
174G!C IL-6
596G!A IL-6
572G!C IL-6
174G!C IL-6
174G!C IL-6
174G!C IL-6
174G!C IL-6
573G!C IL-6
598A!G IL-6
174G!C IL-6
174G!C IL-6
174G!C IL-6
572G!C IL-6
174G!C IL-6
174G!C IL-6
572G!C IL-6
174G!C IL-10
819T!C IL-10
1082A!G IL-10
592A!C IL-10 G78A IL-10 19C!T IL-10 953T!C IL-10 117C!T IL-10
819T!C IL-10
592A!C IL-10
1082A!G IL-10
819T!C IL-10
1082A!G IL-10
819T!C IL-10
592A!C TNF a
308G!A TNF a –857C!A TNF a –851C!T TNF a -238G!A TNF (Asp26!Thr) TNF a
308G!A TNF a
308G!A

Population

No. of Patients

No. of Controls

Results

References

318 2694 2694 523 906

320 530 530 2092 827

–2518GG" No change –403G/G" 23T No change

25 26 26 33 38

Italian Italian Japanese

115 158 188

80 153 104

Italian

335

205

Italian France/Ireland

139 640

198 719

English German American Swedish

2751 2559 901 1213

Denmark Italian Germany Sweden

Hungarian Swiss Swiss American English

IL-1ra " No change No change
511T " IL-1ra " No change

33 41 40 42

No change
174CC " –596A "

43 54

729 500 1561

–174CC" No change
174CC" No change

50 56 51 55

333 139 1322 280

– 198 1023 –


174CC "
174CC " No change No change

52 43 57 58

English

–

–

No change

59

Italian German

139 998

– 340


174CC # No change

53 63

English

1107

1082

No change

62

Japanese

2818

2242

No change

64

Germany

300

–


1082G "

65

Italian

232

263


1082G "
819C "

60

France

641

710

No change

69

England England Chinese

199 674 641

81 1059

No change No change
308A"

68 38 70 (continued )

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Atherosclerosis

TABLE 25.2 Continued Gene Polymorphisms TNF a
308G!A TNF-a 308G!A TNF-b 252A! G TNF-a 308G!A TNF-b 252A! G TNF-a 308G!A TNF-a
863C!A TNF-b 252A! G TNF (Thr! Asp26) TNF a 308G!A TGF-b
988C!A TGF-b 509C!T TGF-b
800G!A TGF-b þ72G TGF 263C!T TGF-b
800G!A TGF 74G!C TGF 29T!C TGF-b 509C!T TGF-b2 TGF 29T!C

Population

No. of Patients

No. of Controls

Results

References

Spain Brazil

341 148

207 148


308A" No change

71 73

Finland

700

–

No change

74

Germany

998

340

No change

63

Japan France IrelandþFrance

299 563

146 629

Thr!Asp26" No clear results No change

75 72 82

English

655

244

No change

83

Australian England Japanese

371 101 315

– 100 591

No change No change No change

79 80 81

RANTES, another CC chemokine, seems to be involved in both acute and chronic inflammation.27 It is a potent chemo-attractant for monocytes and T lymphocytes, is inducibly expressed within inflamed organs, binds to endothelial cells and promotes haptotaxis. These findings suggest that RANTES might effect the migration of antigenspecific immune cells into an inflammatory site. In keeping with this suggestion, Matsumoto et al.28 demonstrated increased levels of MCP-1 and RANTES in the patients with acute MI compared to those with stable angina pectoris. Parissis et al.29 also detected significant elevations of major C–C chemokines, MCP-1, MIP-1a, and secreted RANTES, during the course of MI, with the highest levels in patients with MI complicated by heart failure manifestations and severe left ventricular dysfunction. In a single study, Simeoni et al.26 revealed an association between RANTES –403A SNP and CHD patients with respect to their angiographic abnormalities and acute coronary syndromes. The chemokine Eotaxin (CCL11), which promotes migration and activation of eosinophils in a broad range of allergic disorders,30 appears involved in human arteriosclerosis. Haley et al.31 showed increases in eotaxin mRNA (420 fold), overexpression of eotaxin protein and its receptor CCR3 in human atheroma and higher plasma eotaxin in patients with coronary atherosclerosis undergoing elective percutaneous coronary transluminal angioplasty.32 With respect to polymorphisms of the eotaxin gene, Zee et al.33 in a single study found association between T!A substitution at amino acid 23 in the eotaxin gene with an increased risk for incidental MI. Although chemokines seem highly involved in all stages of arteriosclerosis and seem likely to be important candidate genes for cardiovascular risk, there is not yet a solid body of

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Cytokine Gene Polymorphisms in Multifactorial Conditions

evidence to assess their importance in CHD since most reports to date are single studies which require replication in other population groups and with larger numbers.

25.3 INTERLEUKIN-1 The ‘‘prototypic’’ inflammatory cytokine interleukin IL-1 is a primary mediator of systemic inflammatory responses, responsible for clinical signs of illness including loss of appetite, slow-wave sleep and neuro-endocrine changes. It is a family of at least three closely related proteins which are the products of separate genes. The IL-1 gene cluster contains three genes for IL-1a, IL-1b and IL-1RA which is a modulating anti-inflammatory cytokine. Several genetic polymorphisms have been described in the genes of the IL-1 cluster and some have been associated with the severity of chronic inflammatory diseases.34–36 IL-1 promotes the interaction of endothelial cells with circulating leukocytes, induces the activation and proliferation of monocytes/macrophages, and stimulates smooth muscle cell mitogenesis and the synthesis of plasminogen activator inhibitor 1. Through these mechanisms, it is believed to play a key part in atherogenesis and thrombosis.10,37 Francis et al.38 studied IL-1 and IL-1RA polymorphisms in 232 patients with angiographically unobstructed coronary arteries and 674 patients with single vessel disease or multi vessel disease. In this English study, the IL-1 allele frequencies (
889T,
511T, and þ3593T) were not significantly associated with the presence or extent of the disease, whereas homozygotes for IL-1RN*2 was associated with single vessel disease in data pooled from London and Sheffield (OR ¼ 2.8). Contra-intuitively, in this study, gene frequencies from patients with multivessels disease were similar to those of healthy and patient controls. The IL-1RA VNTR 2 polymorphism was studied by Manzoli et al.39 but they did not show any clear-cut association between allele 2 of the Il-1RA gene polymorphism and CHD. Momiyama et al.40 instead, found that IL-1 gene polymorphisms IL-1 –511T and IL-1RA VNTR 2 played a role in the development of CHD, especially in MI, where patients had co-existing Chlamydia pneumonia infection. This study enrolled 292 patients and CHD was defined as at least one coronary artery having 450% luminal artery stenosis. Conversely, Iacoviello et al.41 did not find any significant association between IL-1RN*2 and infarction in 148 infarct survivors (men 4 45 years of age, women 450 years of age) compared to 153 controls. Similarly Vohnout et al.42 did not find any difference in the gene frequencies of the two IL-1 polymorphisms IL-1RN*2 and IL-1b
511C/T in CHD. These polymorphisms were studied in 335 patients with angiographically documented CHD (stenosis 4 50% in one major coronary artery) and compared with 205 unrelated individuals free of CHD signs at angiogram. Licastro et al. studied the bi-allele SNP (C 4 T) in the promoter region (
511) of IL-1b in 139 males with MI but found that the genotype frequency of C 4 T SNP was comparable between controls and subjects with MI.43 All in all, these results would suggest that despite evidence for IL-1 being involved in atherogenesis and thrombosis,10,37 there is no clear support that any of the IL-1 polymorphisms studied track with atherosclerosis or any of its disease manifestations.

25.4 INTERLEUKIN-6 IL-6 is a pleiotropic cytokine capable of regulating proliferation, differentiation, and activity in a variety of cell types. It plays a major role in bone remodelling, neuroendocrine homeostasis, hemopoiesis and immune system regulation. In particular, IL-6 plays a pivotal role in acute phase responses and in the balancing of the pro-inflammatory/antiinflammatory pathways. IL-6 stimulates endothelial activation, vascular smooth muscle cell

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369

(SMC) proliferation, and leukocyte recruitment, all of which lead to plaque growth or instability. IL-6 is involved in impaired lipid metabolism and in the production of triglycerides that is an important cardiovascular disease risk factor. IL-6 decreases lipoprotein lipase activity and monomeric lipoprotein lipase levels in plasma contributing to increases in macrophage uptake of lipids. In fatty streaks and in the atheromatous cap and shoulder regions, macrophage foam cells and SMCs express IL-6 suggesting a role for this cytokine in the progression of atherosclerosis. During vascular injury SMCs are exposed to platelets or their products, and cytokine production by SMCs further contributes to vascular damage. Furthermore, circulating IL-6 stimulates the hypothalamic-pituitaryadrenal axis, activation of which is associated with central obesity, hypertension, and insulin resistance.37,44–46 Thus a role for IL-6 has been proposed in the pathogenesis of CHD through a combination of autocrine, paracrine, and endocrine mechanisms. As inflammatory markers are associated with the development of CHD, with disease severity and with the occurrence of coronary events, Biasucci et al. suggested that the elevated levels of IL-6 are predictive of future cardiovascular events and indicate poor prognosis in acute coronary syndrome.47–49 Humphries et al.50 in one of the earliest studies involving 2751 middle-aged healthy men, noted a weak but significant association of the IL-6
174C SNP with the risk of CHD. This effect was seen most strongly in smoking men who had a risk of 2.7-fold compared to IL-6
174GG non-smokers. In 2002 Jenny et al.51 associated IL-6
174C SNP with risk of atherosclerosis when comparing controls and a group categorized as subclinical CHD, though conversely no association was found when case and control groups were compared suggesting that the effect of the genotype is modified by environmental factors. In this study the level of IL-6 differentiated individuals with subclinical CHD from those without disease. Bruunsgaard et al.52 also studied the IL-6
174C/G genotype in 333 subjects (153 men and 171 women, including an 80-year-old age group), 18% of whom had a perceived history of cardiovascular disease. In this study the authors provided evidence that the IL-6
174GG genotype, associated with low levels of IL-6 in their study, was protective with respect to all cause mortality in current non-smokers in the 80-year-old group. In apparent keeping with this finding, Licastro et al.43 noted that the C allele was more frequent among 139 patients with MI compared to 198 controls. The odds ratio of developing MI was OR ¼ 2.654 for C allele subjects and therefore the
174C SNP was moderately associated with MI and increased risk of atherosclerosis. On the other hand, Antonicelli et al.53 studying 139 elderly males (age range 65 to 98 years) with diagnosis of acute coronary syndrome (ACS) (i.e. MI and unstable angina) for
174CG SNPs, showed that carriers of the IL-6
174C þ allele had an increased chance of survival after one year of follow up, compared to C-patients affected by ACS.53 A couple of groups have studied more than one IL-6 SNP with respect to cardiovascular risk. Georges et al. found association between SNPs IL-6 -174C and IL-6 -596A, and MI in 640 patients and 719 age-matched controls.54 In 2003, Bennet et al.55 also studied three IL-6 SNPs
174G/C,
573G/C, and 598G/A in 1213 patients (852 men and 361 women) and 1561 controls. The study found a gender-related difference in IL-6 serum concentration with elevated levels of IL-6 associated with increased risk for non-fatal MI in men but not women. However, these authors suggested that IL-6 polymorphisms were unlikely to contribute significantly to the genetic background of MI. Some studies have shown no association between IL-6 SNPs and cardiovascular disease. Nauck et al.56 did not find any association between the
174C SNP and the risk of CHD or MI in a study of 2559 German patients with CHD compared to 729 controls. CHD was defined as the presence of at least one stenosis of 20% in one of the three major coronary

370

Cytokine Gene Polymorphisms in Multifactorial Conditions

arteries. In a later study Lieb et al.57 also failed to show any association either between the IL-6 SNP
174G/C allele and serum IL-6 levels or any relationship in patients with MI. Bennermo et al.58 also reported no association between IL-6 levels and SNP
174C. This study further reported no association between the
174C SNP and cardiovascular death or a new MI. One other IL-6 SNP, –572C showed a borderline increase in risk in the Bennermo study though Kelberman et al.59 also investigating the –572C/G SNP did not confirm any association between the –572C SNP and IL-6 levels nor any contribution to the risk of cardiovascular disease. Although IL-6 appears to have predictive value in future cardiovascular events, the role of the most common IL-6 SNP
174C with respect to cardiovascular diseases is far from clear. A number of studies report markedly divergent results for the association of the
174C locus with cardiovascular risk or with other important parameters such as arterial responsiveness or CRP serum levels.

25.5 INTERLEUKIN-10 IL-10, a cytokine with anti-inflammatory and B cell stimulating activity, is produced by activated T cells, B cells, monocytes/macrophages, and dendritic cells. The principal function of IL-10 appears to be to limit and ultimately terminate the inflammatory signal. Several lines of evidence indicate an involvement of IL-10 in the development of atherosclerosis. IL-10 can limit the progression of experimental atherosclerosis and has several antiatherogenic effects including inhibition of adhesion of LDL-activated monocytes to endothelium and down-regulation of fibrinogen biosynthesis. IL-10 is detectable in human atherosclerotic plaques and has been claimed to play a regulatory role in the progression of atherosclerotic human CHD. In addition, serum levels of IL-10 have been held to be important prognostic determinants in patients with acute coronary syndromes.60,61 Donger et al.62 studied several SNPs: 78G!A at exon 1, 19C!T at intron 3, 953T!C in intron 3 and 117C!T in 1107 subjects (25–69 age range) with 1082 controls of comparable age and sex. However, the results did not show any protection against MI. Similarly, Koch et al.63 did not find any measurable influence on the occurrence of CHD or MI in angiographically evaluated patients with respect to IL-10 gene SNPs:
1082G,
819C, and
592C. Yamada et al.64 analyzed 2819 patients (2003 men and 816 women) with a diagnosis of MI (all underwent coronary angiography and left ventriculography) for the IL-10
819C and IL-10
592C SNPs but no association was found with MI. On the other hand, Girndt et al.65 found association between risk of cardiovascular disease and IL-10 –1082 GG genotytpe in 300 hemodialysis patients. The allele
1082G, associated with low levels of IL-10 production, demonstrated elevated markers of systemic inflammation such as C reactive protein and was predictive for higher cardiovascular morbidity. Lio et al.60 studied the three IL-10 SNPs
1082G,
819C,
592C in two cohorts of men diagnosed with MI by typical electrocardiographic changes, echocardiography, and coronary angiography. The first cohort comprised 142 patients (age range 55–80) and 153 controls from northern Italy (Bologna). The second younger cohort comprised 90 patients (age range 23–46) and 110 healthy controls from Sicily. A third cohort comprised two groups of oldest old men (495 years old) from Sicily (52 individuals) and Bologna (57 individuals). Significant differences in genotype distribution were found between controls and old individuals with MI, between oldest old and old patients and between controls and oldest old. Significant differences between oldest old and men with MI were also observed. The evidence for any association between the various polymorphisms of IL-10 and cardiovascular disease would seem to be largely negative though the IL-10
1082G SNP,

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associated with lower IL-10 cytokine levels, would seem to deserve further study in larger more homogenous population groups. On the other hand, cardiovascular diseases are multifactorial ones, so different single genes are expected to strongly contribute to general risk, which depends also on environmentally interaction, such as grade of inflammation and type of diet. Accordingly, inflammatory mediators are induced in all patients with chronic renal failure due to uremia and renal replacement therapy. However, while those with the IL-10 highproducer genotype may effectively limit inflammation, this is not the case in the lowproducer group.65 So, the different results obtained in the Italian patients might also depend on the differential importance of classical risk factors for atherosclerosis and MI in the Italian population since the traditional Mediterranean diet may affect the incidence and prevalence of MI.60,66,67

25.6 TUMOR NECROSIS FACTOR The TNF cluster genes which map within the major histocompatibility complex (MHC) encode three inflammation-related proteins, TNF-a, TNF-b, and LT-b. Several polymorphic areas are documented within the TNF gene cluster. Major effects on the cardiovascular system include increased expression of adhesion molecules and MHC proteins, release of endothelial cytokines and nitric oxide, enhanced vascular permeability, reduced lipoprotein lipase activity, increased hepatic fatty acid synthesis, involvement in obesity-related insulin resistance, and prothrombotic effects (through enhanced expression of plasminogen activator inhibitor 1, von Willebrand factor and through suppression of the anticoagulant protein C).10,37 Braun et al.68 investigated the functional SNP Asp26!Thr which correlates with TNF production in 199 men with CHD and 81 controls. No association was found with CHD. Negative association results were also obtained by Herrmann et al.69 who studied five TNF SNPs: (
308,
857,
851,
238) in 641 men surviving MI or with CHD (mean age 54 years) and 710 controls from four regions of France and Northern Ireland. Additionally, Francis at al.38 did not find any association between the SNP
308A and angiographically confirmed coronary artery stenosis in 674 patients and 1059 controls. In contrast, Wang et al.70 reported positive and significant associations between the TNF-a
308A variant polymorphism and levels of extra-cellular superoxide dismutase which can either cause oxidative stress or enhance lipid-related oxidation, both of which are relevant to atherosclerosis. The study enrolled 641 Caucasian subjects (age 56 years) and checked for coronary disease by angiography. Vendrell et al.71 also studied the TNF-a
308A/G SNP in 341 CHD patients with type II diabetes, 135 patients with type II diabetes without CHD and 207 healthy controls and noted that TNF-a
308A allele was higher in CHD compared to controls and independent from other risk factors. CHD patients with diabetes type II showed increased TNF-a
308A allele frequency compared with controls (40.6% vs. 23.2%). The results suggest that the TNF-a
308A variant polymorphism may contribute to CHD. On the other hand, Bernard et al. found association between TNF-a
308A SNP for unstable angina but not very clear results with respect to MI.72 A few studies have assessed polymorphisms of both TNF-a and TNF-b. Padovani et al.73 did not find any significant interactive effect between TNF-a
308A or TNF-b 252A SNPs and risk factors for coronary artery disease in 148 patients and 148 age-gender and racematched controls. Koch et al.63 studying the TNF gene SNPs TNF-a
308G/A,
863C/A, TNF-b 252G/A in 998 CHD patients compared with 340 controls found no association with CHD for any TNF variant polymorphism TNF-a
308A,
863A, TNF-b 252A.

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A similar negative finding was noted by Keso et al.74 who did not find any differences in coronary stenosis or in the frequency of old or recent MI with respect to TNF-a
308A or TNF-b 252A SNPs. Using microarray technology, Ozaki et al.75 studied 92,788 gene-based-SNP markers associated with MI. Two SNPs in TNF-b (Thr!Asp26), were significantly associated with increased risk for MI. This interesting finding, using the newly available genomic technology platforms, deserves further study.

25.7 TRANSFORMING GROWTH FACTOR-b1 TGF-b1 is expressed by a wide range of cells, including platelets, endothelial, hematopoietic, and connective tissue cells. Major functions attributed to TGF-b1 are immunosuppression, reduction of inflammation, promotion of wound healing, and regulation of cell proliferation, cell migration, cell differentiation, and extracellular matrix production, such as collagen. Various studies suggest an inverse relation between TGF-b1 and cardiovascular diseases, while others suggest a role in vascular restenosis. It has been suggested that TGF-b1 may interfere with the development of atherosclerosis, principally through its action on endothelial function. TGF-b1 modulates the endothelial expression of several molecules involved in cell adhesion and spreading or in the regulation of vasomotor tone and cell proliferation. TGF-b1 also preserves endothelial function and protects against reperfusion injury in several models of reperfusion after ischemia. Another mechanism linking TGF-b1 and atherogenesis could involve an interaction with the fibrinolytic system.10,76,77 With regard to clinical studies Grainger et al.78 first reported that serum active TGF-b levels were low in 31 patients with triple vessel coronary disease. Several studies of single TGF-b SNPs in different populations appear to show no relationship with CHD. Wang et al.79 studying the SNP TGF-b1 C509T in 371 patients with coronary vessel disease (50% luminal obstruction demonstrated angiographically), did not find any association with the severity of CHD or TGF-b levels, though this study had no data linking circulating levels of TGF-b to SNPs. Biggart similarly did not find any association between TGF-b2 SNPs and early onset CHD.80 In one study in Japanese (2000) survivors of MI there appeared to be some suggestion of a sex-related difference in allele frequency of TGF-b1 SNP 29C.81 Cambien et al.82 identified several TGF-b1 SNPs: three in the upstream region of the gene at position
988A,
800A, 509T; one in a non-translated region at position þ72; two in the signal peptide sequence Leu10!Pro (29C), Arg25!Pro (74C); and one in the region of the gene coding for protein Thr263!Ile (263T). However, no particular association was found with MI. Similarly, Syrris et al.83 examined four SNPs of TGF-b1: Arg25!Pro (74C), Leu10!Pro (29C), Thr263!Ile (263T),
800A in relation to CHD. In 655 patients with angiographically confirmed CHD, no significant difference was found in the distribution of any of these SNPs or associated haplotypes compared with 244 normal individuals. Generally therefore polymorphisms of TGF-b1 analyzed either singly or in combination showed no association with CHD risk despite early suggestions that active TGF-b serum levels might associate with atherosclerosis.

25.8 INTERFERON-c In addition to innate immunity, clonotypic immunity also plays a role in atherosclerosis. Recent findings support the hypothesis that a crucial component of atherosclerosis is represented by T cell-mediated immune responses that are inappropriate in terms of time of

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onset, intensity, and target. On the other hand, the most direct evidence for the critical role for T cells, IFN-g and IFN-g-driven molecules in atherosclerosis, is provided by mice with combined deficiencies of apolipoprotein E (apoE) and the IFN-g receptor, in which the development of atheromata is significantly reduced in comparison to mice with only apoE deficiency, whereas exogenous IFN-g enhances atherosclerosis.84–87 However, to the best of our knowledge no study has been published on IFN-g polymorphisms and atherosclerosis.

25.9 CONCLUSIONS In this chapter we reviewed the data in the literature, comparing the gene frequencies between patients and controls of cytokine gene polymorphisms potentially related to atherosclerotic cardiovascular diseases. Divergent results exist across population groups, between the types and severity of cardiovascular-related diseases and between numbers and age of subjects. To date, few studies have had the adequate power required for reliable statistical comparison because many candidate polymorphisms related to inflammatory genotypes have relatively low population frequencies. Consistent replication in different populations has been argued as strong evidence of causality.88 However, the immunogenetics of CHD and MI is both complex and intriguing and may alter according to sex and age group. The lack of replication may not necessarily imply lack of causality, but might simply point to the need for more studies in certain populations or more detailed study of the function of a particular gene, taking into account different gene environment interactions.88 It is already accepted that the cardiovascular/ atherosclerosis-related phenotype is strongly affected by life-style and environmental factors and by complex epistatic and pleiotropic effects on several genes. The polymorphisms involved in age-related multifactorial inflammatory diseases are fairly common in the general population, so there is a strong likelihood that any given individual will inherit one or more of the high-risk alleles: the occurrence of CHD and/or MI is likely to depend on interactions between different high-risk alleles, exposure to pathogens, environmental factors and lifestyle choices. So, the small contribution of a single novel polymorphism to the overall risk of multifactorial diseases such as CHD and MI may be obscured by the presence of one or more dominant classical risk factors. No cytokine works in isolation and there is a need for studies to look at interaction between cytokines with respect to CHD or MI. In a single study, Licastro et al.43 reported that the simultaneous presence of the allele C of IL-1b and the allele C of IL-6 was strongly associated with MI; so this kind of study might be a promising approach. Furthermore, in the specific case of MI, given its high early mortality, possible alleles associated with rapidly fatal infarction may be underestimated among survivors (survival bias) altering gene frequency with increasing age. An innovative approach to study potential susceptibility genes for cardiovascular diseases has been followed by Caruso and collaborators60,89,90 by using centenarians as healthy controls. It is known that the major feature characterizing centenarian offspring is the significant reduction of cardiovascular disease prevalence.91 Thus, alleles associated to CHD susceptibility would not be included in the genetic background favouring longevity.60 To evaluate whether
308G/A TNF-a SNP is a component of the genetic background of protection against the cardiovascular diseases, Caruso et al.89 genotyped the TNF
308G/A SNP in male patients affected by acute MI, age-matched controls and centenarians from South Italy. The main result of the study was that
308A SNP, associated to an increased production of this pro-inflammatory cytokine, was over-represented in MI patients and under-represented in centenarian men, with intermediate values in healthy young controls. Significance was obtained only by comparing MI patients versus oldest old people.

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So, individuals with exceptional longevity possess genetic factors that modulate ageing processes and, in particular, protective cardiovascular disease factors. More interestingly, centenarians, who have overcome the major age-related diseases, may be a better control group for case-control studies focussed on age associated diseases with multifactorial aetiology as CHD or AMI.60,89,90 Publishing bias may also skew the knowledge base with respect to cytokine polymorphisms and cardiovascular disease since it is much easier to publish small studies with significant results rather than a large one where no effect on risk is observed. Given the complex interactions likely to be involved in the molecular genetics of multifactorial disorders such as CHD and MI, it is surprising that so many studies have yielded ‘‘positive results.’’ Careful attention to the phenotypic characterization of patients seems a necessary prerequisite for any new study since a new genetic risk factor is more likely to emerge within homogeneous groups of patients with similar disease presentation and categorization. Identifying such homogeneous groups is likely to be difficult and may require rigorous control not only of age, sex, race, and ethnic grouping but also of clinical features and biochemical markers linked to specific pathogenetic mechanisms. Dissecting out the influence of cytokine polymorphism genetics within the complex pathophysiology of CHD and MI disease will help to provide a more complete risk assessment and complement known classical cardiological risk factors. The detection of a risk profile will potentially allow both the early identification of individuals susceptible to disease and the possible discovery of potential targets for drug or lifestyle modification. The advent of DNA chip technology and high throughput genetic analyses allowing the simultaneous rapid assessment of multiple genetic variants with sophisticated biostatistical programmes promises to identify ‘‘genetic signatures’’ for cardiovascular disease and should enable us to draw a more accurate profile of the inflammatory gene variants involved in CHD.

ACKNOWLEDGMENTS Original work of the authors was supported by grants from the Italian Ministry of Education, University and Research, ex 60%, to GC, DL, GCR, CC, and FIRB to CC. Funds from Ministry of Health to CC and GCR are also acknowledged. The collaboration between the ‘‘Gruppo di Studio sull’immunosenescenza’’ coordinated by Prof. C. Caruso and the University of Belfast was enhanced by a grant from Palermo University.

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26

Longevity Irene Maeve Rea, Giuseppina Candore, Luca Cavallone, Fabiola Olivieri, Maurizio Cardelli, Claudio Franceschi, Giuseppina Colonna-Romano, Domenico Lio, Owen Anthony Ross, and Calogero Caruso

CONTENTS 26.1 26.2 26.3 26.4 26.5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interleukin-1 Cluster and Tumor Necrosis Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interleukin-6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interferon-g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Anti-Inflammatory Cytokines Interleukin-10 and Transforming Growth Factor-b . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.6 Interleukin-2, Interleukin-12 and Interleukin-8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

379 380 385 386 386 388 389 391 391

26.1 INTRODUCTION Life span is a multifactorial quantitative trait that is affected by genetic and environmental factors. It also contains a stochastic component resulting from the interaction between the individual’s chance of surviving and unpredictable events that occur throughout the life course. Advances in the treatment of fatal diseases and improvements in nutrition and living conditions led to a drastic reduction in death rate at young ages before 1950 and at old ages after 1950 in the developed world. As a result, mean life span has experienced a remarkable increase in developed countries.1 However, why some people live into their nineties or even become centenarians while others die earlier in life of infection, cancer, or inflammatory diseases such as atheroscelerosis, diabetes, or autoimmune disease remains largely unknown. The conventional wisdom that long life runs in families has consistent support from a growing number of studies. However, a familial component of longevity does not necessarily mean a genetic component. In resolving the problems of shared environment, twin studies are the most reliable indicator of a genetic contribution to human longevity. A study of Danish twins noted only modest heritability in the ability to reach the septuagenarian years and above; but found no evidence for an effect of shared family environment.2 On the other hand, siblings of centenarians were shown to have a four-fold higher survival rate to ages above 85 years compared to siblings of persons who died at the age of 73 years.3 Whereas the twin study examined correlations of age at death in those of average longevity, Perl’s study3 focused on survival to extreme old age, and was therefore likely to detect a stronger effect if genetic factors play a greater role with increasing age. Common gene variants with mildly deleterious effect are present in the human population and are expected to make up a significant part of the genetic contribution to the variation 379

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in life span. Such gene variants may have reached high frequencies in present populations if they increase the risk of disease only late in life and thus escape the force of natural selection. A typical example is shown by APOE alleles which increase the susceptibility to cardiovascular disease and dementia.4 Studying loci implicated in multiple age-related diseases may prove successful in elucidating the genetic contribution to mortality. Gene variants mediating inflammation may be relevant in this respect since inflammation appears to be a common pathway in the development of age-related diseases such as atherosclerosis,5 dementia,6 and type II diabetes.7 Persons who attain extreme old age might simply lack the genetic risk factors for late-onset diseases that are associated with mortality in the general population. A very attractive alternative hypothesis is that extreme longevity might be mediated by a limited number of major protective gene effects. So, extreme longevity might be determined by other genetic and environmental factors when compared with general population mortality. Cytokine dysregulation is believed to play a key role in the proposed remodeling of the immune system accompanying old age. Cytokines play a pivotal role in the regulation of the type and magnitude of the immune-inflammatory responses in elderly people8,9 and so may play an important role in ageing and survival. Moreover, several studies point out that the lack of ability to control systemic inflammation may be a good marker of unsuccessful ageing. Ageing per se involves a complex reshaping of the body’s cytokine pattern, which has been interpreted as a progressive increased propensity toward pro-inflammatory status, a phenomenon which has been called inflamm-ageing.10 A potent inflammatory response is vital in the defence against pathogens throughout life and may influence reproductive success, but chronic inflammation appears to be a common component in the development of major age-related diseases. This trade-off effect is largely predictable since advanced age was not foreseen by evolution.10–13 Cytokine polymorphisms warrant consideration as factors explaining variation in the human immune and inflammatory responses and as candidate susceptibility genes for related pathological states, which mitigate against longevity. The polymorphic nature of the cytokine genes may confer flexibility on the immune response with certain alleles promoting differential production of cytokines that may influence the outcome of viral and bacterial infections or increase susceptibility and resistance to autoimmune disorders and age-related inflammatory diseases.14–18 Many age-related diseases display altered cytokine profiles, suggesting that an inflammatory pathogenesis may be at the basis of these common causes of morbidity and mortality among elderly. It could be expected that people reaching the extreme limits of human life-span, having escaped from major-age-related diseases, i.e. healthy centenarians, will be characterized by genotypic and haplotypic combinations with an ‘‘optimal’’ pro/anti-inflammatory activity.10–13 This review will consider different studies and weigh the evidence for or against cytokine polymorphisms having an important role in longevity in several populations of very elderly subjects in Europe (Figure 26.1 shows the studied polymorphisms and the obtained results are summarized in Table 26.1).

26.2 INTERLEUKIN-1 CLUSTER AND TUMOR NECROSIS FACTOR The ‘‘prototypic’’ inflammatory cytokine IL-1 is a primary mediator of systemic inflammatory responses. It is a family of at least three closely related proteins that are the products of separate genes, i.e. IL-1a, IL-1b, and IL-1Ra. A number of biallelic and multiallelic markers in the surrounding region of IL-1 genes have been identified and several reports have provided evidence that these polymorphisms play a pathophysiological role,

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z

FIGURE 26.1 Single nucleotide polymorphisms assayed in pro- and anti-inflammatory cytokine genes (a) IL-1 gene cluster (IL-1a, IL-1b, IL-1ra) is located on the long arm of chromosome 2 (2q13), within a region of 430 kb (IL-1a
889 rs1800587; IL-1b
551 rs1143627, þ3953 rs1143634; IL-1RN VNTR rs380092); (b) IL-2 gene is located on the long arm of chromosome 4 (4q26–q27), in a region of 5.02 kb (Il-2
330 rs2069762); (c) IL-6 gene is located on the short arm of chromosome 7 (7p21), in a region of 4.80 kb (IL-6
174 rs1800795); (d) IL-8 gene is located on the long arm of chromosome 4 (4q12–q13), in a region of 3.14 kb (IL-8
251 rs4073); (e) IL-10 gene is located on the long arm of chromosome 1 (1q31–1q32), in a region of 4.89 kb (IL-10
1082 rs1800896); (f) IL-12 (p40 subunit) gene is located on the long arm of chromosome 5 (5q31.1–q33.1), in a region of 15.69 kb (IL-12 þ 16974 rs1874396); (g) IFN-g gene is located on the long arm of chromosome 12 (12q14), in a region of 4.97 kb (IFN-g þ874 rs2430561, (Ca)rep rs3138557); (h) TNF gene cluster (TNF-a and TNF-b) is located on the short arm of chromosome 6 (6p21.3), in a region of 7 kb (TNF-a
308 rs361525; TNF-b þ252 rs2857713); (i) TGF-b1 gene is located on the long arm of chromosome 19q13.1 in a region of 43.38 kb (TGF-b1
800 rs1800468,
509 rs1800469, þ869 rs1982073, þ915 rs1800471). ¼ exons; ! ¼ transcription sense 50 !30 .

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Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 26.1 Studies on Cytokine Gene Polymorphisms in Young, Elderly and Centenarians Gene Polymorphism

Centenarians

IL-1a
889 C/T26 IL-1a
889 C/T IL-1a IL-1a IL-1b IL-1b


889C/T20
889C/T
511C/T
511C/T

40 8 94 9 40 8 94 9

IL-1b
511 C/T26 IL-1b
511 C/T IL-1b þ3953 IL-1b þ3953 IL-1raVNTR86bp IL-1raVNTR86bp IL-1raVNTR86bp20 IL-1raVNTR86bp

Elderly (Age)

Young (Age)

52 8 (90) 198 9 (90)

400 (18–60)

1608(65–99) 1499(65–99) 1608(65–99) 1499(65–99) 52 8 198 9 52 8 198 9 52 8 198 9

(19–65) (19–65) (19–65) (19–65)

400 (18–60) 400 (18–60) 400 (18–60)

Results

Finnish Finnish

No change No change

Italian Italian Italian Italian

No No No No

change change change change

Finnish Finnish Finnish Finnish Finnish Finnish

No No No No No No

change change change change change change

Italian Italian

No change No change

1608(65–99) 1499(65–99)

478 8 (19–65) 210 9 (19–65)

IL-2
330 T/G50 IL-2
330 T/G

288 (80–97) 65 9(80–97)

41 8 (19–45) 59 9 (19–45)

Irish Irish

No change No change

IL-6 –174 C/G26 IL-6 –174 C/G

52 8 (90) 198 9 (90)

400 (18–60)

Finnish Finnish

No change No change

Italian Italian

# GG No change

IL-6 –174 C/G48 IL-6 –174 C/G

40 8 94 9

(90) (90) (90) (90) (90) (90)

478 8 210 9 478 8 210 9

Population

68 8 255 9

1508(60–99) 2279(60–99)

IL-6 –174 C/G50 IL-6 –174 C/G

55 8(80–97) 1279(80–97)

69 8 (19–45) 120 9 (19–45)

Irish Irish

No change No change

IL-6 –174 C/G49 IL-6 –174 C/G

58 8(80–97) 1359(80–97)

75 8 (19–45) 107 9 (19–45)

Irish Irish

# GG

44 8 (19–73) 78 9 (18–73)

Italian Italian

No change No change

474 (18–59)

Danish

" GG

68 8 (60) 68 9 (60)

Italian Italian

No change No change

Irish Irish Irish Irish

No No No No

400 (18–60)

Finnish Finnish

No change No change

IL-6 –174 C/G51 IL-6 –174 C/G

19 8 62 9

IL-6 –174 C/G53

178

IL-6 –174 C/G52 IL-6 –174 C/G

36 8 76 9

IL-8
251 A/T50 IL-8
251 A/T IL-10 –1082A/G IL-10 –1082A/G

1058 (60
95)

28 8(80–97) 65 9(80–97) 28 8(80–97) 65 9(80–97)

IL-10 –1082A/G26 IL-10 –1082A/G

52 8 (90) 198 9 (90)

418 59 9 41 8 59 9

(19–45) (19–45) (19–45) (19–45)

change change change change

IL-10 –1082A/G64 IL-10 –1082A/G

31 8 159 9

161 8 (18–60) 99 9 (18–60)

Italian Italian

" GG No change

IL-10 –1082A/G32 IL-10 –1082A/G

72 8 102 9

115 8 (22–60) 112 9 (22–60)

Italian Italian

" GG No change

IL-10 –1082A/G62

54 8

110 8 (18–60)

Italian

" GG

IL-10 –1082A/G52 IL-10 –1082A/G

32 8 55 9

31 8 (60) 54 9 (60)

Italian Italian

No change No change

Irish Irish Irish Irish

No No No No

IL-12 exon8 A/C50 IL-12 exon8 A/C IFN-g intron 1 IFN-g intron 1

28 8(80–97) 65 9(80–97) 28 8(80–97) 65 9(80–97)

41 8 59 9 41 8 59 9

(19–45) (19–45) (19–45) (19–45)

change change change change

(Continued )

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TABLE 26.1 Continued Gene Polymorphism

Centenarians

Elderly (age)

Young (age)

Population

Results

IFN-g þ847T/A59 IFN-g þ847T/A

32 8 142 9

158 8 (19–45) 90 9 (19–45)

Italian Italian

No change "A

IFN-g þ847T/A52 IFN-g þ847T/A

32 8 64 9

36 8 (19–45) 58 9 (19–45)

Italian Italian

No change No change

400 (18–60)

Finnish Finnish

No change No change

115 8 (18–60) 112 9 (18–60)

Italian Italian

No change No change

TNF-a
308G/A26 TNF-a
308G/A TNF-a
308G/A32 TNF-a
308G/A TNF-a TNF-a TNF-b TNF-b

52 8 (90) 198 9 (90) 72 8 102 9


308G/A33
308G/A þ252A/G þ252A/G

TGF-b1 –800G/A78 TGF-b1
800G/A TGF-b1
509C/T TGF-b1
509C/T TGF-b1 þ 869C/G TGF-b1 þ 869C/G TGF-b1 þ 915C/G TGF-b1 þ 915C/G

28 8(80–97) 65 9(80–97) 28 8(80–97) 65 9(80–97) 50 8 122 9 50 8 122 9 50 8 122 9 50 8 122 9

41 8 59 9 41 8 59 9

(19–45) (19–45) (19–45) (19–45)

Irish Irish Irish Irish

No No No No

change change change change

94 8 153 9 94 8 153 9 94 8 153 9 94 8 153 9

(20–60) (20–60) (20–60) (20–60) (20–60) (20–60) (20–60) (20–60)

Italian Italian Italian Italian Italian Italian Italian Italian

No change No change No change No change

" and # refer to significant ( p 5 0.05) increase or respectively decrease of alleles or genotypes respect to control population. IL-1raVNTR86bp polymorphism refers to three alleles with different number of repeats. IFN-g intron 1 polymorphism refers to (CA)n microsatellite repeats and the 12 repeats allele is in linkage with þ847T allele. Note that the further studies performed on IL-6 in oldest old Irish people and IL-10 in Italian centenarians include subjects typed in the previous ones.

by influencing the susceptibility and the severity of a variety of disorders, including age-related diseases.19,20 IL-1 promotes the interaction of endothelial cells with circulating leucocytes, induces the activation and proliferation of monocytes/macrophages, stimulates smooth muscle cell mitogenesis and the synthesis of plasminogen activator inhibitor 1. So, it is believed to play a key part in atherogenesis and IL-1 cluster polymorphisms can be implied in cardiovascular disease susceptibility (see Chapter 7). IL-1 is overexpressed within affected cerebral cortical regions of the AD brain, as shown by quantitative assays of tissue IL-1 concentrations and by increased numbers of IL-1 immunoreactive microglia associated with AD plaques.21–24 Accordingly the IL-1 cluster polymorphism has been implied in AD susceptibility.25 In spite of the role of the IL-1 gene cluster in age-related diseases, the two studies which have related the IL-1 cluster to ageing have shown no attrition in IL-1 cluster gene frequency with increasing age. In the Finnish nonagenarian study there was no difference in the allele frequencies for IL-1a, IL-1b, and IL-1Ra gene polymorphisms between nonagenarians compared to younger subjects nor between the sexes.26 In a very large Italian study, including 134 centenarians, there was also no difference in IL-1a, IL-1b, and IL-1RA allele frequency between the aged and younger subject groups nor between the sexes.20 Together these studies have looked at a large number of nonagenarians and centenarians

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Cytokine Gene Polymorphisms in Multifactorial Conditions

and neither have produced any evidence of change in IL-1 cluster gene frequencies as a result of age suggesting that IL-1 gene cluster does not affect longevity. TNF-a is a pro-inflammatory cytokine whose gene maps to chromosome 6 (p21.1–21.3), within a region that codes for three inflammation-related proteins: TNF-a, TNF-b, and lymphotoxin-b, which are important mediators of the immune response. Several polymorphic sites are documented within the TNF gene cluster and SNPs in the TNF promoter region have been observed to associate with the rate of protein production. TNF genes are thought to determine the strength, effectiveness, and duration of local and systemic inflammatory reactions as well as repair and recovery from infectious and toxic agents and as such they are prime candidates to be involved in age-related disease processes and ageing itself.27 Major effects on the cardiovascular system include increased expression of adhesion molecules and human leukocyte antigen proteins, release of endothelial cytokines and nitric oxide, enhanced vascular permeability, negative inotropism, reduced lipoprotein lipase activity, increased hepatic fatty acid synthesis, involvement in obesity-related insulin resistance, and prothrombotic effects (through enhanced expression of plasminogen activator inhibitor 1 and von Willebrand factor and through suppression of the anticoagulant protein C).28,29 A haplotype for TNF-a associates in siblings with late onset AD30 and carriers of
308A showed an earlier mean age at onset, suggesting that the TNF-a
308 polymorphism affects the age at onset of late AD.31 The TNF-a
308A/G polymorphism has been investigated in three studies aimed to assess its association with longevity. In a Finnish study26 of nonagenarians and young subjects there was no difference in the frequency of the TNF-308A/G polymorphism between the two groups. In an Italian study,32 the frequency of TNF-a
308A/G polymorphism did not vary between centenarians and younger subjects and no significant sex difference emerged. In an Irish study,33 the frequency of TNF-a
308A/G polymorphism in Irish nonagenarians was not different compared to younger control nor was there any sex difference. In the same study no significant frequency difference for the TNF-b þ252A/G polymorphism between Irish nonagenarians and young control subjects was found. Thus, these three studies appear to demonstrate that the TNF-a
308 polymorphism does not affect longevity. Thus, neither IL-1 cluster nor TNF-a polymorphisms showed attrition with longevity in European nonagenarians and centenarians, which is fascinating given the important roles that IL-1 and TNF-a hold at the center of the immune response. However, the major role that these cytokines play in illness has to be taken into account. In illness during the course of an infection, sick individuals experience weakness, malaise, listlessness and inability to concentrate. They become depressed and lethargic, show little interest in their surroundings and stop eating and drinking. The symptoms of sickness, together with the fever response and the associated blood changes are thought to be mostly induced by pro-inflammatory cytokines, and represent a highly organized phylogenetically conserved strategy of the organism to fight infections.34 Thus, we can hypothesize that the decreased ability to control these immune-related activities might be involved on the one hand in an increased susceptibility to age-related diseases and on the other hand in a prompt response to illness. This apparently negative result has nevertheless an important message with respect to the role of pro-inflammatory molecules for ageing and long-term survival. Our working hypothesis for the interpretation of this data is that these polymorphisms in the populations are optimally set to cope with important ‘‘danger’’ agents. We surmise that such agents would be life threatening pathogenic microbes and that the intrinsic immune response is so fundamental to survival as to be non-malleable. From this perspective the association between IL-1 or TNF-a polymorphisms and diseases, including some age-related diseases, can be interpreted as a side-effect of fundamentally conserved genetic variance during the life span. On the whole the data suggest that no one particular polymorphism of either the

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385

IL-1 or TNF gene cluster gives an advantage for survival in the last decade of life and is compatible with the hypothesis that these polymorphisms constitute an evolutionary shield protecting against pathogens thoroughout the entire life-span.

26.3 INTERLEUKIN-6 IL-6 plays a pivotal role in acute phase response and in the balancing of the proinflammatory/anti-inflammatory pathways.35 Elevated IL-6 levels are associated with the development and severity of coronary heart diseases (CHD), as well as with the transition to plaque instability.36,37 Carriers of the
174G SNP appear to be prone to develop lipid abnormalities, have worse glucose handling capacity, higher blood glycosylated hemoglobin, higher fasting insulin levels, and higher insulin sensitivity.38 Conversely, Cþ male carriers of the
174C/G polymorphism have been suggested to be protected from CHD.39 Moreover, microglia, astroglia, neurons, and endothelial cells seem capable of synthesizing IL-6,40,41 elevated levels of IL-6 cause significant CNS damage and behavioral deficits and several reports suggest an association of IL-6 polymorphism with AD.42,43 It has been suggested that the discrepancies observed between IL-6
174 SNP and CHD or AD in some studies, might depend on the genetic background of the population under study and the variable influence of individual genotype on plasma IL-6 levels.42,44 However, serum IL-6 has been proposed as a reliable marker for functional decline, as a predictor of morbidity and mortality in old age and it has been associated with functional disability, cognitive decline, and stroke in older people.45–47 Thus, there has been considerable interest in the 174 IL-6 C/G polymorphism in ageing since it could be argued that if IL-6 tracts with functional decline and age-related disease, then there may be attrition of IL-6GG homozygotes, which produce higher levels of IL-6 in serum, in older survivors in a population. Seven studies have looked at the IL-6 174 C/G polymorphism with respect to ageing. In the earliest study, Bonafe` et al.48 noted a marked reduction in GG homozygotes in male though not female Italian centenarians compared to elderly (60–80 years) and longlived (80–99 years) subjects. In Irish nonagenarians, a non-significant trend was reported for a reduced frequency of the GG polymorphism of IL-6 in the octo/nonagenarians from the BELFAST study group (56%) compared to local population younger subjects (61%), which was more marked in elderly males compared to females.49,50 Wang26 in Finland detected no significant change in IL-6 frequencies between nonagenarians and blood donors, though a reduction of 2% was noted in GG frequency in comparison with their widely ageselected younger control group. This trend for a reduction in GG homozygosity in elderly males in three countries across Europe seems intriguing, since it appears to confirm in different study populations and with a different study design, the earlier findings obtained in the Italian population.48 However, in later studies no difference in the IL-6
174 C/G promoter allelic and genotypic frequencies between centenarians and controls was reported by Capurso et al.51 or by Pes et al.,52 but the number of subjects enrolled in these studies was low. Conversely, a modest, but significant, increase in the frequency of IL-6
174 GG homozygotes with age was noted in a large group of Danish subjects, though no analysis was carried out for gender.53 The reason for the discrepancies regarding the association between longevity and the IL-6
174 C/G polymorphism is unclear. The ethnic difference as well as the lifestyle and cultural difference amongst these populations could play a role, as well as other unidentified factors. In studies carried out to date, IL-6 looks like the most interesting cytokine with respect to longevity. Studies performed in separate Caucasian European elderly populations and with different selection criteria, appear to demonstrate a decrease in the IL-6
174G/G homozygote frequency with extreme old age. Italian researchers additionally demonstrated

386

Cytokine Gene Polymorphisms in Multifactorial Conditions

a reduction in IL-6 high producer allele frequency for male centenarians which was not seen in females or replicated in any other studies. Large scale studies at the European level on many ethnic populations are needed to clarify this important topic.

26.4 INTERFERON-c IFN-g, a key regulator of the development and function of the immune system, plays a key role in immune defence against intracellular pathogens.54 There is some evidence that IFN-g polymorphisms may be involved in infectious disease susceptibility, with the increased IFN-g producer allele decreased in tuberculosis55 and an interesting report links IFN-g CA repeats (alleles 10/11) with total serum IgE.56 On the other hand, no study has been published on the association between the age-related inflammatory disease atherosclerosis and IFN-g polymorphisms. However, both in experimental animals and in human beings, IFN-g seems to be involved in the development of atherosclerotic plaques and AD.11,12 However, two recent reports suggest no association between IFN-g polymorphisms and AD in Italian patients.57,58 In centenarians, Lio and colleagues59 first reported that carriage of the þ874A allele (847 SNP is in linkage with a repeat microsatellite allele) was associated with longevity in centenarian females likely by controlling inflammatory status. This finding could not be replicated by Ross et al.50 in nearly 200 Irish nonagenarians, where they reported similar frequencies for the CA/12 allele repeat in control and aged subjects. The small decrease in the CA/12 repeat in aged Irish female nonagenarians was not significant, but does demonstrate a similar trend to the findings of Lio et al.59 in their Italian centenarian female group. The CA/13 repeat allele of IFN-g microsatellite, also determined by Ross et al.,50 was apparently similarly represented between Irish aged (52%) and young groups (49%) with no sex difference. Ross et al.50 also commented on a notable but non-significant decrease in the frequency of the heterozygote 12, 13 genotype within the aged subjects (37%) in comparison to the young controls (49%) which was also reflected in both male (49% vs. 39%) and female (49% vs. 35%) young controls and aged subjects, respectively. These findings suggest that bigger repeat studies need to be considered to see if these findings can be replicated, particularly where sex differences need to be taken into account. Interestingly, a decrease in IFN-g þ 874T was observed among female Sardinian centenarians, although the differences did not reach statistical significance. These findings may relate to the relatively small number of Sardinian female centenarians, which may have limited the statistical power of the study.52 Thus, the IFN-g high producer combination haplotype 12CA/þ874T showed a decrease in centenarian Italian women with a trend for the same change in Irish nonagenarians and Sardinian centenarians but this finding, although suggestive, needs replication.

26.5 THE ANTI-INFLAMMATORY CYTOKINES INTERLEUKIN-10 AND TRANSFORMING GROWTH FACTOR-b IL-10, a cytokine with anti-inflammatory and B cell stimulating activity, is produced by activated T cells, B cells, monocytes/macrophages, and dendritic cells. IL-10 is thought to block the ability of monocytes/macrophages and dendritic cells to act as antigen presenting cells by down regulation of major histocompatibility complex (MHC) products and co-stimulatory molecules via suppression of the MAPK cascade. Thus, the principal function of IL-10 appears to be to limit and ultimately terminate the inflammatory signal.60,61 From the point of view of age-related diseases, which might influence death, although IL-10 is expressed in human atherosclerotic plaques, case-control studies across Europe

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do not support any role for IL-10 in either atherosclerotic-related disease or myocardial infarction.61,62 However, a more recent study in two Italian samples of patients affected by myocardial infarction suggests a role for IL-10 polymorphism linked to low cytokine production in the occurrence of the disease.62 In addition, the presence of
1082A allele and in particular of
1082A/
819T/
592A haplotype, associated with a low production of anti-inflammatory cytokine IL-10 has been suggested to be an additive and independent genetic risk factor for AD.61,63 The IL-10 G 1082A/G allele has been reported to be a male-specific marker for longevity. In three studies, Lio and colleagues32,62,64 reported an increased frequency of the homozygote
1082GG genotype in Italian centenarian men. The
1082GG genotype, associated with high IL-10 production, was argued to confer an anti-inflammatory status which was postulated to enhance the possibility of extreme longevity. This result was not replicated in an Irish nonagenarian study50 where comparable frequencies between aged males (32%) and younger males (37%) were described, nor in the Finnish nonagenarian study26 for all nonagenarian subjects or males alone. In addition, no significant differences were observed by analyzing IL-10 genotypic and allelic frequencies among Sardinian centenarians and controls both together and when the data were analyzed by gender.52 The suggestion that enhanced male life expectancy is associated with IL-10-1082GG homozygote status is interesting in view of the findings by Westendorp65 that heritable factors in IL-10, associated with higher IL-10 production, were important in serious meningococcal septicaemia. Here patients and families who were high IL-10 producers had a 20-fold higher chance of a fatal outcome than families with a low production of IL-10. Additionally, in keeping with this finding, other studies show that patients with fatal outcome of pyrexia66 and children with sudden infant death have high IL-10 levels or high IL-10 producer allele status.67 These findings are seemingly counter-intuitive to the enhanced male longevity associated with homozygous IL-10
1082GG status, which is the high IL-10 producing allele. Males are reputed throughout life to have a slightly increased mortality from infectious causes,68 increased mortality in shock,69 and there is known sexual dimorphism in the immune response.70,71 In order to rationalize these two seemingly conflicting situations, it might be argued that IL-10
1082GG homozygous males who are lucky enough not to contract serious bacterial infection earlier in life may have an increased chance of long-life survival (trade-off). However the same appears not to be true for female life expectancy. No cytokine works in isolation and there is a need for studies to look at the balance between pro-inflammatory and anti-inflammatory groups of cytokines with respect to ageing. In a single study, Lio et al.32 reported that a combination of high IL-10 and low TNFa producer polymorphisms was a genetic combination which favored longevity in male but not in female centenarians, but the number of males was relatively small and this finding needs replication. Although a high anti-inflammatory and low pro-inflammatory haplotype is an attractive hypothesis for longevity, it has some difficulties since, in earlier life, high IL-10 producer polymorphism tracks with increased mortality in bacterial infections which seems contra-intuitive (see above). However, inflammatory genotypes may be both friends and enemies since they are important and necessary parts of the normal host responses to pathogens. A highly-charged overproduction of inflammatory cytokines might cause immune-mediated inflammatory diseases and early death, whereas an anti-inflammatory genotype might be highly advantageous in the last decades of life where a chronic proinflammatory status appears to develop with increasing old age. This phenomenon, called inflamm-ageing,10 is more evident in men than in women and may be a possible explanation for the higher frequency of anti-inflammatory genotype found in very old male subjects. TGF-b1, the prototypic member of the family of the TGF-b superfamily, has been shown to have an essential role in inflammation and in maintenance of immune response

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Cytokine Gene Polymorphisms in Multifactorial Conditions

homeostasis. TGF-b1 belongs to the group of cytokines with anti-inflammatory effects, being a deactivating factor of macrophages and having potent anti-inflammatory properties.72,73 TGF-b1 seems to have an important role in human ageing. In fact, a TGF-b1 gene overexpression has been observed in human fibroblasts that display a senescent-like phenotype following exposure to oxidative stress.74 Polymorphisms in human TGF-b1 gene influencing cytokine production have been identified and these polymorphisms have been linked to age-related pathologies, such as hypertension,75 osteoporosis76 and Alzheimer disease.77 To test the hypothesis that this variability of the TGF-b1 gene affects successful ageing and longevity, Carrieri et al.78 analyzed 419 subjects from Northern and Central Italy, including 172 centenarians and 247 younger controls. They found that the level of the active cytokine increased with age and a significant difference was found between the age groups for the genotype and allele frequencies at the þ915 site, but none for other tested variants (the
800,
519, and þ869 loci). As this polymorphism occurs at codon 25 within the signal peptide that is cleaved from the TGF-b1 precursor at the level of codon 29, it is possible that the (Arg4Pro)25 substitution could play a role in the efficient production of the mature TGF-b1. Since TGF-b1 is immunosuppressive, the age-related increase of the active cytokine suggests that it could counteract and counterbalance the harmful effects of inflamm-ageing, which is likely to be a common driving force of most age-associated pathologies.

26.6 INTERLEUKIN-2, INTERLEUKIN-12 AND INTERLEUKIN-8 An age-related decline in IL-2 production has been recognized since the early work of Gillis et al.79 who identified a T cell growth factor, later called IL-2, that was decreased in ageing. Subsequent studies showed that IL-2, essential for T cell proliferation and growth and for an efficient effector response, is reduced in aged subjects with associated effects on intracellular activation of nuclear transcription pathways.80–82 No studies have been performed in age-related diseases. In the only study, to date, related to ageing, the IL-2
330 G/T polymorphism was compared in young and very elderly Irish subjects.50 This single study does not support any major change in the frequencies of IL-2
330 genotypes in Irish subjects as a function of increasing age. IL-12, a cytokine that is secreted by activated phagocytes and dendritic cells and induces IFN-g production by natural killer cells and T lymphocytes, is a key regulator of the polarization of immune responses (type-1 vs. type-2) and plays a role in autoimmune and infectious diseases.83 From the published studies to date, there is not much evidence that infections or age-related degenerative diseases are affected by IL-12 polymorphisms and it seems unlikely that the frequencies of IL-12 polymorphisms would be altered with age. In the one paper looking at IL-12 polymorphisms and ageing, Ross et al.50 demonstrates apparently similar frequencies of the IL-12A/C polymorphism in aged vs. control subjects with similar values for A alleles in aged vs. controls (79% vs. 81%) and C alleles (21% vs. 19%), respectively. Although there was a trend for AA homozygotes to be under-represented in elderly males (54% vs. 70%) with a 7% decrease in the A allele in elderly males, neither of these decreases achieved significance. No apparent difference was present for old and young female subjects. IL-8 is a potent neutrophil chemokine that brings neutrophils to inflammatory sites where they limit and contain the infection. Because septicaemia and serious infection are more common and difficult to treat in very old people, it has often been suspected that some aspects of neutrophil function might be comprised with increasing age, though evidence for this has been inconsistent.84 There was therefore interest in whether any polymorphisms of IL-8 might be altered in ageing. In a single study looking at the

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IL-8
251A/T polymorphism and longevity, Ross et al.50 reported that AA homozygotes, associated with higher IL-8 production, showed a frequency of 25% in 100 controls compared to 22% in 93 Irish aged subjects, with no age attrition in homozgyotes overall. In single population studies, these cytokines appeared to have no real influence on longevity or differential longevity between the sexes. However, in the Irish study only one hundred aged and control subjects were compared and so statistical power may have been compromised. So, these early studies need to be replicated in another population and with bigger numbers of males and females, possibly centenarians (see Conclusions) to see if results are consistent.

26.7 CONCLUSIONS In this chapter, we reviewed the available literature data on cytokine gene polymorphisms in centenarians and nonagenarians which could affect the individual’s chance to reach the extreme limit of human life. The data show that the immunogenetics of ageing and longevity is both complex and intriguing. Indeed, as discussed by Franceschi,85 the longevity phenotype is strongly affected by life-style and environmental factors and by complex epistatic and pleiotropic gene effects. The genetics of ageing and longevity is highly unusual and most probably represents a post reproduction genetic scenario, where the force of selection progressively fades in the later decades of life. Thus, we can argue that the ageing process allows the emergence of biological effects of individual genetic differences that might remain neutral or silent in earlier life. Besides, our data suggests that gender is an important variable in the biology of the ageing process.86 It remains unexplained why many more women than men become nonagenarians or even centenarians. As previously discussed, sexual dimorphism in the immune response has been described in innate and cell-mediated responses in vitro and in vivo. These emerging studies looking at cytokine polymorphisms and haplotypes and longevity hint again and again that a differential immune responsiveness may be present between the sexes which extends to very old age. This raises important questions about whether there could be fundamentally different basic biological mechanisms at the cellular level between the sexes. The gene–sex interaction suggests that the effect of a gene on a multifactorial trait depends on the physiological background in which the gene is expressed. If the age-related physiological scenario changes in males and females differently, the effects of a certain gene on disease or survival could vary between the sexes, which indicates that males and females may follow different trajectories toward extreme longevity.86 The findings, while intriguing, lack adequate statistical power and need to be repeated in large pan-European studies since few countries alone could provide adequate numbers of male centenarians who are even today relatively rare. However, considering the data obtained in Italian male centenarians, there is the intriguing suggestion that alleles coding for low levels of pro-inflammatory cytokine IL-6 or high levels of anti-inflammatory cytokine IL-10 may affect the individual life-span expectancy. On the other hand, the discordant results reported in Finnish, Irish, and Sardinian populations do not confirm this hypothesis but could be related to the nonagenarian cohorts studied, who may be less selected than centenarians investigated in Italian studies, and/or to the relatively low number of subjects. In addition, differences may relate to different genetic population pools and gene–environment interactions. In this context, there are well described differences in ApoE genotype frequency across Europe and world populations, which undoubtedly link into pathological and environmental disease mechanisms and differential morbidity and mortality rates from atherosclerotic-related disease, and there may be similar effects for cytokine genotypes.4 It is noteworthy that the epidemiological data available on CHD in Sardinia indicate a low mortality of CHD

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in this population compared with mainland Italy. Interestingly, the frequency of the well-known risk factor APOEe 4 is unusually low and, most interestingly, does not change in the different age groups, i.e. does not decrease in old subjects and does not influence lipid metabolism.87 The different results obtained in the Italian population might also depend on the differential importance of classical risk factors for atherosclerosis and CHD in the Italian population since the traditional Mediterranean diet may affect the incidence and prevalence of CHD.88,89 Centenarians are characterized by marked delay or escape from age-associated diseases that normally cause mortality at earlier ages. Centenarian offspring have a marked increased probability of longevity and show a reduced prevalence of age-associated diseases, particularly related to cardiovascular disease and cardiovascular risk factors. So, genes involved in cardiovascular diseases may play an opposite role in human longevity, and individuals with exceptional longevity may possess genetic factors that modulate ageing processes or are protective against cardiovascular disease.90 Our data prompt consideration of the role that antagonistic pleiotropy plays in disease and in longevity.91 Our immune system has evolved to control pathogens and so proinflammatory responses are likely to be evolutionarily programmed to resist fatal infections. Yet genetic backgrounds promoting pro-inflammatory responses may play opposite roles in cardiovascular diseases and in longevity, such that cardiovascular diseases are a late consequence of an evolutionary pro-inflammatory response highly charged and programmed to resist infections in earlier life. Genetic polymorphisms responsible for a low inflammatory response might result in an increased chance of long life-span in an environment with a reduced antigen (i.e. pathogens) load, such as a modern day health environment, and may also permit a lower grade survivable inflammatory response to atherogenesis and atherosclerosis-related disease. In this regard, the role of toll-like receptor(TLR)4 may be paradigmatic. The transmembrane lipopolysaccaride receptor TLR4 initiates the innate immune response to common Gram-negative bacteria and polymorphisms known to attenuate receptor signaling, such as ASP299GLY, determine a lower risk of carotid atherosclerosis, and less intimal media thickness in the common carotid artery.92,93 Moreover, subjects with mutant genotype had lower levels of pro-inflammatory cytokines, acute phase reactants, and soluble adhesion molecules and in CHD patients, controls and centenarians, this polymorphism showed significantly lower frequencies in myocardial infarction patients compared to controls, whereas centenarians showed higher frequencies.93 Hence, the TLR4 genotype, known to attenuate receptor signaling and therefore inflammatory responses, was found to be associated with the possibility of reaching the extreme limit of human life-span in men but was under represented in CHD patients. In conclusion there is some suggestion that people genetically predisposed to weak inflammatory activity may be at reduced chance of developing CHD and, therefore, may achieve longer life span if they avoid serious life-threatening infectious disease throughout life. Thus, the pathogen burden, by interacting with host genotype, could determine the type and intensity of the immune-inflammatory response responsible both for pro-inflammatory status and CHD. These findings point to a strong relationship between the genetics of inflammation, successful ageing, and the control of cardiovascular disease13 but do seem to suggest that the evidence for men is much stronger, whereas in females the situation seems to be quite different. The jury therefore remains close to delivering a verdict as to which and what combination of cytokines influence longevity. Accumulating evidence suggests that immunological determinants for cardiovascular risk factors play an important role in ageing and the intriguing issue of the sexual differential in lifespan seems more and more likely to be explained by genetic cytokine interactions influenced by a whole range of pathogenic

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challenges and environmental backgrounds. No studies, to date, in nonagenarians and centenarians have had adequate statistical power to give clear unambiguous answers and this is especially true for centenarian males who are even rarer in number than females. Larger studies with collaborative efforts are required to achieve the sample size of many hundreds of case-control pairs that is necessary to deliver the definitive verdict.

ACKNOWLEDGMENTS Original work of authors was supported by grants from the Italian Ministry of Education, University and Research, ex 60%, to GC, DL, GCR, CC and CF and FIRB to CC and CF. Funds from EU 5FP T-CIA project to CF and Ministry of Health to CF and GCR are also acknowledged. The collaboration between three ‘‘Gruppo di Studio sull’immunosenescenza’’ coordinated by Prof. C. Caruso and INRCA was enhanced by a cooperation contract (longevity and elderly disability biological markers).

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46. Ershler, W. B. and Keller, E. T., Age-associated increased interleukin-6 gene expression, late-life diseases, and frailty, Annu. Rev. Med., 51, 245, 2000. 47. Cesari, M. et al., Inflammatory markers and physical performance in older persons: the InCHIANTI study, J. Gerontol. A Biol. Sci. Med. Sci., 59, 242, 2004. 48. Bonafe, M. et al., A gender–dependent genetic predisposition to produce high levels of IL-6 is detrimental for longevity, Eur. J. Immunol., 31, 2357, 2001. 49. Rea, I. M. et al., Interleukin-6-gene C/G 174 polymorphism in nonagenarian and octogenarian subjects in the BELFAST study. Reciprocal effects on IL-6, soluble IL-6 receptor and for IL-10 in serum and monocyte supernatants, Mech. Ageing Dev., 124, 555, 2003. 50. Ross, O. A. et al., Study of age-association with cytokine gene polymorphisms in an aged Irish population, Mech. Ageing Dev., 124, 199, 2003. 51. Capurso, C. et al., F. Interleukin 6-174 G/C promoter gene polymorphism in centenarians: no evidence of association with human longevity or interaction with apolipoprotein E alleles, Exp. Gerontol., 39, 1109, 2004. 52. Pes, G. M. et al., Association between longevity and cytokine gene polymorphisms. A study in Sardinian centenarians, Aging Clin. Exp. Res., 16, 244, 2004. 53. Christiansen, L. et al., Modest implication of interleukin-6 promoter polymorphisms in longevity, Mech. Ageing Dev., 125, 391, 2004. 54. Novelli, F. and Casanova, J. L., The role of IL-12, IL-23 and IFN-gamma in immunity to viruses, Cytokine Growth Factor Rev., 15, 367, 2004. 55. Lio, D. et al., Genotype frequencies of the þ874T–>A single nucleotide polymorphism in the first intron of the interferon-gamma gene in a sample of Sicilian patients affected by tuberculosis, Eur. J. Immunogenet., 29, 371, 2002. 56. Nagarkatti, R. et al., Association of IFNG gene polymorphism with asthma in the Indian population, J. Allergy Clin. Immunol., 110, 410, 2002. 57. Scola, L. et al., Allele frequencies of þ874T –> A single nucleotide polymorphism at the first intron of IFN-gamma gene in Alzheimer’s disease patients, Aging Clin. Exp. Res., 15, 292, 2003. 58. Galimberti, L. et al., G. þ874(T–>A) single nucleotide gene polymorphism does not represent a risk factor for Alzheimer’s disease, Immun. Ageing, 1, 6, 2004. 59. Lio, D. et al., Allele frequencies of þ874T–>A single nucleotide polymorphism at the first intron of interferon-gamma gene in a group of Italian centenarians, Exp. Gerontol., 37, 315, 2002. 60. Sato, K. et al., Extracellular signal-regulated kinase, stress-activated protein kinase/c-Jun N-terminal kinase, and p38mapk are involved in IL-10-mediated selective repression of TNF-alpha-induced activation and maturation of human peripheral blood monocyte-derived dendritic cells, J. Immunol., 162, 3865, 1999. 61. Lio, D. and Caruso C., IL-10, Genetic polymorphism and its relevance to age-related diseases. In Interleukin-10, edited by Francesco M. Marincola, Landes Bioscience, Georgetown, Texas, USA, 93–106, 2006. 62. Lio, D. et al., Opposite effects of interleukin 10 common gene polymorphisms in cardiovascular diseases and in successful ageing: genetic background of male centenarians is protective against coronary heart disease, J. Med. Genet., 41, 790, 2004. 63. Lio, D. et al., Interleukin-10 promoter polymorphism in sporadic Alzheimer’s disease, Genes Immun., 4, 234, 2003. 64. Lio, D. et al., Gender-specific association between
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69. Higgins, T. L. et al., Early indicators of prolonged intensive care unit stay: impact of illness severity, physician staffing, and pre-intensive care unit length of stay, Crit. Care Med., 31, 45, 2003. 70. Roberts, C. W., Walker, W., and Alexander, J., Sex-associated hormones and immunity to protozoan parasites, Clin. Microbiol. Rev., 14, 476, 2001. 71. Klein, S. L., The effects of hormones on sex differences in infection: from genes to behavior, Neurosci. Biobehav. Rev., 24, 627, 2000. 72. Weiss, J. M., Cuff, C. A., and Berman, J. W., TGF-beta downmodulates cytokine-induced monocyte chemoattractant protein (MCP)-1 expression in human endothelial cells. A putative role for TGF-beta in the modulation of TNF receptor expression, Endothelium, 6, 291, 1999. 73. Letterio, J. J. and Roberts, A. B., Regulation of immune responses by TGF-beta, Annu. Rev. Immunol., 16, 137, 1998. 74. Frippiat, C. et al., O. Signal transduction in H2O2-induced senescence-like phenotype in human diploid fibroblasts, Free Radic. Biol. Med., 33, 1334, 2002. 75. Li, B. et al., TGF-beta1 DNA polymorphisms, protein levels, and blood pressure, Hypertension, 33, 271, 1999. 76. Yamada, Y. et al., Association of a Leu(10) ! Pro polymorphism of the transforming growth factor-beta1 with genetic susceptibility to osteoporosis and spinal osteoarthritis, Mech. Ageing Dev., 116, 113, 2000. 77. Luedecking, E. K. et al., Analysis of genetic polymorphisms in the transforming growth factor-beta1 gene and the risk of Alzheimer’s disease, Hum. Genet., 106, 565, 2000. 78. Carrieri, G. et al., C. The G/C915 polymorphism of transforming growth factor beta1 is associated with human longevity: a study in Italian centenarians, Aging Cell, 3, 443, 2004. 79. Gillis, S. et al., Immunological studies of aging. Decreased production of and response to T cell growth factor by lymphocytes from aged humans, J. Clin. Invest., 67, 937, 1981. 80. Candore, G. et al., A. The effect of age on mitogen responsive T cell precursors in human beings is completely restored by interleukin-2, Mech. Ageing Dev., 63, 297, 1992. 81. Rea, I. M. et al., Changes in lymphocyte subsets, interleukin 2, and soluble interleukin 2 receptor in old and very old age, Gerontology, 42, 69, 1996. 82. Whisler, R. L., Beiqing, L., and Chen, M., Age-related decreases in IL-2 production by human T cells are associated with impaired activation of nuclear transcriptional factors AP-1 and NF-AT, Cell Immunol., 169, 185, 1996. 83. Langrish, C. L. et al., IL-12 and IL-23: master regulators of innate and adaptive immunity, Immunol. Rev., 202, 96, 2004. 84. Di Lorenzo, G. et al., Granulocyte and natural killer activity in the elderly, Mech. Ageing Dev., 108, 25, 1999. 85. Franceschi, C. et al., Genes involved in immune response/inflammation, IGF1/insulin pathway and response to oxidative stress play a major role in the genetics of human longevity: the lesson of centenarians, Mech. Ageing Dev., 126, 351, 2005. 86. Franceschi, C. et al., Do men and women follow different trajectories to reach extreme longevity? Italian Multicenter Study on Centenarians (IMUSCE), Aging (Milano), 12, 77, 2000. 87. Deiana, L. et al., L. Lack of influence of apolipoprotein E4 on lipoprotein levels in the island population of Sardinia, Eur. J. Clin. Invest., 28, 290, 1998. 88. Massaro, M. et al., Direct vascular antiatherogenic effects of oleic acid: a clue to the cardioprotective effects of the Mediterranean diet, Cardiologia, 44, 507, 1999. 89. Barzi, F. et al., Mediterranean diet and all-causes mortality after myocardial infarction: results from the GISSI-Prevenzione trial, Eur. J. Clin. Nutr., 57, 604, 2003. 90. Terry, D. F. et al., Cardiovascular disease delay in centenarian offspring, J. Gerontol. A Biol. Sci. Med. Sci., 59, 385, 2004. 91. Nesse, R. M. and Williams, G. C., Evolution and the origins of disease, Sci. Am., 279, 86, 1998. 92. Kiechl, S. et al., Toll-like receptor 4 polymorphisms and atherogenesis, N. Engl. J. Med., 347, 185, 2002. 93. Balistreri, C. R. et al., Role of Toll-like receptor 4 in acute myocardial infarction and longevity, JAMA, 292, 2339, 2004.

27

AIDS Alexandre Vasilescu, Herve´ Do, and Jean-Francois Zagury

CONTENTS 27.1

Introduction: HIV-1 Infection and AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1.1 Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1.2 Viral Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.1.3 Current Treatments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.2 Pathogenesis of HIV-1 Infection: Many Inconclusive Hypotheses . . . . . . . . . . . . . . 27.3 Genetic Studies in AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.3.1 Cohorts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.3.2 Methodological Principles of Genetic Association Analysis in AIDS . . . . 27.3.3 Candidate Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4 Polymorphisms of the Chemokine System Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.1 The CCR5 Gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.1.1 Structure of the CCR5 Gene and Polymorphisms . . . . . . . . . . . . 27.4.1.2 Genetic Associations in AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.1.3 Biological Interpretation of the Associations. . . . . . . . . . . . . . . . . . 27.4.2 CCR2 Gene Polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.2.1 Structure of the CCR2 Gene and Polymorphisms . . . . . . . . . . . . 27.4.2.2 Associations with AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.2.3 Biological Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.2.4 The CCR2/CCR5 Locus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.3 RANTES Gene Polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.4 Other Polymorphisms in the Chemokine Genes . . . . . . . . . . . . . . . . . . . . . . . . 27.5 Polymorphisms in Cytokines Genes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.5.1 Th1–Th2 Cytokine Gene Polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.5.2 TNFa Gene Polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.5.3 Cytokine Receptor Gene Polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

395 395 396 396 396 397 397 397 398 398 398 398 399 399 400 400 400 400 400 400 401 402 402 402 404 404 406

27.1 INTRODUCTION: HIV-1 INFECTION AND AIDS 27.1.1 DESCRIPTION In 1983, Barre´-Sinoussi et al.1 isolated the human immunodeficiency virus type 1 (HIV-1) and Gallo et al. proved in 1984 that it was the etiologic agent responsible for acquired immunodeficiency syndrome (AIDS).2 HIV-1 and HIV-2 are two cousin types of retroviruses able to infect humans and they both belong to the lentivirus subfamily. While HIV-1 has led to worldwide pandemics, HIV-2 is mostly limited to West Africa and appears to be less pathogenic than HIV-1.3,4 395

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Cytokine Gene Polymorphisms in Multifactorial Conditions

27.1.2 VIRAL CYCLE HIV cycle follows the ‘‘classical’’ retroviral cycle with the following steps: (1) binding of the virus to receptors, (2) fusion with the viral core inserted into the cell, (3) reverse transcription of the viral genome, (4) nuclear import of double-stranded DNA, (5) integration of the proviral DNA into the host genomic DNA, (6) transcription of viral RNA and translation of viral proteins, (7) budding of the virus from the cell membrane and maturation, and (8) new cycle of infection of uninfected cells. HIV infects mainly the CD4þ cells of the immune system and cells from the reticulo-endothelial system such as macrophages. Once integrated in the genome, the provirus behaves essentially as a cellular gene and can be reactivated following an immune stimulation linked to undercurrent infections or to stress.5–7 The time span between the HIV-1 initial infection and the appearance of disease symptoms can vary from a few months to several years. The CD4 antigen is the primary cell surface receptor for the virus8 but an interaction with additional receptors is required for the entry into the cell and the initiation of the infection. In vitro, the entry could be mediated by more than a dozen G-protein-coupled co-receptors from the chemokine receptor family.9,10 However, there is little evidence that all these coreceptors are used in vivo.10,11 Schematically, the two most relevant coreceptors for HIV-1 replication in vivo are the b-chemokine receptor CCR5 and the a-chemokine receptor fusin CXCR4. The viruses that exclusively use CCR5 (receptor of a-chemokines RANTES, MIP-1a and MIP-1b) are known as R5 strains (generally non-syncytiuminducing), and those that exclusively use CXCR4 (receptor of a-chemokine SDF-1) are called X4 strains (generally syncytium-inducing). R5 strains are predominant for the initial infection of most individuals and are progressively replaced by X4 variants whose appearance has been associated with CD4þ cell decline and disease progression.12

27.1.3 CURRENT TREATMENTS To date, no effective vaccine or definitive cure for AIDS exists. The current antiviral therapies, called highly active antiretroviral therapy (HAART), include 3–4 drugs that act in combination to antagonize distinct steps of the retroviral life cycle (reviewed in Ref. 13). The protease inhibitors (PIs) target the aspartyl protease responsible for cleaving the gag and gag-pol structural proteins during virion maturation. The other drugs target the reverse transcription process. The nucleoside reverse transcriptase inhibitors (NRTIs) inhibit reverse transcription by blocking the elongation of the nascent polynucleotide chain and the non-nucleoside reverse transcriptase inhibitors (NNRTI) inhibit replication by reducing the activity of the reverse transcriptase. Recently, small molecules targeting viral entry have been developed at the clinical stage:14 peptides inhibiting the fusion process and antagonists of the CCR5 and CXCR4 coreceptors. The current drug regimens pose serious challenges due to their complexity (drugresistant mutations) and toxicity. Therefore, novel therapeutics must be developed to complement the antiviral drugs and for this a better understanding of the HIV-1/host interaction is needed. Large-scale pharmacogenomic studies are specifically undertaken in order to unravel the molecular mechanisms of HIV-1 infection and thus rationally derive new diagnostic and therapeutic strategies.

27.2 PATHOGENESIS OF HIV-1 INFECTION: MANY INCONCLUSIVE HYPOTHESES Despite a vigorous innate and adaptive immunity against HIV-1, this pathogen is almost never eliminated from an infected individual, leading to chronic infection. The main feature

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of HIV-1 infection is the depletion of CD4þ lymphocytes that causes the impairment of the immune defenses and leads to the appearance of opportunistic diseases, cachexia, or cancers. To date, the molecular mechanisms of AIDS physiopathogenesis remain unclear although many hypotheses have been proposed since the mid-1980s: (i) direct effect of the virus: cytopathic effect15 or syncitia formation,16 (ii) induction of immune disorders: anergy,17 autoimmunity,18,19 superantigen,20 and (iii) disruption of the reticuloendothelial system leading to the destruction of the lymphoid organs.21 However, the only conclusive and reproducible observations point out the cytokine dysbalance, for instance the so-called Th1/Th2 shift,22 and the greater frailty of the cells leading to their apoptosis.23,24

27.3 GENETIC STUDIES IN AIDS 27.3.1 COHORTS Early after the discovery of HIV-1, cohorts of patients were created in order to correlate biological data with disease stage or progression. Theoretically, three types of factors could be at stake: viral genetic factors, host genetic factors, and environmental factors. In the mid-1990s, the cohorts were used to identify the human genetic determinants involved in infection and/or AIDS progression. Initially, the cohorts were longitudinal, composed of patients at all-stages of disease, many of whom were followed since their seroconversion. Later, special groups of patients exhibiting extreme patterns of disease progression were gathered for genetic association case-control studies. Hence, patients with slow progression (SP) have been defined consensually as subjects infected for more than 8 years, with no clinical symptomas and keeping a CD4þ cell count above 500/mm3, in the absence of any antiretroviral therapy.25,26 Patients with rapid progression (RP) are characterized by a drop in their CD4þ cell count below 300/mm3 in less than 3 years after the last seronegative test.26 A list of the major cohorts has been presented in the meta-analysis of Ioannidis et al. on CCR5/CCR2 gene polymorphisms.27 To date, the most informative cohorts for genetic associations are the seroconverter patients cohorts such as the MACS cohort (about 1500 patients at all stages of the disease) and the extreme patients cohorts such as the GRIV cohort (composed of 100 RP and 300 SP). Based on the observations of the clinical centers, the extreme phenotypes SP and RP represent each a 1–2% subset of the seropositive patients and therefore the GRIV study is equivalent to the extremes of a longitudinal cohort of 26 000 patients at all stages of disease.28

27.3.2 METHODOLOGICAL PRINCIPLES OF GENETIC ASSOCIATION ANALYSIS IN AIDS The use of longitudinal cohorts versus extreme case-control studies implies different statistical approaches to correlate the genotypes with patient evolution. Kaplan–Meier ‘‘survival’’ curves are generated for longitudinal cohorts to compare the effect of different genotypes on specific AIDS outcomes whereas Fisher’s exact tests (or 2-like tests) are performed for comparing cases to controls in transversal studies: in both cases P values measuring the statistical significance are produced. The most common polymorphisms are the single nucleotide polymorphisms (SNPs). The presence of a variant allele in the binding site of a transcription factor could affect the expression level of a gene and therefore influence disease development. Similarly a haplotype can influence the onset/progression of disease even if the SNPs it derives from do not have any individual effect. As a consequence, the approach used in the GRIV study was to study systematically: (1) the effect of individual SNPs, (2) global haplotypes estimated from all SNPs,

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Cytokine Gene Polymorphisms in Multifactorial Conditions

(3) haplotypes estimated from the polymorphisms of the promoter region, (4) haplotypes estimated from the nonsynonymous variants, and (5) haplotypes estimated from the synonymous variants. The associations must also be analyzed in different genetic modes: dominant, recessive, allelic frequency, and genotypic distribution. The systematic application of Bonferroni corrections is still controversial: confirmation in other cohorts and a biological explanation for the identified association remain the best proofs of its significance.28

27.3.3 CANDIDATE GENES Up to now, the approach for genetic association studies is a candidate-gene approach: if an association between a gene allele and a specific pattern of progression (phenotype) is identified, it suggests that the gene (or its product) is involved in disease development. In HIV-1 infection, the initial studies performed in the 1990s have dealt mainly with the human leukocyte antigen complex (HLA).29 Since the identification of chemokines as inhibitors of HIV-1 infection in 199530 and the discovery of chemokine receptors as HIV-1 coreceptors in 1996,31 the genes of the chemokine system have been subjected to intense scrutiny.32,33 In the following sections, we will describe the results obtained on the chemoattractant cytokine — i.e. chemokine genes and more generally on the cytokine genes. They indeed constitute priority candidate genes due to the role of the chemokine system for viral entry and the role of cytokines in the regulation of the immune system.

27.4 POLYMORPHISMS OF THE CHEMOKINE SYSTEM GENES 27.4.1 THE CCR5 GENE 27.4.1.1

Structure of the CCR5 Gene and Polymorphisms

The CC chemokine receptor 5 (CCR5) gene, spanning 6 kb on human chromosome 3p21, has been the most studied gene by researchers working on HIV infection. The three exons are coding for a seven-transmembrane G protein-coupled cellular receptor, which binds the CC chemokines macrophage inflammatory protein-1a and -1b (MIP-1a and MIP-1b, respectively) and RANTES (regulated on activation, normal T cell expressed and secreted).34–36 CCR5, like several human chemokine and chemoattractant receptors, has an alternative splicing in the 50 UTR.37 The transcripts are initiated from two distinct promoters: a weak promoter in leukocytic cells, called upstream promoter (PU) located upstream of exon 1, and a strong constitutive promoter called downstream promoter (PD) which corresponds to the region between exons 1 and 2. Thirteen SNPs within the 50 upstream regulatory region of the human CCR5 gene have been described:
2733 A/G,
2554 G/T,
2459 G/A,
2150 A/G,
2136 C/A,
2135 T/C,
2132 C/T,
2115 C/A,
2086 A/G,
2078 T/C,
2048 C/G,
1951 G/A,
1835 C/T (positions relative to the translational start site).38–41 By performing an EMSA, Bream et al. showed no difference in binding for the variants at three sites (
2459,
2135, and
2086). However, the T-bearing oligonucleotide at site
2554 displayed 5- to 12-fold greater binding to specific nuclear proteins (or proteins) than the G-bearing oligonucleotide did.42 A 32-pb deletion (CCR5
32) in exon 3 (rs333), causing a frameshift at amino acid 185, encodes a truncated and nonfunctional protein both as chemokine receptor and HIV-1 coreceptor.43–45 The frequency of CCR5-
32 is 10% in people of European descent and null (or very low) in sub-Saharan Africa and eastern Asian populations, suggesting a recent origin of this mutation.46

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AIDS

27.4.1.2

Genetic Associations in AIDS

The first publications demonstrating the major role of CCR5 as HIV-1 co-receptor in AIDS came out in 1996.44,45 They showed in longitudinal cohorts that subjects heterozygous for the CCR5-
32 progress more slowly towards AIDS than subjects homozygous for the wild-type. In the heterozygous state, the CCR5-
32 allele is not protective against HIV-1 transmission, but confers a delay in time-to-death of 2–4 years following seroconversion, suggesting that the maximal protective effect is exerted in the earlier years of infection.45,47–50 In 1996, Liu et al. also showed that subjects homozygous for the
32 allele were resistant to HIV-1 infection: the comparison between uninfected highly exposed subjects with infected subjects revealed a higher occurrence of
32 homozygous individuals in the first group.43 However, the protective effect is strong but not absolute since infected subjects homozygous for CCR5-
32 have been identified.51–56 All these results confirm the major role of CCR5 as a primary coreceptor for HIV-1 infection. In 1998, studies were published on polymorphisms located in the promoter of CCR5: McDermott et al.39 and Martin et al.38 showed respectively that the presence of
2459A/A (rs1799987) or the double haplotype P1/P1 (with P1 being:
2554G,
2150A,
2136C,
2135C,
2132C,
2115C,
2086A,
2078T,
2048C,
1951G) were associated with accelerated AIDS progression. Complete linkage disequilibrium between
2459A and the P1 haplotype has been confirmed in African-Americans and Caucasians.57 McDermott et al. showed that the infected individuals
2459 G/G have a slower (on average 3.8 years) disease progression compared with A-homozygotes. The analysis of the promoter activity reveals that the G allele has 45% lower activity than the A allele, suggesting that the mechanism of action of the variant at position
2459 is the differential regulation of CCR5 gene transcription.39 The effect of the
2459G/P1 haplotype has been confirmed in other cohorts as being dominant.57–60 Other CCR5 promoter polymorphisms seem to play a role in AIDS. Mummidi et al. demonstrated that individuals with a
1835T allele (rs1800024) progress to AIDS or death more slowly than individuals homozygous for the
1835C allele.40 A study performed on SNP
2086A/G (rs1800023) show that female sex workers from northern Thailand tended to have higher frequency of G-homozygotes compared with controls.61 More than 30 rare natural CCR5 variations (maximum frequency of the minor allele reaching 1%) in the coding region have been characterized and appear to be relatively specific to various ethnicities.62–67 For instance, the variant at position 303 (rs1800560) introduces a premature stop codon and the final product of the CCR5 m303 mutant is a truncated protein without any coreceptor function, conferring resistance to HIV-1 infection when associated to the CCR5-
32 mutant gene.68 The putative m303 homozygosity and its association with the CCR5-
32 allele could account for unexplained cases of resistance to HIV-1 infection in individuals who are apparently wild-type or heterozygous for the
32 allele.68 27.4.1.3

Biological Interpretation of the Associations

Compared with CCR5 þ/þ individuals, heterozygotes CCR5-
32/þ present a reduction in the rate of CD4þ T-cell decline and in viral load,48 which are linked with a decrease of the level of CCR5 expression on CD4þ T lymphocytes.69 Salkowitz et al. also observed a lower CCR5 density on stimulated CD14þ monocytes from healthy Caucasian blood donors with the
2459 G/G and A/G genotypes compared to A/A genotypes.70 The Langerhans cells isolated from individuals with one or two
2459G allele (s) tend to be less susceptible to infection by R5 HIV-1 strains than those from individuals who are homozygous for
2459A.71 Overall, the patients exhibiting low CCR5 expression exhibit a lower viral load and progress more slowly to AIDS.72

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Cytokine Gene Polymorphisms in Multifactorial Conditions

27.4.2 CCR2 GENE POLYMORPHISMS 27.4.2.1

Structure of the CCR2 Gene and Polymorphisms

CC-chemokine receptor 2 (CCR2) mediates in vitro responses to macrophage inflammatory protein (MIP)-173 and acts as an additional coreceptor during cellular infection of some HIV-1 strains.74 The human CCR2 gene, spanning 6.8 kb, contains three exons and it has been mapped on chromosome 3p21–22. There are 13 published SNPs75,76 in the gene and their positions numbered relative to ATG and according to Genbank accession number NT_079509.1 are:
108 A/G (intron 1),
94 G/A (intron 1), 156 G/T (V52V), 189 C/T (V63V), 190 G/A (V64I), 669 G/A (S223S), 698 G/A (R233Q), 780 C/T (N260N), 849 G/T (L283L), 860 C/T (T287M), 2225 A/G (P339P), 1044 G/A (T348T), 2272 G/A (G355E). 27.4.2.2

Associations with AIDS

In 1997, Smith et al. showed that the replacement of valine by isoleucine at position 64 (rs1799864) in the first transmembrane domain of the chemokine receptor CCR2 was strongly associated with a delay (2–4 years) in the onset of AIDS progression for homozygotes (CCR2-64I/64I) and heterozygotes (CCR2-64V/64I), but has no effect on HIV-1 transmission.76 This delaying effect of CCR2-64I has been confirmed by several independent cohort studies (reviewed in Ref. 33 and meta-analyses27,77). The effect of CCR264I appears to be weaker in the transversal GRIV cohort than the one observed in the longitudinal cohorts.50,59 Since the GRIV cohort is prone to show early effects on disease progression, this suggests that CCR2-64I might play a role at a later stage of disease. It seems indeed that CCR5-
32 and CCR2-64I have independent and potent additive effects on delaying AIDS.76 Unlike CCR5-
32 which is present only among Caucasians, CCR2-64I variant frequency is 10% in Caucasians, 15% in African-Americans, 17% in Hispanics, and reaches 25% in Asians and the association could be confirmed in various ethnicities. 27.4.2.3

Biological Interpretation

The carriers of the CCR2-64I allele have a slower CD4þ lymphocyte decline and a lower RNA virus load, suggesting that the mechanism of action of CCR2-64I is mediated through CCR5.78 The mechanism by which the CCR2-64I allele exerts a protective effect in HIV-1 progression in vivo is still not clear but Nakayama et al. reported that CCR2 has the ability to bind CCR5 in the cytoplasm and therefore down-modulates its surface expression. This differential ability to modulate CCR5 expression could explain the delay in HIV-1 disease progression in patients with CCR2-64I allele.79 27.4.2.4

The CCR2/CCR5 Locus

Human CCR5 and CCR2 chemokine receptor genes are separated by only 20 kb on chromosome 3p21–22 and are tightly linked. Both alleles CCR2-64I and CCR5-
32 are in complete linkage disequilibrium with the wild-type promoter CCR5-P1, but they are never together on the same haplotype. Overall there are four major haplotypes: (þ/not P1/þ), (þ/P1/þ), (þ/P1/
32), and (64I/P1/þ) in Caucasians. From the analysis of the transversal GRIV cohort, it appears that the accelerating effect of CCR5-P1 is weaker than the protective effect of CCR5-
32 against rapid progression.59

27.4.3 RANTES GENE POLYMORPHISMS Among the three natural CCR5 ligands, RANTES showed the highest potency to suppress in vitro replication of R5 strains.30 Among the PBMCs of different individuals,

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AIDS

RANTES secretion levels vary widely and are inversely correlated with the rate of disease progression.80,81 The human RANTES gene, spanning 8.8 kb, contains three exons and has been mapped on chromosome 17q11.2–q12. A Japanese study identified two SNPs in the promoter region (
403 G/A and
28 C/G relative to the major transcription start, respectively rs2107538 and rs2280788) and demonstrated that the haplotype
403A/
28G is associated, in a dominant manner, with reduced CD4þ cell depletion rates. Although RANTES levels varied greatly among subjects, the CD4þ lymphocytes from individuals with haplotype
403A/
28G secreted significantly more RANTES than those from individuals without this haplotype.82 Moreover, the
403A and
28G alleles were shown to increase promoter activity suggesting that the increased RANTES expression within HIV-1 infected patients helps prevent viral spread and disease progression.82,83 McDermott et al. showed that the RANTES
403A allele is a risk factor for acquiring HIV-1 but may be protective in progression.84 Since the haplotype
403A/
28G is not frequent in non-Far East Asians, the contribution of this haplotype to HIV-1 world epidemiology appears limited.85 Five additional polymorphisms (
109 T/C,
105 C/T, In1.1 T/C, In1.2 G/ A, 30 222 T/C) have been identified in another study demonstrating that In1.1C is associated in a dominant model with an accelerated HIV-1 disease progression in both EuropeanAmerican and African-American patients.83 It appears that In1.1 alleles differentially bind nuclear proteins and have a powerful regulatory activity on gene expression. Therefore, the diminished transcription of RANTES induced by In1.1C allele could be consistent with increased HIV-1 spread in vivo, leading to accelerated progression to AIDS. The polymorphisms
28G,
403A, In1.1C and 30 222C are in strong LD and both
28G and In1.1C always occur on a
403A-bearing haplotype. It is thus difficult to separate the independent effects of the four variants. Recently, it has been demonstrated that the patients homozygous for the RANTES R1 haplotype, carrying the most frequent allele at the four positions, present lower initial HIV-1 plasma RNA.86 All these studies confirm the association of RANTES variants with accelerated disease progression to AIDS.

27.4.4 OTHER POLYMORPHISMS GENES

IN THE

CHEMOKINE

The human gene for CXCR6, a G-coupled seven-transmembrane receptor and putative coreceptor for HIV-1, spans over 4.9 kb on chromosome 3p21.31 and contains two exons. Duggal et al. studied a nonsynonymous G/A mutation (E3K and rs2234355) frequent among African-Americans but rare among Caucasians.87 This study demonstrated that CXCR6-3K homozygosity increases the length of time from initial AIDS diagnosis of Pneumocystis carinii pneumonia to death in an African-American cohort, suggesting that CXCR6 might play a role in late-stage HIV-1 infection.87 CX3CR1, or chemokine (C-X3-C motif) receptor 1 is the leukocyte chemotactic/adhesion receptor for fractalkine (particularly expressed in the brain) and has been identified as a putative HIV-1 coreceptor in vitro.88 Human CX3CR1 gene, spanning 16.5 kb, contains two exons and has been mapped on chromosome 3p21. A study in the longitudinal SEROCO cohort suggested a faster progression to clinical AIDS for CX3CR1-M280 homozygotes compared with CX3CR1-T280 homozygotes (rs3732378).89 This association has not been confirmed in three other large scale studies90–92 suggesting that it is likely a cohort artifact. Indeed the p-value for the association was rather weak (p ¼ 0.03) and the number of patients homozygous for the M280 allele is rather low (n ¼ 16 out of 426 patients). Stromal cell-derived factor-1 (SDF-1) is considered to be the only known natural CXCR4 ligand. Human SDF-1 gene, spanning 14.9 kb, contains four exons and has been mapped on chromosome 10q11. Winkler et al. identified a G/A SNP at position 801 (relative to the translational start site-rs1801157)) in the 30 untranslated region (30 UTR).93

402

Cytokine Gene Polymorphisms in Multifactorial Conditions

Homozygosity for the SDF1-30 A allele in a longitudinal cohort, which occurs at a frequency of 6%, has been reported to slow disease progression.93 This association was not confirmed in other AIDS cohorts27,40,94–97 and might be due to a cohort bias. Unlike the CX3CR1 study, the p-value observed in the initial SDF-1 30 A study was very low (p ¼ 0.001). However, the number of patients homozygous for SDF-1 30 A was also rather low (n ¼ 32 out of 639 patients). The previous observations on CX3CR1 and SDF-1 polymorphisms suggest that a large enough number of subjects with a given genotype is necessary in order to assess with certainty an association in longitudinal cohorts.

27.5 POLYMORPHISMS IN CYTOKINES GENES 27.5.1 Th1–Th2 CYTOKINE GENE POLYMORPHISMS Although many hypotheses have been presented to explain the molecular mechanisms leading to CD4þ cell depletion in AIDS,98 the most conclusive and reproducible observations involve the dysbalance of cytokines and in particular the so-called Th1/Th2 shift (for a review, see Ref. 99). Thus, genetic studies of cytokines are of particular relevance in HIV-1 infection. Vasilescu et al. performed a systematic genetic study by resequencing the coding regions and promoters of eight Th1–Th2 cytokine genes, IL-2, IL-4, IL-6, IL-10, IL-12 p35 and p40, IL13, and IFN-g.100 The study leads to the identification of 64 SNPs and four deletions with frequency 41% (Figure 27.1) and significant associations were observed with haplotypes of the IL4 and IL10 genes. It confirmed the previously reported association of the IL4
589T allele (rs2243250) with slower progression to AIDS.101 The
589 T/C polymorphism affects the IL-4 transcription,102 the T allele shows greater binding to nuclear transcription factors than the C allele and an alteration in EMSA was observed with the T allele.103,104 Nakashima et al. demonstrated that the haplotype
589C,
33C, and B2 (a three tandem repeat in the third intron) presents a lower IL-4 production than the
589T,
33T, and B1 (two tandem repeats).105 IL-4 displays both stimulatory and inhibitory effects on HIV-1 replication (depending of the state of maturation of monocyte into macrophage), and its secretion was associated with HIV-1 infection (by differentially regulating the expression of CCR5 and CXCR4).106 Vasilescu et al. confirmed the association of IL-10 promoter
592 C/C genotype (rs1800872) with an unfavorable clinical outcome,107 but it did not confirm the association identified by Shin et al. who found an opposite effect of IL-10
592C/C on HIV-1 infection.108 IL-10
592A has a differential promoter allele affinity for transcription factors and is associated with a decrease in transcription and production of IL-10.108 More studies are thus needed to elucidate the effect of IL-10 polymorphisms on AIDS progression. Finally, the study of Vasilescu et al. is consistent with the one of Bream et al. that failed to identify any significant association between IFN-g polymorphisms and AIDS.109

27.5.2 TNFa GENE POLYMORPHISMS Tumor necrosis factor alpha (TNFa) is a cytokine with cytotoxic and antitumor activity and plays key roles in inflammation and protective immune responses against intracellular pathogens. In HIV infection, elevated TNFa levels have been observed throughout all stages of infection.110 The excessive TNFa expression may accelerate the apoptosis of infected and uninfected lymphocytes, thus decreasing the CD4þ subset and favoring disease progression. The human TNFa is mapped to locus 6p21.3 in the class III region of HLA, 250 kb centromeric to HLA-B (class I), and 850 kb telomeric to HLA-DR (class II). Studies have dealt with the analysis of four G/A SNPs (
376,
308,
238, and
163 relative

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403

FIGURE 27.1 Organization of the IL-2, IL-4, IL-6, IL-10, IL-12p35, IL-12p40, IL-13, and IFN-g genes investigated in the French GRIV cohort. SNPs with a minor allele frequency 41% are shown. Coding and untranslated regions are respectively indicated by solid and open rectangles. SNP positions and regions that have been sequenced (horizontal lines) are according to the first nucleotide of the initiation codon as þ1 (indicated by a black triangle). The genomic sequences used for alignment are IL-2 (NT_022960.5), IL-4 (NT_007072.7), IL-6 (NT_025766.6), IL-10 (NT_029217.3), IL-12p35 (NT_005818.7), IL-12p40 (NT_007006.7), IL-13 (NT_007072.9), and IFN-g (NT_029419.2).

404

Cytokine Gene Polymorphisms in Multifactorial Conditions

to the transcription initiation site) of the promoter region of the TNFa gene in AIDS and yielded conflicting results reviewed by Carrington et al.111 The effects of TNFa polymorphisms on onset/progression to AIDS remain thus unclear.

27.5.3 CYTOKINE RECEPTOR GENE POLYMORPHISMS The cytokine receptors are usually constituted by an alpha subunit, essential for the binding of the cytokine, and a beta subunit required for the intracellular signal transduction.112 Only one study has been published on the role of the polymorphism of cytokine receptors in AIDS: Wang et al. analyzed an A/G SNP of the IL-4Ra gene (rs1801275) that introduces a Q576R mutation in the protein.113 The study demonstrates that A/A homozygotes present a diminished susceptibility to HIV-1 infection in African-American population but the results did not fit with Hardy–Weinberg expectations. Recently, Do et al.114 performed a study on four cytokine receptor genes, namely IL-2Ra, IL-4Ra, IL-10Ra, and IFN-gR1 in the GRIV cohort composed of French rapid and slow progressors. The coding regions and promoters of these genes were resequenced and the identified polymorphisms were evaluated for their association with disease. They identified 104 SNPs and four deletions with a frequency 41% (Figure 27.2) and all polymorphisms fit with Hardy–Weinberg expectations. Three haplotypes — one estimated with the ten polymorphisms of IL-2Ra with a frequency 410% and two estimated with the four polymorphisms located in the promoter region of IL-4Ra — exhibited positive signals after Bonferroni corrections. These haplotypes, with rather weak associations with AIDS, were not correlated to a particular SNP. No biological explanation could be drawn yet to explain these associations. The GRIV study failed to confirm the observed effect of IL-4Ra_rs1801275 observed by Wang et al.113 but this is explained by the difference in the ethnical background between the two cohorts.

27.6 CONCLUSION With an estimated 40 million people carrying the virus, AIDS is one of the most serious infectious diseases to have affected humankind. Pharmacogenomic studies should be of help to better understand the molecular mechanisms of HIV-1 pathogenesis and as a consequence, allow the rational design of new prophylactic and therapeutic strategies. The initial genomic studies in AIDS had focused on HLA gene polymorphisms, and when the role of the chemokine receptors for HIV-1 entry was discovered, studies shifted to the polymorphisms of their genes. More recently, cytokine genes have started to be investigated due to their major role in the regulation of the immune response. The most striking results to date deal with the CCR5 polymorphisms (CCR5-
32 and CCR5-P1) which explain why some subjects exhibit a resistance to HIV-1 infection. Other polymorphisms have been associated with disease progression in the CCR2 and RANTES genes. These results emphasize the relevance of drugs targeting viral entry in AIDS. Beside the chemokine system, cytokine and cytokine receptor genes have been less studied. However, independent studies suggest that IL-4 and IL-10 gene polymorphisms can affect AIDS onset and progression. Table 27.1 summarizes the results obtained by the main studies for all these candidate genes: many still need confirmation in other cohorts and/or a biological explanation for the effect of the polymorphism. These genomic studies are of interest not only for AIDS but for other immune-related diseases. They also point out putative functional properties of polymorphisms (for instance the over-expression of a gene associated with a promoter SNP). Indeed, the functional properties linked to the polymorphisms in CCR5 or CCR2 (CCR5-
32, CCR5-P1, CCR264I), IL-4 (
589 T/C), and IL-10 (
592 C/A) were studied after finding their genetic association with AIDS. Reciprocally, promoter polymorphisms with reported functional

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405

FIGURE 27.2 Organization of the IL-2Ra, IL-4Ra, IL-10Ra, and IFN-gR1 genes investigated in the French GRIV cohort. SNPs with a minor allele frequency 41% are shown. Coding and untranslated regions are respectively indicated by solid and open rectangles. SNP positions and regions that have been sequenced (horizontal lines) are according to the first nucleotide of the initiation codon as þ1 (indicated by a black triangle). The genomic sequences used for alignment are IL-2Ra (NT_077569.2), IL-4Ra (NT_010393.15), IL-10Ra (NT_033899.7), and IFN-gR1 (NT_025741.13).

properties in IL-13,115 IFN-g,109 and IFN-gR1116,117 have not been yet associated with an AIDS progression pattern. It has been estimated that more than 90% of the genetic and non-genetic influence on AIDS progression in people infected with HIV-1 is still undiscovered.118 More genomic work has thus to be performed to unravel AIDS molecular mechanisms, and cytokines remain good candidate genes. The future directions of research include the confirmation of the associations already described, their biological interpretation, and the discovery of new

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Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 27.1 Associations between Cytokine Polymorphisms and HIV-1 Infection Gene

Genotype

Effect on AIDS progression

Status*

CCR5


2459A/A or P1/P1
32/
32
32/þ
1835T/T or
1835T/C 64I/64I or 64V/64I haplotype
403A/
28G|
403A/
28G In1.1C/C or In1.1 T/C 3K/3K M280/M280 30 A/30 A
589T/T haplotype H2
592 C/C
592 C/C haplotype H4 haplotype H10 Haplotype H7 Promoter haplotype H1 Promoter haplotype H2

Accelerate Partial resistance to HIV-1 Slow down Slow down Slow down Slow down

Confirmed Confirmed Confirmed To be confirmed Confirmed Confirmed

38, 44, 45, 40 27, 82

Accelerate Slow down Accelerate Slow down Slow down Accelerate Accelerate Slow down Accelerate Slow down Accelerate Slow down Accelerate

To be confirmed To be confirmed Infirmed Infirmed Confirmed To be confirmed To be confirmed To be confirmed To be confirmed To be confirmed To be confirmed To be confirmed To be confirmed

83 87 89 93 100,101 100 100,107 108 100 100 114 114 114

CCR2 RANTES

CXCR6 CX3CR1 SDF-1 IL4 IL10

IL2Ra IL4Ra

References

39, 57 45, 48, 49 47, 48, 49, 50 77

*The status of an association is confirmed if two or more studies identified it, is infirmed by three or more studies, needs to be confirmed if less than two studies have been performed.

associations on genes not yet studied. Since cytokines act as a complex network of interactive proteins, it might also be necessary to depict more complex patterns of polymorphisms involving groups of cytokines/receptors such as the primitive Th1/Th2 groups.

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36. Raport, C. J. et al., Molecular cloning and functional characterization of a novel human CC chemokine receptor (CCR5) for RANTES, MIP-1beta, and MIP-1alpha, J. Biol. Chem., 271, 17161, 1996. 37. Mummidi, S. et al., The human CC chemokine receptor 5 (CCR5) gene. Multiple transcripts with 50 -end heterogeneity, dual promoter usage, and evidence for polymorphisms within the regulatory regions and noncoding exons, J. Biol. Chem., 272, 30662, 1997. 38. Martin, M. P. et al., Genetic acceleration of AIDS progression by a promoter variant of CCR5, Science, 282, 1907, 1998. 39. McDermott, D. H. et al., CCR5 promoter polymorphism and HIV-1 disease progression. Multicenter AIDS Cohort Study (MACS), Lancet, 352, 866, 1998. 40. Mummidi, S. et al., Genealogy of the CCR5 locus and chemokine system gene variants associated with altered rates of HIV-1 disease progression, Nat. Med., 4, 786, 1998. 41. Kostrikis, L. G. et al., A chemokine receptor CCR2 allele delays HIV-1 disease progression and is associated with a CCR5 promoter mutation, Nat. Med., 4, 350, 1998. 42. Bream, J. H. et al., CCR5 promoter alleles and specific DNA binding factors, Science, 284, 223, 1999. 43. Liu, R. et al., Homozygous defect in HIV-1 coreceptor accounts for resistance of some multiply-exposed individuals to HIV-1 infection, Cell, 86, 367, 1996. 44. Samson, M. et al., Resistance to HIV-1 infection in caucasian individuals bearing mutant alleles of the CCR-5 chemokine receptor gene, Nature, 382, 722, 1996. 45. Dean, M. et al., Genetic restriction of HIV-1 infection and progression to AIDS by a deletion allele of the CKR5 structural gene. Hemophilia Growth and Development Study, Multicenter AIDS Cohort Study, Multicenter Hemophilia Cohort Study, San Francisco City Cohort, ALIVE Study, Science, 273, 1856, 1996. 46. Martinson, J. J. et al., Global distribution of the CCR5 gene 32-basepair deletion, Nat. Genet., 16, 100, 1997. 47. Rappaport, J. et al., 32 bp CCR-5 gene deletion and resistance to fast progression in HIV-1 infected heterozygotes, Lancet, 349, 922, 1997. 48. Huang, Y. et al., The role of a mutant CCR5 allele in HIV-1 transmission and disease progression, Nat. Med., 2, 1240, 1996. 49. Zimmerman, P. A. et al., Inherited resistance to HIV-1 conferred by an inactivating mutation in CC chemokine receptor 5: studies in populations with contrasting clinical phenotypes, defined racial background, and quantified risk, Mol. Med., 3, 23, 1997. 50. Hendel, H. et al., Distinctive effects of CCR5, CCR2, and SDF1 genetic polymorphisms in AIDS progression, J. Acquir. Immune Defic. Syndr. Hum. Retrovirol., 19, 381, 1998. 51. Balotta, C. et al., Homozygous delta 32 deletion of the CCR-5 chemokine receptor gene in an HIV-1-infected patient, Aids, 11, F67, 1997. 52. Biti, R. et al., HIV-1 infection in an individual homozygous for the CCR5 deletion allele, Nat. Med., 3, 252, 1997. 53. Heiken, H. et al., HIV-1 infection in a heterosexual man homozygous for CCR-5 delta32, Aids, 13, 529, 1999. 54. Kuipers, H. et al., An HIV-1-infected individual homozygous for the CCR-5 delta32 allele and the SDF-1 30 A allele, Aids, 13, 433, 1999. 55. Sheppard, H. W. et al., HIV-1 infection in individuals with the CCR5-Delta32/Delta32 genotype: acquisition of syncytium-inducing virus at seroconversion, J. Acquir. Immune Defic. Syndr., 29, 307, 2002. 56. Theodorou, I. et al., HIV-1 infection in an individual homozygous for CCR5 delta 32, Seroco Study Group, Lancet, 349, 1219, 1997. 57. An, P. et al., Influence of CCR5 promoter haplotypes on AIDS progression in AfricanAmericans, Aids, 14, 2117, 2000. 58. Clegg, A. O. et al., CCR5 promoter polymorphisms, CCR5 59029A and CCR5 59353C, are under represented in HIV-1-infected long-term non-progressors, The Australian Long-Term Non-Progressor Study Group, Aids, 14, 103, 2000. 59. Winkler, C. A. et al., Dominant Effects of CCR2-CCR5 Haplotypes in HIV-1 Disease Progression, J. Acquir. Immune Defic. Syndr., 37, 1534, 2004.

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84. McDermott, D. H. et al., Chemokine RANTES promoter polymorphism affects risk of both HIV infection and disease progression in the Multicenter AIDS Cohort Study, Aids, 14, 2671, 2000. 85. Gonzalez, E. et al., Global survey of genetic variation in CCR5, RANTES, and MIP-1alpha: impact on the epidemiology of the HIV-1 pandemic, Proc. Natl. Acad. Sci. USA, 98, 5199, 2001. 86. Duggal, P. et al., The Effect of RANTES Chemokine Genetic Variants on Early HIV-1 Plasma RNA Among African American Injection Drug Users, J. Acquir. Immune Defic. Syndr., 38, 584, 2005. 87. Duggal, P. et al., Genetic influence of CXCR6 chemokine receptor alleles on PCP-mediated AIDS progression among African Americans, Genes Immun., 4, 245, 2003. 88. Rucker, J. et al., Utilization of chemokine receptors, orphan receptors, and herpesvirusencoded receptors by diverse human and simian immunodeficiency viruses, J. Virol., 71, 8999, 1997. 89. Faure, S. et al., Rapid progression to AIDS in HIVþ individuals with a structural variant of the chemokine receptor CX3CR1, Science, 287, 2274, 2000. 90. Kwa, D., Boeser-Nunnink, B., and Schuitemaker, H., Lack of evidence for an association between a polymorphism in CX3CR1 and the clinical course of HIV infection or virus phenotype evolution, Aids, 17, 759, 2003. 91. Hendel, H. et al., Validation of genetic case-control studies in AIDS and application to the CX3CR1 polymorphism, J. Acquir. Immune Defic. Syndr., 26, 507, 2001. 92. McDermott, D. H. et al., Genetic polymorphism in CX3CR1 and risk of HIV disease, Science, 290, 2031, 2000. 93. Winkler, C. et al., Genetic restriction of AIDS pathogenesis by an SDF-1 chemokine gene variant. ALIVE Study, Hemophilia Growth and Development Study (HGDS), Multicenter AIDS Cohort Study (MACS), Multicenter Hemophilia Cohort Study (MHCS), San Francisco City Cohort (SFCC), Science, 279, 389, 1998. 94. van Rij, R. P. et al., The role of a stromal cell-derived factor-1 chemokine gene variant in the clinical course of HIV-1 infection, Aids, 12, F85, 1998. 95. Meyer, L. et al., CC-chemokine receptor variants, SDF-1 polymorphism, and disease progression in 720 HIV-infected patients. SEROCO Cohort. Amsterdam Cohort Studies on AIDS, Aids, 13, 624, 1999. 96. Magierowska, M. et al., Combined genotypes of CCR5, CCR2, SDF1, and HLA genes can predict the long-term nonprogressor status in human immunodeficiency virus-1-infected individuals, Blood, 93, 936, 1999. 97. Brambilla, A. et al., Shorter survival of SDF1-30 A/30 A homozygotes linked to CD4þ T cell decrease in advanced human immunodeficiency virus type 1 infection, J. Infect. Dis., 182, 311, 2000. 98. McCune, J. M., The dynamics of CD4þ T-cell depletion in HIV disease, Nature, 410, 974, 2001. 99. Becker, Y., The changes in the T helper 1 (Th1) and T helper 2 (Th2) cytokine balance during HIV-1 infection are indicative of an allergic response to viral proteins that may be reversed by Th2 cytokine inhibitors and immune response modifiers — a review and hypothesis, Virus Genes, 28, 5, 2004. 100. Vasilescu, A. et al., Genomic analysis of Th1-Th2 cytokine genes in an AIDS cohort: identification of IL4 and IL10 haplotypes associated with the disease progression, Genes Immun., 4, 441, 2003. 101. Nakayama, E. E. et al., Protective effect of interleukin-4
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28

Tropical Infectious Diseases Thereza Quirico-Santos, Alda Maria Da-Cruz, Claire Fernandez Kubelka, Joseli Lannes-Vieira, and Milton Ozo´rio Moraes

CONTENTS 28.1 28.2 28.3

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Viral Hemorrhagic Fevers (VHF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Protozoan Diseases: Leishmaniasis and Chagas Disease . . . . . . . . . . . . . . . . . . . . . . . . 28.3.1 Leishmaniasis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.3.2 Chagas Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.4 Mycobacterial Diseases: Leprosy and Tuberculosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

413 414 416 416 417 419 424 424

28.1 INTRODUCTION Numerous host proteins recognize structures or molecular patterns present on foreign organisms,1 though progression of infection and clinical outcome is dependent upon environmental factors (nutritional status, previous vaccination, and exposition to environmental pathogens) and genetic background of either the pathogen or host. It is estimated that susceptibility to infectious diseases is a phenomenon that occurs in a small percentage of the exposed population. Moreover, diseases usually present different clinical patterns and exhibit mild or severe states, such as tuberculoid or lepromatous forms of leprosy; mild or hemorrhagic forms of Dengue fever; cutaneous or visceral forms of Leishmaniasis; asymptomatic or cardiomyopathic forms of Chagas disease or even pleuritic and pulmonary forms of tuberculosis. Differences in clinical patterns may indicate the influence of environmental and genetic factors in the susceptibility to infectious diseases. In fact, in both leprosy and tuberculosis, monozygotic twins are significantly more often disease and disease-type concordant than dizygotic twins, and familial clustering has been reported in leishmaniasis and leprosy.2,3 Furthermore, for several infectious diseases, such as malaria, leprosy, tuberculosis, and leishmaniasis, it has been observed that, in an endemic area with similar exposure to the infectious agent, prevalence rates are associated to distinct ethnic groups.2–5 Vaccination with Mycobacterium bovis Bacille Calmette-Guerin (BCG) can confer protection to either leprosy or tuberculosis, although it is not effective in all populations. Finally, complex segregation analyses, candidate-gene approaches, and genome wide scans have all provided evidence for various genetic associations and linkages in infectious diseases, clearly suggesting that genetics contribute to the outcome of these diseases. The capacity of the immune system to mount defensive reactions against unanticipated pathogens is related to the presence of clonally distributed receptors capable of recognizing a multitude of antigens.6,7 Pathogens, however, often trigger polarized T Helper-1 (TH1)/ T Helper-2 (TH2) immune responses for evading host immunity and protecting their niche 413

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from the inflammatory response.8 Therefore, resistance to certain intracellular protozoa depends on the ability of certain cytokines, such as interleukin (IL)-12, to promote development and expansion of CD4þ TH1 cells that produce IFNg, which in turn activates macrophages. On the other hand, susceptibility to infection is characterized by the presence of a CD4þ TH2 T-cell response and the production of IL-4, IL-10, and IL-13 cytokines.6 In parallel, activation of anti-inflammatory circuits protect against pathological effects of infections, preventing tissue damage.9 Thus, among the different immunological and inflammatory pathways that likely participate in the susceptibility/resistance to infections, the cross-talk between host and pathogen always involves cytokines that seem to be key mediators in inducing protective immune responses against infections, firstly through innate and later through adaptive responses. One of the indications of this in humans is the immunosuppressive effect of AIDS/HIV that favors the outcome of tuberculosis, probably due to the decrease in CD4þ T cells and the low levels of T cell-derived cytokines.8,10,11 Furthermore, HIV-leishmaniasis co-infection suggests that the parasite induces HIV replication, which is associated with increased severity in co-infected patients.10,11 On the contrary, the absence of peripheral T cell responsiveness does not account for severity or reactivation in leprosy.12 Another example of the role of cytokines against intracellular pathogens is that specific chemotherapy for autoimmune conditions, such as rheumatic arthritis or Crohn’s disease using tumor necrosis factor-alpha (TNFa) blockers, have been associated with the development of either tuberculosis or leprosy in these patients.13,14 The most blatant example is observed in patients exhibiting severe infections due to weakly virulent pathogens (non-tuberculous mycobacteria, M. bovis Bacille Calmette-Gue´rin or Salmonella species). These bacterial diseases implicate the IL-12/IL-23/ interferon-gamma (IFNg) axis to resistance to intracellular pathogens. Mutations have been reported in coding regions of the following cytokine and receptor genes: IL-12/23 p40, IL-12/ 23Rb1, IFN-gR1, IFN-gR2, and STAT-1;15,16 yet, other genes such as TNFa may also play an important role. Nevertheless, these diseases have a Mendelian mode of transmission in that it is unlikely to account for genetic susceptibility to common infectious diseases. It is obvious that many genes and genetic polymorphisms are involved in controlling signaling pathways critical to host resistance, disease susceptibility, and severity in these common infectious diseases.17 However, variations associated to these complex traits are subtle when compared to mutations in the type-1 cytokine axis leading to severe infections. Thus, common single nucleotide polymorphisms (SNPs) in promoter or even coding regions of cytokine genes that mildly regulate the production or activity of these proteins are very strong candidates that may influence the outcome and development of these pathologies.18,19 We herein will briefly introduce the immunological and clinical aspects of tuberculosis, leprosy, leishmaniasis, Chagas disease, and viral hemorrhagical fever (VHF) and further review recent data concerning the influence of cytokine gene polymorphisms and their association to disease outcome and/or severity. Most of the data gathered from studies with polymorphisms in infectious diseases describe frequency of cytokine SNPs in case-control studies, but family-based designs have also been reported. Most cytokine variations studied are non-coding and specifically located in the promoter region. The most characterized regions are related to TNFa and IL-10 loci that are good representatives of the paradigm between genes that modulate protective versus susceptible responses.

28.2 VIRAL HEMORRHAGIC FEVERS (VHF) Hemorrhagic fever may be caused by a group of viruses usually transmitted by vectors, rodents, or arthropods and is mostly of tropical incidence. Although VHF present diversity in etiology and severity, similar clinical symptoms and pathological mechanisms are

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observed. Among the most well known are yellow fever and dengue from the Flaviviridae family, Ebola and Marburg (Filoviruses) and Hantavirus (Bunyaviridae).20–22 The main clinical features related to severity, hemorrhagic manifestations, and shock syndrome are associated with vascular permeability and leakage and cytokines play a key role in the generation of these processes. It is likely that the vascular endothelium is directly or indirectly affected by the viral infection resulting in vascular lesions.20,21 Ebola and Marburg viruses represent the most severe hemorrhagic fevers with intense hemorrhage, rapid death, and high mortality rates reaching up to 88% death rates.23 Yellow fever causes systemic mild symptoms before recovery in most patients. About 15% of patients enter a toxic phase developing jaundice, abdominal pain, vomiting, bleeding, and renal failure. Half of these severe patients die and others recover completely.24 The occurrence of rare fatal cases of hemorrhagic fever has been associated with the yellow fever vaccine.25,26 Dengue disease is the most important arthropod-borne emerging viral disease in tropical countries presenting high morbidity and increased risk of mortality.27 Genetic and antigenic variations of viral strains may also lead to differences in the severity of the disease.28,29 Asymptomatic or oligosymptomatic infections were detected in 56% of the school children in a Brazilian population.30 In Haiti, the absence of DHF cases is associated with dengue resistance among Haitians of African descent.31 VHF lesions, with the possible exception of yellow fever, are not severe enough to account for terminal shock and death of the host, yet a fulminate shock-like syndrome characterizes VHF, suggesting that inflammatory mediators play an important role in the pathogenesis. Fatal VHF is characterized by high viremia and immunosuppression.21 However, the involvement of the vascular system, particularly the endothelium, plays an important role in the outcome. Some viruses may directly target endothelial cells but an indirect effect through soluble cytokines, chemokines, and factors produced by infected mononuclear phagocytes and dendritic cells may cause endothelial dysfunction.20 Usually, viral entrance occurs through the skin by mosquito bites and small lesions, although Hantavirus is inhaled by aerosols. Viral particles are then uptaken by dendritic, Langerhans cells and/or tissue macrophages. These infected cells migrate to regional lymphoid tissues where they activate specific immune response with resultant induction and release of cytokines (e.g. TNFa, IL-6 IL1-b, IFNg, IL-10) and chemokines (IL-8, MIP-1a/CCL3, MCP-1/CCL2). Factors produced by virus-infected cells induce alterations in the endothelial cell junction organization, particularly the VE-cadherin/catenin complex.20,32,33 In addition, up-regulation of TNF receptors and adhesion molecules, PECAM-1, E- and P-Selectin, are important for cell migration through endothelium, and may cause fluid unbalance between the intravascular and extravascular space, ultimately leading to shock.20,34,35 In infections such as dengue, TNFa and IL-1b are associated with activation of coagulation and fibrinolysis.33,36 Tissue factor (TF), an early mediator in the coagulation cascade, depends on macrophage activation by TH 1 cytokines such as IFNg, whereas TH 2 cytokines IL-4, IL-10, and IL-13 suppress TF.37 These cytokine–mediated coagulation events are important for the establishment of severity. Therefore, it is clear that high cytokine levels are directly or indirectly associated to viral infection severity, especially in hemorrhagic and shock forms. In spite of the genetic variation attributed to each viral strain triggering differential immuno-inflammatory responses, it is likely that SNPs regulating the level of these cytokines could explain the inter-individual variation as well as the disease outcome. TNFa is thought to mediate this exacerbated inflammatory reaction. For instance, clinical course of Hantavirus-infected patients was more severe in individuals carrying a
308A TNFA polymorphism than in non-carriers.38 The allele frequency of TNFA
308A was increased in Venezuelan patients with Dengue hemorrhagic fever (DHF) when compared to patients with classical dengue,39 indicating that TNFA
308A carriers would be 2.5 times

416

Cytokine Gene Polymorphisms in Multifactorial Conditions

more likely to develop DHF than non-carriers. IFN-g, IL-6, TGF-b1, and IL-10, however, showed similar distributions in DF and DHF.39 On the other hand, no association has been found with polymorphisms in IL-4 and IL-1RA genes although a positive association with HLA-DQ1 suggests that variants of TNFa linked to the MHC may influence the outcome of DHF.40,41 It is conceivable that for VHF, not only virus genotype variants but also an array of host altered genes and several factors acting synergistically may be influencing the outcome of the disease. However, it is necessary to conduct further studies enroling large sample sizes to better understand the exact contribution of the host and pathogen genetics to the disease. In view of this, a study conducted in Thailand in a large cohort associated dengue susceptibility and severity to a promoter SNP in the gene for DC-SIGN, a dendritic cell receptor for Dengue virus and other pathogens.42 The unusual association was a result of the same variant allele with both protection against dengue fever and susceptibility to dengue hemorrhagic fever. The
336G variation which is associated to lower receptor expression could be involved in inefficient phagocytic function producing suitable (protective) cytokine patterns and eliminating viruses. In Dengue hemorrhagic fever, there might be an alternative entry in cells and the
336G variation is not able to prevent adverse responses.42 This data reinforces the idea that not only cytokine variations contribute to disease susceptibility and severity but also other mediators in cytokine expression pathways.

28.3 PROTOZOAN DISEASES: LEISHMANIASIS AND CHAGAS DISEASE Leishmaniasis and Chagas diseases are vector-borne complex diseases caused by Leishmania sp. and Trypanosoma cruzi protozoan parasites, respectively, and are highly prevalent in tropical regions. In both diseases, the clinical pattern is profoundly influenced by the multiplicity of host/vector interactions and parasite strains. A broad number of Leishmania species (subdivided into subgenera Viannia or Leishmania) are associated to cutaneous leishmaniasis (CL), mucosal leishmaniasis (ML), diffuse cutaneous leishmaniasis (DCL), or visceral leishmaniasis (VL). In contrast, T. cruzi is unique in presenting distinct biological behavior and biochemical characteristics that do not predict clinical evolution to cardiac or digestive forms of the disease.43 Although leishmaniasis and Chagas disease are distinct infections they share many immunopathogenic features. Following infection with Leishmania sp. and T. cruzi, some individuals generate effective T cell responses, control the parasite and become asymptomatic. On the other hand, T cell anergy or induction of macrophages deactivating cytokines, cause an overwhelming parasite replication with extensive tissue damage, which is characteristic of visceral leishmaniasis, diffuse cutaneous leishmaniasis, and the acute phase of Chagas disease. Imbalance of effector functions or cytokine production, however, can lead to an exacerbated immune response capable of mediating pathological damage, as observed in mucosal leishmaniasis and the cardiac form of Chagas disease.

28.3.1 LEISHMANIASIS Macrophages, the main host cells of leishmania, are activated by IFN-g and TNF-a for killing parasites. Cytokines such as IL-4, IL-5, or TGF-b favor the host and IL-10 counterbalances the pro-inflammatory effects of TNF-a or IFN-g.44,45 Once a favorable immuno-inflammatory response is achieved, infection will be controlled and the patient achieves clinical cure. Healing of lesions is associated with a preferential induction of type 1 cytokines, in conjunction with a down regulation of IL-4 and IL-5.46,47 A suitable amount of TNF-a and IFN-g is important in mediating cure, but higher levels of both cytokines do not appear to be associated with protection.48–50 On the contrary, an excess of these

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cytokines is observed in more severe leishmaniasis clinical manifestations, but it seems that they act in different ways in ML in comparison to DCL and VL. In cutaneous leishmaniasis, a clear mixed type 1 and 2 cytokine pattern is observed during the active disease and the balance between these cytokines will dictate the future of the infection.46,51,52 Immune response to Leishmania brasiliensis can lead to several manifestations from subclinical infection, self-healing, as well as mild (CL) and exacerbated response (ML). ML is not as common as CL, affecting approximately 5% of patients infected almost exclusively by L. braziliensis. The exact mechanism that leads to ML is unknown but it is believed that an exacerbation of cell-mediated immunity (CMI), involving both T lymphocyte subset effector functions and cytokine profile, has the potential to control parasite growth as well as cause pathology. Proposed immune pathogenic mechanisms include: (i) persistent overexpression of IFN-g and TNFa causing both destruction of infected macrophages as well as tissue damage; (ii) increased production of type 2 cytokines that facilitate parasite replication and apparently inhibit type 1 cytokines; and (iii) decreased ability of IL-10 and TGF-b to modulate pro-inflammatory responses.44,46,47,52,53 Since intensity of cytokine production is crucial for host/parasite interaction, it is possible that SNPs altering cytokine gene regulation may affect disease severity, similarly to that suspected for viral hemorrhagic versus classic fevers. It is known that ML patients produce higher amounts of IFNg and TNFa than CL patients.49,54 Thus, it is conceivable that polymorphisms in TNF-a and LT-a (or TNFB) genes may influence susceptibility to mucosal disease. In fact, polymorphisms in the second intron of LTa allele 2 as well as TNFA promoter
308A were observed in a higher frequency among ML patients.55 These data point to the importance TNFa and LTa in affecting severity of leishmaniasis. Infections with viscerotropic leishmanias (L. donovani, L. chagasi or L. infactum) also result in a range of manifestations, varying from no clinical signs of the disease to mild disease with consequent development of protective immunity or even progression to a fatal outcome. VL patients with active disease present a marked depression of T cell function and TH2 cell activation, as well as polyclonal B-cell activation. Unresponsiveness was shown to be mediated by the IL-10 suppression of antigen presentation and/or inhibition of IFN-g functions.56–58 Asymptomatic or subclinically infected individuals produce higher IFN-g than those who progress to VL.59 On the contrary, up-regulation of TNF-a possibly contributes to impairment of hematopoiesis, fever and weight loss, although such alterations are reverted after therapy. The diversity of clinical manifestations following viscerotropic Leishmania infection suggests that genetic variability also contributes to the outcome and development of visceral leishmaniasis. In a family-based study of asymptomatic and symptomatic VL Brazilian patients, using transmission disequilibrium test, TNF
308G was transmitted more frequently than expected from heterozygous parents to asymptomatic individuals, while TNF
308A was associated with symptomatic VL.60 In fact, TNFa levels were higher in TNF
308 (GA) heterozygous than in TNF
308 (GG) homozygous patients.60 In accordance, Blackwell61 associated the TNF
308A allele with higher TNF-a production. No evidence, however, has been presented for an association between VL and the
308 polymorphism of the TNFA gene and the polymorphism in intron 1 (þ252) of the LTA gene.62 Similarly to data from other infectious diseases such as Chagas disease, tuberculosis and leprosy, analyses of TNFA promoter polymorphisms and their association to visceral leishmaniasis are controversial. Possible explanations to such results will be discussed later.

28.3.2 CHAGAS DISEASE The establishment of inflammatory processes during the acute infection seems to be crucial for the control of T. cruzi dissemination. Nevertheless in 30% of patients, inflammation

418

Cytokine Gene Polymorphisms in Multifactorial Conditions

becomes progressive, resulting in chronic disease mainly characterized by myocarditis associated with prominent fibrosis and organ dysfunction.63,64 Several studies have associated chronic myocarditis with autoimmune recognition of heart tissue by T cell rich inflammatory infiltrate.63 However, parasite persistence associated with maladapted homeostatic mechanisms such as oxidant/antioxidant processes and pro-inflammatory/ anti-inflammatory cytokines, as well as chemoattractant cytokines, is critically involved in pathogenesis and disease progression.64–66 Apparently, cytokines that are produced in the heart tissue of T. cruzi-infected individuals during the initial immune response also influence the regulation of the subsequent immune reaction. The pro-inflammatory cytokines IFN-g and TNFa play a major role in controlling T. cruzi tissue parasitism during experimental T. cruzi infection. IFN-g and TNFa are also present in the inflamed hearts of chronic chagasic patients,67,68 thus suggesting that besides contributing to control of parasitism, IFN-g and TNF-a may also be involved in the maintenance of chronic myocarditis. The TNF-a participation in the pathophysiology of T. cruzi infection has not yet been elucidated. However, the parasite or its antigens involving a NF-kB dependent transcriptional pathway can directly trigger production of TNFa.69 In this respect, several T. cruziderived molecules, including tGPI mucins and DNA have been shown to stimulate the production of pro-inflammatory cytokines and chemokines70–72 involving TLR-mediated or MyD88-dependent pathways.72,73 TNF-a signaling via TNFR1 (p55) plays a critical role in resistance to experimental acute T. cruzi infection by controlling parasite uptake, nitric oxide (NO) and chemokine production,74 unravelling a pivotal role for TNF-a in the genesis of effective inflammation and parasite control. In contrast, it has been shown that TNF-a plasma levels correlate with the degree of heart dysfunction in chronically infected T. cruzi patients.66,74,75 This suggests that a TNF-a unbalance may participate in the evolution of chronic cardiomyopathy chagasic (CCC). Interestingly, TNF-a has previously been implicated in cachexia occurring during the acute infection76 and in splenic necrotic changes associated with severe T. cruzi infection.77 The data for Chagas disease points to the same conclusions that are observed in leishmaniasis and viral hemorrhagic fevers, where TNF-a and IFN-g are critical in either protection or promotion of the pathology. It is clear, however, that slight changes in concentrations of these cytokines could directly contribute to the susceptibility or severity to Chagas disease. Potential differences between groups of patients (asymptomatic vs. chronic cardiomyopathic) and between patients and healthy individuals could be related to variations in the TNFA gene promoter. The results concerning TNF polymorphisms are also conflicting in Chagas disease, as observed for visceral leishmaniasis. Studies performed with populationbased designs analyzing the frequency of TNFA promoter polymorphisms (
308,
244, and
238) in a small group of Spanish patients did not find any association comparing asymptomatic and CCC patients.78 In a Mexican study, the frequency of TNF
308A was increased in patients when compared to healthy individuals while CCC patients also presented a higher frequency of TNF
308A when compared to asymptomatic patients.79 TGF-b and IL-10 selectively modulate the expression of CC-chemokines triggered by T. cruzi infection,74 raising the question of whether or not these regulatory cytokines play a role in controlling cell influx into target tissues. Likewise, high production of IL-10 by macrophages/monocytes may lead to regulation of the immune response in indeterminate patients.80 Nonetheless, the potential participation of TGF-b and IL-10 in regulatory mechanisms controlling the exacerbated inflammation, particularly regulating antioxidant metabolism, cell recruitment and migration, and myocarditis outcome, remains to be evaluated in T. cruzi infection. T. cruzi-infected human and mouse macrophages as well as murine cardiomyocytes produce CC-chemokines CCL5/RANTES, CCL3/MIP-1a, CCL4/ MIP-1b, and CCL2/MCP-1, which, in an autocrine manner, stimulate infected cells to release NO and control T. cruzi growth.74,81,82

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The 59029G allele of CCR5, which is a receptor for CCL5/RANTES, CCL3/MIP-1a and CCL4/MIP-1b, is more frequent in asymptomatic than in cardiomyopathic patients,83,84 although the second study did not find a significant association. Interestingly, higher frequencies of circulating leukocytes expressing CCR5 and CXCR4 (receptor for CXCL12/SDF-1) are detected in patients with mild myocardiopathy. On the other hand, patients with severe disease present frequencies of CCR5-bearing leukocytes similar to non-infected individuals.85 Thus, the lower frequency of CCR5þ peripheral blood leukocytes in chagasic individuals with more severe disease can be due to the presence of heart dysfunction or sequestering of CCR5þ cells in target tissues. In fact, CCR5 is mostly expressed in CD8þ T cells present in the heart of T. cruzi-infected mice.86,87 Moreover, the treatment with antagonists demonstrated that the massive influx of inflammatory cells, especially CCR5þ cells, into the cardiac tissue is not crucial for cell-mediated anti-T. cruzi immunity.87 Hence, the genetic background of the host influences expression of CC-chemokines and CCR5 receptors that could be involved in the differential influx of inflammatory cells and pathogenesis of T. cruzi-elicited myocarditis. Altogether, the discussed data strongly suggest the participation of cytokines in the pathophysiology of Chagas’ disease and point to the fact that an immune response with sufficient strength and appropriate focus may control T. cruzi infection without induction of disease. Thus, understanding the molecular events that underlie tissue inflammation will shed light on the mechanisms responsible for parasite growth control and inflammationassociated tissue damage during T. cruzi infection. This certainly might aid in the development of novel strategies to control parasite dissemination and chronic debilitating inflammation.

28.4 MYCOBACTERIAL DISEASES: LEPROSY AND TUBERCULOSIS Mycobacterium leprae and M. tuberculosis respectively cause leprosy and tuberculosis, the two most important human mycobacterial diseases. M. tuberculosis infects 2 billion people worldwide and the disease kills 3 million people every year, predominantly in developing countries. M. leprae and M. tuberculosis are intracellular pathogens, infecting macrophages (M. tuberculosis in the lungs and M. leprae in the skin), although M. leprae is also found in Schwann cells of peripheral nerves. Leprosy is the major infectious cause of nerve impairment, with 30% of the patients developing some kind of disability.88 Leprosy and tuberculosis are spectral diseases in which patients exhibit severe and mild clinical patterns. In leprosy, the mild patients, called tuberculoid (TT), present a low mycobacterial count and an active cellular immune response. The severe form (lepromatous, LL) is characterized by an absence or very low levels of cellular immune response and high bacterial load. These polar forms of the disease are separated by three other clinical manifestations, called borderline, that are defined by their proximity to the tuberculoid (borderline tuberculoid) or lepromatous (borderline lepromatous) poles. The intermediate clinical type of leprosy is called borderline borderline (BB). Unlike other infectious agents such as Dengue virus, Leishmania sp. or even M. tuberculosis, M. leprae has a low genetic diversity.89 Therefore this suggests that the host immune response is the predominant factor in determining the clinical manifestations in leprosy. In this context, leprosy was the first human example of the Th1/ Th2 paradigm.90 A myriad of clinical forms is also observed in tuberculosis. The most severe is milliary TB, which is a disseminated form with large numbers of bacteria. Nevertheless, tuberculosis is generally a pulmonary infection which can either be mild or severe (either chronic, cavitary,

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Cytokine Gene Polymorphisms in Multifactorial Conditions

or destructive disease). The patterns of immune responses are not as dichotomical as in leprosy. High levels of the cytokines, such as IFN-g and TNF-a, are observed in severe states, such as the cavitary form, and are not associated to protection, but rather to the immunopathological response along the course of the disease. Thus, the role of cytokines in leprosy and tuberculosis is similar to that observed in Leishmania or T. cruzi infection where there is a dual participation not only controlling parasite growth but also favoring inflammation. The majority of studies in tuberculosis were conducted in a sample population of a single ethnicity, generally using one type of experimental design (Table 28.1). The results obtained for the þ874A SNP in the IFNG gene showed association with susceptibility to tuberculosis. The data were independently replicated in three distinct populations,91–93 while a fourth study evaluating an Italian population found the same trend. The frequency of the þ874A allele was increased in patients as compared to controls, although not significantly.94 This data strongly suggests a role of IFN-g in susceptibility to tuberculosis. It has been demonstrated that þ874A is associated to low IFN-g production in response to M. tuberculosis antigens.91 Therefore, the presence of the þ874A allele among individuals secreting lower levels of IFN-g would explain the inability of these people to properly mount an immune response to M. tuberculosis, facilitating its growth and consequently the outcome of the disease. However, no associations were reported between interferon-gamma receptor (IFNGR gene) polymorphisms and tuberculosis.95 Likewise, in Korean leprosy patients, no association was found among the IFNGR1 and IL12RB1 polymorphisms studied.96 On the other hand, screening of polymorphisms in IL12RB1 in Moroccan families and in a Japanese population showed that a promoter variant in Moroccans and a haplotype of coding polymorphisms in Japanese were associated with susceptibility to tuberculosis.97,98 The data explored the functionality of IL12RB1 suggesting that the R214-T365-R378 haplotype was less responsive to IL-12 signaling.97 The results obtained with IFNG and IL12RB1 suggest that the cellular immune axis is important in regulating protective response against tuberculosis. Data are not as conclusive when concerning other cytokines since studies conducted in other populations failed to confirm the previous associations. This is the case of IL-8 analysis in American (associated) and Gambian (not associated) populations.99,100 Furthermore, variations in TNF-a were also discrepant among populations, as observed in leishmaniasis and Chagas disease. Delgado101 and Selvaraj102 found no correlation between the
308 SNP and pulmonary tuberculosis. Contradictory data demonstrated that the
308A allele was associated with TB in a small population of Sicilian patients,103 and TNF
308A was associated with tuberculosis resistance while the TNF
238A allele represented a susceptibility factor for TB in Chileans.104 Variations in the IL-10 promoter in population-studies in tuberculosis patients also led to conflicting results. In a Spanish,91 a Chinese93 and a Gambian population with pulmonary tuberculosis105 no association was found between tuberculosis and the IL-10 promoter SNPs. On the other hand, Delgado101 reported that the
1082GA genotype was increased among Cambodian pulmonary tuberculosis patients, and Scola et al.103 reported that the
1082A allele was associated with chronic tuberculosis in Sicilian patients. Analysis in two populations (Indian and Brazilian) suggested opposite associations of TNF
308A with leprosy. TNF
308A is associated with resistance to leprosy in the Southern Brazilian sample105,107 while in the Indian sample there is an increased frequency of the SNP among severe or lepromatous forms of the disease.108 A second study in another Brazilian population (Northern Brazilian) using family-based approaches confirmed the association of
308A to resistance.108 Interestingly, family-based studies conducted in Vietnamese leprosy families found that region 6p21, which includes TNF, was nonstringently linked to leprosy per se.109 In the IL10 promoter region, the
819TT was


2 (T)

R214–T365–R378

þ874(A)

þ874(A)

þ874(A)

þ874(A)

363 TB/320 HC 101 families (157 offspring)

98 TB/197 HC

100 HC/125 PPDþ/82 PPD
/113 TB

313 TB/235 HC

385 TB/451 HC

45 TB/97 HC

IL12RB1

IFNG


251(A)

VNTR (intron 1) Allele 2 (CA)n repeat intron 5
511 VNTR (intron 1) Allele 2


511/þ3953

Polymorphism (VNTR or SNP) Position

240 TB/274 HC

408 TB/417 HC

89 TB/114 HC

Sampling

IL8

IL1RN IL1A IL1B IL1RN

IL1b

Gene

TABLE 28.1 Association of Cytokine Gene Polymorphisms with Tuberculosis

Italian

Chinese

South African

Spanish

Japanese

Gambian Moroccan

American

Gambian

Indians (Gurajati)

Population

No association No association No association Resistance P ¼ 0.03, OR ¼ 0.45 [95% CI 0.21–0.99] Susceptibility P ¼ 0.01, OR ¼ 3.41 [95% CI 1.52–7.54] No association Susceptibility P ¼ 0.013, OR ¼ 2.69 [95% CI, 1.19–6.09]. Susceptibility P ¼ 0.013, OR ¼ 2.45 [95% CI, 1.20–4.99]. Susceptibility P ¼ 0.0017, OR ¼ 3.75 [95%CI 2.26–6.23] Susceptibility P ¼ 0.0055, OR ¼ 1.64 [95%CI 1.16–2.30] Susceptibility P 5 0.001, OR ¼ 3.79 [95% CI ¼ 1.93–7.45] No association

No association

Association

(Continued )

94

93

92

91

97

100 98

99

114 104 104 104

114

References

Tropical Infectious Diseases 421


1030/
863/
857/
308
308/
238
308(A)
1082(GA)


1082/
819/
592
1082/
819/
592
1082/
819/
592

358 TB/106 PPDþ 210 TB/120 HC 45 TB/114 HC 358 TB/106 PPDþ

408 TB/417 HC 100 healthy/PPDþ125/PPD
82/TB 113 385 TB/451 HC

IL10

TB ¼ tuberculosis; HC ¼ healthy controls; PPD ¼ purified protein derivative.

Several
308G/
238A

Polymorphism (VNTR or SNP) Position

320 TB/320 HC 135 TB/435 HC

Sampling

IFNGRA TNFA

Gene

TABLE 28.1 Continued

Gambian Spanish Chinese

Cambodian Indian Italian Cambodian

Gambian Chilean

Population

No association Susceptibility P ¼ 0.02, OR ¼ 1.8 No association No association Susceptibility Susceptibility P ¼ 0.01, OR ¼ 1.84 [95% CI ¼ 1.15-2.93] No association No association No association

Association

104 91 93

101 102 103 101

95 105

References

422 Cytokine Gene Polymorphisms in Multifactorial Conditions

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associated with disease.107 Furthermore, the combination of distal SNPs in a haplotype (
3575A/
2849G/
2763C) revealed an increased frequency among controls when compared to patients, where a
3575T/
2849A/
2763C that is in linkage to
819T was associated to the disease.110 In these studies, conflicting results may primarily reflect biases of design such as low number of individuals or poor selection of controls enrolled in these population-based studies. These results may also be ascribed to an association of other polymorphisms in TNF or IL10 loci, which are differentially in linkage disequilibrium to
308A or
1082G alleles, respectively, due to differences in haplotype structure. This could also be the case for IL8 or the IL1 cluster. Recently, studies have been pointing towards analyses representing an entire haplotype in a certain locus, rather than individual SNP genotypes. There are two major advantages in defining haplotypes. First of all, a larger region is taken into account that carries more information facilitating the localization of the associated locus, thus being more accurate than any single SNP. Secondly, the analysis of an entire block carrying a combination of SNPs along the gene (promoter, 30 UTR, etc.) makes it easier to associate them to a special phenotype status. Alternatively, we cannot exclude the possibility that different environmental pressures are selecting ethnic-specific susceptibility/resistant genes. Since Caucasian, Asian, African, and American Indians have been exposed to very different selective environments in the past 300 years (at least), it is possible that they mounted distinct strategies to cope with infectious pathogens. For example, it has been suggested that Canadian aborigines are much more susceptible to tuberculosis than Caucasian Canadians due to the recent history of exposure.111 An evidence of this ethnic-specific resistance/susceptibility gene selection was obtained from the adaptation of Dutch farmers to Surinam. The HLA frequency distribution differed between ancestors in the Netherlands and farmers that had survived typhoid and yellow fever epidemics.112 Regardless of the huge discrepancy among the studies, data strongly suggest that none of these studied polymorphisms (TNFA, IL10, IL1 cluster, and IL8) are major common variants associated with susceptibility to leprosy or tuberculosis. Since several associations were reported, it is likely that the implicated SNP or haplotype in these genes has not yet been found. The other important issue is to confirm the biological mechanisms underlying functionality of each of the SNPs (or haplotypes) in regulating gene expression to establish a clear genotype–phenotype status for each SNP (haplotype) in each specific population. The physiological data generated for IFNG gene polymorphism þ874A as a low producer91 has pointed in this direction. Concerning TNFA and IL10 SNPs, few papers analyzed their functional status. Indirectly, clinical or biological parameters that are allegedly influenced by the cytokine (and their polymorphisms) have been used to test their functionality. The injection of heat-killed Mycobacterium leprae in the forearm induces a delayed immune response that is detected 28 days after the injection. Likewise, the injection of purified protein derivative (PPD) from M. tuberculosis triggers the same kind of reaction, but in 2–3 days. The inflammatory reactions are called Mitsuda and Mantoux for leprosy and tuberculosis, respectively. When patients from a specific clinical form of leprosy (borderline tuberculoid) were tested for the M. leprae antigens, those carrying
308A allele in the TNFA promoter were found to present a stronger skin response.113 Similarly, patients with tuberculosis carrying the IL1RN A2þ allele (VNTR), which are suggested as higher producers of the IL-1 receptor antagonist, exhibit reduced Mantoux induration when challenged with PPD.114 In leprosy, slit skin smears were used for the counting of bacilli in vivo as a clinical parameter to compare groups of patients. The mycobacterial load in TNFA
308A carriers presented lower bacteriological counts than non-carriers.115 In this case, the augmented production of TNF could be associated with the
308A allele based on this indirect evidence.

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Cytokine Gene Polymorphisms in Multifactorial Conditions

28.5 CONCLUSIONS The literature suggests that genetic heterogeneity in infectious disease susceptibility rely not only on cytokines, but also on other genes that mediate immune responses. In view of this, it is likely that genes not involved in classical pathways of immunity could also play a substantial role in susceptibility to these diseases. Genome-wide scans using a family-based Vietnamese study, replicated in a Brazilian case-control sample, have provided evidence of the association of genes involved in the proteolytic pathway, such as PARK2 and Parkin co-regulated gene (PACRG) in susceptibility to leprosy.116 Nevertheless, the genome-wide scan in another Brazilian population implicated a region of chromosome 17, where several genes involved in immune activation, such as nitric oxide synthase (NOS2A) and STAT5A, are found. The search for functional SNPs is essential to understand disease associations. High throughput techniques to genotype large numbers of SNPs are required to determine the precise haplotypes that are functional and that are associated with diseases. This strategy, when performed in conjunction with transcriptomic and proteomic analyses, will reveal several other regions involved in the heterogeneous susceptibility to infectious disease. Such large-scale methods are now available and will lead to a more sophisticated understanding of the genetic regulation of susceptibility to infectious diseases in the not too distant future.

REFERENCES 1. Schroder, N. W., and Schumann, R. R., Single nucleotide polymorphisms of Toll-like receptors and susceptibility to infectious disease, Lancet Infect. Dis., 5, 156, 2005. 2. Beiguelman, B., Some remarks on the genetics of leprosy resistance, Acta Genet. Med. Gemellol. (Roma), 17, 584, 1968. 3. Bucheton, B. et al., The interplay between environmental and host factors during an outbreak of visceral leishmaniasis in eastern Sudan, Microbes Infect., 4, 1449, 2002. 4. Dolo, A. et al., Difference in susceptibility to malaria between two sympatric ethnic groups in Mali, Am. J. Trop. Med. Hyg., 72, 243, 2005. 5. Stead, W. W. et al., Racial differences in susceptibility to infection by Mycobacterium tuberculosis, N, Engl. J. Med., 322, 422, 1990. 6. Mason, N. J., Artis, D., and Hunter, C. A., New lessons from old pathogens: what parasitic infections have taught us about the role of nuclear factor-kappaB in the regulation of immunity, Immunol Rev., 201, 48, 2004. 7. Schwartz, R. H., Natural regulatory T cells and self-tolerance, Nat Immunol., 6, 327, 2005. 8. Sher, A., Pearce, E., and Kaye, P., Shaping the immune response to parasites: role of dendritic cells, Curr. Opin. Immunol., 15, 421, 2003. 9. O’Garra, A. and Vieira, P., Regulatory T cells and mechanisms of immune system control, Nat. Med., 10, 801, 2004. 10. Da-Cruz, A. M. et al., Cellular immune responses to Leishmania braziliensis in patients with AIDS-associated American cutaneous leishmaniasis, Trans. R. Soc. Trop. Med. Hyg., 94, 569, 2000. 11. Zhao, C., Papadopoulou, B., and Tremblay, M. J., Leishmania infantum promotes replication of HIV type 1 in human lymphoid tissue cultured ex vivo by inducing secretion of the pro-inflammatory cytokines TNF-alpha and IL-1 alpha, J. Immunol., 172, 3086, 2004. 12. Sampaio, E. P. et al., Cellular immune response to Mycobacterium leprae infection in human immunodeficiency virus-infected individuals, Infect. Immun., 63, 1848, 1995. 13. Keane, J., Tumor necrosis factor blockers and reactivation of latent tuberculosis, Clin. Infect. Dis., 39, 300, 2004. 14. Joyce, M. P., and Scollard, D. M. 2002. Borderline lepromatous in a patient treated with infliximab (a tumor necrosis factor inhibitor). In 16th International Leprosy Congress. Salvador, Brazil, 145.

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89. Monot, M. et al., On the origin of leprosy, Science, 308, 1040, 2005. 90. Yamamura, M. et al., Defining protective responses to pathogens: cytokine profiles in leprosy lesions, Science, 254, 277, 1991. 91. Lopez-Maderuelo, D. et al., Interferon-gamma and interleukin-10 gene polymorphisms in pulmonary tuberculosis, Am. J. Respir. Crit. Care Med., 167, 970, 2003. 92. Rossouw, M. et al., Association between tuberculosis and a polymorphic NFkappaB binding site in the interferon gamma gene, Lancet, 361, 1871, 2003. 93. Tso, H. W. et al., Association of interferon gamma and interleukin 10 genes with tuberculosis in Hong Kong Chinese, Genes Immun., 6, 358, 2005. 94. Awomoyi, A. A. et al., No association between interferon-gamma receptor-1 gene polymorphism and pulmonary tuberculosis in a Gambian population sample, Thorax, 59, 291, 2004. 95. Lee, S. B. et al., Missense mutations of the interleukin-12 receptor beta 1(IL12RB1) and interferon-gamma receptor 1 (IFNGR1) genes are not associated with susceptibility to lepromatous leprosy in Korea, Immunogenetics, 55, 177, 2003. 96. Akahoshi, M. et al., Influence of interleukin-12 receptor beta1 polymorphisms on tuberculosis, Hum Genet., 112, 237, 2003. 97. Remus, N. et al., Association of IL12RB1 polymorphisms with pulmonary tuberculosis in adults in Morocco, J. Infect. Dis., 190, 580, 2004. 98. Ma, X. et al., Association between interleukin-8 gene alleles and human susceptibility to tuberculosis disease, J. Infect. Dis., 188, 349, 2003. 99. Cooke, G. S. et al., Interleukin-8 polymorphism is not associated with pulmonary tuberculosis in the gambia, J. Infect. Dis., 189, 1545, 2004. 100. Delgado, J. C. et al., Ethnic-specific genetic associations with pulmonary tuberculosis, J. Infect. Dis., 186, 1463, 2002. 101. Selvaraj, P. et al., Tumour necrosis factor alpha (
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29

Susceptibility to Infection and Severe Disease in Schistosomiasis Violaine Arnaud and Christophe Chevillard

CONTENTS 29.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.2 Life Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.3 Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.4 Control of Infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.5 Susceptibility to Advanced Schistosomiasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

431 431 432 437 439 441 442 442

29.1 INTRODUCTION Schistosomiasis is the second leading parasitic disease after Malaria. It comprises a group of chronic diseases caused by helminth digenetic trematodes of the Schistosoma genus. Five species of Schistosoma can affect humans. Schistosoma mansoni, S. japonicum, S. mekongi and S. intercalatum inhabit the mesenteric vessels and S. hematobium inhabits the vesical plexus. Two hundred and fifty millions of subjects are at risk of infection and in endemic regions, 5 to 20% of the population develops severe diseases, while 250 000 to 300 000 individuals die annually of the consequences of this infection.1,2

29.2 LIFE CYCLE (FIGURE 29.1) Infective larvae (cercariae) are released by fresh water snails. Human infection results from contact with water. The larva secretes enzymes that break down the skin’s protein to enable its penetration in the skin. During this migration, cercariae transform into schistosomulae. Twelve to 48 hours after infection, this new form circulates in the body for over 15 days, through the pulmonary vasculature where it undergoes further developmental changes. Then, young worms reach their final habitat in the venous mesenteric plexus (S. mansoni, S. japonicum) or in the urinary tract (S. haematobium). Schistosoma lives in his host for 3 to 5 years. Within the portal vasculature, male and female adults pair off and migrate along the endothelium, against portal blood flow, to the mesenteric (S. mansoni, S. japonicum) or vesicular (S. haematobium) veins where the female lay on average 300 to 3000 eggs a day. These eggs migrate through the bowel or bladder wall to be shed in feces or urine. They hatch in fresh water and release ciliated motile miracidia (approximately 10 days). Free-swimming miracidia infect susceptible snail and 431

432

Cytokine Gene Polymorphisms in Multifactorial Conditions

FIGURE 29.1 Life cycle of schistosomes. Infection occurs when cercariae penetrate the skin (1). Cercariae lose their tail and become schistosomulae (2) which move to the veins. Adults mature in the veins surrounding either the intestines or the bladder, depending on the species. Schistosoma hematobium matures in veins around the bladder whereas S. mansoni and S. japonicum mature in veins around the intestines (3). Females release eggs which move from the veins to the lumen of the intestine (S. mansoni and S. japonicum) or the bladder (S. hematobium). The eggs are then passed from the body to the feces or urine (4). They hatch in fresh water and release a motile larvae called miracidium (5). The miracidium infects the intermediate host (6) and multiplies asexually inside it. After 4 to 6 weeks novel cercariae emerge (7).

multiply asexually. Within 4 to 6 weeks mature cercariae emerge and exit the snail to seek a human host in a circadian rhythm, dependent on ambient temperature and light.

29.3 PATHOLOGY Disease manifestations caused by schistosome infection are multiple and related to the three different stages of development of the pathogen (cercariae, mature worms, and eggs) and to the host immune status. Acute schistosomiasis follows the penetration of cercariae in naive host and the oviposition. A serum sickness-like illness called katayama fever can occur, particularly in S. japonicum infection. It is thought to be caused by antigen–antibody complex deposition, and pro-inflammatory cytokines production in response to adult worms and massive egg antigens concentration.3 Symptoms usually resolve over several weeks, but in rare cases it can be fatal. The pathology of chronic schistosomiasis results from egg-induced immune response, granuloma formation, and associated fibrotic changes. Usually, eggs pass into feces

433

Susceptibility to Infection and Severe Disease in Schistosomiasis

(S. mansoni) or urine (S. haematobium) but some of them remain trapped in the tissues, mainly in liver, intestine, spleen, bladder, and ureter walls and cause major pathological disorders. Indeed, eggs induce vigorous immune responses. In experimental murine models of infection, eggs first elicit a predominantly T-helper type 1 (Th1) cellular response, marked by an influx of mononuclear cells and the initiation of increased collagen formation. Over time, a modulation of the initial cellular reaction may take place as eggs deposition continues; the intensity of inflammation diminishes and a shift to a predominantly Th2 type cellular response is seen with prominent eosinophilic infiltration of the granuloma and continuing deposition of fibrous tissue.4,5 In humans, an abnormal scarring process leads to fibrosis characterized by synthesis, deposition, remodeling and turnover of extracellular matrix proteins. S. mansoni fibrosis (Symmers’ fibrosis) causes periportal hypertension in severe cases. Additional complications, including splenomegaly, ascites, oesophageal varice bleeding, and development of collateral circulation, may lead to usual possible sequelae. Collagen deposition may also reduce urine flow through the ureters, leading to hydroureters and hydronephrosis. S. haematobium causes hematuria, dysuria, bladder polyps and ulcers, and even obstructive uropathies. Levels of infection and degree of severe disease in humans are under the control of several factors (environmental, comportmental, vector, parasite, and host specific factors). This review will focus on host factor studies which have benefit, in the last decade, of the development of new technologies that now allow the identification of major genes and polymorphisms associated to these controls. The main milestones are summarized in Table 29.1 and will be further described.6–30

TABLE 29.1 Milestones toward the Identification and the Characterization of the Genetic Factors That Control Human Susceptibility to Infection and Severe Diseases in Schistosomiasis Year

Summary

Reference

1980

An increased incidence of certain HLA genes was found in people with schistosomiasis who develop hepatosplenic disease. This finding may pinpoint individuals at risk of morbidity and direct early treatment to them.

6

1981

Lack of association between Schistosoma japonica infection and immunoglobulin allotypes in Filipinos.

7

1982

Immune responsiveness of 121 patients with post-schistosomal liver cirrhosis to schistosomal antigens was investigated. A significant increase in frequency of HLA-Bw44-DEn haplotype was observed. On the other hand, the HLA-Bw52-Dw12 haplotype which was reported to be in strong linkage disequilibrium with an immune suppression gene for schistosomal adult worm antigen was significantly decreased.

8

1984

The association of HLA specificity with low or high immune responsiveness to Schistosoma japonicum antigen was demonstrated among individuals who had previously been exposed to S. japonicum infection. The frequency of HLA-Aw24 specificity among low responders in the IgG antibody response was higher than that among high responders. Significant association between HLA-B7 and high responsiveness was observed in the IgE antibody response. The frequency of HLA-Bw52-Dw12 was also found to increase among individuals with higher levels of total serum IgE. These results suggest that antibody responses to Schistosoma japonicum are regulated by an immune response gene(s) linked to the major histocompatibility complex (MHC).

9

(Continued )

434

Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 29.1 Continued Year

Summary

Reference

1987

Immunogenetic factors were studied in 60 patients with chistosoma japonicum in the Philippines, of whom 15 were characterized by marked hepatosplenic lesions and 45 characterized by cerebral symptoms. A significant association between HLA-B40 and high responders to the schistosomal antigen was observed, and this HLA specificity was increased in frequency in the hepatosplenic patients. HLA-B16 was not observed in the hepatosplenic patients, but was common in the cerebral patients, and this HLA specificity was commoner in the low responders than in the high responders.

10

1987

The HLA-DR2 molecule from a non-responder haplotype (HLA-Dw12-DR2-DQwl) is required for the proliferative T cell response to Schistosoma japonicum antigen, as a restriction element, indicating that the HLA-DR2 is the product of the immune response gene, and that the HLA-DQwl molecule of the non-responder haplotype is important in the antigen-specific suppression of the response to this antigen, suggesting that it is the product of the immune suppression gene.

11

1991

No apparent correlation between the chronic forms of the disease from a southern Brazilian hospital and the expression of HLA-A1 and B5 antigens was detected. Conversely, the association of histocompatibility antigens with splenomegaly is consistent and significant only for HLA-B5, but not HLA-A1.

12

1991

Severe clinical disease caused by the major human parasite Schistosoma mansoni is the consequence of high and prolonged infections. Epidemiological studies indicate that, for individuals having frequent contacts with cercaria-infested waters, both infection intensities and reinfection after treatment depend, in a large part, on their intrinsic susceptibility/ resistance to infection, suggesting a role for genetic factors in human resistance to S. mansoni. The results of a segregation analysis on infection intensities are consistent with the hypothesis that there is a codominant major gene controlling human susceptibility/resistance to infection by S. mansoni. Parameter estimates indicate a frequency of 0.20–0.25 for the deleterious allele; thus, about 5% of the population is predisposed to high-intensity infections, 60% are resistant, and 35% have an intermediate, although fairly good, level of resistance. These findings provide a genetic basis for earlier observations on the lower resistance and the predisposition to reinfection of certain individuals. In addition to the detection of a major gene effect, the data suggest that immunity to S. mansoni develops progressively during childhood to reach a maximum around the age of puberty.

13

1992

The design of programs for the control of endemics requires the knowledge of the principal factors that determine parasite transmission and infection levels in exposed populations. In the studies summarized in this article, the role of environmental and host specific factors in the infection by S. mansoni have been evaluated. It is shown that a limited number of factors actually influence infection intensity: water contacts, age, and sex were shown to account for 20 to 25% of infection variance, while 35 to 40% of it was accounted for by the effect of a major codominant gene. A remarkable fact is the important weighting (around 55% of the variance) of factors (the major gene and age) that influence human capacities of resistance.

14

1993

The study was carried out on 47 patients with Schistosoma mansoni and 20 healthy volunteers served as control group for the immunological parameters and 200 subjects for the genetic studies. A statistically significant association was found between HLA-B5 and DR3 and with the occurrence of hepatosplenic disease; this phenotype also correlated with changes in T lymphocyte subsets and high immune reactivity, both humoral and cell mediated. HLA-DQI was also associated with failure to develop hepatosplenic disease.

15

(Continued )

435

Susceptibility to Infection and Severe Disease in Schistosomiasis

TABLE 29.1 Continued Year

Summary

Reference

1996

A segregation analysis in a Brazilian population infected by the helminth parasite Schistosoma mansoni. The analysis was performed on IL-5 levels produced by blood mononuclear cells of these subjects after in vitro restimulation with either parasite extracts (IL-5/schistosomula sonicates [SS] phenotype) or a T-lymphocyte mitogen (IL-5/phytohemagglutin [PHA]). The results provide clear evidence for the segregation of a codominant major gene controlling IL-5/SS and IL-5/PHA production and accounting for 70% and 73% of the phenotypic variance, respectively; the frequency of the allele predisposing to low IL-5 production was approximately 0.22 for both phenotypes. No significant relationship was found between these genes and the gene controlling infection intensities by S. mansoni detected in a previous study.

16

1996

Intensity of infection by Schistosoma mansoni was influenced by a major gene, indicating that host genetic factors are probably critical in controlling schistosome infection and disease development. To localize this gene, referred to as SM1, we performed a genome-wide study on 142 Brazilian subjects belonging to 11 informative families. The results show a linkage to only one region, on chromosome 5q31–q33, with maximum two-point lod scores of þ4.74 and þ4.52 for D5S636 and the colony stimulating factor-1 receptor marker (CSF1R), respectively. This was corroborated by multipoint analysis, indicating a close proximity to CSF1R as the most likely location of SM1.

17

1996

A study on 351 persons living in an area endemic for Schistosoma mansoni in northeastern Brazil do not provide association of HLA-DR or DQ with egg excretion. Hepatosplenic disease was less likely in patients positive for DRB1*11 and was more likely in patients positive for DRB1*07 or DQB1*0201. However, only the DQB1*0201 association remained significant (odds ratio ¼ 3.72; P 5 0.005) following Bonferroni correction.

18

1998

On 108 individuals living in an area endemic for Schistosoma japonicum in China, two alleles, HLA-DRB1*1202 (P ¼ 0.002) and HLA-DQA*0601 (P ¼ 0.001) were strongly associated with resistance to advanced disease. In contrast, HLA-DQB1*05031 (P ¼ 0.02) was associated with susceptibility to advanced schistosomiasis. Allele DRB1*1202 co-occurred with allele DQA1*0601; therefore, their independent protective effects could not be ascertained. In contrast, alleles DQA1*0601 and DQB1*05031 never co-occurred and had opposite and significant effects on the occurrence of disease.

19

1998

MHC haplotypes have been reported to segregate with susceptibility to schistosomiasis in murine models. In humans, a major gene related to susceptibility/resistance to infection by S. mansoni (SM1) and displaying the mean fecal egg count as phenotype was detected by segregation analysis. This gene displayed a codominant mode of inheritance with an estimated frequency of 0.20–0.25 for the deleterious allele and accounted for more than 50% of the variance of infection levels. To determine if the SM1 gene segregates with the human MHC chromosomal region, they performed a linkage study by the lod score method. It clearly indicated that there is no physical linkage between HLA and SM1 genes. Thus, susceptibility or resistance to schistosomiasis, as defined by mean fecal egg count, is not primarily dependent on the host’s HLA profile.

20

1998

The MHC-DP alleles of the variable second exons and their human leukocyte antigen (HLA) epitopes were correlated with egg excretion, interleukin-4 and interferon-gamma patterns, and bladder abnormalities, as detected by ultrasonography. A methionine at position 11 of the DP alpha molecule (Met-11) and DPA1*0301 were associated with schistosomiasis when compared with controls (phenotypic gene frequencies ¼ 0.791 versus 0.583 and 0.555 versus 0.375, respectively). Met-11 homozygosity occurred more often in patients, whereas healthy (Continued )

436

Cytokine Gene Polymorphisms in Multifactorial Conditions

TABLE 29.1 Continued Year

Summary

Reference

controls were more frequently homozygous for an alanine at position 11 (Ala-11). The combination of the DPB1-epitope DEAV (positions 84–87 of the DP beta molecule) and Met-11 positive DPA1 alleles was more frequent in patients than in controls (0.573 versus 0.316). Two years after antischistosomal treatment, the rate of reinfection was higher in DPA1*0301-positive individuals than in those not possessing this allele (P 5 0.001). Ala-11 positive individuals showed less frequently ultrasonographic signs of bladder pathology than Ala-11 negative individuals (P 5 0.05).

21

1999

It reports the full results of a genome-wide search that was performed on this population to localize SM1 in 5q31–q33. Three additional regions, 1p22.2, 7q36, and 21q22-22-qter, yielded promising, although not significant, lod-score values.

22

1999

This study performed in China shows that the HLA-DRB1*1101-DQA1* 0501-DQB1*0301 (Pc 5 0.02) and HLA-DRB1*1501-DRB5*0101 (Pc 5 0.02) haplotypes are associated with protection and susceptibility to grade I fibrosis, respectively, and that the HLA-DPA1*0103 -DPB1*0201 haplotype (Pc 5 0.02) is associated with protection from both grade II and III severe fibrosis. There was no association between HLA-B DNA haplotypes and the disease.

23

1999

Lethal disease due to hepatic periportal fibrosis occurs in 2–10% of subjects infected by Schistosoma mansoni in endemic regions such as Sudan. To investigate the genetic control of severe hepatic fibrosis (assessed by ultrasound examination) causing portal hypertension, a segregation analysis was performed in 65 Sudanese pedigrees from the same village. Results provide evidence for a codominant major gene, with 16 as the estimated allele A frequency predisposing to advanced periportal fibrosis. For AA males, AA females, and Aa males a 50% penetrance is reached after, respectively, 9, 14, and 19 years of residency in the area, whereas for other subjects the penetrance remains 50.02 after 20 years of exposure. Linkage analysis performed in four candidate regions shows that this major locus maps to chromosome 6q22–q23 and that it is closely linked (multipoint LOD score 3.12) to the IFN-gammaR1 gene encoding the receptor of the strongly antifibrogenic cytokine interferon-gamma.

24

2001

The present study is an autosome-wide scan searching for additional human loci implicated in the regulation of S. mansoni infection intensities. The weighted pairwise correlation modelfree linkage method was used in order to consider large pedigrees and to conduct a two-locus analysis (i.e., to search for a second locus taking into account linkage to 5q31–q33). The most significant linkage results were again obtained in the 5q31–q33 region. Two additional regions provided linkage results with significance levels around 0.001, 1p21–q23 (results independent of 5q31–q33) and 6p21–q21 (results in interaction with 5q31–q33).

25

2002

In Thailand, the TNF-alpha 50 -flanking region shows biallelic polymorphic sites at nucleotides
238,
308,
857,
863, and
1031, and seven alleles have been identified in patients from Myanmar. We found that the TNF promoter (TNFP)-D allele was significantly associated with cerebral malaria in populations from Karen (P 5 0.0001, OR ¼ 124.86) and ethnic Burma (P 5 0.0001, OR ¼ 34.50). In China, we have identified two major genes related to the severity of liver fibrosis, one an HLA class II gene, and the other the IL-13 gene. The frequency of the HLA-DRB5*0101 allele and that of the IL-13 promoter A/A (IL-13P-A/A) genotype were elevated in fibrotic patients, although the two genes are located on different chromosomes, chromosomes 6p and 5q, respectively. Subjects with both genotypes had odds ratios (OR ¼ 24.5) much higher than the sum of the ratios for each individual genotype (OR ¼ 5.1, 95% confidence interval 1.3–24.7 for HLA-DRB5*0101, OR ¼ 3.1 95%, CI 1.5 – 6.5 for IL-13P-A/A).

26

2003

Four polymorphisms (TNF-alpha
376 G/A,
308 G/A,
238 G/A, and þ488 G/A) were investigated in two Sudanese populations living in an area in which S. mansoni is endemic. No evidence of association was detected between these four polymorphisms and periportal fibrosis in both of these studies. However, this result does not exclude the possibility that these polymorphisms have a minor effect on PPF development.

27

(Continued )

437

Susceptibility to Infection and Severe Disease in Schistosomiasis

TABLE 29.1 Continued Year

Summary

Reference

2003

This study screened putative polymorphic sites within the IFNg gene in a population living in an endemic area for Schistosoma mansoni. Two polymorphisms located in the third intron of the IFN-gamma gene are associated with PPF. The IFN-gamma þ2109 A/G polymorphism is associated with a higher risk for developing PPF, whereas the IFN-gamma þ3810 G/A polymorphism is associated with less PPF. The polymorphisms result in changes in nuclear protein interactions with the intronic regions of the gene, suggesting that they may modify IFN-gamma mRNA expression. These results are consistent with the results of previous studies. Indeed, PPF is controlled by a major locus located on chromosome 6q22–q23, closely linked to the gene encoding the alpha-chain of the IFN-gamma receptor, and low IFNgamma producers have been shown to have an increased risk of severe PPF.

28

2004

Schistosomiasis is a major endemic parasitic disease in the world. In China, they have identified two major genes related to the severity of liver fibrosis, one an HLA class II gene, and the other the IL-13 gene. The frequency of the HLA-DRB5*0101 allele and that of the IL-13 promoter A/A (IL-13P-A/A) genotype were elevated in fibrotic patients, although the two genes are located on different chromosomes, chromosomes 6p and 5q, respectively. Subjects with both genotypes had odds ratios (OR ¼ 24.5) much higher than the sum of the ratios for each individual genotype (OR ¼ 5.1, 95% confidence interval 1.3–24.7 for HLA-DRB5*0101, OR ¼ 3.1, 95% CI 1.5–6.5 for IL-13P-A/A). Although they have not yet characterized the functional difference between HLA-DRB5*0101 and other alleles, peripheral blood mononuclear cells from IL-13PA/A donors produced much higher amount of mRNA than IL-13PA/B 24 h after the stimulation with PHA.

29

2005

This study evaluates whether certain polymorphisms in IL4, IL5, or IL13 determine schistosome infection in two Dogon villages where Schistosoma haematobium is endemic. The alleles IL13-1055C (p ¼ 0.05) and IL13-591A (p ¼ 0.01) are shown, by family-based association test, to be preferentially transmitted to children with the 10% highest infections. A logistic regression analysis that included IL13-1055 G/G, G/T and T/T genotypes, age, gender, and village of residency, applied to the whole study population, showed that subjects bearing the IL13-1055T/T genotype were on average much less infected than individuals with other genotypes. Previous studies on asthma indicated that the IL13-1055T allele increased gene transcription, which is in agreement with the fact that this cytokine enhances resistance to infection by schistosome in humans.

30

29.4 CONTROL OF INFECTION The prevalence and severity of schistosomal infections vary with age. Children and adolescents are infected most often and most heavily. In subjects older than 19 years, the prevalence of active infection and egg counts slowly declines that may reflect an increasing host immune response or a decreasing exposure to contaminated water as they age. In order to characterize the immune response associated to infection, several studies in experimental models of schistosomiasis have been developed. Capron et al. showed that rats are protected against S. mansoni by the passive transfer of schistosome-specific IgE antibodies31 which lead to the death of schistosome larvae by activating macrophages, eosinophils and platelets.31–35 Thus, the neonatal suppression of IgE increases rat’s susceptibility to S. mansoni infection.36 Moreover macrophage37 and eosinophils38,39 damage larvae through antibody dependent or independent pathway and young larvae are also damaged by the membrane attack complex resulting from complement activation.

438

Cytokine Gene Polymorphisms in Multifactorial Conditions

In a human population infected by S. mansoni or S. haematobium, an association between high IgE levels and resistance to reinfection after Praziquantel treatment was shown. This positive effect is counterbalanced by the opposite action of IgG4.14,40–42 The data suggest that protection against schistosome depends on a balance between these two isotypes: IgG4 probably competes with IgE for binding to the antigen.43 As IgE and eosinophils are highly dependent on IL-4, IL-13, and IL-5, these results suggest that protection against infection involves a Th2 immune response. This hypothesis was tested by analyzing T cell clones derived from resistant and susceptible subjects. A Th0/2 immune response producing high levels of IL-4 and IL-5 and low levels of IFN-g was associated to resistance, while susceptibility to infection was associated with a Th0/1 immune response producing high levels of IFN-g and low levels of IL-4 and IL-5.44,45 The role of host specific factors in the infection by S. mansoni and S. haematobium has been evaluated in Brazilian14 and Kenyan populations.46 Differences of infection levels are the consequence of individual capacity to fight against the parasite.46 Subjects with the highest infection intensities were found to be clustered within certain families.14 This suggested that infection levels may be influenced by inherited factors. These levels were adjusted for exposure, age, and gender. We tested, by a segregation analysis, whether the distribution of the trait (infection levels) in Brazilian families (20 pedigrees, 269 individuals) supported the hypothesis of a single locus controlling the trait. This analysis provided clear and convincing evidence that infection levels are controlled by a major co-dominant locus (SM1). This means that the distribution of infection levels in families is best explained by a model that includes age, gender, exposure, and a major co-dominant gene effect. Importantly, the effects of this genetic control account for half of the variance in infection levels indicating that gene(s) at this locus exerts a strong genetic control on infection. The frequency of the deleterious allele was estimated to be between 0.20 and 0.25; about 5% of the population was predisposed to a high level of infection, 60% was resistant, and 35% had an intermediate level of resistance. To confirm this genetic control and localize SM1, a whole genome scan study was performed. The linkage analysis was conducted on 142 Brazilian subjects belonging to 11 informative families (two large pedigrees, five smaller pedigrees, and four nuclear families). The genome was scanned with 246 polymorphic microsatellites, corresponding to a 15 cM map. Fifty-four markers provided maximum lod scores of above 0.1, but only one region on chromosome 5 (5q31–q33) showed suggestive linkage. Two adjacent markers, D5S393 and D5S410, provided a maximum lod score of 3.18 and 3.06 for a recombination fraction y of 0.09 and 0.15, respectively. To investigate this region, 11 additional markers were analyzed and significant linkage (lod score 4 3.3) was observed for two close markers. The maximum two-point lod score was 4.74 (y: 0.07) for D5S636 and 4.52 (y: 0.04) for the colony stimulating factor (CSF1R) according to the estimated marker allele frequencies. This successful mapping confirmed the existence of a major gene, denoted SM1, controlling the intensity of S. mansoni infection and showed that this gene is localized on chromosome 5q31–q33.17,22 This result was confirmed by Horstman et al. in Senegal.47 Moreover, linkage studies demonstrate that familial eosinophilia48,49 and total serum IgE concentration50 map to the same chromosomal region. The locus 5q31–q33 contains several genes of important cytokines for the regulation of the immune system like IL-4, IL-5, IL-9, IL-12, IL-13, the granulocyte-macrophage colony stimulating factor (CSF-2), the interferon regulatory factor 1 (IRF1), and the colony stimulating factor 1 receptor (CSF-1R). To test whether any polymorphisms in IL-4, IL-5, and IL-13 genes could affect susceptibility to infection, another study was carried out in a Malian population highly exposed to S. haematobium. No association was found for polymorphisms of IL4 and IL5 but analysis of polymorphisms IL13-1055C/T and IL13-591A/G showed that the IL13-1055C and IL13-591A alleles were preferentially transmitted to subjects with the highest infection.30

Susceptibility to Infection and Severe Disease in Schistosomiasis

439

This association between IL13-1055C and IL13-591A alleles and infection levels was detected as well with family-based association test as with multivariate regression analysis. Moreover, the infection levels may be estimated by measuring serum levels of circulating anodic antigen. Here again, based on this phenotype, multivariate regression analysis indicated that the IL13-1055C was associated to high circulating anodic antigen concentration. The fact that this association was found on these two phenotypes indicates that IL-13 is essential to the control of infection level and not to immunity against fecondity. Previous experiments performed on asthma have indicated that IL13-1055T/T genotype was associated with altered regulation of IL-13 and with elevated IgE levels.51,52 These association tests and functional assays results are consistent with the fact that in schistosomiasis infection a Th2 immune response has a protective effect. Schistosomes possess, among others, some proteases that aid their migration through the various skin layers53 and as a result, cause the induction of significant inflammatory reactions.54 Studies performed on mice indicated that after 3 h larvae had passed the epidermis and rapidly induce edema and dilation of peripheral blood vessels, followed by neutrophil rich focal infiltrates of cells in the underlying dermis. This influx of cells into the dermis is likely to be coordinated by the secretion of pro-inflammatory chemokines and cytokines. These pro-inflammatory cytokines not only ensure the infiltration of innate immune cells but also promote their activation. IL-13 may play a critical role as it activates eosinophils and stimulates their recruitment in the invading site.55 This cytokine can also inhibit the production of pro-inflammatory cytokines and indirectly drive T-cell differentiation into Th2. Indeed, IL-13 like IL-4 induces e transcription, a prerequisite for switching and IgE production.56,57 Moreover, IL-13 enhances the production of IgM and IgG and induces IgG4 and IgE synthesis by human B cells.56,58,59

29.5 SUSCEPTIBILITY TO ADVANCED SCHISTOSOMIASIS The fibrosis due to schistosoma infection is the consequence of the formation of a granuloma whose deleterious effects lead to an uncontrolled production of collagen. The extracellular matrix is mainly produced by the Ito cells after their differentiation into myofibroblasts.60–65 However, the granuloma formation and the repair process are regulated by several cytokines like TGF-b, IL-4, IL-5, IL-10, IL-12, IL-13, IFN-g, and TNF-a.66–69 Several studies have been carried out on murine models to evaluate the factors that determine host pathology. As we discussed previously, IgE seems to be a major mediator in host resistance to infection by triggering the functions of effector cells through interaction with the high affinity receptor FceRI. In addition to triggering effector cell function against the parasite, this interaction may also stimulate the production of IL-4 necessary to drive a Th2 response. To study the role of the Th2 response in the immunopathology of schistosomiasis, Sher et al. generated FceRI-deficient mice infected by S. mansoni. In the absence of the IgE/FceRI interaction, the infection develops normally and the mice show an aberrant immunopathologic response by enhanced egg-granuloma formation and hepatic fibrosis demonstrating that Th2 responses may influence host resistance to pathology in mice.70 Opposite results were found by Wynn et al. Indeed, they developed a mouse model using S. mansoni eggs and cytokine-deficient mice to induce highly polarized Th1 or Th2 environments, and used microarray analysis to analyze global gene expression profiles. They found that Th1-polarized mice develop small granulomas with less fibrosis whereas Th2 polarized mice formed large granulomas with massive collagen deposition.71,72 Other studies established that a prolonged Th1 response achieved significant suppression of hepatic

440

Cytokine Gene Polymorphisms in Multifactorial Conditions

granulomas and decreased collagen deposition in mice.73 By giving anti-IL-4 treatment to S. mansoni infected mice, Cheever et al. inhibited the development of hepatic fibrosis, showing the importance of IL-4 in the development of liver pathology in mice.74 A study on baboons also showed that periportal fibrosis is increased when profibrotic molecules including IL-4 and TGF-b are produced.75 TGF-b1 enhances collagen production and its level is markedly increased in the hepatic parenchyma of mice infected with schistosomiasis.76 IL-13 is also a key cytokine in Th2 response and its effects on hepatic fibrosis have been studied on a murine model. Thus, IL-13 deficient mice demonstrate significantly enhanced survival and reduced hepatic fibrosis that indicated this cytokine is a profibrotic agent.77 Moreover, a recent study provided evidence of a pathway of fibrogenesis that is IL-13 dependent but TGF-b1 independent, demonstrating the importance of IL-13 in fibrosis caused by S. mansoni.78 IL-13 receptor a2 is a decoy receptor of IL-13 which inhibits its activity. Mice with a target deletion of IL-13Ra2 fail to down-modulate granuloma formation and develop severe fibrosis.79–81 IL-13 seems to be a key target for therapeutic intervention. Thus, treatments with IL-13 inhibitors have been experimented in murine models of schistosomiasis and these studies demonstrated that IL-13 blockade stops the development of hepatic fibrosis caused by chronic Th2-mediated inflammatory responses.82,83 Together, these studies illustrate the central role played by IL-13 and IL-13Ra2 in murine severe schistosomiasis. IL-2 and IL-5 also play a role in immunopathology since in vivo treatment of S. mansoni infected mice with anti-IL-2 antibodies significantly diminished the size of granulomas in the liver and decreased hepatic fibrosis,84 and treatment of S. japonicum infected mice with anti-IL-5 antibodies diminished the size of granulomas but hepatic fibrosis was unaffected.85 The role played by IL-5 remains unclear and another study carried out by Sher et al. demonstrated that this cytokine is not required in granuloma formation induced by infection with S. mansoni.86 IL-10 is a major immunoregulatory cytokine influencing Th cell development and the production of several pro-inflammatory cytokines. To determinate its role in severe schistosomiasis, IL-10-deficient mice were infected with S. mansoni and the size of granuloma and fibrosis were analyzed. Surprisingly, these mice displayed a significant increase of granuloma size, but no increase of fibrosis and a normal down modulation of the chronic stage of infection were observed.69 Another study reveals that IL-10 plays a central role in the pathogenesis of schistosomiasis by regulating both Th1 and Th2 responses.87 Several studies on experimental models and in vitro have shown the key role of IFN-g and TNF-a in the processes of fibrogenesis and fibrolysis.88–94 Studies on mice model have established the antifibrogenic properties of IFNg.76,95 Several in vitro studies show that IFN-g inhibits the differentiation of Ito cells into myofibroblasts, collagen production, and the production of metalloprotease inhibitors implicated in the degradation of fibrous tissue. IFN-g can also stimulate the synthesis of these metalloproteases.91,93,96–99 Several immunological studies have been carried out to determine the cytokines involved in human periportal fibrosis caused by schistosomiasis. Immunological evaluations were performed by the measurement of secreted cytokines in peripheral blood mononuclear cells (PBMC) stimulated by parasite antigens. Thus, a study realized in Sudan shows that IFN-g may play a role in the protection of S. mansoni-infected patients against fibrosis, whereas TNF-a may aggravate the disease.100 Other studies demonstrate that advanced fibrosis is associated with higher levels of IL-4, IL-5, IL-10, IL-13, and TNF-a in supernatant of soluble egg antigen-stimulated PBMC compared to early or moderate fibrosis.101,102 Another study highlights that periportal fibrosis is associated with cytokine production profiles that vary with age and gender.103 Thus, children, adult males and adult females had different factors associated with fibrosis. Fibrosis in children was associated with low IL-10 levels. Adult females at lowest risk of fibrosis had relatively high IFN-g levels whereas those at higher risk presented relatively

Susceptibility to Infection and Severe Disease in Schistosomiasis

441

high levels of TNF-a. Adult males fibrosis was associated with high TNF-a levels or intermediate TNF-a combined with low RANTES levels. A study was carried out in a Sudanese population living in an endemic area for S. mansoni.104 The degree of fibrosis was identified by ultrasound (which is a non-invasive tool to evaluate fibrosis) and three grades were determined: early (FI), moderate (FII) and advanced (FIII) fibrosis. Gender may be a risk factor because they observed a low prevalence of FII in women aged 20–30 compared with men of the same age. Level and duration of infection were shown to play an important role in the progression of disease toward FII. Moreover, FII and FIII were clustered in certain pedigrees which suggested that inherited factors are important in the progression of fibrosis from FII to FIII. To analyze this genetic control and to localize the gene implied, a linkage analysis was performed in 65 Sudanese pedigrees from the same village. Results provide evidence for a major locus called SM2 and mapped in 6q22–q23 region closely linked to IFN-gR1 gene encoding the receptor of the antifibrogenic cytokine IFN-g.24,105,106 The localization of this locus was recently confirmed on an Egyptian population.107 Further studies tested whether polymorphisms located in the IFN-g locus could alter the susceptibility to periportal fibrosis caused by S. mansoni. Two polymorphisms (IFNGþ2109A/G and IFNGþ3810G/A) were found to be associated with the disease. The IFNGþ2109A/G polymorphism is associated with a higher risk for developing periportal fibrosis, whereas the IFNGþ3810G/A polymorphism is associated with less periportal fibrosis. No subject was carrying the both polymorphisms in the same time in the studied population. These polymorphisms resulted in changes in nuclear protein interactions with the intronic regions of the gene, suggesting that they may modify IFN-g mRNA expression.28 Four polymorphisms in TNF-a gene (TNFA
376G/A, TNFA
308 G/A, TNFA
238 G/A and TNFAþ488 G/A) were also analyzed but no evidence of association with periportal fibrosis was found.27 However, the authors didn’t exclude the possibility that these polymorphisms play a minor role in the disease development or that other polymorphisms of this gene could be associated with periportal fibrosis. Hirayama et al. have analyzed polymorphisms of HLA class II and IL-13 genes in patients presenting liver fibrosis caused by S. japonicum in China.26,29 They found that the frequency of the HLA-DRB5*0101 allele and the IL-13 promoter A/A genotype were elevated in fibrotic patients (grades I, II, III). They also indicate that PBMC cells from IL-13PA/A donors produced much higher amount of mRNA than those of IL-13PA/B donors 24 h after the stimulation with PHA.

29.6 CONCLUSION These studies on human schistosomiasis have allowed us to describe, for the first time in an infectious disease, that the control of infection and disease in S. mansoni-infected subjects are distinct.108 Two major loci called SM1 and SM2 have been identified. The existence of these controls and the position of the genes involved were confirmed in different populations.47,107 Integrated epidemiological–immunological–genetic approaches allow us to identify genes and polymorphisms associated to these controls. However, it will be careless to think that this list is complete. Moreover, the genetic control of the human susceptibility to schistosomes may be more complicated in some populations in which bacterial and viral co-infections are dominant. Identification and characterization of all the factors involved in these controls will result in a better understanding of this pathology and will allow us to develop in the future some new therapeutic approaches that will be focused on critical steps of the pathogenic process and that will be hopefully more efficient.

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Cytokine Gene Polymorphisms in Multifactorial Conditions

ACKNOWLEDGMENT The authors thank Pr. Alain Dessein for his constant support and for helpful discussions and critics of the manuscript.

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Index

A Acquired immunodeficiency syndrome, 395–412 CCR2 gene in, 400 CCR5 gene in, 398–400 cytokine receptor gene polymorphisms, 404 description of, 395 genetic studies, 397–398 highly active antiretroviral therapy, 396 IFNG polymorphisms, genetic associations, 164 nucleoside reverse transcriptase inhibitors, 396 pathogenesis, 396–397 polymorphisms chemokine system genes, 398–402 cytokines genes, 402–404 RANTES, 400–401 T helper 1-T helper 2 cytokine gene polymorphisms, 402 treatments, 396 tumor necrosis factor alpha, gene polymorphisms, 402–404 viral cycle, 396 Acquired immunodeficiency syndrome risk/ progression, IFNG polymorphisms, genetic associations, 164 Acute graft-versus-host disease, interleukin-1 gene cluster, polymorphisms, disease association, 102 Acute kidney rejection, interleukin-2/ interleukin-2R polymorphisms, 113 Adaptive immunity, cytokines of, 10–25 T cell development, proliferation, death, and survival, 10–13 interleukin-2, 11–12 interleukin-7, 10–11 interleukin-15, 12–13 interleukin-21, 13 T helper 1 immune responses, 13–22 interferon-gamma, 17–18 interleukin-4, 20–21 interleukin-5, 21 interleukin-12, 13–14

interleukin-13, 21–22 interleukin-18, 16–17 interleukin-23, 14–15 interleukin-27, 15–16 lymphotoxins, 18–19 T helper 2 immune responses, 19–22 Admixture mapping, 57 AIDS. See Acquired immunodeficiency syndrome Alcoholic chronic pancreatitis, IFNG polymorphisms, genetic associations, 163 Alcoholic hepatic fibrosis, interleukin-1 gene cluster, polymorphisms, disease association, 102 Alcoholism, interleukin-1 gene cluster, polymorphisms, disease association, 102 Allergy IFNG polymorphisms, genetic associations, 163 polymorphisms, chemokines, receptors, 215 Allograft nephropathy, IFNG polymorphisms, genetic associations, 164 Alopecia areata, 102 interleukin-1 gene cluster, polymorphisms, disease association, 102 Alpha gene polymorphisms, interleukin-2 receptor, 115 Alzheimer’s disease IFNG polymorphisms, genetic associations, 165 interleukin-10 association, 135 interleukin-1 gene cluster, polymorphisms, disease association, 102 American Rheumatism Association for Classification of Systemic Lupus Erythematosus, revised criteria, 258 Ankylosing spondylitis, interleukin-1 gene cluster, polymorphisms, disease association, 102 Antiviral activity, cytokines with, 9–10 type I interferons, 9–10 447

448

Cytokine Gene Polymorphisms in Multifactorial Conditions

Aplastic anaemia, IFNG polymorphisms, genetic associations, 165 Arthritis chronic, juvenile, interleukin-1 gene cluster, polymorphisms, disease association, 103 idiopathic, juvenile, IFNG polymorphisms, genetic associations, 162 macrophage migration inhibitory factor, 195 pauciarticular, juvenile, interleukin-2/ interleukin-2R polymorphisms, 113 reactive, interleukin-10 association, 136 rheumatoid IFNG polymorphisms, genetic associations, 162 interleukin-10 association, 136 interleukin-1 gene cluster, polymorphisms, disease association, 103 interleukin-2/interleukin-2R polymorphisms, 113 Asthma, 229–244 bronchial challenges, 231 cytokines, 233–238 eosinophils, 230 genetics, 231 IFNG polymorphisms, genetic associations, 163 interleukin-10 association, 135 phenotyping, 230–231 total serum immunoglobulin E, 230 Atherosclerosis, 363–378 eotaxin, 364–368 interferon-gamma, 372–373 interleukin-1, 368 interleukin-6, 368–370 interleukin-10, 370–371 RANTES, 364–368 transforming growth factor-b1, 372 tumor necrosis factor, 371–372 Atopic diseases, interleukin-1 gene cluster, polymorphisms, disease association, 102 Atopy, 229–244 bronchial challenges, 231 cytokines, 233–238 eosinophils, 230 genetics, 231 mechanisms, 232–233 phenotyping, 230–231 total serum immunoglobulin E, 230 Autoimmune disease interleukin-2 biology, polymorphisms, 110–111 allotypes, 110–111 molecular mechanisms, 111

polymorphisms, chemokines, receptors, 213 tumor necrosis factor polymorphisms, 181–182 Autoimmunity, multiple sclerosis, 291–293

B Beta gene polymorphisms, interleukin-2 receptor, 115 Biology of cytokines, 3–34 adaptive immunity, cytokines of, 10–25 T cell development, proliferation, death, and survival, 10–13 interleukin-2, 11–12 interleukin-7, 10–11 interleukin-15, 12–13 interleukin-21, 13 T helper 1 immune responses, 13–22 interferon-gamma, 17–18 interleukin-4, 20–21 interleukin-5, 21 interleukin-12, 13–14 interleukin-13, 21–22 interleukin-18, 16–17 interleukin-23, 14–15 interleukin-27, 15–16 lymphotoxins, 18–19 T helper 2 immune responses, 19–22 antiviral activity, cytokines with, 9–10 type I interferons, 9–10 chemokines, 25–27 immune response regulation, 22–25 interleukin-10-related cytokines, 23–24 interleukins-10, 23–24 transforming growth factor-beta, 24–25 innate immunity, cytokines of, 4–10 cytokines in inflammation, 4–9 gp130 receptor subunit, 8–9 interleukin-1, 7–8 interleukin-6, 8–9 tumor necrosis factor, 4–7 phenotype cytokine-deficient mice, 5 cytokine receptor-deficient mice, 6 BLASTn. See Nucleotide-nucleotide BLAST Bone marrow transplantation, graft-versus-host disease after, IFNG polymorphisms, genetic associations, 164 Breast cancer, IFNG polymorphisms, genetic associations, 165 Bronchial challenges, asthma, atopy, 231 Bronchiolitis obliterans after lung transplant, IFNG polymorphisms, genetic associations, 164 Brucellosis, IFNG polymorphisms, genetic associations, 163

449

Index

C Cancer. See also under specific cancer type polymorphisms, chemokines, receptors, 215–216 tumor necrosis factor polymorphisms, 180–181 Candidate-gene/whole-genome association studies, 54–55 false positives, 55–57 statistical fluctuations, chance/multiple testing issues, 56 replication, 55–57 detection, sample sizes, 56–59 population stratification, 55 sample sizes, 56–59 statistical fluctuations by chance/multiple testing issues, 56 technical artifacts, 55–56 statistical fluctuations, chance/multiple testing issues, 56 Cardiac allograph outcome, interleukin-2/ interleukin-2R polymorphisms, 113 Cardiac disease, rheumatic, interleukin-10 association, 136 Cardiovascular diseases, polymorphisms, chemokines, receptors, 213–214 Case-control study, association test statistic, 50 CCR2 gene, acquired immunodeficiency syndrome, 400 CCR5 gene, acquired immunodeficiency syndrome, 398–400 Cervical cancer IFNG polymorphisms, genetic associations, 165 interleukin-10 association, 135 Chagas disease, 416–419 Chemokines, 25–27 Chromosome 5q23.1–q31.1 cytokine cluster, 121–132 evolution, 122–123 functions, 123–124 genomic orientation, 122–123 linkage, 125–130 variants, 124–125 Chronic allograft nephropathy, IFNG polymorphisms, genetic associations, 164 Chronic colitis, macrophage migration inhibitory factor, 195 Chronic hepatitis B, IFNG polymorphisms, genetic associations, 163 Chronic hepatitis C, 343–345 IFNG polymorphisms, genetic associations, 163

Chronic inflammatory bowel diseases, 338–340 Cirrhosis, hepatitis C virus-induced, interleukin-1 gene cluster, polymorphisms, disease association, 102 Coeliac disease IFNG polymorphisms, genetic associations, 163 interleukin-10 association, 135 Colitis, ulcerative, interleukin-2/interleukin-2R polymorphisms, 113 Colorectal cancer, interleukin-10 association, 135 Complex genetic disorders, genetic contributions in, 36 Coronary atherosclerosis, interleukin-1 gene cluster, polymorphisms, disease association, 102 Coronary stent, restenosis after, IFNG polymorphisms, genetic associations, 163 Coronary vasculopathy after heart transplant, IFNG polymorphisms, genetic associations, 164 Cutaneous malignant melanoma, IFNG polymorphisms, genetic associations, 165 Cytokine blockade, multiple sclerosis, 298–299 Cytokine-deficient mice, phenotype of, 5 Cytokine gene nucleotide sequence alignments, 73–82 MAP, 74 Multalin, 74–75 nucleotide-nucleotide BLAST, 75–76 pre-generated cytokine gene nucleotide sequence alignments, 77–80 dbCFC, Cytokine Family cDNA Database, 77–79 human cytokine nucleotide sequence alignments, 79–80 mouse cytokine nucleotide sequence alignments, 79–80 UCSC Genome Bioinformatics, 77 single nucleotide polymorphisms, 73 SNP BLAST, 76–77 user-generated cytokine gene nucleotide sequence alignments, 74–77 Cytokine pharmacogenetics, 251–252 interleukin-1, 252 tumor necrosis factor, 251–252 Cytokine receptor-deficient mice, phenotype of, 6 Cytokines in inflammation, 4–9

D dbCFC, Cytokine Family cDNA Database, 77–79

450

Cytokine Gene Polymorphisms in Multifactorial Conditions

Death of T cells, 10–13 Development of T cells, 10–13 Diabetes, 305, 308–310 anti-inflammatory agents, 310 cytokine gene polymorphisms, 310–313 interleukin-1 gene cluster, polymorphisms, disease association, 102 interleukin-2/interleukin-2R polymorphisms, 113 Diabetic nephropathy, interleukin-1 gene cluster, polymorphisms, disease association, 102 Duodenal ulcer disease, interleukin-1 gene cluster, polymorphisms, disease association, 102

E Early-onset pauciarticular juvenile chronic arthritis, interleukin-2/interleukin-2R polymorphisms, 113 Encephalomyelitis, IFNG polymorphisms, genetic associations, 163 Endometriosis, IFNG polymorphisms, genetic associations, 165 ENSEMBL, 69–70 learning to use, 69–70 navigation tips, 70 resources, 70 typical uses, 70 Environmental factors, genes, interplay of, 42–43 Eotaxin, atherosclerosis, 364–368 Epidermodysplasia verruciformis, interleukin-10 association, 135 Epstein-Barr virus infection, interleukin-1 gene cluster, polymorphisms, disease association, 102 Ethnic/racial differences, single nucleotide polymorphism frequencies, 185 European Molecular Biology Laboratory. See ENSEMBL Examples of genotyping methods, 85–90

F False positives, candidate-gene/whole-genome association studies, 55–57 population stratification, 55 technical artifacts, 55–56 Fibrogenic mediators, pulmonary fibrosis, 352–355 Fibrosis after lung transplant, IFNG polymorphisms, genetic associations, 164

G Gamma chain gene polymorphisms, interleukin-2 receptor, 115 Gastric cancer, 337–338 interleukin-10 association, 135 interleukin-1 gene cluster, polymorphisms, disease association, 102 Gastrointestinal disease, 337–350 chronic inflammatory bowel diseases, 338–340 gastric cancer, 337–338 Helicobacter infection, 337–338 Gene discovery strategies, complex traits, 38 Genetics, multifactorial disorders, 35–46 complex genetic disorders, genetic contributions in, 36 environmental factors, genes, interplay of, 42–43 future developments, 43–44 gene discovery strategies, complex traits, 38 haplotype blocks, 40 heterogeneity, 37 mendelian vs. complex traits, 36 phenotype, definition of, 41–42 relative risk, examples, 41 Genotyping methods, compared, 86 Giant cell arteritis, IFNG polymorphisms, genetic associations, 162 Glucocorticoids, macrophage migration inhibitory factor, 200 Golden Path, UCSC bioinformatics, 66–68 learning to use, 67 navigation tips, 67–68 resources, 67 typical uses, 68 gp130 receptor subunit, 8–9 Graft-versus host disease after bone marrow transplantation, 164 interleukin-10 association, 135 interleukin-1 gene cluster, polymorphisms, disease association, 102 Graves’ disease IFNG polymorphisms, genetic associations, 162 interleukin-1 gene cluster, polymorphisms, disease association, 102

H HAART. See Highly active antiretroviral therapy Haplotype blocks, 40 Haplotypes, interleukin-1, 101–104 HapMap era, disease-gene discovery, 39–41

Index Hay fever, IFNG polymorphisms, genetic associations, 163 HCV. See Hepatitis C Heart transplant coronary vasculopathy after, IFNG polymorphisms, genetic associations, 164 interleukin-2/interleukin-2R polymorphisms, 113 rejection after, IFNG polymorphisms, genetic associations, 164 Helicobacter infection, 337–338 IFNG polymorphisms, genetic associations, 163 Hematopoiesis, tumor necrosis factor polymorphisms, 178 Henoch-Schonlein disease, interleukin-1 gene cluster, polymorphisms, disease association, 102 Hepatic fibrosis, alcoholic, interleukin-1 gene cluster, polymorphisms, disease association, 102 Hepatitis B, 341–343 IFNG polymorphisms, genetic associations, 163 Hepatitis C, 343–345 cirrhosis, interleukin-1 gene cluster, polymorphisms, disease association, 102 IFNG polymorphisms, genetic associations, 163 Hepatocellular carcinoma, IFNG polymorphisms, genetic associations, 165 Herpes zoster, interleukin-10 association, 135 Heterogeneity, 37 Highly active antiretroviral therapy, acquired immunodeficiency syndrome, 396 Human interleukin-2/interleukin-2R polymorphisms, 111–115 Hypertension, IFNG polymorphisms, genetic associations, 165

I Idiopathic pulmonary fibrosis, IFNG polymorphisms, genetic associations, 163 Idiopathic recurrent miscarriage, interleukin-1 gene cluster, polymorphisms, disease association, 102 IFNG polymorphisms, genetic associations, 162–165 IgA nephropathy, 102, 163 Immune response regulation, 22–25 interleukin-10-related cytokines, 23–24

451 interleukins-10, 23–24 Immunoglobulin E, asthma, atopy, 230 Infectious disease polymorphisms, chemokines, receptors, 212–213 tumor necrosis factor polymorphisms, 180 Inflammation cytokines in, 4–9 Helicobacter pylori, 163 Inflammatory bowel disease, 338–340 IFNG polymorphisms, genetic associations, 163 interleukin-10 association, 136 interleukin-1 gene cluster, polymorphisms, disease association, 102 interleukin-2/interleukin-2R polymorphisms, 113 Inflammatory cytokines, pulmonary fibrosis, 352–353 Inflammatory myopathies, juvenile, interleukin-1 gene cluster, 103 Innate immunity, cytokines of, 4–10 cytokines in inflammation, 4–9 gp130 receptor subunit, 8–9 interleukin-1, 7–8 interleukin-6, 8–9 tumor necrosis factor, 4–7 Integrated bioinformatic resources, 61–72 annotation, 64–65 challenges, 63 content control, 65–66 direct sequence navigation, 66 ENSEMBL, 69–70 learning to use, 69–70 navigation tips, 70 resources, 70 typical uses, 70 fundamental concepts, 64–66 integrative bioinformatic resources, 66–72 literature, 65 mapping, 64–65 National Center for Biotechnology Information, 68–69 learning to use, 68 navigation tips, 69 resources, 69 uses, 69 navigation, 65–66 presentation metaphors, 65–66 protein structure, function, 65 scope, 63 sequence, 64 simple text search, 66

452

Cytokine Gene Polymorphisms in Multifactorial Conditions

Integrated bioinformatic resources [continued ] SNPper, 70–72 learning to use it, 71 navigation tips, 71 resources, 71 uses, 71–72 specific resource types, 64–65 UCSC bioinformatics (Golden Path), 66–68 learning to use, 67 navigation tips, 67–68 resources, 67 typical uses, 68 using resources, 66 Interferon, multiple sclerosis, 297–298 Interferon gamma, 17–18 atherosclerosis, 372–373 interleukin-26, interleukin-22 cytokine gene cluster, 157–174 disease associations, 160–167 haplotype structure, 158–160 intron 1, allelic variation, 160 longevity, 386 multiple sclerosis, 294–295 Sjo¨gren’s syndrome, 285 Interleukin-1, 7–8, 95–108 atherosclerosis, 368 cytokine pharmacogenetics, 252 expression, interleukin-1 genes, 97 functions of interleukin-1 family genes, 97–99 haplotypes, 101–104 interleukin-1 family proteins, 96–97 interleukin-1Ra protein levels, effect of gene polymorphisms, 100–101 linkage disequilibrium within, 101–104 longevity, 380–385 multiple sclerosis, 296 polymorphism, 99–100 disease association, 102–103 psoriasis, 328–329 rheumatoid arthritis, 247–248 single marker polymorphism, disease associations, 101 Sjo¨gren’s syndrome, 284–285 spondylo-arthropathies, 250 structure of, 95–96 Interleukin-2, 11–12 alpha gene polymorphisms, interleukin-2 receptor, 115 autoimmune diseases, 110–111 allotypes, 110–111 molecular mechanisms, 111 beta gene polymorphisms, interleukin-2 receptor, 115 as bi-functional cytokine, 109–110

biology, polymorphisms, 109–120 gamma chain gene polymorphisms, interleukin-2 receptor, 115 human interleukin-2/interleukin-2R polymorphisms, 111–115 longevity, 388–389 rs2069762 single nucleotide polymorphism, 112–114 Interleukin-4, 20–21 multiple sclerosis, 296–297 Sjo¨gren’s syndrome, 285 Interleukin-5, 21 Interleukin-6, 8–9 atherosclerosis, 368–370 longevity, 385–386 rheumatoid arthritis, 248 Sjo¨gren’s syndrome, 284 spondylo-arthropathies, 250 Interleukin-7, 10–11 Interleukin-8, longevity, 388–389 Interleukin-10, 23–25, 133–146 atherosclerosis, 370–371 disease association studies, 134–137 expression, 134 genetic variation, 134 haplotypes, 139 longevity, 386–388 multiple sclerosis, 297 pairwise linkage disequilibrium, 139 psoriasis, 330 resequencing, 137 rheumatoid arthritis, 248–249 single nucleotide polymorphism, 138–139 Sjo¨gren’s syndrome, 279–283 spondylo-arthropathies, 250 systemic lupus erythematosus, 269–271 variation, 137–138 Interleukin-12, 13–14 longevity, 388–389 multiple sclerosis, 295 psoriasis, 329 Interleukin-13, 21–22 Interleukin-15, 12–13 Interleukin-18, 16–17 Interleukin-19, 147–156 functions, 148–150 molecular biology, 147–148 molecular genetic studies, 150–153 Interleukin-21, 13 Interleukin-22, interferon gamma, 157–174 disease associations, 160–167 haplotype structure, 158–160 intron 1, allelic variation, 160 Interleukin-23, 14–15 Interleukin-26, interferon gamma, 157–174

453

Index disease associations, 160–167 haplotype structure, 158–160 intron 1, allelic variation, 160 Interleukin-27, 15–16 Interleukin-2R polymorphisms, disease association studies, 113 Interleukin-1Ra protein levels, effect of gene polymorphisms, 100–101 Intermediate uveitis, IFNG polymorphisms, genetic associations, 163 Interstitial lung diseases, 355–357

J Juvenile chronic arthritis, interleukin-1 gene cluster, polymorphisms, disease association, 103 Juvenile idiopathic arthritis, IFNG polymorphisms, genetic associations, 162 Juvenile idiopathic inflammatory myopathies, interleukin-1 gene cluster, polymorphisms, disease association, 103

K Kidney rejection, interleukin-2/interleukin-2R polymorphisms, 113

L Large-scale genotyping methods, 85–88 allele-specific primer extension with ligation, 87–88 gap-filled ligation with molecular inversion probes, 87 long-range resequencing, unique sequences on microarrays, 86–87 primer extension with long probes, 87 random whole genome markers on microarrays, 85–86 targeted single nucleotide polymorphisms, highly multiplexed assays on microarrays, 87–88 Leishmaniasis, 416–419 Leprosy, 419–423 IFNG polymorphisms, genetic associations, 163 Lichen sclerosis, interleukin-1 gene cluster, polymorphisms, disease association, 103 Linkage analysis, 48–50 defined, 48–49 power, 50 result interpretation, 49–50 study design, 48–49

Linkage disequilibrium, 50–57 definition, 50–52 within interleukin-1, 101–104 marker selection, 52–54 selection of markers, 52–54 study design, 50–52 Liver, 340–345 chronic hepatitis C virus, 343–345 hepatitis B, 341–343 macrophage migration inhibitory factor, 197 transplant rejection, 164 Longevity, 379–394 interferon-gamma, 386 interleukin-2, 388–389 interleukin-6, 385–386 interleukin-8, 388–389 interleukin-10, 386–388 interleukin-12, 388–389 interleukin-1 cluster, 380–385 transforming growth factor-beta, 386–388 tumor necrosis factor, 380–385 Lung cancer, small cell, interleukin-10 association, 135 Lung transplant bronchiolitis obliterans after, IFNG polymorphisms, genetic associations, 164 fibrosis after, IFNG polymorphisms, genetic associations, 164 Lupus, 257–278 American Rheumatism Association for Classification of Systemic Lupus Erythematosus, revised criteria, 258 IFNG polymorphisms, genetic associations, 162 IL10 polymorphisms, association studies, 269–271 interleukin-10 association, 136 interleukin-1 gene cluster, polymorphisms, disease association, 103 polymorphisms, 258–268 tumor necrosis factor genes, association studies, 268–269 Lupus nephritis, IFNG polymorphisms, genetic associations, 163 Lymphoid organ development, tumor necrosis factor polymorphisms, 178 Lymphotoxins, 18–19

M Macrophage migration inhibitory factor, 191–206 arthritis, 195 association with disease, 198–199 chronic colitis, 195

454

Cytokine Gene Polymorphisms in Multifactorial Conditions

Macrophage migration inhibitory factor [continued] disease and, 194–197 as enzyme, 193–194 functions, 192–194 gene, 197–200 glucocorticoids, 200 as hormone, 193 human gene, polymorphisms of, 197–198 liver, 197 mechanism of action, 194 as pro-inflammatory cytokine, 192–193 promoter activity of, 199–200 protein, 192 psoriasis, 195, 330–331 regulation, 194 sarcoidosis, 195 tumors, 195–197 Malaria IFNG polymorphisms, genetic associations, 163 interleukin-1 gene cluster, polymorphisms, disease association, 103 Malignancy, tumor necrosis factor polymorphisms, 178 Malignant melanoma, cutaneous, IFNG polymorphisms, genetic associations, 165 Medium-scale genotyping methods, 88–89 capillary electrophoresis of mobility tags, multiplex ligation detection, 88–89 fluorescence detection on tag arrays, multiplex PCR and primer extension detection, 88 lass spectrometry, multiplex PCR with primer extension detection, 88 Mendelian vs. complex traits, 36 Metalloproteinases, pulmonary fibrosis, 352–354 MIF. See Macrophage migration inhibitory factor Miscarriage, idiopathic, recurrent, interleukin-1 gene cluster, polymorphisms, disease association, 102 Multalin, 74–75 Multifactorial disorder genetics, 35–46 complex genetic disorders, genetic contributions in, 36 environmental factors, genes, interplay of, 42–43 future developments, 43–44 gene discovery strategies, complex traits, 38 haplotype blocks, 40 HapMap era, disease-gene discovery, 39–41 heterogeneity, 37 mendelian vs. complex traits, 36 phenotype, definition of, 41–42 relative risk, examples, 41

Multiple sclerosis, 289–304 autoimmune hypothesis, 291–293 cytokine blockade, 298–299 genetic studies, cytokines, 294–297 IFNG polymorphisms, genetic associations, 162 interferon, 297–298 interferon gamma, 294–295 interleukin-1, 103, 296 interleukin-4, 296–297 interleukin-10, 297 interleukin-12, 295 interleukin-2/interleukin-2R polymorphisms, 113 phenotypic variability, 290–291 role of cytokine polymorphism, 293–294 treatment, 297–299 tumor necrosis factor alpha, 295–296 Myasthenia gravis, interleukin-1 gene cluster, 103 Mycobacterial diseases, 419–423

N Nasal polyposis, interleukin-1 gene cluster, 103 Nasopharyngeal cancer, interleukin-10 association, 135 National Center for Biotechnology Information, 68–69 learning to use, 68 navigation tips, 69 resources, 69 uses, 69 NCBI. See National Center for Biotechnology Information Nephritis, lupus, IFNG polymorphisms, genetic associations, 163 Neurodegenerative disorders, polymorphisms, chemokines, receptors, 215 Non-Hodgkin’s lymphoma, interleukin-10 association, 135 NRTIs. See Nucleoside reverse transcriptase inhibitors Nucleoside reverse transcriptase inhibitors, acquired immunodeficiency syndrome, 396 Nucleotide-nucleotide BLAST, 75–76 Nucleotide sequence alignments, cytokine gene, 73–82 MAP, 74 Multalin, 74–75 nucleotide-nucleotide BLAST, 75–76 pre-generated cytokine gene nucleotide sequence alignments, 77–80

Index dbCFC, Cytokine Family cDNA Database, 77–79 human cytokine nucleotide sequence alignments, 79–80 mouse cytokine nucleotide sequence alignments, 79–80 UCSC Genome Bioinformatics, 77 single nucleotide polymorphisms, 73 SNP BLAST, 76–77 user-generated cytokine gene nucleotide sequence alignments, 74–77

O Osteoarthritis, 250–251 interleukin-10 association, 136 Osteoporosis, interleukin-1 gene cluster, polymorphisms, disease association, 103

P Pancreatitis alcoholic, IFNG polymorphisms, genetic associations, 163 IFNG polymorphisms, genetic associations, 163 Paravirus B19, interleukin-10 association, 135 Parkinson’s disease, interleukin-1 gene cluster, polymorphisms, disease association, 103 Pauciarticular juvenile chronic arthritis, interleukin-2/interleukin-2R polymorphisms, 113 Periodontitis interleukin-10 association, 136 interleukin-1 gene cluster, 103 interleukin-2/interleukin-2R, 113 Phenotype cytokine-deficient mice, 5 cytokine receptor-deficient mice, 6 definition of, 41–42 Pneumococcus, interleukin-10 association, 136 Pneumonia, interleukin-10 association, 136 Polymorphism admixture mapping, 57 candidate-gene/whole-genome association studies, 54–55 false positives, 55–57 replication, 55–57 population stratification, 55 technical artifacts, 55–56 case-control study, association test statistic, 50 chemokines, receptors, 207–226 allergy, 215

455 autoimmune diseases, 213 cancer, 215–216 cardiovascular diseases, 213–214 CCR2/CCL2 axis, 210 CCL2 variants, 210 CCR2 variants, 210 CCR5/CCL5 axis, 208–210 CCL5 variants, 209–210 CCR5D32, 209 CX3CR1/CX3CL1 axis, 210–211 CX3CR1 gene promoter polymorphisms, 211 CX3CR1 variants, 211 CXCR4/CXCL12 axis, 211–212 CXCL12 variants, 212 CXCR4 variants, 211 disease associations, 212–216 infectious diseases, 212–213 neurodegenerative disorders, 215 transplantation, 214–215 interleukin-1, 99–100 linkage analysis, 48–50 defined, 48–49 power, 50 result interpretation, 49–50 study design, 48–49 linkage disequilibrium, 50–57 definition, 50–52 selection of markers, 52–54 study design, 50–52 statistical approaches, 47–60 systemic lupus erythematosus, 258–268 Polymyalgia rheumatica IFNG polymorphisms, genetic associations, 162 interleukin-1 gene cluster, polymorphisms, disease association, 103 Power, linkage analysis, 50 Pre-eclampsia, interleukin-1 gene cluster, polymorphisms, disease association, 103 Pre-generated cytokine gene nucleotide sequence alignments, 77–80 dbCFC, Cytokine Family cDNA Database, 77–79 human cytokine nucleotide sequence alignments, 79–80 mouse cytokine nucleotide sequence alignments, 79–80 UCSC Genome Bioinformatics, 77 Pregnancy loss, recurrent, interleukin-10 association, 136 Pro-inflammatory cytokine, macrophage migration inhibitory factor, 192–193 Proliferation of T cells, 10–13 Protozoan disease, 416–419

456

Cytokine Gene Polymorphisms in Multifactorial Conditions

Psoriasis, 321–336 IFNG polymorphisms, genetic associations, 163 interferon genes, 328 interleukin-1, 103, 328–329 interleukin-2, 113 interleukin-10, 136, 330 interleukin-12, 329 macrophage migration inhibitory factor, 195, 330–331 tumor necrosis factor gene cluster, 323–327 vascular endothelial growth factor, 330–331 Pulmonary fibrosis, 351–362 fibrogenic mediators, 352–355 gene-environment interactions, 357 gene-gene interactions, 357 IFNG polymorphisms, genetic associations, 163 inflammatory cytokines, 352–353 interstitial lung diseases, 355–357 metalloproteinases, 352–354 T helper 1 cytokines, 353–354 Puumala hantavirus infection, interleukin-1 gene cluster, polymorphisms, disease association, 103

R Racial differences, single nucleotide polymorphism frequencies, 185 RANTES acquired immunodeficiency syndrome, 400–401 atherosclerosis, 364–368 Reactive arthritis, interleukin-10 association, 136 Recurrent pregnancy loss, interleukin-10 association, 136 Regulation of immune response, 22–25 interleukins-10, 23–24 transforming growth factor-beta, 24–25 Rejection after heart transplant, IFNG polymorphisms, genetic associations, 164 Rejection after liver transplant, IFNG polymorphisms, genetic associations, 164 Rejection after renal transplant, IFNG polymorphisms, genetic associations, 164 Relative risk, examples, 41 Renal transplant, rejection after, IFNG polymorphisms, genetic associations, 164 Research resources, integrated bioinformatic, 61–72 annotation, 64–65 challenges, 63 content control, 65–66 direct sequence navigation, 66

ENSEMBL, 69–70 learning to use, 69–70 navigation tips, 70 resources, 70 typical uses, 70 fundamental concepts, 64–66 integrative bioinformatic resources, 66–72 literature, 65 mapping, 64–65 National Center for Biotechnology Information, 68–69 learning to use, 68 navigation tips, 69 resources, 69 uses, 69 navigation, 65–66 presentation metaphors, 65–66 protein structure, function, 65 scope, 63 sequence, 64 simple text search, 66 SNPper, 70–72 learning to use it, 71 navigation tips, 71 resources, 71 uses, 71–72 specific resource types, 64–65 UCSC bioinformatics (Golden Path), 66–68 learning to use, 67 navigation tips, 67–68 resources, 67 typical uses, 68 using resources, 66 Restenosis after coronary stent, 163 protection after PTCA, 103 Rheumatic disease, 245–256 cardiac, interleukin-10 association, 136 cytokine pharmacogenetics, 251–252 interleukin-1, 252 tumor necrosis factor, 251–252 osteoarthritis, 250–251 rheumatoid arthritis, 246–249 interleukin-1, 247–248 interleukin-6, 248 interleukin-10, 248–249 tumor necrosis factor, 246–247 spondylo-arthropathies, 249–250 interleukin-1, 250 interleukin-6, 250 interleukin-10, 250 tumor necrosis factor, 249–250 Rheumatoid arthritis, 246–249 IFNG polymorphisms, genetic associations, 162

Index interleukin-1, 103, 247–248 interleukin-6, 248 interleukin-10, 136, 248–249 interleukin-2/interleukin-2R polymorphisms, 113 tumor necrosis factor, 246–247 rs2069762 single nucleotide polymorphism, interleukin-2, 112–114

S Sanger Institute. See ENSEMBL Sarcoidosis, macrophage migration inhibitory factor, 195 Scarring trachoma, IFNG polymorphisms, genetic associations, 163 Schistosomiasis, 431–446 genetic factors, 433–437 hepatic fibrosis in, IFNG polymorphisms, genetic associations, 163 infection control, 437–439 life cycle, 431–432 pathology, 432–437 susceptibility, 439–441 Schizophrenia interleukin-10 association, 136 interleukin-2/interleukin-2R polymorphisms, 113 Sclerosis, interleukin-1 gene cluster, polymorphisms, disease association, 103 Sepsis, interleukin-1 gene cluster, polymorphisms, disease association, 103 Severe hepatic fibrosis in schistosomiasis, IFNG polymorphisms, genetic associations, 163 Severity of inflammation in Helicobacter pylori infection, IFNG polymorphisms, genetic associations, 163 Single-lex genotyping methods, 89–90 allele-specific hybridization, with probe cleavage, 89 allele-specific invasive probe cleavage, 89 fluorescence polarization detection, primer extension with, 90 melting curve analysis, kinetic PCR with, 89 Single marker polymorphism, interleukin-1, disease associations, 101 Single nucleotide polymorphism frequencies, ethnic/racial differences, 185 Single nucleotide polymorphism genotyping techniques, 83–92 examples of genotyping methods, 85–90 future developments, 90 genotyping methods, compared, 86

457 large-scale genotyping methods, 85–88 allele-specific primer extension with ligation, 87–88 gap-filled ligation with molecular inversion probes, 87 long-range resequencing, unique sequences on microarrays, 86–87 primer extension with long probes, 87 random whole genome markers on microarrays, 85–86 targeted single nucleotide polymorphisms, highly multiplexed assays on microarrays, 87–88 medium-scale genotyping methods, 88–89 capillary electrophoresis of mobility tags, multiplex ligation detection, 88–89 fluorescence detection on tag arrays, multiplex PCR and primer extension detection, 88 lass spectrometry, multiplex PCR with primer extension detection, 88 principles, 84–85 single-lex genotyping methods, 89–90 allele-specific hybridization, with probe cleavage, 89 allele-specific invasive probe cleavage, 89 fluorescence polarization detection, primer extension with, 90 melting curve analysis, kinetic PCR with, 89 Sjo¨gren’s syndrome, 279–288 interferon-gamma, 285 interleukin-1, 103, 284–285 interleukin-4, 285 interleukin-6, 284 interleukin-10, 136, 279–283 transforming growth factor beta1, 285 tumor necrosis factor alpha, 283–284 tumor necrosis factor beta, 284 Skin squamous cell carcinoma, interleukin-10 association, 135 SLE. See Systemic lupus erythematosus Small cell lung cancer, interleukin-10 association, 135 SNP BLAST, 76–77 SNPper, 70–72 learning to use it, 71 navigation tips, 71 resources, 71 uses, 71–72 Spondylo-arthropathies, 249–250 interleukin-1, 250 interleukin-6, 250 interleukin-10, 250 tumor necrosis factor, 249–250

458

Cytokine Gene Polymorphisms in Multifactorial Conditions

Spontaneous preterm birth, interleukin-10 association, 136 Squamous cell carcinoma, interleukin-10 association, 135 Sudden infant death syndrome, interleukin-10 association, 136 Survival of T cells, 10–13 Systemic lupus erythematosus, 257–278 American Rheumatism Association for Classification of Systemic Lupus Erythematosus, revised criteria, 258 IFNG polymorphisms, genetic associations, 162 IL10 polymorphisms, association studies, 269–271 interleukin-10 association, 136 interleukin-1 gene cluster, polymorphisms, disease association, 103 polymorphisms, 258–268 tumor necrosis factor genes, association studies, 268–269 Systemic sclerosis, interleukin-1 gene cluster, polymorphisms, disease association, 103

T T cell development, 10–13 T helper 1 cytokines, pulmonary fibrosis, 353–354 T helper 1 immune responses, 13–22 adaptive immunity, cytokines of, 19–22 cytokines in, 19–22 T helper 2 immune responses, cytokines in, 19–22 T helper 1-T helper 2 cytokine gene polymorphisms, acquired immunodeficiency syndrome, 402 TNFR superfamily, 176–178 Total serum immunoglobulin E, asthma, atopy, 230 Trachoma, scarring, IFNG polymorphisms, genetic associations, 163 Transforming growth factor beta, 24–25 atherosclerosis, 372 longevity, 386–388 Sjo¨gren’s syndrome, 285 Transplantation. See also under specific type of transplantation polymorphisms, chemokines, receptors, 214–215 tumor necrosis factor polymorphisms, 182–183 Tropical infectious disease, 413–430 Chagas disease, 416–419

Leishmaniasis, 416–419 leprosy, 419–423 mycobacterial diseases, 419–423 protozoan disease, 416–419 tuberculosis, 419–423 viral hemorrhagic fevers, 414–416 Tuberculosis, 419–423 IFNG polymorphisms, genetic associations, 163 interleukin-1 gene cluster, polymorphisms, disease association, 103 Tumor necrosis factor, 4–7 acquired immunodeficiency syndrome, 402–404 atherosclerosis, 371–372 autoimmune disease, 181–182 cancer, 180–181 cytokine pharmacogenetics, 251–252 disease association, 185 hematopoiesis, 178 infectious disease, 180 longevity, 380–385 lymphoid organ development, 178 malignancy, 178 multiple sclerosis, 295–296 polymorphisms, 175–190 psoriasis, 323–327 rheumatoid arthritis, 246–247 single nucleotide polymorphism, ethnic/racial differences, 185 single nucleotide polymorphisms, 185 Sjo¨gren’s syndrome, 283–284 spondylo-arthropathies, 249–250 structure-function analysis, 179 systemic lupus erythematosus, 268–269 TNFR superfamily, 176–178 transplantation, 182–183 Type 1, type 2 diabetes, 305, 308–310 anti-inflammatory agents, 310 cytokine gene polymorphisms, 310–313 Type I interferons, 9–10

U UCSC bioinformatics, 66–68, 77 learning to use, 67 navigation tips, 67–68 resources, 67 typical uses, 68 Ulcer disease, duodenal, interleukin-1 gene cluster, polymorphisms, disease association, 102 Ulcerative colitis, interleukin-2/interleukin-2R polymorphisms, 113

459

Index User-generated cytokine gene nucleotide sequence alignments, 74–77 Uveitis, intermediate, IFNG polymorphisms, genetic associations, 163

V Vascular endothelial growth factor, psoriasis, 330–331 VHF. See Viral hemorrhagic fevers Viliuisk encephalomyelitis, IFNG polymorphisms, genetic associations, 163

Viral hemorrhagic fevers, 414–416 Vulvar carcinogenesis, interleukin-1 gene cluster, polymorphisms, disease association, 103 Vulvar vestibulitis, interleukin-1 gene cluster, polymorphisms, disease association, 103

W Wegener’s granulomatosis, interleukin-10 association, 136