Psychiatric Disorders: Methods and Protocols

METHODS IN MOLECULAR BIOLOGY™ Series Editor John M. Walker School of Life Sciences University of Hertfordshire Hatfi...

Author: Firas H. Kobeissy

124 downloads 2014 Views 9MB Size Report

This content was uploaded by our users and we assume good faith they have the permission to share this book. If you own the copyright to this book and it is wrongfully on our website, we offer a simple DMCA procedure to remove your content from our site. Start by pressing the button below!
Report copyright / DMCA form

DOWNLOAD PDF

METHODS

IN

MOLECULAR BIOLOGY™

Series Editor John M. Walker School of Life Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK

For further volumes: http://www.springer.com/series/7651

Psychiatric Disorders Methods and Protocols Edited by

Firas H. Kobeissy Division of Addiction Medicine, Department of Psychiatry, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA

Editor Firas H. Kobeissy, Ph.D. Division of Addiction Medicine Department of Psychiatry Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute University of Florida Gainesville, FL, USA [email protected]

ISSN 1064-3745 e-ISSN 1940-6029 ISBN 978-1-61779-457-5 e-ISBN 978-1-61779-458-2 DOI 10.1007/978-1-61779-458-2 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011943889 © Springer Science+Business Media, LLC 2012 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Humana Press is part of Springer Science+Business Media (www.springer.com)

Dedication This Book is dedicated to Kawsar, Maha, and my dear dad Hosni, whose love and patience gave me hope in my path, to my wise mentor, Professor Mark S. Gold and his wife Mrs. Janice Gold and to the angel Zahraa M. Assi whose advice and remarks are so valuable in my career. Finally, to Deema Adnan Wannous and to the angel Zahraa M. Assi.

Foreword I am pleased to describe this comprehensive text and the incredible stable of world-class experts who have made this book something very special. Most books have experts, but the task given to them and the one that they delivered allows the reader to understand where Psychiatry is today and also allows us to forecast the future of basic science research in psychiatry. The depths of information available from such a group of active researchers, thought leaders, and renowned experts of in vivo and in vitro research will greatly inform the field. Although the focus of this text is psychiatry, neurology, neuroscience, all of the discipline relying on translational neuroscience should benefit from this text. I am confident that it will be useful in a variety of clinical contexts and to researchers and clinicians alike. It provides a 2012 manual of cutting edge, bench-to-beside research methodology. As someone who has worked in translational research since the early 1970s, I enjoyed the history of animal models of behavior and modeling of the most common progressive and debilitating psychiatric disorders like eating disorders, schizophrenia, the various mood disorders, alcoholism, and other drug addictions, obesity, Alzheimer’s disease, etc. Modeling human psychopathology in customizable animal models gives insight into the manifestations of behaviors and disease, from beginning to end. The book addresses the usefulness of DSM criteria as it relates to these models and explores alternatives, such as the NIMH Research Doman Criteria (RdoC) and collaborative, interdisciplinary work with others, such as mathematicians, physicists, etc., for the mapping and imaging of the functions of the brain. This text also outlines the value of qualitative and quantitative research, usefulness of current pharmacological therapies, and issues arising from long-term use (e.g., haloperidol). It will also touch on identification of novel technologies (e.g., use of stem cells and synthetic viruses), molecular biology, proteomics/genomics fields, biomarkers, and endophenotypes. Perfectly suited for neuroproteomics leader Dr. Kobeissy, this volume allows him to help us understand a wide range of models and diseases. Dr. Kobeissy has an established career in Neuroproteomics/Systems Biology (e.g., genomics, proteomics) and the translational research of drug- and trauma-induced brain injury. A primary example of Dr. Kobeissy’s work was the unveiling of several biomarkers of drug abuse-induced neurotoxicity. These findings pave the way for early diagnosis, prevention, and treatment of brain cell loss and memory and cognitive declines among individuals with preexisting drug use who may present with resultant psychiatric symptomatology. Lastly, I hope and trust that the insights gained from the authors in this work will help produce targets and therapies of similar impact and lend to better research in years to come. Gainesville, FL, USA

Mark S. Gold

vii

Preface Without animal testing, there will be no new drugs for new or hard-to-treat diseases… Rather than apologise for medicine as it is pursued today, society should be seeking to strengthen it. Animal research is an essential part of compassionate humanistic endeavour. (The Lancet, Volume 364, Issue 9 437, Pages 815–816, 4 September 2004.)

Within the past few years, research in the fields of neuroscience and psychiatry has greatly advanced, especially with the introduction of high-throughput techniques applied on the cellular and molecular levels. This new technology has been enhanced with the development of experimental, customizable animal models that are predictive of human neuropsychiatric pathology and give insights on the mechanisms and pathways involved. The need for developing and studying these animal models cannot be overstressed, paving the way for the development of novel treatments and therapeutics. The techniques and protocols describing these animal models would provide researchers and clinicians with road map methodology for conducting translational bench-to-beside studies that could lead to novel targets relevant to human neuropsychiatric disorders and diseases. Both neuroscience and psychiatric research are multidisciplinary entities, apparent by the number of scientists attending neuroscience conferences (Attendance for the Society for Neuroscience 2011 conference topped more than 34,000). While researchers and laboratories may master some of the useful techniques applied on animal models, we believe that providing a detailed description of these protocols (modified successfully from their original source) will benefit researchers aiming to broaden their experimental repertoire. It will also serve as a guide for students and novice postgraduates who are starting their scientific careers seeking novel techniques as well as novel models relevant to their research areas. Thus, this volume should be useful for graduates, postdoctoral workers, and established scientists, working on behavioral and molecular neuropsychiatric research. In preparing this book, Psychiatric Disorders: Methods and Protocols, we invited top of the line neuroscience and psychiatry experts who are practitioners in academia and industry as well as clinicians to write integrated chapters on neuropsychiatric research sharing their insightful expertise and opinions focusing on both the animal models as well as the cutting edge techniques applied. As this book is focused on methods and protocols, we strive to provide a comprehensive overview of the in vivo as well as the in vitro models available to demonstrate these disorders. Each Method chapter starts with a short introduction, which outlines the background and literature of the animal model discussed along with the methodology and descriptions of the principles of its application and utility. In addition, coupled to these introductions, each of these chapters ends with a troubleshooting notes section that highlights the alterations and expected pitfalls of the protocol outlined. This is derived from the expert’s experience in that particular protocol and is different from what is published in its original manual. In this book, we included 37 chapters divided into five primary parts describing the protocols, techniques, methods, and different models applied in neuropsychiatric disorders.

ix

x

Preface

The first part consists of three chapters and offers an overview of the experimental modeling of neuropsychiatric studies by describing the usefulness and the need of animal models to relate the cellular and molecular changes occurring in human mental illness (Kaffaman and Krystal). In the second chapter, a detailed and elegant description of the pros and cons of having preclinical animal models of psychiatric diseases and their relevance to mimic human disorders is presented (Edwards and Koob). Lastly, this is followed by a discussion chapter detailing the dilemma of the qualitative vs. quantitative nature of psychiatric research (Razafsha and Gold et al.). The second part (consisting of nine chapters) is dedicated to experimental models of neuropsychiatric illness, including cognitive decline models, a self-injurious behavior animal model, anxiety testing, and depression models, etc. The third part (consisting of ten chapters) discusses animal models of substance abuse and is complementary to the items in Part II. It discusses experimental models related to alcohol, nicotine, cannabis, cocaine, methamphetamine, and tobacco abuse paradigms and methods used to develop these models as well as the techniques to assess their outcome and their effects. Collectively, Parts II and III illustrate modeling neuropsychiatric illness and drug abuse paradigms and techniques. The last two parts outline the novel approaches and techniques recently introduced to decipher and investigate topics considered “nonclassical” to the areas of neuropsychiatric disorders. Among, the topics discussed are biomarker identification, autoimmune inflammatory response, and neuroendocrine alteration in the areas of psychiatry (Part V). Lastly, Part VI (consisting of eight chapters) describes the state-of-the-art “Omics approaches” and neurosystems biology/data mining techniques to compute and analyze genomic and proteomics alteration occurring within neuropsychiatric models. The last part offers a new dimension for researchers especially in the areas translational research. We hope that this book will benefit researchers conducting studies at all stages related to neuropsychiatry. Actually, the methods and concepts described throughout demonstrate the formidable power of utilizing these animal models. It is our hope that this book enables neuroscientists and psychiatrists to handle several unanswered scientific questions with a more creative and insightful approach. Gainesville, FL, USA

Firas H. Kobeissy, PhD

Acknowledgments First, I especially want to thank all the book authors; they ultimately made this work possible by providing their top quality manuscripts. Without their extremely valuable and “prompt” contributions, this special volume would have been delayed. In addition, I wish to express my gratitude to Professor John Walker for his immediate availability and his quick response, every time I asked advice when facing a technical or editorial problem. I would like to take this opportunity to thank my colleagues from the University of Florida, Departments of Psychiatry and Neuroscience, who contributed to my academic, professional, and intellectual training and development: Professors Kevin K. Wang, Sue S. Rowland, John Petitto, Mark Lewis, and Lisa Merlo. I want to offer my special thanks to Professor Mark S. Gold and his family, my mentor and chairman, who offered me his wise advice for author selection and the completion of this book. I feel privileged that he agreed to write the Foreword for this book. I am very grateful to both Noni Graham, MS and Dr. Noah Walton, for their talented editorial skills and English proficiency. They kindly assisted in the editing process, reading and commentary on various components of the book. Last but not least, I greatly appreciate the encouragement of many of my friends and colleagues specifically Drs. Ziqhun Zhang, Pavlo Kuzick, Nelson Klahr, Shankar Sadasivan, Niocole Giordani, Rabih Moshourab, and Ali Hemadeh. To my special Deema Adnan Wannous, for her unconditional love, encouragement, and inspiration throughout the endeavor of the project. Thank you. Firas H. Kobeissy

xi

Contents Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PART I

OVERVIEW OF THE ANIMAL RESEARCH IN PSYCHIATRIC ILLNESS AND SUBSTANCE ABUSE

1 New Frontiers in Animal Research of Psychiatric Illness. . . . . . . . . . . . . . . . . . Arie Kaffman and John J. Krystal 2 Experimental Psychiatric Illness and Drug Abuse Models: From Human to Animal, an Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Scott Edwards and George F. Koob 3 Qualitative Versus Quantitative Methods in Psychiatric Research . . . . . . . . . . . Mahdi Razafsha, Hura Behforuzi, Hassan Azari, Zhiqun Zhang, Kevin K. Wang, Firas H. Kobeissy, and Mark S. Gold

PART II

v vii ix xi xvii

3

31 49

METHODS IN ANIMAL MODELS OF PSYCHIATRIC ILLNESS

4 Animal Models of Self-Injurious Behaviour: An Overview . . . . . . . . . . . . . . . . Darragh P. Devine 5 Rodent Models of Adaptive Decision Making . . . . . . . . . . . . . . . . . . . . . . . . . Alicia Izquierdo and Annabelle M. Belcher 6 Animal Models of Depression and Neuroplasticity: Assessing Drug Action in Relation to Behavior and Neurogenesis . . . . . . . . . . . . . . . . . . . . . . Ying Xu, Philip A. Barish, Jianchun Pan, William O. Ogle, and James M. O’Donnell 7 Modeling Depression in Animal Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . David H. Overstreet 8 Behavioral Model for Assessing Cognitive Decline. . . . . . . . . . . . . . . . . . . . . . Michael Guidi and Thomas C. Foster 9 The Pemoline Model of Self-Injurious Behaviour . . . . . . . . . . . . . . . . . . . . . . Darragh P. Devine 10 Modeling Risky Decision Making in Rodents . . . . . . . . . . . . . . . . . . . . . . . . . Nicholas W. Simon and Barry Setlow 11 Open Space Anxiety Test in Rodents: The Elevated Platform with Steep Slopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abdelkader Ennaceur

xiii

65 85

103

125 145 155 165

177

xiv

Contents

12 An Animal Model to Study the Molecular Basis of Tardive Dyskinesia . . . . . . . Mahendra Bishnoi and Ravneet K. Boparai

PART III

METHODS IN ANIMAL MODELS OF SUBSTANCE ABUSE

13 Models of Chronic Alcohol Exposure and Dependence . . . . . . . . . . . . . . . . . . Darin J. Knapp and George R. Breese 14 Rat Models of Prenatal and Adolescent Cannabis Exposure . . . . . . . . . . . . . . . Jennifer A. DiNieri and Yasmin L. Hurd 15 Modeling Nicotine Addiction in Rats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stephanie Caille, Kelly Clemens, Luis Stinus, and Martine Cador 16 Animal Models of Nicotine Withdrawal: Intracranial Self-Stimulation and Somatic Signs of Withdrawal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rayna M. Bauzo and Adrie W. Bruijnzeel 17 Methods in Drug Abuse Models: Comparison of Different Models of Methamphetamine Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Firas H. Kobeissy, Jeremiah D. Mitzelfelt, Irina Fishman, Drake Morgan, Roger Gaskins, Zhiqun Zhang, Mark S. Gold, and Kevin K. Wang 18 Cocaine Self-Administration in Rats: Hold-Down Procedures . . . . . . . . . . . . . Benjamin A. Zimmer and David C.S. Roberts 19 Cocaine Self-Administration in Rats: Discrete Trials Procedures. . . . . . . . . . . . Carson V. Dobrin and David C.S. Roberts 20 Cocaine Self-Administration in Rats: Threshold Procedures. . . . . . . . . . . . . . . Erik B. Oleson and David C.S. Roberts 21 Assessing Locomotor-Stimulating Effects of Cocaine in Rodents . . . . . . . . . . . Drake Morgan, Jameson P. DuPree, Alex D. Bibbey, and Glen M. Sizemore 22 Methods in Tobacco Abuse: Proteomic Changes Following Second-Hand Smoke Exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Joy Guingab-Cagmat, Rayna M. Bauzo, Adrie W. Bruijnzeel, Kevin K. Wang, Mark S. Gold, and Firas H. Kobeissy

PART IV

193

205 231 243

257

269

279 291 303 321

329

METHODS IN ANIMAL MODELS OF EATING DISORDERS

23 Animal Models of Sugar and Fat Bingeing: Relationship to Food Addiction and Increased Body Weight . . . . . . . . . . . . . . . . . . . . . . . . Nicole M. Avena, Miriam E. Bocarsly, and Bartley G. Hoebel 24 Animal Models of Overeating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neil E. Rowland 25 The Activity-Based Anorexia Mouse Model . . . . . . . . . . . . . . . . . . . . . . . . . . . Stephanie J. Klenotich and Stephanie C. Dulawa

351 367 377

Contents

xv

PART V BIOMARKERS, NEUROENDOCRINE AND INFLAMMATORY PROFILES RELEVANT TO NEUROPSYCHIATRIC DISORDERS 26 Dissociating Behavioral, Autonomic, and Neuroendocrine Effects of Androgen Steroids in Animal Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amy S. Kohtz and Cheryl A. Frye 27 Interleukin-2 and the Septohippocampal System: Intrinsic Actions and Autoimmune Processes Relevant to Neuropsychiatric Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . John M. Petitto, Zhi Huang, Danielle Meola, Grace K. Ha, and Daniel Dauer 28 Experimental Schizophrenia Models in Rodents Established with Inflammatory Agents and Cytokines . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hiroyuki Nawa and Kiyofumi Yamada 29 P11: A Potential Biomarker for Posttraumatic Stress Disorder . . . . . . . . . . . . . Lei Zhang, Robert J. Ursano, and He Li

PART VI

397

433

445 453

“OMICS” ANALYSIS AND SYSTEMS BIOLOGY APPLICATIONS PSYCHIATRIC DISORDERS

IN

30 Investigation of Age-Specific Behavioral and Proteomic Changes in an Animal Model of Chronic Ethanol Exposure. . . . . . . . . . . . . . . . . . . . . . Antoniette M. Maldonado-Devincci, Stanley M. Stevens Jr., and Cheryl L. Kirstein 31 Quantitative Peptidomics to Measure Neuropeptide Levels in Animal Models Relevant to Psychiatric Disorders . . . . . . . . . . . . . . . . . . . . Julia S. Gelman, Jonathan Wardman, Vadiraja B. Bhat, Fabio C. Gozzo, and Lloyd D. Fricker 32 ADHD Animal Model Characterization: Transcriptomics and Proteomics Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yoshinori Masuo, Junko Shibato, and Randeep Rakwal 33 Psychiatric Disorder Biomarker Discovery Using Quantitative Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michaela D. Filiou and Christoph W. Turck 34 Gene Profiling of Laser-Microdissected Brain Regions and Individual Cells in Drug Abuse and Schizophrenia Research . . . . . . . . . . . Pietro Paolo Sanna, Vez Repunte-Canonigo, and Alessandro Guidotti 35 Stable Isotope Labeling with Amino Acids in Cell Culture-Based Proteomic Analysis of Ethanol-Induced Protein Expression Profiles in Microglia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bin Liu, David S. Barber, and Stanley M. Stevens Jr.

471

487

505

531

541

551

xvi

Contents

36 Systems Biology in Psychiatric Research: From Complex Data Sets Over Wiring Diagrams to Computer Simulations. . . . . . . . . . . . . . . . . . . . . . . Felix Tretter and Peter J. Gebicke-Haerter 37 Data Mining in Psychiatric Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Diego Tovar, Eduardo Cornejo, Petros Xanthopoulos, Mario R. Guarracino, and Panos M. Pardalos Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

567 593

605

Contributors NICOLE M. AVENA • Department of Psychiatry, McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Department of Psychology, Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA HASSAN AZARI • Department of Psychiatry, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA DAVID S. BARBER • Department of Physiological Sciences, University of Florida, Gainesville, FL, USA PHILIP A. BARISH • Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA RAYNA M. BAUZO • Department of Psychiatry, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA HURA BEHFORUZI • Department of Psychiatry, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA ANNABELLE M. BELCHER • Neuroimaging Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, USA VADIRAJA B. BHAT • Agilent Technologies, Wilmington, DE, USA ALEX D. BIBBEY • Division of Addiction Medicine, Department of Psychiatry, University of Florida, Gainesville, FL, USA MAHENDRA BISHNOI • Department of Pharmacology, Southern Illinois University School of Medicine, Springfield, IL, USA MIRIAM E. BOCARSLY • Department of Psychology, Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA RAVNEET K. BOPARAI • Department of Internal Medicine, Southern Illinois University School of Medicine, Springfield, IL, USA GEORGE R. BREESE • Bowles Center for Alcohol Studies, School of Medicine, University of North Carolina, Chapel Hill, NC, USA ADRIE W. BRUIJNZEEL • Department of Psychiatry, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA MARTINE CADOR • CNRS UMR 5287, “Neuropsychopharmacology of Addiction” Group, University of Bordeaux, Bordeaux, France STEPHANIE CAILLE • CNRS UMR 5287, “Neuropsychopharmacology of Addiction” Group, University of Bordeaux, Bordeaux, France KELLY CLEMENS • Neuropharmacology Laboratory, School of Psychology, The University of New South Wales, Sydney, NSW, Australia EDUARDO CORNEJO • Department of Industrial and Systems Engineering, Center for Applied Optimization, University of Florida, Gainesville, FL, USA

xvii

xviii

Contributors

DANIEL DAUER • Departments of Psychiatry, Neuroscience, and Pharmacology & Therapeutics, McKnight Brain Institute, University of Florida, Gainesville, FL, USA DARRAGH P. DEVINE • Departments of Psychology and Neuroscience, University of Florida, Gainesville, FL, USA JENNIFER A. DINIERI • Departments of Psychiatry, Pharmacology & Systems Therapeutics, and Neuroscience, Mount Sinai School of Medicine, New York, NY, USA CARSON V. DOBRIN • Neuroscience Program, Wake Forest University Health Sciences, Winston Salem, NC, USA STEPHANIE C. DULAWA • Committee on Neurobiology, Department of Psychiatry, University of Chicago, Chicago, IL, USA JAMESON P. DUPREE • Division of Addiction Medicine, Department of Psychiatry, University of Florida, Gainesville, FL, USA SCOTT EDWARDS • Committee on the Neurobiology of Addictive Disorders, Pearson Center for Alcoholism and Addiction Research, The Scripps Research Institute, La Jolla, CA, USA ABDELKADER ENNACEUR • Department of Pharmacy, University of Sunderland, Sunderland, UK MICHAELA D. FILIOU • Max Planck Institute of Psychiatry, Proteomics, and Biomarkers, Munich, Germany IRINA FISHMAN • Department of Neuroscience, University of Florida, Gainesville, FL, USA THOMAS C. FOSTER • Department of Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, FL, USA LLOYD D. FRICKER • Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, USA CHERYL A. FRYE • Departments of Psychology and Biological Sciences, Centers for Life Sciences and Neuroscience Research, The University at Albany-SUNY, Albany, NY, USA ROGER GASKINS • Department of Neuroscience, University of Florida, Gainesville, FL, USA PETER J. GEBICKE-HAERTER • Department of Psychopharmacology, Central Institute for Mental Health, Mannheim, Germany JULIA S. GELMAN • Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA MARK S. GOLD • Departments of Psychiatry, Neuroscience, and Community Health & Family Medicine, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA FABIO C. GOZZO • Institute of Chemistry, University of Campinas, Campinas, Sao Paulo, Brazil MARIO R. GUARRACINO • High Performance Computing and Networking Institute, National Research Council, Naples, Italy

Contributors

xix

MICHAEL GUIDI • Department of Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, FL, USA ALESSANDRO GUIDOTTI • Department of Psychiatry, College of Medicine, The Psychiatric Institute, University of Illinois at Chicago, Chicago, IL, USA JOY GUINGAB-CAGMAT • Department of Psychiatry, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, Gainesville, FL, USA GRACE K. HA • Departments of Psychiatry, Neuroscience, and Pharmacology & Therapeutics, McKnight Brain Institute, University of Florida, Gainesville, FL, USA BARTLEY G. HOEBEL • Department of Psychology, Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA ZHI HUANG • Departments of Psychiatry, Neuroscience, and Pharmacology & Therapeutics, McKnight Brain Institute, University of Florida, Gainesville, FL, USA YASMIN L. HURD • Departments of Psychiatry, Pharmacology & Systems Therapeutics, and Neuroscience, Mount Sinai School of Medicine, New York, NY, USA ALICIA IZQUIERDO • Laboratory of Cognitive Neuroscience, Department of Psychology, California State University, Los Angeles, CA, USA ARIE KAFFMAN • Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA CHERYL L. KIRSTEIN • Cognitive and Neurosciences, Department of Psychology, University of South Florida, Tampa, FL, USA STEPHANIE J. KLENOTICH • Committee on Neurobiology, University of Chicago, Chicago, IL, USA DARIN J. KNAPP • Bowles Center for Alcohol Studies, School of Medicine, University of North Carolina, Chapel Hill, NC, USA FIRAS H. KOBEISSY • Division of Addiction Medicine, Department of Psychiatry, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA AMY S. KOHTZ • Department of Psychology, The University at Albany-SUNY, Albany, NY, USA GEORGE F. KOOB • Committee on the Neurobiology of Addictive Disorders, Pearson Center for Alcoholism and Addiction Research, The Scripps Research Institute, La Jolla, CA, USA JOHN J. KRYSTAL • Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA HE LI • Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD, USA BIN LIU • Department of Pharmacodynamics, University of Florida, Gainesville, FL, USA ANTONIETTE M. MALDONADO-DEVINCCI • Cognitive and Neurosciences, Department of Psychology, University of South Florida, Tampa, FL, USA YOSHINORI MASUO • Laboratory of Neuroscience, Department of Biology, Toho University, Funabashi, Chiba, Japan

xx

Contributors

DANIELLE MEOLA • Departments of Psychiatry, Neuroscience, and Pharmacology & Therapeutics, McKnight Brain Institute, University of Florida, Gainesville, FL, USA JEREMIAH D. MITZELFELT • Division of Addiction Medicine, Department of Psychiatry, University of Florida, Gainesville, FL, USA DRAKE MORGAN • Division of Addiction Medicine, Department of Psychiatry, University of Florida, Gainesville, FL, USA HIROYUKI NAWA • Division of Molecular Neurobiology, Brain Research Institute, Niigata University, Niigata, Japan JAMES M. O’DONNELL • Behavioral Medicine and Psychiatry, School of Medicine, West Virginia University, Morgantown, WV, USA WILLIAM O. OGLE • Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA ERIK B. OLESON • Department of Neurobiology and Anatomy, University of Maryland, School of Medicine, Baltimore, MD, USA; Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, NC, USA DAVID H. OVERSTREET • Department of Psychiatry and Center for Alcohol Studies, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA JIANCHUN PAN • Institute of Neurobiology, Pharmacy School, Wenzhou Medical College, Wenzhou, Zhejiang Province, China PANOS M. PARDALOS • Department of Industrial and Systems Engineering, Center for Applied Optimization, University of Florida, Gainesville, FL, USA; J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA JOHN M. PETITTO • Departments of Psychiatry, Neuroscience, and Pharmacology & Therapeutics, McKnight Brain Institute, University of Florida, Gainesville, FL, USA RANDEEP RAKWAL • Laboratory of Neuroscience, Department of Biology, Toho University, Funabashi, Chiba, Japan; School of Medicine, Showa University, Shinagawa, Tokyo, Japan MAHDI RAZAFSHA • Department of Psychiatry, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA VEZ REPUNTE-CANONIGO • Department of Molecular and Integrative Neuroscience, The Scripps Research Institute, La Jolla, CA, USA DAVID C.S. ROBERTS • Department of Physiology and Pharmacology, Wake Forest University Health Sciences, Winston-Salem, NC, USA NEIL E. ROWLAND • Department of Psychology, University of Florida, Gainesville, FL, USA PIETRO PAOLO SANNA • Department of Molecular and Integrative Neuroscience, The Scripps Research Institute, La Jolla, CA, USA BARRY SETLOW • Departments of Psychiatry and Neuroscience, University of Florida College of Medicine, Gainesville, FL, USA JUNKO SHIBATO • Laboratory of Neuroscience, Department of Biology, Toho University, Funabashi, Chiba, Japan

Contributors

xxi

NICHOLAS W. SIMON • Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA GLEN M. SIZEMORE • Division of Addiction Medicine, Department of Psychiatry, University of Florida, Gainesville, FL, USA STANLEY M. STEVENS, JR. • Department of Cell Biology, Microbiology, and Molecular Biology, University of South Florida, Tampa, FL, USA LUIS STINUS • CNRS UMR 5287, “Neuropsychopharmacology of Addiction” Group, University of Bordeaux, Bordeaux, France DIEGO TOVAR • Department of Industrial and Systems Engineering, Center for Applied Optimization, University of Florida, Gainesville, FL, USA FELIX TRETTER • Kompetenzzentrum Sucht, Isar-Amper-Klinikum gemeinnützige GmbH, Klinikum München-Ost, Haar, Germany CHRISTOPH W. TURCK • Max Planck Institute of Psychiatry, Proteomics, and Biomarkers, Munich, Germany ROBERT J. URSANO • Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD, USA KEVIN K. WANG • Departments of Psychiatry, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA JONATHAN WARDMAN • Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, USA PETROS XANTHOPOULOS • Department of Industrial and Systems Engineering, Center for Applied Optimization, University of Florida, Gainesville, FL, USA YING XU • Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA; Behavioral Medicine and Psychiatry, School of Medicine, West Virginia University, Morgantown, WV, USA KIYOFUMI YAMADA • Department of Neuropsychopharmacology and Hospital Pharmacy, Nagoya University Graduate School of Medicine, Nagoya, Japan LEI ZHANG • Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD, USA ZHIQUN ZHANG • Department of Psychiatry, Center for Neuroproteomics and Biomarkers Research at the Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA BENJAMIN A. ZIMMER • Neuroscience Program, Wake Forest University Health Sciences, Winston-Salem, NC, USA

Part I Overview of the Animal Research in Psychiatric Illness and Substance Abuse

sdfsdf

Chapter 1 New Frontiers in Animal Research of Psychiatric Illness Arie Kaffman and John J. Krystal Abstract Alterations in neurodevelopment are thought to modify risk of numerous psychiatric disorders, including schizophrenia, autism, ADHD, mood and anxiety disorders, and substance abuse. However, little is known about the cellular and molecular changes that guide these neurodevelopmental changes and how they contribute to mental illness. In this review, we suggest that elucidating this process in humans requires the use of model organisms. Furthermore, we advocate that such translational work should focus on the role that genes and/or environmental factors play in the development of circuits that regulate specific physiological and behavioral outcomes in adulthood. This emphasis on circuit development, as a fundamental unit for understanding behavior, is distinct from current approaches of modeling psychiatric illnesses in animals in two important ways. First, it proposes to replace the diagnostic and statistical manual of mental disorders (DSM) diagnostic system with measurable endophenotypes as the basis for modeling human psychopathology in animals. We argue that a major difficulty in establishing valid animal models lies in their reliance on the DSM/International Classification of Diseases conceptual framework, and suggest that the Research Domain Criteria project, recently proposed by the NIMH, provides a more suitable system to model human psychopathology in animals. Second, this proposal emphasizes the developmental origin of many (though clearly not all) psychiatric illnesses, an issue that is often glossed over in current animal models of mental illness. We suggest that animal models are essential to elucidate the mechanisms by which neurodevelopmental changes program complex behavior in adulthood. A better understanding of this issue, in animals, is the key for defining human psychopathology, and the development of earlier and more effective interventions for mental illness. Key words: Animal models, Mental illness, Neurodevelopment, Endophenotype, RDoC

1. Introduction Many previous reviews have discussed the difficulties involved in constructing animal models of mental illnesses, such as schizophrenia, depression, and autism (1–4). Most reviews have used a hierarchical list of criteria introduced by Paul Willner (1) to assess validity of animal models of depression, including face validity, predictive validity, and construct validity. Face validity reflects the ability of Firas H. Kobeissy (ed.), Psychiatric Disorders: Methods and Protocols, Methods in Molecular Biology, vol. 829, DOI 10.1007/978-1-61779-458-2_1, © Springer Science+Business Media, LLC 2012

3

4

A. Kaffman and J.J. Krystal

the model to recapitulate specific anatomical, biochemical, or behavioral features of the human condition (e.g., large ventricles in an animal model of schizophrenia (5)). Predictive validity describes the model’s ability to mimic clinical response in humans (e.g., response to chronic but not acute course of antidepressant medication (6)) while construct validity reflects the ability of the model to recapitulate at least some aspects of the underlying human pathophysiology (e.g., transgenic mice models of Rett syndrome (7) or experimental autoimmune encephalitis (EES) as a model of multiple sclerosis (8)). One issue that received surprisingly little attention in this discussion is the notion that animal models should primarily be used to improve clinical outcomes in humans. In other words, construct validity is a key feature in modeling because it provides new insights about the pathophysiology, which in turn is necessary to develop new treatment options in humans. This clinical utility criterion requires that construct validity recapitulates at least one aspect, but not necessarily all aspects, of the human condition. For example, EES is an imperfect model of multiple sclerosis, yet it was used to elucidate the mechanism by which interleukin-17T helper cells gain entry into the brain and induce encephalopathy in mice. Blocking this step in mice prevents the induction of EES, providing a novel therapeutic target for multiple sclerosis (8). The absence of reliable genetic markers or pathognomonic pathological lesions has placed psychiatry in a unique category among all other branches of medicine, and has presented an enormous challenge for establishing animal models with construct and predictive validities (4). This assertion is supported by the observation that, to the best of our knowledge, not a single example exists in which work in animals led to the development of novel and effective interventions in mental illness, though some rare exceptions to this observation may occur in the near future (9–11). In the first section, we summarize some of the main challenges for establishing animal models with construct and clinical validity of mental illness. We suggest that two related factors are mainly responsible for the slow progress in the development of such animal models. These include: (1) the reliance on the diagnostic and statistical manual of mental disorders (DSM)/International Classification of Diseases (ICD) diagnosis system as a conceptual framework for establishing current models and (2) the almost exclusive focus on adult psychopathology while ignoring important neurodevelopmental changes that are responsible for these changes. In the second section, we examine important conceptual and technological advances that are likely to establish animal models with improved construct and predictive validities. These include the development of alternative strategies for diagnosing mental illness, identification of large effect-size genes implicated in mental illness, genomic and proteomic approaches, vehicles for region-specific manipulation of

1

Psychiatric Illness in Animal Research

5

gene expression in animal models, and availability of inducible pluripotent cells from humans carrying mutations in large effect-size genes. In the final section, we provide two examples that demonstrate how these new technologies could be used to define underlying neurodevelopmental changes that are responsible for the behavioral deficits in adulthood. We suggest that this type of neurodevelopmental approach is necessary to establish animal models with better construct and predictive validity. 1.1. The Five Challenges

Here, we describe five main reasons that account for the relative slow progress in our ability to develop animal models with good construct and predictive validities for psychiatric conditions. First, the absence of known pathognomonic lesions in mental illness prevented the use of traditional pathological investigations available in all other branches of medicine, including common neurological conditions. Second, only recently, reliable genetic markers of psychiatric illnesses have become available (12, 13). The absence of such genetic markers, for many years, created an enormous obstacle in the construction of valid models of psychiatric illness. Third, some outcomes may be specific to humans and difficult to model in animals even if good genetic models are available. For example, mutation in the FoxP2 gene causes significant language impairment in humans (14, 15) that is challenging to model in mice (for an interesting attempt to address this issue, see ref. 16). Fourth, the complexity of the human brain and its relative inaccessibility have allowed for only rudimentary understanding of how the brain generates emotions, constructs perception, and focuses attention. See more on this issue in the Chapter 36 in this book. The lack of clarity on how normal mentation is generated in humans makes it difficult to explain how these processes are impaired in mental illness. Fifth, the current diagnosis system of mental illness provides an inadequate framework for establishing animal models with good construct and predictive validities.

1.2. The Development of the DSM/ICD System

Despite a long-standing appreciation of the difficulty involved in using the current DSM system to establish animal models of mental illness, no viable alternatives are currently available, and relatively little attention has been paid to its role in hindering the development of valid animal models. We start to examine this issue by providing an important historical perspective on how the DSM system was originally created and why it provides an inadequate system for animal work. In the absence of psychopathological understanding of mental illness, the field has created diagnostic criteria for mental illness that were primarily aimed at achieving good inter-rater reliability (for an excellent review on this issue, see ref. 17). The rationale for this effort was first to establish a common language by which different clinicians could agree on the diagnosis. Each

6


diagnostic category should share a particular set of symptoms, similar natural history, and response to interventions (17–20). The underlying assumption was that such effort would group together individuals with similar pathology allowing for further characterization of the underlying pathology and therefore improving clinical outcome. An important stipulation of this heuristic attempt was the notion that it serves as a “work in progress proposal” that needs to be continuously examined, particularly in terms of its clinical utility (20). This approach for defining and categorizing mental disorders is shared by two of the most commonly used classification systems for mental disorders: DSM published by the American Psychiatric Association and its international counterpart the ICD produced by the World Health Organization. Despite the absence of biomarkers to aid diagnosis, these manuals yield good inter-rater reliability levels that are similar to other branches of medicine (18, 19, 21). 1.3. The Absence of a Developmental Perspective

Perhaps, the most significant conceptual drawback of the DSM/ ICD system is its failure to recognize that alterations in neurodevelopment play an important role in programming adult psychopathology (22, 23). Several lines of evidence support this assertion. First, retrospective and prospective studies have consistently shown that maltreatment early in life is a major risk factor for the development of adult psychopathology. Recent analysis from the national comorbidity replication survey suggested that maltreatment accounts for roughly a third of all adult psychopathology and almost half of all childhood psychopathology in the general population (24), and far greater prevalence in individuals with chronic mental illness (25, 26). Several randomized clinical trials demonstrated that interventions that improve quality of parental care in high-risk children led to robust and sustained improvement in several behavioral and cognitive outcomes (27–29), consistent with the notion that parental care plays an important role in neurodevelopment and the presence of behavioral abnormalities later in life. Work in rodents and nonhuman primates identified neurodevelopmental changes in circuits that regulate fear, stress reactivity, cognition, and reward sensitivity in offspring exposed to low levels of parental care (see Table 1), providing important insights into the mechanisms by which parental care influences neurodevelopment and adult behavior (30, 31). Second, many of the recently identified genes implicated in mental illness are expressed in high levels during development and regulate neurodevelopmental processes, such as neural stem cell proliferation, migration, differentiation, and synaptogenesis (32–37). Third, recent neuroimaging studies have identified brain changes in asymptomatic high-risk adolescents that resemble those seen in full-blown adult psychopathology (38, 39). For example,

1


7

Table 1 Alterations in levels of postnatal maternal care are associated with a broad range of behavioral changes in adulthood Behavior

Circuit examined

Genes involved

References

Anxiety-like behavior

Amygdala-brain stem NE systems, such as NTS/LC

GABA-A g2 receptor, adrenoreceptor a2, CRF receptor

(142–147)

Maternal care

MPA–VTA–NAc

Oxytocin/oxytocin receptor and estrogen receptor

(148–152)

Play behavior

Unknown

Unknown

(153)

Hippocampaldependent memory

Hippocampus

NMDA receptor subunits NR1, NR2A, NR2B, synaptophysin, acetylcholine esterase, BDNF

(154–158)

HPA reactivity

Hippocampus–PVNh– pituitary

GR, MR, CRF

(137–139, 147, 148, 159–165)

Prepulse inhibition

mPFX

DA, COMT

(166, 167)

Substance abuse/ reward

NAc

DAT, DA

(168–171)

Abbreviations: BDNF brain-derived neurotrophic factor, CRF corticotropin-releasing factor, COMT catechol-O-methyltransferase, DA dopamine, DAT dopamine transporter, GABA gamma-aminobutyric acid, GR glucocorticoid receptor, MPA medial preoptic area, MR mineralocorticoid receptor, Nac nucleus accumbens, NE norepinephrine, NMDA N-methyl-D-aspartate, LC locus ceruleus, mPFX medial prefrontal cortex, NTS nucleus tractus solitarius, PVNh paraventricular nucleus of the hypothalamus, VTA ventral tegmental area

work from the Personal Assessment and Crisis Evaluation (PACE) clinic in Melbourne, Australia, developed a strategy to identify asymptomatic adolescents that are at high risk for developing schizophrenia (40). The rate of conversion from this presymptomatic stage to schizophrenia spectrum disorder (SSD) is roughly 40% per year, allowing for the identification of neurodevelopmental biomarkers that predict conversion to SSD in this population (41). This work identified changes in prefrontal white matter in individuals that later develop psychotic symptoms (42). Similar changes were reported in both first-episode (43) and established patients with schizophrenia (44) demonstrating that developmental abnormalities in prefrontal white matter are present prior to the onset of full-blown SSD. Similarly, fMRI studies with high-risk, asymptomatic, adolescent daughters of mothers with recurrent depression showed abnormal processing of reward/punishment that is also seen in depressed individuals (39), consistent with the notion that abnormal development of reward circuitry is present prior to the development of depressive episodes. Fourth, almost all forms of adult psychopathology are preceded by childhood psychopathology, suggesting that neurodevelopmental

8


changes in childhood play an important role in modifying the risk for adult psychopathology (22, 45–49). For example, a longitudinal assessment of psychopathology in a large birth cohort (n = 1,037) from ages 11 until 26 showed that 75% of adulthood psychopathology was diagnosed before age 18 with roughly half diagnosed prior to age 15 (50). In some cases, childhood symptoms preceded a similar pattern in adulthood (i.e., childhood anxiety preceded adult anxiety), but in many cases childhood diagnosis evolved from one DSM category in childhood into a different one in adulthood. For instance, 40% of the individuals diagnosed with SSD in adulthood were diagnosed with anxiety disorder between the ages of 11 and 15 (50). The view that adult psychopathology is an extension of childhood psychopathology is consistent with a growing body of research showing that obesity early in life is a major risk factor for developing obesity in adulthood (51–54). Indeed, roughly two-thirds of children with the highest body mass index quartile continue to be in this category in adulthood, and over half of the individuals with adult obesity were obese in childhood (52, 54). The lack of developmental perspective in the DSM/ICD system creates an artificial chasm between childhood and adult psychiatry. This myopic view of psychopathology focuses attention on adult interventions at the expense of early interventions that are likely to be more efficacious. The comparison to treatment of adult obesity is again illuminating with its recent emphasis on early prevention strategies (55). Since animal models of psychiatric illness have traditionally followed the DSM/ICD framework, a similar trend in preclinical work has focused mainly on adult behavior with little attention paid to important neurodevelopmental processes that guide these behaviors. For example, elegant work in mice has shown that some adult mice are more susceptible to the long-term consequences of repeated social defeat compared to others (56). Most of the work so far has focused on the mechanisms by which exposure to chronic stress causes long-lasting behavioral changes in adult animals with little attention paid to the underlying developmental processes that program this differential response to stress. Similarly, work in rats has shown that high impulsivity plays an important role in mediating compulsive drug-seeking behavior in adult animals (57). Again, no effort has been made so far to assess the developmental processes that establish impulsivity in adult rodents. Even animal models that study the effects of early-life stress (ELS) on adult behavior have mainly focused on characterizing adult behavior while neglecting to track the developmental processes responsible for these changes. Animal models of psychiatric care are as good as the questions we ask. The absence of a developmental perspective in the way we conceptualize mental illness hinders the development of animal models with improved construct and predictive validity.

1


9

1.4. The Heterogeneity and Subjectivity Pitfalls

A more common criticism of the DSM/ICD approach is that its good inter-rater reliability was achieved by using a set of polythetic (i.e., a system that allows one to choose a subset of options from a larger menu of options) and arbitrarily chosen criteria that placed individuals with very different presentations and psychopathologies in the same category (17). For example, clinicians can diagnose major depression by selecting five from a pool of nine possible criteria, many of which can deviate from baseline in either direction (e.g., decrease or increase sleep). In theory, this approach can be used to diagnose depression in two individuals that share no common symptoms. This heterogeneity within a given diagnosis probably contributed to the slow progress of identifying robust genetic biomarkers associated with mental illness (13, 17). This suggestion is supported by a growing body of work showing that genes with robust association to mental illness do not align themselves along specific DSM/ICD diagnoses (12, 13). From an animal modeling perspective, such a system is problematic for several reasons. First, it relies exclusively on subjective reports with no objective measurements to support the diagnosis (4, 22). Second, the arbitrary and polythetic nature of the definition is impractical to model in animals, leading different researchers to focus on different aspects of the diagnosis (e.g., sucrose preference as a measure of anhedonia or immobility in the forced swim test (4)). This in turn created an ambiguity as to what constitutes an appropriate animal model of depression or schizophrenia, especially given that core features, such as anhedonia, are not specific for depression and can be seen in other conditions, such as negative symptoms of schizophrenia, schizoid personality disorders, chronic pain, or long-standing substance abuse (58).

1.5. The Comorbidity Issue

The DSM/ICD system is predicated on the assumption that these categories represent distinct and nonoverlying psychopathologies. There is now a growing body of evidence to suggest that such assumption is unlikely to be correct (17). For example, over 80% of individuals with major depression have additional DSM diagnoses and roughly 90% of individuals with generalized anxiety report lifetime comorbidity with other DSM diagnoses (59). High rates of comorbidities were described for many other DSM diagnoses (60–63), indicating that comorbidity among some psychiatric conditions is far more common than the pure single diagnosis. The reason for this high rate of comorbidity is currently unclear but it may reflect the ability of a single pathology to present itself in different ways—in the same way that retinopathy, renal failure, and peripheral neuropathy are all manifestations of poorly controlled diabetes. This is consistent with the observations that exposure to early-life adversity increases the risk for a broad spectrum of psychopathologies (24, 64, 65), and that genes that increase the risk for schizophrenia also increase the risk for other

10


psychopathologies (13). We suggest that the paucity of animal work studying the issue of comorbidity is its absence from the DSM/ICD conceptual framework.

2. The Opportunity The availability of novel technologies, coupled with a new effort led by the NIMH to develop a novel conceptual framework for defining psychopathology (described below), is likely to transform psychiatric care in the upcoming decades. The next section summarizes some of these key advances and their potential to improve construct and predictive validities of animal models of mental illness. 2.1. The Research Domain Criteria as a Novel Conceptual Framework for Diagnosing Mental Illness

The inherent heterogeneity within each DSM/ICD category, its inability to account for the high rates of comorbidities, and the lack of developmental framework have raised serious doubts about the utility of the DSM/ICD approach to uncover underlying pathology and guide treatment. These concerns have led the NIMH to embark on an ambitious effort to develop an alternative approach for diagnosing and treating mental illness, known as the NIMH Research Domain Criteria (RDoC) (17, 66). The RDoC differs from the DSM/ICD approach in several important ways. First, it relies on advances in neuroscience as the guiding principles for defining psychopathology rather than clinical expertise. Second, it places brain circuit rather than a group of symptoms as the organizing principle for defining pathology. One example is the role of the prefrontal cortex, hippocampus, and amygdala in regulating fear conditioning and extinction (67, 68). Other examples include the role of the striatum and orbital prefrontal cortex in reward prediction (39, 69–72) or the role that the hippocampus plays in spatial and episodic memory (73, 74). Third, pathology is defined as boundaries placed on a quantifiable and objective measurement related to a particular circuit output (e.g., abnormally delayed response in the Go NoGo paradigm (75), a failure to extinct in a fear conditioning paradigm (67), or abnormal p300 event-related recordings (76)). This definition emphasizes the need to anchor pathology to measurable objective information rather than the exclusive reliance on gathering subjective reports in the DSM/ ICD system (22, 66). It also assumes that pathology is best defined by placing a boundary on a continuous spectrum in a manner analogous to the definition of hypertension or obesity and not as a discrete category, such as bacterial pneumonia and most DSM/ ICD diagnoses (17, 22). It is important to recognize that pathology is not equivalent to functional impairment (i.e., morbidity) but can also be defined as a risk factor for impairment. This important

1


11

concept is again consistent with the clinical diagnosis of hypertension and diabetes that are risk factors for stroke and cardiovascular disease but are not associated with any measurable impairment by themselves. Pathology in these conditions is defined at the boundary by which interventions seem to reduce morbidity and mortality (17, 22). It is, therefore, possible that some measurements of stress reactivity may justify interventions even in asymptomatic individuals as a way to prevent the onset of depression. Finally, abnormal output of a particular circuit may modify the risk across different DSM/ICD categories providing a possible explanation for the high rate of morbidity. For example, poor impulse control may predispose for increased risk for suicidality, substance abuse, and/or emotional liability/aggression. These measurable endophenotypes are then analyzed in two directions. Upward analysis investigates the relationship between a particular response to clinically relevant impairment (i.e., morbidity) and response to interventions. Downward analysis studies the molecular and cellular details that modify output of this circuit (66). The RDoC approach is a more compatible framework for animal work because of its reliance on an objective measurable phenotype that reflects an output from a specific brain circuit. The RDoC initiative is at its infancy and its implementation is likely to be both challenging and imperfect. For example, most of the focus has been on using this tool as an alternative diagnostic system for human pathology with little attention paid to how to integrate animal work into this effort. Moreover, it is currently unclear how neurodevelopmental perspective, on circuit assembly, is incorporated into this new effort. Nevertheless, the development of an alternative approach to the DSM/ICD system represents an important and necessary step for the development of animal models with improved validities. 2.2. Microarrays

Recent advances in high-throughput sequencing technologies provided complete genetic maps for the human genome, and a growing list of genomes from other model organisms (for details, see http://www.ncbi.nlm.nih.gov/genomes/leuks.cgi). This genomic revolution allowed for the development of unbiased methods to screen for changes in RNA and protein levels associated with human psychopathology in a manner that was not available before. Despite many limitations due to sample heterogeneity, this approach was able to reproducibly identify “cellular markers” that distinguish affected and control groups (77–80). One of the most robust findings has been the identification of abnormal expression of genes implicated in myelination in the prefrontal cortex of individuals with schizophrenia (80–83). These findings are consistent with neuroimaging studies demonstrating white matter abnormalities in the prefrontal cortex of asymptomatic high-risk individuals (42), first-onset unmediated individuals (43), and in individuals with

12


chronic schizophrenia (44). However, white matter abnormalities are unlikely to be a specific marker for schizophrenia (84–90) and therefore additional work is needed to determine how these changes modify brain function and risk for psychopathology. Genomic tools have been instrumental in bridging the gap between gene expression and behavior in animal models that led to new insights about parallel processes in humans. A good example is the discovery that low BDNF levels in the nucleus accumbens (NA) appear to mediate vulnerability to chronic stress in mice and in humans (56). Microarrays provide also a powerful tool to probe for important differences in the neurobiology between humans and other model organisms. Such information is sorely needed to evaluate and address important limitations in our ability to model unique human traits in animals. For instance, the transcription factor FoxP2 plays an important role in the development of language in humans (14, 91). The amino acid composition of FoxP2 is highly conserved among rodents, nonhuman primates, and humans suggesting that it serves an important common function in mammals. Interestingly, there are only three amino acid changes between the mouse and the human protein, two of which are unique to humans and are not found in other apes (92). This striking finding suggests that the FOXP2 gene underwent important changes in recent history that may have modified its transcriptional activity, allowing for the development of language in humans. This hypothesis was recently tested using a genomic approach comparing the transcriptional activity of the human and the chimpanzee’s FOXP2 genes (93). Interestingly, transgenic mice expressing the human FOXP2 gene show altered vocalization demonstrating the complexity of studying unique human behaviors in rodents (16). In summary, microarrays provide a powerful tool to refine the construct and predictive validities of animal models of psychiatric illnesses. 2.3. Novel Genetic Pathways Implicated in Mental Illness

Recent studies documented significant variability in genomic content among individuals that was not previously recognized (94, 95). This genomic variability, termed copy number variation (CNV), is common but in most cases appears to be inconsequential. However, in rare instances, it interferes with expression of genes that mediate risk for the development of several psychiatric illnesses. For a good review on this issue, see ref. 13. Increased CNV burden has been found in individuals with schizophrenia compared to matched controls (96–99). CNVs that are associated with increased risk for schizophrenia appear to target genes implicated in synaptic development (12, 97). The observation that the rate of CNV in noncoding DNA was similar in schizophrenics and controls (97) suggests that the increased burden of CNV is not due to a general increase in genomic instability. A small portion of these CNVs is located in specific hotspots in the genome that confer high risk for schizophrenia (e.g., 1q21.1, 15q11.2, 15q13.3, and

1


13

22q11.2). The genomic instability in these regions is most likely due to flanking tandem repeats driving nonallelic homologous recombination in these regions. These more common CNVs account for only 2–4% of cases of schizophrenia (13). In fact, most individuals with schizophrenia have a single-unique hit that is not shared with other individuals with schizophrenia (13, 97). Interestingly, a particular CNV is not specific for schizophrenia and may also increase the risk for other mental illnesses, such as autism, mental retardation, or mood disorders (12, 13, 100). Together, these findings suggested that genomic instability is responsible for rare hits in many different developmental genes that substantially modify the risk of mental illness in a manner that does not follow a specific DSM/ICD category. DNA microarray provides a powerful and inexpensive technology to identify CNVs associated with high risk for mental illness (101). However, this technology is now being replaced by new advances that are able to sequence the entire coding sequence of the human genome (i.e., exomes) at a cost of $4,000 or less (101, 102). In fact, the cost associated with sequencing the entire human genome is likely to reach the NIH goal of $1,000 within the next decade (102). This technology provides single-base resolution of individual genomes and has already been used successfully for gene discovery and to guide novel interventions (103–107). The explosive nature of these advances undoubtedly generates a long list of genes and pathways implicated in mental illness (see step 1 in Fig. 1). Such a list provides a tremendous opportunity for progress, but this progress requires the development of clinical and preclinical tools to bridge the gap between genes and complex behavior. From a clinical point of view, there is a need to map intermediate phenotypes (i.e., endophenotypes, and see step 2 in Fig. 1) that more closely track these genetic variations (for two good examples of such endophenotypes, see refs. 76, 108). Animal models, especially in mice where genetic manipulations allow for deletion and overexpression of genes, are critical for elucidating the mechanism by which genes implicated in mental illness modify neurodevelopment and adult behavior (see steps 6–9 in Fig. 1). In Subheading 3, we provide more details on how this approach will likely improve construct and predictive validity of animal models of psychiatric illness. 2.4. Viral Gene Delivery and Pluripotent Stem Cells

Advancements in molecular and cellular biology have provided several new tools to bridge the gap between gene expression and human psychopathology. Here, we briefly describe two such examples. The first example is the development of synthetic viruses that can be used to manipulate gene expression within a specific brain region or a cell type. This technology takes advantage of the fact that viral particles are made by assembling a protein capsid shell around a DNA (or RNA) sequence. The capsid shell allows the

14


Fig. 1. Animal work should play a central role in the development of more effective interventions for mental illness. Advances in sequencing technologies provide a growing list of candidate genes implicated in mental illness (step 1). Genes implicated in mental illness are used to define endophenotypes (step 2) that segregate with the genetic biomarker. Endophenotypes should also inform about pathophysiology (step 3) and help guide interventions (step 4) with improved clinical outcome (step 5). Work in animals plays a central role in the transition along steps 1–5. This includes characterization of neurodevelopmental pathways by which genes identified in step 2 affect brain function and adult behavior. Such work identifies additional genes implicated in these behavioral changes (step 6), helps define possible endophenotypes (step 7), informs about pathological changes (step 8), and helps in the development of novel diagnostic and interventional strategies (step 9).

virus to attach itself and gain entry into specific cells. Once inside the cell, the particle disassembles delivering the DNA into the infected cell providing the necessary information to assemble new particles that can then go on to infect other cells. By modifying the genetic sequence packaged in these particles, one can deliver genetic instructions that modify expression of specific genes in neurons or glial cells without expressing other viral genes that harm these cells (109, 110). In animals, this method provides a powerful tool to determine how changes in gene expression, within a particular brain region, modify brain function and behavior. This approach was used to show that high levels of brain-derived neurotrophic factor (BDNF) produced in the ventral tegmental area (VTA) are necessary to mediate susceptibility to social defeat in mice (56). Viruses can also be used to modify gene expression in other model organisms, such as nonhuman primates, where transgenic animals are not yet available. Finally, viral gene delivery in humans is likely to provide a promising novel strategy for interventions in the future (111, 112). The second example is the development of novel stem cell technology that can reprogram differentiated somatic cells (i.e., fibroblasts) into pluripotent stem cells by expressing a defined

1


15

combination of transcription factors. The inducible pluripotent cells (iPS) can then be differentiated in vitro to give rise to different cell types, including neurons and glial cells (113). In practical terms, this approach allows us to harvest fibroblasts from individuals carrying a mutation of interest and their normal siblings, transform them into neurons, and examine their structural, biochemical, and electrophysiological properties in the dish. A recent report has demonstrated significant improvements in the methodology and the establishment of an iPS cell line from fibroblasts obtained from an 8-year-old girl with Rett syndrome (114). This method may help circumvent the current inaccessibility of fresh brain tissue for pathological examination, providing an important tool for validating findings in animal models as well as guiding preclinical work.

3. Section 3: Lessons from developmental work in rodents

3.1. Lessons from DISC1

In this last section, we provide two examples to demonstrate how developmental work in rodents can provide important insights into the pathophysiology of mental illness in humans. We suggest that this kind of developmental work is necessary to improve construct and predictive validity of current animal models of psychiatric illness. In 1970, Patricia Jacobs and her colleagues reported an aberrant translocation in an 18-year-old boy that had severe conduct disorder but was otherwise healthy (115). The balanced translocation occurred between chromosomes 1 and 11, t(1:11) (q43,q21), and was detected across three generations in many members of his extended family (carriers n = 34, noncarriers n = 43) (76, 116). No phenotypic abnormalities were noted during the initial evaluation, but a follow-up study, conducted 20 years later, found unusually high incidence of psychiatric hospitalizations in this family (116). Carriers of this translocation showed high incidence of schizophrenia (n = 7), bipolar disorder (n = 1), unipolar depression (n = 10), adolescent conduct disorder (n = 2), and minor depression (n = 1) (116). All the individuals with severe mental illness in this family carried the translocation with a maximum LOD score of 7.1 for linkage between this translocation and severe mental illness. Interestingly, only 60% of the carriers developed severe psychopathology suggesting that the presence of the translocation alone is not sufficient to induce severe mental illness (76, 100). Initial characterization of the translocation suggested that it disrupted at least two genes (117, 118), named Disrupted in Schizophrenia 1 and 2 (i.e., DISC1 and DISC2). DISC2 appears to be a noncoding RNA that is transcribed in the opposite

16


direction of DISC1 and is believed to regulate DISC1 expression. A large number of studies have now confirmed an association between mutations in DISC1 and increased risk for a host of psychopathologies (reviewed in refs. 100, 119), providing the field with one of its first reliable genetic biomarkers for human psychopathology. 3.2. The Search for an Endophenotype

One important lesson from the DISC1 discovery is the need to better characterize the clinical presentation associated with this genetic biomarker. For instance, despite its name, abnormal expression of DISC1 is not a specific genetic marker for schizophrenia and a substantial portion of individuals that carry the t(1:11) translocation develop depression or show no evidence of mental illness (76, 116). This nonspecific relationship has been described now for many other large-effect genes, underscoring the importance of defining an intermediate phenotype (i.e., an endophenotype) that better segregates with the mutation and also links it to clinical impairment (12, 13, 108). An interesting example of such an endophenotype is the finding that carriers of the t(1:11) translocation showed a decrease in amplitude of the P300 event-related potential not seen in noncarrier family members (76). Importantly, this test was able to distinguish between carriers and noncarriers regardless of their clinical diagnosis (depression vs. schizophrenia) or clinical impairment (mental illness vs. no mental illness). The observation that decreased P300 amplitude was seen in carriers with no evidence of mental illness is not necessarily problematic as long as this biomarker is a good predictor of the development of mental illness, an assertion that is supported by some reports (120–122). This is analogous to the observation that many individuals with hypertension do not develop stroke (i.e., clinical morbidity), yet we prevent stroke by treating hypertension because hypertension is a good predictor for future morbidity and it is amenable to treatment. Moreover, hypertension is a risk factor for many forms of morbidities, including heart disease and kidney disease, demonstrating that a single-risk factor can have different clinical presentations. In summary, a good endophenotype should provide an objective measurement that distinguishes between carriers and noncarriers and relay information regarding risk for clinical impairment (see step 2 in Fig. 1). The DSM/ICD system may be useful for describing clinical impairment but not for uncovering psychopathology or guiding treatment. The RDoC initiative should facilitate the identification of endophenotypes that are likely to be more informative regarding the pathophysiology and intervention strategies. Such endophenotypes would also improve construct validity of animal models in psychiatric research by providing important postmarks to guide this work (step 7, Fig. 1). Similarly, work with transgenic animals carrying mutations in these genes can provide important insights

1


17

for testing specific endophenotypes in humans (step 7, Fig. 1). For example, reports from several groups demonstrated a decrease in prepulse inhibition (PPI) (i.e., a measurement of sensorimotor gating) in transgenic animals carrying mutations in the DISC1 gene (5, 123, 124). These deficits appear to be due to inappropriate maturation of dopamine innervations in the prefrontal cortex of these mice (124). Defects in PPI have been documented in individuals with schizophrenia and other mental illnesses, but to the best of our knowledge have not been used to distinguish between carrier and noncarrier family members with a mutated DISC1 gene. This kind of reciprocal translational work demonstrates how work in animals can guide the identification of an endophenotype in humans.

4. Animal Models Play a Key Role in Elucidating the Mechanism by Which Large Effect-Size Genes Modify Behavior

Animal work has played an instrumental role in elucidating the mechanisms by which mutations in DISC1 modify behavior. For example, biochemical and cellular studies have shown that the DISC1 protein regulates at least two major cellular pathways that are necessary for neural stem cell (NSC) proliferation, migration, and synaptogenesis (119). One pathway involves a direct inhibition of GSK3β allowing for stabilization of β-catenin, which in turn is necessary for cell-cycle entry and NSC proliferation (34). The second pathway involves recruiting microtubule-assembly proteins, such as LIS1 and NUdEL, into a dynein-mediated motor complex that transports the complex to the centrosome. Disruption of this latter pathway interferes with centrosome-mediated cellular functions, such as cell division, cell migration, and neurite outgrowth (125, 126). Several lines of transgenic animals with dysregulated DISC1 activity have been characterized and much work has been done to demonstrate behavioral and anatomical alterations in adulthood (5, 123, 127). Recent work has focused on trying to understand how changes in DISC1 levels modify behavior in animals. Mao et al. (2009) showed that DISC1 knockdown is associated with decreased proliferation of NSC in the hippocampus of adult mice, a decrease that was associated with increased helpless behavior in the forced swim test. Abnormalities in NSC proliferation and helpless behavior were eliminated after administrating GSK3β inhibitors (34). In other words, DISC1 inhibition of GSK3β is necessary for NSC proliferation and therefore GSK3β inhibitors can compensate for DISC1 loss of function. Availability of iPS cell lines from family members with and without a mutation in DISC1 can assess the validity of these findings in humans. These examples provide a vivid demonstration of how a molecular understanding

18


of the underlying biology in rodents can potentially lead to novel interventional strategies in humans (steps 8 and 9 in Fig. 1). Several observations suggest that many of the behavioral abnormalities seen in animals with mutated DISC1 are neurodevelopmental in nature. First, DISC1 modifies processes, such as NSC proliferation, migration, and synaptogenesis, that are essential for normal neurodevelopment. Second, expression of DISC1 peaks during embryogenesis and the juvenile (i.e., adolescencelike) period (32). Despite this well-accepted notion that DISC1 is likely to play an important role in neurodevelopment, most effort so far has been on characterizing abnormal behavior in adulthood with little effort made to link these behavioral abnormalities to specific neurodevelopmental changes. A unique exception to this general trend has been a recent report by Niwa et al. (2010). These authors first developed a method that allowed them to transiently knock down DISC1 mainly in pyramidal prefrontal cortex cells (124). This transient decrease in DISC1 (from embryonic day 14 to roughly postnatal day 10) caused abnormal dendritic development in these neurons that persisted into adulthood despite the restoration of normal levels of DISC1 in these cells at 2 weeks after birth. Next, the authors wanted to know whether defects in dendritic arborization impaired the ability of these cells to receive dopaminergic innervations that normally mature during young adulthood (128). Indeed, defects in dendritic arborization were associated with impaired dopaminergic input and deficits in several prefrontal mediated tasks that were apparent in late (i.e., postnatal day 56) but not early adolescence (i.e., postnatal day 28). This work demonstrates how early developmental abnormalities affect later developmental processes accounting for the emergence of abnormal behavior in early adulthood. We suggest that this kind of developmental approach is likely to improve construct and predictive validity of animal models of psychiatric illness by defining the underlying pathology and facing the challenges of treating developmental psychopathology in adulthood (see steps 8 and 9 in Fig. 1). In conclusion, understanding the mechanisms by which DISC1 modifies the risk for psychopathology in humans requires the identification of reliable endophenotypes that link this gene with objective measurements that predict the risk for clinical impairment. Animal models provide an instrumental tool to understand how alterations in this gene modify adult behavior and this work can aid in identifying endophenotypes in humans. Current animal work has focused on characterizing adult behavior in animals with abnormal DISC1 protein activity with little attention paid to how neurodevelopmental changes contribute to these underlying behavioral abnormalities. A better understanding of the neurodevelopmental processes by which disruption of DISC1 modifies adult behavior represents an important and promising area of research for future animal work.

1

4.1. Parental Care Programs Neurodevelopment


19

Childhood maltreatment represents one of the most significant risk factors for the development of mental illness in adulthood. The importance of this issue as a major public health concern was recently acknowledged by several influential sources, including the World Health Organization and the Institute of Medicine (129, 130). Roughly, 1.5 million children are abused or neglected each year in the USA and these alarming statistics have been documented now for the past 30 years (30). In the absence of effective interventions, maltreated children go on to develop a host of behavioral, emotional, cognitive, and medical sequelae that are chronic and in most cases refractory to psychiatric treatment (24, 130–133). The relationship between ELS and mental illness has now been demonstrated using both retrospective and prospective studies (reviewed in ref. 130), and several reports have consistently found that more than half (!) of the individuals with chronic mental illness have been physically, verbally, or sexually abused early in life (25, 26). Finally, in a recent report from the Institute of Medicine, the total cost related to ELS was estimated at $247 billion annually (129), placing it at equal footing with the estimated costs for all cancers combined. The observations that many of the symptoms associated with exposure to ELS are present early in life and persist into adulthood suggest that exposure to ELS is somehow able to modify brain development in a manner that influences the risk for mental illness in adulthood. The molecular and cellular mechanisms by which ELS influences such diverse and severe clinical outcomes are still poorly understood in humans, but similar outcomes in rodents and nonhuman primates suggest that at least some aspects of this process could be further studied in animal models (30, 131). Here, we briefly summarize key findings from Dr. Michael Meaney’s laboratory on the developmental sequelae of maternal neglect model in the rat. These are presented to illustrate how developmental work on early adversity in animals can inform us about parallel processes in humans. Maternal behavior during the first postnatal week is normally distributed in rats such that some dams lick and groom (LG) their pups almost three times as much compared to others (134). Highand low-LG dams were defined as those that are 1 SD above and below the mean, respectively, creating two nonoverlapping extremes of maternal care—reviewed in ref. 135. Longitudinal follow-up studies demonstrated a host of behavioral differences between adult offspring of high- and low-LG dams (see Table 1). Levels of LG peak during the first 2 days after birth in both highand low-LG dams followed by a gradual decline to similar low levels at around postnatal 9 (134). These observations suggest that differences in frequency of LG during the first 9 days after birth are somehow able to alter many behavioral outcomes in adulthood. Cross-fostering studies showed that most behavioral outcomes are

20


dictated by levels of postnatal maternal care provided by the adopting dam rather than the biological dam, and that tactile stimulation provided by the dam during a critical period of development is responsible for these changes in behavior, reviewed in ref. 31. Exposure to high levels of LG during the first week of life is necessary to induce a cascade of developmental changes that ultimately lead to the removal of DNA methylation from a promoter that controls glucocorticoid receptor (GR) expression in the hippocampus (for a detailed review, see ref. 136). Demethylation of this regulatory element allows the transcription factor NGFI-A to bind this promoter, resulting in higher levels of GR in the hippocampus of offspring raised by high-LG dams (137, 138). Low levels of LG are not sufficient to trigger demethylation of this promoter resulting in low expression levels of GR in offspring raised by low-LG dams. Once established, the DNA methylation at this promoter persists into adulthood accounting for the higher levels of GR in the hippocampus of adult offspring raised by high-LG compared to those of low-LG dams. High levels of GR in the hippocampus allow for more efficient termination of the release of corticosterone from the adrenal gland explaining why offspring of high-LG dams have a more blunted hypothalamic-pituitaryadrenal (HPA) response to stress compared to offspring of low-LG dams (137–139). This work has demonstrated how early-life events cause stable alterations in gene expression that modify HPA reactivity in adulthood, providing an important paradigm to explain how early adversity could modify vulnerability to mental illness in adulthood. The relevance of these findings to human psychopathology was examined in a recent postmortem study showing higher levels of DNA methylation and lower GR in the hippocampus of individuals exposed to early maltreatment compared to matched controls (140). This work provides a plausible molecular model to explain previous data documenting increased stress reactivity in both humans and nonhuman primates exposed to ELS (131), and demonstrates the potential of using animal models to elucidate some of the molecular mechanisms by which exposure to stress early in life modifies vulnerability to stress in adult humans (steps 7–9, Fig. 1). Changes in DNA methylation is likely to be only one of many molecular mechanisms by which events early in life modify the risk for psychopathology in adulthood and there is a need to use unbiased genomic strategies to further characterize other developmental pathways modified by ELS. Some examples include neural stem proliferation/survival/differentiation, synaptogenesis, and synaptic pruning. Moreover, current work has mainly focused on demonstrating behavioral or physiological changes in

1


21

adult animals exposed to ELS, with little attention paid to the underlying developmental changes that are responsible for these changes. Finally, additional effort is needed to explain how ELS is able to modify so many different behavioral outcomes in adulthood (see Table 1). Such work is likely to shed new light on the underlying developmental processes that are responsible for the high rate of comorbidity seen in some forms of mental illness (59, 60, 62, 141). In summary, exposure to maltreatment early in life represents a major risk factor for a host of psychopathologies in humans. Animal models of ELS are likely to provide valuable molecular insights into the underlying pathology that is likely to improve our ability to diagnose and treat this common form of psychopathology.

5. Conclusions In the absence of viable alternatives, attempts to model human psychopathology in animals have relied almost exclusively on the DSM/ICD conceptual framework. Here, we suggest that this conceptual framework is inadequate for studying human psychopathology and therefore inappropriate to guide this issue in animals. We propose that animal work should focus instead on the role that genes and/or environmental factors play in the development of circuits that regulate specific physiological and behavioral outcomes in adulthood. Such an approach is consistent with the notion that most (though clearly not all) adult psychopathology is programmed earlier in development and is necessary to elucidate the underlying biology of a growing list of developmental genes implicated in human psychopathology. A better understanding of these processes in animals improves construct and predictive validity of animal models of mental illness and facilitates the development of earlier diagnostic and interventional strategies that are likely to improve clinical outcomes.

Acknowledgments This work was supported by NIMH 1KO8MH074856, DANA foundation Program in Brain and Immuno-imagine 2011, the Clinical Neuroscience Division of the VA National Center for PTSD, the NIAAA Center for the Translational Neuroscience of Alcoholism (P50- AA012870-09), and CTSA Grant Number UL1 RR024139 from the National Center for Research Resources.

22


References 1. Willner, P. (1984) The validity of animal models of depression, Psychopharmacology (Berl) 83, 1–16. 2. Kellendonk, C., Simpson, E. H., and Kandel, E. R. (2009) Modeling cognitive endophenotypes of schizophrenia in mice, Trends Neurosci 32, 347–358. 3. Chadman, K. K., Yang, M., and Crawley, J. N. (2009) Criteria for validating mouse models of psychiatric diseases, Am J Med Genet B Neuropsychiatr Genet 150B, 1–11. 4. Nestler, E. J., and Hyman, S. E. Animal models of neuropsychiatric disorders, Nat Neurosci 13, 1161–1169. 5. Hikida, T., Jaaro-Peled, H., Seshadri, S., Oishi, K., Hookway, C., Kong, S., Wu, D., Xue, R., Andrade, M., Tankou, S., Mori, S., Gallagher, M., Ishizuka, K., Pletnikov, M., Kida, S., and Sawa, A. (2007) Dominantnegative DISC1 transgenic mice display schizophrenia-associated phenotypes detected by measures translatable to humans, Proc Natl Acad Sci USA 104, 14501–14506. 6. Santarelli, L., Saxe, M., Gross, C., Surget, A., Battaglia, F., Dulawa, S., Weisstaub, N., Lee, J., Duman, R., Arancio, O., Belzung, C., and Hen, R. (2003) Requirement of hippocampal neurogenesis for the behavioral effects of antidepressants, Science 301, 805–809. 7. Shahbazian, M., Young, J., Yuva-Paylor, L., Spencer, C., Antalffy, B., Noebels, J., Armstrong, D., Paylor, R., and Zoghbi, H. (2002) Mice with truncated MeCP2 recapitulate many Rett syndrome features and display hyperacetylation of histone H3, Neuron 35, 243–254. 8. Reboldi, A., Coisne, C., Baumjohann, D., Benvenuto, F., Bottinelli, D., Lira, S., Uccelli, A., Lanzavecchia, A., Engelhardt, B., and Sallusto, F. (2009) C-C chemokine receptor 6-regulated entry of TH-17 cells into the CNS through the choroid plexus is required for the initiation of EAE, Nat Immunol 10, 514–523. 9. Berry-Kravis, E., Hessl, D., Coffey, S., Hervey, C., Schneider, A., Yuhas, J., Hutchison, J., Snape, M., Tranfaglia, M., Nguyen, D. V., and Hagerman, R. (2009) A pilot open label, single dose trial of fenobam in adults with fragile X syndrome, J Med Genet 46, 266–271. 10. Sanacora, G., Zarate, C. A., Krystal, J. H., and Manji, H. K. (2008) Targeting the glutamatergic system to develop novel, improved therapeutics for mood disorders, Nat Rev Drug Discov 7, 426–437.

11. Grillon, C. (2009) D-cycloserine facilitation of fear extinction and exposure-based therapy might rely on lower-level, automatic mechanisms, Biol Psychiatry 66, 636–641. 12. State, M. W. (2010) Another piece of the autism puzzle, Nat Genet 42, 478–479. 13. Sebat, J., Levy, D. L., and McCarthy, S. E. (2009) Rare structural variants in schizophrenia: one disorder, multiple mutations; one mutation, multiple disorders, Trends Genet 25, 528–535. 14. Lai, C. S., Fisher, S. E., Hurst, J. A., VarghaKhadem, F., and Monaco, A. P. (2001) A forkhead-domain gene is mutated in a severe speech and language disorder, Nature 413, 519–523. 15. Hurst, J. A., Baraitser, M., Auger, E., Graham, F., and Norell, S. (1990) An extended family with a dominantly inherited speech disorder, Dev Med Child Neurol 32, 352–355. 16. Enard, W., Gehre, S., Hammerschmidt, K., Holter, S. M., Blass, T., Somel, M., Bruckner, M. K., Schreiweis, C., Winter, C., Sohr, R., Becker, L., Wiebe, V., Nickel, B., Giger, T., Muller, U., Groszer, M., Adler, T., Aguilar, A., Bolle, I., Calzada-Wack, J., Dalke, C., Ehrhardt, N., Favor, J., Fuchs, H., GailusDurner, V., Hans, W., Holzlwimmer, G., Javaheri, A., Kalaydjiev, S., Kallnik, M., Kling, E., Kunder, S., Mossbrugger, I., Naton, B., Racz, I., Rathkolb, B., Rozman, J., Schrewe, A., Busch, D. H., Graw, J., Ivandic, B., Klingenspor, M., Klopstock, T., Ollert, M., Quintanilla-Martinez, L., Schulz, H., Wolf, E., Wurst, W., Zimmer, A., Fisher, S. E., Morgenstern, R., Arendt, T., de Angelis, M. H., Fischer, J., Schwarz, J., and Paabo, S. (2009) A humanized version of Foxp2 affects cortico-basal ganglia circuits in mice, Cell 137, 961–971. 17. Hyman, S. E. The diagnosis of mental disorders: the problem of reification, Annu Rev Clin Psychol 6, 155–179. 18. Helzer, J. E., Clayton, P. J., Pambakian, R., Reich, T., Woodruff, R. A., Jr., and Reveley, M. A. (1977) Reliability of psychiatric diagnosis. II. The test/retest reliability of diagnostic classification, Arch Gen Psychiatry 34, 136–141. 19. Helzer, J. E., Robins, L. N., Taibleson, M., Woodruff, R. A., Jr., Reich, T., and Wish, E. D. (1977) Reliability of psychiatric diagnosis. I. A methodological review, Arch Gen Psychiatry 34, 129–133. 20. Feighner, J. P., Robins, E., Guze, S. B., Woodruff, R. A., Jr., Winokur, G., and

1 Psychiatric Illness in Animal Research

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

Munoz, R. (1972) Diagnostic criteria for use in psychiatric research, Arch Gen Psychiatry 26, 57–63. Pies, R. (2007) How “objective” are psychiatric diagnoses?: (guess again), Psychiatry (Edgmont) 4, 18–22. Widiger, T. A., and Clark, L. A. (2000) Toward DSM-V and the classification of psychopathology, Psychol Bull 126, 946–963. Thompson, B. L., and Levitt, P. (2010) The clinical-basic interface in defining pathogenesis in disorders of neurodevelopmental origin, Neuron 67, 702–712. Green, J. G., McLaughlin, K. A., Berglund, P. A., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., and Kessler, R. C. Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication I: associations with first onset of DSM-IV disorders, Arch Gen Psychiatry 67, 113–123. Muenzenmaier, K., Meyer, I., Struening, E., and Ferber, J. (1993) Childhood abuse and neglect among women outpatients with chronic mental illness, Hosp Community Psychiatry 44, 666–670. Bryer, J. B., Nelson, B. A., Miller, J. B., and Krol, P. A. (1987) Childhood sexual and physical abuse as factors in adult psychiatric illness, Am J Psychiatry 144, 1426–1430. Olds, D., Henderson, C. R., Jr., Cole, R., Eckenrode, J., Kitzman, H., Luckey, D., Pettitt, L., Sidora, K., Morris, P., and Powers, J. (1998) Long-term effects of nurse home visitation on children’s criminal and antisocial behavior: 15-year follow-up of a randomized controlled trial, Jama 280, 1238–1244. Olds, D. L., Kitzman, H., Cole, R., Robinson, J., Sidora, K., Luckey, D. W., Henderson, C. R., Jr., Hanks, C., Bondy, J., and Holmberg, J. (2004) Effects of nurse home-visiting on maternal life course and child development: age 6 follow-up results of a randomized trial, Pediatrics 114, 1550–1559. Olds, D. L., Robinson, J., Pettitt, L., Luckey, D. W., Holmberg, J., Ng, R. K., Isacks, K., Sheff, K., and Henderson, C. R., Jr. (2004) Effects of home visits by paraprofessionals and by nurses: age 4 follow-up results of a randomized trial, Pediatrics 114, 1560–1568. Kaffman, A. (2009) The silent epidemic of neurodevelopmental injuries, Biol Psychiatry 66, 624–626. Kaffman, A., and Meaney, M. J. (2007) Neurodevelopmental sequelae of postnatal maternal care in rodents: clinical and research implications of molecular insights, J Child Psychol Psychiatry 48, 224–244.

23

32. Schurov, I. L., Handford, E. J., Brandon, N. J., and Whiting, P. J. (2004) Expression of disrupted in schizophrenia 1 (DISC1) protein in the adult and developing mouse brain indicates its role in neurodevelopment, Mol Psychiatry 9, 1100–1110. 33. Duan, X., Chang, J. H., Ge, S., Faulkner, R. L., Kim, J. Y., Kitabatake, Y., Liu, X. B., Yang, C. H., Jordan, J. D., Ma, D. K., Liu, C. Y., Ganesan, S., Cheng, H. J., Ming, G. L., Lu, B., and Song, H. (2007) Disrupted-InSchizophrenia 1 regulates integration of newly generated neurons in the adult brain, Cell 130, 1146–1158. 34. Mao, Y., Ge, X., Frank, C. L., Madison, J. M., Koehler, A. N., Doud, M. K., Tassa, C., Berry, E. M., Soda, T., Singh, K. K., Biechele, T., Petryshen, T. L., Moon, R. T., Haggarty, S. J., and Tsai, L. H. (2009) Disrupted in schizophrenia 1 regulates neuronal progenitor proliferation via modulation of GSK3beta/ beta-catenin signaling, Cell 136, 1017–1031. 35. Berkel, S., Marshall, C. R., Weiss, B., Howe, J., Roeth, R., Moog, U., Endris, V., Roberts, W., Szatmari, P., Pinto, D., Bonin, M., Riess, A., Engels, H., Sprengel, R., Scherer, S. W., and Rappold, G. A. Mutations in the SHANK2 synaptic scaffolding gene in autism spectrum disorder and mental retardation, Nat Genet 42, 489–491. 36. Jamain, S., Quach, H., Betancur, C., Rastam, M., Colineaux, C., Gillberg, I. C., Soderstrom, H., Giros, B., Leboyer, M., Gillberg, C., and Bourgeron, T. (2003) Mutations of the X-linked genes encoding neuroligins NLGN3 and NLGN4 are associated with autism, Nat Genet 34, 27–29. 37. Laumonnier, F., Bonnet-Brilhault, F., Gomot, M., Blanc, R., David, A., Moizard, M. P., Raynaud, M., Ronce, N., Lemonnier, E., Calvas, P., Laudier, B., Chelly, J., Fryns, J. P., Ropers, H. H., Hamel, B. C., Andres, C., Barthelemy, C., Moraine, C., and Briault, S. (2004) X-linked mental retardation and autism are associated with a mutation in the NLGN4 gene, a member of the neuroligin family, Am J Hum Genet 74, 552–557. 38. Correll, C. U., Hauser, M., Auther, A. M., and Cornblatt, B. A. (2010) Research in people with psychosis risk syndrome: a review of the current evidence and future directions, J Child Psychol Psychiatry 51, 390–431. 39. Gotlib, I. H., Hamilton, J. P., Cooney, R. E., Singh, M. K., Henry, M. L., and Joormann, J. Neural processing of reward and loss in girls at risk for major depression, Arch Gen Psychiatry 67, 380–387.

24


40. Pantelis, C., Velakoulis, D., Wood, S. J., Yucel, M., Yung, A. R., Phillips, L. J., Sun, D. Q., and McGorry, P. D. (2007) Neuroimaging and emerging psychotic disorders: the Melbourne ultra-high risk studies, Int Rev Psychiatry 19, 371–381. 41. Yung, A. R., Phillips, L. J., McGorry, P. D., McFarlane, C. A., Francey, S., Harrigan, S., Patton, G. C., and Jackson, H. J. (1998) Prediction of psychosis. A step towards indicated prevention of schizophrenia, Br J Psychiatry Suppl 172, 14–20. 42. Walterfang, M., Yung, A., Wood, A. G., Reutens, D. C., Phillips, L., Wood, S. J., Chen, J., Velakoulis, D., McGorry, P. D., and Pantelis, C. (2008) Corpus callosum shape alterations in individuals prior to the onset of psychosis, Schizophr Res 103, 1–10. 43. Walterfang, M., McGuire, P. K., Yung, A. R., Phillips, L. J., Velakoulis, D., Wood, S. J., Suckling, J., Bullmore, E. T., Brewer, W., Soulsby, B., Desmond, P., McGorry, P. D., and Pantelis, C. (2008) White matter volume changes in people who develop psychosis, Br J Psychiatry 193, 210–215. 44. Woodruff, P. W., McManus, I. C., and David, A. S. (1995) Meta-analysis of corpus callosum size in schizophrenia, J Neurol Neurosurg Psychiatry 58, 457–461. 45. Ferdinand, R. F., and Verhulst, F. C. (1995) Psychopathology from adolescence into young adulthood: an 8-year follow-up study, Am J Psychiatry 152, 1586–1594. 46. Ferdinand, R. F., Verhulst, F. C., and Wiznitzer, M. (1995) Continuity and change of self-reported problem behaviors from adolescence into young adulthood, J Am Acad Child Adolesc Psychiatry 34, 680–690. 47. Hofstra, M. B., Van der Ende, J., and Verhulst, F. C. (2002) Pathways of self-reported problem behaviors from adolescence into adulthood, Am J Psychiatry 159, 401–407. 48. Hofstra, M. B., van der Ende, J., and Verhulst, F. C. (2002) Child and adolescent problems predict DSM-IV disorders in adulthood: a 14-year follow-up of a Dutch epidemiological sample, J Am Acad Child Adolesc Psychiatry 41, 182–189. 49. Hofstra, M. B., Van der Ende, J., and Verhulst, F. C. (2000) Continuity and change of psychopathology from childhood into adulthood: a 14-year follow-up study, J Am Acad Child Adolesc Psychiatry 39, 850–858. 50. Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., and Poulton, R. (2003) Prior juvenile diagnoses in adults with mental disorder: developmental follow-back

51.

52.

53.

54.

55.

56.

57.

58.

59.

60.

61.

of a prospective-longitudinal cohort, Arch Gen Psychiatry 60, 709–717. Biro, F. M., and Wien, M. Childhood obesity and adult morbidities, Am J Clin Nutr 91, 1499S–1505S. Deshmukh-Taskar, P., Nicklas, T. A., Morales, M., Yang, S. J., Zakeri, I., and Berenson, G. S. (2006) Tracking of overweight status from childhood to young adulthood: the Bogalusa Heart Study, Eur J Clin Nutr 60, 48–57. Guo, S. S., and Chumlea, W. C. (1999) Tracking of body mass index in children in relation to overweight in adulthood, Am J Clin Nutr 70, 145S-148S. Whitaker, R. C., Wright, J. A., Pepe, M. S., Seidel, K. D., and Dietz, W. H. (1997) Predicting obesity in young adulthood from childhood and parental obesity, N Engl J Med 337, 869–873. Reilly, J. J., Armstrong, J., Dorosty, A. R., Emmett, P. M., Ness, A., Rogers, I., Steer, C., and Sherriff, A. (2005) Early life risk factors for obesity in childhood: cohort study, BMJ 330, 1357. Krishnan, V., Han, M. H., Graham, D. L., Berton, O., Renthal, W., Russo, S. J., Laplant, Q., Graham, A., Lutter, M., Lagace, D. C., Ghose, S., Reister, R., Tannous, P., Green, T. A., Neve, R. L., Chakravarty, S., Kumar, A., Eisch, A. J., Self, D. W., Lee, F. S., Tamminga, C. A., Cooper, D. C., Gershenfeld, H. K., and Nestler, E. J. (2007) Molecular adaptations underlying susceptibility and resistance to social defeat in brain reward regions, Cell 131, 391–404. Belin, D., Mar, A. C., Dalley, J. W., Robbins, T. W., and Everitt, B. J. (2008) High impulsivity predicts the switch to compulsive cocaine-taking, Science 320, 1352–1355. Gorwood, P. (2008) Neurobiological mechanisms of anhedonia, Dialogues Clin Neurosci 10, 291–299. Kessler, R. C., McGonagle, K. A., Zhao, S., Nelson, C. B., Hughes, M., Eshleman, S., Wittchen, H. U., and Kendler, K. S. (1994) Lifetime and 12-month prevalence of DSMIII-R psychiatric disorders in the United States. Results from the National Comorbidity Survey, Arch Gen Psychiatry 51, 8–19. Kessler, R. C., DuPont, R. L., Berglund, P., and Wittchen, H. U. (1999) Impairment in pure and comorbid generalized anxiety disorder and major depression at 12 months in two national surveys, Am J Psychiatry 156, 1915–1923. Moffitt, T. E., Caspi, A., Harrington, H., Milne, B. J., Melchior, M., Goldberg, D., and

1 Psychiatric Illness in Animal Research

62.

63.

64.

65.

66.

67.

68. 69.

70.

71.

72.

Poulton, R. (2007) Generalized anxiety disorder and depression: childhood risk factors in a birth cohort followed to age 32, Psychol Med 37, 441–452. Ormel, J., VonKorff, M., Ustun, T. B., Pini, S., Korten, A., and Oldehinkel, T. (1994) Common mental disorders and disability across cultures. Results from the WHO Collaborative Study on Psychological Problems in General Health Care, Jama 272, 1741–1748. Olfson, M., Fireman, B., Weissman, M. M., Leon, A. C., Sheehan, D. V., Kathol, R. G., Hoven, C., and Farber, L. (1997) Mental disorders and disability among patients in a primary care group practice, Am J Psychiatry 154, 1734–1740. Mullen, P. E., Martin, J. L., Anderson, J. C., Romans, S. E., and Herbison, G. P. (1996) The long-term impact of the physical, emotional, and sexual abuse of children: a community study, Child Abuse Negl 20, 7–21. Bebbington, P. E., Bhugra, D., Brugha, T., Singleton, N., Farrell, M., Jenkins, R., Lewis, G., and Meltzer, H. (2004) Psychosis, victimisation and childhood disadvantage: evidence from the second British National Survey of Psychiatric Morbidity, Br J Psychiatry 185, 220–226. Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., and Wang, P. (2010) Research domain criteria (RDoC): toward a new classification framework for research on mental disorders, Am J Psychiatry 167, 748–751. Delgado, M. R., Nearing, K. I., Ledoux, J. E., and Phelps, E. A. (2008) Neural circuitry underlying the regulation of conditioned fear and its relation to extinction, Neuron 59, 829–838. LeDoux, J. E. (2000) Emotion circuits in the brain, Annu Rev Neurosci 23, 155–184. Berridge, K. C., and Robinson, T. E. (1998) What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience?, Brain Res Brain Res Rev 28, 309–369. O’Doherty, J., Kringelbach, M. L., Rolls, E. T., Hornak, J., and Andrews, C. (2001) Abstract reward and punishment representations in the human orbitofrontal cortex, Nat Neurosci 4, 95–102. Roesch, M. R., and Olson, C. R. (2004) Neuronal activity related to reward value and motivation in primate frontal cortex, Science 304, 307–310. Nestler, E. J., Barrot, M., DiLeone, R. J., Eisch, A. J., Gold, S. J., and Monteggia, L.

73.

74.

75.

76.

77.

78.

79.

80.

81.

82.

25

M. (2002) Neurobiology of depression, Neuron 34, 13–25. Squire, L. R. (1992) Memory and the hippocampus: a synthesis from findings with rats, monkeys, and humans, Psychol Rev 99, 195–231. Fanselow, M. S., and Dong, H. W. Are the dorsal and ventral hippocampus functionally distinct structures?, Neuron 65, 7–19. Strauss, G. P., Frank, M. J., Waltz, J. A., Kasanova, Z., Herbener, E. S., and Gold, J. M. (2011) Deficits in Positive Reinforcement Learning and Uncertainty-Driven Exploration Are Associated with Distinct Aspects of Negative Symptoms in Schizophrenia, Biol Psychiatry. Blackwood, D. H., Fordyce, A., Walker, M. T., St Clair, D. M., Porteous, D. J., and Muir, W. J. (2001) Schizophrenia and affective disorders – cosegregation with a translocation at chromosome 1q42 that directly disrupts brain-expressed genes: clinical and P300 findings in a family, Am J Hum Genet 69, 428–433. Bray, N. J. (2008) Gene expression in the etiology of schizophrenia, Schizophr Bull 34, 412–418. Karssen, A. M., Li, J. Z., Her, S., Patel, P. D., Meng, F., Evans, S. J., Vawter, M. P., Tomita, H., Choudary, P. V., Bunney, W. E., Jr., Jones, E. G., Watson, S. J., Akil, H., Myers, R. M., Schatzberg, A. F., and Lyons, D. M. (2006) Application of microarray technology in primate behavioral neuroscience research, Methods 38, 227–234. Newton, S. S., Bennett, A., and Duman, R. S. (2005) Production of custom microarrays for neuroscience research, Methods 37, 238–246. Uranova, N. A., Vostrikov, V. M., Vikhreva, O. V., Zimina, I. S., Kolomeets, N. S., and Orlovskaya, D. D. (2007) The role of oligodendrocyte pathology in schizophrenia, Int J Neuropsychopharmacol 10, 537–545. Hakak, Y., Walker, J. R., Li, C., Wong, W. H., Davis, K. L., Buxbaum, J. D., Haroutunian, V., and Fienberg, A. A. (2001) Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia, Proc Natl Acad Sci USA 98, 4746–4751. Sugai, T., Kawamura, M., Iritani, S., Araki, K., Makifuchi, T., Imai, C., Nakamura, R., Kakita, A., Takahashi, H., and Nawa, H. (2004) Prefrontal abnormality of schizophrenia revealed by DNA microarray: impact on glial and neurotrophic gene expression, Ann N Y Acad Sci 1025, 84–91.

26


83. Tkachev, D., Mimmack, M. L., Ryan, M. M., Wayland, M., Freeman, T., Jones, P. B., Starkey, M., Webster, M. J., Yolken, R. H., and Bahn, S. (2003) Oligodendrocyte dysfunction in schizophrenia and bipolar disorder, Lancet 362, 798–805. 84. Coplan, J. D., Abdallah, C. G., Tang, C. Y., Mathew, S. J., Martinez, J., Hof, P. R., Smith, E. L., Dwork, A. J., Perera, T. D., Pantol, G., Carpenter, D., Rosenblum, L. A., Shungu, D. C., Gelernter, J., Kaffman, A., Jackowski, A., Kaufman, J., and Gorman, J. M. (2010) The role of early life stress in development of the anterior limb of the internal capsule in nonhuman primates, Neurosci Lett 480, 93–96. 85. Cotter, D., Mackay, D., Chana, G., Beasley, C., Landau, S., and Everall, I. P. (2002) Reduced neuronal size and glial cell density in area 9 of the dorsolateral prefrontal cortex in subjects with major depressive disorder, Cereb Cortex 12, 386–394. 86. De Bellis, M. D., Keshavan, M. S., Beers, S. R., Hall, J., Frustaci, K., Masalehdan, A., Noll, J., and Boring, A. M. (2001) Sex differences in brain maturation during childhood and adolescence, Cereb Cortex 11, 552–557. 87. De Bellis, M. D., Keshavan, M. S., Shifflett, H., Iyengar, S., Beers, S. R., Hall, J., and Moritz, G. (2002) Brain structures in pediatric maltreatment-related posttraumatic stress disorder: a sociodemographically matched study, Biol Psychiatry 52, 1066–1078. 88. Vataja, R., Pohjasvaara, T., Leppavuori, A., Mantyla, R., Aronen, H. J., Salonen, O., Kaste, M., and Erkinjuntti, T. (2001) Magnetic resonance imaging correlates of depression after ischemic stroke, Arch Gen Psychiatry 58, 925–931. 89. Walterfang, M., Yucel, M., Barton, S., Reutens, D. C., Wood, A. G., Chen, J., Lorenzetti, V., Velakoulis, D., Pantelis, C., and Allen, N. B. (2009) Corpus callosum size and shape in individuals with current and past depression, J Affect Disord 115, 411–420. 90. Aston, C., Jiang, L., and Sokolov, B. P. (2005) Transcriptional profiling reveals evidence for signaling and oligodendroglial abnormalities in the temporal cortex from patients with major depressive disorder, Mol Psychiatry 10, 309–322. 91. Fisher, S. E., Lai, C. S., and Monaco, A. P. (2003) Deciphering the genetic basis of speech and language disorders, Annu Rev Neurosci 26, 57–80. 92. Enard, W., Przeworski, M., Fisher, S. E., Lai, C. S., Wiebe, V., Kitano, T., Monaco, A. P., and Paabo, S. (2002) Molecular evolution of

93.

94.

95.

96.

97.

98.

FOXP2, a gene involved in speech and language, Nature 418, 869–872. Konopka, G., Bomar, J. M., Winden, K., Coppola, G., Jonsson, Z. O., Gao, F., Peng, S., Preuss, T. M., Wohlschlegel, J. A., and Geschwind, D. H. (2009) Human-specific transcriptional regulation of CNS development genes by FOXP2, Nature 462, 213–217. Sebat, J., Lakshmi, B., Troge, J., Alexander, J., Young, J., Lundin, P., Maner, S., Massa, H., Walker, M., Chi, M., Navin, N., Lucito, R., Healy, J., Hicks, J., Ye, K., Reiner, A., Gilliam, T. C., Trask, B., Patterson, N., Zetterberg, A., and Wigler, M. (2004) Largescale copy number polymorphism in the human genome, Science 305, 525–528. Iafrate, A. J., Feuk, L., Rivera, M. N., Listewnik, M. L., Donahoe, P. K., Qi, Y., Scherer, S. W., and Lee, C. (2004) Detection of large-scale variation in the human genome, Nat Genet 36, 949–951. Schizophrenia Consortium (2008) Rare chromosomal deletions and duplications increase risk of schizophrenia, Nature 455, 237–241. Walsh, T., McClellan, J. M., McCarthy, S. E., Addington, A. M., Pierce, S. B., Cooper, G. M., Nord, A. S., Kusenda, M., Malhotra, D., Bhandari, A., Stray, S. M., Rippey, C. F., Roccanova, P., Makarov, V., Lakshmi, B., Findling, R. L., Sikich, L., Stromberg, T., Merriman, B., Gogtay, N., Butler, P., Eckstrand, K., Noory, L., Gochman, P., Long, R., Chen, Z., Davis, S., Baker, C., Eichler, E. E., Meltzer, P. S., Nelson, S. F., Singleton, A. B., Lee, M. K., Rapoport, J. L., King, M. C., and Sebat, J. (2008) Rare structural variants disrupt multiple genes in neurodevelopmental pathways in schizophrenia, Science 320, 539–543. Rujescu, D., Ingason, A., Cichon, S., Pietilainen, O. P., Barnes, M. R., Toulopoulou, T., Picchioni, M., Vassos, E., Ettinger, U., Bramon, E., Murray, R., Ruggeri, M., Tosato, S., Bonetto, C., Steinberg, S., Sigurdsson, E., Sigmundsson, T., Petursson, H., Gylfason, A., Olason, P. I., Hardarsson, G., Jonsdottir, G. A., Gustafsson, O., Fossdal, R., Giegling, I., Moller, H. J., Hartmann, A. M., Hoffmann, P., Crombie, C., Fraser, G., Walker, N., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Djurovic, S., Melle, I., Andreassen, O. A., Hansen, T., Werge, T., Kiemeney, L. A., Franke, B., Veltman, J., Buizer-Voskamp, J. E., Sabatti, C., Ophoff, R. A., Rietschel, M., Nothen, M. M., Stefansson, K., Peltonen, L., St Clair, D., Stefansson, H., and Collier, D. A. (2009) Disruption of the neurexin 1 gene is associated with schizophrenia, Hum Mol Genet 18, 988–996.

1 Psychiatric Illness in Animal Research 99. Stefansson, H., Rujescu, D., Cichon, S., Pietilainen, O. P., Ingason, A., Steinberg, S., Fossdal, R., Sigurdsson, E., Sigmundsson, T., Buizer-Voskamp, J. E., Hansen, T., Jakobsen, K. D., Muglia, P., Francks, C., Matthews, P. M., Gylfason, A., Halldorsson, B. V., Gudbjartsson, D., Thorgeirsson, T. E., Sigurdsson, A., Jonasdottir, A., Bjornsson, A., Mattiasdottir, S., Blondal, T., Haraldsson, M., Magnusdottir, B. B., Giegling, I., Moller, H. J., Hartmann, A., Shianna, K. V., Ge, D., Need, A. C., Crombie, C., Fraser, G., Walker, N., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Paunio, T., Toulopoulou, T., Bramon, E., Di Forti, M., Murray, R., Ruggeri, M., Vassos, E., Tosato, S., Walshe, M., Li, T., Vasilescu, C., Muhleisen, T. W., Wang, A. G., Ullum, H., Djurovic, S., Melle, I., Olesen, J., Kiemeney, L. A., Franke, B., Sabatti, C., Freimer, N. B., Gulcher, J. R., Thorsteinsdottir, U., Kong, A., Andreassen, O. A., Ophoff, R. A., Georgi, A., Rietschel, M., Werge, T., Petursson, H., Goldstein, D. B., Nothen, M. M., Peltonen, L., Collier, D. A., St Clair, D., and Stefansson, K. (2008) Large recurrent microdeletions associated with schizophrenia, Nature 455, 232–236. 100. Muir, W. J., Pickard, B. S., and Blackwood, D. H. (2008) Disrupted-in-Schizophrenia-1, Curr Psychiatry Rep 10, 140–147. 101. Lifton, R. P. (2010) Individual genomes on the horizon, N Engl J Med 362, 1235–1236. 102. Kircher, M., and Kelso, J. High-throughput DNA sequencing – concepts and limitations, Bioessays 32, 524–536. 103. Bilguvar, K., Ozturk, A. K., Louvi, A., Kwan, K. Y., Choi, M., Tatli, B., Yalnizoglu, D., Tuysuz, B., Caglayan, A. O., Gokben, S., Kaymakcalan, H., Barak, T., Bakircioglu, M., Yasuno, K., Ho, W., Sanders, S., Zhu, Y., Yilmaz, S., Dincer, A., Johnson, M. H., Bronen, R. A., Kocer, N., Per, H., Mane, S., Pamir, M. N., Yalcinkaya, C., Kumandas, S., Topcu, M., Ozmen, M., Sestan, N., Lifton, R. P., State, M. W., and Gunel, M. (2010) Whole-exome sequencing identifies recessive WDR62 mutations in severe brain malformations, Nature 467, 207–210. 104. Choi, M., Scholl, U. I., Ji, W., Liu, T., Tikhonova, I. R., Zumbo, P., Nayir, A., Bakkaloglu, A., Ozen, S., Sanjad, S., NelsonWilliams, C., Farhi, A., Mane, S., and Lifton, R. P. (2009) Genetic diagnosis by whole exome capture and massively parallel DNA sequencing, Proc Natl Acad Sci USA 106, 19096–19101. 105. Ng, S. B., Bigham, A. W., Buckingham, K. J., Hannibal, M. C., McMillin, M. J., Gildersleeve,

106.

107.

108.

109.

110.

111.

112.

113.

27

H. I., Beck, A. E., Tabor, H. K., Cooper, G. M., Mefford, H. C., Lee, C., Turner, E. H., Smith, J. D., Rieder, M. J., Yoshiura, K., Matsumoto, N., Ohta, T., Niikawa, N., Nickerson, D. A., Bamshad, M. J., and Shendure, J. Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome, Nat Genet 42, 790–793. Ng, S. B., Buckingham, K. J., Lee, C., Bigham, A. W., Tabor, H. K., Dent, K. M., Huff, C. D., Shannon, P. T., Jabs, E. W., Nickerson, D. A., Shendure, J., and Bamshad, M. J. Exome sequencing identifies the cause of a mendelian disorder, Nat Genet 42, 30–35. Ng, S. B., Turner, E. H., Robertson, P. D., Flygare, S. D., Bigham, A. W., Lee, C., Shaffer, T., Wong, M., Bhattacharjee, A., Eichler, E. E., Bamshad, M., Nickerson, D. A., and Shendure, J. (2009) Targeted capture and massively parallel sequencing of 12 human exomes, Nature 461, 272–276. Brunetti-Pierri, N., Berg, J. S., Scaglia, F., Belmont, J., Bacino, C. A., Sahoo, T., Lalani, S. R., Graham, B., Lee, B., Shinawi, M., Shen, J., Kang, S. H., Pursley, A., Lotze, T., Kennedy, G., Lansky-Shafer, S., Weaver, C., Roeder, E. R., Grebe, T. A., Arnold, G. L., Hutchison, T., Reimschisel, T., Amato, S., Geragthy, M. T., Innis, J. W., Obersztyn, E., Nowakowska, B., Rosengren, S. S., Bader, P. I., Grange, D. K., Naqvi, S., Garnica, A. D., Bernes, S. M., Fong, C. T., Summers, A., Walters, W. D., Lupski, J. R., Stankiewicz, P., Cheung, S. W., and Patel, A. (2008) Recurrent reciprocal 1q21.1 deletions and duplications associated with microcephaly or macrocephaly and developmental and behavioral abnormalities, Nat Genet 40, 1466–1471. Kwon, I., and Schaffer, D. V. (2008) Designer gene delivery vectors: molecular engineering and evolution of adeno-associated viral vectors for enhanced gene transfer, Pharm Res 25, 489–499. Hommel, J. D., Sears, R. M., Georgescu, D., Simmons, D. L., and DiLeone, R. J. (2003) Local gene knockdown in the brain using viral-mediated RNA interference, Nat Med 9, 1539–1544. McCown, T. J. (2010) The future of epilepsy treatment: focus on adeno-associated virus vector gene therapy, Drug News Perspect 23, 281–286. Chen, G., Twyman, R., and Manji, H. K. (2010) p11 and gene therapy for severe psychiatric disorders: a practical goal?, Sci Transl Med 2, 54ps51. Takahashi, K., Tanabe, K., Ohnuki, M., Narita, M., Ichisaka, T., Tomoda, K., and

28

114.

115.

116.

117.

118.

119.

120.

121.

122.

A. Kaffman and J.J. Krystal Yamanaka, S. (2007) Induction of pluripotent stem cells from adult human fibroblasts by defined factors, Cell 131, 861–872. Hotta, A., Cheung, A. Y., Farra, N., Vijayaragavan, K., Seguin, C. A., Draper, J. S., Pasceri, P., Maksakova, I. A., Mager, D. L., Rossant, J., Bhatia, M., and Ellis, J. (2009) Isolation of human iPS cells using EOS lentiviral vectors to select for pluripotency, Nat Methods 6, 370–376. Jacobs, P. A., Aitken, J., Frackiewicz, A., Law, P., Newton, M. S., and Smith, P. G. (1970) The inheritance of translocations in man: data from families ascertained through a balanced heterozygote, Ann Hum Genet 34, 119–136. St Clair, D., Blackwood, D., Muir, W., Carothers, A., Walker, M., Spowart, G., Gosden, C., and Evans, H. J. (1990) Association within a family of a balanced autosomal translocation with major mental illness, Lancet 336, 13–16. Millar, J. K., Christie, S., Anderson, S., Lawson, D., Hsiao-Wei Loh, D., Devon, R. S., Arveiler, B., Muir, W. J., Blackwood, D. H., and Porteous, D. J. (2001) Genomic structure and localisation within a linkage hotspot of Disrupted In Schizophrenia 1, a gene disrupted by a translocation segregating with schizophrenia, Mol Psychiatry 6, 173–178. Brandon, N. J., Handford, E. J., Schurov, I., Rain, J. C., Pelling, M., Duran-Jimeniz, B., Camargo, L. M., Oliver, K. R., Beher, D., Shearman, M. S., and Whiting, P. J. (2004) Disrupted in Schizophrenia 1 and Nudel form a neurodevelopmentally regulated protein complex: implications for schizophrenia and other major neurological disorders, Mol Cell Neurosci 25, 42–55. Brandon, N. J., Millar, J. K., Korth, C., Sive, H., Singh, K. K., and Sawa, A. (2009) Understanding the role of DISC1 in psychiatric disease and during normal development, J Neurosci 29, 12768–12775. Blackwood, D. H., Glabus, M. F., Dunan, J., O’Carroll, R. E., Muir, W. J., and Ebmeier, K. P. (1999) Altered cerebral perfusion measured by SPECT in relatives of patients with schizophrenia. Correlations with memory and P300, Br J Psychiatry 175, 357–366. O’Donnell, B. F., McCarley, R. W., Potts, G. F., Salisbury, D. F., Nestor, P. G., Hirayasu, Y., Niznikiewicz, M. A., Barnard, J., Shen, Z. J., Weinstein, D. M., Bookstein, F. L., and Shenton, M. E. (1999) Identification of neural circuits underlying P300 abnormalities in schizophrenia, Psychophysiology 36, 388–398. Turetsky, B. I., Cannon, T. D., and Gur, R. E. (2000) P300 subcomponent abnormalities in schizophrenia: III. Deficits In unaffected

123.

124.

125.

126.

127.

128.

129.

130.

siblings of schizophrenic probands, Biol Psychiatry 47, 380–390. Clapcote, S. J., Lipina, T. V., Millar, J. K., Mackie, S., Christie, S., Ogawa, F., Lerch, J. P., Trimble, K., Uchiyama, M., Sakuraba, Y., Kaneda, H., Shiroishi, T., Houslay, M. D., Henkelman, R. M., Sled, J. G., Gondo, Y., Porteous, D. J., and Roder, J. C. (2007) Behavioral phenotypes of Disc1 missense mutations in mice, Neuron 54, 387–402. Niwa, M., Kamiya, A., Murai, R., Kubo, K., Gruber, A. J., Tomita, K., Lu, L., Tomisato, S., Jaaro-Peled, H., Seshadri, S., Hiyama, H., Huang, B., Kohda, K., Noda, Y., O’Donnell, P., Nakajima, K., Sawa, A., and Nabeshima, T. (2010) Knockdown of DISC1 by in utero gene transfer disturbs postnatal dopaminergic maturation in the frontal cortex and leads to adult behavioral deficits, Neuron 65, 480–489. Kamiya, A., Kubo, K., Tomoda, T., Takaki, M., Youn, R., Ozeki, Y., Sawamura, N., Park, U., Kudo, C., Okawa, M., Ross, C. A., Hatten, M. E., Nakajima, K., and Sawa, A. (2005) A schizophrenia-associated mutation of DISC1 perturbs cerebral cortex development, Nat Cell Biol 7, 1167–1178. Morris, J. A., Kandpal, G., Ma, L., and Austin, C. P. (2003) DISC1 (Disrupted-InSchizophrenia 1) is a centrosome-associated protein that interacts with MAP1A, MIPT3, ATF4/5 and NUDEL: regulation and loss of interaction with mutation, Hum Mol Genet 12, 1591–1608. Koike, H., Arguello, P. A., Kvajo, M., Karayiorgou, M., and Gogos, J. A. (2006) Disc1 is mutated in the 129 S6/SvEv strain and modulates working memory in mice, Proc Natl Acad Sci USA 103, 3693–3697. Benes, F. M., Taylor, J. B., and Cunningham, M. C. (2000) Convergence and plasticity of monoaminergic systems in the medial prefrontal cortex during the postnatal period: implications for the development of psychopathology, Cereb Cortex 10, 1014–1027. National Research Council (US) and Institute of Medicine (US) Committee on the Prevention of Mental Disorders and Substance Abuse Among Children, Y., and Young Adults: Research Advances and Promising Interventions (2009) Preventing mental, emotional and behavioral disorders among young people: progress and possibilities, National Academies Press (US, Washington (DC). Gilbert, R., Widom, C. S., Browne, K., Fergusson, D., Webb, E., and Janson, S. (2009) Burden and consequences of child maltreatment in high-income countries, Lancet 373, 68–81.

1 Psychiatric Illness in Animal Research 131. Kaffman, A., and Meaney, M. (2007) Neurodevelopmental Sequelae of Postnatal Maternal Care in Rodents: Clinical and Research Implications of Molecular Insights, J Child Psychol Psychiatry 48, 224–244. 132. Nemeroff, C. B., Heim, C. M., Thase, M. E., Klein, D. N., Rush, A. J., Schatzberg, A. F., Ninan, P. T., McCullough, J. P., Jr., Weiss, P. M., Dunner, D. L., Rothbaum, B. O., Kornstein, S., Keitner, G., and Keller, M. B. (2003) Differential responses to psychotherapy versus pharmacotherapy in patients with chronic forms of major depression and childhood trauma, Proc Natl Acad Sci U S A 100, 14293–14296. 133. Zeanah, C. H., Egger, H. L., Smyke, A. T., Nelson, C. A., Fox, N. A., Marshall, P. J., and Guthrie, D. (2009) Institutional rearing and psychiatric disorders in romanian preschool children, Am J Psychiatry 166, 777–785. 134. Champagne, F. A., Francis, D. D., Mar, A., and Meaney, M. J. (2003) Variations in maternal care in the rat as a mediating influence for the effects of environment on development, Physiol Behav 79, 359–371. 135. Meaney, M. J. (2001) Maternal care, gene expression, and the transmission of individual differences in stress reactivity across generations, Annu Rev Neurosci 24, 1161–1192. 136. Szyf, M., McGowan, P., and Meaney, M. J. (2008) The social environment and the epigenome, Environ Mol Mutagen 49, 46–60. 137. Weaver, I. C., Cervoni, N., Champagne, F. A., D’Alessio, A. C., Sharma, S., Seckl, J. R., Dymov, S., Szyf, M., and Meaney, M. J. (2004) Epigenetic programming by maternal behavior, Nat Neurosci 7, 847–854. 138. Weaver, I. C., D’Alessio, A. C., Brown, S. E., Hellstrom, I. C., Dymov, S., Sharma, S., Szyf, M., and Meaney, M. J. (2007) The transcription factor nerve growth factor-inducible protein a mediates epigenetic programming: altering epigenetic marks by immediate-early genes, J Neurosci 27, 1756–1768. 139. Weaver, I. C., Champagne, F. A., Brown, S. E., Dymov, S., Sharma, S., Meaney, M. J., and Szyf, M. (2005) Reversal of maternal programming of stress responses in adult offspring through methyl supplementation: altering epigenetic marking later in life, J Neurosci 25, 11045–11054. 140. McGowan, P. O., Sasaki, A., D’Alessio, A. C., Dymov, S., Labonte, B., Szyf, M., Turecki, G., and Meaney, M. J. (2009) Epigenetic regulation of the glucocorticoid receptor in human brain associates with childhood abuse, Nat Neurosci 12, 342–348. 141. Moffitt, T. E., Harrington, H., Caspi, A., Kim-Cohen, J., Goldberg, D., Gregory, A.

142.

143.

144.

145.

146.

147.

148.

149.

150.

151.

29

M., and Poulton, R. (2007) Depression and generalized anxiety disorder: cumulative and sequential comorbidity in a birth cohort followed prospectively to age 32 years, Arch Gen Psychiatry 64, 651–660. Caldji, C., Diorio, J., and Meaney, M. J. (2003) Variations in maternal care alter GABA(A) receptor subunit expression in brain regions associated with fear, Neuropsychopharmacology 28, 1950–1959. Caldji, C., Francis, D., Sharma, S., Plotsky, P. M., and Meaney, M. J. (2000) The effects of early rearing environment on the development of GABAA and central benzodiazepine receptor levels and novelty-induced fearfulness in the rat, Neuropsychopharmacology 22, 219–229. Caldji, C., Tannenbaum, B., Sharma, S., Francis, D., Plotsky, P. M., and Meaney, M. J. (1998) Maternal care during infancy regulates the development of neural systems mediating the expression of fearfulness in the rat, Proc Natl Acad Sci USA 95, 5335–5340. Francis, D. D., Caldji, C., Champagne, F., Plotsky, P. M., and Meaney, M. J. (1999) The role of corticotropin-releasing factor – norepinephrine systems in mediating the effects of early experience on the development of behavioral and endocrine responses to stress, Biol Psychiatry 46, 1153–1166. Francis, D. D., and Meaney, M. J. (1999) Maternal care and the development of stress responses, Curr Opin Neurobiol 9, 128–134. Meaney, M. J., Bhatnagar, S., Larocque, S., McCormick, C., Shanks, N., Sharma, S., Smythe, J., Viau, V., and Plotsky, P. M. (1993) Individual differences in the hypothalamicpituitary-adrenal stress response and the hypothalamic CRF system, Ann N Y Acad Sci 697, 70–85. Anisman, H., Zaharia, M. D., Meaney, M. J., and Merali, Z. (1998) Do early-life events permanently alter behavioral and hormonal responses to stressors?, Int J Dev Neurosci 16, 149–164. Champagne, F., Diorio, J., Sharma, S., and Meaney, M. J. (2001) Naturally occurring variations in maternal behavior in the rat are associated with differences in estrogen-inducible central oxytocin receptors, Proc Natl Acad Sci USA 98, 12736–12741. Champagne, F. A., Chretien, P., Stevenson, C. W., Zhang, T. Y., Gratton, A., and Meaney, M. J. (2004) Variations in nucleus accumbens dopamine associated with individual differences in maternal behavior in the rat, J Neurosci 24, 4113–4123. Champagne, F. A., Weaver, I. C., Diorio, J., Dymov, S., Szyf, M., and Meaney, M. J.

30

152.

153.

154.

155.

156.

157.

158.

159.

160.

161.

162.

A. Kaffman and J.J. Krystal (2006) Maternal Care Associated with Methylation of the Estrogen Receptor{alpha}1b Promoter and Estrogen Receptor{alpha} Expression in the Medial Preoptic Area of Female Offspring, Endocrinology 147, 2909–2915. Champagne, F. A., Weaver, I. C., Diorio, J., Sharma, S., and Meaney, M. J. (2003) Natural variations in maternal care are associated with estrogen receptor alpha expression and estrogen sensitivity in the medial preoptic area, Endocrinology 144, 4720–4724. Parent, C. I., and Meaney, M. J. (2008) The influence of natural variations in maternal care on play fighting in the rat, Dev Psychobiol 50, 767–776. Bredy, T. W., Grant, R. J., Champagne, D. L., and Meaney, M. J. (2003) Maternal care influences neuronal survival in the hippocampus of the rat, Eur J Neurosci 18, 2903–2909. Bredy, T. W., Humpartzoomian, R. A., Cain, D. P., and Meaney, M. J. (2003) Partial reversal of the effect of maternal care on cognitive function through environmental enrichment, Neuroscience 118, 571–576. Bredy, T. W., Zhang, T. Y., Grant, R. J., Diorio, J., and Meaney, M. J. (2004) Peripubertal environmental enrichment reverses the effects of maternal care on hippocampal development and glutamate receptor subunit expression, Eur J Neurosci 20, 1355–1362. Champagne, D. L., Bagot, R. C., van Hasselt, F., Ramakers, G., Meaney, M. J., de Kloet, E. R., Joels, M., and Krugers, H. (2008) Maternal care and hippocampal plasticity: evidence for experience-dependent structural plasticity, altered synaptic functioning, and differential responsiveness to glucocorticoids and stress, J Neurosci 28, 6037–6045. Liu, D., Diorio, J., Day, J. C., Francis, D. D., and Meaney, M. J. (2000) Maternal care, hippocampal synaptogenesis and cognitive development in rats, Nat Neurosci 3, 799–806. Caldji, C., Diorio, J., and Meaney, M. J. (2000) Variations in maternal care in infancy regulate the development of stress reactivity, Biol Psychiatry 48, 1164–1174. Francis, D., Diorio, J., Liu, D., and Meaney, M. J. (1999) Nongenomic transmission across generations of maternal behavior and stress responses in the rat, Science 286, 1155–1158. Laplante, P., Diorio, J., and Meaney, M. J. (2002) Serotonin regulates hippocampal glucocorticoid receptor expression via a 5-HT7 receptor, Brain Res Dev Brain Res 139, 199–203. Liu, D., Caldji, C., Sharma, S., Plotsky, P. M., and Meaney, M. J. (2000) Influence of

163.

164.

165.

166.

167.

168.

169.

170.

171.

neonatal rearing conditions on stress-induced adrenocorticotropin responses and norepinepherine release in the hypothalamic paraventricular nucleus, J Neuroendocrinol 12, 5–12. Liu, D., Diorio, J., Tannenbaum, B., Caldji, C., Francis, D., Freedman, A., Sharma, S., Pearson, D., Plotsky, P. M., and Meaney, M. J. (1997) Maternal care, hippocampal glucocorticoid receptors, and hypothalamic-pituitary-adrenal responses to stress, Science 277, 1659–1662. Meaney, M. J., and Aitken, D. H. (1985) The effects of early postnatal handling on hippocampal glucocorticoid receptor concentrations: temporal parameters, Brain Res 354, 301–304. Weaver, I. C., La Plante, P., Weaver, S., Parent, A., Sharma, S., Diorio, J., Chapman, K. E., Seckl, J. R., Szyf, M., and Meaney, M. J. (2001) Early environmental regulation of hippocampal glucocorticoid receptor gene expression: characterization of intracellular mediators and potential genomic target sites, Mol Cell Endocrinol 185, 205–218. Zhang, T. Y., Chretien, P., Meaney, M. J., and Gratton, A. (2005) Influence of naturally occurring variations in maternal care on prepulse inhibition of acoustic startle and the medial prefrontal cortical dopamine response to stress in adult rats, J Neurosci 25, 1493–1502. Zhang, T. Y., Hellstrom, I. C., Bagot, R. C., Wen, X., Diorio, J., and Meaney, M. J. Maternal care and DNA methylation of a glutamic acid decarboxylase 1 promoter in rat hippocampus, J Neurosci 30, 13130–13137. Huot, R. L., Thrivikraman, K. V., Meaney, M. J., and Plotsky, P. M. (2001) Development of adult ethanol preference and anxiety as a consequence of neonatal maternal separation in Long Evans rats and reversal with antidepressant treatment, Psychopharmacology (Berl) 158, 366–373. Meaney, M. J., Brake, W., and Gratton, A. (2002) Environmental regulation of the development of mesolimbic dopamine systems: a neurobiological mechanism for vulnerability to drug abuse?, Psychoneuroendocrinology 27, 127–138. Francis, D. D., and Kuhar, M. J. (2008) Frequency of maternal licking and grooming correlates negatively with vulnerability to cocaine and alcohol use in rats, Pharmacol Biochem Behav 90, 497–500. Brake, W. G., Zhang, T. Y., Diorio, J., Meaney, M. J., and Gratton, A. (2004) Influence of early postnatal rearing conditions on mesocorticolimbic dopamine and behavioural responses to psychostimulants and stressors in adult rats, Eur J Neurosci 19, 1863–1874.

Chapter 2 Experimental Psychiatric Illness and Drug Abuse Models: From Human to Animal, an Overview Scott Edwards and George F. Koob Abstract Preclinical animal models have supported much of the recent rapid expansion of neuroscience research and have facilitated critical discoveries that undoubtedly benefit patients suffering from psychiatric disorders. This overview serves as an introduction for the following chapters describing both in vivo and in vitro preclinical models of psychiatric disease components and briefly describes models related to drug dependence and affective disorders. Although there are no perfect animal models of any psychiatric disorder, models do exist for many elements of each disease state or stage. In many cases, the development of certain models is essentially restricted to the human clinical laboratory domain for the purpose of maximizing validity, whereas the use of in vitro models may best represent an adjunctive, well-controlled means to model specific signaling mechanisms associated with psychiatric disease states. The data generated by preclinical models are only as valid as the model itself, and the development and refinement of animal models for human psychiatric disorders continues to be an important challenge. Collaborative relationships between basic neuroscience and clinical modeling could greatly benefit the development of new and better models, in addition to facilitating medications development. Key words: Animal model, Anxiety, Depression, Drug addiction, Preclinical model, Psychiatric disorders, Stress

1. Introduction The past two decades have seen monumental growth in the neurosciences, with a particular focus on the investigation of cellular and molecular correlates of psychiatric disorders. From these studies, various neuroadaptations in cortical and subcortical circuitry have been proposed to mediate the transition to specific disease states (e.g., refs. 1, 2). These advances in basic neuroscience research have relied heavily on the development and refinement of animal

Firas H. Kobeissy (ed.), Psychiatric Disorders: Methods and Protocols, Methods in Molecular Biology, vol. 829, DOI 10.1007/978-1-61779-458-2_2, © Springer Science+Business Media, LLC 2012

31

32

S. Edwards and G.F. Koob

models, and a critical review of past and current methods will support future endeavors toward the ultimate goal of providing better therapeutics for the clinical setting. This overview serves as an introduction for the following chapters describing both in vivo and in vitro preclinical models of psychiatric disorders. The appropriate modeling of such disease states is particularly challenging given that, despite significant progress, our fundamental understanding of the brain is still rudimentary compared with other systems. One upside to this dilemma is that investigators are able to concomitantly discover new mechanisms of brain function while striving to serve the unmet health needs of society. An important point to always remember is that the refinement of animal models for psychiatric diseases is a never-ending process for neuroscientists. Particularly when working with animals, the generation of positive data should never by itself justify the accuracy or validity of the methods employed. Although models are not necessarily intended to be perfect, the robustness and utility of data generated by them can only be as good as the model itself. Thus, models are almost never described as ultimate or complete, and investigators should continuously question and refine existing models for the benefit of future scientists and patients. In a similar vein, investigators should never be unduly anchored to existing models if a more valid model can be conceptualized.

2. Conceptual Framework for Animal Models of Psychiatric Disorders

Animal models for a complete syndrome of a psychiatric disorder are highly unlikely to be attainable either conceptually or practically. Thus, although there are no perfect animal models of any psychiatric disorder, models do exist for many elements of each disease state or stage. As such, an animal model can be viewed as an experimental preparation or set of reproducible methods developed to study a given phenomenon found in humans. Certain areas of the human condition are obviously a challenge to replicate in animal studies (e.g., comorbidity, polysubstance dependence, child abuse). Moreover, from a practical standpoint, psychiatric disorders are necessarily based on a nosology that is both complex and continually evolving and most certainly involves multiple subtypes, diverse etiology, and constellations of many different disorders. Thus, an approach to the development of animal models that has gained widespread acceptance is that animal models are most likely to have construct validity when the model mimics only the specific signs or symptoms associated with the psychopathological condition (3). It is, therefore, essential to understand exactly what conditions the animal model is intending to describe. Yet, the confounding

2

Models of Drug Abuse and Psychiatric Illness

33

influences of psychiatric comorbidity have at their basis overlapping and interconnected neuroanatomical and neurochemical systems. This is no better illustrated than when the treatment (or modeling) of one symptom produces an undesirable (yet familiar) side effect. This dilemma often forces us to choose between strictly limiting the number of variables under investigation (good science) and accurately modeling what may be a constellation of symptoms (good modeling). Moreover, many psychiatric diseases can be conceptualized as progressive timelines consisting of transitory stages of disease, each with unique criteria, necessitating multiple levels of depth and breadth to describe the composite phenomenon. For example, drug dependence can be described as a transition from recreational to excessive drug use, with accompanying psychiatric symptoms that may in turn exacerbate dependence. In addition to perturbing brain reward chemistry directly, repeated illicit drug exposure results in the recruitment of conditioning factors that may also support dependence with reexposure to these same environmental factors during protracted abstinence. Moreover, factors related to age (4–7), gender (8, 9), and even circadian rhythms (10, 11) are critical components of practically all psychiatric disease states. Nonetheless, the focus of animal models on a given component or stage of the disordered process eliminates a fundamental problem associated with basic models of human psychopathology, namely, the frustration of attempting to completely validate the entire syndrome. When definitive data related to a specific domain of the disorder can be generated, the confidence of cross-species validity is increased substantially. This framework also leads to a more pragmatic and reproducible approach to the study of the neurobiological mechanisms of the behavior in question.

3. Construct and Other Validities Associated with Animal Models

The most relevant conceptualization of validity for animal models of psychiatric disorders is the concept of construct validity (12). Construct validity refers to the interpretability, “meaningfulness,” or explanatory power of each animal model and thereby incorporates most other measures of validity in which multiple measures or dimensions are associated with conditions known to affect the construct (13). A procedure has construct validity if there are statistical or deterministic propositions that relate constructs to observables derived from the procedure (14). An alternative conceptualization of construct validity is the requirement that models meet the concept of functional equivalence, defined as “assessing how controlling variables influence outcome in the model and the target disorder” (15). The most straightforward process for testing

34


functional equivalence has been argued to be through common experimental manipulations, which should have similar effects in both the animal model and the target disorder (15). This process is very similar to the broad use of the term predictive validity (see below). By comparison, face validity often represents the starting point in the development of animal models in which animal syndromes are produced that resemble those found in humans (16). Reliability refers to the stability and consistency with which the variable of interest can be measured both within and between laboratories. Reliability is achieved when, following objective repeated measurement of the variable, small within- and betweensubject variability is observed, and the phenomenon is readily reproduced under reasonably similar environmental circumstances (for review, see ref. 17). Predictive validity in the more narrow sense refers to the model’s ability to accurately predict the human phenomenon based on the response of the model system. Predictive validity is used most often in animal models of psychiatric disorders to refer to the ability of the model to identify pharmacological agents with potential therapeutic benefits in humans (16, 18). Alternatively, others have argued that this type of predictive validity can be considered more explicitly as “pharmacological isomorphism,” which is the use of clinically relevant standards as positive controls to validate a model or set of procedures (19, 20). However, when predictive validity is more broadly expanded to explore the underlying physiological mechanisms of action related to psychiatric disorders, others have argued that it can incorporate other types of validity (e.g., etiological, convergent or concurrent, discriminant) considered to be important for animal models and thereby recenters around the concept of construct validity (21). However, it is critical to note that the particular behavior being used for an animal model may not even necessarily be symptomatic of the disorder, but nonetheless must be defined objectively and observed reliably. Indeed, the behavioral output being observed may be seen in both pathological and nonpathological states but still have predictive validity. A good example of such a case would be the widespread use of positive reinforcement or reward as an animal model of addiction. Drug reinforcement does not necessarily lead to addiction (e.g., the widespread social drinking of alcohol), but the self-administration of alcohol has major predictive validity for the binge/intoxication stage of addiction (described in the next section and in ref. 22), and it would appear impossible to model addiction without an initial positive reinforcement stage. The next sections of this chapter provide an overview of current models of drug dependence and affective disorders. Hopefully, it becomes clear that many of these models overlap to a great extent in terms of utility because many psychiatric disorders share common neural substrates.

2

4. Current Models of Psychiatric Illness and Drug Addiction 4.1. Overview of Current Models of Drug Addiction


35

Drug addiction has been conceptualized as a disorder that progresses from impulsivity to compulsivity in a connected cycle comprising three stages that correspond to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (23, 24): first, preoccupation/anticipation, second, binge/intoxication, and third, withdrawal/negative affect. In the past, much of the focus of animal and in vitro studies have been on the anatomical and synaptic sites and signaling mechanisms in the central nervous system on which drugs of abuse act initially to produce their positive reinforcing effects. More recently, new animal models of the motivational effects of dependence with more face validity for the human condition have been developed and employed. Motivation can be defined here as a “rough label for the relatively persisting states that make an animal initiate and maintain actions leading to particular outcomes or goals” (25). Thus, animal models of addiction on specific drugs, such as psychostimulants, opioids, alcohol, nicotine, and Δ9-tetrahydrocannabinol (THC), can be categorized by models relevant to different stages of the addiction cycle (26). Animal models for the binge/ intoxication stage of addiction can be considered as measuring acute drug reward/reinforcement, in which reward can be defined as a positive reinforcer with some added emotional value, such as pleasure, and positive reinforcement is represented by any event that increases the probability of an operant response. Animal models of positive reward and reinforcement are extensive and well-validated and include intravenous or intracranial drug self-administration, place conditioning, and states of reduced brain reward thresholds (27). Brain reward thresholds are measured by intracranial self-stimulation (ICSS) methodology, in which animals press a lever to obtain electrical stimulation of the medial forebrain bundle (28). Animal models of the withdrawal/negative affect stage include conditioned place aversion (vs. preference) to either spontaneous or precipitated withdrawal from chronic drug exposure, states of increased brain reward thresholds, and dependence-induced increases in drug-seeking behavior during withdrawal. Rodents increase intravenous or oral self-administration with extended access to the drugs and during withdrawal from the dependent state, measured both by an increased amount of drug administration and working exponentially harder to obtain the drug. Such increased self-administration in dependent animals has been observed with cocaine, methamphetamine, nicotine, heroin, and alcohol (29–34). Finally, the use of yoked-administration models allows for the investigation of neuroadaptations associated with reinforcement-related vs. noncontingent drug exposure. For example, Edwards et al. found that individual preferred levels of cocaine self-administration in rats positively correlated

36


with the phosphorylation state of cyclic adenosine monophosphate response element binding protein (CREB) in the central nucleus of the amygdala, although this relationship was not observed in rats receiving passive cocaine infusions at identical levels and patterns as their self-administering partners (35). Animal models of craving, representing the preoccupation/ anticipation stage of drug addiction, involve reinstatement of drug seeking behavior following extinction training and subsequent exposure to the drugs themselves, cues/contexts paired with drug self-administration, or stressors (36, 37). The latency to reinitiate responding, or the amount of responding on the previously extinguished lever, is hypothesized to reflect the motivation for drugseeking behavior. Stress-induced reinstatement most often involves the application of acute stressors that reinitiate drug seeking, such as footshock, although more natural stressors should be utilized (38). In rats with a history of dependence, protracted abstinence can be defined as a period after acute physical withdrawal has disappeared and is often accompanied by elevations in drug intake or drug-seeking behavior (e.g., 2–8 weeks post withdrawal from chronic drug self-administration). Protracted abstinence has also been linked to increased brain reward thresholds and increases in sensitivity to anxiety-like behavior that have been shown to persist after acute withdrawal symptoms have subsided in animals with a history of dependence. Stress-induced reinstatement of drug-seeking and stress-induced reinstatement of anxiety-like states during protracted abstinence represent models of the persistent preoccupation/anticipation (craving) stage of the addiction cycle. Most of the animal models discussed above have predictive validity for some components of the addiction cycle (compulsive use, withdrawal, or craving) and are highly reliable. Consistency and stability of the measures, small within-subject and betweensubject variability, and reproducibility of the phenomenon are characteristic of most of the measures employed in animal models of dependence, with the possible exception of conditioned place preference (39). For the positive reinforcing effects of drugs, drug self-administration, ICSS, and conditioned place preference have been shown to have predictive validity. Animal models of withdrawal can be focused on either motivational constructs of withdrawal or physical or somatic signs. Animal models of conditioned drug effects (e.g., reinstatement, place preference) are successful in predicting the potential for conditioned drug effects in humans. Predictive validity is more problematic for such concepts as craving largely because of the inadequate formulation of the concept of craving in humans (see below, and refs. 13, 40, 41). Clearly, much remains to be explored about the face validity and predictive validity of unconditioned positive and negative motivational states and particularly the conditioned positive and negative motivational states associated with drug use and withdrawal. However, the responsibility

2


37

for filling the gaps in knowledge may lie more in the human clinical laboratory setting than in the animal models domain. 4.2. Overview of Animal Models of Depression

Depression is a major health care problem and a significant economic burden to society. Animal models of depression with good predictive validity but limited construct validity include the forced swim test, tail suspension test, learned helplessness models, olfactory bulbectomy, and maternal deprivation (42). However, there has been a shift away from traditional animal models of depression to more focused “endophenotype-like” approaches. This section describes animal models that have face validity and in some cases a degree of reliability and construct validity for a key element underlying depression: reward deficits. Reward and motivational deficits represent critical underlying elements of a number of psychiatric disorders, ranging from drug addiction to major depression. Animal models of such deficits are well-established and include brain stimulation reward thresholds and preference for a sweet solution, among many others. The use of these two models is described here in the context of a depression model, and evidence for face and construct validity is described. Similar to drug dependence, major depressive disorder (or unipolar depression) is a chronic relapsing disorder that has a significant genetic component (43, 44) and a long-hypothesized contribution from stress-related mechanisms (45). Major depressive periods show a kindling-like effect, in which episodes worsen over time if left untreated. Suicide is a very possible outcome of affective disorders, with 60–70% of severely depressed individuals having suicidal ideations and 10–15% ultimately attempting suicide (46). The present section describes animal models that have face validity and, in certain cases, a degree of reliability and construct validity for measuring reward deficits associated with depression. For brevity, we only review the chronic mild stress model as an animal model of depression induction. Chronic and unpredictable mild stress produces a number of behavioral and physiological abnormalities that have face validity for the various symptoms of depression (47). These include decreased sexual and exploratory behavior, sleep abnormalities, immune and hypothalamic-pituitary-adrenal axis dysregulation, and hedonic deficits measured by sucrose consumption, place conditioning, and brain stimulation reward. In the chronic unpredictable stress model, rats are exposed to various moderate environmental perturbations consisting of several weeks of random stressors, such as food and water deprivation, circadian cycle disruption, cage tilt, soiled cage, temperature fluctuations, stroboscopic lighting, exposure to an empty bottle following water deprivation, and the presence of foreign objects in the cage (48, 49). However, it is essential to employ a regimen of stressors that limits the potential confound of stress-induced weight loss (50). The chronicity

38


and unpredictability of these challenges can produce depression-like motivational symptoms measured by the techniques described below. 4.2.1. Brain Stimulation Reward

As mentioned earlier in the chapter, brain stimulation reward (or intracranial self-stimulation) is a procedure in which animals perform an operant response to receive highly rewarding electrical stimulation to their medial forebrain bundle. Brain stimulation reward has many advantages over assaying the pursuit and consumption of natural rewards. It directly activates brain reward systems, bypassing much of the periphery of hedonic circuitry. Additionally, no confounding motivational deficit states (e.g., food or water deprivation) are required for the procedure. Responses are also controllable, with very small increments in reward value systematically changing behavior. Using brain stimulation reward, Jean-Luc Moreau and colleagues have consistently shown reliable hedonic deficits following chronic mild stress by measuring threshold changes in the ventral tegmental area that are reversed by chronic administration of a number of antidepressant treatments (47).

4.2.2. Sucrose Consumption

Sucrose is a highly rewarding sweet substance in rodents, and rats show a concentration-dependent increase in both consumption and preference for sucrose that forms an inverted U-shaped function (51). Reduced preference for a sucrose solution in rats has been hypothesized to reflect a decreased sensitivity to reward homologous with anhedonia (52). Sucrose consumption/preference is normally monitored by tracking, over repeated test sessions, the decrease in the consumption of or preference for a palatable, lowconcentration (1–2%) sucrose solution in the home cage. Chronic sequential exposure to mild unpredictable stress has been found to decrease the consumption of palatable sweet solutions, and in some cases preference for palatable sweet solutions (48, 49, 53, 54). Additionally, the chronic mild stress-induced decrease in palatable solution intake has been replicated with social stress (55), novelty stress (56), and forced swim stress (49). Perhaps more impressive have been numerous studies showing that the decrease in consumption or preference was reversible by chronic but not acute antidepressant treatment (48, 49, 53, 57–60). Clearly, there are significant differences among the sensitivity, reliability, and construct validity of these two measures of motivational deficits. Brain stimulation reward provides a reliable and sensitive measure of a reward deficit in drug withdrawal, consistent with reward deficiencies described in the human condition. It also has been validated via manipulation of both reward and performance variables (61). Neuropharmacological validation of brain stimulation reward has shown that agents that decrease thresholds increase reward in humans (e.g., drugs of abuse), and agents that increase thresholds generally produce dysphoric responses in

2


39

humans, lending some predictive, and thus construct validity to this measure. However, sucrose consumption or preference measures, although used extensively, may have much less reliability and validity. The majority of data in fact largely indicate that humans with major depressive episodes report a magnified “craving” for sweets, in contrast to rats exposed to chronic mild stress. However, sucrose consumption following chronic mild stress does have predictive validity for antidepressant treatment, which is presumably one rationale for its popularity. The use of sucrose consumption/preference has increased asymptotically in the literature. Another reason for the extensive use of sucrose consumption/ preference presumably corresponds to the ease of measurement compared with brain stimulation reward, which requires specialized operant equipment. 4.3. Overview of Current Models of Anxiety Disorders

Anxiety is a common emotion and represents an integrated response to the trials and tribulations of life. Anxiety is adaptive when mild, but may be incapacitating when present at extreme and intractable levels. Anxiety appears in several clinically recognizable forms. Patients who suffer from persistent, diffuse psychological feelings of dread, unremitting nervousness, tension, and worry accompanied by motor tension, vigilance, and autonomic hyperactivity in the absence of obvious external stressors are distinguished from patients who are relatively symptom-free until an acute precipitated anxiety or panic attack occurs. Panic attacks are accompanied by subjective feelings of terror, apprehension, and fear of dying. Somatic symptoms occur across multiple physiological systems and include dyspnea, sweating, faintness, and trembling. The signs and symptoms of panic disorder are similar to those occurring during a life-threatening situation or during intense physical exercise. Further diagnostic distinctions are made among patients with anxiety caused by posttraumatic stress disorder (PTSD), obsessive-compulsive disorder, and phobic disorders (23). Anxiety can also be a prominent component of other psychiatric disorders, including schizophrenia, affective illness, and substance abuse. Clinical anxiety research has rapidly evolved with the delineation of several subtypes of specific anxiety states. Unknown is whether these subtypes and their distinctive signs and symptoms reflect a unitary phenomenon or are independent syndromes with separate neurobiological substrates. Several animal models of general anxiety disorder have been developed, including the operant conflict test (62) and social interaction test (63). Unfortunately, there are few, if any, animal models sufficiently validated to discriminate among the various subtypes of anxiety disorders. A future challenge will be to develop animal models that reflect specific aspects of these clinical anxiety syndromes. What follows is a description of two examples of currently used animal models of anxiety-like states: the elevated plus maze and defensive burying task.

40


4.3.1. Elevated Plus Maze

This ethologically based exploratory model of anxiety measures how animals, typically rats and mice, respond to a novel approachavoidance situation by measuring the relative investigation of two distinct environments: a lit, exposed runway and a dark, walled runway intersected to form a plus sign. Both runways are elevated high off the floor. No motivational constraints are necessary, and the animal is free to remain in the darkened arm or venture onto the open and exposed arms. This type of approach-avoidance situation is a classic animal model of “emotionality” (64) and is very sensitive to treatments that produce disinhibition (such as sedative/hypnotic drugs) and stress (65). Moreover, the simplicity of the elevated plus maze provides a high degree of utility in measuring emotional reactivity to experimental treatments. Accordingly, the elevated plus maze has been the subject of several hundred studies of rodent emotionality since the description and validation of the modern testing protocol in 1984 and 1985 (66, 67). Experimental treatments, such as γ-aminobutyric acid (GABA) inverse agonists, which reduce open-arm exploration, are identified as anxiogeniclike in the elevated plus maze, whereas drugs, such as GABA agonists (which increase open-arm exploration), are anxiolytic-like (68). Other dedicated reviews (69, 70) offer critical examination of the validity of the elevated plus maze as a model of anxiety. A similar test, termed defensive withdrawal, consists of an illuminated open field with a small, enclosed, and darkened chamber situated near one corner of the field and shows comparable validity to the elevated plus maze (71).

4.3.2. Defensive Burying

Rodents have a natural defense reaction (sometimes termed “active coping”) to unfamiliar and potentially dangerous objects by spraying material over the object, leading to total coverage of the threatening object. The best-known procedure to measure this behavior employs a metal prod protruding into the animal’s cage from which, at first contact, a mild electric shock is delivered (72). The total time spent burying the prod with bedding material, the total number of burying acts, and the height of bedding material deposited over the prod serve as validated measures of emotionality in this test (73, 74). In an environment without bedding material, in which the active burying option is not possible, subjects adopt a passive strategy by exhibiting immobility in locations away from the probe (75). The anxiety disorder most effectively modeled in terms of face validity by the defensive burying task may be a specific phobia (formerly, simple phobia), the essential feature of which is a marked and persistent fear of clearly discernible, circumscribed objects or situations (23). The lack of extinction of burying behaviors with repeated exposure to the inducing stimuli has provided some comparison of this animal model of anxiety to obsessive-compulsive disorders, the symptomatology for which includes repetitive acts aimed at preventing or reducing distress (76).

2


41

Regarding face and construct validity, the majority of animal models of anxiety have been developed to identify anxiolytic drugs and to reject nonanxiolytic drugs. The two standard models reviewed here appear to have good predictive validity for drugs that are effective in the treatment of generalized anxiety disorder. Each of the models has its strengths and weaknesses that need to be recognized, and use of multiple models always provides a convergent validation of research findings. One major difference between animal models of anxiety and the clinical disorders is that most patients requiring drug treatment for anxiety are presenting with high trait anxiety, whereas all animal tests are based on conditions that presumably reflect transient changes in state anxiety. The tests described above measure adaptive responses to a test situation, not a pathological state. However, as long as these tests are predictive of various aspects of the pathological state, then they have some validity as animal models (17). Clearly, the use of specific genetic strains and molecular genetic manipulations allows for the exploration of state vs. trait similarities or differences. Finally, individual differences most likely play a very large role in terms of vulnerability versus resilience to anxiety-related disorders (77, 78) and therefore represents a much-needed dimension of animal modeling.

5. The Case for Preclinical Human Models

In many cases, the development of certain models is practically restricted to the human clinical laboratory domain for maximizing both internal and external validity, and a good case of this is the phenomenon of substance craving. Craving can be conceptualized as an intersection of exteroceptive or interoceptive cues with an individual’s motivational impetus to seek and take a substance. Human laboratory models are well-suited for studying craving mechanisms, given the immediacy of effects obtained under wellcontrolled conditions (79) as well as allowing for subjective reporting. This approach also represents a cost-effective and efficient way to facilitate the understanding of psychological mechanisms underlying human behavior and to identify and develop new treatment options (80). By comparison, animal models, particularly the extinctionreinstatement model, may be best suited to study the neuronal mechanisms involved in drug-seeking behavior (37). Although subjective reports of craving are impossible to obtain in animals, the reinstatement model has appreciable face validity for relapse behavior (15). Unfortunately, as others have pointed out (81), whether the model has predictive validity is currently unknown because few clinical or preclinical human trials have tested effective drugs or conditions employed in the model. Thus, collaborative relationships between basic neuroscience and preclinical human

42


modeling could be useful in facilitating medications development, as well as in developing new and better models. This conceptualization has been termed the “Rosetta Stone” approach and represents a bridge between predictive and construct validity toward the mutual benefit of both approaches (82). For example, numerous animal studies show that stress both increases previously extinguished drug-seeking behavior in response to alcohol-associated cues and potentiates the effects of other environmental cues previously associated with alcohol self-administration (32). Although comparative studies in humans appear inconsistent, they also allow for the separation of specific negative emotional stimuli into those that precipitate craving from those that do not. Marlatt and Gordon (83) suggest that negative experiences with which the subject has an intimate history (such as social pressures or lob loss) are more likely to be associated with relapse to drinking. Mason et al. (84) found that aversive but personally irrelevant cues (such as images of a threatening snake) were ineffective at inducing craving, whereas preferred beverage-related cues were very effective. As discussed above, such distinctions can be engineered back into preclinical models as refinements, in which more relevant and specific social stressors (e.g., maternal separation) can be incorporated into animal models of stress-induced reinstatement and neuroplasticity (38).

6. In Vitro Methods to Facilitate the Modeling and Treatment of Psychiatric Disorders

While lacking in some obvious aspects of validity versus wholeanimal models, in vitro models may best represent an adjunctive, well-controlled means to model specific neuroplastic mechanisms associated with psychiatric disorders. One example of this utility is represented by studies of the transcription factor ΔFosB by Eric Nestler and colleagues. ΔFosB accumulates in a brain regionspecific manner in response to several types of chronic neural stimulation, a phenomenon hypothesized to be attributable to the unusual stability of the protein. The persistence of ΔFosB engenders the transcription factor with long-lasting effects on gene expression well after the termination of the original stimulus (e.g., chronic stress or illicit drug exposure), particularly considering the broad amplifying effects of transcriptional regulation on physiological systems. Thus, the unique characteristics of ΔFosB have established this protein as a candidate “molecular switch” mediating the transition to drug dependence (85). After a series of studies examining the precise nature of ΔFosB’s stability in vitro (e.g., (86–88)), the group was able to engineer viral constructs that overexpressed phosphorylation site-specific mutant forms of ΔFosB in whole animals and demonstrated a disruption of the effects of chronic cocaine in rats given this intervention (89). These studies benefited from a

2


43

strategic combination of in vitro (including both implemental reagent development and investigatory aims) and in vivo methodologies. Another pioneering use of in vitro work in the field of drug abuse has been the continuing search for ethanol’s binding sites, which has produced a list of defined criteria for ethanol targets and several leading receptor candidates (90). Identification of this site would not only satisfy a long-standing pharmacological curiosity, but may also provide a direct therapeutic target for alcoholism. A related problem is how endogenous opioids and exogenous opiates/opioids differentially regulate desensitization, endocytosis, and subsequent resensitization of the μ-opioid receptor (a longestablished target). Jennifer Whistler and colleagues determined that the endogenous ligands at μ receptors mediate a normal recycling of receptors in vitro, presumably corresponding to a dynamic and adaptive signal for the organism’s benefit. In contrast, morphine stimulation of μ receptors leads to either a protracted desensitization of receptors or other intracellular changes that most likely contribute to the pronounced in vivo tolerance and dependence that occur with chronic morphine exposure (91). These results could have a dramatic impact on drug development strategies, which have mostly relied on adjusting ligand efficacy or the duration of action in an attempt to design better analgesic agents with reduced potential for dependence. As an alternative, Berger and Whistler (92) proposed that drug candidates (or even drug cocktails) can be screened for their ability to regulate endocytosis, similar to endogenous ligands. In terms of medications development, a more comprehensive elucidation of the mechanisms of action of current treatments for dependence should facilitate the discovery of therapeutic drugs with even greater efficacy. For example, the anticraving drug acamprosate is commonly hypothesized to function by dampening hyperglutamatergic states associated with alcohol dependence and withdrawal. However, given the vast array of neuronal targets for modulating excitatory neurotransmission (e.g., AMPA/NMDA receptor channels vs. metabotropic glutamate receptors vs. presynaptic vesicle release mechanisms), a better understanding of acamprosate targets is needed (93). Such investigations, aided by in vitro methodology, could also shed light on the neurobiological mechanisms underlying relapse to other drugs of abuse. A comprehensive understanding of drug tolerance and dependence (as well as therapeutic drug mechanisms) will most likely require the coalescence of multiple knowledge bases at various levels of analysis, from molecular to behavioral. Finally, the complexity and validity of cell culture studies can be enhanced by the use of primary culture systems (94). When maintained under tightly regulated culture conditions, neurons extend axons and dendrites and form physiologically and functionally active synaptic contacts (95). Cocultures composed of neurons from two distinct neuronal populations can further aid in the

44


characterization of simple circuits. Gao and Wolf (96) used cocultures containing rat ventral tegmental area (VTA, dopamine-synthesizing neurons) and excitatory prefrontal cortex (PFC) neurons to investigate mechanisms of dopamine–glutamate interactions within this isolated PFC–VTA circuit, a neuronal pathway hypothesized to drive synaptic transmission relevant to stress sensitization and drug-seeking behavior in vivo (97–99).

7. Conclusion The refinement of basic models of psychiatric illness will continue to be a challenging endeavor and will be greatly facilitated by both horizontal (across disease models) and vertical (in vitro, in vivo, and human model) integration. Specific techniques associated with preclinical models and the investigation of changes in the central nervous system that are associated with these models are subjects described in the chapters that follow. Altogether, these tools will undoubtedly continue to provide valuable insights into the etiology of psychopathologies associated with drug addiction and other psychiatric disorders.

Acknowledgments The authors would like to thank Michael Arends for editorial assistance. This is publication number 20895 from The Scripps Research Institute. Preparation of this chapter was funded by the Pearson Center for Alcoholism and Addiction Research and National Institutes of Health grants AA018250, AA06420, AA12602, and AA08459 from the National Institute on Alcohol Abuse and Alcoholism, DA04043, DA04398, and DA023597 from the National Institute on Drug Abuse, and DK26742 from the National Institute of Diabetes and Digestive and Kidney Diseases. References 1. Edwards, S., and Koob, G. F. (2010) Neurobiology of dysregulated motivational systems in drug addiction, Future Neurol 5, 393–401. 2. Covington, H. E., 3rd, Vialou, V., and Nestler, E. J. (2010) From synapse to nucleus: novel targets for treating depression, Neuropharmacology 58, 683–693. 3. McKinney, W. (1989) Basis of development of animal models in psychiatry: an overview. in Animal models of depression (Koob, G. F.,

Ehlers CL, Kupfer DJ, Ed.), pp 3–17, Birkhauser, Boston, Basel. 4. Adriani, W., Granstrem, O., Macri, S., Izykenova, G., Dambinova, S., and Laviola, G. (2004) Behavioral and neurochemical vulnerability during adolescence in mice: studies with nicotine, Neuropsychopharmacology 29, 869–878. 5. Brown, S. A., and Tapert, S. F. (2004) Adolescence and the trajectory of alcohol use: basic to clinical studies, Ann N Y Acad Sci 1021, 234–244.

2


6. O’Dell, L. E. (2009) A psychobiological framework of the substrates that mediate nicotine use during adolescence, Neuropharmacology 56 Suppl 1, 263–278. 7. Schramm-Sapyta, N. L., Walker, Q. D., Caster, J. M., Levin, E. D., and Kuhn, C. M. (2009) Are adolescents more vulnerable to drug addiction than adults? Evidence from animal models, Psychopharmacology (Berl) 206, 1–21. 8. Palanza, P. (2001) Animal models of anxiety and depression: how are females different?, Neurosci Biobehav Rev 25, 219–233. 9. Fattore, L., Altea, S., and Fratta, W. (2008) Sex differences in drug addiction: a review of animal and human studies, Womens Health (Lond Engl) 4, 51–65. 10. McClung, C. A. (2007) Circadian genes, rhythms and the biology of mood disorders, Pharmacol Ther 114, 222–232. 11. Falcon, E., and McClung, C. A. (2009) A role for the circadian genes in drug addiction, Neuropharmacology 56 Suppl 1, 91–96. 12. Ebel, R. (1961) Must all tests be valid?, American Psychologist 16, 640–647. 13. Sayette, M. A., Shiffman, S., Tiffany, S. T., Niaura, R. S., Martin, C. S., and Shadel, W. G. (2000) The measurement of drug craving, Addiction 95 Suppl 2, S189–210. 14. Cronbach, L. J., and Meehl, P. E. (1955) Construct validity in psychological tests, Psychol Bull 52, 281–302. 15. Katz, J. L., and Higgins, S. T. (2003) The validity of the reinstatement model of craving and relapse to drug use, Psychopharmacology (Berl) 168, 21–30. 16. McKinney, W. (1988) Models of Mental Disorders: A New Comparative Psychiatry, Plenum, New York. 17. MA Geyer, A. M. (1995) Animal models of psychiatric disorders, in Psychopharmacology: The Fourth Generation of Progress (FE Bloom, D. K., Ed.), pp 787–798 Raven Press, New York. 18. Willner, P. (1984) The validity of animal models of depression, Psychopharmacology (Berl) 83, 1–16. 19. Matthysse, S. (1986) Animal models in psychiatric research, Prog Brain Res 65, 259–270. 20. Ellenbroek, B. A., and Cools, A. R. (2000) Animal models for the negative symptoms of schizophrenia, Behav Pharmacol 11, 223–233. 21. Markou, A., and Koob, G. F. (1992) Construct validity of a self-stimulation threshold paradigm: effects of reward and performance manipulations, Physiol Behav 51, 111–119. 22. Gilpin, N. W., and Koob, G. F. (2008) Neurobiology of Alcohol Dependence: Focus

23. 24.

25. 26. 27.

28.

29.

30.

31.

32.

33.

34.

35.

45

on Motivational Mechanisms, Alcohol Res Health 31, 185–195. Association, A. P. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4 ed. Koob, G. F., and Le Moal, M. (2001) Drug addiction, dysregulation of reward, and allostasis, Neuropsychopharmacology 24, 97–129. Bindra (1976) A Theory of Intelligent Behavior, Wiley, New York. Koob, G. F. (2008) A role for brain stress systems in addiction, Neuron 59, 11–34. Shippenberg TS, G. K. (2002) Recent advances in animal models of drug addiction and alcoholism, in Neuropsychopharmacology: The Fifth Generation of Progress (KL Davis, D. C., JT Coyle, C Nemeroff, Ed.), pp 1381–1397, Lippincott Williams and Wilkins, Philadelphia. Carlezon, W. A., Jr., and Chartoff, E. H. (2007) Intracranial self-stimulation (ICSS) in rodents to study the neurobiology of motivation, Nat Protoc 2, 2987–2995. Ahmed, S. H., and Koob, G. F. (1998) Transition from moderate to excessive drug intake: change in hedonic set point, Science 282, 298–300. Ahmed, S. H., Walker, J. R., and Koob, G. F. (2000) Persistent increase in the motivation to take heroin in rats with a history of drug escalation, Neuropsychopharmacology 22, 413–421. Roberts, A. J., Heyser, C. J., Cole, M., Griffin, P., and Koob, G. F. (2000) Excessive ethanol drinking following a history of dependence: animal model of allostasis, Neuropsychopharmacology 22, 581–594. Breese, G. R., Chu, K., Dayas, C. V., Funk, D., Knapp, D. J., Koob, G. F., Le, D. A., O’Dell, L. E., Overstreet, D. H., Roberts, A. J., Sinha, R., Valdez, G. R., and Weiss, F. (2005) Stress enhancement of craving during sobriety: a risk for relapse, Alcohol Clin Exp Res 29, 185–195. Kitamura, O., Wee, S., Specio, S. E., Koob, G. F., and Pulvirenti, L. (2006) Escalation of methamphetamine self-administration in rats: a dose-effect function, Psychopharmacology (Berl) 186, 48–53. O’Dell, L. E., Chen, S. A., Smith, R. T., Specio, S. E., Balster, R. L., Paterson, N. E., Markou, A., Zorrilla, E. P., and Koob, G. F. (2007) Extended access to nicotine self-administration leads to dependence: Circadian measures, withdrawal measures, and extinction behavior in rats, J Pharmacol Exp Ther 320, 180–193. Edwards, S., Graham, D. L., Bachtell, R. K., and Self, D. W. (2007) Region-specific tolerance to cocaine-regulated cAMP-dependent protein phosphorylation following chronic

46

36.

37.

38.

39.

40.

41.

42.

43. 44.

45. 46.

47.

48.

S. Edwards and G.F. Koob self-administration, Eur J Neurosci 25, 2201–2213. Self, D. W. (1998) Neural substrates of drug craving and relapse in drug addiction, Ann Med 30, 379–389. Shaham, Y., Shalev, U., Lu, L., De Wit, H., and Stewart, J. (2003) The reinstatement model of drug relapse: history, methodology and major findings, Psychopharmacology (Berl) 168, 3–20. Miczek, K. A., Yap, J. J., and Covington, H. E., 3rd. (2008) Social stress, therapeutics and drug abuse: preclinical models of escalated and depressed intake, Pharmacol Ther 120, 102–128. Callahan, L. B., Tschetter, K. E., and Ronan, P. J. (2007) Difficulties associated with the cocaine conditioned place preference (CPP) test using rats, in Society for Neuroscience Abstracts, San Diego. Markou, A., Weiss, F., Gold, L. H., Caine, S. B., Schulteis, G., and Koob, G. F. (1993) Animal models of drug craving, Psychopharmacology (Berl) 112, 163–182. Tiffany, S. T., Carter, B. L., and Singleton, E. G. (2000) Challenges in the manipulation, assessment and interpretation of craving relevant variables, Addiction 95 Suppl 2, S177–187. JF Cryan, C. S., TG Dinan, F Borsini. (2008) Developing more efficacious antidepressant medication: improving and aligning preclinical and clinical assessment tools. in Animal and Translational Models for CNS Drug Discovery (RA McArthur, F Borsini, Ed.), Elsevier, Amsterdam. Levinson, D. F. (2006) The genetics of depression: a review, Biol Psychiatry 60, 84–92. Krishnan, V., and Nestler, E. J. (2008) The molecular neurobiology of depression, Nature 455, 894–902. Wurtman, R. J. (2005) Genes, stress, and depression, Metabolism 54, 16–19. Moller, H. J. (2003) Suicide, suicidality and suicide prevention in affective disorders, Acta Psychiatr Scand Suppl, 73–80. Moreau, J. L. (1997) Reliable monitoring of hedonic deficits in the chronic mild stress model of depression, Psychopharmacology (Berl) 134, 357–358; discussion 371–357. Willner, P., Towell, A., Sampson, D., Sophokleous, S., and Muscat, R. (1987) Reduction of sucrose preference by chronic unpredictable mild stress, and its restoration by a tricyclic antidepressant, Psychopharmacology (Berl) 93, 358–364.

49. Yu, J., Liu, Q., Wang, Y. Q., Wang, J., Li, X. Y., Cao, X. D., and Wu, G. C. (2007) Electroacupuncture combined with clomipramine enhances antidepressant effect in rodents, Neurosci Lett 421, 5–9. 50. Reid, I., Forbes, N., Stewart, C., and Matthews, K. (1997) Chronic mild stress and depressive disorder: a useful new model?, Psychopharmacology (Berl) 134, 365–367; discussion 371–367. 51. Muscat, R., Kyprianou, T., Osman, M., Phillips, G., and Willner, P. (1991) Sweetnessdependent facilitation of sucrose drinking by raclopride is unrelated to calorie content, Pharmacol Biochem Behav 40, 209–213. 52. Willner, P., Muscat, R., and Papp, M. (1992) Chronic mild stress-induced anhedonia: a realistic animal model of depression, Neurosci Biobehav Rev 16, 525–534. 53. Muscat, R., and Willner, P. (1992) Suppression of sucrose drinking by chronic mild unpredictable stress: a methodological analysis, Neurosci Biobehav Rev 16, 507–517. 54. Katz, R. J. (1982) Animal model of depression: pharmacological sensitivity of a hedonic deficit, Pharmacol Biochem Behav 16, 965–968. 55. Von Frijtag, J. C., Van den Bos, R., and Spruijt, B. M. (2002) Imipramine restores the longterm impairment of appetitive behavior in socially stressed rats, Psychopharmacology (Berl) 162, 232–238. 56. Duncko, R., Schwendt, M., and Jezova, D. (2003) Altered glutamate receptor and corticoliberin gene expression in brain regions related to hedonic behavior in rats, Pharmacol Biochem Behav 76, 9–16. 57. Cheeta, S., Broekkamp, C., and Willner, P. (1994) Stereospecific reversal of stress-induced anhedonia by mianserin and its (+)-enantiomer, Psychopharmacology (Berl) 116, 523–528. 58. Rygula, R., Abumaria, N., Domenici, E., Hiemke, C., and Fuchs, E. (2006) Effects of fluoxetine on behavioral deficits evoked by chronic social stress in rats, Behav Brain Res 174, 188–192. 59. Rygula, R., Abumaria, N., Flugge, G., Hiemke, C., Fuchs, E., Ruther, E., and HavemannReinecke, U. (2006) Citalopram counteracts depressive-like symptoms evoked by chronic social stress in rats, Behav Pharmacol 17, 19–29. 60. Casarotto, P. C., and Andreatini, R. (2007) Repeated paroxetine treatment reverses anhedonia induced in rats by chronic mild stress or dexamethasone, Eur Neuropsychopharmacol 17, 735–742.

2


61. Markou, A., and Koob, G. F. (1991) Postcocaine anhedonia. An animal model of cocaine withdrawal, Neuropsychopharmacology 4, 17–26. 62. I Geller, J. S. (1960) The effect of meprobamate, barbiturates, d-amphetamine and promazine on experimentally-induced conflict in the rat, Psychopharmacologia 1, 482–491. 63. File, S. E., and Hyde, J. R. (1978) Can social interaction be used to measure anxiety?, Br J Pharmacol 62, 19–24. 64. Archer, J. (1973) Tests for emotionality in rats and mice: a review, Anim Behav 21, 205–235. 65. Dawson, G. R., and Tricklebank, M. D. (1995) Use of the elevated plus maze in the search for novel anxiolytic agents, Trends Pharmacol Sci 16, 33–36. 66. Handley, S. L., and Mithani, S. (1984) Effects of alpha-adrenoceptor agonists and antagonists in a maze-exploration model of ‘fear’-motivated behaviour, Naunyn Schmiedebergs Arch Pharmacol 327, 1–5. 67. Pellow, S., Chopin, P., File, S. E., and Briley, M. (1985) Validation of open:closed arm entries in an elevated plus-maze as a measure of anxiety in the rat, J Neurosci Methods 14, 149–167. 68. Pellow, S., and File, S. E. (1986) Anxiolytic and anxiogenic drug effects on exploratory activity in an elevated plus-maze: a novel test of anxiety in the rat, Pharmacol Biochem Behav 24, 525–529. 69. Handley, S. L., and McBlane, J. W. (1993) An assessment of the elevated X-maze for studying anxiety and anxiety-modulating drugs, J Pharmacol Toxicol Methods 29, 129–138. 70. M Reibaud, A. B. (1993) Evolution of putative anxiolytics in the elevated plus-maze, in Paradigms for the Study of Behavior (Conn, M., Ed.), pp 230–239, Academic Press, San Diego. 71. Gorman, A. L., and Dunn, A. J. (1993) Betaadrenergic receptors are involved in stressrelated behavioral changes, Pharmacol Biochem Behav 45, 1–7. 72. JS Andrews, C. B. (1993) Procedures to identify anxiolytic or anxiogenic agents, in Behavioral Neuroscience: A Practical Approach (Sahgal, A., Ed.), pp 37–54, IRL Press, Oxford. 73. Korte, S. M., Korte-Bouws, G. A., Bohus, B., and Koob, G. F. (1994) Effect of corticotropin-releasing factor antagonist on behavioral and neuroendocrine responses during exposure to defensive burying paradigm in rats, Physiol Behav 56, 115–120. 74. Bowers, R. L., Herzog, C. D., Stone, E. H., and Dionne, T. J. (1992) Defensive burying

75.

76.

77.

78.

79.

80.

81.

82.

83. 84.

85.

86.

87.

47

following injections of cholecystokinin, bombesin, and LiCl in rats, Physiol Behav 51, 969–972. Korte, S. M., and Bohus, B. (1990) The effect of ipsapirone on behavioural and cardiac responses in the shock-probe/defensive burying test in male rats, Eur J Pharmacol 181, 307–310. CL Broekkamp, F. J. (1989) The relationship between various animal models of anxiety, fearrelated psychiatric symptoms and response to serotonergic drugs, in Behavioral Pharmacology of 5-HT (P Bevan, R. C., T Archer, Ed.), pp 321–325, Erlbaum, Hillsdale. Feder, A., Nestler, E. J., and Charney, D. S. (2009) Psychobiology and molecular genetics of resilience, Nat Rev Neurosci 10, 446–457. Harro, J. (2010) Inter-individual differences in neurobiology as vulnerability factors for affective disorders: implications for psychopharmacology, Pharmacol Ther 125, 402–422. Litt, M. D., and Cooney, N. L. (1999) Inducing craving for alcohol in the laboratory, Alcohol Res Health 23, 174–178. Mason, B. J., Light, J. M., Williams, L. D., and Drobes, D. J. (2009) Proof-of-concept human laboratory study for protracted abstinence in alcohol dependence: effects of gabapentin, Addict Biol 14, 73–83. Epstein, D. H., and Preston, K. L. (2003) The reinstatement model and relapse prevention: a clinical perspective, Psychopharmacology (Berl) 168, 31–41. Koob, G. F., Kenneth Lloyd, G., and Mason, B. J. (2009) Development of pharmacotherapies for drug addiction: a Rosetta stone approach, Nat Rev Drug Discov 8, 500–515. GA Marlatt, J. G. (1985) Relapse Prevention, Guilford Press, New York. Mason, B. J., Light, J. M., Escher, T., and Drobes, D. J. (2008) Effect of positive and negative affective stimuli and beverage cues on measures of craving in non treatment-seeking alcoholics, Psychopharmacology (Berl) 200, 141–150. Nestler, E. J., Barrot, M., and Self, D. W. (2001) DeltaFosB: a sustained molecular switch for addiction, Proc Natl Acad Sci USA 98, 11042–11046. Ulery, P. G., Rudenko, G., and Nestler, E. J. (2006) Regulation of DeltaFosB stability by phosphorylation, J Neurosci 26, 5131–5142. Carle, T. L., Ohnishi, Y. N., Ohnishi, Y. H., Alibhai, I. N., Wilkinson, M. B., Kumar, A., and Nestler, E. J. (2007) Proteasomedependent and -independent mechanisms for FosB destabilization: identification of FosB

48

88.

89.

90.

91.

92.

93.

94.

S. Edwards and G.F. Koob degron domains and implications for DeltaFosB stability, Eur J Neurosci 25, 3009–3019. Alibhai, I. N., Green, T. A., Potashkin, J. A., and Nestler, E. J. (2007) Regulation of fosB and DeltafosB mRNA expression: in vivo and in vitro studies, Brain Res 1143, 22–33. Ulery-Reynolds, P. G., Castillo, M. A., Vialou, V., Russo, S. J., and Nestler, E. J. (2009) Phosphorylation of DeltaFosB mediates its stability in vivo, Neuroscience 158, 369–372. Harris, R. A., Trudell, J. R., and Mihic, S. J. (2008) Ethanol’s molecular targets, Sci Signal 1, re7. Martini, L., and Whistler, J. L. (2007) The role of mu opioid receptor desensitization and endocytosis in morphine tolerance and dependence, Curr Opin Neurobiol 17, 556–564. Berger, A. C., and Whistler, J. L. (2010) How to design an opioid drug that causes reduced tolerance and dependence, Ann Neurol 67, 559–569. Littleton, J. (2007) Acamprosate in Alcohol Dependence: Implications of a Unique Mechanism of Action, Journal of Addiction Medicine 1, 115–125. Hollenbeck, P. J., and Bamburg, J. R. (2003) Comparing the properties of neuronal culture

95.

96.

97.

98.

99.

systems: a shopping guide for the cell biologist, Methods Cell Biol 71, 1–16. Matteoli, M., Verderio, C., Krawzeski, K., Mundigl, O., Coco, S., Fumagalli, G., and De Camilli, P. (1995) Mechanisms of synaptogenesis in hippocampal neurons in primary culture, J Physiol Paris 89, 51–55. Gao, C., and Wolf, M. E. (2007) Dopamine alters AMPA receptor synaptic expression and subunit composition in dopamine neurons of the ventral tegmental area cultured with prefrontal cortex neurons, J Neurosci 27, 14275–14285. Fitzgerald, L. W., Ortiz, J., Hamedani, A. G., and Nestler, E. J. (1996) Drugs of abuse and stress increase the expression of GluR1 and NMDAR1 glutamate receptor subunits in the rat ventral tegmental area: common adaptations among cross-sensitizing agents, J Neurosci 16, 274–282. Wolf, M. E. (1998) The role of excitatory amino acids in behavioral sensitization to psychomotor stimulants, Prog Neurobiol 54, 679–720. Saal, D., Dong, Y., Bonci, A., and Malenka, R. C. (2003) Drugs of abuse and stress trigger a common synaptic adaptation in dopamine neurons, Neuron 37, 577–582.

Chapter 3 Qualitative Versus Quantitative Methods in Psychiatric Research Mahdi Razafsha, Hura Behforuzi, Hassan Azari, Zhiqun Zhang, Kevin K. Wang, Firas H. Kobeissy, and Mark S. Gold Abstract Qualitative studies are gaining their credibility after a period of being misinterpreted as “not being quantitative.” Qualitative method is a broad umbrella term for research methodologies that describe and explain individuals’ experiences, behaviors, interactions, and social contexts. In-depth interview, focus groups, and participant observation are among the qualitative methods of inquiry commonly used in psychiatry. Researchers measure the frequency of occurring events using quantitative methods; however, qualitative methods provide a broader understanding and a more thorough reasoning behind the event. Hence, it is considered to be of special importance in psychiatry. Besides hypothesis generation in earlier phases of the research, qualitative methods can be employed in questionnaire design, diagnostic criteria establishment, feasibility studies, as well as studies of attitude and beliefs. Animal models are another area that qualitative methods can be employed, especially when naturalistic observation of animal behavior is important. However, since qualitative results can be researcher’s own view, they need to be statistically confirmed, quantitative methods. The tendency to combine both qualitative and quantitative methods as complementary methods has emerged over recent years. By applying both methods of research, scientists can take advantage of interpretative characteristics of qualitative methods as well as experimental dimensions of quantitative methods. Key words: Qualitative, Quantitative, Methodology, Animal models, Naturalistic, In-depth interview

1. Introduction Behind every quantity there must lie a quality. (Gertude Jaeger Selznick)

This section introduces different dimensions of qualitative and quantitative research methods for psychiatric researchers; it particularly shows the usefulness of qualitative research methods,


49

50

M. Razafsha et al.

theoretical underpinnings of this type of research, and various approaches toward particular research methods. Hopefully, this section also places qualitative approaches within the broader research design, in combination with quantitative method, to show that qualitative and quantitative methods are complementary instead of competitive. 1.1. Qualitative and Quantitative Research: A Brief Overview

Although psychiatry is directly related to behavior and behavior is naturally more subjective rather than objective, this branch of science has gained its unique objectivity through quantitative methods. Qualitative methods were considered not to have enough validity and reliability to be a part of psychiatric research (1). Quantity, measurement, and objectivity became reliable parts of most research projects and attempts to find any association became a unique goal of researchers. “P-value” improved the main determinant of “association” and making quantitative association regardless of “causality” became an unwritten rule for most articles to become eligible for publication in most prestigious journals (2). This “p-value movement” helped science in general and psychiatry in particular to find solutions for many problems. However, these results ended in a huge pile of information and association relationships—most of them are useless (3, 4). At this stage, metaanalysis came to accumulate information from different experimental and correlational studies. Meta-analysis assembles databases across independent studies that address a related set of research (5). Although meta-analysis has been very successful in joining information from different studies, there are still enormous amounts of information and correlations that remain useless. Every year, billions of dollars and many human resources are spent to discover new areas in science and medicine. However, the amount of useful practical data that came from this investment is not as satisfying as expected. Drug discovery and development is one of the substantial areas of concern. A major program of the National Cancer Institute (NCI) involving the “screening” of plants randomly collected worldwide ended in late 1981. This program, which was started in 1960, tested 35,000 plant species for antitumor activity in laboratory animals. Although a large number of highly active antitumor agents were produced by NCI program, none have been approved for use against human cancer by the FDA. One can argue that this blind screening approach of any available plants for testing is entirely unscientific and too costly to be continued. Perhaps, this was the reason for the NCI to cancel its program. Surely, a program that fails to produce a useful drug after 25 years of testing more than 35,000 plant species must be examined to determine the weaknesses and faults (6). This apparent failure might, however, be attributed more to the nature of the initial screening approach rather than a deficiency of nature.

3

Qualitative Versus Quantitative Methods in Psychiatric Research

51

At the same time, another program at Eli Lilly Company discovered two useful antitumor drugs which are widely used today. This program identified about 440 species of plants for inclusion in a broad biological screening program. Their approach to identify promising plants was to survey standard traditional books to find accounts of plants that were used by indigenous practitioners for treatment of diseases. From early 1958 onward, Dr. Gordon Svoboda and his two high-school graduate assistants started to work on extracts, which resulted in the isolation of a novel and highly active antitumor agent, Alkaloid V. This was the 40th plant that he selected for inclusion in the program. In 1961, FDA approved the alkaloid for general sale and use in cancer patients. Currently, Vincristin and Vinblastin are two alkaloid products used in the treatment of childhood leukemia, Hodgkin’s disease, and other malignancies. Less than 6 years was required for FDA approval and marketing of these drugs (7). In an attempt to find new biologically active extracts in higher plants, two approaches are applied. The first approach is to simply look for new chemical constituents and start to plan for many randomized controlled trials (RCTs) in an effort to find a useful extract. This approach adopted by the first study was not successful despite spending enormous amounts of time, energy, and money. In the second approach, the researchers conducted a preliminary qualitative research based on ethnopharmacological data interviewing traditional practitioners and then they started to run quantitative studies. 1.2. Qualitative Research

Qualitative research can be defined in general terms as “a form of systematic empirical inquiry into meaning” (8) or a “broad umbrella term for research methodologies that describe and explain persons’ experiences, behaviors, interactions, and social contexts” (9). However, Denzin and Lincoln (2000) described qualitative research as “an interpretive, naturalistic approach that study things in their natural settings, attempting to make sense of, or to interpret, phenomena in terms of the meanings people bring to them” (10). Other writers believe that human behavior is significantly influenced by the setting; thus, research must be conducted in the setting, where all the contextual variables are acting. That is why Patton believes that qualitative research uses a naturalistic approach and tries to understand phenomena in a “real world setting [where] the researcher does not attempt to manipulate the phenomenon of interest” (11). Many researchers describe qualitative methods by not being quantitative as Hoepfl illustrates: “Unlike quantitative researchers who seek causal determination, prediction, and generalization of findings, qualitative researchers seek instead illumination, understanding, and extrapolation to similar situations” (12, 13). Other researchers define qualitative methods as simply not being quantitative (14). Strauss and Corbin (1990)

52

M. Razafsha et al.

describe qualitative research as “any kind of research that produces findings not arrived at by means of statistical procedures or other means of quantification” (9). However, this form of definition can be misleading because, as discussed later, many qualitative methods are based upon statistic and quantity measures as well. For instance, qualitative researches on documentary or audio/video analysis based upon word counting use statistical comparison between documents and/or interviewees. In addition, many observational studies need calculation, measurement, and statistical comparison. It is worthy to mention that what has been referred to as qualitative data is completely different from qualitative methods. Any data which is not measurable is considered qualitative data, but this is not interchangeably applicable to qualitative studies. Qualitative methods have their own characteristics and tools that employ measurement and statistics in different stages to show the results and make comparison between different findings. “Grounded theory” which is almost equivalently used for qualitative methodology was first introduced by Glaser and Strauss (1967) (15). It indicates generation of theory from data in the process of conducting research. Rather than beginning by developing a hypothesis, the first step is data collection and then generating a concept from the collected data (16). Grounded theory refers to “the generation of emergent conceptualizations into integrated patterns, which are denoted by categories and their properties” (17).

2. Essential Features of Qualitative Research Versus Quantitative Methods

Qualitative methods are mostly employed at earlier phases of research projects to seek an important question that asks “why” some patients exhibit specific behaviors or symptoms. When quantitative research tries to understand the “frequency” of an event by questions like “how often” and “how many,” qualitative methods seek to explore the “reasoning” behind the event. Qualitative methods also seek to investigate “how” a behavior happens (18). By understanding these important questions through different methods like in-depth interview, researchers would be able to come up with new ideas and new hypotheses about the research paradigm they are going to conduct. Consequently, in qualitative methods, the design emerges as the study unfolds in contrast to quantitative methods, where the researcher has a thorough and vivid view toward different aspects of the research before data are collected. That is, in qualitative research, a hypothesis is not needed to begin research; however, all quantitative research requires a hypothesis before research can proceed. It is, therefore, essential for many research projects, especially those with more complicated

3


53

influencing factors, to begin with qualitative methods to explore different dimensions of the study. This is especially true in cases when relevant variables are not initially apparent. “Rather than taking a reductionist view of the subject in order for events to be measured, the holistic nature of the qualitative approach allows preservation of complexities, so that their nature can be explored and better understood” (18). Another major difference between qualitative and quantitative research is the underlying assumptions about the role of the researcher. In quantitative research, the researcher is ideally an objective observer separated from the subject; he/she neither participates in nor influences what is being studied. In qualitative research, however, it is thought that the researcher actively participates in the process that may influence the results (19). These basic underlying assumptions of both methodologies affect the types of data collection methods employed. If we consider hypothesis-generating functions for qualitative inquiries, quantitative methods can be used to verify which of such hypotheses are true. Because “qualitative data” might be skewed by interviewers’ subjective inclination, quantitative methods— preferably “double blinds”—should be considered to evaluate the results regardless of the interviewer and interviewee’s beliefs. While qualitative studies aim to access the phenomena of interest using the subject’s perspective, quantitative studies provide accurate measurement in order to generalize beyond the particular context in which the research has been conducted (18). Although generalizability can be offered for some qualitative studies, however, this is not a prototypical characteristic. Researchers take advantage of in-depth examination of a small number of people by qualitative interview but need to reduce generalizability expectations. This is because of the fact that it is not usually possible to interview many participants in a qualitative form (14). On the other hand, the aim of a quantitative method is to classify features, gauge them, and construct statistical models to be able to explain what has been observed initially through qualitative inquiries. They have to be devised in a stepwise fashion that can be easily replicable by other researches in order to gain reliable results. A good quantitative study generalizes beyond the particular context under which the study has been conducted and need to measure the phenomena of interest accurately. Validity, representativeness, and reliability are particular characteristics that a quantitative study needs to appropriately achieve (18). If we consider quantitative and qualitative methods as two different modes of inquiry, we can define two different approaches. Although some researchers consider qualitative and quantitative approaches as incompatible and competitive, others believe that researchers can successfully combine two approaches (20). The fundamental differences in qualitative and quantitative approaches

54

M. Razafsha et al.

Table 1 Qualitative versus quantitative approaches Qualitative approaches

Quantitative approaches

Realities are multiple, constructed, and holistic

Reality is single, tangible, and fragmentable

How do my informants define these concepts?

How can I operationally define these concepts?

End with hypotheses

Start with hypotheses

Emergence and portrayal

Manipulation and control

Researcher as instrument

Use formal instruments

Naturalistic

Experimentation

Inductive

Deductive

Interpretative

Predictive

Search for patterns

Component analysis

Seek pluralism, complexity

Seek consensus, the norm

Make minor use of numerical indices

Reduce data to numerical indices

Contextualization

Generalizability

are illustrated in Table 1 (19, 21, 22). The combination of qualitative and quantitative methods provides a more comprehensive and unbiased situation allowing the research project to be more accurate and trustful (23).

3. Tools for Qualitative Data Inquiry in Psychiatry

In-depth interview, focus group, and participant observation are among those qualitative methods of inquiry commonly used in psychiatry (24). They may be employed separately or in combination with each other. Data collection in focus groups or in-depth interviews can be conducted through tape recording and transcription of conversation. One of the advantages of employing tape recording and transcription is to provide an opportunity for further analysis by an independent observer. Multiple analyses by different observers as well as meticulous recording of interviews and documenting the process of analysis help to improve retest reliability (25). In-depth interviews and focus groups both involve “the elucidation of subjective meaning, experience, beliefs, and attitudes, either through one-on-one interviews or small, facilitator-led, group discussion” (24). While an interview elicits individual’s

3


55

Table 2 Tools for qualitative data inquiry Qualitative tools Observation Unstructured Structured Participant In-depth interview Unstructured Structured Semistructured Focus group Questionnaires Concept mapping Focused life history narrative Audio, video, or document content analysis Documentary analysis Case study

experience, ideas, and feeling, focus groups identify group norms and variety within populations. A focus group has a number of advantages: (1) it encourages participants to develop and explore their own analysis of their experience; (2) it helps to identify cultural norms; (3) it encourages open conversation about embarrassing subjects and facilitates the expression of underdeveloped ideas and experiences (26). There are many tools for qualitative data inquiry described in Table 2. 3.1. Qualitative Research Implications

As discussed earlier, qualitative methods can be employed in the early stages of many studies (27), especially when influencing factors are complicated. Many great works in the field of psychiatry have been based upon qualitative methods. Drug discovery and development following initial qualitative ethnopharmacologic studies manifest better outcome, as compared earlier in cases of the NCI project and Dr. Gordon Svoboda method. Instead of a blind approach to examine every accessible plant or chemical essence, we can obtain valuable information from traditional literature in the field of interest (28). Before the modern era in medicine, traditional practitioners in every region tried to treat diseases based on regional plants growing in that area. Although many critics believe that most of the success physicians achieved can be attributable to the accompanying psychological contribution of therapist, their

56

M. Razafsha et al.

achievements were obviously more than that. That is why the World Health Organization (WHO) is trying to promote ethnomedicine to implement regional conventions in therapeutic methods (29). Today, many ethnopharmacologic articles are being published in this field hoping to develop new treatments based on ethnographic data (30). These ethnographic data can be achieved not only by inquiry in traditional texts, but also through observation or interviewing traditional practitioners still working in the region (28). Another application of qualitative research methods in psychiatry is designing questionnaires. Questionnaires are valuable tools that seek to gather data from a potentially large number of respondents. They are inexpensive, easy to use, and can elicit respondents’ perception, thought, feeling, and judgment. It is important to remember that questionnaire design should be viewed as a multistage process beginning with important questions (e.g.: “What kind of factors can affect the subject I am going to study?”) (31). The best approach is conducting a primary qualitative study to understand what kind of variables can influence the subject (31, 32). For example, if a researcher seeks to devise a questionnaire to measure “happiness” of people, he or she can start by asking people to complete the sentence that “I feel happy when …” By gathering the answers, the researcher can find a general view toward potential factors influencing the “happiness.” Along the same line, establishing diagnostic criteria for different psychiatric diseases needs preliminary qualitative studies. A scientist should understand various contributing factors in case of symptomatology, laboratory data, etc. to be able to design a comprehensive list that encompasses both inclusive and exclusive criteria. In questionnaire and criteria design, preliminary qualitative methods should be followed by quantitative studies to compare new results with previously acceptable diagnostic tools to ensure that they are reliable and valid (33). Studies of attitudes and beliefs are important studies in psychiatry and public health that can be sought by qualitative methods. There is still a deep level of stigma and discrimination against individuals with mental illness within the system (34) which obviously interferes with everyday life and recovery of the patients. Considering the fact that many psychiatric problems are not curable and patients may experience fluctuating courses of illness may add to the stigmatizing problem of these patients. In fact, the conventional mental health policy that focuses only on symptom relief failed to address this important debilitating aspect of patients’ life. Thus, mental health policy is shifting away from simply focusing on treatment of symptoms to more recovery-oriented policy, which considers patients as an inseparable part of the community and environment. Qualitative tools due to their natural holistic view can be successfully employed in this field. Perhaps, the largest qualitative study

3


57

conducted to explore different dimensions of recovery-oriented policy is sponsored by the American Government. The national project, entitled “What Helps and What Hinders Recovery Project,” was initiated in 1999 by a small group of experts discussing the need for the development of recovery-oriented performance indicators. Discussions led to awareness that mental health recovery is an intensely personal process influenced by many factors, including the operations of formal mental health services. To understand this process, empirical data were needed. These data could only be attained by asking people in recovery about the impact of their experiences of being recipients of services provided by recovery systems. The focus group method was employed during this phase of the project. Ten focus groups were asked several questions that organized the brainstorming of ideas. The groups provided more than 1,000 pages of transcribed qualitative data. These data were then carefully analyzed and revealed a set of important themes (35). Qualitative methods have been well-used to improve our understanding of patients suffering from dementia. Studies on the notion of selfhood based upon qualitative methods have led to the development of new theories in this field. Further qualitative work about the relationship of people with dementia and caregivers and the role of health system policies has highlighted new systems for benefiting people with dementia and their caregivers (36). Quality of life studies on the phenomenology of dementia are increasingly supporting the fundamental change in our conventional understanding of the disease and shifting to new systems which see treatment regimens in an everyday context. The right of children to contribute directly to the research process as subjects rather than merely objects is not a new topic in child and adolescent psychiatry (37). However, more recently, there has been an encouraging move toward research with children rather than on children. This means engaging them as active participants, recognizing their rights, respecting their autonomy, and giving them voices. This requires a new definition of the relationship between researchers and child/adolescent participants. Qualitative research, with its focus on shared construction of meaning with participants, and flexibility in design, method, and process can be used here allowing subjects to communicate their experiences without having them transformed by the researcher so as to alter their meaning in any significant manner (37, 38). Research projects dealing with socially sensitive issues can be well-managed by qualitative methods. In a study conducted in two deprived areas of the UK, researchers tried to understand why government policy to increase cigarette smoking prices failed to achieve its goal to decrease smoking. They also wanted to know how the people dealt with increased prices knowing that they were from poor communities. A cross-sectional study using qualitative

58

M. Razafsha et al.

semistructured interview was conducted in 100 male and female smokers selected from general practitioners’ lists from two health centers. Strategies to maintain smoking consumption among smokers included purchasing cheaper brands of cigarettes, switching to home-rolled cigarettes, cross-border shopping, and buying contraband products. In just a small minority of cases, respondents tried to reduce their cigarette consumption to reduce costs. Many smokers criticized the government for its policy and mentioned that purchasing contraband tobacco was viewed as rational in the face of material hardship (39). Feasibility studies based on qualitative methods can be undertaken when there is uncertainty about the motivation of patients and expertise of clinicians for the recruitment phase of clinical trials (40). Snowden et al. (1997) retrospectively interviewed parents who had agreed to enroll their critically ill newborn babies in an RCT. They learned that the nature of the trial, random basis of the allocation of treatment, and rationale behind this approach were not appropriately understood by patients (41). They concluded that this can be a major threat to many clinical trials. In fact, an entire project can be undermined because of the inability to recruit sufficient participants while the lack of recruitment can be related to a basic misunderstanding about the concept of randomization. This justifies preliminary investment in a brief qualitative study in many clinical trials that have problems recruiting. This is particularly pertinent in psychiatric research fields, where disease stigmatization is a real concern and can affect the capacity to give informed consent (40, 41).

4. Qualitative Methods in Animal Models

Qualitative methods have been widely employed in animal models of psychiatry. Similar to other fields, qualitative methods have been very successful in theory generation from animal model experiments. Simple observation was the first qualitative tool used by Pavlov to observe dog’s saliva reaction to conditioned (CS) and unconditioned stimulus (UCS) (42). This simple observation led to the important theory of classical conditioning which is the fundamental basis for behavior therapy. “Helplessness theory” was among those basic theories of depression that was incidentally “observed” by Martin Seligman (43, 44). He discovered the theory when studying the effects of inescapable shock on active avoidance learning in dogs. Seligman put dogs in a Pavlovian harness, where escape was impossible, and then administered several shocks paired with a conditioned stimulus based on classical conditioning studies of Pavlov. In the next stage, these dogs were placed in a shuttle box, where they could avoid shock by jumping over a barrier. Interestingly, most of the dogs failed to attempt to avoid shock. Seligman proposed that prior exposure to an inescapable situation

3


59

interfered with the ability to learn in a new situation, where escape was possible (43). For establishing any animal model, the first step would be finding similarities between animal symptoms and human manifestations. This important preliminary phase is not possible without applying qualitative methods. As Seligman argued later, there are similarities between the learned helplessness model of depression in animals and human characteristics of depression (44). For example, he suggested “lack of response initiation” in animal as an equal manifestation of “feeling without energy” in humans. Ethology—the study of animal behavior and expanding it into human behavior without external manipulations—is regaining its credibility in modern psychiatry parallel to naturalistic movements in other branches of science. The idea of qualitative description of what has been naturally observed and identifying behavioral units seems to have many capacities in theory generation in psychiatry. There are growing studies showing that dogs can be natural models of anxiety disorders. They appear to exhibit behavioral responses in their clinical presentation similar to separation anxiety, noise phobia, OCD, PTSD, and panic attack (45). A dog diagnosed with separation anxiety exhibits behavioral signs of distress when denied access to its group. Because domestic dogs usually consider humans part of their social group, they feel attached to family members. When separated from family members, dogs may experience distress and exhibit behavioral problems, including destruction, vocalization, elimination of urine and/or stool, anorexia, drooling, attempts at escape, and behavioral depression (46). Due to the similarity in symptoms between dogs and humans, these species have been an appropriate source of naturalistic studies. Clomipramine (Tricyclic antidepressants) is a drug successfully used for anxiety treatment in both dogs and humans (46, 47). Natural rates of licking and grooming of rat pups by mothers have been used by scientists to evaluate maternal care. Caldji et al. showed that qualitative differences in maternal behavior in early life can develop differences in behavioral responses to stress in rat pups in the future. He showed that offspring of low-grooming mothers can show more stressful symptoms than high-grooming mothers. In addition, differences in maternal care characteristics are transmitted from mother to daughter (48). The “social interaction test” is one of the first tests in animal models that uses Ethological evaluation methods. Various behavior measures (e.g., sniffing, following, or grooming the partner) are recorded by this test to evaluate anxiety when a mouse meets a stranger. It, therefore, avoids the use of food, water deprivation, electric shock. This test avoids manipulative interventions such as water deprivation or electric shock, that can change animal behavior and interfere with the result. Due to its naturalistic basis, “social interaction test” considers a pair of rats as a unit and only issues one score for the pair (49, 50).

60

M. Razafsha et al.

Qualitative methods have been employed to study sex differences of “play fighting” behavior in rats. Play fighting in rats involves attack of the nape of the neck and defense tactics. Defensive tactics can be either moving the nape away from the attacker by jumping, running, swerving away, or applying some maneuvers that lead to the defender facing the attacker (facing defense). The increased roughness in postpubertal play fighting by males may be considered a male-typical trait; however, play fighting studies in animals propose new evidences in sexual differentiation in females. Traditional models for sexual differentiation viewed the female as the default condition, and in this model ovarian hormones are not needed to fully feminize females. However, new evidences based upon play fighting studies suggest that some female characteristics may not simply be attributable to the default conditions, but rather ovarian hormones may play a role to fully feminize them (51). Many of the behavioral measures used to assess different aspects of animal models have been under laboratory manipulations to control the situation. “Emotionality” is an example of such an area of concern in animal models that uses qualitative methods in addition to quantitative studies. The animal is simply placed in an unfamiliar situation (novel environment tests) and then many characteristics, like defecation, urination, ambulation, and rearing, as representatives of emotionality evaluated (52). Qualitative methods are being used in validity tools. “Face validity” is a form of qualitative intuitive judgment by outside observers to see if the given instrument is really assessing what is supposed to be measured. “Content validity” is another validity tool that helps to evaluate whether all dimensions of a given construct are measured or not. It bears resemblance to face validity in that they both have elements of subjectivity. Both measures use qualitative methods to evaluate the validity of animal models. In conclusion, an animal model may represent a disease phenotype on three different levels: first, it may mimic disease manifestation phenomenologically; second, it may reproduce inducing factor(s) like a genetic defect to evaluate the subsequent pathological processes; and finally, it may predict responsiveness to already available treatments (48). Qualitative methods in cooperation with quantitative analysis can be employed in experimental animal models to reach these animal model goals. References 1. Greenhalgh, T., and Taylor, R. (1997) How to read a paper: Papers that go beyond numbers (qualitative research), BMJ 315, 740–743. 2. McKibbon, K. A., and Gadd, C. S. (2004) A quantitative analysis of qualitative studies in clinical journals for the 2000 publishing year, BMC Med Inform Decis Mak 4, 11.

3. Ioannidis, J. P. (2005) Why most published research findings are false, PLoS Med 2, e124. 4. Sterne, J. A., and Davey Smith, G. (2001) Sifting the evidence-what’s wrong with significance tests?, BMJ 322, 226–231. 5. Delahaye, F., Landrivon, G., Ecochard, R., and Colin, C. (1991) Meta-analysis, Health Policy 19, 185–196.

3


6. Cragg, G., Boyd, M., Cardellina II, J., Grever, M., Schepartz, S., Snader, K., and Suffness, M. (1993) The search for new pharmaceutical crops: Drug discovery and development at the National Cancer Institute, in New crops (Janick, J., and Simon, J., Eds.), p 7, Wiley, New York. 7. Farnsworth, N. R. (1988) Screening plants for new medicines, in Biodiversity (Wilson, E. O., Ed.), National Academy Press, Washington, D.C. 8. Shank, G. (2002) Qualitative Research. A Personal Skills Approach, Merill Prentice Hall, New Jersey. 9. Strauss, A., and Corbin, J. (1990) Basics of qualitative research: Grounded theory procedures and techniques, Sage Publications, Inc., Newbury Park, CA. 10. Denzin, N. K., and Lincoln, Y. S. (2000) Handbook of qualitative research, 2nd ed., Sage Publications, Thousand Oaks, Calif. 11. Patton, M. Q., (Ed.) (2002) Qualitative evaluation and research methods, 3rd ed., Sage Publications, Inc, Thousand Oaks, CA. 12. Hoepfl, M. C. (1997) Choosing Qualitative Research: A Primer for Technology Education Researchers, Journal of Technology Education 9. 13. Golafshani, N. (2003) Understanding Reliability and Validity in Qualitative Research, The Qualitative Report 8, 10. 14. Fossey, E., Harvey, C., McDermott, F., and Davidson, L. (2002) Understanding and evaluating qualitative research, Aust N Z J Psychiatry 36, 717–732. 15. Glaser, B. G., and Strauss, A. L. (1967) Discovery of grounded theory: Strategies for qualitative research, Aldine de Gruyter, Hawthorne, NY. 16. Glaser, B. G. (2000) The discovery of grounded theory, Sociology Press Mill Valley, CA. 17. Glaser, B. G. (2002) Conceptualization: On Theory and Theorizing Using Grounded Theory, International Journal of Qualitative Methods 1. 18. Buston, K., Parry-Jones, W., Livingston, M., Bogan, A., and Wood, S. (1998) Qualitative research, Br J Psychiatry 172, 197–199. 19. Glesne, C., and Peshkin, A. (1992) Becoming qualitative researchers: an introduction, Longman, White Plains, N.Y. 20. Patton, M. Q. (1999) Enhancing the quality and credibility of qualitative analysis, Health Serv Res 34, 1189–1208. 21. Lincoln, Y. S., and Guba, E. G. (1985) Naturalistic inquiry, Sage Publications, Beverly Hills, Calif. 22. Spradley, J. P. (1979) The ethnographic interview, Holt, Rinehart and Winston, New York.

61

23. Creswell, J. W., and Tashakkori, A. (2007) Editorial: Developing Publishable Mixed Methods Manuscripts, Journal of Mixed Methods Research 1, 107–111. 24. Whitley, R., and Crawford, M. (2005) Qualitative research in psychiatry, Can J Psychiatry 50, 108–114. 25. Mays, N., and Pope, C. (1995) Qualitative Research: Rigour and qualitative research, BMJ 311, 109–112. 26. Kitzinger, J. (1995) Qualitative Research: Introducing focus groups, BMJ 311, 299–302. 27. Brown, C., and Lloyd, K. (2001) Qualitative methods in psychiatric research, Adv Psychiatr Treat 7, 350–356. 28. Raza, M. (2006) A role for physicians in ethnopharmacology and drug discovery, J Ethnopharmacol 104, 297–301. 29. Akerele, O. (1984) WHO’s traditional medicine programme: progress and perspectives, WHO Chron 38, 76–81. 30. Heinrich, M., Edwards, S., Moerman, D. E., and Leonti, M. (2009) Ethnopharmacological field studies: a critical assessment of their conceptual basis and methods, J Ethnopharmacol 124, 1–17. 31. Nelson, D. D. (1985) Informal testing as a means of questionnaire development Journal of Official Statistics 1, 179–188. 32. Presser, S., Couper, M. P., Lessler, J. T., Martin, E., Martin, J., Rothgeb, J. M., and Singer, E. (2004) Methods for Testing and Evaluating Survey Questions, Public Opin Q 68, 109–130. 33. Skodol, A. E., and Spitzer, R. L. (1982) The Development of Reliable Diagnostic Criteria in Psychiatry, Annual Review of Medicine 33, 317–326. 34. Reidy, D. (1994) The Mental Health System as Agent of Stigma, Resources 6, 8. 35. Davidson, L., Ridgway, P., Kidd, S., Topor, A., and Borg, M. (2008) Using qualitative research to inform mental health policy, Can J Psychiatry 53, 137–144. 36. Gibson, G., Timlin, A., Curran, S., and Wattis, J. (2004) The scope for qualitative methods in research and clinical trials in dementia, Age Ageing 33, 422–426. 37. Grover, S. (2004) Why Won’t They Listen to Us?: On Giving Power and Voice to Children Participating in Social Research, Childhood 11, 81–93. 38. Bassett, R. (2010) Time to catch up… Qualitative research in child and adolescent psychiatry, J Can Acad Child Adolesc Psychiatry 19, 2.

62

M. Razafsha et al.

39. Wiltshire, S., Bancroft, A., Amos, A., and Parry, O. (2001) “They’re doing people a service”qualitative study of smoking, smuggling, and social deprivation, BMJ 323, 203–207. 40. Rutter, D. (2006) Qualitative methods in psychiatry in Research Methods in Psychiatry (Freeman, C., and Peter, T., Eds.) 3 ed., RC PSYCH Publication. 41. Snowdon, C., Garcia, J., and Elbourne, D. (1997) Making sense of randomization; responses of parents of critically ill babies to random allocation of treatment in a clinical trial, Soc Sci Med 45, 1337–1355. 42. Pavlov, I. P. (1927) Conditioned Reflexes, Dover, New York. 43. Maier, S. F., and Seligman, M. E. P. (1976) Learned Helplessness: Theory and Evidence, Journal of Experimental Psychology: General 105, 3–46. 44. Overmier, J. B., and Seligman, M. E. (1967) Effects of inescapable shock upon subsequent escape and avoidance responding, J Comp Physiol Psychol 63, 28–33. 45. Shekhar, A., McCann, U. D., Meaney, M. J., Blanchard, D. C., Davis, M., Frey, K. A., Liberzon, I., Overall, K. L., Shear, M. K., Tecott, L. H., and Winsky, L. (2001) Summary of a National Institute of Mental Health workshop: developing animal models of anxiety disorders, Psychopharmacology (Berl) 157, 327–339.

46. Horwitz, D. F. (2000) Diagnosis and treatment of canine separation anxiety and the use of clomipramine hydrochloride (clomicalm), J Am Anim Hosp Assoc 36, 107–109. 47. King, J. N., Simpson, B. S., Overall, K. L., Appleby, D., Pageat, P., Ross, C., Chaurand, J. P., Heath, S., Beata, C., Weiss, A. B., Muller, G., Paris, T., Bataille, B. G., Parker, J., Petit, S., and Wren, J. (2000) Treatment of separation anxiety in dogs with clomipramine: results from a prospective, randomized, double-blind, placebo-controlled, parallel-group, multicenter clinical trial, Appl Anim Behav Sci 67, 255–275. 48. Caldji, C., Diorio, J., and Meaney, M. J. (2000) Variations in maternal care in infancy regulate the development of stress reactivity, Biol Psychiatry 48, 1164–1174. 49. File, S. E., and Seth, P. (2003) A review of 25 years of the social interaction test, Eur J Pharmacol 463, 35–53. 50. Flint, J., and Shifman, S. (2008) Animal models of psychiatric disease, Curr Opin Genet Dev 18, 235–240. 51. Pellis, S. M. (2002) Sex differences in play fighting revisited: traditional and nontraditional mechanisms of sexual differentiation in rats, Arch Sex Behav 31, 17–26. 52. Archer, J. (1973) Tests for emotionality in rats and mice: a review, Anim Behav 21, 205–235.

Part II Methods in Animal Models of Psychiatric Illness

sdfsdf

Chapter 4 Animal Models of Self-Injurious Behaviour: An Overview Darragh P. Devine Abstract Self-injurious behaviour is highly prevalent in neurodevelopmental disorders. Interestingly, it is not restricted to any individual diagnostic group. Rather, it is exhibited in various forms across patient groups with distinct genetic defects and classifications of disorders. This suggests that there may be shared neuropathology that confers vulnerability. Convergent evidence from clinical pharmacotherapy, brain imaging studies, postmortem neurochemical analyses, and animal models indicates that dopaminergic insufficiency is a key culprit. This chapter provides an overview of studies in which animal models have been used to investigate the biochemical basis of self-injury, and highlights the convergence in findings between these models and expression of self-injury in humans. Key words: Self-injurious behaviour, Lesch-Nyhan syndrome, Prader-Willi syndrome, Dopamine, Striatum, Animal model,

1. Introduction 1.1. Clinical Relevance

Self-injurious behaviour (SIB) is a devastating characteristic that is commonly expressed in a variety of genetic disorders, including Lesch-Nyhan (1, 2), Prader-Willi (3, 4), and Cornelia de Lange (5) syndromes. SIB is also prevalent in autistic (6, 7) and intellectually handicapped individuals of diverse etiological backgrounds (8–10). The forms of SIB differ somewhat between these diagnostic groups, and in most groups, there is heterogeneity in terms of incidence and severity of expression even within the affected population. Virtually all patients with Lesch-Nyhan syndrome exhibit severe self-biting behaviours (11), whereas 80–90% of Prader-Willi patients pick their skin (4, 12), and approximately 50% of children with autism bang their heads and punch or slap themselves (13). The reasons for these individual differences are not well characterized. However, the homogeneity of occurrence of SIB across neurodevelopmental disorders, and the heterogeneity of expression within


65

66

D.P. Devine

specific disorders suggest that shared biochemical mechanisms may confer vulnerability for SIB that is then shaped by environmental circumstances across and within these patient groups. SIB is often reported among patients who exhibit impaired communication skills (9, 10, 14–19) or who live in impoverished institutional environments (10, 20–26). There also appears to be a high prevalence of SIB in syndromes that are associated with chronic limbic dysfunction and pathological irritability (27). This includes patients with Lesch-Nyhan syndrome (11), and other disorders (28, 29), wherein exhibition of specific episodes of SIB are often related to the presence of environmental challenges and disturbances. In addition, there is evidence that SIB is more highly prevalent in subjects that have a greater degree of intellectual handicap, among samples of nonsyndromic patients (30). A substantial body of clinical research has been targeted at this behavioural pathology. Most of this research focuses on intervention for reinforcing social interactions that maintain SIB. This approach has yielded treatment programs that are partially effective for many self-injurers (16, 17, 24, 25, 31–36), and behaviour therapy is clearly the treatment of choice. However, functional analyses reveal that social interactions do not reinforce SIB in at least 30% of cases (37, 38). Furthermore, many self-injurious patients are highly resistant to behavioural interventions (11, 36, 39), and some groups (especially Lesch-Nyhan syndrome) are especially unresponsive (11, 40). Accordingly, it is extremely important to understand the neurobiological basis of SIB in these populations. 1.2. Biological Basis of Clinical SIB

The most frequent and severe expressions of SIB are commonly seen in Lesch-Nyhan syndrome (1), an X-linked recessive disorder that results from a point mutation in a gene that encodes the purine salvage enzyme hypoxanthine-guanine phosphoribosyl transferase (HPRT). Afflicted boys express a biologically inert HPRT molecule (41), resulting in diminished dopaminergic innervation of the striatum, severe dystonia, and SIB (42, 43). Diminished dopamine content or function has also been reported in patients with autism (44) and Rett syndrome (45), where SIB is a common feature. Furthermore, research on Lesch-Nyhan syndrome has revealed that striatal D1 and D2 receptors are upregulated in postmortem immunohistochemical analyses (46). Accordingly, disregulation of dopamine neurotransmission is strongly implicated in this disorder, but the mechanisms by which gross alterations in dopamine neurotransmission may lead to SIB are not understood. Moreover, it is important to note that dopamine systems are probably not the only neurotransmitter systems that are disregulated in LeschNyhan syndrome and other neurodevelopmental disorders. Evaluations in Lesch-Nyhan, autistic, and intellectually handicapped self-injurers have also revealed abnormal markers of adenosine (41, 47–49), opioid (46, 50–55), and serotonergic (42, 56)

4

Self-Injurious Behaviour Overview

67

functions, and there is recent evidence that disregulation of the limbic hypothalamic pituitary adrenal (LHPA) axis may be an important characteristic of self-injurers (50, 57, 58). However, the biochemical bases of all these abnormalities and mechanisms by which they may contribute to vulnerability for SIB are not clear, so additional investigations are mandated. 1.3. Pharmacological Trials for Clinical SIB

A great variety of pharmacological agents have been evaluated for the treatment of SIB in clinical trials. Unfortunately, these trials have yielded largely equivocal results. For example, it has been reported that opioid receptor antagonists (e.g., naloxone, naltrexone) reduce SIB in some studies (59–67), but not in others (68, 69). Similar contradictions have been reported in terms of neuroleptic (60, 70–74) and serotonergic (75–82) interventions for SIB. In light of the lack of consistent therapeutic effects of these interventions, it is difficult to draw conclusions about the neurobiological basis of SIB from these clinical trials. One interpretation of these data is that there may be subgroups of self-injurers in which differing (or at least partially differing) neuropathologies contribute to the expression of SIB. However, the difficulty in interpreting these clinical data is compounded by the fact that some studies have been conducted with imprecise dependent measures (62, 63, 72, 83, 84), open label trials are common (62, 72, 76, 83–85), many trials include subjects who receive multiple drugs concurrently (83, 84), many drugs exert multiple pharmacological actions (83–85), and long-term follow up studies are generally not done (some exceptions are refs. 59, 70, 73). The most parsimonious explanation remains that common neuropathology confers vulnerability across the multiple populations of self-injurers, and the expression of SIB may be influenced by additional social and biological factors.

2. Animal Models in SIB It is noteworthy that SIB is frequently observed in captive populations of animals. Spontaneous SIB is common in caged monkeys (86, 87), farm animals (88), household pets (89–91), and in a strain of inbred rabbits (92). Although less common, SIB has also been reported in the wild. For example, Jane Goodall described the case of a Gombe chimpanzee that exhibited severe self-injury following the death of its mother (93). Thus, it appears that SIB can be a naturally occurring behaviour that is expressed in the context of stress or deprivation in many diverse animal species. It follows then that the manipulations that invoke SIB in laboratory models likely impact the self-same endogenous neurobiological mechanisms that underlie the expression of SIB in these more naturalistic contexts.

68

D.P. Devine

Table 1 Animal models of SIB Category

Example

Lesion models

Neonatal 6-OHDA lesions

Environmental manipulations

Early environmental deprivation

Pharmacological manipulations

Chronic pemoline

Genetic

HPRT enzyme knockouts

A variety of laboratory models have been formulated in which developmental and neurochemical manipulations result in expression of SIB. These models can be classified into four types of experimental manipulations (see Table 1). The most well-characterized of these models are the 6-hydroxydopamine (6-OHDA) lesion model, early environmental deprivation, administration of caffeine, pemoline or Bay K 8644, and an HPRT knockout mouse. 2.1. The 6-OHDA Lesion Model

This model is a model wherein dopaminergic innervation of the striatum is destroyed in neonatal rats. Then, administration of dopamine agonists (e.g., L-dopa, apomorphine) in adulthood results in immediate and profound expression of SIB. Since the model is dependent upon early developmental destruction of dopaminergic neurons (i.e., lesions do not produce SIB if inflicted in adulthood), it has relevance for the developmental pathophysiology of LeschNyhan syndrome (94, 95). However, it should be noted that there is no clear relationship between any developmental milestone and the onset of SIB in Lesch-Nyhan syndrome or any other neurodevelopmental disorder, and in fact, the age of onset is quite variable in these disorders. It should also be noted that the 6-OHDA model is only effective if the dopaminergic neurons are almost completely destroyed in the neonatal animals, and this level of destruction does not match postmortem findings in any neurodevelopmental disorder. Nevertheless, the neonatal 6-OHDA model has been characterized more extensively than any other animal model of SIB, and it has yielded very interesting behavioural observations and neurochemical data. Data from the 6-OHDA model have revealed interesting lesion-induced changes in striatal chemoarchitecture. Adult rats that were lesioned as neonates exhibit increases in striatal serotonin (5-HT), met-enkephalin, and substance P (SP) content (96, 97), as well as a reduction in (3H]naloxone-binding to m-opioid receptors (98). These rats also exhibit unchanged or increased binding of [3H]spiroperidol or [3H]raclopride to the D2 class of dopamine receptors in the striatum (98–100), and unchanged or decreased binding of [3H]SCH23390 to the D1 receptor class (96, 98–100).

4


69

The reports of increases in D2 binding concur with postmortem immunohistochemical data from Lesch-Nyhan brains, but the decrease in D1 binding conflicts with the data from Lesch-Nyhan striata (46). The meaning of this discrepancy is not clear. In this model, the decreases in binding to the D1 class, and increases in binding to the D2 class might lead one to expect that the dopamine agonist-induced SIB results from enhanced actions on the D2 rather than the D1 types of receptors. Surprisingly, this appears not to be the case. Iontophoretic application of the D1 agonist SKF 38393 causes a greater inhibitory responsiveness of spontaneously firing striatal units in rats after neonatal 6-OHDA than it does in control rats, whereas responses to the D2 agonist PPHT are unchanged (100). So, it appears that the density of D1 and D2 receptors are uncoupled from the sensitivity of neuronal responses to administration of dopamine and selective receptor agonists after 6-OHDA lesions. The mechanisms of these effects are unknown, but the importance of D1 receptors in SIB after 6-OHDA appears clear. Administration of SKF 38393 induces SIB in rats after neonatal 6-OHDA lesions (97, 101–104). Furthermore, the SIB-producing effects of L-dopa and SKF 38393 are reliably blocked by administration of D1 antagonists (SCH 23390, SCH 39166, NO-0756, A-69024) (97, 101–104), but not by administration of a D2 antagonist (metoclopramide) (104) (although risperidone, a mixed D2/5-HT2 antagonist attenuated L-dopa-induced SIB (105)). Administration of a D2 agonist (LY 171555) produces hyperlocomotion and stereotypy, but no SIB in lesioned rats (97, 101, 102). In summary, although 6-OHDA lesions do not increase expression of, or binding to the D1 class of receptors, it appears that increased sensitivity of signaling through D1 receptors is important in the induction of SIB in neonatally lesioned rats. This interpretation is further supported by a recent report that striatal phospho-p38MAPK (Thr180/Tyr182) and phospho-CREB (Ser133) are increased in the neonatal 6-OHDA model. One of the most striking effects of neonatal 6-OHDA lesions is a hyper-innervation of striatal serotonergic (5-HT) neurons (94, 106–109) in adulthood. This hyperinnervation is accompanied by increased 5-HT1B and 5-HT2 receptor binding and supersensitivity to 5-HT receptor agonists (106). Accordingly, one might predict a serotonergic involvement in SIB in neonatally lesioned rats. However, there are conflicting reports on the effects of administration of 5-HT agonists in these animals. In one study, administration of 5-HT did not induce SIB (94), although another study reported that systemic administration of a 5-HT2c receptor agonist did produce self-injury (110). Accordingly, the role of lesioninduced 5-HT disregulation is unclear, but it appears that actions on 5-HT2c receptors may play a role in SIB in this model. Stress may also play an important role in the expression of SIB in these animals, a finding that is redolent of data from human

70

D.P. Devine

clinical reports (11, 27–29). Footshock stress potentiates the ability of apomorphine to induce SIB in neonatally lesioned rats (111). Since emotional stress increases dopamine neurotransmission (112), there appears to be convergence in the actions of apomorphine (a direct dopamine receptor agonist) and stress in the induction of SIB in this animal model. Accordingly, this finding provides further support for the potential involvement of dopamine neurotransmission in exhibition of SIB. 2.2. The Early Environmental Deprivation Model

This model originated in observations that nonhuman primates exhibit a variety of abnormal behaviours, including spontaneous SIB if they are reared in impoverished environments (86, 113, 114). This model has particular relevance to the high incidence of SIB that is often seen in institutionalized populations (10, 20–26). In fact, it has long been unclear if institutional environments specifically promote the etiology of SIB, or if the prevalence of SIB in these populations derives from the fact that intellectually handicapped self-injurers tend to be placed into these institutions more often than noninjurers do. However, in the 1990s, a large number of ostensibly normal children were released from highly impoverished Romanian orphanages, and one report describes that 24% of these children exhibited SIB when adopted into normal family homes (26). This finding lends strong support to the idea that impoverished institutional environments specifically promote the etiology and expression of SIB. In the early environmental deprivation model, there are interesting connections to dopaminergic function. Maternally deprived rhesus macaques had lower concentrations of the metabolite 3,4-dihydroxyphenylacetic acid (DOPAC) in cerebrospinal fluid (CSF) samples than did maternally reared animals (115). Furthermore, isolation-reared rhesus monkeys exhibit increases in the occurrence and intensity of stereotyped behaviours after apomorphine administration at doses that do not produce stereotypy in group-housed controls (116). This suggests that early environmental deprivation produces permanent alterations in dopamine receptor sensitivity, and this interpretation is further supported by neurochemical analyses of striatal function in isolated monkeys. Rhesus monkeys that experienced early environmental deprivation exhibit a pronounced loss of striatal patch/matrix organization and chemoarchitecture in adulthood (19–24 years later) (117). In the early environmental deprivation model, there is also an important connection with stress responsiveness. Isolation-reared nonhuman primates frequently express SIB in the context of emotional stress (114, 118, 119), and this is redolent of human selfinjurers (11, 27–29). These self-injurious monkeys also exhibit altered functioning of the LHPA axis, including blunted cortisol response to acute stress exposure (120, 121). As in the neonatal 6-OHDA model, a connection may be drawn between the abnormal

4


71

stress responsiveness and dopaminergic function because emotional stress is known to activate dopamine neurotransmission (112). Interestingly, the stress-induced increases in extracellular dopamine concentrations were exaggerated in striata of isolation-reared rats, when compared with concentrations in group-housed rats (122). However, it should be noted that one study reported no differences in CSF monoamine metabolite concentrations when comparing samples taken from monkeys with and without a history of SIB (120). 2.3. The Chronic Caffeine Model

This is a model in which rats are exposed to extremely high doses of caffeine for 10–12 days, until they exhibit SIB. Caffeine has been administered by the oral route (usually in the rats’ food or drinking water) (123–127), or by daily subcutaneous injections (128–130). The connection between caffeine and altered dopaminergic function is mediated by the antagonist actions of this methylxanthine on adenosine receptors (131). This can result in modulatory presynaptic actions on dopamine neurotransmission (132), as well as changes in postsynaptic responses to dopamine (133, 134). Caffeine administration has also been shown to exaggerate L-DOPA-induced SIB in neonatal 6-OHDA lesioned rats (135), whereas intrastriatal administration of a variety of adenosine agonists (NECA, CPA, and 2-CLA) is protective (103). Furthermore, chronic caffeine-induced SIB was exaggerated by handling stress. Treated rats exhibited SIB whenever they were picked up by the tail (124). In summary, caffeine-induced SIB may involve actions on dopamine neurotransmission or closely related systems, and as we saw in other animal models of SIB, there is evidence of an involvement of stress responses in caffeine-induced SIB. However, we evaluated the caffeine model of SIB and found that only a small percentage of the rats actually exhibited SIB, and the SIB was minor, even when we used high doses that are toxic in all the rats (i.e., weight loss, chromodacryorrhea, thymus involution, and death) (130). The low levels of caffeine-induced selfinjury in our study do not concur with some previous reports (123–129, 135), but the toxic actions of these high doses of caffeine have been noted in other studies (123–125, 128). Because the incidence of SIB was restricted to a very small percentage of the rats in our study, and especially because of the severe toxic actions of caffeine at the doses that were required to produce this minor SIB, we have concluded that this model is not suitable for ongoing studies on the neurobiological basis of SIB (130).

2.4. The Pemoline Model

This is a model in which high doses of this psychostimulant are administered to rats. Pemoline is a long-lasting (136) indirect monoamine agonist that blocks reuptake of dopamine, 5-HT, and norepinephrine (137). SIB can be produced within 48 h by acute administration of a single 300 mg/kg dose (138–143), or gradually

72

D.P. Devine

after 4–12 daily treatments with doses of 80–200 mg/kg/day (130, 144, 145). In this model, the rats appear healthy throughout the treatment regimen, and assays of aspartate and alanine aminotransferase activity indicate that there is no organotoxicity (146). Furthermore, cortical damage enhances pemoline-induced SIB (141), loosely linking this animal model of SIB with the vulnerability to self-injure in intellectually handicapped human populations. Administration of dopamine antagonists (haloperidol or pimozide) eliminate pemoline-induced SIB (142), providing evidence that the pemoline-induced behavioural syndrome is mediated (at least in part) through dopaminergic mechanisms. Furthermore, we recently identified that repeated treatment with pemoline causes approximately 30% depletion of striatal dopamine content (147). This resembles the degree of dopamine loss that is seen in Lesch-Nyhan syndrome (42, 43), and raises the possibility that alterations in postsynaptic signaling underlie the induction of SIB during repeated pemoline treatment. This contention is further supported by evidence that cortically evoked striatal depolarizing postsynaptic potentials (DPSPs) are decreased by bath application of dopamine in slices from vehicle-treated rats and in slices from rats that were treated with pemoline, but did not acquire self-injury, whereas these DPSPs are increased by dopamine application in slices from pemoline-treated rats that self-injured (138). Serotonergic neurotransmission is also implicated in this monoaminergic model of SIB. Co-administration of the selective 5-HT reuptake inhibitor paroxetine exaggerates pemoline-induced SIB (145). Thus, excess serotonergic function (as is seen in LeschNyhan syndrome (42, 56), and following neonatal lesions in the 6-OHDA model (94, 106–109)) may play an important role in the etiology and expression of SIB. To our knowledge, the role of adrenergic neurotransmission has not been examined in the pemoline model of SIB. One interesting finding is that pemoline-induced SIB is blocked by administering the N-methyl-D-aspartate (NMDA) receptor antagonist MK-801 (139, 148). In fact, pemoline-induced SIB was blocked if and only if the MK-801 was administered prior to administration of pemoline (i.e., not if MK-801 was administered 8 h after pemoline administration—even though this time point precedes the actual expression of SIB by the rats). Transient actions of glutamate on NMDA receptors are an important initial step in classical glutamate-mediated synaptic plasticity, as these actions initiate cascades of intracellular signaling that invoke enduring changes in neuronal function (for review see ref. (149)). Thus, it seems that this acute phase of glutamate-mediated neuroplasticity was blocked in the rats that were pre-treated with MK-801, but not in the rats that were treated 8 h after the pemoline injection. Overall, the SIB-suppressing actions of MK-801 implicate glutamate neurotransmission, and the time dependence of these actions suggests

4


73

a role for glutamate-induced neuroplasticity in the pathophysiology of pemoline-induced SIB. This interpretation is further supported by our recent demonstration that the lower-affinity NMDA receptor antagonist memantine (which does not disrupt classical glutamatemediated neuroplasticity (150, 151)) failed to block pemolineinduced SIB (148). Another important feature of the model is that individual outbred rats differ in vulnerability for pemoline-induced SIB. If a moderately high dose of pemoline (100–150 mg/kg/day) is administered, approximately 50% of the rats develop patterns of SIB (130). We examined this phenomenon and identified that these individual differences in vulnerability for pemoline-induced SIB arise from innate individual differences in stress responsiveness. Rats were prescreened for behavioural responsiveness to the mild stress of a novel environment. Those that exhibited high rates of locomotor activation developed SIB when subsequently treated with pemoline, whereas the rats that exhibited lower rates of behavioural activation did not self-injure (152). It appears that these individual differences in stress responsiveness arise from a combination of genetic and environmental determinants (153), and individual differences in regional expression of glucocorticoid receptors (GR) and corticotropin releasing hormone (CRH) appear to make important contributions to the phenotype (154). Thus, these observations have important heuristic value for ongoing analyses of the biochemical basis of vulnerability for SIB. We also found that this innate vulnerability for pemolineinduced SIB can be modified by environmental manipulations. Since stress exposure appears to exacerbate SIB in clinical samples (11, 28), we examined the impact of repeated social defeat stress on pemoline-induced SIB. In this experiment, rats that had a history of 12 daily stress exposures exhibited earlier onset, greater incidence, and more severe expression of self-injury than handled controls did (155, 156). Vulnerability for pemoline-induced SIB was also exacerbated by early environmental deprivation. In this experiment, rats were housed in enriched environments (complex cages with toys, shelters, and social pairs) or impoverished environments (isolation in austere stainless steel cages) for 65 days postweaning. The rats in the impoverished environments exhibited greater tissue injury than did the enriched rats when treated with pemoline during the final 5 days of the experiment (156, 157). Overall, these findings concur with data from human self-injurers, and they provide additional tools with which to manipulate and study individual differences in vulnerability for SIB. 2.5. The Bay K 8644 Model

Bay K 8644 is a dihydropyridine L-type Ca2+ channel agonist that induces dystonia and SIB in mice (158–160), especially if administered during early post-weaning development (160). Importantly, the Bay K 8644-induced SIB was blocked specifically by administration

74

D.P. Devine

of the dihydropyridine L-type Ca2+ channel antagonists nifedipine, nimodipine, and nitrendipine, but not by the nondihydropyridine antagonists diltiazem, flunarizine, or verapamil (160). The SIB was augmented by administration of the indirect dopamine agonists amphetamine and GBR 12909 (158), the monoamine oxidase inhibitor clorgyline (159), and the serotonin uptake inhibitor fluoxetine (159). Bay K 8644-induced SIB was attenuated when vesicular stores of dopamine were depleted by administration of reserpine or tetrabenazine (158), or when serotonin was depleted by administration of p-chlorophenylalanine or 5,7-dihydroxytryptamine (159), suggesting involvement of dopaminergic and serotonergic systems. Bay K 8644-induced SIB was also attenuated by co-administration of SCH-23390, SKF-38566 (D1/ D5 dopamine receptor antagonists), U-99194, or GR-103691 (D3 antagonists) (161). On the other hand, L-741,626 and L-745,870 (D2 and D4 antagonists, respectively) were ineffective. The effects of Bay K 8644 were also attenuated in D3 receptor knockout mice, but they were exaggerated in D1 knockouts (161). The contrary effects in D1 knockout mice were attributed to delays in physical maturation of these mice. Thus, taken all together, the data suggest that dopaminergic and serotonergic neurotransmission play important roles in the induction of SIB by Bay K 8644 in mice, and its behavioural effects appear to be mediated through D1, D3, and/or D5 receptor signaling actions. 2.6. HPRT Knockout Mice

HPRT knockout mice have been developed as an animal model of the biological impairment found in Lesch-Nyhan syndrome. These mice exhibit complete enzymatic inactivity of the HPRT molecule (162, 163) and greatly elevated purine biosynthesis (164, 165)—closely resembling neuropathological features of Lesch-Nyhan syndrome. They also have significant reductions in striatal dopamine content (166–168), but it should be noted that the dopamine deficiency (approximately 19% depletion) may not be as extreme as in Lesch-Nyhan patients (167). Despite the biochemical similarities between HPRT knockout mice and Lesch-Nyhan patients, these knockouts do not show any of the behavioural symptoms that are seen in Lesch-Nyhan syndrome. In particular, the mice do not exhibit motoric dysfunction or SIB (167, 169), even when challenged with apomorphine (167). Furthermore, these mice do not differ from wild-type mice in expression of SIB when treated with clonidine or Bay K 8644 (170) (both of which produce SIB in mice (158–160, 171, 172)). It is currently unclear why HPRT knockout mice fail to exhibit behavioural symptoms of Lesch-Nyhan syndrome (apart from the differences in the levels of dopamine neurotransmission). One possibility is that mice are not as dependent upon this purine salvage enzyme as humans are (in which case another purine salvage enzyme, PRPP might compensate for the missing HPRT).

4


75

3. Summary and Discussion Disregulation of dopamine function constitutes a neurobiological feature upon which our knowledge of clinical SIB and animal models of SIB converge (42–46, 94, 95, 97, 100–104, 115, 135, 138, 142, 147, 158, 161). Accordingly, the mechanisms that produce this disregulation need to be investigated thoroughly in animal models of SIB so that we might develop a greater understanding of the neurobiological basis of this behavioural pathology. Additional convergence is found in assays of serotonergic (42, 56, 96, 106– 110, 145, 159), opioid (46, 50–55, 67, 173), and adenosinergic (41, 47–49, 103, 123–130, 135) function. There is a clear need to investigate these potential contributors more extensively. Individual differences in vulnerability to exhibit SIB are also apparent in both clinical populations (4, 5, 30, 174, 175) and experimentally induced SIB (123, 125, 129, 130, 138, 141, 144, 145, 152). These individual differences have not received a lot of attention, but early environmental impoverishment (10, 20–26, 86, 113, 114, 118, 119, 157, 176) and exposure to stress (11, 28, 111, 114, 118, 119, 155, 156) are common elements that may help to drive vulnerability for SIB. In fact, a key common element in vulnerability for SIB in clinical samples and animal models may be individual differences in affective and physiological responsiveness to stress (27, 29, 120, 121, 152). Degree of intellectual handicap is also an important determinant of vulnerability for SIB in clinical samples (30), and this is supported by evidence from cortical lesions in pemoline-treated rats (141). The utility of the neonatal 6-OHDA, early environmental impoverishment, pemoline, and Bay K 8644 models is well-established, and further investigations of the biochemical basis of SIB in these models is important. The caffeine model appears to have limited utility, owing to the toxic actions of the doses that are required (130). The HPRT knockout mouse surprisingly does not exhibit motor abnormalities or SIB (167, 169), and so it will be particularly challenging to identify why these animals differ from humans with Lesch-Nyhan syndrome. However, this is an important question that certainly warrants additional investigation. Since SIB is prevalent in multiple genetically distinct syndromes, and can be invoked by multiple manipulations in animal models, we could conclude that this behaviour is driven by multiple distinct pathophysiological processes in different syndromes and across different animal models. However, it appears more reasonable to conclude that multiple different neurochemical abnormalities may contribute to the pathophysiology of SIB in the various diagnostic groups and in the various animal models, but there appear to be common elements upon which these inputs

76

D.P. Devine

coalesce. For example, it was recently reported that the Ca2+ channel antagonist nifedipine blocks the induction of SIB in four distinct animal models of SIB. This includes the neonatal 6-OHDA, Bay K 8644, and pemoline models , as well as a methamphetamine model of SIB in mice (which was not discussed in this review) (177). Furthermore, NMDA receptor antagonists have attenuated SIB in both the neonatal 6-OHDA and pemoline models of SIB (139, 148, 178). It is unclear if the beneficial effects of nifedipine will carry over to clinical populations, since this drug has not yet been evaluated in clinical trials. However, the convergent findings with MK-801 in animal models appear to be particularly compelling. This glutamate receptor antagonist cannot be administered to humans because it has psychotomimetic actions (179). However, drugs that diminish glutamate release (e.g., riluzole, lamotrigine) are showing promise for attenuating the expression of SIB in a broad variety of clinical disorders (180–183). References 1. Lesch, M. and Nyhan, W. L. (1964) A familial disorder of uric acid metabolism and central nervous system function, Am. J. Med., 36, 561–570. 2. Nyhan, W. L. (1968) Seminars on the LeschNyhan syndrome: Summary of clinical features, Fed. Proc., 27, 1034–1041. 3. Stein, D. J., Keating, J., Zar, H. J., and Hollander, E. (1994) A survey of the phenomenology and pharmacotherapy of compulsive and impulsive-aggressive symptoms in Prader-Willi syndrome, J. Neuropsychiatry. Clin. Neurosci., 6, 23–29. 4. Symons, F. J., Butler, M. G., Sanders, M. D., Feurer, I. D., and Thompson, T. (1999) Selfinjurious behavior and Prader-Willi syndrome: behavioral forms and body locations, Am. J. Ment. Retard., 104, 260–269. 5. Berney, T. P., Ireland, M., and Burn, J. (1999) Behavioural phenotype of Cornelia de Lange syndrome, Arch. Dis. Child., 81, 333–336. 6. Poustka, F. and Lisch, S. (1993) Autistic behaviour domains and their relation to self-injurious behaviour, Acta Paedopsychiatr., 56, 69–73. 7. Wing, L. (1975) The syndrome of early childhood autism, Br. J. Psychiatry, Spec No 9, 349–360. 8. Oliver, C., Murphy, G. H., and Corbett, J. A. (1987) Self-injurious behavior in people with mental handicap: a total population study, J. Ment. Def. Res., 31, 147–162. 9. Ando, H. and Yoshimura, I. (1979) Speech skill levels and prevalence of maladaptive behaviors in autistic and mentally retarded

children: a statistical study, Child Psychiatry Hum. Dev., 10, 85–90. 10. Schroeder, S. R., Schroeder, C. S., Smith, B., and Dalldorf, J. (1978) Prevalence of selfinjurious behaviors in a large state facility for the retarded: a three-year follow-up study, J. Autism. Child Schizophr., 8, 261–269. 11. Anderson, L. T. and Ernst, M. (1994) Selfinjury in Lesch-Nyhan disease, J. Autism. Dev. Disord., 24, 67–81. 12. Clarke, D. J., Waters, J., and Corbett, J. A. (1989) Adults with Prader-Willi syndrome: abnormalities of sleep and behaviour, J. R. Soc. Med., 82, 21–24. 13. Baghdadli, A., Pascal, C., Grisi, S., and Aussilloux, C. (2003) Risk factors for selfinjurious behaviours among 222 young children with autistic disorders, J Intellect. Disabil. Res., 47, 622–627. 14. Sigafoos, J., Elkins, J., Kerr, M., and Attwood, T. (1994) A survey of aggressive behaviour among a population of persons with intellectual disability in Queensland, J. Intellect. Disabil. Res., 38, 369–381. 15. Durand, V. M. and Carr, E. G. (1985) Selfinjurious behavior: motivating conditions and guidelines for treatment, School Psychol. Rev., 14, 171–176. 16. Carr, E. G. and Durand, V. M. (1985) Reducing behavior problems through functional communication training, J. Appl. Behav. Anal., 18, 111–126. 17. Iwata, B. A., Dorsey, M. F., Slifer, K. J., Bauman, K. E., and Richman, G. S. (1982)

4 Toward a functional analysis of self-injury, Analysis & Intervention Dev. Dis., 2, 3–30. 18. Bird, F., Dores, P. A., Moniz, D., and Robinson, J. (1989) Reducing severe aggressive and self-injurious behaviors with functional communication training, Am. J. Ment. Retard., 94, 37–48. 19. Sigafoos, J. and Meikle, B. (1996) Functional communication training for the treatment of multiply determined challenging behavior in two boys with autism, Behav. Modif., 20, 60–84. 20. Barron, J. L. and Sandman, C. A. (1984) Selfinjurious behavior and stereotypy in an institutionalized mentally retarded population, App. Res. Ment. Ret., 5, 499–511. 21. Griffin, J. C., Williams, D. E., Stark, M. T., Altmeyer, B. K., and Mason, M. (1986) Selfinjurious behavior: a state-wide prevalence survey of the extent and circumstances, Appl. Res. Ment. Retard., 7, 105–116. 22. Maurice, P. and Trudel, G. (1982) Selfinjurious behavior prevalence and relationships to environmental events, Monogr. Am. Assoc. Ment. Defic., 5, 81–103. 23. Singh, N. N. (1977) Prevalence of self-injury in institutionalised retarded children, N. Z. Med. J., 86, 325–327. 24. Favell, J. E., McGimsey, J. F., and Schell, R. M. (1982) Treatment of self-injury by providing alternate sensory activities, Analysis & Intervention Dev. Dis., 2, 83–104. 25. Favell, J. E., Azrin, N. A., Baumeister, A. A., Carr, E. G., Dorsey, M. F., Forehand, R., Foxx, R. M., Lovaas, O. I., Rincover, A., Risley, T., Romanczyk, R. G., Russo, D. C., Schroeder, S. R., and Solnick, J. V. (1982) The treatment of self-injurious behavior, Behav. Ther., 13, 529–554. 26. Beckett, C., Bredenkamp, D., Castle, J., Groothues, C., O’Connor, T. G., and Rutter, M. (2002) Behavior patterns associated with institutional deprivation: a study of children adopted from Romania, J. Dev. Behav. Pediatr., 23, 297–303. 27. Sovner, R. and Fogelman, S. (1996) Irritability and Mental Retardation, Semin. Clin. Neuropsychiatry, 1, 105–114. 28. Lindauer, S. E., DeLeon, I. G., and Fisher, W. W. (1999) Decreasing signs of negative affect and correlated self-injury in an individual with mental retardation and mood disturbances, J. Appl. Behav. Anal., 32, 103–106. 29. Verhoeven, W. M. A., Tuinier, S., van den Berg, Y. W. M. M., Coppus, A. M. W., Fekkes, D., Pepplinkhuizen, L., and Thijssen, J. H. H. (1999) Stress and self-injurious behavior;


77

hormonal and serotonergic parameters in mentally retarded subjects, Pharmacopsychiatry., 32, 13–20. 30. Rojahn, J. and Esbensen, A. J. (2002) Epidemiology of self-injurious behavior in mental retardation: A review. In: Schroeder, S. R., Oster-Granite, M. L., Thompson, T. (Eds.), Self-Injurious Behavior: Gene-BrainBehavior Relationships, American Psychological Association, Washington, D.C., pp. 41–77. 31. Durand, V. M. and Carr, E. G. (1991) Functional communication training to reduce challenging behavior: maintenance and application in new settings, J. Appl. Behav. Anal., 24, 251–264. 32. Azrin, N. H., Gottlieb, L., Hughart, L., Wesolowski, M. D., and Rahn, T. (1975) Eliminating self-injurious behavior by educative procedures, Behav. Res. Ther., 13, 101–111. 33. Cowdery, G. E., Iwata, B. A., and Pace, G. M. (1990) Effects and side effects of DRO as treatment for self-injurious behavior, J. Appl. Behav. Anal., 23, 497–506. 34. Linscheid, T. R., Iwata, B. A., Ricketts, R. W., Williams, D. E., and Griffin, J. C. (1990) Clinical evaluation of the self-injurious behavior inhibiting system (SIBIS), J. Appl. Behav. Anal., 23, 53–78. 35. Tarpley, H. D. and Schroeder, S. R. (1979) Comparison of DRO and DRI on rate of suppression of self-injurious behavior, Am. J. Ment. Def., 84, 188–194. 36. Bruhl, H. H., Fielding, L., Joyce, M., Peters, W., and Wieseler, N. (1982) Thirty-month demonstration project for treatment of selfinjurious behavior in severely retarded individuals, Monogr. Am. Assoc. Ment. Defic., 191–275. 37. Vollmer, T. R. (1994) The concept of automatic reinforcement: implications for behavioral research in developmental disabilities, Res. Dev. Disabil., 15, 187–207. 38. Iwata, B. A., Pace, G. M., Dorsey, M. F., Zarcone, J. R., Vollmer, T. R., Smith, R. G., Rodgers, T. A., Lerman, D. C., Shore, B. A., Mazalesk, J. L., and . (1994) The functions of self-injurious behavior: an experimental-epidemiological analysis, J. Appl. Behav. Anal., 27, 215–240. 39. Underwood, L. A., Figueroa, R. G., Thyer, B. A., and Nzeocha, A. (1989) Interruption and DRI in the treatment of self-injurious behavior among mentally retarded and autistic selfrestrainers, Behav. Modif., 13, 471–481. 40. Olson, L. and Houlihan, D. (2000) A review of behavioral treatments used for Lesch-Nyhan syndrome, Behav. Modif., 24, 202–222.

78

D.P. Devine

41. Seegmiller, J. E., Rosenbloom, F. M., and Kelley, W. N. (1967) Enzyme defect associated with a sex-linked human neurological disorder and excessive purine synthesis, Science, 155, 1682–1684. 42. Lloyd, K. G., Hornykiewicz, O., Davidson, L., Shannak, K., Farley, I., Goldstein, M., Shibuya, M., Kelley, W. N., and Fox, I. H. (1981) Biochemical evidence of dysfunction of brain neurotransmitters in the Lesch-Nyhan syndrome, N. Eng. J. Med., 305, 1106–1111. 43. Ernst, M., Zametkin, A. J., Matochik, J. A., Pascualvaca, D., Jons, P. H., Hardy, K., Hankerson, J. G., Doudet, D. J., and Cohen, R. M. (1996) Presynaptic dopaminergic deficits in Lesch-Nyhan disease, N. Engl. J. Med., 334, 1568–1572. 44. Ernst, M., Zametkin, A. J., Matochik, J. A., Pascualvaca, D., and Cohen, R. M. (1997) Low medial prefrontal dopaminergic activity in autistic children, Lancet, 350, 638. 45. Brucke, T., Sofic, E., Killian, W., Rett, A., and Riederer, P. (1987) Reduced concentrations and increased metabolism of biogenic amines in a single case of Rett-syndrome: a postmortem brain study, J Neural Transm., 68, 315–324. 46. Saito, Y., Ito, M., Hanaoka, S., Ohama, E., Akaboshi, S., and Takashima, S. (1999) Dopamine receptor upregulation in LeschNyhan syndrome: a postmortem study, Neuropediatrics., 30, 66–71. 47. Rosenberger-Debiesse, J. and Coleman, M. (1986) Preliminary evidence for multiple etiologies in autism, J. Autism. Dev. Disord., 16, 385–392. 48. Page, T. and Coleman, M. (1998) De novo purine synthesis is increased in the fibroblasts of purine autism patients, Adv. Exp. Med. Biol., 431, 793–796. 49. Sweetman, L. and Nyhan, W. L. (1970) Detailed comparison of the urinary excretion of purines in a patient with the Lesch-Nyhan syndrome and a control subject, Biochem. Med., 4, 121–134. 50. Sandman, C. A., Barron, J. L., Chicz-DeMet, A., and DeMet, E. M. (1990) Plasma b-endorphin levels in patients with self-injurious behavior and stereotypy, Am. J. Ment. Retard., 95, 84–92. 51. Coid, J., Allolio, B., and Rees, L. H. (1983) Raised plasma metenkephalin in patients who habitually mutilate themselves, Lancet, 2, 545–546. 52. Gillberg, C., Terenius, L., and Lonnerholm, G. (1985) Endorphin activity in childhood psychosis. Spinal fluid levels in 24 cases, Arch. Gen. Psychiatry., 42, 780–783.

53. Sandman, C. A. (1988) b-endorphin disregulation in autistic and self-injurious behavior: a neurodevelopmental hypothesis, Synapse, 2, 193–199. 54. Willemsen-Swinkels, S. H. N., Buitelaar, J. K., Weijnen, F. G., Thijssen, J. H. H., and Van Engeland, H. (1996) Plasma beta-endorphin concentrations in people with learning disability and self-injurious and/or autistic behaviour, Brit. J. Psychiat., 168, 105–109. 55. Sandman, C. A., Hetrick, W., Talyor, D., Marion, S., and Chicz-DeMet, A. (2000) Uncoupling of proopiomelanocortin (POMC) fragments is related to self-injury, Peptides, 21, 785–791. 56. Jankovic, J., Caskey, T. C., Stout, J. T., and Butler, I. J. (1988) Lesch-Nyhan syndrome: A study of motor behavior and cerebrospinal fluid neurotransmitters, Ann. Neurol., 23, 466–469. 57. Symons, F. J., Sutton, K. A., Walker, C., and Bodfish, J. W. (2003) Altered diurnal pattern of salivary substance P in adults with developmental disabilities and chronic self-injury, Am. J Ment. Retard., 108, 13–18. 58. Kemp, A. S., Fillmore, P. T., Lenjavi, M. R., Lyon, M., Chicz-DeMet, A., Touchette, P. E., and Sandman, C. A. (2008) Temporal patterns of self-injurious behavior correlate with stress hormone levels in the developmentally disabled, Psychiatry Res., 157, 181–189. 59. Crews, W. D. J., Bonaventura, S., Rowe, F. B., and Bonsie, D. (1993) Cessation of long-term naltrexone therapy and self-injury: a case study, Res. Dev. Disabil., 14, 331–340. 60. Gillman, M. A. and Sandyk, R. (1985) Opiatergic and dopaminergic function in Lesch-Nyhan syndrome, Am. J. Psychiatry., 142, 1226. 61. Herman, B. H., Hammock, M. K., ArthurSmith, A., Egan, J., Chatoor, I., Werner, A., and Zelnick, N. (1987) Naltrexone decreases self-injurious behavior, Ann. Neurol., 22, 550–552. 62. Richardson, J. S. and Zaleski, W. A. (1983) Naloxone and self-mutilation, Biol. Psychi., 18, 99–101. 63. Sandman, C. A., Barron, J. L., Crinella, F. M., and Donnelly, J. F. (1987) Influence of naloxone on brain and behavior of a self-injurious woman, Biol. Psychi., 22, 899–906. 64. Sandman, C. A., Barron, J. L., and Colman, H. (1990) An orally administered opiate blocker, naltrexone, attenuates self-injurious behavior, Am. J. Ment. Retard., 95, 93–102. 65. Sandyk, R. (1985) Naloxone abolishes selfinjuring in a mentally retarded child, Ann. Neurol., 17, 520.

4 66. Benjamin, E. and Buot-Smith, T. (1993) Naltrexone and fluoxetine in Prader-Willi syndrome, J. Am. Acad. Child Adolesc. Psychiatry., 32, 870–873. 67. Symons, F. J., Thompson, A., and Rodriguez, M. C. (2004) Self-injurious behavior and the efficacy of naltrexone treatment: a quantitative synthesis, Ment. Retard. Dev. Disabil. Res. Rev., 10, 193–200. 68. Willemsen-Swinkels, S. H. N., Buitelaar, J. K., Nijhof, G. J., and Van Engeland, H. (1995) Failure of naltrexone hydrochloride to reduce self-injurious and autistic behavior in mentally retarded adults – Double-blind placebocontrolled studies, Arch. Gen. Psychiatry., 52, 766–773. 69. Davidson, P. W., Kleene, B. M., Carroll, M., and Rockowitz, R. J. (1983) Effects of naloxone on self-injurious behavior: a case study, App. Res. Ment. Ret., 4, 1–4. 70. Allen, S. M. and Rice, S. N. (1996) Risperidone antagonism of self-mutilation in a LeschNyhan patient, Prog. Neuropsychopharmacol. Biol. Psychiatry, 20, 793–800. 71. Cohen, S. A., Ihrig, K., Lott, R. S., and Kerrick, J. M. (1998) Risperidone for aggression and self-injurious behavior in adults with mental retardation, J. Autism. Dev. Disord., 28, 229–233. 72. Horrigan, J. P. and Barnhill, L. J. (1997) Risperidone and explosive aggressive autism, J. Autism. Dev. Disord., 27, 313–323. 73. Gualtieri, C. T. and Schroeder, S. R. (1989) Pharmacotherapy for self-injurious behavior: preliminary tests of the D1 hypothesis, Psychopharmacol. Bull., 25, 364–371. 74. Singh, N. N. and Winton, A. S. (1984) Behavioral monitoring of pharmacological interventions for self-injury, Appl. Res. Ment. Retard., 5, 161–170. 75. Gedye, A. (1990) Dietary increase in serotonin reduces self-injurious behaviour in a Down’s syndrome adult, J. Ment. Def. Res., 34, 195–204. 76. Markowitz, P. I. (1992) Effect of fluoxetine on self-injurious behavior in the developmentally disabled: a preliminary study, J. Clin. Psychopharmacol., 12, 27–31. 77. Sovner, R., Fox, C. J., Lowry, M. J., and Lowry, M. A. (1993) Fluoxetine treatment of depression and associated self-injury in two adults with mental retardation, J. Intellect. Disabil. Res., 37, 301–311. 78. Warnock, J. K. and Kestenbaum, T. (1992) Pharmacologic treatment of severe skin-picking behaviors in Prader-Willi syndrome. Two case reports, Arch. Dermatol., 128, 1623–1625.


79

79. Frith, C. D., Johnstone, E. C., Joseph, M. H., Powell, R. J., and Watts, R. W. E. (1976) Double-blind clinical trial of 5-hydroxytryptophan in a case of Lesch-Nyhan syndrome, J. Neurol. Neurosurg. & Psychi., 39, 656–662. 80. Ciaranello, R. D., Anders, T. F., Barchas, J. D., Berger, P. A., and Cann, H. M. (1976) The use of 5-hydroxytryptophan in a child with Lesch-Nyhan syndrome, Child Psychiatry Hum. Dev., 7, 127–133. 81. Davanzo, P. A., Belin, T. R., Widawski, M. H., and King, B. H. (1998) Paroxetine treatment of aggression and self-injury in persons with mental retardation, Am. J. Ment. Retard., 102, 427–437. 82. Anders, T. F., Cann, H. M., Ciaranello, R. D., Barchas, J. D., and Berger, P. A. (1978) Further observations on the use of 5-hydroxytryptophan in a child with Lesch-Nyhan syndrome, Neuropadiatrie., 9, 157–166. 83. Janowsky, D. S., Kraus, J. E., Barnhill, J., Elamir, B., and Davis, J. M. (2003) Effects of topiramate on aggressive, self-injurious, and disruptive/destructive behaviors in the intellectually disabled: an open-label retrospective study, J Clin. Psychopharmacol., 23, 500–504. 84. Smathers, S. A., Wilson, J. G., and Nigro, M. A. (2003) Topiramate effectiveness in Prader-Willi syndrome, Pediatr. Neurol., 28, 130–133. 85. Shapira, N. A., Lessig, M. C., Murphy, T. K., Driscoll, D. J., and Goodman, W. K. (2002) Topiramate attenuates self-injurious behaviour in Prader-Willi syndrome, Int. J. Neuropsychopharmacol., 5, 141–145. 86. Harlow, H. F. and Harlow, M. K. (1962) Social deprivation in monkeys, Scient. Am., 207, 136–146. 87. Novak, M. A., Crockett, C. M., and Sackett, G. P. (2002) Self-injurious behavior in captive macaque monkeys. In: Schroeder, S. R., OsterGranite, M. L., Thompson, T. (Eds.), SelfInjurious Behavior: Gene-Brain-Behavior Relationships, American Psychological Association, Washington D.C., pp. 151–161. 88. Dodman, N. H., Normile, J. A., Shuster, L., and Rand, W. (1994) Equine self-mutilation syndrome (57 cases), J. Am. Vet. Med. Assoc., 204, 1219–1223. 89. Jenkins, J. R. (2001) Feather picking and selfmutilation in psittacine birds, Vet. Clin. North Am. Exot. Anim Pract., 4, 651–667. 90. Schwartz, S. (1996) Animal behavior case of the month. A cat was referred for evaluation of self-mutilation, J. Am. Vet. Med. Assoc., 208, 1813–1814.

80

D.P. Devine

91. Schwartz, S. (2002) Separation anxiety syndrome in cats: 136 cases (1991–2000), J. Am. Vet. Med. Assoc., 220, 1028–1033. 92. Iglauer, F., Beig, C., Dimigen, J., Gerold, S., Gocht, A., Seeburg, A., Steier, S., and Willmann, F. (1995) Hereditary compulsive self-mutillating behaviour in laboratory rabbits, Lab. Animals, 29, 385–393. 93. Goodall, J., The Chimpanzees of Gombe: Patterns of Behavior, Bellknap Press of Harvard University Press, Cambridge, MA, 1986. 94. Breese, G. R., Baumeister, A. A., McCown, T. J., Emerick, S. G., Frye, G. D., Crotty, K., and Mueller, R. A. (1984) Behavioral differences between neonatal and adult 6-hydroxydopamine-treated rats to dopamine agonists: relevance to neurological symptoms in clinical syndromes with reduced brain dopamine, J. Pharmacol. & Exp. Ther., 231, 343–354. 95. Breese, G. R., Baumeister, A. A., McCown, T. J., Emerick, S. G., Frye, G. D., and Mueller, R. A. (1984) Neonatal-6-hydroxydopamine treatment: Model of susceptibility for selfmutilation in the Lesch-Nyhan syndrome, Pharmacol. Biochem. Behav., 21, 459–461. 96. Sivam, S. P., Pugazhenthi, S., Pugazhenthi, V., and Brown, H. (2008) L-DOPA-induced activation of striatal p38MAPK and CREB in neonatal dopaminergic denervated rat: relevance to self-injurious behavior, J. Neurosci. Res., 86, 339–349. 97. Sivam, S. P. (1989) D1 dopamine receptormediated substance P depletion in the striatonigral neurons of rats subjected to neonatal dopaminergic denervation: implications for self-injurious behavior, Brain Res., 500, 119–130. 98. Neal, B. S. and Joyce, J. N. (1992) Neonatal 6-OHDA lesions differentially affect striatal D1 and D2 receptors, Synapse, 11, 35–46. 99. Molina-Holgado, E., Van Gelder, N. M., Dewar, K. M., and Reader, T. A. (1995) Dopamine receptor alterations correlate with increased GABA levels in adult rat neostriatum: Effects of a neonatal 6-hydroxydopamine denervation, Neurochem. Int., 27, 443–451. 100. Radja, F., El Mansari, M., Soghomonian, J.-J., Dewar, K. M., Ferron, A., Reader, T. A., and Descarries, L. (1993) Changes of D1 and D2 receptors in adult rat neostriatum after neonatal dopamine denervation: In situ hybridization and iontophoresis, Neurosci., 57, 635–648. 101. Breese, G. R., Baumeister, A. A., Napier, T. C., Frye, G. D., and Mueller, R. A. (1985) Evidence that D-1 dopamine receptors contribute to the supersensitive behavioral

responses induced by l-dihydroxyphenylalanine in rats treated neonatally with 6-hydroxydopamine, J. Pharmacol. & Exp. Ther., 235, 287–295. 102. Criswell, H. E., Mueller, R. A., and Breese, G. R. (1992) Pharmacologic evaluation of SCH39166, A-69024, NO-0756, and SCH-23390 in neonatal-6-OHDA-lesioned rats. Further evidence that self-mutilatory behavior induced by L-DOPA is related to D1 dopamine receptors, Neuropsychopharmacol., 7, 95–103. 103. Criswell, H. E., Mueller, R. A., and Breese, G. R. (1988) Assessment of purine-dopamine interactions in 6-hydroxydopamine-lesioned rats: evidence for pre- and postsynaptic influences by adenosine, J. Pharmacol. & Exp. Ther., 244, 493–500. 104. Fletcher, G. H. and Starr, M. S. (1987) Topography of dopamine behaviours mediated by D1 and D2 receptors revealed by intrastriatal injection of SKF 38393, lisuride and apomorphine in rats with a unilateral 6-hydroxydopamine-induced lesion, Neurosci., 20, 589–597. 105. Allen, S. M., Freeman, J. N., and Davis, W. M. (1998) Evaluation of risperidone in the neonatal 6-hydroxydopamine model of LeschNyhan syndrome, Pharmacol. Biochem. Behav., 59, 327–330. 106. El Mansari, M., Radja, F., Ferron, A., Reader, T. A., Molina-Holgado, E., and Descarries, L. (1994) Hypersensitivity to serotonin and its agonists in serotonin-hyperinnervated neostriatum after neonatal dopamine denervation, Eur. J. Pharmacol., 261, 171–178. 107. Jackson, D. and Abercrombie, E. D. (1992) In vivo neurochemical evaluation of striatal serotonergic hyperinnervation in rats depleted of dopamine at infancy, J. Neurochem., 58, 890–897. 108. Mrini, A., Soucy, J.-P., Lafaille, F., Lemoine, P., and Descarries, L. (1995) Quantification of the serotonin hyperinnervation in adult rat neostriatum after neonatal 6-hydroxydopamine lesion of nigral dopamine neurons, Brain Res., 669, 303–308. 109. Towle, A. C., Criswell, H. E., Maynard, E. H., Lauder, J. M., Joh, T. H., Mueller, R. A., and Breese, G. R. (1989) Serotonergic innervation of the rat caudate following a neonatal 6-hydroxydopamine lesion: an anatomical, biochemical and pharmacological study, Pharmacol. Biochem. Behav., 34, 367–374. 110. Allen, S. M. and Davis, W. M. (1999) Relationship of dopamine to serotonin in the neonatal 6-OHDA rat model of LeschNyhan syndrome, Behav. Pharmacol., 10, 467–474.

4 111. Stodgell, C. J., Loupe, P. S., Schroeder, S. R., and Tessel, R. E. (1998) Cross-sensitization between footshock stress and apomorphine on self-injurious behavior and neostriatal catecholamines in a rat model of Lesch-Nyhan syndrome, Brain Res., 783, 10–18. 112. Sorg, B. A. and Kalivas, P. W. (1991) Effects of cocaine and footshock stress on extracellular dopamine levels in the ventral striatum, Brain Res., 559, 29–36. 113. Cross, H. A. and Harlow, H. F. (1965) Prolonged and progressive effects of partial isolation on the behavior of macaque monkeys, J. Exp. Res. Pers., 1, 39–49. 114. Gluck, J. P. and Sackett, G. P. (1974) Frustration and self-aggression in social isolate rhesus monkeys, J. Abn. Psychol., 83, 331–334. 115. Clarke, A. S., Ebert, M. H., Schmidt, D. E., McKinney, W. T., and Kraemer, G. W. (1999) Biogenic amine activity in response to fluoxetine and desipramine in differentially reared rhesus monkeys, Biol. Psychiatry., 46, 221–228. 116. Lewis, M. H., Gluck, J. P., Beauchamp, A. J., Keresztury, M. F., and Mailman, R. B. (1990) Long-term effects of early social isolation in Macaca-Mulatta: changes in dopamine receptor function following apomorphine challenge, Brain Res., 513, 67–73. 117. Martin, L. J., Spicer, D. M., Lewis, M. H., Gluck, J. P., and Cork, L. C. (1991) Social deprivation of infant rhesus monkeys alters the chemoarchitecture of the brain: I. Subcortical regions, J. Neurosci., 11, 3344–3358. 118. Young, L. D., Suomi, S. S., Harlow, H. F., and McKinney, W. T., Jr. (1973) Early stress and later response to separation in rhesus monkeys, Am. J. Psychiatry., 130, 400–405. 119. Davenport, M. D., Lutz, C. K., Tiefenbacher, S., Novak, M. A., and Meyer, J. S. (2008) A rhesus monkey model of self-injury: effects of relocation stress on behavior and neuroendocrine function, Biol. Psychiatry., 63, 990–996. 120. Tiefenbacher, S., Novak, M. A., Jorgensen, M. J., and Meyer, J. S. (2000) Physiological correlates of self-injurious behavior in captive, socially-reared rhesus monkeys, Psychoneuroendo., 25, 799–817. 121. Tiefenbacher, S., Novak, M. A., Marinus, L. M., Chase, W. K., Miller, J. A., and Meyer, J. S. (2004) Altered hypothalamic-pituitaryadrenocortical function in rhesus monkeys (Macaca mulatta) with self-injurious behavior, Psychoneuroendo., 29, 501–515. 122. Fulford, A. J. and Marsden, C. A. (1998) Effect of isolation-rearing on conditioned dopamine release in vivo in the nucleus accumbens of the rat, J. Neurochem., 70, 384–390.


81

123. Peters, J. M. (1967) Caffeine-induced hemorrhagic automutilation, Arch. Int. Pharmacodyn. Ther., 169, 139–146. 124. Hoefnagel, D. (1968) Seminars on the LeschNyhan syndrome: summary, Fed. Proc., 27, 1042–1046. 125. Ferrer, I., Costell, M., and Grisolia, S. (1982) Lesch-Nyhan syndrome like behavior in rats from caffeine injestion, FEBS Lett., 141, 275–278. 126. Minana, M. D., Portoles, M., Jorda, A., and Grisolia, S. (1984) Lesch-Nyhan syndrome, caffeine model: increases of purine and pyrimidine enzymes in rat brain, J. Neurochem., 43, 1556–1560. 127. Minana, M. D. and Grisolia, S. (1986) Caffeine ingestion by rats increases noradrenaline turnover and results in self-biting, J. Neurochem., 47, 728–732. 128. Mueller, K., Saboda, S., Palmour, R. A., and Nyhan, W. L. (1982) Self-injurious behaviour produced in rats by daily caffeine and continuous amphetamine, Pharmacol. Biochem. Behav., 17, 613–617. 129. Mueller, K. and Nyhan, W. L. (1983) Clonidine potentiates drug induced selfinjurious behavior in rats, Pharmacol. Biochem. Behav., 18, 891–894. 130. Kies, S. D. and Devine, D. P. (2004) Selfinjurious behaviour: A comparison of caffeine and pemoline models in rats, Pharmacol. Biochem. Behav., 79, 587–598. 131. Snyder, S. H. (1985) Adenosine as a neuromodulator. In: Cowan, W. M., Shooter, E. M., Stevens, C. F., Thompson, R. F. (Eds.), Annual Review of Neuroscience, Annual Reviews Inc., Palo Alto, California, pp. 103–124. 132. Ferré, S., Fuxe, K., von Euler, G., Johansson, B., and Fredholm, B. B. (1992) Adenosinedopamine interactions in the brain, Neurosci., 51, 501–512. 133. Brown, S. J., James, S., Reddington, M., and Richardson, P. J. (1990) Both A1 and A2a purine receptors regulate striatal acetylcholine release, J. Neurochem., 55, 31–38. 134. Brown, S. J., Gill, R., Evenden, J. L., Iversen, S. D., and Richardson, P. J. (1991) Striatal A2 receptor regulates apomorphine-induced turning in rats with unilateral dopamine denervation, Psychopharmacol., 103, 78–82. 135. Casas-Bruge, M., Almenar, C., Grau, I. M., Jane, J., Herrera-Marschitz, M., and Ungerstedt, U. (1985) Dopaminergic receptor supersensitivity in self-mutilatory behavior of Lesch-Nyhan disease, Lancet., 1(8435), 991–992.

82

D.P. Devine

136. King, B. H., Cromwell, H. C., Lee, H. T., Behrstock, S. P., Schmanke, T., and Maidment, N. T. (1998) Dopaminergic and glutamatergic interactions in the expression of self-injurious behavior, Dev. Neurosci., 20, 180–187. 137. Everett, G. M. (1976) Comparative pharmacology of amphetamine and pemoline on biogenic amine systems, Fed. Proc., 35, 405. 138. Cromwell, H. C., King, B. H., and Levine, M. S. (1997) Pemoline alters dopamine modulation of synaptic responses of neostriatal neurons in vitro, Dev. Neurosci., 19, 497–504. 139. King, B. H., Au, D., and Poland, R. E. (1995) Pretreatment with MK-801 inhibits pemolineinduced self-biting behavior in prepubertal rats, Dev. Neurosci., 17, 47–52. 140. Mueller, K. and Hsiao, S. (1980) Pemolineinduced self-biting in rats and self-mutilation in the deLange syndrome, Pharmacol. Biochem. Behav., 13, 627–631. 141. Cromwell, H. C., Levine, M. S., and King, B. H. (1999) Cortical damage enhances pemoline-induced self-injurious behavior in prepubertal rats, Pharmacol. Biochem. Behav., 62, 223–227. 142. Mueller, K. and Nyhan, W. L. (1982) Pharmacologic control of pemoline induced self-injurious behavior in rats, Pharmacol. Biochem. Behav., 16, 957–963. 143. Genovese, E., Napoli, P. A., and BolegoZonta, N. (1969) Self-aggressiveness: a new type of behavioural change induced by pemoline, Life Sci., 8, 513–515. 144. Mueller, K., Hollingsworth, E., and Pettit, H. (1986) Repeated pemoline produces self-injurious behavior in adult and weanling rats, Pharmacol. Biochem. Behav., 25, 933–938. 145. Turner, C. A., Panksepp, J., Bekkedal, M., Borkowski, C., and Burgdorf, J. (1999) Paradoxical effects of serotonin and opioids in pemoline-induced self-injurious behavior, Pharmacol. Biochem. Behav., 63, 361–366. 146. Muehlmann, A. M., Brown, B. D., and Devine, D. P. (2008) Pemoline-induced selfinjurious behavior: a rodent model of pharmacotherapeutic efficacy, J. Pharmacol. Exp. Ther., 324, 214–223. 147. Muehlmann, A. M. and Devine, D. P. (2008) Self-injurious behavior: Individual differences in neurotransmitter concentrations using an animal model. Keystone Symposium: Towards Identifying the Pathophysiology of Autistic Syndromes. 148. Muehlmann, A. M. and Devine, D. P. (2008) Glutamate-mediated neuroplasticity in an animal model of self-injurious behaviour, Behav Brain Res., 189, 32–40.

149. Soderling, T. R. and Derkach, V. A. (2000) Postsynaptic protein phosphorylation and LTP, Trends Neurosci., 23, 75–80. 150. Barnes, C. A., Danysz, W., and Parsons, C. G. (1996) Effects of the uncompetitive NMDA receptor antagonist memantine on hippocampal long-term potentiation, short-term exploratory modulation and spatial memory in awake, freely moving rats, Eur. J. Neurosci., 8, 565–571. 151. Chen, H. S., Wang, Y. F., Rayudu, P. V., Edgecomb, P., Neill, J. C., Segal, M. M., Lipton, S. A., and Jensen, F. E. (1998) Neuroprotective concentrations of the N-methyl-D-aspartate open-channel blocker memantine are effective without cytoplasmic vacuolation following post-ischemic administration and do not block maze learning or longterm potentiation, Neurosci., 86, 1121–1132. 152. Muehlmann, A. M., Wilkinson, J. A., and Devine, D. P. (2011) Individual differences in vulnerability for self-injurious behavior: Studies using an animal model, Behav. Brain Res., 2;217(1), 148–154. 153. Stead, J. D. H., Clinton, S., Neal, C., Schneider, J., Jama, A., Miller, S., Vazquez, D. M., Watson, S. J., and Akil, H. (2006) Selective breeding for divergence in novelty-seeking traits: heritability and enrichment in spontaneous anxiety-related behaviors, Behav. Genet., 36, 697–712. 154. Kabbaj, M., Devine, D. P., Savage, V. R., and Akil, H. (2000) Neurobiological correlates of individual differences in novelty-seeking behavior in the rat: differential expression of stress-related molecules, J. Neurosci., 20, 6983–6986. 155. Muehlmann, A. M., Wolfman, S., and Devine, D. P. (2008) Examining the effects of chronic stress on self-injurious behavior in an animal model. Soc. Neurosci. Abstr., 34, 446.29. 156. Devine, D. P. and Muehlmann, A. M. (2009) Tiermodelle für selbstverletzendes Verhalten (Animal models of self-injurious behavior). In: Schmahl, C., Stiglmayr, C. (Eds.), Selbstverletzendes Verhalten bei Stressassoziierten Erkrankungen (SelfInjurious Behaviour in Stress-Associated Disorders), Verlag W. Kohlhammer, Stuttgart, Germany, pp. 39–60. 157. Kies, S. D., Turner, C. A., Lewis, M. H., and Devine, D. P. (2002) Effects of environmental complexity in an animal model of self-injury. Soc. Neurosci. Abstr., 28, 207.8. 158. Kasim, S. and Jinnah, H. A. (2003) Self-biting induced by activation of L-type calcium channels in mice: dopaminergic influences, Dev. Neurosci., 25, 20–25.

4 159. Kasim, S., Egami, K., and Jinnah, H. A. (2002) Self-biting induced by activation of L-type calcium channels in mice: serotonergic influences, Dev. Neurosci., 24, 322–327. 160. Jinnah, H. A., Yitta, S., Drew, T., Kim, B. S., Visser, J. E., and Rothstein, J. D. (1999) Calcium channel activation and self-biting in mice, Proc. Natl. Acad. Sci. USA., 96, 15228–15232. 161. Kasim, S., Blake, B. L., Fan, X., Chartoff, E., Egami, K., Breese, G. R., Hess, E. J., and Jinnah, H. A. (2006) The role of dopamine receptors in the neurobehavioral syndrome provoked by activation of L-type calcium channels in rodents, Dev. Neurosci., 28, 505–517. 162. Hooper, M., Hardy, K., Handyside, A., Hunter, S., and Monk, M. (1987) HPRTdeficient (Lesch-Nyhan) mouse embryos derived from germline colonization by cultured cells, Nature., 326, 292–295. 163. Kuehn, M. R., Bradley, A., Robertson, E. J., and Evans, M. J. (1987) A potential animal model for Lesch-Nyhan syndrome through introduction of HPRT mutations into mice, Nature., 326, 295–298. 164. Jinnah, H. A., Hess, E. J., Wilson, M. C., Gage, F. H., and Friedmann, T. (1992) Localization of hypoxanthine-guanine phosphoribosyltransferase mRNA in the mouse brain by in situ hybridization, Mol. & Cell. Neurosci., 3, 64–78. 165. Jinnah, H. A., Page, T., and Friedmann, T. (1993) Brain purines in a genetic mouse model of Lesch-Nyhan disease, J. Neurochem., 60, 2036–2045. 166. Dunnett, S. B., Sirinathsinghji, D. J., Heavens, R., Rogers, D. C., and Kuehn, M. R. (1989) Monoamine deficiency in a transgenic (Hprt-) mouse model of Lesch-Nyhan syndrome, Brain Res., 501, 401–406. 167. Finger, S., Heavens, R. P., Sirinathsinghji, D. J. S., Kuehn, M. R., and Dunnett, S. B. (1988) Behavioral and neurochemical evaluation of a transgenic mouse model of Lesch-Nyhan syndrome, J. Neurol. Sci., 86, 203–213. 168. Jinnah, H. A., Wojcik, B. E., Hunt, M., Narang, N., Lee, K. Y., Goldstein, M., Wamsley, J. K., Langlais, P. J., and Friedmann, T. (1994) Dopamine deficiency in a genetic mouse model of Lesch-Nyhan disease, J. Neurosci., 14, 1164–1175. 169. Engle, S. J., Womer, D. E., Davies, P. M., Boivin, G., Sahota, A., Simmonds, H. A., Stambrook, P. J., and Tischfield, J. A. (1996) HPRT-APRT-deficient mice are not a model for Lesch-Nyhan syndrome, Hum. Mol. Genet., 5, 1607–1610.


83

170. Kasim, S. and Jinnah, H. A. (2002) Pharmacologic thresholds for self-injurious behavior in a genetic mouse model of LeschNyhan disease, Pharmacol. Biochem. Behav., 73, 583–592. 171. Razzak, A., Fujiwara, M., Oishi, M. R., and Ueki, S. (1977) Possible involvement of a central noradrenergic system in automutilation induced by clonidine in mice, Jpn. J. Pharmacol., 27, 145–152. 172. Bhattacharya, S. K., Jaiswal, A. K., Mukhopadhyay, M., and Datla, K. P. (1988) Clonidine-induced automutilation in mice as a laboratory model for clinical self-injurious behaviour, J. Psychi. Res., 22, 43–50. 173. King, B. H., Au, D., and Poland, R. E. (1993) Low dose naltrexone inhibits pemoline-induced self-biting behavior in prepubertal rats, J. Child Adol. Psychopharmacol., 3, 71–79. 174. Rojahn, J. (1986) Self-injurious and stereotypic behavior of noninstitutionalized mentally retarded people: prevalence and classification, Am. J. Ment. Defic., 91, 268–276. 175. Rojahn, J. (1984) Self-injurious behavior in institutionalized severely/profoundly retarded adults: prevalence data and staff agreement, J. Behav. Assessment., 6, 13–27. 176. Belluardo, N., Mudo, G., Trovato-Salinaro, A., Le Gurun, S., Charollais, A., Serre-Beinier, V., Amato, G., Haefliger, J. A., Meda, P., and Condorelli, D. F. (2000) Expression of connexin36 in the adult and developing rat brain, Brain Res., 865, 121–138. 177. Blake, B. L., Muehlmann, A. M., Egami, K., Breese, G. R., Devine, D. P., and Jinnah, H. A. (2007) Nifedipine suppresses self-injurious behaviors in animals, Dev. Neurosci., 29, 241–250. 178. Criswell, H. E., Johnson, K. B., Mueller, R. A., and Breese, G. R. (1993) Evidence for involvement of brain dopamine and other mechanisms in the behavioral action of the N-methyl-Daspartic acid antagonist MK-801 in control and 6-hydroxydopamine-lesioned rats, J. Pharmacol. Exp. Ther., 265, 1001–1010. 179. Ellison, G. (1995) The N-methyl-D-aspartate antagonists phencyclidine, ketamine and dizocilpine as both behavioral and anatomical models of the dementias, Brain Res. Brain Res. Rev., 20, 250–267. 180. Davanzo, P. A. and King, B. H. (1996) Open trial lamotrigine in the treatment of self-injurious behavior in an adolescent with profound mental retardation, J. Child Adolesc. Psychopharmacol., 6, 273–279. 181. Sasso, D. A., Kalanithi, P. S., Trueblood, K. V., Pittenger, C., Kelmendi, B., Wayslink, S.,

84

D.P. Devine

Malison, R. T., Krystal, J. H., and Coric, V. (2006) Beneficial effects of the glutamatemodulating agent riluzole on disordered eating and pathological skin-picking behaviors, J. Clin. Psychopharmacol., 26, 685–687. 182. Pittenger, C., Krystal, J. H., and Coric, V. (2005) Initial evidence of the beneficial effects

of glutamate-modulating agents in the treatment of self-injurious behavior associated with borderline personality disorder, J. Clin. Psychiatry., 66, 1492–1493. 183. Rizvi, S. T. (2002) Lamotrigine and borderline personality disorder, J. Child Adolesc. Psychopharmacol., 12, 365–366.

Chapter 5 Rodent Models of Adaptive Decision Making Alicia Izquierdo and Annabelle M. Belcher Abstract Adaptive decision making affords the animal the ability to respond quickly to changes in a dynamic environment: one in which attentional demands, cost or effort to procure the reward, and reward contingencies change frequently. The more flexible the organism is in adapting choice behavior, the more command and success the organism has in navigating its environment. Maladaptive decision making is at the heart of much neuropsychiatric disease, including addiction. Thus, a better understanding of the mechanisms that underlie normal, adaptive decision making helps achieve a better understanding of certain diseases that incorporate maladaptive decision making as a core feature. This chapter presents three general domains of methods that the experimenter can manipulate in animal decision-making tasks: attention, effort, and reward contingency. Here, we present detailed methods of rodent tasks frequently employed within these domains: the Attentional Set-Shift Task, Effortful T-maze Task, and Visual Discrimination Reversal Learning. These tasks all recruit regions within the frontal cortex and the striatum, and performance is heavily modulated by the neurotransmitter dopamine, making these assays highly valid measures in the study of psychostimulant addiction. Key words: Reward, Rat, Cognitive flexibility, Effort, Choice behavior, Addiction

1. Introduction Despite noteworthy technological advances in functional imaging, practical and ethical limitations inherent in human brain research drive researchers to continue to rely on the animal model to uncover the neurobiological mechanisms of complex cognitive processes. A large corpus of data gathered across experimental species indicates that animals engage in decision making that can be tested to help uncover the neural circuitry and neurotransmitter systems involved in orchestrating choice behavior.


85

86

A. Izquierdo and A.M. Belcher

1.1. Modeling Adaptive Decision Making in Rats

To make adaptive choices, organisms must evaluate the cost of rewards and respond to changes in the incentive value of rewards, a process sometimes referred to as cognitive flexibility (1, 2). Usually, changes in the occurrence or incentive value of a reward (such as food) can be predicted by cues in the environment, and the ability to perceive, attend to, and respond flexibly to those cues is highly predictive of survival and success (3). For example, a rat that typically forages a familiar environment for food must use the new presence of a sensory cue (e.g., a cat) to gather information about the risk or effort involved in obtaining a food reward. When selecting a strategy to obtain the reward, the rat’s choice is informed by at least three important factors: (1) the ability to attend to relevant cues and ignore irrelevant cues (cat odor versus food odor: Which of the two is most relevant to the rat at this time?); (2) the cost or effort required to obtain the reward (What will the rat be required to do to obtain the reward?); and (3) past experience with reward contingency (Has this sensory cue predicted reward or punishment in the past?). Few organisms exist in static, unchanging environments, so the more plastic these associations, the more successful the organism is at coping with changes that affect its ability to procure the goal. Impairments in the ability to flexibly update action–outcome associations, for example, often manifest as perseverative behaviors and/or the inability to monitor one’s own behavior. Similarly, drug addiction is characterized as a compulsion to take the substance with a narrowing of the behavioral repertoire toward excessive intake, and a loss of control of limiting intake (4): features which lie at the very core of a disrupted system subserving cognitive flexibility. Indeed, several clinical reports provide convincing evidence that humans addicted to psychostimulant drugs exhibit significant impairments in multiple domains of executive function, such as in the updating and shifting of new, relevant information, and in their ability to inhibit prepotent responding (5–7). We submit that a comprehensive understanding of addiction cannot be realized without first achieving an understanding of the neural mechanisms of cognitive flexibility. Although humans engage in complex decision making, the use of rodents has been instrumental in uncovering the neural mechanisms of such adaptive responses. The aim of this chapter is to provide researchers with three well-validated behavioral tools by which cognitive flexibility can be explored in the rodent. We also note that this chapter does not review the procedures that manipulate brain mechanisms (the independent variables), but rather the dependent variables or measures by which we frequently assess complex, adaptive decision making in rats. Following a detailed protocol for food restriction in rodents (a procedure common to many assays of instrumental learning), we describe a task that is employed to assess rats’ ability to shift attentional domain: the Attentional Set-Shift Task (ASST). The

5

Adaptive Choices in Rats

87

ASST is a rodent analogue to the Wisconsin Card Sort Task used widely in humans to assess frontal cortex integrity. Like the human version of the task, intact performance in the rat requires that the subject pay attention to shifts in reward contingencies, and importantly, to identify the perceptual features that are rewarded at a given time point. A distinct advantage of this task is in its ability to capture perseverative response patterns and to identify impairments in the ability to make rule-based attentional set-shifts (shifts which may be either intra- or extradimensional in nature). Extradimensional shifting ability is sensitive to lesions of the medial frontal cortex (8), noradrenergic manipulations (9, 10), and psychostimulant exposure (11, 12). Additionally, we have reported that the ability to reverse learned contingencies in this task is impaired by brief, toxic exposure to methamphetamine (13). To assess rats’ responses to changing cost or effort, we then describe the Effortful T-maze Task (ETT) in detail. Lesions or temporary inactivations of the medial frontal cortex, amygdala, and nucleus accumbens produce a pattern of work aversion on this task (14–16), with dopaminergic manipulations producing the most salient impairments on effortful behavior (17, 18). The task is well-validated and with training and testing on effortful barriers complete in approximately 2 months, it provides a fairly quick assessment of these neural substrates in the rat. Lastly, to assess rats’ adaptive responses to changing reward contingency, we outline a protocol for an automated visual discrimination reversal learning (VDRL) task using touchscreen response methodology (13). There are many kinds of reversal tasks used in experimental animals: odor discrimination reversals, response reversals, spatial reversals, and discrimination reversals using visual stimuli. The latter is most similar to that used in cognition studies in nonhuman primates, and is therefore most conducive to cross-species comparisons. Lesions of frontal cortex (19), and medial dorsal thalamic recruitment in rats (20) is modulated by dopamine (21) and thought to be a reliable measure of cognitive flexibility in rodents.

2. Materials 2.1. Attention Set-Shift Task

Rats are trained in a Plexiglas arena measuring 36.8 cm (height) × 45.7 cm (width) × 68.6 cm (length), with the animal’s bedding substrate generously poured into the apparatus. The box is divided equally into thirds so that each compartment is 22.9 cm long (see Fig. 1). The front of the apparatus should further be divided into two separate sections, where the bowls are contained separately, to avoid animals having access to both bowls simultaneously. Additionally, access to each compartment (and bowl) at the front of the box should be restricted by an opaque, removable

88


Fig. 1. The attentional set-shift task (ASST). A rat makes a choice to dig in one of two bowls for a reward based on media cues. The two media shown are shredded paper and paper squares.

divider. The back third of the apparatus should be divided from the other compartments with a removable divider; this intertrial chamber is where rats are placed at the beginning of each trial. Access to the intertrial chamber is blocked once a trial is in progress. Food rewards are hidden in 3.8-cm tall, nonporous ceramic bowls having an internal diameter of 8.3 cm. Rats are trained on successive days to make discriminations based on two dimensions: media of varying textures: paper squares, shredded paper, foam triangles, straws, ¼ foam shells, and crushed foam (all of which can be created using commercially available items) or scents: nutmeg, cloves, cinnamon, cumin, celery seed, and sumac (all crushed or powdered), available commercially in grocer’s aisles (see Note 1). Scents can be mixed interchangeably with media so that combinations of the two dimensions are possible, but pairs of scents or media are kept constant (e.g., nutmeg is always presented with cloves; paper squares are always presented with shredded paper). Food reward consists of half “froot loops” (Kellogg NA Co., Battle Creek, Michigan) buried at the bottom of the bowl. 2.2. Effortful T-Maze Task

A t-maze is commercially available (Stoelting Co., Wood Dale, Illinois) or can be constructed from wood and painted with a gloss or semigloss opaque finish for ease in wiping clean with alcohol. For use in rat behavioral testing, each goal arm measures 41.9 cm in length, 10.2 cm wide, with walls at least 20.3 cm high. The start arm measures 50.3 cm in length. Located approximately 2.5 cm from the far edge of each goal arm are two white ceramic bowls measuring 5.1 cm in diameter. The t-maze should be placed

5


89

Fig. 2. The effortful t-maze task (ETT). (a) A t-maze is outfitted with two ceramic bowls in either goal arm. In the effort phase of training and testing, rats could either scale a barrier impeding procurement to the high reward (four ½ froot loops) or select the low reward arm (1/2 froot loop) with no barrier blocking the reward. (b) Barriers increase in height from 15 to 20, 25, and lastly to 30 cm. Rats are required to scale the 90° side of the barrier to obtain the high reward.

approximately 94.0 cm above the floor during testing and should not be moved throughout the duration of testing. A removable black-and-white-striped Plexiglas insert measuring 40.6 × 101.6 cm is used to position the rat in the start arm before commencing each trial. Between trials, rats are placed in a glass holding tank (25 cm in diameter and 30 cm tall). To allow access to only one of the goal arms (as in Subheading 3.4.3), a white cardboard insert measuring 17.8 × 10.2 cm blocks the goal arm not chosen. For trials in which the rat is required to choose between a high reward of four ½ “froot loops” versus a low reward of only a ½ froot loop, the goal arm containing the high reward is blocked by a barrier of different height: 15, 20, 25, or 30 cm (see Fig. 2). Wire mesh is mounted on all barriers to ease movement up the barrier and down the incline. 2.3. Visual Discrimination Reversal Learning Task

A similar protocol for this task has been outlined in mice (21–23). Operant chambers (#80004, Lafayette Instrument Co., Lafayette, IN) measuring 35.6 cm (length) × 27.9 cm (width) × 33.7 cm (height) are each housed within a sound- and light-attenuating cubicle (#83018DDP Lafayette Instrument Co., Lafayette, IN). Each operant chamber is outfitted with a touch-sensitive, 12″ LCD flat screen (EloTouch, Menlo Park, CA). The chamber floor is covered with a clear Plexiglas sheet to facilitate mobility. The touchscreen and a single houselight are located at one end of the chamber, and a tone generator, a pellet receptacle, and a pellet dispenser, at the other end (see Fig. 3a). The pellet dispenser delivers 45 mg dustless sucrose pellets (BioServ, Frenchtown, NJ). Stimulus presentation, reward delivery, and contingencies are controlled by

90


Fig. 3. Visual discrimination and reversal learning (VDRL) task. (a) An operant chamber is modified to accommodate a touchscreen (this setup is used for testing mice). Animals are required to nose poke the touchscreen on one end of the chamber, and procure a pellet on the opposite side of the chamber. (b) Equiluminant stimuli used in discrimination and reversal learning. Adapted from Izquierdo et al. 2006 Behav Brain Res.

custom-designed software developed for use in nonhuman primate experiments (Ryklin Software, Inc.) but adapted for assessment in the rodent. These materials as well as the equiluminant stimuli are the same as those reported in a previous study (13). There are now, however, commercially available touchscreenequipped operant chambers (“Bussey Touchscreen Chambers”) and software for testing mice and rats (Lafayette Instrument Co., Lafayette, IN).

3. Methods 3.1. Food Restriction

Dietary restriction is used as a motivator to enhance the pursuit of the reinforcer (food) in rats; a sated or overfed rat is not likely to engage in motivated behavior to procure food rewards. The restriction level is commonly no lower than 85% of a rat’s free feeding weight (this is typically deemed an acceptable level by most Institutional Animal Care and Use Committees). Food rewards vary widely in animal tasks. The following can be used as a guide for behavioral studies in the rat.

3.1.1. Establishing Free-Feeding, Baseline Weights

Rats that are food restricted should have free access to water in their home cage at all times. For rats on “rest” (animals not currently being tested, with free access to food), a baseline is established by taking their weights after 1 week or more of free feeding and at least 1 week after their arrival to the vivarium from the supplier. If rats are bred in-house, they should be at least 190 g to undergo a food-restricted diet. An established baseline weight serves as the highest weight from which to calculate the 85% “minimum” weight

5


91

(see the next section for details). For behavioral studies requiring reward-driven responses, rats should be individually housed in order to carefully monitor food consumption and weight. 3.1.2. Establishing 85% Free-Feeding Weight

In the event that a rat reaches a new highest weight, this number should be used to calculate the new 85% body weight. This occurs frequently with younger rats ( 0.05 for effects of session). (b) Depiction of unstable performance across a five-session span ( p < 0.05 for main effect of session).

other confounding factors that may influence performance and promote enhanced omissions or slight behavioral biases. However, this approach may not be desirable when using within-subjects experimental designs (see below). 5. In order to compare two groups of subjects, use a mixed-design repeated measures ANOVA with group as the between-subjects factor, and trial block (risk of punishment) as the repeated measures factor. 3.5. Repeated Measures Treatment Procedure (WithinSubjects Designs)

1. Prior to any treatment (e.g.—acute systemic drug administration, intracranial microinjections, acute behavioral manipulations), it is critical that all groups of rats have achieved stable performance in the Risky Decision-Making Task. If performance is unstable, session-to-session fluctuations in behavior could either promote a false-positive effect (type 1 error) or mask an effect of treatment (type 2 error). 2. We use systemic amphetamine administration as an example of a treatment regimen with four different conditions. For the first session, each rat is given one of three doses of amphetamine (0.33, 1.0, 1.5 mg/kg) or 0.9% saline vehicle prior to testing. In the second session, each subject performs the Risky Decision-Making Task with no treatment. This pattern continues for a total of eight consecutive sessions, with the order in which the treatments are administered counterbalanced across subjects. 3. After this eight-session experimental schedule, data are available from four treatment sessions (sessions 1, 3, 5, and 7) and four baseline sessions (sessions 2, 4, 6, and 8). The four treat-

10

Risky Decision Making in Rodents

173

ment sessions can be compared using a repeated measures analysis (trial block X treatment) to detect any effects of treatment on risky decision making. The four baseline sessions should also be compared using a similar analysis. This latter test is used to determine whether treatment exerted any longterm effects on behavior that outlasted the individual treatment sessions (i.e.—“carryover effects”). If an effect of session is revealed with this analysis, performance underwent a “baseline shift,” and therefore any effects of treatment may be confounded. If a treatment produces a significant baseline shift, the simple repeated measures statistical design described above may not be an effective method of assessing differences between doses/treatment parameters, and alternative analyses may be necessary (e.g.—normalizing performance in each treatment session to the level of performance in the immediately preceding baseline session). To avoid such confounds, additional baseline sessions may be used between the treatment sessions. 4. If multiple rounds of experimental manipulations are to be performed, rats should be tested for a minimum of five untreated baseline sessions in between each treatment schedule. These five sessions should be analyzed for stability (see Subheading 3.4); if performance is not stable in five sessions, baseline testing should continue until stability is achieved (see Note 8).

4. Notes 1. As currently configured by the factory, the mounting position for the photobeam hardware on the Coulbourn Instruments food trough places the photobeam farther back in the trough than is optimal for detecting head entries. To circumvent this problem, we drill holes in the sides of the food trough to allow placement of the photobeam as close as possible to the front (entry) of the trough, and use superglue to affix the photobeam hardware in place on the sides of the trough. 2. In our experience, the grain-based pellets are readily consumed by food-restricted rats, and are easier to work with than sucrose pellets as they do not as readily absorb moisture and become sticky when exposed to air. They do produce dust that can clog pellet dispensers if not cleaned regularly; however, dispensers can be cleaned easily with a compressed air duster (such as that used for cleaning computer components). 3. These shaping procedures were adapted from refs. 6, 7, and can be used for any two-choice decision-making task (8, 9). 4. The identity and positions of the response levers should be balanced such that for half of the test chambers the left lever is the

174

N.W. Simon and B. Setlow

“large risky reward” lever, and for the other half of the chambers the right lever is the “large risky reward” lever. This can be accomplished most easily in the Coulbourn Instruments system at the hardware level by specifying the same set of inputs/outputs to correspond to the “large risky” and “small safe” lever across all test chambers at the software level, but alternating the left/right configuration of which lever is actually plugged into which set of connections across chambers (e.g.—so that “switch 1” at the software level controls either the left or right lever at the hardware level, depending on the chamber). This ensures that factors, such as proximity to the door of the test chamber, do not bias preference for one or the other levers. In addition, it is important to counterbalance the subjects in different treatment groups across the two different types of chambers (e.g.—so that rats in a given treatment condition do not all have the “large risky” lever on the right). 5. Different strains of rat seem to shape more rapidly than others. For example, in our experience, Long–Evans and SpragueDawley rats typically acquire lever pressing for food reward at a faster rate than Fischer 344 rats (unpublished observations, Simon & Setlow). 6. While a 0.35-mA footshock typically produces a more robust discounting curve than other intensities (9), there is considerable variability between rats in sensitivity to shock in this task. For example, some cohorts of rats may be insensitive to 0.35mA shock, in which case the shock intensity can be increased in small increments (no greater than 0.05-mA increase between sessions). Conversely, some cohorts of rats may avoid this shock intensity, which would require a reduction of intensity between sessions. Note that the 0.35-mA shock value recommended here is optimal for Long–Evans rats; a higher or lower intensity may be optimal for other rat strains. Before performing any experimental manipulations, it is recommended to run a small group of pilot subjects in order to determine ideal footshock parameters, as there are differences in shock apparatus, environment, and rat strain/age that may influence shock sensitivity. Importantly, when determining ideal shock intensity, we have found that behavioral performance is typically more consistent if the intensity is begun at a low point and raised until an optimal point is determined (rather than beginning at a higher intensity and lowered). 7. It is critical to monitor each rat’s task performance carefully on a daily basis. Significant changes in the choice distribution from one day to the next (or a reduction in the overall number of choices) can indicate a problem, such as a clogged feeder, inoperable lever, or rats placed in incorrect test chambers.

10

Risky Decision Making in Rodents

175

8. After extended periods of testing, rats often demonstrate some degree of habituation to the shock. This is behaviorally manifested as a gradual increase in preference for the risky reward across multiple sessions. If this occurs, it may be necessary to increase the footshock intensity by 0.05 mA prior to any subsequent treatment regimen. After any shifts in intensity, it is critical to obtain behavioral stability over a five-session period before conducting further experiments. References 1. Bechara, A., Dolan, S., Denburg, N., Hindes, A., Anderson, S.W., and Nathan, P.E. (2001) Decision-making deficits, linked to dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia. 39, 376–389. 2. Drechsler, R., Rizzo, P., and Steinhausen, H.C. (2008) Decision-making on an explicit risktaking task in preadolescents with attentiondeficit/hyperactivity disorder. J Neural Transm. 115, 201–209. 3. Ernst, M., Kimes, A.S., London, E.D., Matochik, J.A., Eldreth, D., Tata, S., et al. (2003) Neural substrates of decision making in adults with attention deficit hyperactivity disorder. Am J Psychiatry. 160, 1061–1070. 4. Ludewig, K., Paulus, M.P., and Vollenweider, F.X. (2003) Behavioural dysregulation of decision-making in deficit but not nondeficit schizophrenia patients. Psychiatry Res. 119, 293–306. 5. Evenden, J.L. and Ryan, C.N. (1996) The pharmacology of impulsive behavior in rats: the effects of drugs on response choice with varying delays of reinforcement. Psychopharmacology (Berl). 128, 161–170. 6. Cardinal, R.N., Robbins, T.W., and Everitt, B.J. (2000) The effects of d-amphetamine, chlordiazepoxide, α-flupenthixol and behavioural manipulations on choice of signalled and unsignalled delayed reinforcement in rats. Psychopharmacology (Berl). 152, 362–375. 7. Winstanley, C.A., Dalley, J.W., Theobald, D.E., and Robbins, M.J. (2003) Global 5-HT depletion attenuates the ability of amphetamine to decrease impulse choice on a delay-discounting

task in rats. Psychopharmacology (Berl). 170, 320–31. 8. Simon, N.W., Mendez, I.A., and Setlow, B. (2007) Cocaine exposure causes long term increases in impulsive choice. Behav Neurosci. 121, 543–9. 9. Simon, N.W., Gilbert, R.J., Mayse, J.D., Bizon, J.L., and Setlow, B. (2009) Balancing risk and reward: a rat model of risky decision making. Neuropsychopharm. 34, 2208–17. 10. Van Den Bos, R., Lasthius, W., Den Heijer, E., Van Der Harst, J., and Spruijt, B. (2006) Toward a rodent model of the Iowa gambling task. Behav Res Methods. 38, 470–478. 11. Zeeb, F.D., Robbins, T.W., and Winstanley, C.A. (2009) Serotonergic and dopaminergic modulation of gambling behavior as assessed using a novel rat gambling task. Neuropsychopharm. 34, 2329–2343. 12. Jentsch, J.D., Woods, J.A., Groman, S.M., and Seu, E. (2010) Behavioral characteristics and neural mechanisms mediating performance in a rodent version of the Balloon Analog Risk Task. Neuropsychopharm. 35, 1797–806. 13. Cardinal, R. and Howes, N. (2005) Effects of lesions of the nucleus accumbens core on choice between small certain rewards and large uncertain rewards in rats. BMC Neurosci. 6, 37. 14. Negus, S. (2005) Effects of punishment on choice between cocaine and food in rhesus monkeys. Psychopharmacology (Berl). 181, 244–252. 15. Talmi, D., Dayan, P., Kiebel, S.J., Frith, C.D., and Dolan, R.J. (2009) How humans integrate the prospects of pain and reward during choice. J. Neurosci. 29, 14617–14626.

sdfsdf

Chapter 11 Open Space Anxiety Test in Rodents: The Elevated Platform with Steep Slopes Abdelkader Ennaceur Abstract This report describes a behavioral test protocol for assessing anxiety in mice and rats in single or multiple sessions. The test is based on exposure of animals to an open-space elevated platform with suspended steep slopes attached on two opposite sides. In this test, all animals cross frequently onto and spend more time in the areas adjacent to slopes than in the areas adjacent to a void space. Balb/c mice (albinos) were shown consistently to be more anxious than CD-1 mice (albinos), c57/Bl6J and c57/Bl6N (pigmented) mice; they do not cross onto the slopes. When Balb/c mice are treated with amphetamine or diazepam, the number of crossings on the platform is significantly increased but only diazepam-treated mice do cross onto the slopes. In the presence of a protected space on the platform, the behavior of c57/Bl6J compares to that of Balb/c mice; they stop crossings onto the slopes and demonstrate avoidance response. Unlike the current existing tests, the present open-space anxiety test demonstrates reliable and consistent results with strong construct and discriminant validity. It provides unequivocal measures of fear-induced anxiety, which are not confounded with measures of fear-induced escape/avoidance responses, hyperactivity or impulsive responses. Key words: Fear, Avoidance, Anxiety, Anxiolytic, Benzodiazepines, Psychostimulant, Amphetamine

1. Introduction When exposed to an unfamiliar environment, animals do express fear and may experience anxiety, particularly to open spaces and novelty. This procedure has been exploited in various behavioral settings to assess anxiety in animals using an open-field (1, 2), a light/dark box (3), and elevated open/enclosed arm mazes (4–7). In these tests, animals are provided with a protected space, alongside an unprotected space, and most strains of mice and rats, if not all, demonstrate strong preference for the protected space that they can avoid from or escape to. However, fear-induced escape or avoidance is different from fear-induced anxiety (8–10).


177

178

A. Ennaceur

Fig. 1. Configurations of the areas of the elevated platform with steep slopes. (a) Fear-induced anxiety test; (b) fear-induced avoidance/escape test (see Note 1).

In the former, avoidance or escape response can terminate the feeling of fear while in the latter the drive to escape or avoid is compounded with the drive to approach the source of potential threat, and these intermingled conflicting drives promote and maintain the feeling of fear. Hence, it remains questionable whether the preference demonstrated by animals for the walls and corners of an open field, enclosed arms of elevated mazes, and the dark compartment of a light–dark box provides a valid and reliable measure of anxiety. Anxiety can be expressed in a variety of behavioral settings, though not all of these can provide specific measures of this construct. The main issue here is not that a behavioral test does or does not involve anxiety, but how a behavioral test can provide measures of fear-induced anxiety that are not confounded with measures of other behavioral responses to the experimental settings of a test (construct validity), and that these can be clearly discriminated from measures of fear-induced escape or avoidance responses (discriminant validity). In the present report, we describe a test protocol for assessing anxiety in mice and rats using an elevated platform with steep slopes attached on two opposite sides (Fig. 1a). This test provides unequivocal measures of fear-induced anxiety, which are distinct from measures of fear-induced escape/avoidance response. The validity of this test is supported by the following evidence. 1. When exposed to an elevated platform, all animals try to escape and a large number do jump onto the ground if it is not sufficiently raised from the ground. At 75 cm height, animals do not jump onto the ground but do “consider” crossing onto lowered steep slopes. Using both albinos (Balb/c and CD-1) and pigmented (C57/Bl6J, C57/Bl6N) strains of mice, we

11

Open Space Anxiety

179

demonstrated that all mice spend more time in the outer area of the platform than in the inner and central areas, and in the areas adjacent to slopes than in the areas adjacent to a void space (11). This indicates that all mice sense the presence of the slopes and all mice appear to “consider” the option of crossings onto the slopes (discussed later and illustrated in Fig. 5). 2. Both the platform and the slopes represent an anxiogenic environment which animals are forced to explore while trying at the same time to avoid and escape from. Animals which do cross onto the slopes, particularly those that do cross frequently onto and spend longer time on the slopes, are considered less anxious than the one which do remain the entire session on the platform. These animals appear to take risks by crossings onto the slopes while anxious animals remain undecided, spending most of their time on the areas adjacent to the slopes. We demonstrated consistently that Balb/c mice are unable to take risks; they do not cross onto the slopes while CD1, c57/Bl6J, and c57/Bl6N mice do cross onto the slopes (11). 3. Balb/c mice do not cross onto the slopes even after repeated exposures to the test but do continue to explore frequently and spend a large amount of time on the areas adjacent to the slopes (11–13). The total number of crossings onto different areas of the platform and the time spent on the areas adjacent to slopes are comparable between sessions, which indicates that repeated exposures to our open space test apparatus continue to induce fear and maintain anxiety in Balb/c mice (discussed later and illustrated in Fig. 7). 4. In the presence of a protected space—a cylinder in the centre of the platform (see Fig. 1b)—c57/Bl6J mice appear to behave like Balb/c mice; they stop crossing onto the slopes. This protective space significantly reduces the number and duration of entries onto the outer area and increases the time spent in the inner and central areas in both c57 and Balb/c mice (11). The behavior of c57 mice demonstrates clearly that the presence of a protected space promotes the drive to avoid and reduces the drive to approach the source of potential threat. 5. Both diazepam-treated (12, 13) and amphetamine-treated (12) Balb/c mice demonstrated a large, significant increase in the number of crossings on the surface of the platform, but only the former and none of the latter crossed onto the slopes. The number of crossings on the platform in amphetaminetreated mice was significantly higher than that of diazepamtreated mice. Hence, the test configuration prevents a false positive from a drug that induces hyperactivity or impulsivity.

180

A. Ennaceur

2. Materials 2.1. Animals

1. Laboratory mice of most strains, transgenic and knockout mice lines. We tested so far four strains of mice (Balb/c, C57/Bl6J, C57/Bl6N, CD-1(ICR)). Balb/c mice display strong anxiety while C57/Bl6J, C57Bl/6N, and CD-1 mice display low anxiety. Therefore, if screening for an anxiolytic treatment, one has to select Balb/c mice; otherwise, if a treatment is expected to induce anxiety, one has to select c57 or preferably CD-1 mice strains. I recommend including a control group from the least anxious strain when screening for an anxiolytic effect of a treatment and a control group from the most anxious strain when screening for an anxiogenic effect (when possible). 2. The duration of a test session is 12 min (see Subheading 3.3); hence, four animals can be tested in 1 h. It is safe for one person alone to test 24 animals a day. Two people are required when an experiment involves drug treatments. 3. Grouped or individually housed. If grouped, maintain equal number of mice per cage and no more than five mice per cage. 4. In the colony room, avoid unequal light exposure of animal cages. The upper shelf of a rack holding the cages can be occupied with plastic cages filled with clean sawdust.

2.2. Test Apparatus

1. The apparatus is described in the illustration below (see Figs. 1 and 2). It consists of a platform (80cm × 80 cm wide) which is elevated 75 cm from the ground. It is made of grey opaque PVC (0.5 cm thick). Steep inclined panels (80 cm × 25 cm) made of rigid wire mesh are attached on two opposite sides of the platform. From the platform, the angle of depression of each slope is about 77° downward. The slopes need to be visible from the top of the platform.

Fig. 2. Illustration of the settings of the open-space elevated platform with steep slopes.

11

Open Space Anxiety

181

2. The platform is divided into a central area covered with a white tile (16 cm × 16 cm wide and 0.4 cm thick), an inner area surrounding the central area (16 cm wide and 2,048 cm2), and an outer area (16 cm wide and 4,096 cm2). The outer area is further divided into areas adjacent to the slopes (2,048 cm2) and areas adjacent to the void space (2,048 cm2) (see Fig. 1). 2.3. Test Components

1. One grey PVC sheet (80 cm × 80 cm width and 0.5 cm thick). This forms the platform of the test apparatus (see Note 1). 2. Two stainless steel rigid grid panels, 80 cm × 25 cm. Grid holes 0.8 cm wide. These form the steep slopes on two opposite sides of the platform. The slopes can be attached to the side of the platform using hinges with removable pins; hence, the slopes can be detached and taken away for washing. 3. Four table legs: These hold the platform elevated by about 75 cm from the ground. They need to be fixed far from the platform edges so that they cannot be reached by mice. It is preferable to have telescopic legs supporting the table in order to experiment with the platform at different heights. 4. Stainless steel rigid or hard plastic L bars: These form ledges (1 cm wide) on the left, right and bottom sides of the slopes. They would prevent animals going beneath the grid slopes (see Note 2). 5. Two stainless steel rigid square bars: These cross beneath the platform and connect the opposite slopes from each side of the table legs. The bars are screwed against the table legs. These would prevent the slopes from swinging and keep them at a selected angle (see Fig. 2). 6. White tile: Mice are released from this place which is 16 cm × 16 cm wide and 0.5 cm thick (see Note 3). 7. Grey PVC tube: A cylindrical pot can be used to provide a refuge (protected space) for animals to escape to or avoid from (16–18 cm diameter and ³15 cm height). Animals should be able to move freely in and out through three to five access doors (6 cm × 6 cm wide).

2.4. Test Utilities

1. A stopwatch or a timer. It should be kept outside the test room or remove the alarm sound. 2. A camera with wide-angle lens needs to be hooked to the ceiling. The camera needs to be centered above the white tile so that both slopes are visible. In order to achieve a correct view of the slopes, an object of the size of a mouse can be placed at the lower end of each slope and then the camera is adjusted until the objects are in view. CCTV cameras are very cheap and do a great job and there is no need for more than one camera (see video clips online http://www.ennassor.com/index.html).

182

A. Ennaceur

3. Video recording: VCR can be used to record behavior. We used this option in a large number of our experiments. It is not a convenient option as during scoring an observer has to sit in front of a TV monitor displaying the test session and a computer monitor displaying the event logging program. 4. DVD recording: This is the most convenient option. It is prudent to have a DVD recorder with a large hard drive and that the whole-day experiment is recorded first on the DVD recorder before being transferred onto an external large hard drive or DVD disks for archiving. It is easy for DVD media to be damaged. Do not delete your behavioral recording from the DVD hard drive until you have transferred it to a large, external hard drive which can be read on your computer or that you have made triplicate copies on DVDs. Use doublelayer DVD media. A good-quality video DVD records about 6–8 h and high-quality video DVD records about 4 h on a double-layer DVD (see Note 6). 5. Computer program for automated scoring: Event logging computer program is required to record the number, duration, and latencies of entries onto the different areas of the test apparatus (see ref. 14). 2.5. Test Environment

1. Ambient light—no need for strong light. It is preferable to have the same light as in the animal-holding room (see Note 4). 2. A curtain surrounds the test apparatus. It is kept at about 50 cm from the apparatus. Use unicolored heavy curtain that falls and remains straight when released. 3. It is preferable that only depth perception rather than visual cues from the ground determines the behavior of animals in the test apparatus (see Note 9). In our experiments, the floor surface within the perimeter of the curtain was almost the same color as the platform.

3. Methods 3.1. Acclimation

1. Animals obtained from external source as well as those bred in-house need to be left undisturbed for at least 1 week after being allocated to individual or group-holding cages. 2. Transport animals on the day of testing from the animal colony to a waiting space 30–45 min before testing.

3.2. Behavioral Testing

1. Test session 12 min. Do not use session duration shorter than 6 min as it takes about 3 min for some animals to start crossing onto the slopes. I strongly recommend a 12-min session duration. Mice can be tested in single or multiple sessions, one session

11

Open Space Anxiety

183

a day. The selection of the number of sessions depends on the aim of the research project (see Note 5). We demonstrated that anxiety is maintained over five sessions in Balb/c mice without signs of habituation. 2. Use a wet cloth with antibacterial solution followed by 90% ethanol to clean the surface of the platform and the slopes before the introduction of the first mouse even if the test apparatus was cleaned at the end of a previous experiment. Dry with soft paper. The same cleaning procedure applies to a cylinder that provides a protective space if used. 3. Start DVD or VCR recording just before transporting animals to the test room. 4. Use a small blackboard or whiteboard. Write down with a dry, thick pen the date of the day of experiment (DDMMYY), display to camera, and then record it for 10 s. Thereafter, use the board to write the identification code of each mouse before the test session starts. The date can be left and the animal identification added beneath it. Make sure that the board is clearly readable on a screen monitor (see Note 6). 5. Mice can be weighted in a small plastic pot, which is transported to the test room, and the pot is gently tilted over the white tile. The same procedure applies if a cylinder occupies the central area of the platform (see Note 7). 6. After a mouse is released on the tile, the timer is started. Move slowly and no rush. The session is 12 min but the video recording cannot be exactly 12 min; it has about 15–30-s extra time that is ignored when scoring behavior. 7. The experimenter has to move away behind the curtain. It is preferable (not a requirement) that the experimenter stands outside the test room to avoid any influence on the behavior of a mouse. 8. DVD recording should be paused after you remove animals from the test apparatus. Do not pause a VCR as the tape can roll back automatically and may lead to deleting a few seconds from the previous recorded test session. 9. Clean the surface of the platform and slopes with soft paper first to remove droppings and urine, and then use a wet cloth with antibacterial solution followed by 90% ethanol before the introduction of the next mouse. Dry with soft paper. The same cleaning procedure applies to the cylinder if used. 3.3. Behavioral Scoring and Data Analysis

1. Fix a transparent plastic sheet on a TV or video screen monitor. Draw clearly the visible perimeters of the areas of the platform on the sheet. Use a code name for each area (central area = X; inner area = I; slopes, left = LS and right = RS; area adjacent to

184

A. Ennaceur

slopes, left = LAS and right = RAS; areas adjacent to void, back = BAV and front = FAV). Later during data analysis, one can combine LS with RS (S), LAS with RAS (AS), and BAV with FAV (AV). 2. For manual scoring using an event log computer program, one needs to feel comfortable and fluent with a keypad or a keyboard. Exercise scoring method on three or four randomly selected video clips. 3. The recording of the behavior of mice is based on entries into defined areas of the apparatus. An entry is recorded whenever a mouse crosses with all four paws into an area (see Note 8). 4. Behavioral analysis is based on the number of entries, duration of entries, and latency of first entry into the inner area, the area adjacent to slopes, the areas adjacent to void, and onto the slopes. An additional measure is the total number of crossings on the platform before first entry onto a slope. Most of these parameters are required for the interpretation of the results of an experiment and make the present test self-sufficient to account for the effects of an experimental manipulation on anxiety and sensory motor functions (see Subheadings 3.3 and 4 below). 5. For mice which did not cross onto a slope, the latency of first entry is recorded as the full duration of a session. They are also attributed the highest number of crossings before first entry onto a slope that was recorded from any mouse on that day of experiment. 6. In the case of slope entries, it is possible for a mouse to cross onto a slope and remain there for the remaining duration of a test session. An animal that does not return to the platform after its first entry onto a slope should be considered as anxious as the one that does not enter the slope at all. An entry is recorded only when a mouse returns to the platform. If such criterion is not introduced, this mouse could be considered the least anxious compared to a mouse that moved frequently back and forth between the slopes and the platform. It would record the highest duration of entry onto the slopes, if this single entry occurred early in a test session (see Notes 9 and 10). 7. One can divide a 12-min session in three or four bins and examine how exploratory activity evolves throughout a test session. 8. Differences between groups for each measurement are examined for significance with the appropriate statistical test. 9. Within-group comparisons on number and duration of entries between two areas of the platform need to be examined with paired student t-test (two-tailed) or Wilcoxon matched-pairs

11

Open Space Anxiety

185

signed-ranks test as appropriate. These areas are of equal surface (2,048 cm2): (a) Inner area vs. areas adjacent to the slopes (b) Inner area vs. areas adjacent to the void space (c) Areas adjacent to the slopes vs. areas adjacent to the void space 3.4. Behavioral Data Interpretation

1. The number of crossings onto and time spent on the slopes and the latency of first entry onto are used to indicate differences in anxiety response (see Note 10). C57/Bl6J, C57Bl/6N, and CD-1 mice display low anxiety (11); they cross onto the slopes. Balb/c mice display strong anxiety; they avoid the slopes (11–13). When treated with diazepam (0.5, 1 and 3 mg/kg i.p.), Balb/c mice do cross frequently onto the slopes and spent a large amount of time on the slopes (Fig. 3a, b) (12, 13). They do not cross onto the slopes when treated with amphetamine (1, 2.5, 5, and 10 mg/kg i.p.) (12). 2. The total number of crossings on the surface of the platform gives some indications about motor activity though confounded with emotional responses. Diazepam and amphetamine increase dose dependently the number of crossings on the surface of the platform in Balb/c mice (12). Amphetamine induced a significant increase in motor activity compared to diazepam (Fig. 4a, b). 3. The duration of entries onto the areas adjacent to slopes compared to duration of entries onto the areas adjacent to a void space helps determine whether animals have been able to sense the presence of the slopes (see Note 11). All animals that we have tested so far demonstrated longer time spent in the former than in the latter (Fig. 5a, b) (11–13).

Fig. 3. Diazepam increased the number of crossings (a) onto and time spent (b) on the slopes in Balb/c mice. Saline-treated mice did not cross onto the slopes.

186

A. Ennaceur

Fig. 4. Both amphetamine (a) and diazepam (b) increased the total number of crossings on the surface of the platform in Balb/c mice. The number of crossings in amphetamine-treated mice (5 and 10 mg/kg) is almost double of that of diazepam-treated mice (0.5, 1, and 3 mg/kg), but none of the amphetamine-treated mice crossed onto the slopes (see ref. 7).

Fig. 5. (a) The number of crossings indicates preference for the areas adjacent to slopes in C57/Bl6J and CD1 mice; (b) the time in the areas adjacent to slopes indicates significant preference for these areas than for the areas adjacent to the void space in Balb/c, C57/Bl6J, and CD1 mice. Note here that the apparent low number of crossings and time spent in AS and AV for both C57/Bl6J and CD1 mice are due to the fact that these strains of mice did explore the slopes while Balb/c mice spent the entire session on the platform (see Note 12).

4. Time spent in the central and inner areas is mostly useful when assessing avoidance response (11) or when testing animals for anxiety in several sessions (7, 8, 12) (see Note 12). 5. Fear-induced avoidance vs. fear-induced anxiety: When exposed to an open space, both anxious and nonanxious strains of mice cross frequently onto and spend more time in the outer areas than in the inner + central areas (7, 8, 12) while in presence of a protected space they spend more time in the central + inner areas than in the outer areas (Fig. 6a, b). In addition, the presence of a protected space on the platform

11

Open Space Anxiety

187

Fig. 6. The presence of a protected space reduces significantly the number of crossings on the surface of the platform. It also reduces the number of crossings (a) and time spent (b) in the outer areas and time spent in the inner + central areas of the platform in both C57/Bl6J and Balb/c mice. These indicate that both strains of mice show strong preference for the protected space.

Fig. 7. Time spent by c57/Bl6J (a) and Balb/c (b) mice in the areas adjacent to slopes (AS), in the areas adjacent to a void space (AV), and in the inner (INN) and central (CTR) areas over three test sessions. Note here that the apparent low amount of time spent in AS and AV for C57/Bl6J mice is due to the fact that these mice did venture onto the slopes while Balb/c mice remained during the entire session on the platform (see Notes 11 and 12).

appears to discourage the least anxious strain of mice to cross onto the slopes (11). 6. Repeated testing: If habituation does occur, the time spent in the inner and central areas is likely to increase while the number of entries and duration of entries onto the areas adjacent to slopes and to areas adjacent to a void space are likely to decrease. But this is not true for all strains of mice and habituation may not be apparent in all these test parameters (Fig. 7a, b).

188

A. Ennaceur

4. Notes 1. For rats, the size of the platform is 100 cm × 100 cm and the width of each area is 20 cm instead of 16 cm (tile 400 cm2; inner area 3,200 cm2; outer area = 6,400 cm2; areas adjacent to slopes 1,600 × 2; areas adjacent to void 1,600 × 2). The dimensions and the angle of declination of the slopes remain the same as for mice. Escape or avoidance responses can be assessed using a cylindrical pot (20–22 cm diameter, ³25 cm height), which provides a protected space in the central area. Animals should be able to move freely in and out through three or five access doors (9 cm × 9 cm wide; for large rats, one can increase the width and reduce the number of access doors to three). 2. The width of the ledge on this side should be no larger than 1 cm. The presence of a wide ledge (>2 cm) would encourage mice to remain on it for a significant amount of time. It also provides mice a surface from which they can jump onto the ground. Animals seem unable to jump from a steep slope. Falls from the slopes are likely to indicate sensory-motor problems. 3. Comparisons of measures of entries (frequency and duration of investigation) into one area of an open field with another area imply that the two areas are well-delineated and differ in one dimension only. For example, an outer area would differ from the inner area by a certain distance from the edge of the field but should not differ in surface size, texture, or color. Hence, if investigation time is longer in the former, it can be attributed to the edges of the field or walls alone. A large number of studies report that animals avoid the central area of an open field, and this is used as an index of anxiety. However, unlike edges and corners of a spatial setting, the central area has no perceptible physical boundaries. It has a very small surface size and it is not distinct from the inner area. Hence, it is not surprising that only very few brief accidental crossings are recorded in this area (see refs. 14, 15). A tile provides visual and tactile information that would attract animal attention; it promotes an increase in the number of entries and time spent in the centre of an open field. Measures of entries in this area cannot be compared to entries into other areas, which have a larger surface, but they indicate whether animals do really avoid this central area (see ref. 15). 4. Concerns about standardization: The main requirement is the apparatus design and settings which need to be kept as specified. Handling, acclimation, housing maintenance, and illumination are standard procedures that one has to maintain in own lab. However, for various reasons, it is unlikely that the same

11

Open Space Anxiety

189

standard can be met for every experiment in the same laboratory and between experiments from different laboratories. One must bear in mind that all forms of behaviors take place under a fluctuating signal/noise ratio; therefore, a reliable behavioral test should be able to cope with such fluctuations and detect a signal from the noise. Hence, the results of a behavioral test should not be affected by changes to these factors, which are shared by all animals from the same experiment unless one of these factors is explicitly manipulated and varies between groups of animals. The main requirement is that animals should be tested in an environment that is not dramatically different from their housing conditions (i.e., lighting, temperature, and noise level) and that the experimenter is used to handling mice and rats (i.e., no petting and no chasing). 5. One session is sufficient in drug screening for anxiolytics or in behavioral phenotyping of mice. Confirmation and consolidation of the results can be performed in three sessions. In research projects on tolerance, sensitization, and withdrawal, animals can be tested in numerous sessions. We have performed the test in six sessions (13), but it can be performed for much longer. 6. One may need to recall or recognize things weeks, months, or even years later. Recording directly or archiving a 1-day experiment can take more than one DVD, which needs to be identifiable by the date of the experiment (DDMMYY) and the set of animals that it holds on record (id. of first x and last y animals). Use indelible pen marker and write down on each DVD label: DDMMYY; animal id. x and y. You can add other details that you feel appropriate. All recorded or archived DVDs need to be referenced in the lab book. 7. When released manually in the central area, some animals appear to run away immediately from the experimenter while others appear to freeze in place. This affects the reliability of the latency measures of first entry onto the inner and outer areas. The use of a small plastic pot for releasing mice help to overcome this issue. This is not possible with rats that have to be released manually. The experimenter needs to be welltrained in handling rats. It is not acceptable to carry an animal by the tail from its cage to the test apparatus; this is stressful for animals. All animals should be treated, held, and released in the same way. The experimenter must keep a neutral attitude toward all animals. 8. A crossing is recorded only when all four paws are inside an area. Use this criterion very strictly and adhere to it throughout the recording of the observed behavior. Draw the borders of all predefined areas with bright black or bright white-colored thick lines (3 mm). If a mouse seems to move from an area A and appears to investigate an area B with not all four paws inside the

190

A. Ennaceur

area B, this mouse has not crossed into area B and remains recorded in area A. 9. Most mice and rats do jump onto the ground when the platform is raised by 50 cm but not when it is raised by about 75 cm. We did not observe any mouse or rat falling from the platform at this height, except in an experiment with MK-801 (at 0.2 mg/kg i.p.) which induced uncoordinated, unsteady locomotion (see ref. 16). Hence, jumping or falling from the platform may occur in some cases. If a manipulation does induce jumping onto or falling on the ground, the experiment cannot be continued with the group of animals displaying this behavior. Lower the doses if using drugs. One can prevent animals from sliding from the platform by using a ledge (not higher than 0.5 cm height) on each side adjacent to the void space. Do not use ledges on the sides adjacent to the slopes; animals should have free, easy access to the slopes. Keep the platform at 70–75 cm height, and do not raise it further. At 100 cm height, the test is more anxiogenic (see ref. 11) and it is likely to cancel its sensitivity to experimental manipulations. Because of animal welfare regulations, it is advised that a soft carpet (polyethylene foam map about 3–5 cm thick) is laid on the ground beneath the slopes. It is preferable that it is grey or dark unicolor, and covers all the visible areas of the floor within the curtain perimeter that surrounds the test apparatus. 10. Both the platform and the slopes are anxiogenic. Without slopes, it is difficult to determine which area of the platform would discriminate between anxious and nonanxious animals. Measures of crossings onto the slopes provide a solution to this problem. The slopes appear to provide an escape route that the least anxious animals would explore. All animals have equal chances to cross onto the slopes or the void space; they are required to discriminate between these two areas. Hence, reduced anxiety rather than hyperactivity, impulsivity, or impaired sensory functions can account for the crossings onto the slopes. Anxious animals that do cross onto a slope because of hyperactivity, impulsivity, or impaired sensory functions are unlikely to make more than one crossing and are highly likely to stay on a slope for the remaining duration of the test session. 11. Hyperactivity may prevent observation of differences between areas adjacent to slopes and areas adjacent to a void space, and between these areas and the inner area. 12. Pay attention to the data values of crossings onto separate or combined areas of the platform when comparing between animals that did cross onto the slopes and animals that did not. Crossings onto the slopes affect these values, particularly when mice spend a significant part of a test session on the slopes (see Fig. 5).

11

Open Space Anxiety

191

References 1. Denenberg, V.H. (1969) Open-field behavior in the rat: What does it mean? Annals of the New York Academy of Sciences 159, 852–859. 2. Walsh, R.N, Cummins, R.A. (1976) The Open-field test: a critical review. Psychol. Bull. 83, 482–504. 3. Crawley, J.N., Goodwin, F.K. (1980) Preliminary report of a simple animal behaviour for the anxiolytic effects of benzodiazepines. Pharmacol Biochem Behav 13, 167–170. 4. Graeff, F.G., Ferreira Netto C., Zangrossi H. (1998) The elevated T-maze as an experimental model of anxiety. Neurosci. Biobehav. Rev. 23, 237–246. 5. Handley, S.L., Mithani, S. (1984) Effects of a-adrenoreceptor agonists and antagonists in a maze-exploration model of ‘fear’-motivated behaviour. Naunyn-Schmeideberg’s Arch. Pharmacol. 327, 1–5. 6. Montgomery, K.C. (1955) The relation between fear induced by nove1 stimulation and exploratory behavior. J. Comp. Physiol. Psychol. 48, 254–60. 7. Shepherd, J.K., Grewal, S.S., Fletcher, A., Bill, D.J., & Dourish, C.T. (1994). Behavioural and pharmacological characterisation of the elevated “zero-maze” as an animal model of anxiety. Psychopharmacol. 116, 56–64. 8. Blanchard, D.C., Blanchard, R.J. (2008) Defensive behaviors, fear, and anxiety. In. Handbook of Anxiety and Fear, (Blanchard, R.J., Blanchard, D.C., Griebel, G., Nutt, D., Eds.), Elsevier, vol. 17, Ch. 2.4, pp. 63–79 9. Catherall, D.R. (2003) How Fear Differs From Anxiety. Traumatology 9, 76–92.

10. McNaughton, N., Zangrossi, H. (2008) Theoretical approaches to the modeling of anxiety in animals. In. Handbook of Anxiety and Fear, (Blanchard, R.J., Blanchard, D.C., Griebel, G., Nutt, D., Eds.), Elsevier, vol. 17, Ch. 2.1, pp. 11–27. 11. Michalikova, S., van Rensburg, R., Chazot, P.L., Ennaceur, A. (2010) Anxiety responses in Balb/c, c57 and CD-1 mice exposed to a novel open space test. Behav. Brain Res. 207, 402–417. 12. Ennaceur, A., Michalikova, S., van Rensburg, R., Chazot, P.L. (2010) Distinguishing anxiolysis and hyperactivity in a novel open space anxiety test. Behav. Brain Res. 207, 84–98. 13. Ennaceur, A., Michalikova, S., van Rensburg, R., Chazot, P.L. (2010) Tolerance, sensitization and dependence to diazepam in Balb/c mice exposed to a novel open space anxiety test. Behav. Brain Res. 209, 154–164. 14. Ennaceur A., Michalikova, S., Chazot, P.L. (2006) Models of anxiety: Responses of rats to novelty in an open space and an enclosed space. Behav. Brain Res. 171, 26–49. 15. Ennaceur A., Michalikova, S., Chazot, P.L. (2009) Do rats really express neophobia towards novel objects? Experimental evidence from exposure to novelty and to an object recognition task in an open space and an enclosed space. Behav. Brain Res. 197, 417–434. 16. Wu, J., Zou, H., Strong, J.A., Yu, J., Zhou, X., Xie, Q., Zhao, G., Jin, M., Yu, L. (2005) Bimodal effects of MK-801 on locomotion and stereotypy in C57BL/6 mice. Psychopharmacol. 177, 256–263.

sdfsdf

Chapter 12 An Animal Model to Study the Molecular Basis of Tardive Dyskinesia Mahendra Bishnoi and Ravneet K. Boparai Abstract Long-term treatment with haloperidol is associated with a number of extrapyramidal side effects. This limitation presents a marked therapeutic challenge. The present method (21 days administration of haloperidol, 5 mg/kg, i.p.) has been established to gain deeper insight into the molecular etiology (inflammation and apoptosis) of haloperidol-induced cellular death. In the present model, besides the corresponding increase in the vacuous chewing movements (VCMs), enhanced oxidative stress, there was a significant increase in cellular markers of inflammation and apoptotic protein (caspase-3), leading to cellular death. We also suggest that this model will be effective in preclinical testing of new chemical entities for the treatment of haloperidol induced tardive dyskinesia and related symptoms. Key words: Apoptosis, Caspase-3, Haloperidol, Inflammation, Oxidative damage, Tardive dyskinesia

1. Introduction Haloperidol, a typical member of conventional neuroleptics is thought to exert its clinical effects through striatal dopamine D2 receptors (1) and sigma1 receptors (2, 3). The neuroleptic efficacy of haloperidol in psychotic patients is compromised by its liability to cause acute and chronic extrapyramidal side effects including tardive dyskinesia (TD) (4–6). Although newer antipsychotics are devoid of extrapyramidal side effects but typical antipsychotics (haloperidol, chlorpromazine and fluphenazine) are enlisted in the most recent (14th) WHO model list of essential medicine. Hence, there is need to investigate the therapeutic options to treat side effects associated with them. Moreover, typical antipsychotics are less expensive than atypical ones. Keeping economic conditions of most of the countries in mind we cannot rule out usage of these


193

194

M. Bishnoi and R.K. Boparai

medications. Further, atypical antipsychotics are associated with several other side effects such as weight gain and diabetes mellitus. Tardive Dyskinesia syndrome has been characterized by vacuous chewing movements, tongue protrusions, and facial jerkings. It has been causally related to neuroleptic-induced increase in free radical production resulting in degeneration of susceptible neurons and finally death (7, 8). The exact mechanism of neuronal death is still unknown. Subacute (21 days) administration of haloperidol (1 mg/ kg, i.p.) is an animal model used to study behavioral and biochemical changes associated with tardive dyskinesia but it does not offer mechanistic insight into neuronal cell death induced by haloperidol, so we have developed another model (subacute (21 days) administration of haloperidol (5 mg/kg, i.p.)) that clearly shows neuronal cell death mechanism and can be used as a model to test different test drugs against haloperidol induced neuronal death (see Note 1).


2.2. Drugs

Male Wistar rats (180–220 g; 10–12 rats/group) should be used. The animals should be housed under standard laboratory conditions, maintained on a normal light-dark cycle and free access to food and water. Animals should be acclimatized to laboratory conditions before the test. 1. Haloperidol (Serenace, Searle, India). 2. Clozapine (Sun Pharmaceuticals, Mumbai, India). 3. U74500A (Sigma Aldrich, St Louis, USA).

2.3. Behavioral Assessment of Orofacial Movements 2.4. Biochemical Assessment

A small (30 × 20 × 30 cm) plexiglass cage with mirrors on the floor and behind the back wall. This will permit observation of oral dyskinesia when the animal is facing away from the observer. 1. Lipid peroxidation assay (9): 0.1 M phosphate buffer, 20% (w/v) trichloroacetic acid, 0.67% (w/v) thiobarbituric acid. 2. Superoxide anion levels (10): 0.1 M phosphate buffer (pH 8.0), 4% sulphosalicylic acid DTNB (5-5¢-DithioBis-(2Nitrobenzoic acid)). 3. Nonprotein thiols (NPSH) (11): Tris–KCl buffer (pH 7.4), 0.05 mM cytochrome C. 4. Protein content (12): Bovine serum albumin.

2.5. Assessment of Inflammatory Mediators

1. Total Nitric Oxide ELISA: Total nitric Oxide Assay Kit (R&D Systems, Minneapolis, USA). 2. TNF-α ELISA: Quantikine Rat TNF-alpha immunoassay kit (R&D Systems, Minneapolis, USA).

12

Molecular Analysis of Tardive Dyskinesia

195

3. NF-κB p65 subunit ELISA: NF-κB/p65 ActivELISA kit (Imgenex, San Diego, USA). 2.6. Caspase-3 Colorimetric Assay

1. Caspase-3 ELISA: Caspase-3 colorimetric kit (R&D Systems, Minneapolis, USA).

3. Methods Administer all the respective drugs: 1. Haloperidol (5 mg/kg, i.p.), 2. Clozapine (10 mg/kg, i.p.), 3. U-74500A (2.5 and 5 mg/kg, i.p.) + haloperidol (5 mg/kg, i.p) once daily for a 21-day period. All the drugs were administered in a constant volume of 0.5 ml per 100 g of bodyweight of rat. In combination studies, haloperidol and U74500A were administered simultaneously once daily at 09:00 h. 3.1. Behavioral Assessment of Orofacial Movements

1. On the test day, rats should be placed individually in a small (30 × 20 × 30 cm) plexiglass cage for the assessment of oral dyskinesia (see Note 2). 2. Hand operated counters can be used to score vacuous chewing movements (VCMs), tongue protrusions (TPs) and facial jerkings (FJs) for a period of 5 min (13) (see Note 3). VCMs were referred to as single mouth openings in the vertical plane not directed toward any physical object. TPs were referred to stereotypically turning movements of the tongue with protrusions (fly catching tongue) and jerky movements of face in either direction were referred as FJs. We have shown the results of some of our unpublished data in Table 1 in which U-74500A a synthetic antioxidant has prevented the dyskinetic changes induced by haloperidol administration (Table 1).

3.2. Biochemical Assessment

In the following section, alteration in protein thiols, lipid peroxidation, superoxide anion, and protein levels is assessed.

3.2.1. Estimation of Nonprotein Thiols to Quantify Reduced Glutathione Levels

1. Precipitate 0.75 ml of striatal homogenate samples with 0.75 ml of 4% sulphosalicylic acid. Centrifuge at 12,000 × g for 15 min at 4°C. 2. Mix 0.5 ml of supernatant and 4.5 ml of 0.01 M (in 0.1 M phosphate buffer, pH 8.0) DTNB. 3. The yellow color developed can be read immediately at 412 nm using UV/visible spectrophotometer. The results are expressed as nmol of GSH/milligram protein.

196


Table 1 Effect of haloperidol (typical antipsychotic), clozapine (atypical antipsychotic) and coadministration of U74500A with haloperidol on orofacial dyskinetic movements in rat Number of VCM/5 min

Treatment

Day 0 Day 22 Dose (mg/kg) Mean ± SEM

Control

Number of tongue protrusions/5 min

Number of Facial jerkings/5 min

Day 0

Day 22

Day 0

Day 22

2.3 ± 0.5

4.2 ± 0.9

0.4 ± 0.01

1.2 ± 0.1

0.6 ± 0.02

2.1 ± 0.09

Haloperidol

5

3.6 ± 0.4

98 ± 12a

1 ± 0.08

21 ± 2.8a

1.2 ± 0.08

26.2 ± 4.3a

Clozapine

10

3 ± 0.6

12 ± 2b

0.4 ± 0.04

0.8 ± 0.4b

0.8 ± 0.04

4.2 ± 0.3b

U74500A

5

2.8 ± 0.6

3.6 ± 1.1

0.6 ± 0.01

1.1 ± 0.1

0.7 ± 0.02

2.8 ± 0.09

ab

ab

U74500A + Haloperidol

2.5

4.3 ± 0.5

66 ± 7.4

0.5 ± 0.01

12 ± 1.6

0.4 ± 0.02

18 ± 1.4ab

U74500A + Haloperidol

5

2.8 ± 0.3

25 ± 3.8abc

0.8 ± 0.02

6.7 ± 1.1abc

0.8 ± 0.03

8.4 ± 2.6abc

a

p £ 0.05 as compared to control group p £ 0.05 as compared to haloperidol c p £ 0.05 as compared to U74500A (2.5) + Haloperidol (5) b

3.2.2. Estimation of Superoxide Anion

1. Homogenize striatal samples in Tris–KCl buffer to produce 10% homogenate. From each homogenized sample 25 μl of homogenate can be taken and mixed with 0.05 mM cytochrome C solution (in Tris–KCl buffer) to make up the volume to 2 ml. 2. Incubate the mixture for 15 min at 37°C. Terminate the reaction by placing the mixture in ice and then centrifuge at 700 × g for 10 min. 3. Take the supernatant and measure absorbance at 550 nm with UV/VIS spectrophotometer. 4. Results are expressed as nmoles of cytochrome-c reduced/ min using molar extinction coefficient of chromophore ( 2.1 × 104 M−1 cm−1) and expressed as percentage of control taking control values as 100%.

3.2.3. Lipid Peroxidation Assay

1. Incubate 1 ml of striatal homogenate (in phosphate buffer) with 1 ml of 20% (w/v) trichloroacetic acid for 2 h. 2. After 1 h incubation, add 1 ml of 0.67% (w/v) thiobarbituric acid to each sample tube and place them in heating water bath. 3. Absorbance can be measured at 532 nm using UV/visible spectrophotometer. The results are expressed as nmol of

12


197

Fig. 1. Effects of haloperidol (5 mg/kg, i.p. 21 days), clozapine (10 mg/kg, i.p. 21 days), U74500A (2.5 and 5.0 mg/ kg) + Haloperidol (5) on the altered oxidative damage parameters (MDA, Super Oxide anion and NPSH) in rat brain striatum homogenates. Data has been expressed as % control (taking control values as 100). ap £ 0.05 as compared to control group, bp £ 0.05 as compared to haloperidol group, cp £ 0.05 as compared to U74500A (2.5 mg/kg) + Haloperidol (5) group.

malondialdehyde/milligram protein using the molar extinction coefficient of chromophore (1.56 × 105 M−1 cm−1). 3.2.4. Protein Concentration

3.3. Assessment of Inflammatory and Apoptotic Mediators 3.3.1. Total Nitric Oxide ELISA

Protein content may be measured according to the method of Lowry (1951) using bovine serum albumin (BSA) dilutions as a standard. We have shown the results of our unpublished data in Fig. 1, in which U-74500A a synthetic antioxidant has prevented the biochemical changes associated to haloperidol administration (Fig. 1). 1. Prepare all reagents, working standards, and samples as directed in product kit. 2. Add 200 μl of Reaction Buffer (1×) to the blank wells. Add 50 μl of reaction buffer (1×) to the zero standard wells. Add 50 μl of Nitrite Standard or samples to the remaining wells. Add 50 μl of Reaction Buffer (1×) to all standard and sample wells. 3. Add 50 μl Griess Reagent I to each well except the blank wells. Add 50 μl Griess Reagent II to each well except the blank wells. Mix well by tapping the side of the plate gently. 4. Incubate for 10 min at room temperature. 5. Determine the optical density (OD) of each well using a microplate reader set at 540 nm.

198


3.3.2. TNF-a ELISA

1. Prepare reagents, working standards, control, and samples as directed in the product kit. 2. Add 50 μl of assay diluent RD1-41 to each well. Add 50 μl of Standard, Control, or sample to each well. Mix by gently tapping the plate frame for 1 min. Cover with the adhesive strip provided and incubate for 2 h at room temperature. 3. Aspirate each well and wash, repeating the process four times for a total of five washes. Wash by filling each well with Wash Buffer (400 μl) using a squirt bottle (see Note 4). After the last wash, remove any remaining wash buffer by inverting the plate and blotting it against clean paper towels. 4. Add 100 μl of rat TNF-alpha conjugate to each well. Cover with a new adhesive strip. Incubate for 2 h at room temperature. Repeat the washing as in step 3. 5. Add 100 μl of Substrate Solution to each well. Incubate for 30 min at room temperature (see Note 5). 6. Add 100 μl of stop solution to each well. Gently tap the plate to ensure thorough mixing. 7. Determine the optical density of each well within 30 min, using a microplate reader set to 450 nm.

3.3.3. NF-kB p65 Subunit ELISA

1. Prepare reagents, working standards, control, and samples as directed in product kit. 2. Dilute 100 μl of capture antibody (IMK-503-01) in 10 ml of coating buffer (KC-104). Pipette 100 μl of diluted antibody into each well (standards and samples), cover and incubate the plate overnight (12–24 h) at 4°C. After 24 h, wash the coated wells twice with 300 μl of 1× wash buffer. 3. Add 200 μl of prepared blocking buffer to each well to block the remaining reactive surface. Incubate for 30 min to 1 h at room temperature. Remove blocking buffer from wells by flicking into an appropriate waste container and gently tapping the plate face-down on paper towels. 4. Pipette 100 μl of standards, positive/negative controls and 100 μl test samples into the appropriate wells. Incubate plate at 4°C overnight or 4 h at RT (see Note 6). 5. Remove samples and control lysates and wash 4× with 300 μl of 1× Wash Buffer. Tap plate several times upside down to remove residual wash buffer after final wash. 6. Dilute 100 μl of detecting antibody (IMK-503-02) in 10 ml of blocking buffer and add 100 μl to each well. 7. Remove antibody solution and wash wells 4× with 300 μl of 1× Wash Buffer. Remove the residual wash buffer. 8. Dilute 5 μl of AKP-conjugated secondary Ab (KC-130) in 10 ml of blocking buffer. Add 100 μl of diluted secondary antibody to each well and incubate for 1 h at RT.

12


199

9. Remove the secondary antibody and wash thoroughly (5×) with 300 μl of wash buffer (see Note 7). 10. Dissolve 10 mg pNPP substrate into 10 ml of pNPP substrate buffer and mix. Add 100 μl of pNPP substrate to each well. Incubate the plate at RT for 30 min. Read the color development at 405 nm. 3.3.4. Caspase-3 Colorimetric Assay

1. Prepare reagents, working standards, control, and samples as directed in product kit. 2. Add 50 μl of sample and 50 μl of DTT containing 2× reaction buffer in each well. 3. Add 5 μl of Caspase-3 colorimetric substrate (DEVD-pNA) to each well and incubate the plate for 1–2 h. 4. Read the plate on a microplate reader using 405 nm wavelength light. We have shown the results of our unpublished data in Fig. 1, in which U-74500A a synthetic antioxidant has prevented the inflammatory and apoptotic changes associated with haloperidol administration (Fig. 2).

Fig. 2. Effects of haloperidol (5 mg/kg, i.p. 21 days), clozapine (10 mg/kg, i.p. 21 days), U74500A (2.5 and 5.0 mg/kg) + Haloperidol (5) on (a) total nitric oxide (NO) levels (b) TNFalpha levels (c) active p65 NFkappaB unit (nuclear tissue lysate) (d) % caspase activity (control = 100) in rat brain striatum. ap £ 0.05 as compared to control group, bp £ 0.05 as compared to haloperidol group, cp £ 0.05 as compared to U74500A (2.5 mg/kg) + Haloperidol (5) group.

200


4. Notes 1. In previously used animal model of tardive dyskinesia in our lab as well as other labs, haloperidol (1 mg/kg, i.p. for 21 days) was administered. It resulted in significant increase in VCMs and various oxidative stress parameters in the rat striatum but there was no significant effect on cellular markers. However, at higher doses as in the present model (5 mg/kg i.p. for 21 days) besides the corresponding increase in the VCMs, enhanced oxidative stress, there was a significant increase in cellular markers of inflammation and apoptotic protein (caspase-3), leading to cellular death. Although initiation of VCMs may be the result of dopaminergic receptor super sensitivity and generation of free radicals, at higher doses, intensity of VCMs is coupled with increase in striatal inflammatory mediators and caspase-3. Hence, by using this new model, we can assess the cellular mechanism behind cell death associated with haloperidol administration. This will also provide us the opportunity to test new drug candidates. 2. VCM has been referred to as single mouth openings in the vertical plane not directed toward physical material. If tongue protrusion or VCM occurred during a period of grooming, they were not taken into account. Counting was stopped whenever the rat began grooming, and restarted when grooming stopped. 3. Mirrors were placed under the floor and behind the back wall of the cage to permit observation of oral dyskinesia when the animal was faced away from the observer. In all the experiments, the scorer was unaware of the treatment given to the animals. 4. Complete removal of liquid at each step is essential to good performance. 5. Protect from plate from light during the period of incubation. 6. If necessary, samples may be diluted or serially diluted using blocking Buffer. 7. Let the solution sit briefly between each wash. This ensures a thorough wash and lower background. Tap plate upside down several times to remove any residual wash buffer.

Acknowledgment The authors would like to thank Professor S.K. Kulkarni and Dr. Kanwaljit Chopra for their guidance and support.

12


201

References 1. Creese, I., Burt, D., Snyder, S.H. (1976) Dopamine receptor binding predicts clinical and pharmacological potencies of antischizophrenic drugs. Science. 192, 481–483. 2. Walker, J.M., Bowen, W.D., Walker, F.O., Matsumoto, R.R., De Costa, B., Rice, C.K. (1990) Sigma receptors: biology and function. Pharmacol. Rev. 42, 355–402. 3. Vilner, B.J., Costa, B.R., Bowen, W.D. (1995) Cytotoxic effects of sigma ligands: Sigma receptor-mediated alterations in cellular morphology and viability. J Neurosci. 15, 117–134. 4. Meshul, C.K. and Tan, S.E, (1994) Haloperidolinduced morphological alterations are associated with changes in calcium/calmodulin kinase II activity and the glutamate immunoreactivity. Synapse. 18, 205–217. 5. Halliday, G.M., Pond, S.M., Cartwright, H., McRitchie, D.A., Castagnoli, N., Van der Shyf, C.J. (1999) Clinical and neuropathological abnormalities in baboons treated with HPTP, tetrahydropyridine analog of haloperidol. Exp. Neurol. 158,155–163. 6. Post, A., Rücker, M., Ohl, F., Uhr, M., Holsboer, F., Almeida, O.F., Michaelidis, T.M. (2002) Mechanisms underlying the protective potential of alpha-tocopherol (vitamin E) against haloperidol-associated neurotoxicity. Neuropsychopharmacology. 26, 397–407.

7. Sagara, Y. (1998) Induction of reactive oxygen species in neurons by haloperidol. J. Neurochem. 71,1002–1012. 8. Lohr, J.B., Cadet, J.L., Lohr, M.A., Larson, L., Wasli, E., Wade, L., Hylton, R., Vidoni, C., Jeste, D.V., Wyatt, R.J. (1988) Vitamin E in the treatment of tardive dyskinesia: The possible involvement of free radical mechanism, Schizophr. Bull. 14, 291–296. 9. Wills, E.D. (1966) Mechanism of lipid peroxide formation in animal tissues. Biochem. Jour. 99, 667–676. 10. Babior, B.M., Kipner, R.S., Cerutte, J.T. (1973) Biological defense mechanism. The production by leukocytes of superoxide, a potential bacterial agent. J. Clin. Investigation. 52, 741–744. 11. Ellman, G.L. (1959) Tissue sulfhydryl groups. Arch. of Biochemi. Biophy. 82, 70–77. 12. Lowry, O.H. (1951) Protein measurements with the Folin-phenol reagent. J. Biol. Chem. 193, 265–275 13. Bishnoi, M., Chopra, K., Kulkarni, S.K. (2007) Possible anti-oxidant and neuroprotective mechanisms of zolpidem in attenuating typical anti-psychotic-induced orofacial dyskinesia-A biochemical and neurochemical study.Prog. Neuropsychopharmacol. Biol. Psychiatry. 31, 1130–1138.

sdfsdf

Part III Methods in Animal Models of Substance Abuse

sdfsdf

Chapter 13 Models of Chronic Alcohol Exposure and Dependence Darin J. Knapp and George R. Breese Abstract Alcoholism is a chronic treatment-resistant disorder typically presenting with recurrent/cyclic periods of abusive drinking, withdrawal, abstinence, and relapse. Various strategies that attempt to model these processes in animals have been developed to elucidate the behavioral and neural processes underlying alcoholism. Many of these have involved chronic ethanol exposure and withdrawal with the most widely employed methods involving mice or rats. Prominent features of these methods include alcohol vapor or intragastric forced exposure, cyclic or intermittent periods of alcohol availability with various lengths of forced abstinence, voluntary consumption, the use of genetically alcohol-preferring animals, and inclusion of various pharmacological or environmental challenges to worsen or mitigate symptoms. This chapter emphasizes alcohol exposure and withdrawal and discusses representative metrics used to monitor the consequences of employing these methods. These include but are not limited to intensity and pattern of alcohol exposure, seizure sensitivity during withdrawal, and emotional responding. Key words: Alcohol, Repeated, Intermittent, Binge, Chronic, Withdrawal, Sensitization, Animal models, Anxiety-like behavior, Seizures, Drinking

1. Introduction Models of alcoholism are diverse and numerous and have played key roles in understanding many of the factors underlying abusive and pathological alcohol consumption. Each focuses on one or more constructs or suspected etiological factors in alcoholism. Consideration of all these models and their methodologies is far beyond the scope of any single chapter or review. This chapter focuses on methods involving chronic ethanol exposure and withdrawal and emphasizes ethanol dependence arising from repeated, cyclic, or intermittent ethanol exposure. The rationale for including such methods derives in part from the original clinical work (1–3) that highlighted a clinical course of alcoholism that progressively


205

206

D.J. Knapp and G.R. Breese

worsens through a process akin to kindling or sensitization involving repeated detoxifications or withdrawals. Various animal models that attempt to capture aspects of this sensitization process have been developed. This chapter covers these models as well as other basic methods of inducing dependence (as primarily defined by the presence of withdrawal symptoms) without a cyclic component. Importantly, this chapter does not address methods for approaching ethanol addiction per se which is a chronic disease of brain reward, motivation, memory, and related circuitry that manifests in humans with cyclical patterns of alcohol craving, dysfunction of behavioral control, failure to abstain, relapse, and impaired recognition of problems with one’s behaviors and the consequences of drinking. However, basic methods of inducing dependence often provide critical means to prepare animals for studies of potential relationship between dependence history and reinforcement (e.g., ref. 4). The dependence methods covered in this chapter are not inclusive or exhaustive; modifications of them and others are available in the literature.


1. Mice: Depending on experimental needs and constructs under study, mice from Jackson Labs are commonly used as are those from various suppliers, such as Harlan, Charles River, and Taconic. Other local and university sources of select genetic lines may also be suitable. Young adult males are typically used although studies of females/males may be of relevance as may be chronic ethanol effects across developmental stages. 2. Rats: Depending on the purpose, various supply houses offer a host of animals as do select labs breeding specific lines of potential relevance to alcohol-related phenotypes (see Note 1). Other species, including other rodents, can be used. Of particular note are select primates, such as monkeys, that consume ethanol but are generally not available to most researchers.

2.2. Alcohol Exposure Equipment and Materials 2.2.1. Two-Bottle Choice

Drinking bottles: For rats, 100-ml plastic graduated cylinders attached to the animal’s cage with 5½ rubber stoppers and steel ball—tipped sippers protruding into the cage are adequate for single-housed animals. The drinking vessel size can be scaled up or down for multiple-housed animals or for mice, respectively. These tubes can also be used for the rat liquid dietary ethanol preparations described below. For mice, 50-ml plastic conical centrifuge tubes compatible with 5½ rubber stoppers and straight open sipper tubes should be used.

13

Models of Chronic Alcohol Exposure and Dependence

207

Fig. 1. An example vapor chamber system for mice. Picture from Dr. Todd Thiele, University of North Carolina Chapel Hill. 2.2.2. Vapor Chamber Systems

This fairly expensive option allows for relatively good control over the blood ethanol levels the animals achieve at any given time. Commercial chamber systems are available (e.g., from La Jolla Alcohol Research Inc.; e.g., ref. 5) or can be built (see Fig. 1) based on commonly used systems (e.g., ref. 6, 7). For the systems such as those shown in Fig. 1, 95% ethanol is volatilized and pumped into one of the chambers at 140–180 ml/min by a peristaltic pump (e.g., Harvard Apparatus). With air being delivered to the chambers at 10 l/min, the ethanol in the chamber air is approximately 10–13 mg/l air. For mice, intraperitoneal (IP) injections of the alcohol dehydrogenase inhibitor pyrazole are given to reduce alcohol metabolism and thereby increase blood ethanol levels.

2.2.3. Gastric Feeding Options

1. Indwelling catheter construction: This procedure requires the following: (a) Polyethylene (PE) 100 and PE200 tubing for adult rats. (b) Polyethylene (PE50 and PE90 for adult mice or small/ young adolescent rats; Fig. 2). (c) Sterile surgical setup and anesthesia. (d) A sterile surgical tool set for rodent abdominal surgery, including a 6”-long 0.5-cm-diameter stainless steel sharpened trocar tube. (e) 5–0 black monofilament nylon suture. (f) 10-inch flexible/bendable aluminum wire that just fits inside the PE100 tubing (less than 0.86 mm internal diameter).

208


Fig. 2. A polyethylene gastric catheter (sized above for older adolescent rats, see info herein on older rats or mice) used for repeated delivery of liquid solutions, such as ethanol or ethanol-containing diets, directly into the stomach.

(g) Round capped stick needles capable of fitting snugly into the end of a piece of PE100 tubing. (h) 20-gauge needles with the sharp points ground to a smooth circle. (i) 1–15-ml plastic syringes. (j) A metal block or plate approximately 2 × 3 inch that can be fire heated. (k) Benchtop gas burner. (l) Metal tubing (connected to lab air port) that can be heated with the burner to provide a very hot and narrow air stream. (m) Ethanol or ethanol liquid diets, or control solutions, and near-boiling water in a beaker (the beaker should be sized to lower the finished catheter/wire combo into for about 30 s to force the catheter into the shape of the bent wire inside the catheter). 2. Intragastric gavage infusion materials: (a) Stainless steel curved gastric feeding needles (22 × 1.5″ for mice; 16 × 3″ for rats) (see Fig. 3). (b) 1–15-ml plastic syringes. (c) Ethanol or liquid ethanol diets.

13


209

Fig. 3. An intragastric gavage feeding needle and syringe for rats.

3. Alcohol (ethanol) and pyrazole. (a) Procure a 95% solution available from various commercial suppliers as a stock solution for preparing ethanol/water solutions or dietary mixtures. (b) For mouse vapor chamber methods described below, have a solution of pyrazole on hand compatible with 1 mM/kg injections. 2.3. Ethanol Solutions

A 10% v/v solution of ethanol (e.g., 421 ml 95% ethanol to make 4 L) or a series of solutions from 10, 20, and/or 30% ethanol. Green food dye added at 50 drops per gallon of 95% ethanol before diluting to the drinking concentrations.

2.4. Liquid Diets

Three options of multiple ones available are described here.

2.4.1. Mouse Diet and Delivery, Forced Consumption

One option is to obtain PMI® Micro-stabilized Alcohol Rodent Liquid Diet (LD 101A) containing a “dry mix” and maltodextrin (LD 104) online from http://www.TestDiet.com (or ordered direct from Granville Milling, Creedmore, NC). For an ethanolcontaining diet, make a 4.8% ethanol diet: 1. Dry mix. 2. Maltodextrin. 3. Sucrose. 4. 95% ethanol.

2.4.2. Rat Liquid Diet, Forced Consumption

This diet was adapted from an original diet (8) used for decades (9–12). This diet is lactalbumin/dextrose/corn oil-based and generally employed for alcohol concentrations up to 7 or 8%. Assemble these materials from Dyets Inc. (unless otherwise noted). 1. Lactalbumin hydrosylate containing citric acid (#405541 in 552-g plastic containers) (see Note 2).

210


2. Custom mineral mix (#210085 in 667-g plastic containers mixed into 2 L water 2 days in advance of use). 3. Custom vitamin containers).

mixture

(#300054

in

250-g

plastic

4. Tween-80. 5. 10-ml plastic syringe, beakers. 6. Graduated cylinders. 7. Stir/hot plates compatible with 6-L flasks with caps/stoppers or aluminum foil. 8. 4-L metal beakers, commercial kitchen blender. 9. Ice (H2O). 10. Calcium chloride dihydrate (#195088, mixed in advance as 551.58 g in water in a final volume of 1 L). 11. Food-grade dextrose (#401450). 12. Corn oil (#401150) (the mineral mix and CaCl2 are kept mixing at 4°C). 2.4.3. Alternative Liquid Diet

This diet is based on Vanilla Ensure Plus® (Abbott Laboratories, Columbus, OH; available at grocery/pharmacy stores). See ref. 13 for example use of this diet in the gastric gavage method.

2.5. Withdrawal Monitoring Equipment

1. A social interaction (SI) box (Fig. 4, top).

2.5.1. Withdrawal-Induced Anxiety Testing

3. An ultrasonic vocalization-inducing and detecting system.

2.5.2. Social Interaction Box

2. Elevated plus maze (Fig. 4, bottom). 4. A number of other test boxes and/or apparati. A simple SI box is recommended with the plus maze apparatus included as a tool to verify the results from the SI test. The SI box requires the following. 1. The SI box is 60 (W) × 60 cm (L) × 51 cm (H). 2. Material: Black Plexiglas resting on a clear Plexiglas floor piece with four horizontal and vertical lines drawn on the under surface to create 16 readily visible squares of equal size. 3. A digital video camera and TV screen nearby for real-time experimenter-recorded data and for subsequent reassessment from video as may be needed later.

2.5.3. The Rat Plus Maze

1. The rat plus maze is typically also made of black Plexiglas. 2. With four (50 cm long, 10 cm wide) arms elevated 55 cm off the ground and meeting at a 10-cm square center of the maze. 3. The sides and distal ends of two opposing arms are enclosed with approximately 40-cm-tall walls.

13


211

Fig. 4. (a) Top: Social interaction box with two adult male Sprague Dawley rats of approximately equal size. (b) Bottom: The rat elevated plus maze.

4. The two other arms have no sides but may have a small (e.g., 1 cm) ridge or “bumper guard” on the lateral sides of the arms to limit the risk of a rat slipping off the edge. 2.6. Seizure Testing

One option is to employ the electrical kindling equipment and materials of McCown and colleagues (10, 15, 16) requiring: 1. A 35 × 50-cm-tall plastic cylinder or can for conducting the seizure tests. 2. A stereotaxic apparatus. 3. A three-wire electrode and a Grass SD9 stimulator or equivalent that deliver electrical stimulation (30 Hz, 1.5 ms duration) in 20 mA increments every 5 s via the three-wire system. (The three-wire system consists of 0.015″ platinum iridium, insulated except for the tip cross section, with a 0.2-mm vertical tip separation between each of the first, second, and third wires (see Fig. 5). The third one is longest, the second one shorter,

212


Fig. 5. A three-wire electrode for electrical kindling of seizures in rats.

and the first one shortest with all three twisted around each other as they progress to their respective connections on a pin connector strip (Newark Electronics) that in turn communicates with the Grass stimulator.) Animal preparation for kindling is implemented (16). A second alternative set of materials for seizure induction relates to the methods of the bicuculline seizure threshold test or the audiogenic seizure test (e.g., ref. 10). 1. For the audiogenic seizure test: (a) A chamber (a retrofitted medium-sized garbage can with lid will do) fitted with a metal bell capable of producing more than 100 db and equipped with a window for observation. (b) Control subjects or those in withdrawal from chronic ethanol exposure, timer. 2. For the bicuculline seizure threshold test: (a) 0.05 mg/ml solution of the GABAA receptor antagonist bicuculline (ICN Biomedicals). (b) A pump and associated tubing that can deliver fluid at a rate of 1.6 ml/min via a 25-gauge needle. (c) Small hand towels or commercial rat restrainer.

13

2.7. Blood Ethanol Monitoring Equipment

2.7.1. Blood Ethanol Monitoring


213

A method of monitoring ethanol in breath or blood is necessary for knowing when and to which concentration blood levels of ethanol have been elevated. Three methods are described below, two for blood and one for breath. 1. A gas chromatographic (GC) system is a stable, long-term solution for monitoring ethanol (or other volatile substances) in blood, breath, or other sources (17); (see Fig. 6 for some of these materials). The GC system is equipped for receipt of headspace gas samples. 2. SRI 8610C GC is often used; Torrance, CA. 3. Distilled water, blood samples.

Fig. 6. A portable gas chromatographic system for assessing blood or breath ethanol samples.

214


4. 3-ml plastic syringe with cutoff valve. 5. 25-gauge needles. 6. 20- or 40-ml syringes for flushing all components that come in contact with ethanol vapor. 7. NaCl. 8. 12 × 75-mm borosilicate glass tubes with appropriately sized rubber caps compatible with needle puncture. 9. 200-proof unadulterated ethanol. 10. Hot water bath capable of maintaining 55°C water. 11. One or more racks of glass tubes. 12. Marking pen. 13. Timers. 14. Stock solutions of diluted ethanol at a range of 25–400 mg%. 15. Blood or serum from experimental subjects. 2.7.2. Breath Ethanol Monitoring

Breath ethanol: The following materials are needed for sampling breath ethanol. 1. 50-ml conical end polypropylene centrifuge tubes (see Note 3) to be used as rebreathing tubes. 2. 3-ml plastic syringes. 3. A 1.5″-long 20-gauge needle ground to a smooth end, syringe cutoff valve. 4. Rubber stopper (for the centrifuge tube) with hole to accommodate 20-gauge needles.

2.7.3. Enzymatic-Based Tests Are Also Available (13)

1. GM7 Alcohol Analyzer (Analox, London, UK). 2. Enzymatic Determination of Ethanol Test (Sigma Diagnostics, St. Louis, MO).

3. Methods 3.1. Dietary Ethanol Intake

An efficient and cost-effective option requires the animals to consume their daily calories and nutrition in the form of a liquid dietary preparation containing all the vitamins, minerals, fats, carbohydrates, and proteins required for growth and development, along with the adulteration with alcohol at concentrations up to 8% w/v or more. The diet the experimental animals receive (ethanol containing) and the diets the controls receive (no ethanol) have equal calories and nutrition with caloric balancing achieved with different carbohydrate concentrations (e.g., dextrose).

13 3.1.1. Mouse Diet Preparation


215

1. Ethanol-containing diet: (a) Mix 806.8 ml water, 140 g dry mix (b) 5.2 g maltodextrin (c) 50 g sucrose (d) 59.25 ml 95% ethanol to make a 4.8% ethanol diet 2. Control diet: (a) 770 ml water (b) 140 g dry mix (c) 90 g maltodextrin (d) 50 g sucrose 3. 2.4% ethanol diet: (a) 788.5 ml water (b) 140 g dry mix (c) 47.5 g maltodextrin (d) 50 g sucrose (e) 29.7 ml 95% ethanol 4. Heat water (but do not boil) and dissolve sucrose, cool to lukewarm, add to blender, and add the dry mix and maltodextrin. Mix for 30 s on low speed. Pour into storage vessel, add ethanol, stir, and use immediately or store refrigerated for 1–2 days. Add up to 25 ml per mouse per 50-ml mouse drinking tubes with straight/open sippers and place on the mouse cage. Use the diet within 1–2 days. For a 2.4% ethanol diet, the components are 788.5 ml water, 140 g dry mix, 47.5 g maltodextrin, 50 g sucrose, and 29.7 ml 95% ethanol (see Note 4).

3.1.2. Rat Liquid Diet Preparation

1. Instructions for 6 L of control diet stock (the terms “control diet” and “control diet stock” are synonymous here): (a) First, add 2,000 ml water. (b) Add 552 g lactalbumin (add stir bar to a 6-L glass flask, shake initially, and then allow to dissolve slowly while stirring at room temperature). The solution eventually turns to an off-brown color from the original tan. (c) Concurrently, heat 1,300 ml water in metal beaker (but do not boil). (d) Add stir bar and then start adding 1,740 g dextrose. (e) Remove from heat once dissolved and place container on ice to cool the solution closer to room temperature. (f ) Add 240 ml mineral mix to this solution and stir. (g) Add about 300 ml of the dextrose/mineral solution to the blender.

216


(h) Cap blender, start on low speed, uncap, and add the 10 ml Tween-80 from syringe, then 130.8 ml corn oil, and 24 g vitamins. Blend on low for about 1 min. (i) Add this solution to the lactalbumin solution, then add more of the original dextrose/mineral solution to the blender, and blend briefly to remove remaining vitamins. (j) Pour this solution into the lactalbumin flask. (k) Pour remaining dextrose/mineral solution (retain the stir bar) into the lactalbumin. (l) After letting the bubbles settle out for a few minutes, fill the flask with water to the 6-L line. (m) Refrigerate while stirring if possible (i.e., on a stir plate in a cold room) for a maximum of 5–7 days if not used before then. Note that this control diet serves as a ready-to-consume control diet as well as a stock component of the ethanol-containing diet. 2. To make the ethanol diet stock (with no ethanol in it yet): (a) Add 1,400 ml water to 714 g dextrose and follow the instructions above to complete this ethanol diet stock. 3. To prepare 4 L of a 7% solution of ready-to-consume ethanol diet: (a) Add 2,200 ml ethanol diet stock to 1,432 ml control diet stock (prepared as above) and 368 ml 95% ethanol. 4. For 4 L of a 4.5% ethanol diet: (a) Add 1,410 ml ethanol diet stock, 2,354 ml of control diet stock, and 236 ml 95% ethanol. 5. For a 3.5% solution: (a) Add 1,100 ml ethanol diet stock, 2,716 ml control diet stock, and 184 ml 95% ethanol. 6. For 4 L of a 2.5% ethanol diet: (a) Add 790 ml ethanol diet stock, 3,078 ml control diet stock, and 132 ml 95% ethanol (see Note 5). 7. Store all three diets/stocks at 4°C and use within a week. 3.1.3. Alternative Liquid Diet

For a control diet, heat 350 ml of water and slowly add 427.5 g dextrose. When all dextrose is in solution, allow to cool and then add solution to 345.5 ml of Ensure Plus. Stir the entire time. Bring the total volume to 1 L with water. For a 25% w/v ethanol diet, mix 345.5 ml Ensure and 345.5 ml water thoroughly, and then add 309 ml 95% ethanol. Use fresh or store on mixer at 4°C for a few days.

13 3.1.4. Paradigms of Dietary Recipes Delivery


217

Example dietary recipes are described above (see Note 6). Rats are typically exposed to the ethanol-free diet for 2 days, and then exposed to the desired ethanol concentration for the ensuing days or weeks prior to withdrawal and testing (see Note 7). Give rats 50 ml of the control diet for the first 2 days, then switch experimentals to a 4.5% ethanol-containing diet for 2 days, and then either maintain them at 4.5% prior to withdrawing them for 2 days (by giving them control diet) or raise the concentration to 6 or 7% going forward as experimental needs dictate and if rats tolerate the increase. Repeat this 5-day exposure to 4.5% (or higher ethanol access) and 2 days of withdrawal for at least three cycles. At the end of the final day of exposure, give the rats control diet and then wait between 5 and 24 h of withdrawal (for lower versus higher alcohol exposures, respectively [during which time the blood ethanol levels have returned to zero]) before conducting behavioral tests (see Note 8). Representative behavioral test equipment is described above in Subheading 2.3. This method has been used to sensitize emotional (anxiety-like behavior) symptoms in relatively short (e.g., 2–3 weeks) periods of time (example shown in Fig. 7). However, a related and historically well-used method is to simply have the animals consume a 4.5% diet for a couple of days, then increase the concentration to 7 and 8% (if tolerated) without cycles for 8–13 more days prior to abruptly withdrawing the animals, and observe for physical and/or emotional signs of withdrawal starting 6–24 h later. This modified method readily induced a physical withdrawal reaction that includes ultrasonic vocalizations, altered open field behavior, SI deficits, and increased sensitivity to audiogenic and bicuculline-induced seizures. A variety of modifications to the basic three-cycle paradigm have been used to worsen withdrawal-induced anxiety-like behavior. Among these are methods that incorporate cycles of stress, and drugs or chemicals that worsen or mitigate withdrawal sensitization.

Fig. 7. Example designs of cyclic ethanol, stress, and pharmacological paradigms used to sensitize withdrawal symptoms in rats. In I, rats can be treated with an ameliorative drug during the first and second withdrawals OR the third withdrawal.

218


Fig. 8. Representative social interaction (SI) times (an index of anxiety-like behavior in rats) during withdrawal from 15 days of cycled versus continuous ethanol diet exposure. Adapted from ref. 18.

Representative designs are shown in Fig. 7. Representative data from a cycled dietary ethanol paradigm is shown in Fig. 8. 3.2. Intragastric Administration Procedures

Catheter or gavage binge administration is perhaps the most rapid and powerful method available to induce physical dependence in rodents. Depending on the daily doses, the strongest withdrawal reactions (i.e., including seizures, increased risk of death from seizures) generally reported in the literature are possible during withdrawal from just 2–3 days of this intense binge-type administration procedure.

3.2.1. Indwelling Gastric Catheter-Implanted Rats

For adult rats, the ends of a 7″ piece of PE100 tubing should be cut evenly and perpendicular to the shaft with a razor blade or scalpel. With a fire-heated metal block, bring the end of the tube very close to a small flat metal block that has been heated to the point of being capable of melting the PE tubing if touched or brought very close to the surface. With brief touches of the end of the PE segment to the block, slowly melt back the end until a 3-mm-diameter ring or plate is formed on the end of the tube. Do not allow the end to melt to the point of closing off the opening! Do the same thing to the ends of a piece of PE200. Then, cut the disc and approximately 0.5-cm piece of shaft off together as a single piece to form a sheath/ disk that fits snugly over the PE100 shaft down to a point near the disc on the PE100 such that the two discs can touch each other. The other end of the PE100 may need to be cut at a sharp angle to allow the small PE200 may need to be cut disk-containing segment

13


219

to fit over the end. This pressed together seal is eventually used to hold the PE100 disc inside and the PE200 disc outside the forestomach of the rat and thus secure the catheter to the stomach. Next, push the metal wire all the way down the PE100 shaft and place the shaft perpendicular to a narrow stream of fire-heated air arising from a metal tube drive by standard lab bench air port. Turn the shaft in the air stream until the PE just begins to overheat and turn clear in a tight circle around the shaft. Then, push on the tubing from the left and right to make another disk (the stomach side disk). Do this one more time to form a “skin side disk” about 0.5 cm away from the first one; this pair of disks is used to suture the catheter to the abdomen wall (with the stomach side disc inside and the skin side disk outside the abdomen wall). Next, place a third one near the other end of the tube. This third disc is used to suture the catheter to the skin at the exit site behind and between the ears. Then, bend the PE and wire to a shape that allows placement of the catheter into the stomach, exit the stomach at a 90° angle that allows the catheter to run posteriorly and ventrally under the ribs to a point in the abdomen muscle, where the paired discs straddle the inside and outside of the abdomen muscle layers (sutured there around the catheter and between the disks and secured to the muscles) before turning approximately immediately 120° angle just after exiting the abdomen. The catheter then proceeds anteriorly and dorsally subcutaneously to the exit point at the back of the neck, where a final 90°–120° angled bend is made in the catheter approximately ½–¾ inch from the catheter end. This end is the injection port for a 20-gauge needle that has had its sharp end ground off evenly. Mark the spot on the neck that makes the catheter fit the animal. Make a small nick in the shaved neck skin to allow the trocar-guided catheter to exit at the appropriate spot to accommodate the end disk that is sutured to the skin there. Finally, push a stick pin into the open end to close off the catheter. After 4–7 days of recovery, the first ethanol dose can be administered via the methods described below. 3.2.2. Intragastric Catheter Method: Begin with Gastric Surgery

Prepare gastric catheter-implanted rats as described (see Fig. 2). Once recovered for 4–7 days, withdraw regular chow from experimentals and controls, and then initiate a Majchrowicz-type treatment (e.g., ref. 13, 19, 20) by first administering a single 5 g/kg dose of the vanilla Ensure Plus adulterated with ethanol as described above. Subsequent dosages every 8 h are based on an intoxication level estimated on a scale from 0 to 5 (with five being maximally intoxicated) immediately prior to dosing. This second and subsequent doses are given to the rats in boluses of 5, 4, 3, 2, 1, or 0 g/ kg, respectively, depending on current intoxication level. In this way, rats can remain intoxicated without excessive risk of lethal overdose. As little as 48–72 h of this dosing can result in clear signs of physical and emotional withdrawal starting 8–16 h after the last dose (20, 21) (see Note 9).

220


3.2.3. Gastric Feeding Via Gavage Method

A simple alternative binge-type procedure (see Note 10) is to adapt animals to handling, then have a trained staff member hold the animals appropriately (rats around the chest/shoulders/upper abdomen with support for the back feet/legs; mice with the nape of the neck with leg and/or tail restrained with remaining fingers on the hand holding the mouse), and insert an appropriately sized feeding needle into the mouth, then down the throat/esophagus, and into the stomach to dispense the desired dose. While considered by some to be more stressful than infusions through indwelling catheters, this method is fairly easy and when done by trained staff and with handling-habituated animals. Under these circumstances, the stress is arguably limited. Single-infusion volumes for adult rats can be 10 ml or more while for mice corresponding volumes must be scaled downward to adapt the volume to the smaller body sizes (approximately 1:10 reduction in volume). Single or repeated dosing can be conducted by trained staffs who infuse ethanol or dietary ethanol solutions (1–3 evenly spaced times per day) directly into the stomach without the requirement for the gastric surgery (see Note 11). Example procedures include derivations of the Majchrowicz procedure described above, a once-daily 4–5 g/ kg treatment, or related approaches depending on needs (e.g., severity of withdrawal desired).

3.3. Seizure-Based Methods

With these systems, Becker and colleagues showed withdrawal syndromes sensitive to the cycling procedure per se and not just the ethanol (Table 1; Fig. 9) such that noncycled, yet equally ethanolexposed, mice did not show as severe a seizure profile (see ref. 6, 7). For mice, this method begins with an IP injection of ethanol 1.6 g/kg (8% w/v) and an injection of pyrazole (1 mmol/kg; 0.02 ml/g body weight) to stabilize resultant blood ethanol levels.

3.3.1. Vapor Chamber Sensitization of Withdrawal Seizures

Table 1 Handling-induced convulsion (HIC) rating scale from ref. 22 Score

Associated behavior

0

No activity on tail lift or after gentle 360° spin

1

No activity on tail lift, but facial grimace after 360° spin

2

Tonic convulsion after 360° spin

3

Tonic/clonic convulsion after 360° spin

4

Tonic convulsion on tail lift

5

Tonic/clonic convulsion on tail lift, onset delayed by 1–2 s

6

Severe tonic/clonic convulsion on tail lift, no delay in onset

7

Severe tonic/clonic convulsion prior to tail lift

13


221

Fig. 9. Consequences of multiple, single, or continuous ethanol on handling-induced convulsions (HICs) in mice following ethanol vapor chamber exposures. MW multiple withdrawal, SW single withdrawal, CE continuous ethanol, C control. *significantly different from SW group; † significantly different from CE. Modified from ref. 22.

Then, mice are placed in their cages inside the vapor chambers and exposed for 16 (cyclic exposure) to 24 h (continuous exposure matched to number of hours the cycled animals experience ethanol vapor) each day to the ethanol vapor or unadulterated air as a control. After 1–9 days of exposure, mice are allowed to withdraw and seizure testing begins (every hour for the first 10 h, then again at hour 24) with a tail suspension and rotation procedure outlined in Table 1. Data for each day are plotted and areas under the seizure curve are calculated for each group. 3.3.2. Electrical Kindling of Seizures

1. Animal preparation for kindling is implemented (16). Rats are secured in a stereotaxic apparatus. Prepare burr holes over the inferior colliculus such that the three-wire electrode can be inserted into the sensorimotor area of the inferior collicular cortex [−0.3 IAL, 1.8 lateral, 3.2 vertical, according to the atlas of Paxinos and Watson (16)]. Secure with dental cement and machine screws to the skull and cap with a second three-pin connector strip used as a plug when the animal is not being used in a stimulation session. 2. Following recovery from surgery to implant the electrode (described above) and the ethanol treatments of choice, the plugs are removed and the stimulator attached and animals stimulated with a current titration technique (14). Using a grass stimulator, electrical stimulation (30 Hz, 1.5 ms duration) is initiated at 80 mA and increased 20 mA every 5 s until the appearance of wild running behaviors. Stimulation is immediately

222


Fig. 10. Inferior collicular kindling reveals sensitized seizure responses in rats following multiple cycles of chronic ethanol diet. Adapted from ref. 9.

terminated and stimulation behaviors timed (wild running, and subsequent tonus and clonus if present). This procedure determines the seizure threshold current for each animal, which generally ranges from 100 to 200 mA and is stable over long periods. To kindle the animals, rats receive two stimulation sessions per day, one in the morning and one in the afternoon. When the animals exhibit two consecutive episodes of wild running followed by forelimb tonus and hindlimb clonus or myoclonic jerks of the neck and forelimbs, the animals are considered kindled. These steps create a rat with permanent sensitivity to generalized seizure activity (14). To examine the sensitizing effect of repeated chronic ethanol exposure on this pattern, institute the treatment regimens described above for cyclic alcohol exposure (6–10 cycles) before initiating the electrical kindling. An example dataset illustrating the use of this method to reveal sensitizing effects of repeated/cyclic bouts of chronic ethanol exposure is shown here (Fig. 10). 3.3.3. Bicuculline Seizure Threshold Test

After preloading the bicuculline into the pump system/syringe/ tubing, gently restrain the rat in a small hand towel or commercial rat restrainer such that the tail is fully exposed. After securing the needle in the lateral tail vein, insure that the rat’s head/face/ears can be seen, and then begin the flow of drug and start the timer. Closely watch the animal’s head/neck/ear area for the earliest sign of a twitch. Immediately stop the flow and record the time of the first twitch as the threshold/onset of the seizure. Calculate the threshold dose given from the time of flow × the flow rate × the concentration of drug relative to a kilogram of body weight (e.g., ref. 10).

3.4. Two-Bottle Choice Procedures

While most rodents avoid alcohol, many lines readily consume significant amounts of ethanol under the right conditions and genetic predispositions. Select lines may or may not respond to enticement

13


223

to consume the ethanol during initial days, where the ethanol bottle in an operant context also contains a sucrose solution the latter of which is “faded out” over the subsequent days while the ethanol concentration is increased to the desired percentage. Importantly, other rats and mice that are not generally known as alcohol preferring, while exhibiting various degrees of ethanol intake that allow many useful studies to be done (such as those involving positive reinforcement in operant models), do not necessarily achieve a level of drinking with the potential for prompting aspects of withdrawal once drinking ceases. However, the two simple strategies described below result in mild/moderate manifestations of a withdrawal reaction, such as anxiety-like behavior using alcohol-preferring P rats. 3.4.1. Two-Bottle Choice: Option 1

Provide P rats with 3–4 days of choice between 10% ethanol and water bottles (23). Then, remove the water bottle for 4 days and follow with 4 days of water-only, and finally 6 or more weeks of choice between the ethanol and water bottles. Calculate intakes as the weeks progress to identify rats that may not have strong and consistent preferences for water over ethanol. Compare intake on the days of interest relative to the baseline intakes during the initial preference phase (see Note 12). At the end of these steps, and between the sixth and eighth hour of withdrawal, rats can be tested for anxiety-like behavior in the elevated plus maze and SI tests as well as for seizure sensitivity in the bicuculline seizure threshold test described herein.

3.4.2. Two-Bottle Choice: Option 2

Provide P rats with 3 days of forced 10% ethanol (no choice), and then give them a 3-day water-only period followed by 5 days of ethanol and a 2-day water-only period during which time the rats are stressed via restraint in rat restrainers (such as plastic decapicones®) for 1 h starting at hour 4 of deprivation (24). Record before and after drinking readings daily at the same time of day. Repeat this pattern of 5 days of access with 2-day deprivation/ stress cycling at least twice more before initiating tests for withdrawal between hours 5 and 6 of the final deprivation period.

3.5. Blood Ethanol Monitoring

Whatever the ethanol exposure paradigm, knowing the level of ethanol exposure subjects experienced is critical to compare with other methods and to publish other associated data.

3.5.1. GC Parameters Used

1. The GC is equipped with an external syringe adapter and 1-ml external loading loop. The oven temperature is set to isothermal at 140°C and contains a 6¢ Hayesep D column and a flame ionization detector. Hydrogen gas, carrier gas (also hydrogen), and internal air generator flow rates should be set at 13.3, 25, and 250 ml/min, respectively. Peak retention time is around 2 min. The areas under the curve and/or peak heights are

224


quantified (analyzed with SRI PeakSimple software on any laptop or computer) and converted to mg% based on the standards created, stored, and run in parallel with the blood samples. 2. Ethanol standards for blood ethanol determinations: Consider the range that is expected, and then bracket that range with known concentrations of standards, e.g., 25, 50, 100, 200, and/or 400 mg% (mg ethanol per dl water). With a specific gravity of 0.789 g/ml, pure ethanol weights (e.g., 25 mg for the 25 mg% standard stock solution above) must be divided by 0.789 to calculate the volume of stock required [in this case, 31.6 ml] to add to 100 ml of the distilled/deionized water to make a 25 mg% stock solution. Store these stock solutions capped at 4°C for months. Use the same volume of standard in borosilicate glass tubes as for your blood or serum samples (see Notes 3, 13, and 14). 3.5.2. Sample Preparation for the GC Assessment

1. Blood option for GC: Blood obtained from any method is appropriate. A simple method is the tail tip nick, where the skin at the very last 2 mm or so of tail can be clipped perpendicular to the tail and the tail “milked” from the base toward the tip to get a drop or drops. As little as 6 ml is adequate for the preparation methods described next. A day or so prior to blood sampling, prepare the 12 × 75 borosilicate glass tubes containing the sodium chloride and water. Cap with the rubber stoppers compatible with needle punctures for sampling of air, then add 6 ml or more of freshly isolated blood or stored serum (use a fixed volume for all samples), and place into the water/salt solution at the bottom of the tube. Gently swirl, then store on ice or at 4°C, and prepare standards the same way. To prepare standards, create tubes with the same 6-ml volumes of ethanol stock solutions (instead of blood) prepared earlier. These concentrations need to cover the expected range of blood ethanol in the study. Place identical volumes of the blood or stock ethanol solutions into the preprepared salt/ water tubes, cap with the rubber caps, store on ice or 4°C, and then run in the head space gas protocol within a day or so. 2. Headspace gas protocol: Take each of the tubes containing blood or standards and place one at a time (at intervals noted below) into a 55°C water bath such that the hot water comes up to but does not touch the rubber cap. For a typical chromatograph, example intervals are 4 min with software-defined run times of about 3.75 min per sample. These values can be customized based on air/hydrogen mixes and flow rates. Incubate each sample for 10 min before drawing a 1.5 ml air sample (via the 25-gauge needle and 3-ml plastic syringe equipped with a cutoff valve) from the space above the liquid

13


225

in the heated tube and closing off the syringe with the valve. Rapidly twist off the needle and place the cutoff value connection to the accommodating port on the GC injector. Insure that the injector lever is in the load position before placing the syringe onto the GC loading port. Quickly, open the cutoff valve, inject the 1.5-ml sample with the syringe plunger, turn the injector lever to the inject position, and finally press the space bar on the laptop to initiate recording of data with the PeakSimple software. Expect a retention time for ethanol peaks of approximately 2.3 min. Later, isolate peak heights and/or area under the curves from automatically saved files for each sample. Convert these to mg% based on the standards that were run identically. 3.5.3. Blood Option for Enzymatic Detection

1. Obtain blood as per preferred methods (e.g., 100–200 ml). 2. Spin at 6,000 rpm at 2,300 × g for 10 min to separate serum. 3. Store serum frozen until ready to inject 10 ml directly into an instrument, such as the Analox analyzer. 4. An example of Enzymatic detection is described in ref. 13. Blood sample is centrifuged for 5 min at 1,800 × g and then stored at −20°C until analysis Blood ethanol concentrations are assessed with a GM7 Alcohol Analyser. Based on the rate of oxygen consumption as ethanol is converted to acetaldehyde, it is compared to an external standard (300 mg/dl). Data are presented as mg% or mg/dl.

3.6. Breathylizer Strategies

1. Mice A convenient, indirect method of relatively innocuous repeat testing of blood ethanol in the same animal is to use breath samples and convert (with a standard curve of preestablished blood/breath concentration ratio) to blood ethanol in mg% or mg/dl. The 50-ml conical-end centrifuge tube works well for this purpose as adapted for both mice and rats (see setup in Fig. 6; Subheading 2.7.2, and see Notes 14 and 15). The mouse rebreathing tube is just the original tube with the needle hole in the conical end. Mice up to about 30–35 g are allowed to enter the tube (which many tend to do with a minimum of guidance) to about 3 cm from the conical end and are held there gently by their tails (larger mice may require a slightly larger tube). Their body closes off the air pocket in front of the mouse’s nose. The mouse is retained in this position for period of 15 s during which time lung ethanol and the tube interior (between the mouse’s head and conical end of the tube) equilibrate such that a 1.5-ml sample of ethanolladen rebreathed air can be drawn into a syringe through a needle placed 2 cm into the tube through a small hole (in the

226


closed end of the tube) that just accommodates the needle. This sample is then immediately injected into the GC as described above for running blood samples. The rebreathing tube, syringe, and injection port area are flushed with fresh air, cleaned of urine if present (mice), and the collection/injection process begun anew. When calibrating breath to blood ratios for experimental conditions, use the blood ethanol method above and the breath ethanol method in the same animal at different time points and/or additional animals known to have higher or lower blood levels. 2. Rats A similar air sampling apparatus is used (see Fig. 6) that accommodates just the rat’s head up to approximately its ears. However, the rat rebreathing tube is created by cutting off the conical end of the centrifuge tube and smoothing the new ring surface with sandpaper. The rat is held gently in this position for the 15-s requisite rebreathing period prior to sampling the 1.5 ml of air from the other end of the tube with the syringe/ needle. Process the sample as per the mouse methods above (see Note 15).

4. Notes 1. Two points: First, rats and mice that prefer to drink ethanol solutions relative to water are available. These include alcoholpreferring P rats from Indiana University and other such selectively bred or inbred drinking lines. Similarly in the mice, C57 mice tend to drink more than many others. However, consumption or preference for ethanol may not be the focus if ethanol withdrawal is the primary goal. In the latter case, getting ethanol into animals does not require the face validity of the voluntary intake route to provide useful behavioral phenotypes associated with ethanol withdrawal. Second, with behavioral phenotypes, be sensitive to the fact that a given rodent line may not provide the same effect as another line. Thus, it is best to stick with that line or be prepared to rederive the phenotype with parametric adjustments to the protocol. 2. Request that the company deliver the lactalbumin in individual units compatible with volumes of diet being made on any given day. The lactalbumin is quite dry and powdery and can get into the air and deposit on lab benches; therefore, the less daily handling/measuring, the better. Consider doing this step in a hood.

13


227

3. When using new/fresh conical centrifuge tubes for sampling breath, be sure to uncap them after receiving them from the supplier and allow the various volatiles from the manufacturing process to dissipate. Failure to do this step leads to peaks on the chromatograph that may interfere with the ethanol peaks. A quick sniff of a newly opened tube makes this point clear. 4. The different concentrations of ethanol in the diet permit the investigator some control over the magnitude of the ethanol consumed per day and the subsequent magnitude of withdrawal while maintaining similar total caloric intake between experimental animals and controls over the exposure days. 5. A green generic food dye can be added to the 95% ethanol solution (e.g., 50 drops per gallon of 95% ethanol) so that all solutions applied via diet or water/ethanol solutions (and their concentrations) are easily identified in their stock containers and on the cages. 6. Various diets are available; representative ones are described herein. Other diets with nutritional differences and alcohol contents are possible for various purposes, but in each case, whether crafting a new one or employing an existing one, they should address the nutritional needs of rodents and the need for caloric and nutritional balancing across controls and ethanol-exposed subjects. 7. Sometimes, rats or mice initially resist drinking the diet, particularly with higher ethanol concentrations. Give them a couple of days on the respective control diets if the design allows so as to permit adjustment to the novel food source. Also, starting the rats on 7% or higher solutions can sometimes be problematic, so progress from 4.5% through 7% over a few days to insure that weekly body-weight gains are balanced across the animals. And do not forget to remove their regular chow before initiating the liquid diet! For mice, solutions ranging of 2.4 or 4.8% seem to be adequate although the specific dietary components and mouse line may alter the useful range. 8. It is advisable to keep the treatment room and testing rooms quiet and to avoid cage changes and/or weighings on the day of test. Avoid perfumes and any other sounds/smells that would be noticeable, particularly novel ones. Avoid having new people engage the project at this point and avoid introducing new routines or events. 9. This procedure creates a significantly compromised animal. Thus, considerable attention should be paid to the animal’s health status (including checking body weights, breathing rates, eye closures/ointments). Given the hypothermia created by the high-dose ethanol, room temperatures below normal should be avoided.

228


10. Significant care must be taken to avoid entering the trachea and or dispensing fluid prior to entering the stomach. 11. Such gastric procedures generally expose the animals to highly intoxicating blood levels of ethanol. Thus, getting a reasonably normal amount of daily calorie intake can be challenging. That is, infusion volumes are generally restricted to a maximum of ±10–15 ml depending on the size of the rat (and with multiple infusions per day, volumes and associated calories of subsequent doses may need to be restricted further). With these volumes and ethanol concentrations, the rats will likely not consume any chow for eight or more hours after the infusions due to intoxication and thus they may not be able to make up the caloric deficit. While three infusions per day provide more calories from the infusions, less (or none) may come from eating chow. Thus, be cognizant of the combined caloric intakes, monitor body weights, and restrict the number of days of the study as necessary. 12. Alcohol-preferring P rats and other alcohol-preferring rodents vary (across animals and across days) in the amount of ethanol that they willingly consume; therefore, the resultant withdrawal syndrome may vary in magnitude. Individual subjects that drink little alcohol for whatever reason should be removed from the study and/or an empirically derived criterion set for the minimum consumption required for the particular rodent to show a withdrawal reaction after a defined ethanol exposure period. 13. Generally, a range of 6 ml (when moderate to very high blood ethanol levels are expected) up to 50 or 100 ml (when very low blood ethanol levels are expected) suffices. What matters more is that standard samples and blood samples are identical in volume. 14. While the blood ethanol detection methods herein are wellsuited for determining relative differences in blood ethanol across experimental groups within or across studies and for providing close estimates of absolute blood ethanol levels, investigators should know that limited differences in blood versus serum ethanol have been noted and should be considered when absolute levels are desired. Readers are encouraged to consider these issues as discussed in the work of Brick (25). Furthermore, extrapolation from breath to blood should be done carefully as described above. Finally, initially, use repeated breath and blood sampling to get a sense of the variability resulting from the technique. 15. This method is ideal for repeat testing as the frequency of sampling can be as often as a few minutes (or less frequent depending on the retention time of the sample in the chromatograph).

13


229

Acknowledgment This work was supported in part by AA017462 and AA011605 from NIAAA. References 1. Ballenger, J. C., and Post, R. M. (1978) Kindling as a model for alcohol withdrawal syndromes, Br J Psychiatry 133, 1–14. 2. Brown, M. E., Anton, R. F., Malcolm, R., and Ballenger, J. C. (1988) Alcohol detoxification and withdrawal seizures: clinical support for a kindling hypothesis, Biol Psychiatry 23, 507–514. 3. Malcolm, R., Roberts, J. S., Wang, W., Myrick, H., and Anton, R. F. (2000) Multiple previous detoxifications are associated with less responsive treatment and heavier drinking during an index outpatient detoxification, Alcohol 22, 159–164. 4. Chu, K., Koob, G. F., Cole, M., Zorrilla, E. P., and Roberts, A. J. (2007) Dependence-induced increases in ethanol self-administration in mice are blocked by the CRF1 receptor antagonist antalarmin and by CRF1 receptor knockout, Pharmacol Biochem Behav 86, 813–821. 5. Lee, S., Schmidt, D., Tilders, F., Cole, M., Smith, A., and Rivier, C. (2000) Prolonged exposure to intermittent alcohol vapors blunts hypothalamic responsiveness to immune and non-immune signals, Alcohol Clin Exp Res 24, 110–122. 6. Becker, H. C., and Hale, R. L. (1993) Repeated episodes of ethanol withdrawal potentiate the severity of subsequent withdrawal seizures: an animal model of alcohol withdrawal “kindling”, Alcohol Clin Exp Res 17, 94–98. 7. Griffin, W. C., 3rd, Lopez, M. F., and Becker, H. C. (2009) Intensity and duration of chronic ethanol exposure is critical for subsequent escalation of voluntary ethanol drinking in mice, Alcohol Clin Exp Res 33, 1893–1900. 8. Frye, G. D. a. E., FW (1975) Audiogenic evaluation of withdrawal excitability in rats after chronic ethanol feeding. Pharmacologist 17, 197, 1975., Pharmacologist 17, 1. 9. McCown, T. J., and Breese, G. R. (1990) Multiple withdrawals from chronic ethanol “kindles” inferior collicular seizure activity: evidence for kindling of seizures associated with alcoholism, Alcohol Clin Exp Res 14, 394–399. 10. Wills, T. A., Knapp, D. J., Overstreet, D. H., and Breese, G. R. (2008) Differential dietary

11.

12.

13.

14.

15.

16.

17.

18.

19.

ethanol intake and blood ethanol levels in adolescent and adult rats: effects on anxiety-like behavior and seizure thresholds, Alcohol Clin Exp Res 32, 1350–1360. Wills, T. A., Knapp, D. J., Overstreet, D. H., and Breese, G. R. (2010) Interactions of stress and CRF in ethanol-withdrawal induced anxiety in adolescent and adult rats, Alcohol Clin Exp Res 34, 1603–1612. Janis, G. C., Devaud, L. L., Mitsuyama, H., and Morrow, A. L. (1998) Effects of chronic ethanol consumption and withdrawal on the neuroactive steroid 3alpha-hydroxy-5alphapregnan-20-one in male and female rats, Alcohol Clin Exp Res 22, 2055–2061. Morris, S. A., Kelso, M. L., Liput, D. J., Marshall, S. A., and Nixon, K. (2010) Similar withdrawal severity in adolescents and adults in a rat model of alcohol dependence, Alcohol 44, 89–98. McCown, T. J., Greenwood, R. S., Frye, G. D., and Breese, G. R. (1984) Electrically elicited seizures from the inferior colliculus: a potential site for the genesis of epilepsy?, Exp Neurol 86, 527–542. McCown, T. J., Duncan, G. E., Johnson, K. B., and Breese, G. R. (1995) Metabolic and functional mapping of the neural network subserving inferior collicular seizure generalization, Brain Res 701, 117–128. Paxinos, G., and Watson, C. (1986) The Rat Brain in Stereotaxic Coordinates, Academic Press, New York. Navarro, M., Cubero, I., Knapp, D. J., and Thiele, T. E. (2003) MTII-induced reduction of voluntary ethanol drinking is blocked by pretreatment with AgRP-(83–132), Neuropeptides 37, 338–344. Overstreet, D. H., Knapp, D. J., and Breese, G. R. (2002) Accentuated decrease in social interaction in rats subjected to repeated ethanol withdrawals, Alcohol Clin Exp Res 26, 1259–1268. Majchrowicz, E. (1975) Induction of physical dependence upon ethanol and the associated behavioral changes in rats, Psychopharmacologia 43, 245–254.

230


20. Knapp, D. J., and Crews, F. T. (1999) Induction of cyclooxygenase-2 in brain during acute and chronic ethanol treatment and ethanol withdrawal, Alcohol Clin Exp Res 23, 633–643. 21. Knapp, D. J., Saiers, J. A., and Pohorecky, L. A. (1993) Observations of novel behaviors as indices of ethanol withdrawal-induced anxiety, Alcohol Alcohol Suppl 2, 489–493. 22. Jarvis, M. F., and Becker, H. C. (1998) Single and repeated episodes of ethanol withdrawal increase adenosine A1, but not A2A, receptor density in mouse brain, Brain Res 786, 80–88. 23. Kampov-Polevoy, A. B., Matthews, D. B., Gause, L., Morrow, A. L., and Overstreet, D. H.

(2000) P rats develop physical dependence on alcohol via voluntary drinking: changes in seizure thresholds, anxiety, and patterns of alcohol drinking, Alcohol Clin Exp Res 24, 278–284. 24. Overstreet, D. H., Knapp, D. J., and Breese, G. R. (2007) Drug challenges reveal differences in mediation of stress facilitation of voluntary alcohol drinking and withdrawal-induced anxiety in alcohol-preferring P rats, Alcohol Clin Exp Res 31, 1473–1481. 25. Brick, J. (2006) Standardization of alcohol calculations in research, Alcohol Clin Exp Res 30, 1276–1287.

Chapter 14 Rat Models of Prenatal and Adolescent Cannabis Exposure Jennifer A. DiNieri and Yasmin L. Hurd Abstract Marijuana (Cannabis sativa) is the illicit drug most commonly used by two vulnerable populations relevant to neurodevelopment—pregnant women and teenagers. Human longitudinal studies have linked prenatal and adolescent cannabis exposure with long-term behavioral abnormalities as well as increased vulnerability to neuropsychiatric disorders in adulthood. Animal models provide a means of studying the neurobiological mechanisms underlying these long-term effects. This chapter provides an overview of the animal models we have used to study the developmental impact of cannabis. Key words: Δ-9-Tetrahydrocannabinol, Cannabinoid, Drug addiction, Neurodevelopment, Perinatal

1. Introduction Marijuana (Cannabis sativa) is the illicit drug most used in Western societies. This has important implications to two vulnerable subgroups of individuals given that cannabis exposure is prominent during prenatal and adolescent developmental periods. Approximately 4% of women in the USA report using illegal drugs with marijuana being by far the illicit drug most commonly abused during pregnancy (75%) (1). The prevalence of prenatal cannabis exposure is also between 2 and 5% in European countries (2–4), reaching even up to 13% in high-risk populations (5). One-third of Δ9-tetrahydrocannabinol (Δ9-THC), the major psychoactive component of cannabis (6), undergoes cross-placental transfer upon cannabis smoking (7), raising concerns about the potential impact of maternal cannabis use on the developing fetus. A number of studies have reported increased rates of fetal distress, growth retardation, and adverse neurodevelopmental outcomes with prenatal cannabis exposure (7–9). The pathogenic impact of cannabinoids on the CNS is underscored by several epidemiological and clinical studies documenting impulsive behavior, social deficit, cognitive Firas H. Kobeissy (ed.), Psychiatric Disorders: Methods and Protocols, Methods in Molecular Biology, vol. 829, DOI 10.1007/978-1-61779-458-2_14, © Springer Science+Business Media, LLC 2012

231

232

J.A. DiNieri and Y.L. Hurd

impairment, consumption of addictive substances, and psychiatric disorders (e.g., schizophrenia, depression, and anxiety) in adult individuals with in utero cannabis exposure (10–16). Adolescence is also a critical phase of brain development that is particularly sensitive to external and internal variables, such as drug exposure, environment, and gonadal hormones, since there are active neural changes in, e.g., synapse formation and elimination in brain areas essential for behavioral and cognitive functions (17, 18). Among drugs of abuse, cannabis is the most frequently used by teenagers with as much as 20% of 16-year olds in the US reporting use (1). Clinical evidence has confirmed an increased vulnerability to neuropsychiatric and drug abuse disorders with adolescent cannabis exposure. Early-onset cannabis use is associated with an increased risk of developing schizophrenia (19–21) as well as a worsened course of the disorder (22, 23). Epidemiological studies have consistently found that adolescent cannabis exposure precedes the use of heavy drugs, such as heroin (24–26). Such “gateway” associations could reflect the normal sequence of events in drug-dependence disorders so that substances to which teenagers have easy access (e.g., marijuana, tobacco, alcohol) are abused prior to the use and subsequent abuse of heavier illicit drugs. Many issues, such as culture, family history, and peer pressure can influence the progression from cannabis experimentation to abuse of other substances. However, the gateway associations could also reflect actual neurobiological disturbances to early cannabis exposure that make individuals more vulnerable to the reinforcing effects of other drugs. The multifactorial confounds of the “gateway” phenomena have made it difficult to make definitive causal links between cannabis use and subsequent abuse of other illicit drugs. One strategy to directly evaluate the relationship of prior cannabis experience with specific drugs independent of cultural, social, and moral factors is the use of experimental animal models. This chapter provides an overview of prenatal and adolescent rodent models that we have employed to study the developmental impact of cannabis. We outline basic experimental procedures and provide an overview as to potential weaknesses and limitations that must be considered. Overall, despite the challenges in mimicking developmental cannabis exposure in animal models, such experimental approaches are essential in being able to systematically explore the specific neurobiological mechanisms altered by cannabis that impact adult behavior and the vulnerability to neuropsychiatric disorders.

2. Materials 2.1. Prenatal/Perinatal THC Rodent Model

1. Subjects. Long Evans rats (M&B Taconic, New York, USA) have been used to conduct our experiments, but the conditions used are similar for other rat strains, such as Sprague-Dawley

14

Rat Models of Cannabis Exposure

233

animals. Adult female (6–7-weeks old, 150–175 g) and male (8-weeks old, 250–275 g) rats are usually used. 2. Drugs. Δ9-THC (10 mg/ml in ethanol solution; Sigma– Aldrich, Sweden) evaporated under nitrogen gas, dissolved in 0.9% NaCl with 0.3% Tween 80; Vehicle (VEH, 0.3% Tween 80–sterile saline solution). 3. IV administration. The sterile catheter (Brian Fromant Cambridge, UK) consisting of a silastic tubing (»10 cm, ID 0.30 mm × OD 0.64 mm) is used.

3. Methods 3.1. Prenatal/Perinatal THC Rodent Model

The first step in developing an appropriate animal model is consideration of the obvious species differences in regard to developmental ontogeny. For example, prenatal brain development in humans does not correspond to the same developmental period in rats: rat perinatal period, which extends up to approximately postnatal day (PND) 21, is comparable to the third trimester in humans and PND0–PND2 in the rodent is generally comparable to midgestation in humans. A good online resource (http://translatingtime. net/) which translates specific developmental periods across species is by Clancy and colleagues (27). In this section, we focus on our prenatal animal model that is relevant to the early phase of human development since many women discontinue or significantly reduce drug use during later stages of pregnancy (28). Therefore, evaluation of the early to midgestational period is particularly important to determine whether early cannabis exposure could be harmful to the maturation of the fetus. However, animal models can explore cannabinoid exposure well into the perinatal period to examine the consequences of drug exposure during the entire developmental period. An important consideration when developing an animal model of cannabis exposure is determining which cannabinoid to examine given the chemical complexity of the cannabis plant, which produces over 400 compounds, including approximately 80 phytocannabinoids (29–33). By far, the most well-studied phytocannabinoid is Δ9-THC, which mediates the primary psychoactive effects of cannabis and binds to specific cannabinoid (CB1 and CB2) receptors. It is important to recognize, however, that while Δ9-THC receives the most scientific attention other cannabinoids are also under investigation. For example, exciting new research from our group shows that cannabidiol, a nonpsychoactive constituent of cannabis, inhibits cue-induced heroin seeking and normalizes discrete mesolimbic neuronal disturbances suggesting that cannabidiol may be a potential

234


treatment for heroin craving and relapse (34). Given that cannabinoids other than Δ9-THC also impact neuronal systems relevant to addiction, many animal models of cannabis exposure involve administration of a crude marijuana extract, which is made up of varied cannabinoids, including Δ9-THC, cannabidiol, and cannabinol. Results from studies that have evaluated the effects of developmental Δ9-THC or crude extracts have documented significant short- and long-term impairments on discrete neurobiological systems (35–42). The decision of which cannabinoid or combination of cannabinoids to study ultimately depends on the experimental question being addressed by the investigator. The route of cannabinoid administration is also an important consideration when developing a rat model of cannabis exposure. The selection of an appropriate route of administration depends on a number of factors, including the pharmacokinetics of the drug. We have utilized an intravenous route of Δ9-THC administration in our prenatal rat model since this route of administration more closely mimics the pharmacokinetics of cannabis smoking, the route of administration most commonly used by pregnant women who consume cannabis during pregnancy. Intravenous (IV) drug administration has the added advantage of rapid response, high bioavailability (the total dose is administered into the blood stream), and reduced irritation in response to solutions that may contain irritant drugs. While we find an IV route of administration suitable for our studies, there are disadvantages associated with this type of administration, including the need for trained personnel to perform an invasive surgery under sterile conditions and potentially enhanced toxicity due to rapid onset of the drug action. To circumnavigate these difficulties, most rat models of cannabis exposure have utilized an oral route of administration. However, an oral route of drug administration also has certain disadvantages, including poor bioavailability, first-pass effect, food effects (absorption can be slower or faster with food), and potential respiratory difficulty following oral gavage. Given the constraints of the experiment, other routes of administration (subcutaneous, inhalation) may also be considered. Of the various routes, intraperitoneal is not advisable for drug administration to pregnant females. 3.1.1. Protocol: Rat Prenatal Model of Cannabis Exposure

The following section provides a detailed description of our rat prenatal cannabis exposure model (Fig. 1). Important technical issues to consider at each stage of the model are provided in Subheading 4. 1. Subjects: We typically have conducted our studies on Long–Evans rats, but the conditions used are similar for other rat strains, such as Sprague-Dawley animals. Adult female (6–7-weeks old, 150–175 g) and male (8-weeks old, 250–275 g) rats are acclimated

14


235

Fig. 1. Schematic overview of rat model of prenatal Δ9-THC exposure. The neurobiological impact of prenatal Δ9-THC exposure can be assessed in the brains of offspring at birth and/or at various developmental periods into adulthood when behavioral parameters can also be investigated. GD gestation day, PND postnatal day, VEH vehicle.

to the colony and housed in separate rooms under a 12-h light/dark cycle with controlled room temperature and humidity. Housing conditions include nesting material, which serves as environmental enrichment. 2. Surgery: Adult female rats are surgically implanted with an IV catheter aimed at the right jugular vein to allow for subsequent IV Δ9-THC administration. The sterile catheter (Brian Fromant Cambridge, UK) consisting of a silastic tubing ( 10 cm, ID 0.30 mm × OD 0.64 mm) is placed into the vein and the other end, which provides the portal for subsequent drug infusion, is tunneled subcutaneously and exits the scapular region on the back. After surgery, rats receive daily IV injections of heparin (10 U) and ampicillin (50 mg/kg) for 3 days to prevent infection and subcutaneous injection of Caprofen (0.5 mg) as postsurgery pain management. Catheters are routinely flushed with 0.1 ml of saline containing 30 U heparin. Once recovered from surgery (2 weeks, see Note 1), the patency of each catheter is tested with a single IV injection of Brevital (10 mg/ml, 0.1– 0.2 ml), a fast and short-acting barbiturate anesthetic. Females that show a freezing behavior in response to Brevital, indicative of a clear and open catheter, are paired with a male for mating. 3. Mating: Males and females are pair housed (two females:one male, see Note 2) for 5 days to ensure that each female goes through at least one estrous cycle, which occurs every 4 days in the rat (see Note 3). After 5 days of mating, females are individually housed and the day of separation is recorded as gestation day 1 (GD1). Pregnant females (see Note 4) are subsequently entered into the treatment phase of the experiment. 4. Treatment paradigm: Pregnant female rats are treated with daily IV injections of either Δ9-THC (0.15 mg/kg) or VEH (0.3% Tween 80–sterile saline solution) from GD5–PND2 (~3 weeks), which corresponds to the midgestation (» gestation week 20) development

236


stage in humans. This particular dose of THC was extrapolated from estimates of low-dose cannabis cigarettes (~16 mg of THC) after correcting for differences in route of administration and body weight. During the course of treatment, a number of gestational and offspring parameters are recorded, including maternal weight gain, gestational length, treatment duration, litter size, fetal sex, and body weight (see Note 6). 5. Culling of litters: Following birth, pups can either be sacrificed if that is the end point or they can continue to be studied into later developmental periods. If the latter option is chosen, then an important consideration is whether or not culling of litters should be performed. Litter size influences a number of critical experimental parameters (29). For example, pup body weight gain during lactation is inversely proportional to litter size (43–46). This relationship is associated with milk availability, which generally increases with litter size, but is not without problems as evidenced by lack of increase in milk yield in litters greater than 11 pups (45). Litter size also impacts the variability in pup body weight, which decreases sensitivity of statistical analysis (43, 47). Postnatal development is also affected by litter size. Developmental delays in maturation end points, including eye opening and pinna detachment, have been reported in large litters compared to small litters (47, 48). Litter size also impacts motor behavior, reflex, emotion, and memory in offspring (47, 48). In light of these findings, we consider culling to be a highly desirable procedure. The number of pups born to a female dam varies depending on the strain of rat studied by the investigator. Our studies utilize Long–Evans dams that deliver litters of approximately 13 pups. We normally cull litters on PND2 (see Note 7) to eight to ten pups, which is optimum in reducing adverse effects on pup growth and development (see Note 8). When possible, culled litters should consist of an equal number of males and females, since studies have reported differences in maternal behavior toward one sex over the other (49). 6. Cross-fostering pups: Pups that are studied after birth are cross fostered so that all offspring are raised by VEH-treated dams and no dams raise their own pups (see Note 9). Such an approach should enable the possibility to assign neurodevelopmental alterations in the offspring as being due to prenatal Δ9-THC exposure rather than from other confounds, such as potential poor maternal care of the dams exposed to Δ9-THC during pregnancy. Another approach is to cross foster the litters to surrogates which have not undergone any surgical or experimental manipulations. On PND21, Δ9-THC- and VEH-treated offspring

14


237

are weaned and allowed to mature until they reach the developmental period relevant to the experimental question. 7. Tissue and blood collection: Our paradigm allows the possibility to study brains at either birth or at different developmental periods, including adulthood. Neonate rats are highly tolerant to inhalant anesthetics (e.g., CO2, halothane, isoflurane). As such, if an inhalant anesthetic is used as the euthanasia agent, then the exposure period should be sufficiently long (>20 min) to ensure death. It is important to note that a protracted euthanasia condition can, however, alter molecular and biochemical markers of interest. As such, a physical method, such as decapitation or cervical dislocation, is generally carried out with neonates. Another acceptable method for the euthanasia of neonate rats is injection of a chemical anesthetic (e.g., pentobarbital), but again, depending on the research question, a pharmacological euthanasia condition could potentially alter the neurobiological measures of interest. After euthanasia, brains are quickly dissected and freshly frozen in dry ice-cooled isopentane. Trunk blood can also be taken at this time so that blood cannabinoid levels can be measured through toxicological analysis. Brain specimens can be taken at different developmental stages after birth using the appropriate euthanasia agent. 3.2. Adolescence THC Rodent Model

As mentioned above, adolescence is a developmental period of abundant cannabis exposure and various adolescent Δ9-THC animal studies have been published. In general, the adolescent Δ9THC model is less complex than the prenatal condition, but similar issues, such as time period of treatment, cannabinoid studied, and route of drug administration, are all important considerations. Adolescence, unlike puberty, has a diffuse developmental border not only in humans, but also in animals. The conservative adolescence age range in rats extends from PND28–49 (50), but most studies generally examine periadolescence that can cover the juvenile preadolescent period (~PND21-28) and approximately 10 days later consistent with late adolescence that borders on young adulthood (50, 51). As such, depending on the research question, one can study cannabinoid treatment throughout the entire adolescent developmental period or evaluate exposure during different developmental stages, such as early adolescence (starting at ~PND28), mid-adolescence (starting at ~PND38), and late adolescence (starting at ~PND49), with adulthood starting at ~PND61. In regard to route of drug administration, a smoke inhalation or an intravenous self-administration model would perhaps be ideal; however, both are challenging. Smoke inhalation models are not well-developed and rodents do not readily self-administer intravenous Δ9-THC perhaps due to its partial aversive properties.

238


Fig. 2. Schematic overview of a typical rat model of adolescent Δ9-THC exposure. In addition to treatment throughout the full adolescent period, drug exposure could be targeted to specific phases, such as early adolescence (starting at ~PND28), mid-adolescence (starting at ~PND38), and late adolescence (starting at ~PND49).

Moreover, catheterization of young juvenile animals can be challenging and should be followed by a surgical recovery period of ~7 days, which is a problem given the short adolescent period. As such, the adolescent cannabinoid models that we and others have predominantly used have been the intraperitoneal route due to ease and reproducibility. 3.2.1. Protocol: Rat Model of Adolescent Cannabis Exposure

The following section provides a description of our intraperitoneal rat model of adolescent Δ9-THC exposure (Fig. 2). 1. Subjects: PND21 adolescent male (~50 g) are acclimated to the colony with controlled temperature and humidity. If younger animals are obtained from outside vendors, then the rats need to be shipped with the dams since weaning is normally around PND21. Housing conditions include nesting material, which serves as environmental enrichment. An important consideration for choosing a particular drug treatment paradigm is whether the animals should be individually or group housed. Again, these considerations are dependent on the specific research question. Individual housing is optimal if an intravenous route of administration is used since, as discussed for the prenatal Δ9-THC model, the protrusion of the catheter from the rat’s back is susceptible to damage from other animals. The use of chemical retardants is perhaps not as useful for group housing conditions for extended periods. If a nonintravenous route of administration is chosen, then the animals could be group housed. 2. Treatment paradigm: Various treatments can be carried out that can either extend throughout the adolescent period or at specific phases. For example, we have used a paradigm in which juvenile male rats receive Δ9-THC (1.5 mg/kg, ip) or VEH (0.3% Tween

14


239

80–sterile saline solution, ip) once every 3rd day in their home cage from PND28 to 49 of the early to mid-late adolescence period. The dosing regimen is based on our data, which showed that intermittent administration of this low-moderate dose of Δ9-THC was sufficient to induce significant behavioral differences in heroin self-administration behavior as well as longlasting molecular alterations during adulthood (52, 53). Higher, daily doses of Δ9-THC would likely produce even greater alterations, especially relevant to subpopulation of heavy cannabis users, but the normal pattern of cannabis use in teenagers is generally periodic. 3.3. Summary

Overall, there is significant flexibility in carrying out the developmental cannabinoid rat model to vary the type of cannabinoid studied, dosing, duration of treatment, and/or developmental phase of exposure depending on the research question of interest. Of the developmental models, the prenatal condition has many challenges and multiple issues that must be considered that can significantly impact the success of the experiment and interpretation of the data. Despite the apparent challenges, we have, for example, been able to document similar neurobiological changes in our prenatal rat model (39) to those seen in human fetuses with in utero cannabis exposure (54). Such findings support the validity of the animal models that can now be used to provide much-needed insight into the neurobiological mechanisms underlying developmental cannabis exposure that are highly related to neuropsychiatric disorders.

4. Notes 1. Adult female rats should be given approximately 2 weeks to recovery from catheterization surgery before mating is initiated to allow complete healing of their wound. Mating conducted within a shorter recovery time may aggravate the wound leading to pain, stress, inflammation, and other adverse effects for the female rats. 2. In our experience, mating rats for 5 consecutive days is sufficient to produce females that are pregnant. Vaginal cytology can also be evaluated to establish that the rat is in estrus and mating only subsequently carried out under such conditions, but daily vaginal swabbing can itself alter the estrus cycle by inducing stress. 3. While it is not necessary to check for vaginal plugs in female rats that are mated throughout the estrus cycle to determine whether or not they are pregnant, the plugs help to provide strong evidence of pregnancy.

240


4. Most catheters are designed to protrude from the back region and the catheters on the female rats are, therefore, vulnerable to damage by male animals during mating. In order to minimize chewing and thus prevent damage to the catheter, a threaded metal cover can be placed over the catheter. A chemical barrier may also be necessary to prevent chewing of the catheter plastic pedestal, which might not be protected by the metal cover. Chemical barriers are commonly used by veterinarians to prevent chronic licking, and a variety of such substances are commercially available, such as YUK-2e, a nontoxic bitter tasting gel. This gel can be applied once a day to the base of the catheters using a sterile, disposable cotton tip applicator. 5. Δ9-THC treatment is initiated at GD5 in our prenatal model since administration of the drug at earlier stages of pregnancy has noted adverse effects and can induce spontaneous abortions. 6. The dose and treatment conditions chosen depend on the research question. While it is ideal to have a dose and treatment condition that lack any significant effects on general developmental parameters, it is possible that the research question requires the use of moderate to large doses that can potentially impact fetal growth as documented in human fetuses with in utero cannabis exposure (4, 7, 55). Under such conditions, it is advisable that developmental outcome variables are considered in the statistical analysis. In addition, another nondrug control group could be included in the experimental design in which, e.g., body weight is altered to the same extent as the cannabinoid-treated animals. Such a control group helps to dissociate neurobiological events induced by the cannabinoid treatment versus that induced by impairment of overall fetal growth. 7. The gestation period for Long–Evans rats varies from 21 to 23 days. As such, pups may be born on different days and this has to be considered in the experimental design. In order to maintain consistency, we normally cull litters at approximately PND2. 8. Various outcome measures of interest can be studied in the offspring of each dam given the large litter size of each dam. Ideally, different subsets of animals (£2 pups/litter/group) should be studied for the outcome measures to avoid litter bias. Another approach to account for any potential litter bias is to include litter as a variable in the statistical analysis. 9. It is important to have a reliable pup identification method for long-term studies, especially if the animals are cross fostered. A number of options are available, including subcutaneous implanted electronic ID chips, ear tags, ear punches, and toe clipping. In our experience, the microtattoo system from Fine Science Tools is a convenient and affordable method that produces permanent identification marks on newborn rat pups that last well into adulthood.

14


241

References 1. SAMHSA, Results from the 2006 National Survey on Drug Use and Health: National Findings. Substance Abuse and Mental Health Services Administration 2007, Rockville, MD: Office of Applied Studies, NSDUH Series H-32, DHHS Publication No. SMA 07-4293 2. Lozano, J., et al. (2007) Prevalence of gestational exposure to cannabis in a Mediterranean city by meconium analysis. Acta Paediatr. 96, 1734–7 3. El Marroun, H., et al. (2008) Demographic, emotional and social determinants of cannabis use in early pregnancy: The Generation R study. Drug Alcohol Depend. 98, 218–26 4. Fergusson, D.M., L.J. Horwood, and K. Northstone (2002) Maternal use of cannabis and pregnancy outcome. Bjog. 109, 21–7 5. Williamson, S., et al. (2006) Determination of the prevalence of drug misuse by meconium analysis. Arch Dis Child Fetal Neonatal Ed. 91, F291–2 6. Pertwee, R.G. (2008) The diverse CB1 and CB2 receptor pharmacology of three plant cannabinoids: delta9-tetrahydrocannabinol, cannabidiol and delta9-tetrahydrocannabivarin. Br J Pharmacol. 153, 199–215 7. Hurd, Y.L., et al. (2005) Marijuana impairs growth in mid-gestation fetuses. Neurotoxicol Teratol. 27, 221–9 8. Day, N.L., et al. (1994) Alcohol, marijuana, and tobacco: effects of prenatal exposure on offspring growth and morphology at age six. Alcohol Clin Exp Res. 18, 786–94 9. Fried, P.A. (1995) Prenatal exposure to marihuana and tobacco during infancy, early and middle childhood: effects and an attempt at synthesis. Arch Toxicol Suppl. 17, 233–60 10. Fried, P.A. and B. Watkinson (2001) Differential effects on facets of attention in adolescents prenatally exposed to cigarettes and marihuana. Neurotoxicol Teratol. 23, 421–30 11. Arseneault, L., et al. (2002) Cannabis use in adolescence and risk for adult psychosis: longitudinal prospective study. Bmj. 325, 1212–3 12. Patton, G.C., et al. (2002) Cannabis use and mental health in young people: cohort study. Bmj. 325, 1195–8 13. Richardson, G.A., N.L. Day, and L. Goldschmidt (1995) Prenatal alcohol, marijuana, and tobacco use: infant mental and motor development. Neurotoxicol Teratol. 17, 479–87 14. Huizink, A.C. and E.J. Mulder (2006) Maternal smoking, drinking or cannabis use during pregnancy and neurobehavioral and cognitive

15. 16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

functioning in human offspring. Neurosci Biobehav Rev. 30, 24–41 Kandel, D.B. (2003) Does marijuana use cause the use of other drugs? Jama. 289, 482–3 Porath, A.J. and P.A. Fried (2005) Effects of prenatal cigarette and marijuana exposure on drug use among offspring. Neurotoxicol Teratol. 27, 267–77. Epub 2005 Jan 8 Rice, D. and S. Barone, Jr. (2000) Critical periods of vulnerability for the developing nervous system: evidence from humans and animal models. Environ Health Perspect. 108 Suppl 3, 511–33 Charmandari, E., et al. (2003) Pediatric stress: hormonal mediators and human development. Horm Res. 59, 161–79 Arseneault, L., et al. (2002) Cannabis use in adolescence and risk for adult psychosis: longitudinal prospective study. Bmj. 325, 1212–3 Fergusson, D.M., L.J. Horwood, and N.R. Swain-Campbell (2003) Cannabis dependence and psychotic symptoms in young people. Psychol Med. 33, 15–21 van Os, J., et al. (2002) Cannabis use and psychosis: a longitudinal population-based study. Am J Epidemiol. 156, 319–27 Green, A.I., et al. (2004) First episode schizophrenia-related psychosis and substance use disorders: acute response to olanzapine and haloperidol. Schizophr Res. 66, 125–35 Veen, N.D., et al. (2004) Cannabis use and age at onset of schizophrenia. Am J Psychiatry. 161, 501–6 Lynskey, M.T., et al. (2003) Escalation of drug use in early-onset cannabis users vs co-twin controls. J.A.M.A. 289, 427–433 Fergusson, D.M. and L.J. Horwood (2000) Does cannabis use encourage other forms of illicit drug use? Addiction. 95, 505–520 Agrawal, A., et al. (2004) A twin study of early cannabis use and subsequent use and abuse/ dependence of other illicit drugs. Psychol Med. 34, 1227–37 Clancy, B., et al. (2007) Web-based method for translating neurodevelopment from laboratory species to humans. Neuroinformatics. 5, 79–94 Muhuri, P.K. and J.C. Gfroerer (2009) Substance use among women: associations with pregnancy, parenting, and race/ethnicity. Matern Child Health J. 13, 376–85 Izzo, A.A., et al. (2009) Non-psychotropic plant cannabinoids: new therapeutic opportunities from an ancient herb. Trends in Pharmacological Sciences. 30, 515–27

242


30. Mechoulam, R. and L. Hanus (2000) A historical overview of chemical research on cannabinoids. Chem Phys Lipids. 108, 1–13 31. Mechoulam, R., et al. (2007) Cannabidiol – recent advances. Chemistry & biodiversity. 4, 1678–92 32. Pertwee, R.G. (2008) The diverse CB1 and CB2 receptor pharmacology of three plant cannabinoids: delta9-tetrahydrocannabinol, cannabidiol and delta9-tetrahydrocannabivarin. British Journal of Pharmacology. 153, 199–215 33. Turner, C.E., M.A. Elsohly, and E.G. Boeren (1980) Constituents of Cannabis sativa L. XVII. A review of the natural constituents. J Nat Prod. 43, 169–234 34. Ren, Y., et al. (2009) Cannabidiol, a nonpsychotropic component of cannabis, inhibits cueinduced heroin seeking and normalizes discrete mesolimbic neuronal disturbances. J Neurosci. 29, 14764–9 35. Garcia-Gil, L., et al. (1999) Cannabinoid receptor binding and mRNA levels in several brain regions of adult male and female rats perinatally exposed to delta9-tetrahydrocannabinol. Drug Alcohol Depend. 55, 127–36 36. Navarro, M., et al. (1994) Motor behavior and nigrostriatal dopaminergic activity in adult rats perinatally exposed to cannabinoids. Pharmacol Biochem Behav. 47, 47–58 37. Perez-Rosado, A., et al. (2002) Changes in prodynorphin and POMC gene expression in several brain regions of rat fetuses prenatally exposed to Delta(9)-tetrahydrocannabinol. Neurotox Res. 4, 211–8 38. Rodriguez de Fonseca, F., et al. (1991) Effects of pre- and perinatal exposure to hashish extracts on the ontogeny of brain dopaminergic neurons. Neuroscience. 43, 713–23 39. Spano, M.S., et al. (2007) Prenatal cannabis exposure increases heroin seeking with allostatic changes in limbic enkephalin systems in adulthood. Biol Psychiatry. 61, 554–63 40. Vela, G., et al. (1998) Maternal exposure to delta9-tetrahydrocannabinol facilitates morphine self-administration behavior and changes regional binding to central mu opioid receptors in adult offspring female rats. Brain research. 807, 101–9 41. Walters, D.E. and L.A. Carr (1986) Changes in brain catecholamine mechanisms following perinatal exposure to marihuana. Pharmacol Biochem Behav. 25, 763–8 42. Walters, D.E. and L.A. Carr (1988) Perinatal exposure to cannabinoids alters neurochemical

43.

44.

45.

46.

47.

48.

49.

50.

51.

52.

53.

54.

55.

development in rat brain. Pharmacol Biochem Behav. 29, 213–6 Galler, J.R. and G. Turkewitz (1975) Variability of the effects of rearing in a large litter on the development of the rat. Dev Psychobiol. 8, 325–31 Heggeness, F.W., et al. (1961) Weight gains of overnourished and undernourished preweanling rats. J Nutr. 75, 39–44 Kumaresan, P., R.R. Anderson, and C.W. Turner (1966) Effect of litter size upon milk yield and litter weight gains in rats. Rev Tuberc Pneumol (Paris). 30, 41–5 Widdowson, E.M. and C.R. Mc (1960) Some effects of accelerating growth. I. General somatic development. Proc R Soc Lond B Biol Sci. 152, 188–206 Jen, K.C., F. Wehmer, and J. Morofski (1978) Effects of undernutrition and litter size on material variables and pup development. Dev Psychobiol. 11, 279–87 Nagy, Z.M., K.J. Porada, and J.A. Anderson (1977) Undernutrition by rearing in large litters delays the development of reflexive, locomotor, and memory processes in mice. J Comp Physiol Psychol. 91, 682–96 Alleva, E., A. Caprioli, and G. Laviola (1989) Litter gender composition affects maternal behavior of the primiparous mouse dam (Mus musculus). J Comp Psychol. 103, 83–7 Spear, L.P. (2000) The adolescent brain and age-related behavioral manifestations. Neurosci Biobehav Rev. 24, 417–63 Andersen, S.L. (2003) Trajectories of brain development: point of vulnerability or window of opportunity? Neurosci Biobehav Rev. 27, 3–18 Ellgren, M., et al. (2008) Dynamic changes of the endogenous cannabinoid and opioid mesocorticolimbic systems during adolescence: THC effects. Eur Neuropsychopharmacol. 18, 826–34 Ellgren, M., S.M. Spano, and Y.L. Hurd (2007) Adolescent cannabis exposure alters opiate intake and opioid limbic neuronal populations in adult rats. Neuropsychopharmacology. 32, 607–15 Wang, X., et al. (2006) Discrete opioid gene expression impairment in the human fetal brain associated with maternal marijuana use. Pharmacogenomics J. 6, 255–64 Zuckerman, B., et al. (1989) Effects of maternal marijuana and cocaine use on fetal growth. N Engl J Med. 320, 762–8

Chapter 15 Modeling Nicotine Addiction in Rats Stephanie Caille, Kelly Clemens, Luis Stinus, and Martine Cador Abstract Among the human population, 15% of drug users develop a pathological drug addiction. This figure increases substantially with nicotine, whereby more than 30% of those who try smoking develop a nicotine addiction. Drug addiction is characterized by compulsive drug-seeking and drug-taking behaviors (craving), and loss of control over intake despite impairment in health, social, and occupational functions. This behavior can be accurately modeled in the rat using an intravenous self-administration (IVSA) paradigm. Initial attempts at establishing nicotine self-administration had been problematic, yet in recent times increasingly reliable models of nicotine self-administration have been developed. The present article reviews different characteristics of the nicotine IVSA model that has been developed to examine nicotine reinforcing and motivational properties in rats. Key words: Rat model of addiction, Nicotine, Intravenous self-administration, Nose poke, Lever

1. Introduction Addiction to tobacco products is a worldwide problem, with an estimated 100 million people killed by tobacco-related illness in the twentieth century (World Health Organization, Report on the Global Tobacco Epidemic, 2008). The highly addictive properties of tobacco are exemplified by the large proportion of people that become addicted: 35% of men in developed countries and 50% of men in developing countries who try smoking develop tobacco dependence (World Health Organization, 2002); as well as the difficulty in quitting smoking despite the negative consequences on health. The severity of tobacco addiction can be evaluated by different kinds of tools: either specific to tobacco abuse, such as the Fagerström test of nicotine dependence and the Fagerström tolerance questionnaire which both focus on the quantity and the time course of cigarette smoking, or specific to substance abuse and dependence,


243

244

S. Caille et al.

such as the Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV, American Psychiatric Association, 1994) or the International Classification of Diseases (ICD-10, World Health Organization, 1990) which focus on the symptoms related to cigarette smoking and withdrawal. Among the 4,000 chemicals found in tobacco smoke, nicotine is the main component responsible for tobacco addiction. The process of smoking tobacco is a highly effective and rapid way of delivering nicotine: 90% of nicotine that is inhaled is absorbed, reaching the central nervous system in less than 10 s. Once in the brain, nicotine acts as an agonist at nicotinic acetylcholine receptors (nAChRs). The nAChRs are ligand-gated ion channels comprising five subunits. In the brain, receptors express either five alpha subunits (homomeric receptors) or a combination of alpha and beta subunits (heteromeric receptors). The two main types of neuronal nAChRs are the α7 homo-oligomer—characterized by a fast activation, a low affinity, and a high Ca2+ permeability—and the α4β2 hetero-oligomer—typified by a high affinity for nicotine and slow desensitization. Accumulating evidence suggests that α7* and β2*nAChRs are responsible for the addictive properties of nicotine (1, 2). Both subtypes are found in the midbrain area, a region critically important for the rewarding effects of nicotine, and nicotinic antagonists, such as the nonselective mecamylamine (3) or the α4β2*nAChRs selective dihydro-β-erythroidine (DHβE) (4, 5), reduce the rewarding properties of nicotine. A recent study in rats has indicated that the basal level of expression of α4β2*nAChRs predicts the motivation for nicotine intravenous self-administration (IVSA) (6). The appetitive properties of IV nicotine have been shown in humans, primates, and rodents (7–9). Accurately modeling this process is central to developing a clear picture of nicotine addiction and its most appropriate treatment. In animals, several researchers have developed a passive smoke exposure paradigm (10, 11); however, research shows that passive drug intake by rodents produces different responses than when a drug is self-administered (12). For nicotine, a model of voluntary smoke inhalation in rodents is still missing. Addiction to nicotine involves its reinforcing and motivational properties as well as its psychostimulant effects. In rats, the most widely used procedures to assess the reinforcing and appetitive properties of nicotine are conditioned place preference and intravenous nicotine self-administration (see Note 1). Thus far, the best available means for modeling the efficiency of nicotine delivery from cigarettes is the IVSA paradigm. In this chapter, we focus on the IVSA paradigm and the issues associated with its successful execution. We also examine the importance of several issues, such as the choice of the rat strain, age, use or not of prior food training, food restriction, and the operandum needed.

15

Modeling Nicotine Addiction in Rats

245

2. Materials 2.1. RAT: Age and Sex

1. While nicotine is highly addictive in humans, paradoxically, preclinical laboratories have experienced some difficulty in setting up nicotine self-administration that accurately represents this human behavior. Several arguments have been developed to explain this discrepancy and the subjects’ developmental stage has been highlighted as an important issue. 2. Consistent with the early onset of nicotine addiction in adolescents, it has been suggested that nicotine IVSA would be more successful by using adolescent rats which may be more susceptible to the reinforcing properties of nicotine. Comparison of reactivity to nicotine in both the conditioned place preference paradigm and IVSA has revealed that indeed the age of the rodents used might be important in determining the optimal reinforcing effect of nicotine (13–15). 3. However, due to recent improvements of the surgery methods and protocols for nicotine IVSA, adult rats readily acquire nicotine IVSA in the same range of doses than adolescent rats (16). Thus now, the choice of the rats’ age for a nicotine IVSA experiment rather depends on the main objective of the study rather than on methodological issues. 4. In humans, several studies have indicated sex differences in their susceptibility to nicotine addiction and propensity for relapse. Female smokers appear to experience greater difficulty in cessation and tend to show higher rates of relapse (17, 18). Moreover, female smokers show differential sensitivity to nicotine when administered intravenously (3), and to the incentive effects of nicotine and non-nicotine stimuli (19). 5. Regarding the possible existence of sex differences in nicotine IVSA performances in rats, so far, few studies have addressed this topic. Using a standard procedure (nicotine 0.03–0.09 mg/ kg/infusion), it seems that acquisition of self-administration is similar in male and female animals (20–22). However, while there are no sex differences in nicotine intake under a fixed ratio 5 (FR-5) schedule, when the response requirement becomes more demanding under a progressive ratio schedule, female rats work harder to obtain the nicotine reward (22). Thus, nicotine IVSA studies can involve either female or male rats; however, due to the few studies available on nicotine IVSA in female, most of the studies investigating the addictive properties of nicotine are done with male rats.

2.2. RAT: What Strain?

1. Past research examining strain differences in drug IVSA has demonstrated that some strains are more sensitive to the reinforcing effects of drugs of abuse, including nicotine. For

246

S. Caille et al.

instance, in a report using a classic limited access paradigm, neither Lewis nor Fisher or Holtzman rats readily acquired nicotine self-administration, whereas Long–Evans, Wistar, and Sprague-Dawley rats did so (12, 23, 24). 2. Consistent with these strain differences, it has been shown that Fisher rats failed to acquire nicotine self-administration in a long access paradigm (25). However, when given an extended access to nicotine, Lewis (25, 26) rats as well as Wistar (27, 28), Sprague-Dawley (personal communication), and Holtzman (29, 30) rats have been shown to readily self-administer nicotine. 3. Overall, Sprague-Dawley and Wistar strains are most widely used in the study of drugs of abuse, and a wealth of knowledge exists around the behavior and neurobiology of these strains allowing for direct comparison across studies. For these reasons, Wistar and Sprague-Dawley rats are also the most appropriate subjects for nicotine IVSA experiments. 2.3. Catheter Material and Surgery

1. Several types of catheters are available ready-made from specialized companies (e.g., Braintree Scientific Ltd.). In our laboratory, catheters are made using a modified back-mount from Plastic One (Ref # 313-000BM-10-5UP/1/SPC, USA) and SILASTIC laboratory tubing (ID 0.30—OD 0.64; Ref # 508-001, Dow Corning, USA). 2. Animals are deeply anesthetized with ketamine (100 mg/kg) and xylazine (12 mg/kg). The areas over the surgical sites (jugular and back) are shaved and cleaned with an alcohol wipe. A small incision is then made over the right jugular vein and another on the back, between the scapulae. The catheter tubing is then inserted subcutaneously between these incisions. Connective tissue on the neck is dissected away and the right jugular vein is exposed. A 1-cm section of the vein is isolated and a loose ligature is placed anterior and posterior to the catheter insertion site. A small incision is made between the two ligatures and the catheter is inserted into the vein. The catheter is secured by tightening the loose ligature around the catheter. The opposite end of the catheter is then secured on the back and both incision sites are sutured with regular thread stitches. 3. Animals need a minimum of 6 days of postoperative recovery before the initiation of self-administration training. Catheters are flushed daily with a heparinized saline solution (300 IU/ ml, Sanofi Aventis, France) for the whole experiment. During the experiment, rats are treated with antibiotics (see Note 2). If blood cannot be pulled back, catheter patency should be tested (see Note 3).

2.4. Operant Chambers

1. Self-administration chambers (40 × 30 × 37 cm; Imetronic, France) are located away from the colony room in a dimly lit

15


247

room. Chambers are individually housed in sound-attenuation boxes equipped with a white noise speaker (50 dB) and an exhaust fan for ventilation. Each chamber is illuminated by six white LEDs on the ceiling of the box and has a stainless-steel grid floor that allows for waste collection in a removable tray containing maize sawdust. Each chamber has two opaque operant panels on the right and left sides, and two clear Plexiglas walls on the rear and front sides. 2. Chambers can be equipped either with two nose-poke holes or two levers (depending on the operandum chosen): one of the two nose pokes or levers is designated “active” and the other “inactive.” Each response on the active operandum results in activation of the syringe pump containing nicotine (located outside of the box) which is connected to Tygon tubing (Cole Palmer, USA) and attached via a single-channel liquid swivel (Harvard Apparatus, France) to the back-mount cannula connector (Plastic One) of the animal. The Tygon tubing is protected by a stainless-steel spring (0.3 cm ID, 0.5 cm OD) (Aquitaine Ressort, France) that is suspended at the center of the chamber from the swivel tether connector. A counterbalancing weight-pulley device compensates for vertical movements of the animal. 3. Each delivery is signaled by the onset of a cue light above the active operandum, so the rat can better associate its action with the internal state produced by the drug infusion. With nicotine IVSA, these drug-associated cues can be either visual or auditory or a combination of both (see Note 4) (31, 32).

3. Methods 3.1. Operandum

1. We have recently demonstrated that nose-poking rather than lever-pressing operandum better facilitates the acquisition of nicotine IVSA (32). Since nicotine is considered to be a weak reinforcer compared to cocaine or heroin, it may be that IVSA is improved when the operandum is adapted to rodents’ spontaneous exploratory behavior. 2. Rats more readily acquire the self-administration behavior and sustain a higher rate of responding when nose poking for nicotine than those rats lever pressing for the same drug reward. Moreover, the difference in levels of responding during acquisition persists throughout training, across various doses of nicotine, and influences reinstatement of nicotineseeking behavior. Whereas lever pressing produces more stable nicotine IVSA across days and may be more useful for reinstatement testing, it lacks sensitivity to subtle fluctuations in

248

S. Caille et al.

motivation that are more readily detected with nose poking. Therefore, the most appropriate operandum is likely to be dependent on the aim and desired outcomes of any given study (32). 3.2. Food Training/ Food Restriction

Several preclinical studies have reported that the feeding schedule can affect the subsequent pattern of IVSA with various drugs of abuse. The different programs frequently used when conducting nicotine IVSA experiments are food ad libitum, restricted (resulting in modest but constant weight gain), or deprived (normally to 85% of the rats’ free-feeding weight). 1. With respect to nicotine, food deprivation is frequently employed so that rats can be trained to respond with food prior to the onset of nicotine IVSA. Food instrumental training is a protocol classically used to facilitate the acquisition of operant responding (32–35). Typically, training takes place 1–3 days prior to surgery. Rats are food deprived and placed in the same operant chambers as those that are used for drug self-administration. They learn to respond on a FR-1 schedule of reinforcement, with each operant response resulting in the delivery of a 45-mg food pellet. Importantly, there is no presentation of the cue that is then associated with the delivery of nicotine. Even though such protocols increase responding for nicotine at first, the response rate over the subsequent sessions is not different from nonpretrained animals (32). However, prior food training can have potential confounding consequences on later performances during a reinstatement of drug-seeking procedure (32). 2. In experiments where rats are fed ad libitum, operant responding for nicotine is often quite low (at 0.03 mg base/kg/infusion, number of infusions/60 min £ 10) (36, 37). Such food availability is not suitable when the main goal of the experiment is to have a high level of intake or a high level of responses, either with the objective to test a pharmacological compound that decreases nicotine reinforcing properties or the objective to increase nicotine voluntary impregnation. 3. The best experimental condition most widely used is the use of food restriction beginning just prior to the commencement of nicotine IVSA sessions. Rats receive 20 g of lab chow daily ration, delivered immediately after each session. This restriction allows for normal weight gain (12, 32, 38, 39). Interestingly, food restriction does not alter nicotine rewarding effects when brain reward sensitivity is tested with lateral hypothalamic self-stimulation (40), suggesting that the level of responding for nicotine is reliable under such feeding conditions.

15

3.3. Nicotine Dose– Response Curve

3.4. Schedule of Reinforcement


249

Responding for nicotine across different doses results in a rather flat, inverted, U-shaped curve with little compensation in intake with changing doses (see Note 5). Predictably, extreme low (0.003 mg/kg/infusion) doses do not reliably sustain self-administration due to a lack of detectable reinforcing effect. As well, high (0.1 mg/kg/infusion) doses of nicotine are likely to be aversive (3, 38). The most efficient and widely used doses of nicotine are 0.03 and 0.06 mg base/kg/infusion. These doses both support stable operant responding during 1- or 2-h session (32, 38, 41). 1. Schedules of reinforcement are the precise criteria that must be satisfied before the reinforcer is delivered. The criterion is defined in terms of the number of responses on the “active” operandum required in order to present a reinforcer. These rules are established in order to test different aspects of drugtaking behavior (drug rewarding properties, motivation, etc.). Often, each drug delivery is followed by a time-out (TO) period during which each response has no consequence (see Note 6). 2. Self-administration training typically begins with a FR-1 schedule (e.g., FR-1, one response for one drug delivery) and progressively increases. The FR protocol helps to measure basic drug consumption for each animal (see Fig. 1). Usually, stable and robust IVSA behavior is obtained on FR-5 level of responding (e.g., FR-5, five responses for one drug delivery). Responding for nicotine on this schedule is high enough to demonstrate a decrease if a blocking pharmacological compound is tested (see Note 7). 3. A progressive ratio (PR) schedule of reinforcement is used to increase the work load the rat has to perform in order to get the next reinforcer. This procedure allows to determinate the breaking point which represents the maximal work load the animal is willing to produce to get a reward and can be an indicator of its motivation for the drug. Each specific chain of progression used usually depends on the laboratory, where this protocol is performed. For instance, Corrigall and colleagues (42) have developed a PR schedule, where the response requirement increased by 40% with each infusion. Beginning with a response requirement of five for the first infusion, the response requirements for the first ten infusions of the PR schedule are 5, 7, 10, 14, 20, 28, 39, 55, 77, and 108. Alternatively, the PR progression can also be calculated by using the formula 5 × EXP (0.2 × infusion number) − 5, which results in the following sequence of required responses per reinforcement earned: 3, 6, 10, 15, 20, 25, 32, 40, 50, 62, 77, 95, 118, 145, 179, 219, 268, 328, etc. (43, 44). The steeper the slope of the progressive ratio, the more rapidly rats cease

250

S. Caille et al.

Fig. 1. (a) Operant chamber for intravenous drug self-administration. Cages (30 × 40 × 37 cm, Imetronic, France) are equipped with two nose-poke devices (“active” and “inactive”) and are housed in sound-attenuated cubicles holding a pump for the drug delivery through a Tygon tubing. (b) Nicotine intravenous self-administration acquisition and maintenance in Sprague-Dawley rats. Acquisition of nicotine (30 μg base/kg/0.1 ml) under fixed ratio 1 (FR1), fixed ratio 2 (FR2), and then fixed ratio 5 (FR5) schedules of reinforcement. Rats are then stabilized on FR5 at a dose of 60 μg base/kg/0.1 ml (black arrow ). Black circles indicate the active nose-poking hole and white circles indicate the inactive nose-poking hole across days of self-administration (adapted from Caille et al. 2009).

responding and the breaking point is achieved. Another important variable for the PR schedule is the session length. For instance, if the objective is to characterize the basic motivation for nicotine, then the session will run as long as the rats will respond and the cutoff will be defined by a period of time when no reinforcer is earned (e.g., cutoff after 30 min without reinforcer) (45). If the objective is to test the effect of a pharmacological compound on the motivation for nicotine, then the session will be set to a predetermined length (2–3 h depending on the compound activity profile) implemented over a cutoff condition (45). 3.5. Limited Versus Unlimited Access

1. The majority of nicotine self-administration studies have used the classical limited drug access condition which consists of running daily 1- or 2-h sessions. This particular experimental condition has been useful in enhancing our understanding of the behavioral and neurobiological processes involved in nicotine addiction. However, recent work has been conducted using long access conditions to mimic the access conditions of human smokers (27, 28). 2. Extended access to nicotine self-administration has been developed in several laboratories, where the session length was increased to 6 h (28), 12 h (23), or 23 h a day (27, 29). While such long schedules of access to drugs of abuse, such as cocaine or heroin, result in escalated drug intake, surprisingly, rats do not escalate nicotine intake with responding remaining quite stable across sessions (but see the “deprivation effect” phenomenon

15


251

(46)). Interestingly, such nicotine IVSA extended access is able to induce nicotine physical dependence (27, 28). Further research is required here to determine why escalation of nicotine does not occur in rats, particularly as a progressive increase in smoking is evident in humans. 3.6. Nicotine Reinstatement

1. Reexposure to nicotine, a stressful event, or a previously nicotine-associated stimulus can play a crucial role in maintaining daily tobacco smoking and triggering relapse during abstinence. In the laboratory, reinstatement of nicotine-seeking behavior can be modeled in rats using the reinstatement procedure. Nicotine IVSA acquisition and training are followed either by an extinction procedure, whereby nicotine delivery and all associated visual and/or auditory stimuli are removed and the rat learns a new association “operant response = no drug delivery.” Alternatively, rats experience a long period of abstinence during which access to the operant chamber is interrupted and animals remain in their home cages. On the test day, rats are returned to the operant chambers. Then a nicotine prime, a stress or a cue previously associated with the nicotine delivery is presented and the number of nonreinforced active responses is monitored (namely, drug-seeking behavior). 2. Nicotine priming (from 0.001 to 0.03 mg/kg/per i.v. infusion or 0.3 mg/kg s.c.) can trigger nicotine reinstatement in rats extinguished from nicotine self-administration (32, 47, 48). In this experimental design, rats first go through an extinction period (either across or within a session(s)). During test, rats receive a noncontingent nicotine injection that primes the rat to reinstate the previously extinguished operant response. 3. A large body of evidence supports the conclusion that nonpharmacological factors are a major cause of nicotine relapse. More specifically, the contextual and discrete stimuli associated with nicotine intake during self-administration can lead to reinstatement of responding (31, 49, 50). These discrete cues associated with the drug delivery can be either visual or auditory. 4. Interestingly, several combinations can enhance the intensity of drug-seeking behavior. First, Clemens and colleagues (32) have shown that nicotine-induced reinstatement can be improved when nicotine is contingently presented with the conditioned cue during the test (see Fig. 2). Second, as explained in point 2.1, the choice of operandum is important as it can influence the behavior during the procedure of reinstatement. Indeed, rats trained to lever press for nicotine are more sensitive to reinstatement for cue and drug + cue while the nose-poke operandum is best suited for nicotine + cue and nicotine-induced reinstatement (32).

252

S. Caille et al.

Fig. 2. Nicotine reinstatement using nose-poke (NP) (a) or lever (LVR) (b) operandum showing the number of active (A) and inactive (IA) responses during extinction (Ext) or test (Test). Rats were tested for reinstatement to the previously drug-paired cue (Cue), the cue plus a 0.3 mg/kg injection of nicotine (Cue + Nic) or the nicotine injection alone (Nic) (adapted from Clemens et al. 2010).

5. During the protracted nicotine withdrawal period in humans, exposure to stressors greatly increases the likelihood of relapse to tobacco smoking (51, 52). A stress-induced reinstatement model has, therefore, been developed in rodent to study the negative mood state associated with drug withdrawal and stressinduced relapse in humans (53, 54). In this procedure adapted to nicotine-seeking behavior, the stressor can be the presentation of electric footshocks immediately before the introduction of the rat in the operant chamber (55, 56). Subsequent active responses are counted, but nicotine is not delivered. 3.7. Conclusions

Although initial endeavors into achieving nicotine self-administration may have been problematic, recent years have yielded a wealth of literature employing this technique. This has allowed for exploration of the behavioral and neurobiological mechanisms of tobacco addiction. As with many drugs of abuse, nicotine self-administration also appears to be sensitive to experimental variables, such as the age, sex, and strains of rats’ food access conditions or the nature

15


253

of the operandum used for the operant nicotine-taking behavior. The use of nicotine self-administration still has some limitations (nicotine versus tobacco (see Note 8), IV versus inhaled, lack of escalation, low response rates), yet currently represents the best means of modeling tobacco dependence.

4. Notes 1. Operant behavior and circadian cycle: Self-administration sessions should be run during the dark cycle which corresponds to the most active part of rodents’ circadian cycle. 2. Antibiotics: Animal catheters are flushed daily with 0.2 ml of an ampicillin (0.1 g/ml; Coophavet, France) in heparinized saline solution. 3. Testing of the catheter patency: When required, catheter patency can be verified by infusing 0.1 ml of the short acting nonbarbiturate anaesthetic hypnomidate (Braun Medical, France), which elicits a rapid loss of muscle tone. If needed, heparin concentration can be increased in order to maintain optimal blood fluidity. 4. Cue light or sound as a stimulus: The choice of the stimulus associated with the drug delivery is important because nicotine reinforcing properties depend on both the pharmacological effect and the nicotine-induced increased salience of the associated cue. The cue presentation can last as long as the drug infusion or the drug delivery plus the time-out period altogether. Cue lights are often preferred to a sound presentation that can easily trigger a freezing response in rats. 5. Drug preparation: For each bag of drug solution prepared, it is important to adjust the nicotine base powder weighted to the average weight of the group of rat at the time the bag is prepared. Nicotine dose is always expressed as microgram base/ kg/infusion. 6. Time-out is necessary. In self-administration studies in general, and in nicotine IVSA in particular, each drug injection has to be followed by a time-out period during which any active response is not reinforced. The reason for a TO period is twofold: first, it avoids any possibility of over dosing, and second, it allows a better association between the action (active response) and the reinforcer (the drug delivery). A good timeout period is a 20-s period which should be signified by a specific cue light condition. 7. Blockade of nicotine reinforcement: Nicotine self-administration (0.03 mg/kg/infusion) can be reduced dose dependently

254

S. Caille et al.

by nicotinic receptor antagonists, such as mecamylamine (0–4 mk/kg s.c.) or DHβE (0–16 mg/kg s.c.) (41). 8. Nicotine SA increased by other compounds: Several studies have recently highlighted that the chemistry of cigarette smoking is very different from nicotine by itself; and it could be one of the reasons why nicotine IVSA in rats has been problematic. Therefore, several compounds found in tobacco smoke have been added to nicotine in order to test the motivational, reinforcing, and psychostimulant properties of these “cocktails.” It seems that both the monoamine oxydase inhibitors (37, 57, 58) and the minor alkaloids (nornicotine, cotinine, anabasine, anatabine, and myosmine) (45) found in tobacco smoke enhance nicotine motivational, reinforcing, and psychostimulant properties. References 1. Picciotto, M. R., Addy, N. A., Mineur, Y. S., and Brunzell, D. H. (2008) It is not “either/ or”: activation and desensitization of nicotinic acetylcholine receptors both contribute to behaviors related to nicotine addiction and mood, Prog Neurobiol 84, 329–342. 2. David, V., Besson, M., Changeux, J. P., Granon, S., and Cazala, P. (2006) Reinforcing effects of nicotine microinjections into the ventral tegmental area of mice: dependence on cholinergic nicotinic and dopaminergic D1 receptors, Neuropharmacology 50, 1030–1040. 3. Rose, J. E., and Corrigall, W. A. (1997) Nicotine self-administration in animals and humans: similarities and differences, Psychopharmacology (Berl) 130, 28–40. 4. Coen, K. M., Adamson, K. L., and Corrigall, W. A. (2009) Medication-related pharmacological manipulations of nicotine self-administration in the rat maintained on fixed- and progressive-ratio schedules of reinforcement, Psychopharmacology (Berl) 201, 557–568. 5. Corrigall, W. A., Coen, K. M., and Adamson, K. L. (1994) Self-administered nicotine activates the mesolimbic dopamine system through the ventral tegmental area, Brain Res 653, 278–284. 6. Le Foll, B., Chefer, S. I., Kimes, A. S., Shumway, D., Stein, E. A., Mukhin, A. G., and Goldberg, S. R. (2009) Baseline expression of alpha4beta2* nicotinic acetylcholine receptors predicts motivation to self-administer nicotine, Biol Psychiatry 65, 714–716. 7. Corrigall, W. A., and Coen, K. M. (1989) Nicotine maintains robust self-administration in rats on a limited-access schedule, Psychopharmacology (Berl) 99, 473–478.

8. Goldberg, S. R., Spealman, R. D., and Goldberg, D. M. (1981) Persistent behavior at high rates maintained by intravenous self-administration of nicotine, Science 214, 573–575. 9. Henningfield, J. E., and Goldberg, S. R. (1983) Nicotine as a reinforcer in human subjects and laboratory animals, Pharmacol Biochem Behav 19, 989–992. 10. George, O., Grieder, T. E., Cole, M., and Koob, G. F. (2010) Exposure to chronic intermittent nicotine vapor induces nicotine dependence, Pharmacol Biochem Behav 96, 104–107. 11. Small, E., Shah, H. P., Davenport, J. J., Geier, J. E., Yavarovich, K. R., Yamada, H., Sabarinath, S. N., Derendorf, H., Pauly, J. R., Gold, M. S., and Bruijnzeel, A. W. (2009) Tobacco smoke exposure induces nicotine dependence in rats, Psychopharmacology (Berl) 208, 143–158. 12. Caille, S., Guillem, K., Cador, M., Manzoni, O., and Georges, F. (2009) Voluntary nicotine consumption triggers in vivo potentiation of cortical excitatory drives to midbrain dopaminergic neurons, J Neurosci 29, 10410–10415. 13. Adriani, W., Deroche-Gamonet, V., Le Moal, M., Laviola, G., and Piazza, P. V. (2006) Preexposure during or following adolescence differently affects nicotine-rewarding properties in adult rats, Psychopharmacology (Berl) 184, 382–390. 14. Belluzzi, J. D., Lee, A. G., Oliff, H. S., and Leslie, F. M. (2004) Age-dependent effects of nicotine on locomotor activity and conditioned place preference in rats, Psychopharmacology (Berl) 174, 389–395. 15. Belluzzi, J. D., Wang, R., and Leslie, F. M. (2005) Acetaldehyde enhances acquisition of

15

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

nicotine self-administration in adolescent rats, Neuropsychopharmacology 30, 705–712. Donny, E. C., Caggiula, A. R., Knopf, S., and Brown, C. (1995) Nicotine self-administration in rats, Psychopharmacology (Berl) 122, 390–394. Fortmann, S. P., and Killen, J. D. (1994) Who shall quit? Comparison of volunteer and population-based recruitment in two minimal-contact smoking cessation studies, Am J Epidemiol 140, 39–51. O’Hara, P., Portser, S. A., and Anderson, B. P. (1989) The influence of menstrual cycle changes on the tobacco withdrawal syndrome in women, Addict Behav 14, 595–600. Rose, J. E., Behm, F. M., and Levin, E. D. (1993) Role of nicotine dose and sensory cues in the regulation of smoke intake, Pharmacol Biochem Behav 44, 891–900. Cox, B. M., Goldstein, A., and Nelson, W. T. (1984) Nicotine self-administration in rats, Br J Pharmacol 83, 49–55. Park, M. K., Belluzzi, J. D., Han, S. H., Cao, J., and Leslie, F. M. (2007) Age, sex and early environment contribute to individual differences in nicotine/acetaldehyde-induced behavioral and endocrine responses in rats, Pharmacol Biochem Behav 86, 297–305. Donny, E. C., Caggiula, A. R., Rowell, P. P., Gharib, M. A., Maldovan, V., Booth, S., Mielke, M. M., Hoffman, A., and McCallum, S. (2000) Nicotine self-administration in rats: estrous cycle effects, sex differences and nicotinic receptor binding, Psychopharmacology (Berl) 151, 392–405. Kenny, P. J., and Markou, A. (2006) Nicotine self-administration acutely activates brain reward systems and induces a long-lasting increase in reward sensitivity, Neuropsychopharmacology 31, 1203–1211. Shoaib, M., Schindler, C. W., and Goldberg, S. R. (1997) Nicotine self-administration in rats: strain and nicotine pre-exposure effects on acquisition, Psychopharmacology (Berl) 129, 35–43. Brower, V. G., Fu, Y., Matta, S. G., and Sharp, B. M. (2002) Rat strain differences in nicotine self-administration using an unlimited access paradigm, Brain Res 930, 12–20. Fu, Y., Matta, S. G., Brower, V. G., and Sharp, B. M. (2001) Norepinephrine secretion in the hypothalamic paraventricular nucleus of rats during unlimited access to self-administered nicotine: An in vivo microdialysis study, J Neurosci 21, 8979–8989. O’Dell, L. E., Chen, S. A., Smith, R. T., Specio, S. E., Balster, R. L., Paterson, N. E., Markou, A., Zorrilla, E. P., and Koob, G. F. (2007)


28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

255

Extended access to nicotine self-administration leads to dependence: Circadian measures, withdrawal measures, and extinction behavior in rats, J Pharmacol Exp Ther 320, 180–193. Paterson, N. E., and Markou, A. (2004) Prolonged nicotine dependence associated with extended access to nicotine self-administration in rats, Psychopharmacology (Berl) 173, 64–72. LeSage, M. G., Keyler, D. E., Shoeman, D., Raphael, D., Collins, G., and Pentel, P. R. (2002) Continuous nicotine infusion reduces nicotine self-administration in rats with 23-h/ day access to nicotine, Pharmacol Biochem Behav 72, 279–289. Valentine, J. D., Hokanson, J. S., Matta, S. G., and Sharp, B. M. (1997) Self-administration in rats allowed unlimited access to nicotine, Psychopharmacology (Berl) 133, 300–304. Chiamulera, C. (2005) Cue reactivity in nicotine and tobacco dependence: a “multipleaction” model of nicotine as a primary reinforcement and as an enhancer of the effects of smoking-associated stimuli, Brain Res Brain Res Rev 48, 74–97. Clemens, K. J., Caille, S., and Cador, M. (2010) The effects of response operandum and prior food training on intravenous nicotine self-administration in rats, Psychopharmacology (Berl) 211, 43–54. Kenny, P. J., Chartoff, E., Roberto, M., Carlezon, W. A., Jr., and Markou, A. (2009) NMDA receptors regulate nicotine-enhanced brain reward function and intravenous nicotine self-administration: role of the ventral tegmental area and central nucleus of the amygdala, Neuropsychopharmacology 34, 266–281. LeSage, M. G., Perry, J. L., Kotz, C. M., Shelley, D., and Corrigall, W. A. (2010) Nicotine self-administration in the rat: effects of hypocretin antagonists and changes in hypocretin mRNA, Psychopharmacology (Berl) 209, 203–212. Paterson, N. E., Semenova, S., and Markou, A. (2008) The effects of chronic versus acute desipramine on nicotine withdrawal and nicotine self-administration in the rat, Psychopharmacology (Berl) 198, 351–362. Diergaarde, L., de Vries, W., Raaso, H., Schoffelmeer, A. N., and De Vries, T. J. (2008) Contextual renewal of nicotine seeking in rats and its suppression by the cannabinoid-1 receptor antagonist Rimonabant (SR141716A), Neuropharmacology 55, 712–716. Villegier, A. S., Lotfipour, S., McQuown, S. C., Belluzzi, J. D., and Leslie, F. M. (2007) Tranylcypromine enhancement of nicotine

256

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

S. Caille et al. self-administration, Neuropharmacology 52, 1415–1425. Donny, E. C., Caggiula, A. R., Mielke, M. M., Jacobs, K. S., Rose, C., and Sved, A. F. (1998) Acquisition of nicotine self-administration in rats: the effects of dose, feeding schedule, and drug contingency, Psychopharmacology (Berl) 136, 83–90. Palmatier, M. I., Levin, M. E., Mays, K. L., Donny, E. C., Caggiula, A. R., and Sved, A. F. (2009) Bupropion and nicotine enhance responding for nondrug reinforcers via dissociable pharmacological mechanisms in rats, Psychopharmacology (Berl) 207, 381–390. Cabeza de Vaca, S., and Carr, K. D. (1998) Food restriction enhances the central rewarding effect of abused drugs, J Neurosci 18, 7502–7510. Watkins, S. S., Epping-Jordan, M. P., Koob, G. F., and Markou, A. (1999) Blockade of nicotine self-administration with nicotinic antagonists in rats, Pharmacol Biochem Behav 62, 743–751. Corrigall, W. A., Coen, K. M., Zhang, J., and Adamson, K. L. (2001) GABA mechanisms in the pedunculopontine tegmental nucleus influence particular aspects of nicotine self-administration selectively in the rat, Psychopharmacology (Berl) 158, 190–197. Depoortere, R. Y., Li, D. H., Lane, J. D., and Emmett-Oglesby, M. W. (1993) Parameters of self-administration of cocaine in rats under a progressive-ratio schedule, Pharmacol Biochem Behav 45, 539–548. Donny, E. C., Caggiula, A. R., Mielke, M. M., Booth, S., Gharib, M. A., Hoffman, A., Maldovan, V., Shupenko, C., and McCallum, S. E. (1999) Nicotine self-administration in rats on a progressive ratio schedule of reinforcement, Psychopharmacology (Berl) 147, 135–142. Clemens, K. J., Caille, S., Stinus, L., and Cador, M. (2009) The addition of five minor tobacco alkaloids increases nicotine-induced hyperactivity, sensitization and intravenous self-administration in rats, Int J Neuropsychopharmacol 12, 1355–1366. O’Dell, L. E., and Koob, G. F. (2007) ‘Nicotine deprivation effect’ in rats with intermittent 23-hour access to intravenous nicotine selfadministration, Pharmacol Biochem Behav 86, 346–353. Chiamulera, C., Borgo, C., Falchetto, S., Valerio, E., and Tessari, M. (1996) Nicotine reinstatement of nicotine self-administration after long-term extinction, Psychopharmacology (Berl) 127, 102–107.

48. Dravolina, O. A., Zakharova, E. S., Shekunova, E. V., Zvartau, E. E., Danysz, W., and Bespalov, A. Y. (2007) mGlu1 receptor blockade attenuates cue- and nicotine-induced reinstatement of extinguished nicotine self-administration behavior in rats, Neuropharmacology 52, 263–269. 49. Caggiula, A. R., Donny, E. C., White, A. R., Chaudhri, N., Booth, S., Gharib, M. A., Hoffman, A., Perkins, K. A., and Sved, A. F. (2001) Cue dependency of nicotine selfadministration and smoking, Pharmacol Biochem Behav 70, 515–530. 50. Diergaarde, L., Pattij, T., Poortvliet, I., Hogenboom, F., de Vries, W., Schoffelmeer, A. N., and De Vries, T. J. (2008) Impulsive choice and impulsive action predict vulnerability to distinct stages of nicotine seeking in rats, Biol Psychiatry 63, 301–308. 51. Cohen, S., and Lichtenstein, E. (1990) Perceived stress, quitting smoking, and smoking relapse, Health Psychol 9, 466–478. 52. Kassel, J. D., Stroud, L. R., and Paronis, C. A. (2003) Smoking, stress, and negative affect: correlation, causation, and context across stages of smoking, Psychol Bull 129, 270–304. 53. Koob, G. F., and Le Moal, M. (1997) Drug abuse: hedonic homeostatic dysregulation, Science 278, 52–58. 54. Shaham, Y., Shalev, U., Lu, L., De Wit, H., and Stewart, J. (2003) The reinstatement model of drug relapse: history, methodology and major findings, Psychopharmacology (Berl) 168, 3–20. 55. Buczek, Y., Le, A. D., Wang, A., Stewart, J., and Shaham, Y. (1999) Stress reinstates nicotine seeking but not sucrose solution seeking in rats, Psychopharmacology (Berl) 144, 183–188. 56. Zislis, G., Desai, T. V., Prado, M., Shah, H. P., and Bruijnzeel, A. W. (2007) Effects of the CRF receptor antagonist D-Phe CRF(12– 41) and the alpha2-adrenergic receptor agonist clonidine on stress-induced reinstatement of nicotine-seeking behavior in rats, Neuropharmacology 53, 958–966. 57. Guillem, K., Vouillac, C., Azar, M. R., Parsons, L. H., Koob, G. F., Cador, M., and Stinus, L. (2005) Monoamine oxidase inhibition dramatically increases the motivation to selfadminister nicotine in rats, J Neurosci 25, 8593–8600. 58. Guillem, K., Vouillac, C., Azar, M. R., Parsons, L. H., Koob, G. F., Cador, M., and Stinus, L. (2006) Monoamine oxidase A rather than monoamine oxidase B inhibition increases nicotine reinforcement in rats, Eur J Neurosci 24, 3532–3540.

Chapter 16 Animal Models of Nicotine Withdrawal: Intracranial Self-Stimulation and Somatic Signs of Withdrawal Rayna M. Bauzo and Adrie W. Bruijnzeel Abstract Tobacco addiction is one of the leading causes of preventable death worldwide. Despite the negative health outcomes of tobacco use and a desire to quit, there is a low success rate of maintaining abstinence. Nicotine, the main psychoactive component of tobacco smoke, is mildly rewarding and maintains smoking behavior. Nicotine withdrawal induces somatic symptoms that may contribute to smoking behavior. However, it has been hypothesized that the negative affective signs are of greater motivational significance in contributing to relapse and continued tobacco use than the somatic symptoms of nicotine withdrawal (Markou and Koob (Eds.) Intracranial self-stimulation thresholds as a measure of reward, Vol. 2, Oxford University Press, New York, 1993; Koob et al. Semin Neurosci 5: 351–358, 1993). Intracranial self-stimulation (ICSS) has been established as a method to assess the bivalent properties of nicotine exposure and withdrawal from acute and chronic nicotine administration. Thus, ICSS provides a means to measure the negative affective aspects of nicotine withdrawal in animal models and may contribute to the understanding of the neurobiological bases of nicotine dependence and the development of effective treatment strategies to facilitate nicotine abstinence. Key words: Nicotine, Withdrawal, Intracranial self-stimulation, Somatic signs

1. Introduction Nicotine, the addictive component of tobacco smoke, is one of the most heavily used addictive drugs worldwide. It is one of the leading preventable causes of disease, disability, and death in the USA and leads to more than 400,000 preventable deaths per year (3). Approximately 90% of lung cancer cases in the USA are attributed to cigarette smoking while about 38,000 deaths per year are attributed to secondhand smoke exposure. In the 2008 National Survey on Drug Use and Health, nearly 71 million Americans aged 12 and older had used a tobacco product at least once in the month prior


257

258

R.M. Bauzo and A.W. Bruijnzeel

to being surveyed (4). Despite the well-documented health costs of smoking, many tobacco users find it difficult to quit smoking and many others are becoming addicted. Nicotine addiction is a chronic relapsing disorder that is characterized by a compulsive and persistent desire to smoke despite negative consequences and a desire to quit. Nicotine craving and relapse can occur even after a very long abstinence period (5). In humans, nicotine can temporarily induce positive reinforcing effects, such as decreases in stress and depression, decreases in appetite, stimulation, and pleasure. During initiation of smoking, smokers use nicotine to modulate their level of arousal and to control their mood state (6). Thus, the rewarding effects of nicotine are believed to be important for the initiation of nicotine addiction. The rate of relapse and abuse liability of nicotine obtained from tobacco products is comparable to other drugs of abuse, such as stimulants and opiates (7). However, the psychological effects of nicotine are more subtle compared to other drugs and do not readily predict the difficulty smokers experience in maintaining abstinence (8). The low success rate of smoking cessation treatments utilizing nicotine replacement therapies suggests that there are factors other than the rewarding effects of nicotine that maintain the drug seeking behavior. Withdrawal from nicotine induces somatic signs and negative affective effects. In humans, withdrawal from nicotine leads to somatic symptoms, such as bradycardia, insomnia, gastrointestinal discomfort, increased appetite, and weight gain (9). Nicotine withdrawal also induces negative affective symptoms, such as irritability, depressed mood, restlessness, anxiety, increased stress, problems getting along with friends and family, difficulty concentrating, and craving for tobacco (9, 10). These mood disturbances caused by nicotine withdrawal are comparable in intensity to those seen in psychiatric outpatients (11). Thus, the rewarding effects of nicotine play an important role in the initiation of smoking and preventing withdrawal plays an important role in the maintenance of smoking (1, 2, 12–14). In rodents, discontinuation of nicotine administration or the administration of nicotinic acetylcholine receptor (nAChR) antagonists to rats chronically exposed to nicotine results in the emergence of somatic signs of nicotine withdrawal, including abdominal constrictions, facial fasciculation, increased eye blinks, and ptosis (15–18). Though overt somatic signs of nicotine withdrawal are relatively easy to measure, they do not accurately reflect the motivational state of the animal. Motivation and affect are difficult to measure in animal models. Intracranial self-stimulation (ICSS) is an operant behavioral model that can measure the bivalent effects of acute nicotine administration versus abstinence from chronic nicotine administration on brain reward function. Acute administration of nicotine lowers brain reward thresholds demonstrating the reward enhancing effects of nicotine (19–21). Moreover,

16

Animal Models of Nicotine Withdrawal

259

both spontaneous and precipitated withdrawal from chronic nicotine administration lead to an elevation in brain reward thresholds demonstrating a diminished reward and motivation associated with nicotine withdrawal. This increase in brain reward thresholds associated with diminished reward and motivation has also been established in other drugs of abuse, such as cocaine, amphetamine, opiates, and ethanol (15, 22–26). Thus, brain reward thresholds as assessed with the ICSS procedure, together with physical withdrawal symptoms, provide a means to measure nicotine dependence and withdrawal in animal models. The studies may contribute to the understanding of the neurobiological bases of nicotine dependence and the development of effective treatment strategies to facilitate abstinence of tobacco products.

2. Materials 2.1. Electrode Implantations

1. Rats (200–250 g). 2. Stainless steel bipolar electrodes (model MS303/2 Plastics one, Roanoke, VA, USA) 11 mm in length. 3. Isoflurane/oxygen (1–3% isoflurane). 4. Oster MiniMax Trimmer Narrow blade. 5. Aseptic surgery scrub prep—betadine solution (10% povidoneiodine)/70% ethanol. 6. Model 940 Kopf stereotaxic frame (David Kopf Instruments, Tujunga, CA). 7. Surgical instruments: Scalpel, retractors, spratt bone chisel (Roboz Surgical Instrument Company, Gaithersburg, MD, USA). 8. Cotton swabs. 9. Surgical pen. 10. Stainless steel jeweler screws (shaft length 1.6 mm, shaft diameter 1.57 mm). 11. Micro drill with 1.07-mm (diameter) drill bit. 12. Dental Cement (Pharmaceutical grade Dental Acrylic Cement, CO-Oral-Ite Dental Mfg. Co, USA). 13. Spatula and cup. 14. Flunixin (1 mg/mL).

2.2. Intracranial Self-Stimulation Procedure

1. Operant conditioning chambers and sound-attenuating chambers (Med Associates, St. albans, VT, USA). 2. Wheel manipulatum installed into the wall of the operant conditioning chamber. 3. Stimulators (Stimtek, Acton, MA, USA).

260


2.3. Osmotic Minipump Implantations

1. Osmotic minipumps (Durect corporation, Cupertino, CA). 2. Isoflurane/oxygen (1–3% isoflurane). 3. #40 surgical clipper blade. 4. Aseptic surgery scrub prep—betadine solution (10% povidoneiodine)/70% ethanol. 5. Surgical instruments: Scalpel, blunt tissue forceps, suture. 6. Flunixin (1 mg/mL) (Phoenix Scientific Inc, Fort Dodge, IA, USA). 7. Alzet osmotic pumps (model 2ML2 14-day, Alza Corporation, Palo Alto, CA, USA).

2.4. Somatic Withdrawal Signs

1. Plexiglas observation chamber (25 × 25 × 45 cm; L × W × H). 2. Timer. 3. Checklist labeled with animal ID and abbreviations defined.

3. Methods ICSS is an operant behavioral paradigm in which subjects selfadminister a rewarding electrical stimulus via electrodes implanted in the reward pathway of the brain. Self-administration behavior is maintained when electrodes for ICSS are placed in any of the structures in the reward pathway. However, electrodes directed to the medial forebrain bundle, which contain excitatory inputs into the mesolimbic dopamine pathway, produce reliable ICSS behavior at relatively low stimulation thresholds and with few, if any, motor side effects. An advantage of the ICSS paradigm is that the parameters of brain stimulation reinforcement can be more precisely controlled than other natural or drug reinforcers. Increases in current intensity lead to increases in rates of responding. In contrast, drug self-administration often induces an inverted U-shaped curve, where rates of responding increase with dose on the ascending limb of the dose–response curve and decrease after a peak dose. The decrease in responding is attributed to satiety and adverse effects of high doses of drug. Responding for food also lead to decreases in rates of responding once the subject has reached satiety. Thus, changes in threshold currents can be attributed to changes in mood state and motivation. 3.1. Electrode Implantations

1. Adult male rats (200–250 g) are implanted with stainless steel bipolar electrodes 11 mm in length by using sterotaxic procedures to target the posterior lateral hypothalamus. Rats are initially anesthetized with an isoflurane/oxygen vapor mixture and the depth of anesthesia determined by toe pinch. Anesthesia is maintained on isoflurane throughout the procedure.

16


261

2. Once anesthetized, the rats are prepared for aseptic surgery by removing the hair from the dorsal surface of the cranium with a narrow blade trimmer. The exposed area is then properly cleaned with betadine solution followed by 70% ethanol. Repeat cleaning procedure three times. 3. Subject’s body temperature is maintained throughout the procedure with a “circulating water” heating pad that is automatically controlled and maintained at 35°C, approximately 2.5°C below the body temperature of the rat. A nonmedicated, lubricating ophthalmic ointment is placed in the eyes. 4. The rat is then placed and secured in a model 940 Kopf stereotaxic frame with the incisor bar set 5.0 mm above the interaural line (see Note 1). Coordinates for the stereotaxic procedures are obtained from a standard rat atlas. Stereotaxic coordinates for the electrode placements targeting the medial forebrain bundle are −0.5 mm anterior, ±1.7 mm mediolateral to bregma, and −8.3 mm ventral from dura. 5. A small incision (1 cm) is made in the skin overlying the skull and bregma is exposed for subsequent determination of the implantation site. Retract the skin to allow adequate exposure of the bone surface. 6. With a Spratt bone chisel, gently scrape the skull to remove any connective tissue from the exposed skull. Wipe the skull with a sterile cotton swab to ensure that the surface is dry. 7. Measure the length of the electrode to ensure that it is 11 mm in length. If it is longer, cut to 11 mm with sterile surgical scissors. Using a clean scalpel blade, gently separate the two poles of the electrode to ensure that they are not touching (see Note 2). 8. Secure the electrode to the stereotaxic apparatus with the electrode holder (see Note 3). 9. Determine the coordinates of bregma. Once at bregma, move to the proper anterior/posterior and mediolateral coordinates for electrode placement. Mark gently with a surgical pen. 10. Mark four more areas for placement of anchor screws (see Note 4). 11. Drill 5–0.5-mm holes through the cranial surface with a micro drill. The drill bit should only penetrate the thickness of the bone (see Note 5). Use sterile cotton swabs to dry the surface of the skull if any blood should seep. 12. Thread sterile micro screws into the four holes designated for the anchor screws leaving a thread or two of space between the head of the screw and the skull (see Note 6). 13. Lower the electrode to the dorsal ventral coordinates targeting the posterior lateral hypothalamus.

262


14. Carefully apply dental cement around the electrode and screws with a spatula. Allow the cement to seep between the head of the screw and the skull (see Note 7). 15. Mold the dental cement to form a mushroom-shaped cap. Smooth all the edges of the cap (see Note 8). 16. Allow the cap to harden, and then suture up skin with sterile, nonabsorbable monofilament 3–0 suture around the prep in front and behind the cap. 17. Following completion of surgery, apply betadine ointment (10% povidone-iodine) and pain reliever ointment (betacaine gel, contains 5% lidocaine) to the incision area and perform approved postoperative procedures for your institution. 18. Administer Flunixin. 19. Allow a week for recovery before initiating the intracranial selfstimulation experiments. 3.2. Intracranial Self-Stimulation Procedure

1. A lead is connected to the electrode and the subject is placed in an operant conditioning chamber that is placed inside a sound-attenuating chamber. 2. The lead is connected to a stimulator, which generates electrical stimuli of different intensity levels (100 Hz of 0.1-ms rectangular cathodal pulses, 500-ms train duration, variable current intensity with levels ranging between 50 and 250 μA). 3. A computer program controls the stimulator and records the responses of the subject. 4. There are three stages of training for this operant procedure: simple fixed-ratio (FR) schedule of reinforcement, discretetrial current-threshold procedure, and modification of the psychophysical method of limits. 5. During the initial phase, rats are trained to respond on a simple FR1 schedule of reinforcement to turn a wheel manipulandum (5 × 7 cm; W × H) embedded in the wall of the experimental chamber. 6. Each quarter turn of the wheel results in a delivery of a 0.5-s train of 0.1-ms cathodal square-wave pulses at a frequency of 100 Hz. 7. Training schedule can be repeated up to three times per day. However, training should be restricted to less than an hour per day. Successful acquisition of responding for stimulation on this FR1 schedule is defined as 100 reinforcements within 10 min. 8. Upon completion of the initial training stage, rats begin the second stage of training on a discrete-trial current-threshold procedure. This stage is divided into three phases in which the intertrial interval and delay periods induced by time-out are

16


263

gradually increased until the animal acquires behavior during each part. 9. For all phases, each trial begins with the delivery of a noncontingent electrical stimulus, followed by a 7.5-s response window during which the animal can respond to receive a second contingent stimulus that is identical to the initial noncontingent stimulus. 10. A response during this 7.5-s response window is labeled as a positive response while the lack of a response is labeled as a negative response. During the 2-s period immediately after a positive response, additional responses have no consequences. 11. During the first phase of training, there is a 3-s interval between trials and responding during this interval results in a 1-s penalty delay. Rats should complete a minimum of 200 trials per session (see Note 9). 12. When subjects receive positive responses in 90% of the trials in three consecutive sessions, the subject can be moved to the second phase of training for this stage. During this phase, there is a 5-s interval between trials and responding during this interval results in a 2-s penalty delay. Rats should complete a minimum of 200 trials per session (see Note 10). 13. When subjects receive positive responses in 90% of the trials in three consecutive sessions, the subject can be moved to the third phase of training for this stage. During this phase, there is a 10-s interval between trials and responding during this interval results in a 5-s penalty delay. Rats should complete a minimum of 200 trials per session. During this phase, sessions are typically 30–40 min. There is no benefit of repeated testing within 1 day. 14. The third and final stage of training determines brain reward thresholds by using a modification of the psychophysical method of limits. The parameters used in this method are the same as those for the experimental phase. 15. During this phase, test sessions consist of four alternating series of descending and ascending current intensities starting with a descending series. 16. At the start of each trial, the subject receives a noncontingent sinusoidal electrical stimulus of 250 ms duration and 60 Hz frequency. 17. Subjects are required to rotate the wheel manipulandum onequarter of a rotation to receive a contingent stimulus identical to the previously delivered noncontingent stimulus during a 7.5-s response window. This is defined as a positive response. 18. During the 2-s period immediately after a positive response, additional responses have no consequences. 19. If the subject does not respond within 7.5 s, this is defined as a negative response.

264


20. Following a positive or negative response, there is an intertrial interval that averages 10 s (7.5–12.5 s). Following the intertrial interval, the trial was terminated. 21. Any responding during the intertrial interval resulted in a 10-s delay before the start of the next trial. 22. Blocks of three trials are presented to the subject at a given stimulation intensity, and the intensity is altered systematically between blocks of trials by 5 μA steps. 23. The initial stimulus intensity is set 40 μA above the baseline current-threshold for each animal. Each test session typically lasts 30–40 min and provides two dependent variables for behavioral assessment: brain reward thresholds and response latencies. 24. The current threshold for a descending series was defined as the midpoint between stimulation intensities that supported responding (i.e., positive responses on at least two of the three trials) and current intensities that failed to support responding. 25. The threshold for an ascending series was defined as the midpoint between stimulation intensities that did not support responding and current intensities that supported responding for two consecutive blocks of trials. 26. Four threshold estimates were recorded and the mean of these values was taken as the final threshold. 27. The time interval between the beginning of the noncontingent stimulus and a positive response was recorded as the response latency. The response latency for each test session was defined as the mean response latency on all trials during which a positive response occurred. 28. The rats are tested daily (30 min per session) and the total duration of the experiment is approximately 2 months. A computer records the positive responses of the rats. 29. Rats should be tested until the threshold current is stable and there is less than 20% variability. 30. Once rats are responding stably and there is little variability in the threshold current, the subjects can be implanted with osmotic mini-pumps to induce nicotine dependence. 3.3. Osmotic MiniPump Implantations

1. Adults are implanted with osmotic mini-pumps filled with either saline or nicotine salt dissolved in saline subcutaneously utilizing aseptic surgical techniques. 2. This surgery is conducted approximately 1 month after the implantation of the electrodes, usually after the rats have undergone ICSS training procedures and are responding stably. 3. Osmotic mini-pumps are prepared at least 24 h prior to implantation. For controls, pumps should be filled with sterile saline. Handle carefully to ensure that the pumps remain sterile.

16


265

4. The nicotine concentration must be adjusted to compensate for differences in body weight to ensure delivery of a dose of 9 mg/ kg per day of nicotine salt (3.16 mg/kg/day nicotine base). 5. Inject sterile saline or calculated amount of nicotine into the small pump and seal with the injection needle. 6. Rats are anesthetized with an isoflurane/oxygen vapor mixture (1–3% isoflurane) and depth of anesthesia determined by toe pinch. Anesthesia is maintained on isoflurane (1–2%) throughout the procedure. 7. Once anesthetized, the rats are prepared for aseptic surgery by removing the hair from one-side flank with a #40 surgical clipper blade. The exposed area is then cleaned with betadine solution followed by 70% ethanol. Repeat cleaning procedure three times. 8. Subject’s body temperature is maintained throughout the procedure with a “circulating water” heating pad that is automatically controlled and maintained at 35°C, approximately 2.5°C below the body temperature of the rat. A nonmedicated, lubricating ophthalmic ointment is placed in the eyes. 9. Make a 1.5-cm skin incision posterior of the ribcage. 10. Using sterile blunt tissue forceps, form a small pocket by separating the muscle and subcutaneous layer. 11. Place the tip of the forceps between the muscle and subcutaneous layer. Apply gentle pressure and gently open and close the forceps to excavate the pocket (see Note 11). 12. Remove the forceps in the open position to prevent tearing of tissue. Repeat until the pocket is large enough to accommodate the pump (see Note 12). 13. Insert the mini-pump in the pocket under the skin. With a nonabsorbable suture, close the incision site with a simple interrupted suture. 14. Following completion of surgery, apply betadine ointment (10% povidone-iodine) and pain reliever ointment (betacaine gel, contains 5% lidocaine) to the incision area. 15. Administer Flunixin. 16. The duration of this surgery is approximately 5 min per rat. 3.4. Somatic Withdrawal Signs

1. Rats are habituated to the Plexiglas observation chamber (25 × 25 × 45 cm; L × W × H) for 5–10 min per day on two consecutive days prior to testing. 2. Rats are injected with 2 mg/kg of the nicotinic receptor antagonist mecamylamine to induce pharmacological withdrawal 5 min prior to experiment. 3. Rats are placed in the observation chamber and observed for 10 min.

266


4. The following somatic signs should be recorded based on the checklist of nicotine abstinence signs: (a) Body shakes. (b) Cheek tremors. (c) Escape attempts. (d) Eye blinks. (e) Gasps. (f) Genital licks. (g) Head shakes. (h) Ptosis (see Note 13). (i) Teeth chattering. (j) Writhes. (k) Yawns 5. The total number of somatic signs is defined as the sum of the individual occurrences. 6. For the final statistical analyses, the signs should be divided into the following categories: (a) Abdominal constrictions-include gasps and writhes. (b) Shakes-includes head shakes and body shakes. (c) Facial fasciculations-include cheek tremors and teeth chattering. (d) Eye blinks. (e) Ptosis. (f) Yawns. (g) Other signs-include that may occur occasionally such as escape attempts and genital licks.

4. Notes 1. Proper placement of the incisor bar is important for correct placement of the electrode. 2. The space between the electrode ends should just be wide enough to allow the scalpel blade to slip between the two ends. Do not fray the ends of the electrode by manipulating the ends too vigorously. Do not bend the electrode. 3. Make sure that the electrode is straight in all angles. Gently straighten the electrode with sterile forceps. 4. To ensure a secure anchor, the screws should be placed on different skull plates. The screw placements must be far enough from the electrode placement to allow for proper placement of the top of the electrode.

16


267

5. The dorsal/ventral coordinates are measured from the level of dura. When creating the hole for the electrode, be sure not to disturb the dura in order to accurately measure this coordinate. 6. These screws are necessary to help anchor the electrode and only penetrate the thickness of the bone, approximately 1 mm. Do not thread screws flush to the skull, and leave a space between the head of the screw and the skull (approximately a thread or two) to allow the dental cement and acrylic to seep between the screw and the skull. This forms the anchor necessary to hold the electrode in place. 7. The dental cement and acrylic should be mixed just prior to application. 8. Do not allow the cement to seep under the skin. Use the spatula to control the flow of the cement. The cement should not be too liquid to control, but must not be too hardened to form a seal around the electrode and screws. Do not leave any sharp edges as these can create a site of irritation. 9. Training can be repeated up to three times per day to maximize training efforts. However, training sessions should not exceed an hour. The current may need to be increased or decreased if the subject is not responding. 10. These sessions are slightly longer but can be repeated up to two times per day to maximize training efforts. 11. Be careful not to puncture the muscle tissue. This causes damage to the muscle and prolongs recovery time. 12. The pocket should be large enough to allow positioning of the pump away from the site of the incision. If the pump rests on the incision site, it will erode through the skin through the site of the incision. 13. Ptosis should be counted once per minute if present continuously. References 1. Markou, A., and Koob, G., (Eds.) (1993) Intracranial self-stimulation thresholds as a measure of reward, Vol. 2, Oxford University Press, New York. 2. Koob, G., Markou, A., Weiss, F., and Schulteis, G. (1993) Opponent process and drug dependence: Neurobiological mechanisms, Semin Neurosci 5, 351–358. 3. Volkow, N. (2009) Tobacco Addiction, in Research Report, National Institute on Drug Abuse, Rockville, MD. 4. (2009) Results from the 2008 National Survey on Drug Use and Health: National Findings

Substance Abuse and Mental Health Services Administration, Rockville, MD. 5. Le Foll, B., and Goldberg, S. R. (2009) Effects of nicotine in experimental animals and humans: an update on addictive properties, Handb Exp Pharmacol, 335–367. 6. Benowitz, N. L. (2009) Pharmacology of nicotine: addiction, smoking-induced disease, and therapeutics, Annu Rev Pharmacol Toxicol 49, 57–71. 7. Anthony, J. C., Warner, L. A., and Kessler, R. C. (1994) Comparative Epidemiology of Dependence on Tobacco, Alcohol, Controlled

268

8.

9.

10.

11.

12.

13.

14. 15.

16.

17.

R.M. Bauzo and A.W. Bruijnzeel Substances, and Inhalants: Basic Findings From the National Comorbidity Survey, Experimental and Clinical Psychopharmacology 2, 244–268. Caggiula, A. R., Donny, E. C., White, A. R., Chaudhri, N., Booth, S., Gharib, M. A., Hoffman, A., Perkins, K. A., and Sved, A. F. (2001) Cue dependency of nicotine selfadministration and smoking, Pharmacol Biochem Behav 70, 515–530. Hughes, J. R., Gust, S. W., Skoog, K., Keenan, R. M., and Fenwick, J. W. (1991) Symptoms of tobacco withdrawal. A replication and extension, Arch Gen Psychiatry 48, 52–59. Hughes, J. R., and Hatsukami, D. (1986) Signs and symptoms of tobacco withdrawal, Arch Gen Psychiatry 43, 289–294. Hughes, J. R. (2006) Clinical significance of tobacco withdrawal, Nicotine Tob Res 8, 153–156. Wesnes, K., and Warburton, D. M. (1983) Smoking, nicotine and human performance, Pharmacol Ther 21, 189–208. Bruijnzeel, A. W., and Gold, M. S. (2005) The role of corticotropin-releasing factor-like peptides in cannabis, nicotine, and alcohol dependence, Brain Res Brain Res Rev 49, 505–528. Koob, G. F. (2008) A role for brain stress systems in addiction, Neuron 59, 11–34. Epping-Jordan, M. P., Watkins, S. S., Koob, G. F., and Markou, A. (1998) Dramatic decreases in brain reward function during nicotine withdrawal, Nature 393, 76–79. Malin, D. H., Lake, J. R., Carter, V. A., Cunningham, J. S., Hebert, K. M., Conrad, D. L., and Wilson, O. B. (1994) The nicotinic antagonist mecamylamine precipitates nicotine abstinence syndrome in the rat, Psychopharmacology (Berl) 115, 180–184. Malin, D. H., Lake, J. R., Newlin-Maultsby, P., Roberts, L. K., Lanier, J. G., Carter, V. A., Cunningham, J. S., and Wilson, O. B. (1992) Rodent model of nicotine abstinence syndrome, Pharmacol Biochem Behav 43, 779–784.

18. Hildebrand, B. E., Nomikos, G. G., Bondjers, C., Nisell, M., and Svensson, T. H. (1997) Behavioral manifestations of the nicotine abstinence syndrome in the rat: peripheral versus central mechanisms, Psychopharmacology (Berl) 129, 348–356. 19. Paterson, N. E. (2009) The neuropharmacological substrates of nicotine reward: reinforcing versus reinforcement-enhancing effects of nicotine, Behav Pharmacol 20, 211–225. 20. Nakahara, D. (2004) Influence of nicotine on brain reward systems: study of intracranial selfstimulation, Ann NY Acad Sci 1025, 489–490. 21. Bespalov, A., Lebedev, A., Panchenko, G., and Zvartau, E. (1999) Effects of abused drugs on thresholds and breaking points of intracranial self-stimulation in rats, Eur Neuropsychopharmacol 9, 377–383. 22. Markou, A., and Koob, G. F. (1991) Postcocaine anhedonia. An animal model of cocaine withdrawal, Neuropsychopharmacology 4, 17–26. 23. Lin, D., Koob, G. F., and Markou, A. (1999) Differential effects of withdrawal from chronic amphetamine or fluoxetine administration on brain stimulation reward in the rat – interactions between the two drugs, Psychopharmacology (Berl) 145, 283–294. 24. Schulteis, G., Markou, A., Gold, L. H., Stinus, L., and Koob, G. F. (1994) Relative sensitivity to naloxone of multiple indices of opiate withdrawal: a quantitative doseresponse analysis, J Pharmacol Exp Ther 271, 1391–1398. 25. Schulteis, G., Markou, A., Cole, M., and Koob, G. F. (1995) Decreased brain reward produced by ethanol withdrawal, Proc Natl Acad Sci USA 92, 5880–5884. 26. Leith, N. J., and Barrett, R. J. (1976) Amphetamine and the reward system: evidence for tolerance and post-drug depression, Psychopharmacologia 46, 19–25.

Chapter 17 Methods in Drug Abuse Models: Comparison of Different Models of Methamphetamine Paradigms Firas H. Kobeissy, Jeremiah D. Mitzelfelt, Irina Fishman, Drake Morgan, Roger Gaskins, Zhiqun Zhang, Mark S. Gold, and Kevin K. Wang Abstract Methamphetamine (METH) is a widely abused psychomotor stimulant. Investigating the effects of METH use on the brain has been applied in different animal models, including rats, mice, and nonhuman primates. Human abuse of METH occurs in different paradigms ranging from episodes of binge abuse to chronic abuse over years; different animal models have been established to replicate these various patterns of human behavior. In this chapter, we discuss the different models of METH abuse, including the acute model which assesses the immediate effects of METH on the brain and chronic exposure model which simulates the more common long-term use observed in humans; additionally, two other relevant models, escalating dose paradigm and METH self-administration, are examined. In comparing the models, this chapter briefly considers the METH-induced neurotoxic effects associated with each METH administration paradigm and the behavioral changes observed. Key words: Acute, Chronic, Escalating dose, Neurotoxicity, Methamphetamine, Drug of abuse

1. Introduction 1.1. METH Models

Methamphetamine (METH) is a potent psychomotor stimulant that affects both the dopaminergic and serotonergic systems in the brain (1–4). Studies, investigating the effects of METH exposure on the brain, have shown that this drug leads to neurodegeneration (1, 5), oxidative damage (3), apoptosis (1, 2, 4, 6), and necrosis (7) across various brain regions (3, 4, 6, 8). In order to study the toxic effects of METH administration, numerous animal models have been developed over the years. These methods range from singleexposure acute models to extended chronic models. This chapter describes some of these models and their individual applications.


269

270

F.H. Kobeissy et al.

Among the well-characterized models is the acute model regimen. In this model, rats are exposed to a large dose of METH within a single-day period which can be achieved by administering a singlelarge bolus of METH (3, 8) or through repeated doses of METH during a single day (4, 6, 9, 10). Administering repeated doses allows for the assessment of very high doses of METH without the potential of premature animal death due to sudden overdose of METH. Besides being inherently brief studies, acute models are also useful in assessing the initial neurotoxic effects of METH and have shown oxidative stress (3), ER stress (8), as well as calpain- (4, 6, 10) and caspase (4, 6, 8)-mediated cell death. However, they do not model the long-term use of METH abuse that is commonly observed in humans. To assess the chronic effects of METH exposure, recent studies have attempted to develop chronic METH models in animals. The chronic model or the escalating dose model starts with low nontoxic doses and then increases METH concentration administered over the time period until larger neurotoxic doses of METH are achieved (14). This increase can either be consistent across days as demonstrated in Table 1, which simulates the progression of use observed in humans, or end with a large challenge dose on the final day as shown in Table 2, which is often used to assess any protective effects of previous exposure to METH (11). Neurotoxic studies with these models have shown oxidative damage (3), transient decreases in norepinephrine and serotonin (12), lasting decreases in dopamine and tyrosine hydroxylase throughout the brain (12, 13), as well as changes in dopamine transporter levels: either increasing in the nucleus accumbens (13) or decreasing in the striatum and cortex (12). The chronic model, in comparison to the acute model, not only replicates the behavior of long-term human drug abusers, but has also been shown to elicit an appreciably different pattern of neurotoxicity (3). Past research has consistently supported the view that the pattern of neurotoxicity seen in acute METH administration is appreciably different from that seen in chronic use (3, 14). Tokunaga et al. investigated this question by comparing the peroxidative DNA damage and apoptotic bodies in the brains of acute METHtreated rats versus chronically treated rats. His work involved two groups of rats, one following an acute METH protocol and the other following a chronic METH protocol. The first group following the acute protocol received one-time dose of 50 mg/kg of METH prior to being sacrificed while the second group adhering to the chronic METH protocol received repeated METH administration injections of 10 mg/kg/day for 5 days before being sacrificed and compared to a control group. Both the acutely and chronically treated rats showed free radical generation in their nucleus accumbens; however, only the acutely treated rats showed a significant degree of apoptotic activation in all brain regions

Day 8 (mg/kg) 2 2 2 2

Day 1 (mg/kg) 1

Day 10 (mg/kg) 3 3 3 3

1

1

Day 9 (mg/kg) 2.5 2.5 2.5 2.5

Day 3 (mg/kg) 1

Day 2 (mg/kg) 1

Day 11 (mg/kg) 3.5 3.5 3.5 3.5

Day 4 (mg/kg) 1 1 1 1 Day 12 (mg/kg) 4 4 4 4

Day 5 (mg/kg) 1.5 1.5 1.5 1.5

T1 = time of first injection. Use this same time during each day (i.e., always give first injection at 8 a.m.)

T1 T1 + 2 h T1 + 4 h T1 + 6 h

T1 T1 + 2 h T1 + 4 h T1 + 6 h

Table 1 One model of escalating dose of METH administration over 2 weeks

Day 13 (mg/kg) 4.5 4.5 4.5 4.5

Day 6 (mg/kg) 1.5 1.5 1.5 1.5

Day 14 (mg/kg) 5 5 5 5

Day 7 (mg/kg) 2 2 2 2

17 Models of Methamphetamine Abuse 271

272


Table 2 Another model of chronic/escalating dose of METH administration (3-week period) Week 1 T1 T1 + 1 h T1 + 2 h T1 + 3 h T1 + 4 h T1 + 5 h T1 + 6 h

Day 1 (mg/kg) 0.5

0.5

Week 2 T1 T1 + 1 h T1 + 2 h T1 + 3 h T1 + 4 h T1 + 5 h T1 + 6 h Week 3 T1 T1 + 1 h T1 + 2 h T1 + 3 h T1 + 4 h T1 + 5 h T1 + 6 h T1 + 7 h

Day 2 (mg/kg) 1

Day 3 (mg/kg) 1

Day 4 (mg/kg) 1.5

1

1.5

1

1.5

1

1

1.5

Day 1 (mg/kg) 1

Day 2 (mg/kg) 1.5

1

1.5

1

1.5

Day 3 (mg/kg) 2 2 2 2 2 2

Day 4 (mg/kg) 2.5 2.5 2.5 2.5 2.5 2.5

1

1.5

Day 1 (mg/kg) 2 2 2 2 2 2

Day 2 (mg/kg)

Day 3 (mg/kg) 5 5 5 5 5 5 5 5

Day 4 (mg/kg)

T1 = time of first injection. Use this same time for first injection on each day. Table adapted from ref. 11

examined compared to the control rats (3). Tokunaga et al. proposed that repeated administrations of METH may activate oxygen deletion systems, such as SOD, to prevent DNA damage. The neuroprotection afforded by repeated escalating doses of METH administration allows rats to become more resistant to neurotoxicity when they are then challenged with a high-dose METH injection and this protection has been reported to persist for 1–2 weeks following the last METH injection (3). While the chronic model better simulates a long-term human METH abuser than the acute model, it still does not account for the natural increase in METH intake observed in humans (12). Another model of chronic METH abuse has been previously documented in rats’ self-administration model (12). In the selfadministration model, rats have a catheter surgically implanted into their external jugular veins and are housed in special chambers, where they can self-administer METH during certain time frame each day by poking their nose through the correct nose hole. Rats are sacrificed at varying times following the self-administration phase and brain sections are analyzed for neurotoxicity. Interestingly,

17

Models of Methamphetamine Abuse

273

this model uses rats to naturally replicate the human behavioral tendency of progressive increase in their drug intake. Results of brain tissue analysis in these rats show biochemical changes reminiscent to those seen in postmortem samples of human chronic abusers (12). While self-administration is a useful animal model to study the reinforcing effects of chronic METH administration, its main disadvantage includes the cost of the surgical equipment and self-administration chambers that may not be readily available in all laboratories. 1.2. Pharmacokinetics of METH

Although various rat injection paradigms have been created to recreate the broad range of human METH abuse patterns, one key factor that is commonly neglected is the pharmacokinetic differences between different species. For example, the half-life of METH in humans is 10–12 h while in rats the half-life is 1 h. Thus, daily injections of METH in humans allow for drug accumulation in between successive doses, owing to the longer drug half-life which is absent in daily injections of METH in rats. To compensate for the rapid drug elimination in rats, Segal et al. devised a “dynamic infusion procedure,” in which a catheter is surgically implanted in rats and for 15 consecutive days the rats receive a daily iv infusion of 0.5 mg/kg METH followed by multiple additional mini-injections of METH at 0.28 μl (1.3 μg/kg) over a 16-ms duration to simulate the human METH pharmacokinetics of a 12-h half-life. A microdialysis probe inserted into the caudate– putamen assesses extracellular DA levels as a marker of neurotoxicity. The dynamic infusion method replicates that in human METH abuser profile by achieving a 12-h half-life of METH in rats comparable to the plasma values expected in humans (15, 16). Clearly, many animal models of METH administration have been devised to simulate the diversity of METH abuse patterns demonstrated by humans. Each of these models, with its unique advantages and drawbacks, has enriched our understanding of the pathology behind METH-induced neuronal toxicity.

2. Materials 2.1. Animals and Methamphetamine (See Note 1)

1. Adult male rats that were aged 60 days and weighed between 250 and 275 g (see Note 2). 2. Pharmacologic agent (±) METH hydrochloride (Sigma– Aldrich, St. Louis, MO). 3. 0.9% physiological saline. 4. Water (HPLC grade, Burdick & Jackson, Muskegon, MI). 5. Needles (28 gauge, half inch). 6. Syringes (1.0 ml tuberculin).

274


3. Methods 3.1. Animal Habituation and Drug Injection

1. All procedures involving animal handling and processing were done in compliance with the Animal Welfare Act and the University of Florida Institutional Animal Care and Use Committee (IACUC) and the National Institutes of Health guidelines detailed in the Guide for the Care and use of Laboratory Animals. Adult male Sprague-Dawley rats, each weighing 280–300 g, were all habituated for at least 10 days prior to treatment (see Note 3 and Note 11). Animals were housed in pairs in polyethylene cages containing hardwood bedding in a temperature-controlled (approximately 22°C) room with a 12-h light:dark cycle. Animals were given access to rat chow and tap water ad libitum. 2. Following habituation, the rats were separated into two groups, one set of animals was injected intraperitoneally (i.p.) with racemic METH–HCl while the other group received an equivalent volume of 0.9% saline. For all METH administration models, unless otherwise specified, the control rats adhered to a similar injection schedule as the experimental rats receiving equivalent volumes of physiological saline instead of METH.

3.2. Acute Models 3.2.1. Single Injections

1. Separate animals into two groups. Give a one-time intraperitoneal injection of METH–HCl to the experimental set of animals, and an equivalent volume of 0.9% saline to the control set (see Notes 4 and 5). 2. After predetermined time period, sacrifice animals for tissue collection (see Note 6).

3.2.2. Single Exposure (Multiple Injections on Single Day)

1. As with single injections, two groups of rats are needed: a METH group and a saline control group. 2. Rats in the METH group receive a 10 mg/kg i.p. injection while saline group rats receive a similar volume i.p. injection of 0.9% saline. 3. Repeat METH injections every 1 h (4, 6) or 2 h (9, 10) until desired dose of METH has been administered that day (see Note 7). 4. After predetermined time period, sacrifice animals for tissue collection (see Note 8).

3.3. Chronic Models 3.3.1. Repeated Injections

1. Divide animals into two groups and inject the experimental group with the desired dose of METH and the control rats with a comparable volume of 0.9% saline once daily for several consecutive days (see Notes 9 and 10). 2. Twenty-four hours after last injection, sacrifice animals for tissue collection.

17 3.3.2. Escalating Dose Model


275

1. Divide rats into two groups and administer i.p. injections of racemic METH–HCl to the experimental group for 14 days following the schedule in Table 1. (see Notes 7 and 12). The saline group (vehicle group) receives similar volume i.p. injections of physiological 0.9% saline according to the same schedule. 2. Two weeks after last injection, rats are sacrificed for tissue collection to assess any lasting effects of long-term METH exposure.

3.3.3. METH Pretreatment and Challenge Model

1. Similar to the methods described above, divide the animals into two groups and inject rats with either METH or saline for 3 weeks following the schedule in Table 2 (see Note 7). Low doses are given through the first 9 days of injections (pretreatment), followed by a series of high-dose injections on the last day (challenge). 2. Twenty-four hours after last injection, sacrifice rats for tissue collection.

3.3.4. Self-Administration of Methamphetamine (12)

1. After the usual period of habituation, divide the rats into an METH and a control group. 2. Individual rats are housed in special operant conditioning chambers (see Note 13). 3. A catheter is surgically implanted into their external jugular vein through which rats receive infusions of self-administered METH. 4. For eight consecutive days, there is a specified 15-h time frame during which the rats can self-dispense METH, delivered as 2-s injections of METH at a dose of 0.1 mg/kg/injection, by poking their nose through the “active hole” (see Notes 14 and 15). 5. Rats are sacrificed at varying times following the self-administration phase and brain sections are analyzed with HPLC and Western Blots for varying levels of monoamines and proteins (12).

3.3.5. Dynamic Infusion Procedure (15)

1. Following habituation, rats are divided into two groups: experimental and control. 2. All rats have a catheter surgically implanted into their external jugular vein (16) and are placed into individual chambers (see Note 16). 3. To analyze the effects of METH on DA levels, some of the rats are implanted with bilateral guide cannulae through which microdialysis probes can be inserted periodically to measure DA levels (16). 4. For the first 15 days, the rats receive a daily IV infusion of METH 0.5 mg/kg (administered in 0.105 ml) over a 6-s interval (see Note 17).

276


5. Initial infusion is proceeded by computer-controlled minipulses of METH each 0.28 μl (1.3 μg/kg) infused over a 16-ms duration for a cumulative dose of 4.61 mg/kg in a 24-h period (see Note 18) (16). 6. On the 16th day, the experimental animals do not receive their initial infusion of METH (at 0.5 mg/kg) but continue to receive the computer-controlled minipulses for 24 h to simulate a gradual decline in METH plasma levels. 7. On days 17–19, rats receive only dynamic infusions of saline. 8. On days 20–22, rats are challenged with their previous singledaily dynamic infusion of 0.5 mg/kg of METH (16).

4. Notes 1. All of the methods discussed, both acute and chronic, use similar materials and methods. 2. Across the literature, various rat strains are used. The more important factor is age/weight of the animal. 3. During the habituation phase, which consists of at least 10 days prior to METH treatment, animals were handled daily for several minutes by the same researchers who would be subsequently handling them. 4. Single injections of METH should not be administered above 50 mg/kg as this dose approaches the LD50 of METH in rats (3). 5. If an experimenter struggles to do the injections by himself/ herself, it is advisable that a two-person method is used, whereby one individual holds the rat securely while the other prepares the syringes and injects. 6. Single-injection studies typically sacrifice animals 1–4 h after METH injection to assess immediate effects of METH-induced toxicity. 7. Use caution when handling animals during repeated injections, as the stimulatory effects of METH may still be present in the rat, making it hyperactive and potentially aggressive. 8. Animals are sacrificed after 1 h to assess immediate effects of METH (9) or days after to assess the effects of METH on cell death or protein synthesis (4, 6, 10). 9. Administer METH or saline at same time each day. 10. METH can be administered in large doses across fewer days (3) or in smaller doses for more days (13).

17


277

11. While habituation is not a necessary component of the protocol, handling the rats before starting injections is recommended as it makes them easier to handle when they are on METH. 12. METH was mixed in concentrations so that the volume of each injection was 1 ml/kg. 13. The operant chambers present rats with two possible holes to poke their nose through. Only one hole, the active hole, provides reinforcement by delivering an infusion of METH. A nose poke through this hole is detected by a nose poke operanda and a feedback signal is sent that delivers 2-s injections of METH, at a dose of 0.1 mg/kg/injection, to the rat. The control rats receive an injection of saline every time a responsecontingent injection of 0.1 mg/kg METH is self-administered by the experimental rats (16). 14. For eight consecutive days, rats have a daily 15-h time frame when they can self-administer METH by nose pokes through the active hole. The beginning of a 15-h session is signaled by turning on a white-house light and injecting a priming dose 0.1 mg/kg METH (or saline for the control rats). Thereafter, every nose poke into the active hole delivered an IV injection of 0.1 mg/kg METH followed by a 30-s timeout period, where the chamber was dark and nose pokes did not result in rewards (12). 15. The control rats receive an injection of saline each time a response-contingent injection of 0.1 mg/kg METH is selfadministered by the experimental rats. 16. Rats began METH infusions 2 weeks after catheter placement. 17. Control group receives comparable volumes of 0.9% saline, when the experimental rats are receiving either their initial infusion or computer-controlled minipulse injections. 18. An initial 0.5 mg/kg dose was followed by minipulses delivering 1.3 μg/kg of METH resulting in a daily cumulative dose of 4.61 mg/kg over a 24-h period to achieve a 24-h pharmacokinetic pattern similar to that of METH in humans (16). References 1. Cadet, J. L., Jayanthi, S., and Deng, X. (2003) Speed kills: cellular and molecular bases of methamphetamine-induced nerve terminal degeneration and neuronal apoptosis, Faseb J 17, 1775–1788. 2. Cadet, J. L., Ordonez, S. V., and Ordonez, J. V. (1997) Methamphetamine induces apoptosis in immortalized neural cells: protection by the proto-oncogene, bcl-2, Synapse(New York, N.Y 25, 176–184.

3. Tokunaga, I., Ishigami, A., Kubo, S., Gotohda, T., and Kitamura, O. (2008) The peroxidative DNA damage and apoptosis in methamphetamine-treated rat brain, J Med Invest 55, 241–245. 4. Warren, M. W., Larner, S. F., Kobeissy, F. H., Brezing, C. A., Jeung, J. A., Hayes, R. L., Gold, M. S., and Wang, K. K. (2007) Calpain and caspase proteolytic markers co-localize with rat cortical neurons after exposure to

278

5.

6.

7.

8.

9.

10.

11.

F.H. Kobeissy et al. methamphetamine and MDMA, Acta neuropathologica 114, 277–286. Cadet, J. L., and Krasnova, I. N. (2009) Molecular bases of methamphetamine-induced neurodegeneration, Int Rev Neurobiol 88, 101–119. Warren, M. W., Kobeissy, F. H., Liu, M. C., Hayes, R. L., Gold, M. S., and Wang, K. K. (2005) Concurrent calpain and caspase-3 mediated proteolysis of alpha II-spectrin and tau in rat brain after methamphetamine exposure: a similar profile to traumatic brain injury, Life sciences 78, 301–309. Davidson, C., Gow, A. J., Lee, T. H., and Ellinwood, E. H. (2001) Methamphetamine neurotoxicity: necrotic and apoptotic mechanisms and relevance to human abuse and treatment, Brain research 36, 1–22. Jayanthi, S., McCoy, M. T., Beauvais, G., Ladenheim, B., Gilmore, K., Wood, W., 3rd, Becker, K., and Cadet, J. L. (2009) Methamphetamine induces dopamine D1 receptor-dependent endoplasmic reticulum stress-related molecular events in the rat striatum, PLoS One 4, e6092. Eyerman, D. J., and Yamamoto, B. K. (2007) A rapid oxidation and persistent decrease in the vesicular monoamine transporter 2 after methamphetamine, Journal of neurochemistry 103, 1219–1227. Staszewski, R. D., and Yamamoto, B. K. (2006) Methamphetamine-induced spectrin proteolysis in the rat striatum, Journal of neurochemistry 96, 1267–1276. Broom, S. L., and Yamamoto, B. K. (2005) Effects of subchronic methamphetamine

exposure on basal dopamine and stress-induced dopamine release in the nucleus accumbens shell of rats, Psychopharmacology 181, 467–476. 12. Krasnova, I. N., Justinova, Z., Ladenheim, B., Jayanthi, S., McCoy, M. T., Barnes, C., Warner, J. E., Goldberg, S. R., and Cadet, J. L. (2010) Methamphetamine self-administration is associated with persistent biochemical alterations in striatal and cortical dopaminergic terminals in the rat, PLoS One 5, e8790. 13. Cadet, J. L., McCoy, M. T., Cai, N. S., Krasnova, I. N., Ladenheim, B., Beauvais, G., Wilson, N., Wood, W., Becker, K. G., and Hodges, A. B. (2009) Methamphetamine preconditioning alters midbrain transcriptional responses to methamphetamine-induced injury in the rat striatum, PLoS One 4, e7812. 14. Danaceau, J.P., Deering, C.E., Day, J.E., Smeal, S.J., Johnson-Davis, K.L., Fleckenstein, A.E., Wilkins D.G. (2007) Persistence of tolerance to methamphetamine-induced monoamine deficits. Eur J Pharmacol 559, 46–54. 15. Segal, D.S., Kuczenski, R., O’Neil, M.L., Melega, W.P., and Cho, A.K. (2003) Escalating Dose Methamphetamine Pretreatment Alters the Behavioral and Neurochemical Profiles Associated with Exposure to a High- Dose Methamphetamine Binge. Neuropsychopharmacology 28, 1730–1740. 16. Segal, D.S., Kuczenski, R. (2006) Human Methamphetamine Pharmacokinetics Simulated in the Rat: Single Daily Intravenous Administration Reveals Elements of Sensitization and Tolerance. Neuropsychopharmacology 31, 941–955.

Chapter 18 Cocaine Self-Administration in Rats: Hold-Down Procedures Benjamin A. Zimmer and David C.S. Roberts Abstract For decades, researchers have used animal self-administration models to examine the effects drugs of abuse have on physiology and behavior. Sophisticated self-administration procedures have been developed to model many different aspects of drug addiction. The hold-down procedure provides animals with control over the amount of each injection. Holding the lever down turns the syringe pump on and subsequently releasing the lever turns the pump off. In this way, animals can hold the lever down for any duration of time thereby self-administering any dose on a continuous spectrum. This procedure eliminates some of the ambiguity in translating results from effects only observed at one unit dose and allows examination of which dose the animal “prefers” at different times. Key words: Cocaine self-administration, Hold down, Dose

1. Introduction The use of a unit dose is seen almost exclusively in drug self-administration studies using animals. When humans use drugs, they are able to choose any dose they prefer on a continuous spectrum (e.g., drinking alcohol in different sized sips or inhaling different amounts of smoke from a cigarette). In animal studies however, the dose is offered as a fixed unit dose determined by the experimenter. These studies typically involve the animal pressing a lever to receive an injection. The dose is selected by the experimenter by determining the concentration of drug and the volume of drug to be delivered (volume is determined by the amount of time the syringe pump is on). These procedures have led to the generation of dose–response curves and have provided insight into the drug addiction process. However, it should be emphasized that by using only experimenter-selected unit doses our models may fail to


279

280

B.A. Zimmer and D.C.S. Roberts

account for the complex interactions that determine the pattern of human drug intake. For example, humans likely do not take a consistent dose during a cocaine binge but many doses of various sizes. Therefore, it would be beneficial to have additional procedures available where animals can choose a dose they prefer from a continuous spectrum. Although the majority of self-administration studies use fixed doses, there have been studies that have given animals either a range of doses or a choice between doses within a session. For example, variable-dose procedures offer multiple doses within a single session and measure changes in responding relative to each dose. With this manipulation, post-infusion pauses are examined to determine the ability of the animal to regulate its behavior, and within-session dose–response curves can be generated (1, 2). Other studies have attempted to examine relative reinforcing efficacy of a range of doses by giving animals a choice between two levers, each reinforced with a different dose of the same drug (3–6). The hold-down schedule of reinforcement was created to give animals a true continuous range of doses (see Note 1) to select from (7). This was accomplished by having the syringe pump turn on when the lever was depressed and turn off when the lever was released. The dose that was infused was determined by the length of the hold-down response. Data from Morgan et al. (7) revealed that behavior on the hold-down procedure is tightly regulated and consistent (see Note 2). For example, they demonstrated that animals self-administered a similar amount of drug within each session as on a fixed ratio 1 schedule (where a single lever press results in a unit dose injection). In addition, animals adapted the amount of time the lever was depressed across a 16-fold concentration difference so that the total drug taken did not vary. The hold-down procedure represents a useful alternative to self-administration procedures that use fixed, experimenter-selected unit doses (see Note 3). Here, we describe the protocol for conducting self-administration studies using the hold-down procedure, and discuss methods of analyzing the resulting data.

2. Materials 2.1. Cannulae Supplies

1. Stainless steel guide cannula with threaded, plastic collar, 22-gauge, 5-mm upward projection (Plastics One, Roanoke, VA: C313G-5UP). 2. Silicone elastomer tubing (Silastic, Fisher, USA; 2 sizes: ID 0.012 in., OD 0.025 in. and ID 0.025 in., OD 0.047 in.). 3. Xylene substitute (CitriSolv, Fisher, USA).

18

Hold Down Procedures in Cocaine Self-Administration

281

4. Dental acrylic (Ortho-Jet, Lang Dental, Wheeling, IL). 5. Plastic mesh (Small Parts, KY: CMP-0500-D). 6. Slotted catheter mold (Faircloth Machinery, WinstonSalem, NC). 7. Silicon-based aerosol lubricant (Fisher, USA: 19-047-445). 8. Silicone medical adhesive (Silastic, Dow Corning, Midland, MI). 9. Hand sanding tool (Dremel, Racine, WI). 2.2. Surgical Supplies

1. Needle holders (Roboz, MD). 2. Small microdissecting forceps (Roboz, MD). 3. Curved microdissecting forceps (Roboz, MD). 4. Tissue Forceps (Roboz, MD). 5. Microdissecting scissors (Roboz, MD). 6. Microdissecting scissors 18 mm for vein (Roboz, MD). 7. Scalpel handle (Roboz, MD). 8. Hemostatic forceps, large (Roboz, MD). 9. Hemostatic forceps, small (Roboz, MD). 10. Cannulas (see Subheading 3.1). 11. 2″ × 2″ Gauze (Tyco, MA). 12. Sterile cotton swabs (Fisher, USA). 13. Scalpel blade, size 10 (Feather, Japan). 14. 4–0-Silk suture (Ethicon, USA). 15. 3–0-Monofilament suture (Ethicon, USA). 16. Skin glue (Webglue, Webster Vetinary, MA). 17. Two squares of sterile surgical cloth; one for surgery, one for holding sterile tools (Tyco, MA). 18. 1-ml Syringe filled with sterile saline-attached to a blunted 22-gauge needle with tubing attached to cannula (Becton Dickinson, NJ). 19. Povidone–iodine solution (Betadine, Purdue Products, CT). 20. 70% Isopropyl alcohol solution (Fisher, MA). 21. Artificial tears (Webster Veterinary, MA). 22. Latex/nonlatex gloves. 23. Mask. 24. Clippers to shave rat.

2.3. Selfadministration Supplies

1. Polyethylene tubing (Tygon, Fisher, MA, ID 0.02 in., OD 0.06 in.). 2. Drug dissolved in saline in 10-ml syringe.

282


3. Pump (Razel, CT). 4. Tether and swivel (Instech, PA). 5. Self-administration Associates, VT).

apparatus

(Privately

made

or

Med

3. Methods Catheters are made in our laboratory (see Subheading 3.1), but can also be ordered commercially (CamCaths, Cambridgeshire, UK). Approximately 1 week after arrival to the housing colony, rats are anesthetized (ketamine + xylazine 100 and 8 mg/kg, i.p.) and implanted with chronic indwelling jugular venous catheters (see Subheading 3.2). All catheters feature an externalized access port which attaches via polyethylene tubing (protected with a spring tether) to an infusion pump. Three to five days after surgery rats begin a training protocol that lasts 2–14 days. Animals must acquire a stable pattern of baseline responding, a concept that is referred to as acquisition. In the present protocol, acquisition occurs in 85% of animals. Animals that do not reach acquisition criteria within 10 days of receiving access to cocaine are excluded from self-administration experiments due to potential confounds, such as the development of aversive associations with cocaine and/or the self-administration environment that might have impeded acquisition. After the training criteria have been met, animals begin the HD schedule (see Note 4). 3.1. Cannulae Making Procedure

1. Cut a 14-cm piece of the smaller silicone elastomer tubing (ID 0.012 in.; OD 0.025 in.). 2. Submerse approximately 1.5 cm of the tubing in xylene substitute under a fume hood for about 3 min to expand the plastic. 3. Drain fluid from tubing and slide over the guide cannula until it reaches the plastic collar. Let tubing dry overnight. 4. Cut a 2.5-cm piece of the larger silicone elastomer tubing (ID 0.025 in.; OD 0.047 in.). 5. Completely immerse the tubing in xylene substitute under a fume hood for approximately 3 min until plastic has expanded. 6. Without draining fluid from inside the tubing, slide it over the entire length of the smaller tubing until it reaches the threaded plastic collar, being careful not to kink or damage the small tubing. 7. Cut a 2.5-cm diameter circle of plastic mesh. 8. Using a soldering iron, melt the edges of the mesh together until there are no sharp edges.

18


283

9. Sand the edges of the mesh until they are smooth with a hand sanding tool on the lowest speed. 10. Spray the slotted mold with silicon-based lubricant. 11. Arrange the guide cannula so that roughly one third of the threaded collar protrudes into the mold and clamp tightly. 12. Mix the powder and liquid components of quick-hardening dental acrylic until slightly runny and quickly drip into the mold until the well is nearly full. 13. Place the round piece of mesh onto the well and apply a small amount of the acrylic to secure the mesh to the guide cannula. Allow a minimum of 45 min for acrylic to dry. 14. Remove guide cannula from mold. Smooth any rough edges with the sander and remove any excess acrylic from the plastic mesh. 15. Fill any air holes with acrylic as described above. 16. Apply a small bead of silicone medical adhesive 3.2 cm from the end of the tubing, and let dry overnight. 3.2. Surgery Methods

1. Autoclave the surgical instruments and surgical cloths. 2. Set up surgical supplies listed above. 3. Place tools on the drape it was autoclaved in. 4. Anesthetize animal with 100 mg/kg ketamine and 8 mg/kg xylazine, i.p. 5. Shave the animals back from approximately 1 in. behind the shoulder blades to the midpoint of the back. Then, turn the animal over and shave the right side from the chest to the jaw. 6. Use gauze to do a two stage wash (70% isopropyl alcohol and povidone–iodine solution, repeat twice on each side). 7. Place animal on the surgical cloth-belly down-head pointing left. 8. Using new scalpel blade, make an incision in the midline of the back approximately 1 in. in length centered over the shoulder blades. 9. With the tweezers, hold the skin at the edge of the incision and use the tissue scissors to gently tease away the skin from the underlying tissue. The goal is to make a subcutaneous pocket under the skin which would allow the mesh at the end of the cannula to lie flat. 10. Attach the tubing from the 1-ml syringe onto the cannula and flush with sterile saline. 11. Place the mesh flat under the skin with the tubing pointing toward the animal’s head. 12. Cover the incision with gauze and flip the animal over.

284


13. Look at the shaved area for a pulse; it should be between the shoulder and the middle of the neck. Make a 1–2 cm incision parallel to where the jugular vein is underneath. 14. Using the tweezers, tease the skin away from the tissue all around the incision. 15. With curved small tweezers, scoop the vein up onto the tweezers. Using the small straight tweezers, remove all excess tissue surrounding the vein. 16. Place a piece of suture under the vein to hold it in place. Starting at the top of the neck incision, run the curved hemostats directly under the skin, over the shoulder to the top of the back incision. Push the head of the hemostats through the connective tissue and out of the body. Grab the tubing of the cannula with the hemostats and hold tightly, pulling the tubing through the tunnel along the neck and out of the neck incision. 17. Squirt a small amount of saline through the cannula and irrigate the vein—repeat when necessary to prevent the vein from drying. 18. Using the curved forceps in your right hand, gently slide one side of the straight forceps under the vein. 19. With sharp scissors, make a small cut in the vein. 20. Carefully introduce the tubing from the catheter into the vein. 21. Make a small stitch on either side of the bulb on the catheter to ensure it stays in place. Do not make it so tight that fluid cannot pass through. 22. Place a stitch on the other side of the silicone knob. 23. Sew up the internal tissue with 4–0-silk. 24. Use skin glue to secure the external tissue. 25. Turn the animal over on its belly (head pointing left) and adjust the mesh so it is lying flat under the skin. 26. Close up the rest of the wound with the 3.0-monofilament sutures. 27. Place animal in the recovery area. 3.3. Set Up for Self-administration

1. Connect drug syringe to rat via polyethylene tubing.

3.4. Acquisition Protocol

1. Provide 24 h access to cocaine: After allowing time to recover from surgery (3–7 days), animals are given access to a cocainepaired lever within their home operant chamber. Selfadministration sessions begin 6 h into the 12-h dark cycle and occur 7 days per week. Each session lasts 24 h. Access is

2. Place syringe on pump, making sure there is no slack between the two.

18


285

provided in the middle of the dark cycle because this is the time period at which nocturnal animals exhibit the greatest amount of exploratory behavior. 2. Provide ad libitum food and water: During the acquisition period, animals are given unlimited access to food and water. Experimenters monitor food and water levels in addition to the room temperature daily. In the current protocol, animals are not trained to self-administer food or water prior to being given access to cocaine. 3. Provide a signal that drug is available: The availability of drug is signaled to the animal by the extension of a lever into the home operant chamber at the beginning of each session. The lever itself serves as a conditioned cue predicting the availability of drug. 4. Provide a moderately high dose of cocaine: During the acquisition period, animals are given access to a 0.75 mg/kg dose of cocaine, a moderately high dose that is often readily selfadministered by rats. Note that this dose nears the top of the progressive ratio dose–response curve, and is therefore considered to function as a strong reinforcer. Higher doses are also self-administered but are avoided during acquisition due to the potential development of associations with the aversive effects of high cocaine doses. 5. Infusion size and duration: When the lever is depressed a cocaine solution (2.5 mg/ml) is infused as a bolus of 0.1 ml over approximately 4–5 s. The duration of the cocaine infusion is adjusted to account for the animal’s body weight. Slower infusion rates (e.g., 25 s) may result in different patterns of self-administration behavior after training. 6. Provide a time-out period: Following each response, the lever is retracted and a stimulus light is illuminated for a 20-s timeout period. The time-out serves to prevent the animals from receiving unintended injections by making stereotypic, or repetitive, movements on the lever immediately after the drug injection. It should be noted that trained animals usually avoid the lever during stereotypy and initiate self-imposed time-out periods. 7. Avoid priming the animal: During acquisition animals do not receive experimenter-initiated cocaine injections (i.e., drug primes). Especially, when using high cocaine doses, presenting animals with noncontingent cocaine injections may lead to decreased rates of acquisition, an effect that is presumably due to the development of aversive associations with the high cocaine dose. 8. Session termination: Sessions are terminated after a maximum of 20 infusions or a period of 24 h has elapsed. A 10-min pause

286


is provided between acquisition sessions to allow the experimenter to monitor the health of each animal and record data. At the beginning of each session, the daily response number resets at zero. 9. When has an animal acquired? An animal is considered to have acquired when the following criteria are met: responding begins at the onset of the 24-h session, stable inter-response intervals are observed between responses (these can be statistically verified by assessing the variance between responses), and 20 responses occur within the session. 10. Identification of stable patterns of cocaine self-administration: The 20 responses often occur in two patterns commonly referred to as the loading phase and maintenance phase. The loading phase occurs during the first 5–10 min of the session and is characterized by brief period of rapid responding. The maintenance phase, which is characterized by stable inter-response intervals that are observed for the duration of the experimental session, is a hallmark of stable cocaine acquisition. Often times, when an animal’s indwelling jugular catheter loses patency, or the cocaine bolus is not being delivered properly, the problem is identified by the erratic nature of the inter-injection intervals during the maintenance phase. 3.5. Hold Down

1. Provide ad libitum food and water. Food and water should be regularly monitored to ensure the health of the animal. 2. Choose a cocaine concentration. Animals will have control over the dose they inject, but an adequate concentration of cocaine must be in the syringe. Morgan et al. (7) demonstrated that concentrations as low 1.25 mg/ml and as high as 20 mg/ml are sufficient to maintain responding. 3. Select session length. The experimental question should determine the length of the session. Sessions lasting more than 6 h should include withdrawal periods to minimize tolerance to cocaine and seizures. 4. Provide a signal that drug is available. The availability of drug is signaled to the animal by the extension of a lever into the home operant chamber at the beginning of each session. The lever itself serves as a conditioned cue predicting the availability of drug. 5. Provide a cue that drug is being infused. The stimulus light that illuminates during the time-out period during acquisition (see Subheading 3.4, step 6) serves as a conditioned cue for drug infusion. It is important that this stimulus light be illuminated when the lever is depressed. Because hold-down self-administration does not involve an automatic bolus of drug, the stimu-

18


287

lus light signals that responding on the lever will result in cocaine infusion. 6. Avoid priming the animal. Animals do not receive any automatic infusion of drug. 3.6. Data Analysis

1. Cumulative drug intake: Cumulative drug intake is typically displayed using a line graph, where each drug infusion is represented by a corresponding upward deflection of the line. This analysis is useful for observing trends in self-administration behavior during a session or for comparing self-administration patterns across sessions. Figure 1 shows a cumulative

Fig. 1. Example data from one rat showing the cumulative dose self-administered is stable across multiple sessions. Each response on the lever is represented by an upward deflection in the line. The magnitude of the upward deflection represents the length of time the lever was held down.

288


Fig. 2. Example data from one rat showing the range of doses self-administered in a single HD session. The rat pressed the lever 202 times. Responses occurring within 20 s of each other were grouped together so that there were 72 total infusions. Data represent the percent of these infusions that occurred for each particular dose.

record of the same rat self-administering cocaine on the hold-down procedure for 3 h on two different days. Note that total amount of drug taken during the 3 h session is similar on both days. 2. Dose–response curve: On the hold-down procedure, animals typically choose a wide range of doses throughout the session. A dose–response curve represents the number of times the rat chooses a particular dose. Responses occurring within 20 s of each other are grouped together to create a single infusion (see Note 5). Infusions are then sorted into ranges of doses and graphically represented (Fig. 2). 3. Inter-injection interval: The inter-injection interval is the amount of time in between infusions (an infusion is defined as all responses occurring within 20 s of each other: (see Note 5)). This interval normally correlates positively with the size of the preceding infusion (Fig. 3) indicating that the animal is successfully regulating blood levels of cocaine.

18


289

Fig. 3. Example data from one rat showing the correlation between the dose the rat self-administered and the subsequent inter-injection interval. Each point represents a group of responses occurring within 20 s of each other and the amount of time before the next infusion occurred. The correlation coefficient was calculated (r = 0.67).

4. Notes 1. The hold-down procedure is a successful method of giving animals the ability to choose their dose along a continuum rather than fixed, experimenter-selected unit doses. This is significant because it allows for comparisons between how animals and humans choose to self-administer drugs of abuse, and it removes ambiguous experimental results, such as a treatment that attenuates cocaine self-administration at one unit dose but not another. 2. The hold-down procedure also demonstrates a behavioral phenotype that is not observed in other schedules. Under this schedule animals take a variety of doses, some of which far exceed doses predicted by other self-administration procedures. Unusually large doses are especially likely during the initial loading phase of a session. In addition, following the initial loading dose, animals typically choose small, rapid doses as opposed to large doses. This indicates that animals prefer to tightly titrate their cocaine intake. 3. The hold-down self-administration procedure sidesteps many of the unwanted aspects of other schedules of reinforcement. For example, because animals typically choose larger doses at the beginning of the session (loading phase) and smaller doses throughout the rest of the session (maintenance phase), any unit

290


dose selected by the experimenter will at some point during the session be in conflict with what the animal would self-administer if given the choice on a continuous spectrum. Also, most selfadministration procedures include a time-out period which interrupts the initial loading phase. This may disrupt the natural behavior of the animal, adding a confound with unknown effects. The hold-down procedure avoids this problem by giving animals direct control of their infusions with no time-out periods. Similarly, the maintenance phase, where animals typically titrate blood-levels of cocaine for the remainder of the session, is confounded by the large bolus of drug that unit dose paradigms employ. However, the hold-down procedure gives the animal a choice between taking a bolus or a very small infusion. 4. At the end of an experiment, catheter patency should be confirmed by providing access to cocaine self-administration on a fixed ratio schedule of reinforcement (0.75 mg/kg) for 6 h with a 20 injection maximum. Animals with good catheters should have regular post-infusion pauses and self-administer 20 injections within the session. 5. Responses under the hold-down procedure typically occur in rapid bursts followed by long pauses. We group these clusters of responses together by counting all lever presses that occur within 20 s of each other as one infusion.

Acknowledgments This work was supported by R01 DA14030 (DCSR). References 1. Gerber, G. J., and Wise, R. A. (1989) Pharmacological regulation of intravenous cocaine and heroin self-administration in rats: a variable dose paradigm, Pharmacol Biochem Behav 32, 527–531. 2. Panlilio, L. V., Thorndike, E. B., and Schindler, C. W. (2006) Cocaine self-administration under variable-dose schedules in squirrel monkeys, Pharmacol Biochem Behav 84, 235–243. 3. Johanson, C. E., and Schuster, C. R. (1975) A choice procedure for drug reinforcers: cocaine and methylphenidate in the rhesus monkey, J Pharmacol Exp Ther 193, 676–688. 4. Llewellyn, M. E., Iglauer, C., and Woods, J. H. (1976) Relative reinforcer magnitude under a nonindependent concurrent schedule of cocaine

reinforcement in rhesus monkeys, J Exp Anal Behav 25, 81–91. 5. Lynch, W. J., LaBounty, L. P., and Carroll, M. E. (1998) A novel paradigm to investigate regulation of drug intake in rats self-administering cocaine or heroin intravenously, Exp Clin Psychopharmacol 6, 22–31. 6. Ward, S. J., Morgan, D., and Roberts, D. C. (2005) Comparison of the reinforcing effects of cocaine and cocaine/heroin combinations under progressive ratio and choice schedules in rats, Neuropsychopharmacology 30, 286–295. 7. Morgan, D., Liu, Y., Oleson, E. B., and Roberts, D. C. (2009) Cocaine self-administration on a hold-down schedule of reinforcement in rats, Psychopharmacology (Berl) 201, 601–609.

Chapter 19 Cocaine Self-Administration in Rats: Discrete Trials Procedures Carson V. Dobrin and David C.S. Roberts Abstract A discrete trials procedure involves splitting up a self-administration session so that there are multiple distinct trials and inter-trial-intervals. This schedule is well suited to be used over 24 h periods which allows insight into diurnal variability in self-administration behavior. DT is also well suited for investigations using pretreatments for increasing or decreasing both high and low probability behavior. Key words: Cocaine, Self-administration, Discrete trials, Rodent, Circadian

1. Introduction Intravenous self-administration, first described by Weeks (1964) (1), is an operant task in which animals perform a behavior, typically pressing a lever, to receive a drug injection. There are an infinite numbers of schedules, from a simple fixed-ratio to more complex multiple and concurrent schedules (see ref. 2 for more details) that define the presentation of a reinforcer following a given behavior. The timing within a schedule is very important as behavior is influenced by blood levels of drugs, thus changing the way an animal will respond, depending on current blood levels in the system. Some protocols demand separation of the session into discrete blocks of trials, thus controlling the amount of drug present per trial. A discrete trials (DT) procedure involves splitting up a selfadministration session so that there are multiple distinct trials and inter-trial-intervals (ITI). Stretch was the first to introduce discrete trials into the self-administration literature (3–5). Trials begin at


291

292

C.V. Dobrin and D.C.S. Roberts

Fig. 1. A representative event record for an individual rat self-administering cocaine under a discrete trial (Dt) procedure (three trials per hour, DT3) over 21 days of testing. Intake during the dark hours is indicated by the black bar. Vertical lines indicated the time of a self-administered drug infusion. Dots indicate a trial during which a drug infusion was available but not taken. This event record shows a typical circadian pattern observed with DT3, which is very stable over days. (Reproduced from (8) with permission from Elsevier Science).

fixed points in time, last for a specific amount of time and are followed by a defined ITI period. For example, a trial could start at 10:00 a.m., last for 10 min and then be followed by a 20 min ITI during which the reinforcement schedule is suspended. After the ITI, a new trial begins. One trial presentation per hour is referred to as DT1, two trials per hour as DT2 and so on. Figure 1 shows an event record for an individual rat on a DT3 at 1.5 mg/kg cocaine. Interestingly, rats show highly regular circadian patterns of cocaine self-administration on this schedule with high intake during the dark (or active phase), and lower intake during the light phase (6–8). These types of protocols are much more common in the nonhuman primate literature, whereas rat self-administration studies tend to use schedules without separate components and breaks. We use DT procedures as a way to give animals 24 h access to cocaine without some of the delirious effects of giving free-access. Historically, 24-h access to cocaine produced extreme toxicity and lethality. One of the earliest observations in the cocaine self-administration literature is that rats and nonhuman primates, when given unlimited access to cocaine or other stimulants, self-administered in very long binges, producing extreme toxicity (9–11). Deneau and colleagues (1969) used a nonhuman primate model of unlimited access cocaine self-administration. These monkeys self-administered

19

Discrete Trials Procedures in Cocaine Self-Administration

293

Fig. 2. Effect of access conditions on intake over a 24 h time period. As access is increased so is the amount of drug taken. Shown are data for 2, 3, 4, and 5 discrete trials per hour. Points represent the mean (±S.E.M.) cocaine intake averaged across 21 days. Additionally, when you give animals 24 h access, they take more during the dark phase (as indicated by the black bar ) compared to the light phase. (Reproduced from (8) with permission from Elsevier Science).

a high cocaine dose on a fixed ratio one (or FR1) schedule of reinforcement (where every time the lever was pressed, the monkey received an infusion of cocaine) to the point of severe exhaustion and convulsions. All of the monkeys on this schedule died within 30 days. Because of these studies, and others like it, the use of unlimited access models has declined, in favor of 2 and 6 h schedules, where toxicity can be controlled. Here, we describe how a DT schedule can be used in rodent self-administration studies to allow round-the-clock access to cocaine while limiting toxicity seen with other 24 h access models. Figure 2 shows an example of the circadian pattern of drug intake across different access conditions. As the dose or availability of cocaine is increased so also is the amount of cocaine selfadministered. Traditionally, DT procedures involve restricting the number of drug infusions to one per trial (3–5, 12, 13). More recently, however, we have begun to explore allowing access as many infusions as can be self-administered within a 5 min trial. We have found this to be an excellent way to examine changes in daily drug intake patterns and escalation of drug intake while offering intermittent round-the-clock access. Figure 3 illustrates a fourfold escalation in drug intake across 21 days. This animal was given access to cocaine during 5 min discrete trials, once each hour for the duration of the study.

294


Fig. 3. Escalation of cocaine intake on a discrete trials procedure across 21 days. Each data point represents total cocaine intake during each trial. Animals were given access to as many infusions as could be self-administered within a 5 min trial, one trial per hour for the duration of the study. Trials in which no cocaine was self-administered are not included. Cocaine intake increased nearly fourfold over time (r2 = 0.4). In the beginning, the dose of cocaine tended to be 1 mg/kg and lower. By the final week, the rat was selfadministering as much as 6 mg/kg per 5 min trial.


1. Stainless steel guide cannula with threaded, plastic collar, 22-gauge, 5-mm upward projection (Plastics One, Roanoke, VA: C313G-5UP). 2. Silicone elastomer tubing (Silastic, Fisher, USA; 2 sizes: ID 0.012 in., OD 0.025 in. and ID 0.025 in., OD 0.047 in.). 3. Xylene substitute (CitriSolv, Fisher, USA). 4. Dental acrylic (Ortho-Jet, Lang Dental, Wheeling, IL). 5. Plastic mesh (Small Parts, KY: CMP-0500-D). 6. Slotted catheter mold (Faircloth Machinery, Winston-Salem, NC). 7. Silicon-based aerosol lubricant (Fisher, USA: 19-047-445). 8. Silicone medical adhesive (Silastic, Dow Corning, Midland, MI). 9. Hand sanding tool (Dremel, Racine, WI).

2.2. Surgical Supplies

1. Needle holders (Roboz, MD). 2. Small microdissecting forceps (Roboz, MD). 3. Curved microdissecting forceps (Roboz, MD).

19


295

4. Tissue Forceps (Roboz, MD). 5. Microdissecting scissors (Roboz, MD). 6. Microdissecting scissors 18 mm for vein (Roboz, MD). 7. Scalpel handle (Roboz, MD). 8. Hemostatic forceps, large (Roboz, MD). 9. Hemostatic forceps, small (Roboz, MD). 10. Cannulas (see Subheading 3.1). 11. 2″ × 2″ Gauze (Tyco, MA). 12. Sterile cotton swabs (Fisher, USA). 13. Scalpel blade, size 10 (Feather, Japan). 14. 4–0-Silk suture (Ethicon, USA). 15. 3–0-Monofilament suture (Ethicon, USA). 16. Skin glue (Webglue, Webster Vetinary, MA). 17. Two squares of sterile surgical cloth; one for surgery, one for holding sterile tools (Tyco, MA). 18. 1-ml syringe filled with sterile saline-attached to a blunted 22-gauge needle with tubing attached to cannula (Becton Dickinson, NJ). 19. Povidone–iodine solution (Betadine, Purdue Products, CT). 20. 70% isopropyl alcohol solution (Fisher, MA). 21. Artificial tears (Webster Vetinary, MA). 22. Latex/nonlatex gloves. 23. Mask. 24. Clippers to shave rat. 2.3. Selfadministration Supplies

1. Polyethylene tubing (Tygon, Fisher, MA, ID 0.02 in., OD 0.06 in.). 2. Drug dissolved in saline in 10-ml syringe. 3. Pump (Razel, CT). 4. Tether and swivel (Instech, PA). 5. Self-administration Associates, VT).

apparatus

(Privately

made

or

Med

3. Methods Indwelling venous catheters are made in our laboratory, but can also be ordered commercially (CamCaths, Cambridgeshire, UK). Approximately 1 week after arrival to the housing colony, rats are anesthetized (ketamine + xylazine (100 and 8 mg/kg, i.p.)) and

296


implanted with chronic indwelling jugular venous catheters (see Subheading 3.2). All catheters feature an externalized access port which attaches via polyethylene tubing (protected with a spring tether) to an infusion pump. Three to five days after surgery rats begin a training protocol that lasts 2–14 days. Animals must acquire a stable pattern of baseline responding, a concept that is referred to as acquisition. In the present protocol, acquisition occurs in 85% of animals. Animals that do not reach acquisition criteria within 10 days of receiving access to cocaine are excluded from self-administration experiments due to potential confounds, such as the development of aversive associations with cocaine and/or the self-administration environment that might have impeded acquisition. After the training criteria have been met, they begin the DT schedule. 3.1. Cannulae Making Procedure

1. Cut a 14-cm piece of the smaller silicone elastomer tubing (ID 0.012 in.; OD 0.025 in.). 2. Submerse approximately 1.5 cm of the tubing in xylene substitute under a fume hood for about 3 min to expand the plastic. 3. Drain fluid from tubing and slide over the guide cannula until it reaches the plastic collar. Let tubing dry overnight. 4. Cut a 2.5-cm piece of the larger silicone elastomer tubing (ID 0.025 in.; OD 0.047 in.). 5. Completely immerse the tubing in xylene substitute under a fume hood for approximately 3 min until plastic has expanded. 6. Without draining fluid from inside the tubing, slide it over the entire length of the smaller tubing until it reaches the threaded plastic collar, being careful not to kink or damage the small tubing. 7. Cut a 2.5-cm diameter circle of plastic mesh 8. Using a soldering iron, melt the edges of the mesh together until there are no sharp edges. 9. Sand the edges of the mesh until they are smooth with a hand sanding tool on the lowest speed. 10. Spray the slotted mold with silicon-based lubricant. 11. Arrange the guide cannula so that roughly one third of the threaded collar protrudes into the mold and clamp tightly. 12. Mix the powder and liquid components of quick-hardening dental acrylic until slightly runny and quickly drip into the mold until the well is nearly full. 13. Place the round piece of mesh onto the well and apply a small amount of the acrylic to secure the mesh to the guide cannula. Allow a minimum of 45 min for acrylic to dry.

19


297

14. Remove guide cannula from mold. Smooth any rough edges with the sander and remove any excess acrylic from the plastic mesh. 15. Fill any air holes with acrylic as described above. 16. Apply a small bead of silicone medical adhesive 3.2 cm from the end of the tubing, and let dry overnight. 3.2. Surgery Methods

1. Autoclave the surgical instruments and surgical cloths. 2. Set up surgical supplies listed above. 3. Place tools on the drape it was autoclaved in. 4. Anesthetize animal with 100 mg/kg ketamine and 8 mg/kg xylazine, i.p. 5. Shave the animals back from approximately 1 in. behind the shoulder blades to the midpoint of the back. Then, turn the animal over and shave the right side from the chest to the jaw. 6. Use gauze to do a two stage wash (70% isopropyl alcohol and povidone–iodine solution, repeat twice on each side). 7. Place animal on the surgical cloth-belly down-head pointing left. 8. Using new scalpel blade, make an incision in the midline of the back approx. 1 in. in length centered over the shoulder blades. 9. With the tweezers, hold the skin at the edge of the incision and use the tissue scissors to gently tease away the skin from the underlying tissue. The goal is to make a subcutaneous pocket under the skin which would allow the mesh at the end of the cannula to lie flat. 10. Attach the tubing from the 1-ml syringe onto the cannula and flush with sterile saline. 11. Place the mesh flat under the skin with the tubing pointing toward the animal’s head. 12. Cover the incision with gauze and flip the animal over. 13. Look at the shaved area for a pulse; it should be between the shoulder and the middle of the neck. Make a 1–2 cm incision parallel to where the jugular vein is underneath. 14. Using the tweezers, tease the skin away from the tissue all around the incision. 15. With curved small tweezers, scoop the vein up onto the tweezers. Using the small straight tweezers, remove all excess tissue surrounding the vein. 16. Place a piece of suture under the vein to hold it in place. Starting at the top of the neck incision, run the curve hemostats directly under the skin, over the shoulder to the top of the back incision. Push the head of the hemostats through the connective tissue and out of the body. Grab the tubing of the

298


cannula with the hemostats and hold tightly, pulling the tubing through the tunnel along the neck and out of the neck incision. 17. Squirt a small amount of saline through the cannula and irrigate the vein—repeat when necessary to prevent the vein from drying. 18. Using the curved forceps in your right hand, gently slide one side of the straight forceps under the vein. 19. With sharp scissors, make a small cut in the vein. 20. Carefully introduce the tubing from the catheter into the vein. 21. Make a small stitch on either side of the bulb on the catheter to ensure it stays in place. Do not make it so tight that fluid cannot pass through. 22. Place a stitch on the other side of the silicone knob. 23. Sew up the internal tissue with 4–0-silk. 24. Use skin glue to secure the external tissue. 25. Turn the animal over on its belly (head pointing left) and adjust the mesh so it is lying flat under the skin. 26. Close up the rest of the wound with the 3.0-monofilament sutures. 27. Place animal in the recovery area. 3.3. Set Up for Self-administration


1. Connect drug syringe to rat via polyethylene tubing. 2. Place syringe on pump, making sure there is no slack between the two. 1. Provide 24 h access to cocaine: After allowing time to recover from surgery (3–7 days), animals are given access to a cocainepaired lever within their home operant chamber. Selfadministration sessions begin 6 h into the 12-h dark cycle and occur 7 days per week. Each session lasts 24 h. Access is provided in the middle of the dark cycle because this is the time period at which nocturnal animals exhibit the greatest amount of exploratory behavior. 2. Provide ad libitum food and water: During the acquisition period, animals are given unlimited access to food and water. Experimenters monitor food and water levels in addition to the room temperature daily. In the current protocol, animals are not trained to self-administer food or water prior to being given access to cocaine. 3. Provide a signal that drug is available: The availability of drug is signaled to the animal by the extension of a lever into the home operant chamber at the beginning of each session.

19


299

The lever itself serves as a conditioned cue predicting the availability of drug. 4. Provide a moderately high dose of cocaine: During the acquisition period, animals are given access to a 0.75 mg/kg dose of cocaine, a moderately high dose that is often readily selfadministered by rats. Note that this dose nears the top of the progressive ratio dose–response curve, and is therefore considered to function as a strong reinforcer. Higher doses are also self-administered but are avoided during acquisition due to the potential development of associations with the aversive effects of high cocaine doses. 5. Infusion size and duration: When the lever is depressed a cocaine solution (2.5 mg/ml) is infused as a bolus of 0.1 ml over approximately 4–5 s. The duration of the cocaine infusion is adjusted to account for the animal’s body weight. Slower infusion rates (e.g., 25 s) may result in different patterns of self-administration behavior after training. 6. Provide a time-out period: Following each response, the lever is retracted and a stimulus light is illuminated for a 20-s timeout period. The time-out serves to prevent the animals from receiving unintended injections by making stereotypic, or repetitive, movements on the lever immediately after the drug injection. It should be noted that trained animals usually avoid the lever during stereotypy and initiate self-imposed time-out periods. 7. Avoid priming the animal: During acquisition animals do not receive experimenter-initiated cocaine injections (i.e., drug primes). Especially, when using high cocaine doses, presenting animals with noncontingent cocaine injections may lead to decreased rates of acquisition, an effect that is presumably due to the development of aversive associations with the high cocaine dose. 8. Session termination: Sessions are terminated after a maximum of 20 infusions or a period of 24 h has elapsed. A 10-min pause is provided between acquisition sessions to allow the experimenter to monitor the health of each animal and record data. At the beginning of each session, the daily response number resets at zero. 9. When has an animal acquired?: An animal is considered to have acquired when the following criteria are met: responding begins at the onset of the 24 h session, stable inter-response intervals are observed between responses (these can be statistically verified by assessing the variance between responses), and 20 responses occur within the session. 10. Identification of stable patterns of cocaine self-administration: The 20 responses often occur in two patterns commonly

300


referred to as the loading phase and maintenance phase. The loading phase occurs during the first 5–10 min of the session and is characterized by brief period of rapid responding. The maintenance phase, which is characterized by stable interresponse intervals that are observed for the duration of the experimental session, is a hallmark of stable cocaine acquisition. Often times, when an animal’s indwelling jugular catheter loses patency, or the cocaine bolus is not being delivered properly, the problem is identified by the erratic nature of the interinjection intervals during the maintenance phase. 3.5. Discrete Trials

1. Chose a cocaine dose: DT has been run with doses ranging from 0.3 mg/kg/inj to as high as 2.5 mg/kg/inj. As the dose increases, the amount of drug the animal takes will also increase (see Note 1). 2. Provide 24 h access to cocaine: The self-administration sessions begin 6 h into the 12-h dark cycle and occur 7 days per week. Each session lasts 24 h (see Note 2). Animals are typically run for 10–21 days but can go longer depending on catheter patency (see Note 3). 3. Provide ad libitum food and water: Animals are given unlimited access to food and water. Experimenters monitor food and water levels in addition to the room temperature daily. 4. Provide a signal that drug is available: The availability of drug is signaled to the animal by the extension of a lever into the home operant chamber at the beginning of each trial. The lever itself serves as a conditioned cue predicting the availability of drug. 5. Infusion size and duration: When the lever is depressed the cocaine solution is infused as a bolus of 0.1 ml over approximately 4–5 s. The duration of the cocaine infusion is adjusted to account for the animal’s body weight. 6. ITI: If the trial lasts 10 min, chose an ITI that will give the desired number of trials per hour. For example, if running a DT2 trials per hour, then the ITI would be 20 min. 7. Avoid priming the animal: Animals do not receive experimenter-initiated cocaine injections (i.e., drug primes). 8. Give pharmacological pretreatments. (see Note 4)

3.6. Data Analysis

24 h DT data can be displayed in many ways. 1. Amount of cocaine (in mg/kg) self-administered over time. 2. Percentage of the available infusions taken over time. 3. Intake over several weeks displayed as total amount taken per session over days. 4. Compare averaged weekly intakes by hour over time. 5. Intake in the light hours versus the dark hours.

19


301

4. Notes 1. Under a DT schedule of cocaine self-administration, animals are given 24 h access to drug, but with some restraints on availability. If the maximum hourly intake is restricted, then cocaine self-administration can be studied round-the-clock for many weeks without signs of toxicity. 2. The circadian patterns in cocaine self-administration that emerge under a DT schedule are particularly interesting because human cocaine users also exhibit fluctuations in their motivation to take drug, with recreational use transitioning into binge abstinence cycles (14). An understanding of the physiological processes which dampen interest in drugs could provide new therapeutic targets. Additionally, the cycles in motivation could reflect a disruption in circadian influences normally controlling the timing and duration of drug taking. 3. The consistent daily cycles in drug intake can be used to advantage to examine the effects of various pharmacological manipulations. Drug pretreatments can be given at different times and thus increase the probability of low occurring behavior (low levels of self-administration in the light hours) or decrease the probability of high occurring behavior (high levels of selfadministration in the dark hours) (12, 15, 16). 4. When doing self-administration with indwelling venous catheters, there will always be some attrition when the catheters fail. There are two main ways to determine catheter patency. A fast acting anesthetic, such as sodium brevitol, can be used which causes the rat to become unconscious after i.v. administration if the catheter is patent. We typically do not use this method for concerns of the anesthetic causing changes in selfadministration behavior. Another way to check catheter patency is to have the animal self-administer on an FR1 schedule at a dose of 0.75 mg/kg and a maximum of 20 infusions. For an experienced rat, the event record should show have infusions that are evenly spaced, rather than appearing clumped together. If a rat that has acquired does not get the full 20 infusions, or the pattern is messy, we consider that rat as not patent.

Acknowledgments This work was supported by F31 DA025443 (CVD) and R01 DA14030 (DCSR).

302


References 1. Weeks, J.R. and Collins, R.J. (1964) Factors affecting voluntary morphine intake in selfmaintained addicted rats. Psychopharmacologia, 6, 267–279. 2. Honig, W.K. and Staddon, J.E.R. (1977) Handbook of operant behavior. Prentice-Hall, Englewood Cliffs, N.J. 3. Stretch, R. (1977) Discrete-trial control of cocaine self-injection behaviour in squirrel monkeys: effects of morphine, naloxone, and chlorpromazine. Can J Physiol Pharmacol, 55, 778–790. 4. Stretch, R. (1977) Discrete-trial control of morphine self-injection behaviour in squirrel monkeys: effects of naloxone, morphine, and chlorpromazine. Can J Physiol Pharmacol, 55, 615–627. 5. Stretch, R. and Gerber, G.J. (1977) Discretetrial control of morphine self-injection behaviour in monkeys: effects of injection dose and trials per session. Can J Physiol Pharmacol, 55, 121–125. 6. Fitch, T.E. and Roberts, D.C.S. (1993) The effects of dose and access restrictions on the periodicity of cocaine self-administration in the rat. Drug and Alcohol Dependence, 33, 119–128. 7. Roberts, D.C.S. and Andrews, M.M. (1997) Baclofen suppression of cocaine self-administration: demonstration using a discrete trials procedure. Psychopharmacology (Berl), 131, 271–277. 8. Roberts, D.C.S., Brebner, K., Vincler, M. and Lynch, W.J. (2002) Patterns of cocaine selfadministration in rats produced by various access conditions under a discrete trials procedure. Drug and Alcohol Dependence, 67, 291–299.

9. Deneau, G., Yanagita, T. and Seevers, M.H. (1969) Self-administration of psychoactive substances by the monkey. Psychopharmacologia, 16, 30–48. 10. Johanson, C.E., Balster, R.L. and Bonese, K. (1976) Self-administration of psychomotor stimulant drugs: the effects of unlimited access. PBB, 4, 45–51. 11. Bozarth, M.A. and Wise, R.A. (1985) Toxicity associated with long-term intravenous heroin and cocaine self-administration in the rat. JAMA, 254, 81–83. 12. Brebner, K., Froestl, W., Andrews, M.M., Phelan, R. and Roberts, D.C.S. (1999) The GABA(B) agonist CGP 44532 decreases cocaine self-administration in rats: demonstration using a progressive ratio and a discrete trials procedure. Neuropharmacology, 38, 1797–1804. 13. Lynch, W.J. and Roberts, D.C.S. (2004) Effects of Cocaine Self-Administration on FoodReinforced Responding Using a Discrete Trial Procedure in Rats. Neuropsychopharmacology, 29, 669–675. 14. Gawin, F.H. (1991) Cocaine addiction: psychology and neurophysiology. Science, 251, 1580–1586. 15. Espana, R.A., Oleson, E.B., Locke, J.L., Brookshire, B.R., Roberts, D.C. and Jones, S.R. (2010) The hypocretin-orexin system regulates cocaine self-administration via actions on the mesolimbic dopamine system. Eur J Neurosci, 31, 336–348. 16. Freeman, W.M., Brebner, K., Amara, S.G., Reed, M.S., Pohl, J. and Phillips, A.G. (2005) Distinct proteomic profiles of amphetamine self-administration transitional states. Pharmacogenomics J, 5, 203–214.

Chapter 20 Cocaine Self-Administration in Rats: Threshold Procedures Erik B. Oleson and David C.S. Roberts Abstract Cocaine self-administration provides a methodology allowing researchers to study changes in distinct aspects of drug-taking behavior that model behaviors observed in drug addicts. Traditionally, selfadministration schedules were designed to independently study changes in drug-taking behaviors (e.g., rate of responding, reinforcing efficacy, etc.). The threshold self-administration procedure was developed to measure two distinct dependent measures within the same experimental session that are important in the study of drug addiction: the maximal price an animal expends to self-administer cocaine and an animal’s preferred level of cocaine consumption when available at a low behavioral cost. Key words: Titration, Price, Reinforcing strength, Reinforcing efficacy, Behavioral economics

1. Introduction The procedure described here is designed to assess the lowest unit dose of cocaine that a rat will self-administer (i.e., threshold) and, using a behavioral economic analysis, provide an assessment of an animal’s preferred level of cocaine consumption and the maximal “price” an animal is willing to pay. The protocol, adapted from the work of Zittel-Lazarini and colleagues (1), begins by offering animals a relatively high unit dose of cocaine and then gradually decreasing the unit dose in small increments until responding ceases. In keeping with many previous studies (2–4), the threshold procedure demonstrates that animals adjust their rate of cocaine intake according to the dosage offered. That is, as the available cocaine dose decreases the rate of responding increases. Data, shown below, illustrate that animals appear to maintain a stable level of drug consumption across a wide range of unit prices until a threshold is reached (see Note 1). The concept of “threshold” implies that there is a dose that is minimally effective in supporting self-administration behavior.


303

304

E.B. Oleson and D.C.S. Roberts

However, in determining this threshold, it should be noted that animals must respond at very high rates on a fixed-ratio 1 (FR1) reinforcement schedule in order to maintain a constant level of drug intake. For example, we (5) have shown that a cocaine dose as low as 2.4 μg/infusion can support stable patterns of responding, engendering rates as high as 1,300 responses/h. The threshold must therefore be heavily influenced by the concept of “price.” The fact that rate of responding near threshold is affected by price makes it amenable to behavioral economics analysis. We describe how analysis of drug intake data yields information concerning both consumption (at high doses), as well as the maximal price paid (Pmax). To date, we have, developed two variations of the threshold procedure (5, 6). We first developed a between-sessions threshold procedure that requires 11 daily experimental sessions (5). This approach is simple to implement, but is not necessarily useful to study changes that might occur within a short temporal window. We subsequently adapted the procedure so that a threshold could be determined within a single session (6). This approach provides similar results to the between-sessions procedure, although several differences should be noted that are discussed herein. Both the between- and within-session threshold procedures yield data that can be easily analyzed using behavioral economics, which provides information about both the maximal price being expended to maintain consumption and the level of cocaine intake the animal is titrating around at a minimally constraining price. The within-sessions procedure provides a technique grounded in economic concepts that have been accepted by the field of behavioral pharmacology while catering to the needs of neuroscientists who study concepts involving the neurobiology of addiction. Using this approach, many future experiments could be designed to assess how neural systems change in parallel with behavioral changes in cocaine consumption and the price paid for cocaine.


1. Stainless steel guide cannula with threaded, plastic collar, 22-gauge, 5-mm upward projection (Plastics One, Roanoke, VA: C313G-5UP). 2. Silicone elastomer tubing (Silastic, Fisher, USA; two sizes: ID 0.012 in., OD 0.025 in. and ID 0.025 in., OD 0.047 in.). 3. Xylene substitute (CitriSolv, Fisher, USA). 4. Dental acrylic (Ortho-Jet, Lang Dental, Wheeling, IL). 5. Plastic mesh (Small Parts, KY: CMP-0500-D). 6. Slotted catheter mold (Faircloth Machinery, WinstonSalem, NC).

20

Threshold Procedures in Cocaine Self-Administration

305

7. Silicon-based aerosol lubricant (Fisher, USA: 19-047-445). 8. Silicone medical adhesive (Silastic, Dow Corning, Midland, MI). 9. Hand sanding tool (Dremel, Racine, WI). 2.2. Surgical Supplies

1. Needle holders (Roboz, MD). 2. Small microdissecting forceps (Roboz, MD). 3. Curved microdissecting forceps (Roboz, MD). 4. Tissue forceps (Roboz, MD). 5. Microdissecting scissors (Roboz, MD). 6. Microdissecting scissors 18 mm for vein (Roboz, MD). 7. Scalpel handle (Roboz, MD). 8. Hemostatic forceps, large (Roboz, MD). 9. Hemostatic forceps, small (Roboz, MD). 10. Cannulae (see Subheading 3.1). 11. 2″ × 2″ Gauze (Tyco, MA). 12. Sterile cotton swabs (Fisher, USA). 13. Scalpel blade, size 10 (Feather, Japan). 14. 4–0-Silk suture (Ethicon, USA). 15. 3–0-Monofilament suture (Ethicon, USA). 16. Skin glue (Webglue, Webster Veterinary, MA). 17. Two squares of sterile surgical cloth: one for surgery, one for holding sterile tools (Tyco, MA). 18. 1-ml Syringe filled with sterile saline-attached to a blunted 22-g needle with tubing attached to cannula (Becton Dickinson, NJ). 19. Povidone–iodine solution (Betadine, Purdue Products, CT). 20. 70% Isopropyl alcohol solution (Fisher, MA). 21. Artificial tears (Webster Veterinary, MA). 22. Latex/nonlatex gloves. 23. Mask. 24. Clippers to shave rat.

2.3. SelfAdministration Supplies

1. Polyethylene tubing (ID 0.02 in., OD 0.06 in., Tygon, Fisher, MA). 2. Drug dissolved in saline in 10-ml syringe. 3. Pump (Razel, CT). 4. Tether and swivel (Instech, PA). 5. Self-administration Associates, VT).

apparatus

(Privately

made

or

Med

306


3. Methods Catheters are made in our laboratory (see Subheading 3.1), but can also be ordered commercially (CamCaths, Cambridgeshire, UK). Approximately 1 week after arrival to the housing colony, rats are anesthetized (ketamine + xylazine 100 and 8 mg/kg, i.p.) and implanted with chronic indwelling jugular venous catheters (see Subheading 3.2). All catheters feature an externalized access port which attaches via polyethylene tubing (protected with a spring tether) to an infusion pump. Three to five days after surgery rats begin a training protocol that lasts 2–14 days. Animals must acquire a stable pattern of baseline responding, a concept that is referred to as acquisition. In the present protocol, acquisition occurs in 85% of animals. Animals that do not reach acquisition criteria within 10 days of receiving access to cocaine are excluded from selfadministration experiments due to potential confounds, such as the development of aversive associations with cocaine and/or the self-administration environment that might have impeded acquisition. After the training criteria have been met, animals are given access to cocaine in the threshold procedure. 3.1. Cannulae Making Procedure

1. Cut a 14-cm piece of the smaller silicone elastomer tubing (ID 0.012 in.; OD 0.025 in.). 2. Submerse approximately 1.5 cm of the tubing in xylene substitute under a fume hood for about 3 min to expand the plastic. 3. Drain fluid from tubing and slide over the guide cannula until it reaches the plastic collar. Let tubing dry overnight. 4. Cut a 2.5-cm piece of the larger silicone elastomer tubing (ID 0.025 in.; OD 0.047 in.). 5. Completely immerse the tubing in xylene substitute under a fume hood for approximately 3 min until plastic has expanded. 6. Without draining fluid from inside the tubing, slide it over the entire length of the smaller tubing until it reaches the threaded plastic collar, being careful not to kink or damage the small tubing. 7. Cut a 2.5-cm diameter circle of plastic mesh. 8. Using a soldering iron, melt the edges of the mesh together until there are no sharp edges. 9. Sand the edges of the mesh until they are smooth with a hand sanding tool on the lowest speed. 10. Spray the slotted mold with silicon-based lubricant. 11. Arrange the guide cannula so that roughly one third of the threaded collar protrudes into the mold and clamp tightly.

20


307

12. Mix the powder and liquid components of quick-hardening dental acrylic until slightly runny and quickly drip into the mold until the well is nearly full. 13. Place the round piece of mesh onto the well and apply a small amount of the acrylic to secure the mesh to the guide cannula. Allow a minimum of 45 min for acrylic to dry. 14. Remove guide cannula from mold. Smooth any rough edges with the sander and remove any excess acrylic from the plastic mesh. 15. Fill any air holes with acrylic as described above. 16. Apply a small bead of silicone medical adhesive 3.2 cm from the end of the tubing, and let dry overnight. 3.2. Surgery Methods

1. Autoclave the surgical instruments and surgical cloths. 2. Set up surgical supplies listed above. 3. Place tools on the drape it was autoclaved in. 4. Anesthetize animal with 100 mg/kg ketamine and 8 mg/kg xylazine, i.p. 5. Shave the animals back from approximately 1 in. behind the shoulder blades to the midpoint of the back. Then, turn the animal over and shave the right side from the chest to the jaw. 6. Use gauze to do a two-stage wash (%70 isopropyl alcohol and povidone–iodine solution, repeat twice on each side). 7. Place animal on the surgical cloth-belly down-head pointing left. 8. Using new scalpel blade, make an incision in the midline of the back approximately 1 in. in length centered over the shoulder blades. 9. With the tweezers, hold the skin at the edge of the incision and use the tissue scissors to gently tease away the skin from the underlying tissue. The goal is to make a subcutaneous pocket under the skin which would allow the mesh at the end of the cannula to lie flat. 10. Attach the tubing from the 1-ml syringe onto the cannula and flush with sterile saline. 11. Place the mesh flat under the skin with the tubing pointing toward the animal’s head. 12. Cover the incision with gauze and flip the animal over. 13. Look at the shaved area for a pulse; it should be between the shoulder and the middle of the neck. Make a 1–2 cm incision parallel to where the jugular vein is underneath. 14. Using the tweezers, tease the skin away from the tissue all around the incision 15. With curved small tweezers, scoop the vein up onto the tweezers. Using the small straight tweezers, remove all excess tissue surrounding the vein.

308


16. Place a piece of suture under the vein to hold it in place. Starting at the top of the neck incision, run the curve hemostats directly under the skin, over the shoulder to the top of the back incision. Push the head of the hemostats through the connective tissue and out of the body. Grab the tubing of the cannula with the hemostats and hold tightly, pulling the tubing through the tunnel along the neck and out of the neck incision. 17. Squirt a small amount of saline through the cannula and irrigate the vein—repeat when necessary to prevent the vein from drying. 18. Using the curved forceps in your right hand, gently slide one side of the straight forceps under the vein. 19. With sharp scissors, make a small cut in the vein. 20. Carefully introduce the tubing from the catheter into the vein. 21. Make a small stitch on either side of the bulb on the catheter to ensure it stays in place. Do not make it so tight that fluid cannot pass through. 22. Place a stitch on the other side of the silicone knob. 23. Sew up the internal tissue with 4–0-silk. 24. Use skin glue to secure the external tissue. 25. Turn the animal over on its belly (head pointing left) and adjust the mesh so it is lying flat under the skin. 26. Close up the rest of the wound with the 3.0-monofilament sutures. 27. Place animal in the recovery area. 3.3. Setup for SelfAdministration

1. Connect drug syringe to rat via polyethylene tubing.


1. Provide 24 h access to cocaine: After allowing time to recover from surgery (3–7 days) animals are given access to a cocainepaired lever within their home operant chamber. Selfadministration sessions begin 6 h into the 12-h dark cycle and occur 7 days/week. Each session lasts 24 h. Access is provided in the middle of the dark cycle because this is the time period at which nocturnal animals exhibit the greatest amount of exploratory behavior.

2. Place syringe on pump, making sure there is no slack between the two.

2. Provide ad libitum food and water: During the acquisition period, animals are given unlimited access to food and water. Experimenters monitor food and water levels in addition to the room temperature daily. In the current protocol, animals are not trained to self-administer food or water prior to being given access to cocaine.

20


309

3. Provide a signal that drug is available: The availability of drug is signaled to the animal by the extension of a lever into the home operant chamber at the beginning of each session. The lever itself serves as a conditioned cue predicting the availability of drug. 4. Provide a moderately high dose of cocaine: During the acquisition period, animals are given access to a 0.75 mg/kg dose of cocaine, a moderately high dose that is often readily selfadministered by rats. Note that this dose nears the top of the progressive ratio dose–response curve, and is therefore considered to function as a strong reinforcer. Higher doses are also self-administered but are avoided during acquisition due to the potential development of associations with the aversive effects of high cocaine doses. 5. Infusion size and duration: When the lever is depressed a cocaine solution (2.5 mg/ml) is infused as a bolus of 0.1 ml over approximately 4–5 s. The duration of the cocaine infusion is adjusted to account for the animal’s body weight. Slower infusion rates (e.g., 25 s) may result in different patterns of self-administration behavior after training. 6. Provide a time-out period: Following each response, the lever is retracted and a stimulus light is illuminated for a 20-s time-out period. The time-out serves to prevent the animals from receiving unintended injections by making stereotypic, or repetitive, movements on the lever immediately after the drug injection. It should be noted that trained animals usually avoid the lever during stereotypy and initiate self-imposed time-out periods. 7. Avoid priming the animal: During acquisition, animals do not receive experimenter-initiated cocaine injections (i.e., drug primes). Especially, when using high cocaine doses, presenting animals with noncontingent cocaine injections may lead to decreased rates of acquisition, an effect that is presumably due to the development of aversive associations with the high cocaine dose. 8. Session termination: Sessions are terminated after a maximum of 20 infusions or a period of 24 h has elapsed. A 10-min pause is provided between acquisition sessions to allow the experimenter to monitor the health of each animal and record data. At the beginning of each session, the daily response number resets at zero. 9. When has an animal acquired? An animal is considered to have acquired when the following criteria are met: responding begins at the onset of the 24-h session, stable inter-response intervals are observed between responses (these can be statistically verified by assessing the variance between responses), and 20 responses occur within the session. 10. Identification of stable patterns of cocaine self-administration: The 20 responses often occur in two patterns commonly

310


referred to as the loading phase and maintenance phase. The loading phase occurs during the first 5–10 min of the session and is characterized by brief period of rapid responding. The maintenance phase, which is characterized by stable interresponse intervals that are observed for the duration of the experimental session, is a hallmark of stable cocaine acquisition. Often times, when an animal’s indwelling jugular catheter loses patency, or the cocaine bolus is not being delivered properly, the problem is identified by the erratic nature of the interinjection intervals during the maintenance phase. 3.5. Between-Sessions Threshold Procedure 3.5.1. Training After Acquisition

Following acquisition animals can either enter the threshold procedure directly or undergo further training if drug-taking history is a variable of interest. It should be noted that the behavioral history of the animal can independently change either the level of cocaine intake the animal titrates around or the Pmax for cocaine (5). We have found that providing minimal training can lead to greater variability in baseline responding across the course of the experiment but allows drug-taking behavior to change over time (8). Thus, the experimenter should carefully consider whether stable baseline responding or behavioral flexibility is more important during the design of the experiment (see Note 2).

3.5.2. Between-Sessions Threshold Protocol: Introductory Notes

The between-sessions threshold procedure is easy to implement and involves providing access to 11 cocaine doses across daily 2-h selfadministration sessions. The experimenter manipulates the available dose by changing the duration that the pump infuses cocaine through the IV line following each lever response. Adjusting the available dose by manipulating pump-durations results in a lawful dose– response relationship (see Fig. 1c), but it should be noted that it is important to verify that the infusion pumps are delivering the proper amount of cocaine solution per lever response (see Note 3).

3.5.3. Between-Sessions Threshold Experimental Protocol

1. Timeframe: Animals are given access to cocaine across 11 consecutive daily 2-h self-administration sessions. Each session begins 6 h into the dark cycle. 2. Schedule: Cocaine is provided under an FR-1 schedule, meaning that one lever response results in one intravenous cocaine infusion. 3. Cocaine concentration: A cocaine concentration of 5 mg/ml is provided to the animal. 4. Dose manipulation: The available dose is decreased across daily sessions by manipulating the pump duration. Note that the pump speed remains constant (1.6 ml/s). 5. Pump durations: The time that the pump is on decrease daily in quarter logarithmic units as follows: 3,156, 1,780, 1,000, 560, 310, 180, 100, 56, 31, 18, and 10 ms pump time per lever press.

20


311

Fig. 1. Between-sessions threshold procedure. (a) Event records from a representative animal are shown responding across daily 2-h sessions. Each tick represents a lever response. (b) Cumulative records from a representative animal are shown. Vertical shifts represent drug infusions, horizontal shifts represent time. (c) A dose–response function from a group of animals tested across many doses (see equivalent pump durations on top x-axis) is illustrated.

6. Dose equivalents: The decreasing pump speeds are converted (5 mg/ml (cocaine concentration) × 1.6 ml/min (pump speed) × pump duration) to unit injections doses, which are as follows: 421, 237, 133, 75, 41, 24, 13, 7.5, 4.1, 2.4, and

312


1.3 μg/infusion. These provided unit doses corresponding to doses of (1,120, 630, 350, 200, 110, 60, 30, 20, 10, 5, and 3 μg/kg/infusion) for 375 g rat. 7. Time-out: The lever never retracts during the 2-h session; therefore, the only time-out is imposed by the pump. That is, if the pump is already on when the animal presses the lever, the animal will not receive two drug injections. 8. Data analysis: See Subheading 3.7. 3.5.4. Between-Sessions Threshold Caveat (Time-Out Issue)

We wanted the only restriction on cocaine consumption to be that imposed by gradually decreasing the available unit injection dose. Thus, we decided not to use an experimenter-imposed time-out. The issue with this decision is that it could be argued that the responses being measured (see Note 4) are due to stereotypy or direct drug effects. Although, response rates appear to lawfully increase as the available dose decreases and stable patterns of responding are observed despite the absence of an experimenterimposed time-out (Fig. 1), we decided to further test for a potential confound of uncontrolled responding by substituting saline for cocaine within self-administration sessions. At the time at which substitution occurs, cocaine is still in the animal’s system, so drug-induced behavioral responses should still occur. As illustrated in Fig. 2, following substitution, extinction rapidly occurred. Extinction within a cocaine self-administration session is characterized by a rapid increase in responding followed by complete cessation of responding. These data show that the pattern of responding observed in the threshold procedure is not entirely due to stereotypic behavior or direct drug effects occurring in the absence of an experimenter-imposed time-out.

Fig. 2. Time-out issue addressed. A cumulative record showing saline substitution during a between-sessions threshold experiment is shown. The arrow represents the time of substitution. Extinction is observed after substitution as a rapid increase in responding followed by complete cessation.

20

3.6. Within-Session Threshold Procedure 3.6.1. Within-Session Threshold Protocol: Introductory Notes


313

Many independent variables that experimenters might choose to investigate change within a short temporal window. The betweensessions threshold procedure is poorly designed to test such variables. Thus, we adapted the between-sessions threshold procedure to occur within a single experimental session (6). We achieved this by providing rats with daily access to 11 descending cocaine doses presented in consecutive timed intervals under an FR-1 schedule of reinforcement (Fig. 3). This adaptation provides several advantages. First, two dependent measures can be examined daily,

Fig. 3. Within-session threshold procedure. (a) A cumulative record from a representative animal is illustrated. Each vertical bar represents one 10-min bin during which the available dose is fixed. (b) The same animal’s data are plotted to show responses/bin as a function of dose. (c) The same animal’s data are plotted to show intake/bin as a function of dose.

314


thereby reducing the attrition rates encountered in lengthy selfadministration studies. Second, it allows for the investigation of pharmacological, hormonal, neurochemical, and environmental variables that change quickly. Third, the interval time during which each dose is presented to the animal can be manipulated to accommodate the pharmacokinetics and pharmacodynamics of specific drug-pretreatments. 3.6.2. Within-Session Threshold Experimental Protocol

1. Timeframe: Animals are given access to cocaine across 11 consecutive time bins (e.g., 10 min each) within a daily (e.g., 110 min) experimental session. 2. Schedule: Same as between sessions. 3. Cocaine concentration: Same as between sessions. 4. Dose manipulation: Same as between sessions. 5. Pump durations: Same as between sessions. 6. Dose equivalents: Same as between sessions. 7. Time-out: Same as between sessions. 8. Data analysis: Same as between sessions.

3.6.3. Within-Session Threshold Caveat (Drug Loading)

Animals respond for cocaine at a faster rate during the first 5–10 min of a self-administration session when access is provided under an FR-1 schedule. This disproportionately high rate of responding results in higher levels of cocaine intake occurring in the first bin of the threshold procedure in comparison to that observed across all other doses. The amount of drug intake occurring in the first bin should therefore, be excluded from analyses of the animal’s preferred level of drug intake because it is not reflective of the level of cocaine the animal is titrating around.

3.6.4. How Do WithinSession Data Compare with Between-Sessions Data?

During the within-session threshold procedure lower threshold doses are observed using the same group of animals (Fig. 4). This phenomenon is likely due to the following: 1. Cocaine already being onboard: In the within-session procedure, animals load up with a high cocaine dose so the resulting high blood cocaine concentration can contribute to increased responding (direct drug effects). 2. Fatigue: Fatigue could become a factor in the between-sessions procedure due to the fact that many more responses are necessary to maintain cocaine intake when given access to a low dose for 2 h vs. 10 min.

3.6.5. What Happens When You Shorten the Bin Time?

An advantage of the within-session threshold procedure is that it allows the investigator to vary the length of the experimental session to account for the pharmacokinetics and pharmacodynamics

20


315

Fig. 4. Between-sessions and within-session procedures compared. The mean (±SEM) threshold dose reached by a group of animals responding for cocaine in the betweensessions and within-session threshold procedures.

Fig. 5. Changing bin times dose–response functions are shown depicting the same group of animals responding in the within-session threshold procedure during 5 (open circles) and 10 (filled circles) minute bins.

of drug pretreatments. Adjusting the time of the bins, however, can affect the behavioral results. Figure 5 illustrates dose–response curves from a group of animals responding for cocaine in the within-session threshold procedure with either 5 (open circles) or 10 (filled circles) min bins. These data show that, as expected,

316


animals respond twice as much per bin when the bin length is doubled. More importantly, however, is the observation that animals respond to lower threshold doses when shorter bin sizes are used. This is likely due to the same reasons resulting in lower thresholds in within- vs. between-sessions threshold experiments (i.e., fatigue and direct drug effects). 3.7. Data Analysis: Behavioral Economics 3.7.1. Behavioral Economics: Introductory Notes

3.7.2. Graphical Approach to Behavioral Economics

Behavioral economic theory can be applied to drug self-administration data to assess how drug consumption changes in response to increases in drug price. Many excellent reviews exist that describe how demand curves are fit to drug intake data and dependent measures extracted from the fitted curves to study the maximal behavioral price expended to maintain consumption (9–13). In addition to applying these mathematical approaches to the analysis of threshold data, our lab has applied a simple graphical approach to threshold data analysis. We find that this graphical approach provides an intuitive method to perform behavioral economics analyses that can be validated using mathematical approaches (5). The purpose of a demand curve is to find the point at which consumption of a commodity becomes sensitive to increases in price, or in behavioral economics terms the point at which demand transitions from being inelastic to elastic. This point can be mathematically derived, but can also be observed graphically when many unit prices are assessed as they are in threshold procedures. Unit price is inversely related to the available cocaine dose, as is illustrated on the x-axis in Fig. 6. Therefore, for every decrease in unit dose, the unit price of cocaine increases. Within the low price range animals titrate around a stable level of cocaine intake (mg/bin), which presumably reflects the animal’s preferred level of drug intake. By excluding higher price points, at which consumption is sensitive to price, and the first price point, which is confounded by drug loading (excluded from graph), the animal’s preferred level of cocaine consumption can be calculated by averaging drug intake across the second through fourth unit price. The maximal price expended for cocaine (Pmax) can be graphically determined by assessing the apex of the price-response function (see Note 5). Note that the unit price resulting in peak responding corresponds to the final point at which stable cocaine consumption is maintained. This data analysis approach is particularly powerful in that it extracts two distinct dependent measures from threshold data that are relevant to the study of drug addiction: the maximal price expended for cocaine and the level of cocaine the animal titrates around at a minimally constraining cost.

20


317

Fig. 6. Behavioral economics: a graphical approach to behavioral economics is applied to threshold data. A representative animal’s responses/bin (left y-axis; open triangles) and intake/bin (right y-axis; filled circles) are plotted as a function of unit price (responses/ mg). Vertical dotted lines represent 10-min bins during the within-session threshold procedure. The arrow shows the maximal price the animal expends to maintain consumption (Pmax). The ellipse shows the level of cocaine consumption the animal titrates around at a minimally constraining price.

4. Notes 1. The threshold procedure was designed to assess cocaine selfadministration and therefore, may not be as useful to study the reinforcing effects of other drugs or natural reinforcers. In part, this procedure relies on an animal adjusting their rate of responding to maintain a stable level of cocaine intake, which can be measured in short epochs because IV cocaine is quickly metabolized. 2. We have adopted a quick training procedure for pharmacological studies. The animal is given access to 40 injections of a high cocaine dose (1.5 mg/kg/injection) for 5 consecutive days following acquisition. This training protocol is useful for producing stable baseline responding, which is particularly useful when testing the effects of drug pretreatments. However, this particular training procedure can prevent pharmacological

318


histories from affecting drug-taking behavior if implemented immediately after acquisition (8). When studying the effect behavioral/pharmacological history on drug-taking behavior we find that providing minimal experience after acquisition results in the most robust behavioral changes over time. 3. We were initially concerned that the infusion pumps would not deliver the proper amount of drug solution when short (e.g., 31 ms) pump durations were used. To test this (see supplemental material in (5)), we compared total pump times (seconds per session) vs. total solution (milliliter per session) delivered across all pump durations. This resulted in a high correlation between the two variables assuring us that the pumps were accurately delivering the appropriate unit injection dose, even at short pump durations. To be cautious, however, we still record the total milliliters of solution delivered each day to verify that the levers continue to deliver the appropriate amount of solution and test pumps before the beginning of experiments. 4. Due to the fact that responses occur during the pump-imposed timeout period, the recorded number of injections will not always match the number of responses emitted. To deal with this issue, we always report the number of drug injections, which is the true representation of the number of reinforced responses. 5. Pmax values can vary across sessions when obtained using the within-sessions threshold procedure. When assessing the effects of drug-pretreatments therefore, it might be more useful to compare data collected on the day of testing to data collected immediately preceding treatment rather than an average of baseline data collected across all experimental sessions. References 1. Zittel-Lazarini, A., Cador, M. and Ahmed, S.H. (2007) A critical transition in cocaine selfadministration: behavioral and neurobiological implications. Psychopharmacology (Berl), 192, 337–346. 2. Pickens, R. and Thompson, T. (1968) Cocainereinforced behavior in rats: effects of reinforcement magnitude and fixed-ratio size. J.Pharmacol.Exp.Ther., 161, 122–129. 3. Yokel, R.A. and Piekens, R. (1974) Drug level of d- and l-amphetamine during intravenous self-administration. Psychopharmacologia., 34, 255–264. 4. Wilson, M.C., Hitomi, M. and Schuster, C.R. (1971) Psychomotor stimulant self administra-

tion as a function of dosage per injection in the rhesus monkey. Psychopharmacologia., 22, 271–281. 5. Oleson E.B. and Roberts, D.C.S. (2009) Behavioral economic assessment of price and cocaine consumption following self-administration histories that produce escalation of either final ratios or intake. Neuropsychopharmacology 34, 796–804. 6. Espana, R.A., Oleson, E.B., Locke, J.L., Brookshire, B.R., Roberts, D.C. and Jones, S.R. (2010) The hypocretin-orexin system regulates cocaine self-administration via actions on the mesolimbic dopamine system. Eur J Neurosci, 31, 336–348.

20


7. Morgan, D., Liu, Y. and Roberts, D.C. (2006) Rapid and persistent sensitization to the reinforcing effects of cocaine. Neuropsychopharmacology, 31, 121–128. 8. Hursh, S.R. (1991) Behavioral economics of drug self-administration and drug abuse policy. J.Exp.Anal.Behav., 56, 377–393. 9. Hursh, S.R., Galuska, C.M., Winger, G. and Woods, J.H. (2005) The economics of drug abuse: a quantitative assessment of drug demand. Mol.Interv., 5, 20–28.

319

10. Hursh, S.R. and Silberberg, A. (2008) Economic demand and essential value. Psychol. Rev., 115, 186–198. 11. Bickel, W.K., DeGrandpre, R.J., Higgins, S.T. and Hughes, J.R. (1990) Behavioral economics of drug self-administration. I. Functional equivalence of response requirement and drug dose. Life Sci., 47, 1501–1510. 12. Bickel, W.K., DeGrandpre, R.J. and Higgins, S.T. (1993) Behavioral economics: a novel experimental approach to the study of drug dependence. Drug Alcohol Depend., 33, 173–192.

sdfsdf

Chapter 21 Assessing Locomotor-Stimulating Effects of Cocaine in Rodents Drake Morgan, Jameson P. DuPree, Alex D. Bibbey, and Glen M. Sizemore Abstract Locomotor activity procedures are useful for characterizing the behavioral effects of a drug, the influence of pharmacological, neurobiological, and environmental manipulations on drug sensitivity, and changes in activity following repeated administration (e.g., tolerance or sensitization) are thought to be related to the development of an addiction-like behavioral phenotype. The effects of cocaine on locomotor activity have been relatively extensively characterized. Many of the published studies use between-subject experimental designs, even though changes in sensitivity within a particular individual due to experimental manipulations, or behavioral and pharmacological histories is potentially the most important outcome as these changes may relate to differential development of an addiction-like phenotype in some, but not all, animals (including humans). The two behavioral protocols described herein allow extensive within-subject analyses. The first protocol uses daily locomotor activity levels as a stable baseline to assess the effects of experimental manipulations, and the second uses a pre- versus post-session experimental design to demonstrate the importance of drug–environment interactions in determining the behavioral effects of cocaine. Key words: Stimulant, Operant behavior, Behavioral pharmacology, Locomotor activity, In vivo

1. Introduction Laboratories investigating drug dependence and addiction in rodents using preclinical models have a number of behavioral tools and procedures at their disposal (for a review of these behavioral procedures, see ref. 1). Perhaps the most common behavioral procedure used in the assessment of cocaine’s behavioral effects is the locomotor procedure (see Note 1). These procedures are relatively easy to conduct, little training is typically required (or allowed), and the rapidity of data collection is impressive. Here, we describe two locomotor activity assessment procedures that borrow heavily from the operant conditioning and behavioral pharmacology Firas H. Kobeissy (ed.), Psychiatric Disorders: Methods and Protocols, Methods in Molecular Biology, vol. 829, DOI 10.1007/978-1-61779-458-2_21, © Springer Science+Business Media, LLC 2012

321

322

D. Morgan et al.

literature, allow for extensive within-subject data analysis techniques (see Note 2), and demonstrate the importance of drug–environment interactions in determining the behavioral effects of a drug (see Note 3). Measurement of locomotor activity following administration of a drug can provide reasonable estimates of various pharmacokinetic factors related to cocaine (including the relative potency of the drug, the onset of action, duration of action), and the absolute magnitude of the drug effect (i.e., effectiveness in altering the behavioral response) (see Note 4). Generally using between-groups experimental designs, these procedures have been used to assess changes in the effects of cocaine following manipulations of pharmacology and neurochemistry (e.g., ref. 2), neurobiology (e.g., ref. 3), hormonal function (e.g., ref. 4, 5), genetic backgrounds (e.g., ref. 6), and environmental conditions (e.g., ref. 7) among other factors. The second procedure described here provides a sensitive baseline to assess these types of variables within an individual animal, potentially allowing for greater experimental control, lower levels of variability, greater confidence in the observed changes, and other advantages gained from using single-subject experimental designs (8). Most commonly, the locomotor activity procedure is used to assess changes in sensitivity to cocaine over time. It is well known and widely accepted that cocaine generally increases activity following initial administration (which probably contributes to cocaine being called a “psychomotor stimulant”). Of potential interest is what happens to locomotor activity following repeated administration, and these effects are thought to depend on various factors, including route of administration, frequency, and duration of repeated treatment, administered dose, association between drug administration and exposure to environmental conditions, and time since last injection (i.e., a drug-free, withdrawal/“abstinence” period) (for review, see ref. 9, 10). Three potential outcomes following repeated administration are increases in sensitivity (i.e., sensitization), decreases in sensitivity (i.e., tolerance), or no change in sensitivity. All three phenomena have been observed and documented; however, the exact factors contributing to these differential outcomes are not always clear (certainly the factors mentioned above are often assumed to play critically important roles). The scientific discipline of behavioral pharmacology has made a number of important contributions to experimental design, data collection, and interpretation. One primary contribution is the importance of drug, behavior, environment, and historical interactions in determining a drug effect. One relatively simple way to demonstrate these interactions can be accomplished using prepost experimental designs (either within- or between-subject). In this situation, the primary outcome of interest is the potential development of tolerance or sensitization following repeated administration of the drug of interest, and the primary independent

21

Cocaine-Associated Locomotor-Stimulating Effects

323

variable is whether the drug was administered before the session (thus, the animals behaved and experienced the drug effect in the testing chamber) or after the session (the animals receive the same exposure to drug and the experimental chamber, but do not experience the drug effects in the chamber). Under these conditions, using some standard operant behavior measures (e.g., schedulecontrolled behavior), it is oftentimes observed that the degree of tolerance or sensitization is larger in the “pre” group/condition, relative to the “post” group/condition. This is generally taken as evidence that behaving in the experimental context itself is critical (or at least an important factor) in determining the magnitude and/or direction of change in sensitivity. These experiments are similar to those examining context-dependent and contextindependent sensitization (or tolerance), although the design described here avoids the introduction of an additional novel environment which can add to the complexity of data interpretation. Most of the studies done to date involve between-group comparisons (for example, comparison of locomotor stimulation in saline-treated versus cocaine-treated animals). Little is known regarding changes in sensitivity within individual subjects, although presumably this is what we would like to know about—these individual differences may underlie that apparent wide distribution of responses to cocaine in humans (i.e., not all initial users of cocaine go on to become addicted to cocaine). Both of the approaches described here allow for extensive within-subject analyses

2. Materials 2.1. Subjects

1. Male, Sprague-Dawley rats are purchased from Charles River Laboratories at 3 months of age, and typically weigh between 250 and 300 g. 2. Rats are singly housed to avoid the drug-induced social interactions that would occur when returned to the home cage. 3. Upon arrival in the laboratory, animals are acclimated for at least 1 week.

2.2. Locomotor Activity

1. Activity test chambers (ENV-515) purchased from Med Associates. 2. These chambers measure 17″ × 17″ and are equipped with three arrays of infra-red beams to determine the rat’s location in the chamber, and count the number of rearing events. 3. Data from experimental sessions are collected by a computer, and analyzed by software which saves numerous aspects of the data, including ambulatory distance and counts, stereotypic counts, rearing, and average velocity.

324

D. Morgan et al.

3. Methods The effects of drugs on locomotor activity are important, and can provide relevant information about the potency, the efficacy (i.e., the magnitude of a change), onset, and duration of action of a drug. Of interest to the drug abuse research community is that changes in locomotor activity following repeated administration are thought to model some aspect of the addiction process. The procedures described here use two experimental conditions described in the operant conditioning, behavioral pharmacology literature. In particular, a pre-post session experimental design can tell us about the role of the interaction between experiencing a drug effect in a particular environment versus receiving identical amounts of the drug without the environmental context. Results from these sorts of studies are critical, in order to validate the commonly used procedure of administering a particular drug regimen that would produce a particular change in behavior (e.g., sensitization), but without measuring the behavioral change as to avoid “behaviorally contaminating” the eventual brain tissue samples. That is, someone could argue that the tissue undergoing analysis (e.g., molecular biological, genetic, proteomic) should be obtained from animals that were not behaviorally tested. But it is possible that the desired behavioral phenotype (“sensitized to the locomotor-stimulating effects of cocaine”) only appears in animals that actually experience the drug effect in a particular context. The second described procedure provides a method to repeatedly assess the behavioral effects of a drug within an individual animal, providing results that can be statistically assessed in a meaningful way (e.g., replicability of an effect within an individual provides quality evidence that the effect is “real,” almost regardless of magnitude). This procedure also allows prolonged testing over time allowing the repeated determination of entire dose–effect curves (as one example). 3.1. Subjects

1. Need to be weighed and handled regularly so they adapt to handling. 2. Cocaine hydrochloride or sterile saline is administered in a volume of 1.0 ml/kg.

3.2. Locomotor Activity: Pre/Post Experimental Design

1. All animals are habituated to the testing chambers for one session. 2. On Day 2 of testing, all animals are injected with saline, and locomotor activity is tracked for 20 min. 3. On Day 3 of testing, all animals are injected with cocaine before the session for an initial “cocaine baseline” measurement. 4. During the next testing session, one group of animals receives cocaine pre-session and another group receives cocaine postsession. For injection control purposes, the first group would

21


325

Fig. 1. Changes in locomotor activity from an initial baseline session to a test session conducted following 2 weeks of a drug-free period. For both of these sessions, cocaine was administered immediately before the test. During the dosing regimen however, animals were treated daily for 7 days with 18.0 mg/kg, i.p. either immediately before (presession group) or after (post-session group) a locomotor activity session. Animals in the pre-session group show sensitization to the locomotor-stimulating effects, as well as increases in rearing. Animals in the post-session group fail to show sensitization.

receive an injection with an equal volume of saline post-session and the second group would receive a saline injection presession. 5. Thus, both groups of animals have equal exposure to the testing chambers, identical levels of drug exposure, and the only difference is the temporal relationship of testing and cocaine administration. In one case, the animals experience the drug effects in the environmental context (locomotor chambers) and the other group does not. 6. Treat animals in this manner daily for seven sessions. 7. Following 2 weeks of a drug-free period, all animals are injected with the test dose of cocaine before the session to access the change from baseline cocaine session (i.e., assess the development of tolerance or sensitization, see Fig. 1). 3.3. Locomotor Activity: WithinSubject, Repeated Testing Design

1. All animals are habituated to the testing chambers for at least a week and until the levels of locomotor activity during a 20-min session are stable. 2. Once locomotor behavior is stable drug testing begins. 3. As long as the noninjection days fall within the range of baseline control sessions, twice per week drug/saline pretreatments are administered 20 min before the testing session. This generally happens Tuesday and Friday.

326

D. Morgan et al.

Fig. 2. Data are shown for an individual animal for 85 baseline sessions. Throughout this time, cocaine was administered up to two times per week before a test session. The cocaine dose–effect represents numerous determinations of the effects of cocaine (1.0–30 mg/kg, i.p.). The filled symbols represent the mean, and the error bars represent the range of effects.

4. The doses of cocaine are generally chosen, and generally administered in a quasi-random order. 5. The effects of saline are assessed frequently to identify levels of variability in locomotor activity induced by IP injections before the session. 6. These procedures can then be followed for months at a time, with repeated testing of pharmacological, environmental, neurobiological, and hormonal (among others) manipulations. 7. A major advantage of this procedure is that you always know whether or not you have drug effect by comparing to the range of variability that you have during your baseline control and saline control sessions. Test data that falls outside this range is a drug effect. Replicating this effect several times establishes the reliability of the effect as shown in Fig. 2.

4. Notes 1. Other commonly used procedures include but are not limited to conditioned place preference, schedule-controlled responding (to assess the rate-decreasing and/or rate-dependent effects), drug discrimination, self-administration, effects on complex operant behavior and effects on intracranial selfstimulation. 2. Based primarily in the field of applied behavior analysis, small-n and single-subject experimental designs provide a number of advantages over the standard between-group

21


327

experimental designs. Many of the relevant issues are covered in Sidman, 1960. 3. This is an important topic given the increasing use of these types of behavioral procedures by molecular biologists and other groups of scientists. With the hope of not “behaviorally contaminating” an animal by conducting the important behavioral tests before the subsequent molecular, genetic, and neurobiological analyses, animals are sometimes treated with a dosing regimen previously shown to produce the desired outcome (e.g., sensitization to cocaine’s locomotor effects) without the behavioral testing. It is sometimes said that the animals would have shown the desired behavioral phenotype if tested. Unfortunately, we know that in many cases it is the drug administration combined with the behavioral experience that produces the outcome—not just the drug administration alone. 4. It should be acknowledged that locomotor activity using amphetamine is far more common than with cocaine. This may be in part due to the pharmacokinetic and pharmacodynamic profile of amphetamine—both compounds have a quick onset of action; however, the magnitude of the behavioral and neurochemical changes with amphetamine are generally larger, and the effects longer lasting providing a larger window of opportunity for experimental manipulations. References 1. Sanchis-Segura, C., and Spanagel, R. (2006) Behavioural assessment of drug reinforcement and addictive features in rodents: an overview. Addict. Biol. 11, 2–38. 2. Panos, J.J., and Baker, L.E. (2010) An in vivo microdialysis assessment of concurrent MDMA and cocaine administration in Sprague-Dawley rats. Psychopharmacology 209, 95–102. 3. Sellings, L.H., McQuade, L.E., and Clarke, P.B. (2006) Evidence for multiple sites within rat ventral striatum mediating cocaine-conditioned place preference and locomotor activation. J. Pharmacol. Exp. Ther. 317, 1178–1187. 4. Fiancette, J.F, Balado, E., Piazza, P.V., and Deroche-Gamonet, V. (2010) Mifepristone and spironolactone differently alter cocaine intravenous self-administration and cocaineinduced locomotion in C57BL/6J mice. Addict. Biol. 15, 81–87. 5. Jerlhag, E., Egecioglu, E., Dickson, S.L., and Engel, J.A. (2010) Ghrelin receptor antagonism attenuates cocaine- and amphetamineinduced locomotor stimulation, accumbal

6.

7.

8.

9.

10.

dopamine release, and conditioned place preference. Psychopharmacology 211, 415–422. Zombeck, J.A., Swearingen, S.P., and Rhodes, J.S. (2010) Acute locomotor responses to cocaine in adolescents versus adults from 4 divergent inbred mouse strains. Genes, Brain Behav. 9, 892–8. Smith, M.A., Iordanou, J.C., Coehn, M.B., Cole, K.T., Gergans, S.R., Lyle, M.A., and Schmidt, K.T. (2009) Effects of environmental enrichment on senstivity to cocaine in female rats: importance of control rates of behavior. Behav. Pharmacol. 20, 312–321. Sidman, M. (1960). Tactics of scientific research: evaluating experimental data in psychology. New York, NY: Basic Books. Stewart, J., and Badiani, A. (1993) Tolerance and sensitization to the behavioral effects of drugs. Behav. Pharmacol. 4, 289–312. Martin-Iverson, M.T., and Burger, L.Y. (1995) Behavioral sensitization and tolerance to cocaine and the occupation of dopamine receptors by dopamine. Mol. Neurobiol. 11, 31–46.

sdfsdf

Chapter 22 Methods in Tobacco Abuse: Proteomic Changes Following Second-Hand Smoke Exposure Joy Guingab-Cagmat, Rayna M. Bauzo, Adrie W. Bruijnzeel, Kevin K. Wang, Mark S. Gold, and Firas H. Kobeissy Abstract Smoking is one of the leading preventable causes of disease, disability, and death in the USA and leads to more than 400,000 preventable deaths per year. Nicotine is the major alkaloid present in tobacco smoke, and many of the negative effects of smoking are attributed to nicotine. Nicotine is not only the addictive component of tobacco smoke, but also highly associated with carcinogenesis and induces oxidative stress. Furthermore, the administration of nicotine via subcutaneous mini-osmotic pumps or by injection is an established method in preclinical studies for this area of research. Thus, preclinical research on the negative effects of tobacco smoke and tobacco addiction has focused primarily on the effects of nicotine. However, there are over 4,500 components found in tobacco smoke, many of which are highly toxic. Other components may also contribute to the addictive properties of tobacco smoke. Furthermore, the negative effects of tobacco smoke are not isolated to the smoker but can have negative effects to those exposed to the secondhand smoke (SHS) stream. SHS exposure is the third leading cause of preventable death. Approximately 38,000 deaths per year are attributed to SHS exposure in the USA. SHS exposure increases the risk of heart disease by approximately 30% and is associated with increased risk of stroke, cancer, type II diabetes, as well as pulmonary disease. Thus, methods of administering tobacco smoke in a controlled environment will further our understanding of tobacco addiction and the role tobacco smoke in other disease states. Moreover, combining smoke exposure with proteomics can lead to the discovery of biomarkers that can be potentially useful tools in screening, early diagnosis, prevention, and treatment of diseases caused by SHS. Key words: Tobacco, Secondhand smoke, Proteomics, SHS, Oxidative stress, Addiction, Toxicity

1. Introduction Tobacco smoking is a leading cause of preventable disease, disability, and death in the USA. Despite negative health consequences, smoking continues to be a significant health problem in developed countries. Approximately 90% of lung cancer cases in the USA are attributed to cigarette smoking. In the 2008 National Survey on Firas H. Kobeissy (ed.), Psychiatric Disorders: Methods and Protocols, Methods in Molecular Biology, vol. 829, DOI 10.1007/978-1-61779-458-2_22, © Springer Science+Business Media, LLC 2012

329

330

J. Guingab-Cagmat et al.

Drug Use and Health, nearly 71 million Americans aged 12 and older had used a tobacco product at least once in the month prior to being surveyed (1). Despite the well-documented health costs of smoking, many tobacco users find it difficult to quit smoking and many others are becoming addicted. Furthermore, exposure to secondhand tobacco smoke (SHS) is also a significant health concern worldwide. Its effects are wide-ranging and serious. SHS exposure increases nonsmokers’ risk of cardiovascular disease and stroke (2–9) by inducing several proatherosclerotic changes, including endothelial damage related to oxidative stress and inflammation, increased platelet aggregation, and increased arterial stiffness (6–9). Barnoya and Glantz estimate that these changes increase the risk of cardiovascular disease by 30% (6). SHS is also linked to several diseases of the lung, including cancer (10–15), COPD (16, 17), asthma (18), and tuberculosis (19). SHS is also associated with an increased risk of type 2 diabetes mellitus (20, 21) and with neurocellular changes in infants with perinatal SHS exposure (22–24). Although overall exposure to SHS in the USA has decreased over the past 20 years (25), the incidence of SHS exposure is still worrisome. A 2000 survey of Americans’ smoking habits revealed that 22 million children aged 3–11 years, 18 million nonsmoking youth aged 12–19 years, and 86 million nonsmoking adults aged 20 or more years were chronically exposed to SHS (26). Nicotine is the major alkaloid present in tobacco smoke, and many of the negative effects of smoking are attributed to nicotine. Nicotine is highly addictive and is also highly associated with carcinogenesis and oxidative stress. Furthermore, the administration of nicotine via subcutaneous mini-osmotic pumps or by injection is an established method in preclinical studies for this area of research. Thus, preclinical research on the negative effects of tobacco smoke and tobacco addiction has focused primarily on the effects of nicotine. However, there are over 4,500 components found in tobacco smoke, many of which are highly toxic. Other components may also contribute to the addictive properties of tobacco smoke and diseases associated with tobacco smoke. Several laboratories have employed an animal model in order to better understand the mechanism behind the deleterious effects of SHS exposure (27–29). These models allow researchers to approximate the human response to SHS in a controlled environment. A microprocessor-controlled TE-10 cigarette smoking-machine, developed by Teague and colleagues (30) is utilized in a procedure for precisely controlled delivery of SHS to rodents. Methods of administering tobacco smoke in a controlled environment will further our understanding of tobacco addiction and the role of tobacco smoke in other disease states. Proteomic techniques may be useful in identifying specific biomarkers of tobacco addiction or tobacco-related disease. Repeated nicotine injections resulted in changes in protein expression in

22

Proteomic of Second-Hand Smoke Exposure

331

striatum, amygdala, nucleus accumbens (NA), prefrontal cortex, and the ventral tegmental area (VTA), all of which are regions of the brain related to addiction (31, 32). Furthermore, a different protein expression profile in serum is expressed during active selfadministration, withdrawal, and reinstatement (33). Self-reports can be unreliable, thus further examination of serum protein expression profiles during each stage of the addiction process can help design better screening tools for clinical studies. Moreover, correlating serum protein expression with changes in protein expression profiles in other tissues, such as the heart and lung, may isolate significant biomarkers of tobacco-related diseases. Tandem mass spectrometry (MS/MS) methods can be utilized to measure proteomic changes following tobacco smoke exposure.

2. Materials 2.1. Smoke Exposure

1. Adult male Sprague-Dawley rats (Harlan, Indianapolis, IN, USA) weighed between 250 and 275 g. 2. Standard polycarbonate rodent cages (38 × 28 × 20 cm; L × W × H) with pine bedding and a wire top. 3. Filtered Kentucky 3R4F reference cigarettes (Tobacco Research Institute, University of Kentucky, Lexington, KY). 4. Microprocessor-controlled cigarette smoking-machine (model TE-10, Teague Enterprises, Davis, CA). 5. Microprocessor-controlled nondispersive infrared analyzer (Model 880, Rosemount Analytical Inc., Orrville, OH). 6. Liquid chromatography/tandem mass spectrometry (LC/ MS/MS; API 4000 LC/MS/MS system, Applied Biosystems Inc., Foster City, CA). 7. Nolvasan (chlorohexidine diacetate) disinfectant.

2.2. Blood and Tissue Collection

1. Isoflurane/oxygen mixture. 2. Propylene tubes. 3. 1× PBS. 4. Liquid nitrogen. 5. Dry ice. 6. 3 containers. 7. Mortar and pestle. 8. Spatula. 9. Ethanol. 10. 1× Triton extraction buffer. 11. DC protein assay kit (BIO-RAD; Hercules, CA).

332


2.3. Combined Cation–Anion Exchange Chromatography and SDS-PAGE

1. HPLC grade water (HPLC grade, Burdick & Jackson, Muskegon, MI). 2. Ice cold 20 mM Tris–HCl (pH 7.5 molecular biology grade, Fisher Scientific) as mobile phase A. 3. 1 M NaCl (Fisher Scientific, crystalline 99.8% certified) in ice cold 20 mM Tris–HCl (as mobile phase B). 4. Sulfoproyl (S1)and quaternary ammonium (Q1) modified sepharose prepacked ion-exchange columns (BioRad, CA). 5. 1.5-mL screw-cap microfuge tubes (RPI, Mt. Prospect, IL). 6. Millipore YM-10 ultrafiltration units (Millipore Corporation, Bedford, MA) retaining proteins of >10 kDa. 7. BioRad Biologic DuoFlow Liquid Chromatography system (Bio-Rad, CA).

2.4. In-Gel Digestion for LC-MS/MS Analysis

1. Optima LC-MS grade water (Fisher Scientific, Pittsburg, PA). 2. Optima LC-MS grade acetonitrile (Fisher Scientific, Pittsburg, PA). 3. 50 and 100 mM ammonium bicarbonate (NH4HCO3) (SigmaAldrich, St. Louis, MO). 4. Optima LC-MS grade water with 0.1% formic acid (Fisher Scientific, Pittsburg, PA). 5. Optima LC-MS grade acetonitrile with 0.1% formic acid (Fisher Scientific, Pittsburg, PA). 6. 10 mM DL-dithiothreitol (Sigma-Aldrich, St. Louis, MO) in 50 mM NH4HCO3. 7. 55 mM α-iodoacetamide (Sigma-Aldrich, St. Louis, MO) in 50 mM NH4HCO3. 8. 12.5 ng/μL Promega Gold Trypsin (Promega, Madison, WI) in 50 mM NH4HCO3. 9. 600 μL and 1.5 mL low retention Eppendorf tubes (Fisher Scientific, Pittsburg, PA). 10. 1–200 μL Fisherbrand gel loading tips (Fisher Scientific, Pittsburg, PA). 11. 20–200 μL disposable pipette tips (Fisher Scientific, Pittsburg, PA). 12. Disposable scalpels (Fisher Scientific, Pittsburg, PA). 13. 1.7 μm BEH130 C18 100 × 100 μm column (Waters, Milford, MA). 14. 5 μm symmetry 180 × 20 μm (Waters, Milford, MA). 15. LC vial (Waters, Milford, MA).

22


333

16. Picoemitter (New Objective, Woburn, MA). 17. Vortex (Fisher Scientific, Pittsburg, PA). 18. Backlight platform and glass for gel cutting. 19. 20–200 μL pipette (Fisher Scientific, Pittsburg, PA). 20. Heating block (Fisher Scientific, Pittsburg, PA). 21. Refrigerated microcentrifuge (Fisher Scientific, Pittsburg, PA). 22. Speed vacuum (Fisher Scientific, Pittsburg, PA). 23. Sonic water bath (Fisher Scientific, Pittsburg, PA). 24. Waters NanoAquity-LC system (Waters, Milford, MA). 25. Thermo LTQ-XL (Thermo, San Diego, CA). 2.5. 1D-Gel Electrophoresis

1. BIO-RAD molecular weight markers: Precision Plus Protein All Blue Standards. 2. Precast 10–20% gradient Tris–HCl polyacrylamide gels, 1.0 mm, 10 well (Biorad, CA). 3. Running buffer 10× Tris/Tricine/SDS: 100 mM Tris, pH 8.3, 100 mM Tricine, 0.1% SDS, kept at room temperature (Biorad, CA). 4. 2× Laemmli sample buffer (BIO-RAD with 5% β mercaptoethanol). 5. X-Cell Sure Lock Mini Cell Apparatus (Invitrogen Life Technologies, Ca). 6. BIO-RAD Power PAC-3000. 7. Coomassie Brilliant Blue R-250 (Biorad, CA). 8. Destaining solution: 40% methanol, 50% deionized water, and 10% acetic acid. 9. Methanol, HPLC grade (Fisher Scientific). 10. Glacial acetic acid, HPLC grade (Fisher Scientific).

2.6. Lysis Buffer

1. 0.1% SDS. 2. 150 mM sodium chloride. 3. 1% ethoxylated octylphenol. 4. 1 mM sodium vanadate. 5. 3 mM EDTA. 6. 2 mM EGTA. 7. 1 M fresh DTT stock. 8. Protease inhibitor tablet (Roche). 9. 1% triton X-100.

334


3. Methods 3.1. Smoke Exposure 3.1.1. Animal Exposure

1. Adult male (250–275 g) Sprague-Dawley rats are divided into experimental groups (see Note 1). 2. Subjects are habituated to the smoke machine for at least 3 days prior to smoke exposure in standard polycarbonate rodent cages (see Note 2). 3. SHS-exposed rats are placed in the rodent cages for smoke exposure and placed in the smoke chamber for 30 min on three consecutive days with the fan and compressor turned on but the smoke machine turned off. After 30 min, the rats are returned to their home cages. 4. Each smoke exposure chamber holds four exposure boxes at a time, so it may be necessary to place rats from different home cages into the same exposure box. Clearly, identify subjects to ensure that rats are were returned to the correct home cages (see Note 3). 5. Control rats should be handled similarly by placing them into a standard rodent cage for 30 min and returned to their home cages (see Note 4). 6. One day prior to the first experimental session, draw a 0.25– 0.5 mL blood sample from all subjects to determine baseline levels of cotinine and nicotine. 7. Briefly sedate the rat under 1% isoflurane/oxygen mixture. Shave hair on the hind leg to expose the saphenous vein. Draw blood from the saphenous vein and place on ice. Samples should be analyzed later for nicotine and cotinine levels. Repeat this procedure at least once per week throughout the exposure period to confirm. 8. On the day of smoke exposure, turn the fan and compressor on and allow equilibration for 10 min. 9. Fill the white water container three-fourth full and insert into the compartment below the cigarette igniter. 10. Adjust the pressure regulator knob (Fig. 1) so that the pressure feeding the cigarettes to the igniter is approximately 35 psi (see Note 5). 11. The rats are moved to the exposure cages immediately prior to the tobacco smoke or air exposure session and returned to their home cages after the exposure session (see Note 6). 12. Place 3R4F cigarettes in the cigarette tray so that the end to be burned faces the igniter. Place sufficient cigarettes in the tray to last for about three cycles (see Note 7). 13. Place the subjects to receive SHS in the exposure cages and place inside the smoke chamber. Properly secure the door to the smoke chamber to provide an adequate seal.

22


335

Fig. 1. TE-10 smoking machine used for secondhand smoking: Rat exposure chamber system package composed of: hood unit, mixing and dilution chamber, filter and blower with ducting, air compressor, two rat exposure chambers, cart for exposure chambers, orifice meters and controls, filter sampling unit with filter holder and dry gas meter.

14. Adjust the valve between the smoke generator and the exposure chamber to between (0.18–0.2 psi), using the lever located on the right side in the rear of the machine (Fig. 1) (see Note 8). 15. Begin smoke exposure by flipping the “ON” switch on the smoke machine, to the left of the machine (Fig. 1). 16. As soon as the machine’s display read “Finding Index Position,” use the up or down buttons (Fig. 1) to select the number of cigarettes burned per cycle. (see Note 9). 17. Tobacco smoke is generated by a microprocessor-controlled cigarette smoking-machine (originally described by Teague and colleagues (Teague et al., 1994: See picture below for setup). 18. Smoke is produced by burning filtered Kentucky 3R4F reference cigarettes using a standardized smoking procedure (35 cm3 puff volume, 1 puff per minute, 2 s per puff, 8 puffs per cigarette). 19. Mainstream and sidestream smoke is transported to a mixing and diluting chamber. The smoking machine is adjusted to produce a mixture of 15% mainstream smoke and 85% sidestream smoke (see Note 10). These percentages are based on total suspended particle matter readings. 20. The mixture of mainstream and sidestream smoke is aged for 2–4 min and diluted with filtered air to a concentration of 10 μg of nicotine per cubicmeter and ~70 mg of total suspended particles per cubicmeter (see Note 11). 21. The smoke is then introduced into the exposure chambers. Smoke exposure sessions are typically 4 h (see Note 12).

336


3.1.2. Carbon Monoxide and Total Suspended Particulate Matter

Smoke exposure conditions are monitored for carbon monoxide and total suspended particulate matter. The particle level and carbon monoxide (CO) readings are taken after half of the duration for smoke exposure has elapsed, in order to get an average value for the exposure period. 1. Weigh and record the weight of the filter paper to be used in determining the suspended particulate count. 2. Place the filter paper into the nozzle (Fig. 1) so that the rough side faces up, for optimal particle collection. 3. Remove plug to chamber and insert the nozzle into the hole, making sure that the washer was tightly sealed (see Note 13). 4. Record the exposure chamber pre-volume on the gas meter (Fig. 1). 5. Carbon monoxide levels are assessed using a “monoxer” device. The carbon monoxide and dioxide levels are maintained below the current Occupational Safety and Health Administration (OSHA) permissible exposure limits for humans in the workplace (see Note 14). 6. “To obtain a CO reading, take the monoxer device out of the room with the smoke machine. Turn the monoxer on. When the display value reaches 0-2 ppm, bring the monoxer back into the smoke machine room.” 7. The monoxer device into the exposure chamber via the open know on the right hand side (Fig. 1). 8. Start the secondary fan by pressing the red button on the box above the smoke exposure chamber (Fig. 1). 9. The CO count was read and record the CO count as the highest value that the monoxer device displayed before dropping back down. 10. After 5 min, the secondary fan stopped, and the chamber postvolume was recorded. 11. The filter paper was remove the filter paper and record its postweight was recorded. 12. The particle count was determine the particle count with the formula: Post - filter weight (mg) − pre - filter weight (mg) × 1, 000 Post - volume (m3 ) − pre - volume (m3 ) 13. Number of cigarettes should be adjusted if the particle count is not within the desired levels (see Note 15). Repeat the particle count after half an hour. 14. 10 min prior to the end of the exposure period, turn off the smoke machine (see Note 16).

22 3.1.3. End of the Exposure and Cleaning the Machine


337

1. At the end of the exposure period, turn off the fan and compressor. Allow 5 min for smoke to dissipate prior to opening the chamber. 2. Open the chamber and allow 5 min prior to removing the subjects from the chamber and returning to their home cages. Repeat daily for the duration of the experiment. 3. The cigarettes from the final cycle should have burned out. Remove the cigarette ends and place in the water container. 4. Empty the white container and rinse. Allow to dry overnight. 5. Using a hand vacuum cleaner, clean any ash or cigarette matter from around the smoking machine. Clean the smoking chamber with Nolvasan and remove any bedding.

3.2. Blood and Tissue Collection and Processing

1. At the end of the 30-day smoke exposure period, briefly anesthetize the subjects with 5% isoflurane and sacrifice by decapitation. Collect trunk blood in propylene tubes.

3.2.1. Animal Sacrifice and Blood Collection

2. Rapidly dissect desired tissue (e.g., heart, lung, liver, brain, etc.). Wash with saline solution, snap-freeze in liquid nitrogen, and store at −80°C for further processing. 3. Centrifuge the blood for 10 min at 4,000 × g and collect serum and store at −80°C until further processing.

3.2.2. Tissue Processing

1. To process the tissue, obtain approximately 10 lbs. dry ice. 2. Split dry ice into three containers, one ice bucket for crushing, and two Styrofoam containers for keeping the samples before and after crushing. 3. Crush dry ice with hammer till powder. 4. Clean mortar, pestle, and spatula with ethanol and chill in crushed dry ice for 20 min (see Note 17). 5. Obtain a bucket of liquid nitrogen for freezing each tube while sample is being crushed. Keep a small container of liquid nitrogen available while crushing. 6. Handling with gloves, place each individual sample in mortar. Place a new clean tube in the container of liquid nitrogen. 7. Lightly tap sample to fracture, and then proceed to grind to a fine powder using circular motions with the pestle. Cover the mortar with a round cardboard piece around the pestle to prevent sample loss. 8. Scrape sample with spatula to area near pouring indent. Take sample tube from liquid nitrogen and place in dry ice. Gently lift mortar and scrape sample into tube. Keep samples in dry ice. 9. Prepare lysis buffer (SDS or Triton buffer). For each 10 mL of buffer: (a) Add 0.1% SDS (b) Add 150 mM sodium chloride,

338


(c) Add 1% ethoxylated octylphenol, (d) Add 1 mM sodium vanadate, (e) Add 3 mM EDTA, (f) Add 2 mM EGTA (g) Add 10 μL of 1 M fresh DTT stock (final Concentration 1 mM) (h) Add one protease inhibitor tablet (Roche) (enough vortexing to dissolve) at time of crushing (i) SDS can be substituted with 1% triton X-100 if preferred; (Triton X-100 would add background peak to UV spectrum at 280 nm, but if spectrum not significant then triton may be fine). 10. When ready to extract, add buffer to samples (approximately 500 μL to cortex and 250 μL to hippocampus, more or less so that the sample is covered). Keep on the rotary shaker in the 4°, for 4 h. Vortex every hour. 11. Cool down microcentrifuge to 4°C. 12. Centrifuge all samples at 4° 15,000 × g for 10 min. 13. Aspirate supernatant from samples without disturbing the pellet and transfer to new labeled tube. 14. Conduct a DC protein assay in order to determine protein concentration (see Note 18). 15. For blood protein collection, proteins which could interfere with the LC-MS/MS analysis were precipitated by adding 150 μL methanol to 100 μL serum. This mixture was vortexed for 30 s and then centrifuged at 1,500 × g for 15 min. 16. The clear supernatant (100 μL) was carefully transferred into new propylene tubes (see Note 19). 17. Conduct a DC protein assay in order to determine protein concentration. 18. Samples can be kept at −80°C for further analysis (mass spectrometry or Western blotting, ELISA, etc.) 3.3. Combined Cation–Anion Exchange Liquid Chromatography and SDS-PAGE 3.3.1. Sample Preparation

1. Conduct protein assay and pool protein samples (n = 5). Conduct another protein assay of the pooled sample. 2. Add and pool protein samples in equal amounts to achieve and reconstitute the desired amount of proteins (~1 mg of protein); proteins can be suspended in triton buffer or any lysis buffer (SDS buffer). 3. Prepare the sample to be injected in the loop (make sure the loop volume is higher than the sample volume; without being diluted with buffer A), dilute the sample with buffer A used in

22


339

the cation–anion exchange (CAX) for optimization (critical step) to achieve a total volume equal to the total capacity of the injection loop. That is if the total volume of pooled protein is 125 μL while using a loop of 250 μL, then it is advised to add 125 μL of buffer A to your sample. 4. Make sure that the lysis buffer is compatible with the columns. Check the compatibility info of the chromatography column used. 5. Load the sample via a Hamilton Syringe with the appropriate volume in the loop. 3.3.2. Column Selection: UNO Anion (Q1) and Cation (S1) Exchange Columns Maintenance

The choice of whether to use an anion- or cation exchanger is determined mainly by (a) the isoelectric point (pI) and, (b) the relationship between pH and the activity/stability and complexity of the protein sample of interest. 1. For the brain sample, combined CAX column are connected in tandem. 2. Buffer A is made of 20 mM Tris–HCl while buffer B is 20 mM Tris–HCl with 0.5 M NaCl. 3. A flow rate of 1 mL/min is used throughout the protocol. 4. After sample preparation with proper lysis buffer, sample is injected in the sample loop while the injection valve is at the load position. 5. Fraction of 1 mL over a gradient of 20~30 mL are collected and are concentrated to be run on 1D-PAGE.

3.3.3. Protocol Used for Liquid Chromatography Analysis

Depending on the sample, concentration, lysis buffer, complexity, one can optimize the chromatography run accordingly. For complex samples, such as whole brain tissue, the following protocol has been used and been showing good separation. 1. The whole run will use 1 mL/min flow rate. (See the Chromatogram Monitoring while running) 2. Apply an isocratic flow of a volume of 1.5 mL of buffer A. 3. This is followed by QuadTec Zeroing for baseline zeroing which is followed by the injection into the loop of 1 mL of buffer A. 4. This is followed by load/injection of sample into the loop with a volume of 1.5 mL. 5. Isocratic flow of a volume of 1 mL of buffer A. 6. Linear gradient from 0 to 16% buffer B with a total volume 5 mL. 7. Linear gradient from 16 to 30% buffer B with a total volume 9 mL.

340


8. Linear gradient from 30 to 40% buffer B with a total volume 2 mL. 9. Linear gradient from 40 to 60% buffer B with a total volume 1 mL. 10. Linear gradient from 60 to 0% buffer B with a total volume 2 mL. 11. Isocratic flow of a volume of 3.5 mL of buffer A. 3.3.4. Chromatograms Monitoring and Sample Collection

1. Collect fractions with BioFrac fraction collector into 1.5-mL screw-cap microfuge tubes at UV wavelength of 280 and 214 nm for each run. Overlay using the BioRad software. 2. Concentrate fractions collected throughout CAX chromatography using Millipore YM-10 ultrafiltration units. 3. Prior to use of YM-10 ultrafiltration units, wash with distilled water, and centrifuge for 25 min to wet the membrane. 4. Following this, the fractions collected (total volume of 1 mL), are run twice in each YM-10 unit (capacity 500 μL), each 500 μL will be added and centrifuged at full speed for 40 min which needs to be repeated for two times to run the second 500 μL. 5. Laemmli sample buffer (25 μL) is added to the YM-10 collection filters prior to collection by centrifugation at 1137 g-force for 3 min.

3.3.5. Sample Run on SDS Page and Band Quantification

1. For the SDS-1D-PAGE analysis, protein fractions collected after Millipore YM-10 ultrafiltration are run side-by-side using 10-well, 10–20% gradient Tris–HCl gels. 2. For differential comparison, NIH ImageJ software (version 1.6, NIH, Bethesda, MD) is used for quantitative densitometric analysis of gel band intensity. 3. Protein markers are added at the first and last lane of the gels, if there is an empty well at the end add Laemmli buffer to prevent protein diffusion.

3.4. In-Gel Digestion for LC-MS/MS Analysis 3.4.1. Gel Band Excision from the 1D Gel

3.4.2. Washing of Gel Pieces

1. Wash stained gel slab with Optima LC-MS grade water two times for 10 min each. 2. Use a clean scalpel to excise the band of interest from the gel, cutting as close to the band as possible. 3. Cut the gel band into four cubes that are approximately 1 mm3. Place the gel cubes in 1.5 mL low retention Eppendorf tube containing 150 μL Optima LC-MS water. 1. Remove the liquid using a pipette with a gel loading tip and discard. 2. Add 150 μL Optima LC-MS water, vortex for 5 min, and discard water.

22


341

3. Wash gel pieces with 150 μL 50% 100 mM NH4HCO3/50% ACN for 30 min with 5 min mixing using a vortex. 4. Remove the wash and discard. 5. Repeat steps 3 and 4 until gel pieces are colorless. 6. Dehydrate gel pieces with 20 μL ACN. 7. Dry the gel pieces completely under vacuum for 10 min. 3.4.3. Reduction and Alkylation

1. Rehydrate gel pieces with 50 μL of 10 mM DTT in 50 mM NH4HCO3. 2. Incubate for 30 min at 56°C. 3. Allow tubes to cool to room temperature and discard liquid. 4. Add 50 μL 55 mM iodoacetamide in 50 mM NH4HCO3. 5. Incubate for 30 min in the dark at room temperature. 6. Discard liquid and add 100 μL of 50 mM NH4HCO3. 7. Vortex for 15 min. 8. Repeat steps 6 and 7 two more times. 9. Dehydrate gel pieces with 20 μL ACN for 5 min. 10. Remove the liquid and dry under vacuum for 10 min.

3.4.4. Digestion with Trypsin

1. Rehydrate the gel pieces with 15 μL of 12.5 ng/μL trypsin solution. 2. Incubate at 4°C for 30 min. 3. Add 20 μL of 50 mM NH4HCO3. 4. Incubate overnight at 37°C in a heating block.

3.4.5. Peptide Extraction and Reconstitution

1. Centrifuge sample tubes at 20879 g-force for 15 min. 2. Appropriately label 600 μL low retention Eppendorf microcentrifuge tubes. 3. Transfer the supernatant into the newly labeled tubes. 4. Extract peptides from the gel pieces by adding 30 μL 50% ACN/50% H2O with 0.1% formic acid. 5. Centrifuge for 20 min at 20879 g-force. 6. Transfer the supernatant into the newly labeled tubes. 7. Repeat steps 4–6. 8. Dry the supernatant under vacuum to complete dryness (or to a volume of ~10 μL). 9. Re-suspend peptides in 20 μL of H2O with 0.1% formic acid. 10. Place tubes in sonic water bath for 15 min. 11. Centrifuge tubes for 15 min at 20879 g-force.

342


12. Carefully transfer supernatant into properly labeled LC vials. Avoid pipetting any residue at the bottom of the tube. 13. Analyze samples with LC-MS/MS. 3.5. LC-MS/MS Analysis

3.5.1. Nanoflow Liquid Chromatography

The LC-MS/MS proteomic workflow used for this type of experiment is described below. The workflow involves chromatographic separation on a nanocolumn at a low flow rate with an linear ion trap mass spectrometer. MS/MS is conducted using top 5 datadependent analysis. The MS/MS data acquired are searched against a protein database using database search software to identify proteins. An example of the data collected from this proteomic workflow is shown in Figs. 2 and 3. 1. Set the injection volume to 2 μL 2. Use the following column and corresponding flow rates: (a) Analytical Column: 1.7 μm BEH130 C18 100 × 100 μm Analytical flow rate: 250 nL/min (b) Trap Column: 5 μm symmetry 180 × 20 μm Trapping flow rate: 3 μL/min for 5 min 3. Set the column temperature to 25°C and sample temperature to 18°C.

Fig. 2. All MS/MS spectra are searched against an indexed protein database by a search engine software (i.e., Bioworks Sequest). The search parameters, such as the database, enzyme, and amino acid modifications, are set as shown in a and b. The search results include all peptide matches and their corresponding scores as shown in c.

22


343

Fig. 3. Scaffold (ProteomeSoftware, Inc.) is graphical software used to consolidate and validate protein database search results. It allows comparison of protein expression between samples as shown by the samples view (a). The protein view provides information, such as sequence coverage and list of peptide matches and their corresponding spectra (b).

4. Use the following solvent gradient. Time (min)

3.5.2. Mass Spectrometric Method

%A

%B

Flow rate (nL/min)

0

98

2

250

25

35

65

250

35

2

98

250

40

2

98

250

40.1

98

2

250

60

98

2

250

1. The analysis time is set to 60.00 (same as the length of the LC gradient). 2. The following parameters are set for top 5 data-dependent scan (a) Number of scan events: 6 (b) Scan event 1: Full MS (300–2,000)

344


(c) Scan event 2: Data-dependent MSMS most intense ion from (1) (d) Scan event 3: Data-dependent MSMS 2nd most intense ion from (1) (e) Scan event 4: Data-dependent MSMS 3rd most intense ion from (1) (f) Scan event 5: Data-dependent MSMS 4th most intense ion from (1) (g) Scan event 6: Data-dependent MSMS 5th most intense ion from (1) 3.5.3. Protein Database Search

1. All MS/MS spectra are searched against a protein database for protein identification using Sequest (Proteome Discoverer). The following parameters are applied (a) Peptide tolerance: 2.5 Da (Monoisotopic) (b) Fragment tolerance: 1.00 Da (Monoisotopic) (c) Enzyme: Trypsin (d) Protein database: ipi.RAT. 2. The sequest results file are uploaded onto Scaffold 3 for data consolidation and validation of protein identification with X-tandem database search engine. Stringent filtering criteria, such as below are applied to eliminate low probability protein hits. (a) Min protein probability 99.9% (b) Min peptide probability 95% (c) Min number of peptides 2

4. Notes 1. Subjects should have at least a week to acclimate to the home environment prior to beginning the experiment. However, institutional guidelines for acclimating subjects after arrival to the institution should be followed. 2. Rats can be exposed directly in their home cages. To minimize the smell of smoke in the home room, rats are transferred to a separate standard caging with corn-cob bedding. The same subjects should be placed in the same caging for each smoke or air exposure session. 3. Subjects within the same experimental treatment (smoke vs. air exposed) should be housed together. 4. Animals are given access to rat chow and water ad libitum in the home cage. During exposure, water and food should be

22


345

provided. Food should be changed daily and water bottles changed two times per week. 5. The pressure reading display is on top of the machine, to the right of the pistons. 6. The rats are not restrained (whole body exposure) during the tobacco smoke exposure sessions. Water should be freely available. 7. One cycle lasts approximately 10 min. Check cigarettes every 10–15 min to ensure that the machine is running smoothly and to clear any cigarette jams. Additional cigarettes, if needed, should be added during these checks. 8. The valve controls the amount of smoke that travels between the mixing chamber and the exposure chamber. 9. The number of cigarettes burned per cycle selected is based on the experimental objectives. Mainstream and sidestream smoke, as generated by burning the 3R4F reference cigarettes, contains 0.79 and 4.76 mg of nicotine per cigarette, respectively. SHS levels can be achieved with one to two cigarettes per cycle. Increasing the number of cigarettes to three to four cigarettes per cycle reaches exposure levels similar to firsthand smoke exposure. 10. This mixture most closely resembles the SHS exposure conditions in humans. 11. The particle count for secondhand smoking should be around 30–60 mg/m3 (90–100 mg/m3 for firsthand smoking). This can usually be achieved by using one to two cigarettes. 12. The exposure session time can be adjusted depending on the experimental design and the desired level of nicotine exposure for the intended experiment. 13. If using more than one exposure chamber, the particle count will have to be measured for each chamber separately. 14. The exposure limit for carbon monoxide is 50 parts per million (ppm) parts of air (i.e., 55 mg/m3) and the exposure limit for carbon dioxide is 5,000 ppm (i.e., 9,000 mg/m3). 15. The smoke machine should be cleaned regularly, however increased variability in the particulate count may indicate that there is a build-up of tar. Clean the valves to prevent blockage with methanol. The fan should be cleaned regularly as well. Decreasing particle count can also indicate that there is a problem with cigarettes igniting. Check to make ensure cigarettes are properly aligned with the filament and that the cigarettes are lighting properly. 16. Make sure the final cycle of cigarettes has been lit prior to turning off the machine. This will ensure that no additional cigarettes

346


will be lit. The fan and compressor should be left on to continue to mix and dispersed into the smoking chamber. 17. Washing the mortar, pestle, and spatula should be performed when you are using different animal groups, such as control vs. SHS-exposed. No need for washing when homogenizing tissues within animals of the same group. 18. Tissue sample lysate used in the DC protein assay were diluted up to 1/5 and 1/10 of original volume (with HPLC water) so that they can lie within linear range of DC protein assay (0.125 to 2 μg/μL). 19. The protein supernatant is always kept at 4°C or ice until collection so as to prevent proteolysis.

Acknowledgments This work was supported in part by the Donald and Irene Dizney Eminent Scholar Chair, held by Mark S. Gold, M.D. Distinguished Professor, McKnight Brain Institute. Dr. Adrie W. Bruijnzeel was supported by a Flight Attendant Medical Research Institute Young Clinical Scientist Award (Grant nr. 52312). References 1. (2009) Results from the 2008 National Survey on Drug Use and Health: National Findings Substance Abuse and Mental Health Services Administration, Rockville, MD. 2. Eisner, M. D., Wang, Y., Haight, T. J., Balmes, J., Hammond, S. K., and Tager, I. B. (2007) Secondhand smoke exposure, pulmonary function, and cardiovascular mortality, Ann Epidemiol 17, 364–373. 3. Gallo, V., Neasham, D., Airoldi, L., Ferrari, P., Jenab, M., Boffetta, P., Overvad, K., Tjonneland, A., Clavel-Chapelon, F., Boeing, H., Pala, V., Palli, D., Panico, S., Tumino, R., Arriola, L., Lund, E., Bueno-De-Mesquita, B., Peeters, P. H., Melander, O., Hallmans, G., Riboli, E., Saracci, R., and Vineis, P. Secondhand smoke, cotinine levels, and risk of circulatory mortality in a large cohort study of never-smokers, Epidemiology 21, 207–214. 4. Faught, B. E., Flouris, A. D., and Cairney, J. (2009) Epidemiological evidence associating secondhand smoke exposure with cardiovascular disease, Inflamm Allergy Drug Targets 8, 321–327. 5. Raupach, T., Schafer, K., Konstantinides, S., and Andreas, S. (2006) Secondhand smoke as

6.

7.

8.

9.

an acute threat for the cardiovascular system: a change in paradigm, Eur Heart J 27, 386–392. Barnoya, J., and Glantz, S. A. (2005) Cardiovascular effects of secondhand smoke: nearly as large as smoking, Circulation 111, 2684–2698. Jefferis, B. J., Lowe, G. D., Welsh, P., Rumley, A., Lawlor, D. A., Ebrahim, S., Carson, C., Doig, M., Feyerabend, C., McMeekin, L., Wannamethee, S. G., Cook, D. G., and Whincup, P. H. Secondhand smoke (SHS) exposure is associated with circulating markers of inflammation and endothelial function in adult men and women, Atherosclerosis 208, 550–556. Venn, A., and Britton, J. (2007) Exposure to secondhand smoke and biomarkers of cardiovascular disease risk in never-smoking adults, Circulation 115, 990–995. Panagiotakos, D. B., Pitsavos, C., Chrysohoou, C., Skoumas, J., Masoura, C., Toutouzas, P., and Stefanadis, C. (2004) Effect of exposure to secondhand smoke on markers of inflammation: the ATTICA study, Am J Med 116, 145–150.

22


10. Fontham, E. T., Correa, P., Reynolds, P., Wu-Williams, A., Buffler, P. A., Greenberg, R. S., Chen, V. W., Alterman, T., Boyd, P., Austin, D. F., and et al. (1994) Environmental tobacco smoke and lung cancer in nonsmoking women. A multicenter study, JAMA 271, 1752–1759. 11. Brownson, R. C., Figgs, L. W., and Caisley, L. E. (2002) Epidemiology of environmental tobacco smoke exposure, Oncogene 21, 7341–7348. 12. Hecht, S. S. (2006) A biomarker of exposure to environmental tobacco smoke (ETS) and Ernst Wynder’s opinion about ETS and lung cancer, Prev Med 43, 256–260. 13. Wu, C. F., Feng, N. H., Chong, I. W., Wu, K. Y., Lee, C. H., Hwang, J. J., Huang, C. T., Lee, C. Y., Chou, S. T., Christiani, D. C., and Wu, M. T. Second-hand smoke and chronic bronchitis in Taiwanese women: a health-care based study, BMC Public Health 10, 44. 14. Anderson, K. E., Carmella, S. G., Ye, M., Bliss, R. L., Le, C., Murphy, L., and Hecht, S. S. (2001) Metabolites of a tobacco-specific lung carcinogen in nonsmoking women exposed to environmental tobacco smoke, J Natl Cancer Inst 93, 378–381. 15. Anderson, K. E., Kliris, J., Murphy, L., Carmella, S. G., Han, S., Link, C., Bliss, R. L., Puumala, S., Murphy, S. E., and Hecht, S. S. (2003) Metabolites of a tobacco-specific lung carcinogen in nonsmoking casino patrons, Cancer Epidemiol Biomarkers Prev 12, 1544–1546. 16. Eisner, M. D., Balmes, J., Yelin, E. H., Katz, P. P., Hammond, S. K., Benowitz, N., and Blanc, P. D. (2006) Directly measured secondhand smoke exposure and COPD health outcomes, BMC Pulm Med 6, 12. 17. Eisner, M. D., Iribarren, C., Yelin, E. H., Sidney, S., Katz, P. P., Sanchez, G., and Blanc, P. D. (2009) The impact of SHS exposure on health status and exacerbations among patients with COPD, Int J Chron Obstruct Pulmon Dis 4, 169–176. 18. Butz, A. M., Breysse, P., Rand, C., CurtinBrosnan, J., Eggleston, P., Diette, G. B., Williams, D., Bernert, J. T., and Matsui, E. C. Household Smoking Behavior: Effects on Indoor Air Quality and Health of Urban Children with Asthma, Matern Child Health J. 19. Leung, C. C., Lam, T. H., Ho, K. S., Yew, W. W., Tam, C. M., Chan, W. M., Law, W. S., Chan, C. K., Chang, K. C., and Au, K. F. Passive smoking and tuberculosis, Arch Intern Med 170, 287–292. 20. Houston, T. K., Person, S. D., Pletcher, M. J., Liu, K., Iribarren, C., and Kiefe, C. I. (2006) Active and passive smoking and development of glucose intolerance among young adults in a

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

347

prospective cohort: CARDIA study, BMJ 332, 1064–1069. Kowall, B., Rathmann, W., Strassburger, K., Heier, M., Holle, R., Thorand, B., Giani, G., Peters, A., and Meisinger, C. Association of passive and active smoking with incident type 2 diabetes mellitus in the elderly population: the KORA S4/F4 cohort study, Eur J Epidemiol 25, 393–402. Slotkin, T. A. (2004) Cholinergic systems in brain development and disruption by neurotoxicants: nicotine, environmental tobacco smoke, organophosphates, Toxicol Appl Pharmacol 198, 132–151. Slotkin, T. A., Pinkerton, K. E., and Seidler, F. J. (2006) Perinatal environmental tobacco smoke exposure in rhesus monkeys: critical periods and regional selectivity for effects on brain cell development and lipid peroxidation, Environ Health Perspect 114, 34–39. Slotkin, T. A., Pinkerton, K. E., Tate, C. A., and Seidler, F. J. (2006) Alterations of serotonin synaptic proteins in brain regions of neonatal Rhesus monkeys exposed to perinatal environmental tobacco smoke, Brain Res 1111, 30–35. Pirkle, J. L., Bernert, J. T., Caudill, S. P., Sosnoff, C. S., and Pechacek, T. F. (2006) Trends in the exposure of nonsmokers in the U.S. population to secondhand smoke: 1988– 2002, Environ Health Perspect 114, 853–858. (2006) The health consequences of involuntary exposure to tobacco smoke: a report of the Surgeon General., U.S. Department of Health and Human Services, Atlanta, GA. Maes, T., Provoost, S., Lanckacker, E. A., Cataldo, D. D., Vanoirbeek, J. A., Nemery, B., Tournoy, K. G., and Joos, G. F. Mouse models to unravel the role of inhaled pollutants on allergic sensitization and airway inflammation, Respir Res 11, 7. Song, D. J., Min, M. G., Miller, M., Cho, J. Y., Yum, H. Y., and Broide, D. H. Toll-like receptor-9 agonist inhibits airway inflammation, remodeling and hyperreactivity in mice exposed to chronic environmental tobacco smoke and allergen, Int Arch Allergy Immunol 151, 285–296. Zhang, S., Xu, N., Nie, J., Dong, L., Li, J., and Tong, J. (2008) Proteomic alteration in lung tissue of rats exposed to cigarette smoke, Toxicol Lett 178, 191–196. Teague, S. V., Pinkerton, K. E., Goldsmith, M., Gebremichael, A., Chang, S., Jenkins, R. A., and Moneyhun, J. H. (1994) Sidestream cigarette smoke generation and exposure system for environmental tobacco smoke studies., Inhalation Toxicology 6, 79–93.

348


31. Yeom, M., Shim, I., Lee, H. J., and Hahm, D. H. (2005) Proteomic analysis of nicotineassociated protein expression in the striatum of repeated nicotine-treated rats, Biochem Biophys Res Commun 326, 321–328. 32. Hwang, Y. Y., and Li, M. D. (2006) Proteins differentially expressed in response to nicotine in five rat brain regions: identification using a

2-DE/MS-based proteomics approach, Proteomics 6, 3138–3153. 33. Cecconi, D., Tessari, M., Wille, D. R., Zoli, M., Domenici, E., Righetti, P. G., and Carboni, L. (2008) Serum proteomic analysis during nicotine self-administration, extinction and relapse in rats, Electrophoresis 29, 1525–1533.

Part IV Methods in Animal Models of Eating Disorders

sdfsdf

Chapter 23 Animal Models of Sugar and Fat Bingeing: Relationship to Food Addiction and Increased Body Weight Nicole M. Avena, Miriam E. Bocarsly, and Bartley G. Hoebel Abstract Binge eating is a behavior that occurs in some eating disorders, as well as in obesity and in nonclinical populations. Both sugars and fats are readily consumed by human beings and are common components of binges. This chapter describes animal models of sugar and fat bingeing, which allow for a detailed analysis of these behaviors and their concomitant physiological effects. The model of sugar bingeing has been used successfully to elicit behavioral and neurochemical signs of dependence in rats; e.g., indices of opiate-like withdrawal, increased intake after abstinence, cross-sensitization with drugs of abuse, and the repeated release of dopamine in the nucleus accumbens following repeated bingeing. Studies using the model of fat bingeing suggest that it can produce some, but not all, of the signs of dependence that are seen with sugar binge eating, as well as increase body weight, potentially leading to obesity. Key words: Binge eating, Dopamine, Fat, Food addiction, Nucleus accumbens, Sugar, Body weight

1. Introduction 1.1. Bingeing Behavior

Although binge-eating behavior has traditionally been associated with eating disorders, it is becoming more prevalent in the USA through its emergence in a variety of clinical and nonclinical populations. Bingeing is the main criteria for the diagnosis of bingeeating disorder, a disorder that affects approximately 6% of the population (1). Binge eating is also a hallmark of bulimia nervosa, a disorder characterized by cyclic binge eating and compensatory caloric purging. Further, binge eating has been linked to obesity, which presently afflicts 33% of the adult US population (2, 3). Binge eating may also be a predictor of body-fat gain among children, leading to a high risk for adult obesity (4). In addition to its relationship with obesity, binge eating is associated with increased frequency of body weight fluctuation, depression, anxiety, and substance abuse (5–7). Taken together, these studies suggest that


351

352

N.M. Avena et al.

binge eating affects a significant proportion of our society, and it has deleterious consequences, making it important to study from a public-health perspective. Studies have correlated the increase in obesity with an increase in sugar consumption (8, 9) and fat consumption (10). These two nutrients are the focus of this protocol. 1.2. An Animal Model of Binge-Eating Sugar

Animal models of binge eating can be useful for studying the pathology underlying aberrant eating behaviors in human beings. Binge-eating behavior is observed in rats after just a few days of intermittent access to a sugar (e.g., 25% glucose or 10% sucrose) solution and chow. Rats have access to sugar and chow 12 h daily followed by 12 h of deprivation for approximately 1 month (11). Here, binge-eating behavior is defined as an increase in intake of the sugar solution during the first hour of access (animals have been shown to consume approximately 20% of their total daily sugar intake in the first hour of access). Further, sugar-bingeing rats gradually increase their total daily intake of sugar, eventually drinking as much in the 12-h access period as ad libitum-fed rats do in 24 h (~70 mL/day, see Fig. 1). We impose a 4-h delay between the onset of the dark cycle and the onset of food access in order to induce bingeing, as rats normally feed at the onset of the dark cycle and the delay will ensure that they will be hungry when the food is made available. Meal analyses demonstrate that in addition to escalated intake in the first hour, binge-eating rats show spontaneous binge episodes throughout the day while ad libitum-fed controls do not (12).

1.3. Binge Eating and Food Addiction

Food is a natural reward that activates neurochemical pathways in the brain that evolved to reinforce this behavior and others by making them pleasurable and motivating. Other reinforcers, including many drugs of abuse, exert their powerful reinforcing effects by usurping these brain pathways. Overlaps in the circuitry regulating food and drug intake have been well documented (13–18). Together, this overlapping circuitry, along with selfreports regarding feelings of compulsion to eat sweet or fat-rich foods, similar in some ways to an addict’s compulsion to smoke cigarettes or drink alcohol, has inspired the study of “food addiction.” The sugar binge eating model described in this chapter is a tool that can be used to study food addiction in the laboratory. Bingeing is one criterion used by drug abuse researchers when classifying a substance as potentially addictive. Bingeing represents the transition from substance use to abuse (19), and it involves an escalation in the size and frequency of intake bouts, usually after a period of deprivation (19, 20). In addition to bingeing, other criteria, such as withdrawal, craving and cross-sensitization, have been described as behavioral signs of dependence on drugs of abuse. All of these criteria have been demonstrated using the animal model of sugar binge eating as described in this chapter (12, 21–29). Rats maintained on the described sugar binge protocol also show neurochemical signs of dependence, including an increase in

23

Animal Models of Food Addiction

353

Fig. 1. Sugar and chow intake during the 28-day access period. (a) Rats with binge access to sugar and chow (i.e., intermittent sugar + chow) escalated their total daily sugar intake over time. (b) However, these rats ate fewer grams of chow than the intermittent chow and ad libitum chow control groups. (c) There was no difference among groups in total daily caloric intake. Adapted with permission from (12).

mu-opioid and D1 dopamine (DA) receptor binding in the nucleus accumbens (NAc), and increased D3 dopamine receptor mRNA in the NAc (25, 30). This is one area of the brain involved in motivation and reward for both eating and drug abuse (14, 31–35). Studies using in vivo microdialysis reveal that sugar-bingeing rats release DA in the NAc on days 1, 2, and 21 of bingeing on sugar

354

N.M. Avena et al.

Fig. 2. Changes in extracellular DA in the NAc of sham-feeding and real-feeding rats during sucrose intake. The rectangles along the ordinate indicate when 10% sucrose was available. DA level is expressed as percentage of the mean baseline and is shown before, during and after unrestricted access to the sucrose. Significant differences between groups are indicated by asterisks (p < 0.05). Significant differences from baseline are indicated by (double dagger ) ( p < 0.05). Adapted with permission from (36).

(28), whereas nonbingeing rats show a blunted DA response that is more like the effect seen with a palatable food that is no longer novel (37). Further, this unabated release of DA with sugar bingeing can be elicited by the taste of sucrose, alone, as revealed by sham-feeding ((36), see Fig. 2). These neurochemical alterations are similar, albeit smaller in magnitude, to what is observed when rats repeatedly administer drugs of abuse. After binge-eating sugar for approximately 1 month, rats show signs of opiate-like withdrawal. The opioid antagonist naloxone can be used to precipitate withdrawal signs, such as teeth-chattering, tremors, and ultrasonic vocalizations (24, 38). Signs of withdrawal can also emerge spontaneously by fasting the rats for 24–36 h (38). In both cases, the withdrawal behavior is coupled with an increase in the release of accumbens acetylcholine (ACh) and a decrease in DA (24, 38). This neurochemical imbalance in DA/ACh has been seen during withdrawal from drugs of abuse, such as alcohol, morphine, and nicotine (39–42). Further, following abstinence from sucrose, rats will exhibit a larger binge than ever before, indicating a “deprivation effect” and suggesting craving (43). In addition, cross-sensitization between rats maintained on the sugar-binge feeding schedules and amphetamine, alcohol, and cocaine, have been reported (21–23, 26). 1.4. Sugar Bingeing and Body Weight

Body weight does not differ between rats that are bingeing on sugar and those with ad libitum access to chow or sugar; the rats are able to regulate their caloric intake and compensate for the excess energy obtained from sugar by eating less rodent chow (38).

23


355

This type of spontaneous bingeing/restricting behavior is similar to that of some patients with nonpurging type bulimia (44), particularly those who binge eat, but nonetheless maintain a normal body weight. While eliminating the variable of increased body weight is useful for some studies, it does not help with understanding the suggested link between binge eating and obesity. To study this relationship, we now discuss another animal model using a different primary nutrient: fat. 1.5. An Animal Model of Fat Bingeing

Corwin and colleagues have shown that rats with ad libitum access to rodent chow will binge on vegetable fat when it is presented for 2 h each day (45, 46). This effect is enhanced when the fat is offered on a more restricted schedule; e.g., 2 h, three times per week. Others have used diets rich in both fat and sugar (i.e., Oreo cookies), and find evidence of binge eating on these diets that is enhanced in response to stress (47, 48). Similarly, we describe here a model of binge eating in which limited daily access to sweet-fat chow in nondeprived animals leads to bingeing behavior, as defined by excessively large meals (49, 50). Unlike Corwin’s model which uses pure fat, we used a sweet-fat diet, with the goal of capitalizing on the known effects that sugar bingeing can have on behavior and brain chemistry, and combining them with the effect that fat is expected to have on body weight. Rats with 2-h daily access to sweet-fat chow (45% fat, 20% protein, 35% carbohydrate, 4.7 kcal/g) binge on it, even though they have ad libitum access to standard rodent chow for the other 22 h/day. By week 3 of access, rats consume, on average, 58% of their daily calories during the 2-h binge (49). Although, as described above, sugar bingeing does not lead to obesity, binge eating a combination of sweet-fat does result in significant changes in body weight (49). These animals show daily self-imposed restriction of standard chow intake, resulting in fluctuations in daily body weight characterized by weight loss between binges. However, despite these fluctuations in body weight, animals with binge access to a sweet-fat diet weigh significantly more than control groups that either have standard chow or sweet-fat chow available ad libitum (see Fig. 3). This indicates a model of binge eating that is associated with weight gain and obesity. Further, this is a model of binge eating in the absence of hunger, which in many ways, more accurately reflects voluntary bingeing in humans when energy-deprivation is not driving food intake. The combination of these two nutrients, sugar and fat, constitutes a large proportion of the snacks and desserts that patients with eating disorders tend to overconsume, possibly contributing to body weight gain (51–54). It is of interest to note that, contrary to our initial hypothesis, naloxone-precipitated withdrawal is not seen in rats binge eating the sweet-fat chow (12). This underscores the idea that not all palatable foods, and importantly, combinations of palatable foods, are

356

N.M. Avena et al.

Fig. 3. Caloric intake and body weight alterations in a rat model of sweet-fat bingeing. (a) Total daily caloric intake during Week 3 of access expressed as calories derived from standard chow (white) vs. sweet-fat chow (black). The 2-h Daily Sweet-fat group and a group that received 2-h of sweet-fat chow only on Mondays, Wednesdays, and Fridays (2-h MWF Sweet-fat) both consume more than 50% of their daily calories from sweet-fat chow when it is available (asterisk = p < 0.05 compared with the Ad libitum Standard Chow group, mean ± SEM). (b) A saw-tooth pattern emerges for the 2-h Daily Sweet-fat group in which they decrease in weight pre-binge and increase in weight post-binge each day. (c) However, despite this fluctuation in body weights throughout the day, the rats with 2-h daily sweet-fat gained significantly more total body weight than rats fed standard chow ad libitum. Adapted with permission from (49).

23


357

alike in terms of their effects on behavior and the brain. However, other models of bingeing on a fat-rich food suggest that there may be a link between addiction and overeating of fat (55–60). More research is needed to define the exact role that fat consumption has in addiction-like behavior.

2. Materials 2.1. Sugar Bingeing

1. Sucrose or glucose. 2. Prepare a 25% (w/v) glucose or 10% (w/v) sucrose solution with tap water (see Notes 6–8). 3. Adult male or female rats (e.g., Sprague-Dawley rats) weighing at least 250 g (see Note 1). 4. Standard laboratory rodent chow (e.g., LabDiet #5001, PMI Nutrition International, Richmond, IN; 10% fat, 20% protein, 70% carbohydrate, 3.01 kcal/g). 5. Scale accurate to 0.1 g. 6. Hanging wire-mesh cages or plastic-bottom cages with removable food hoppers (e.g., Allentown Caging Equipment; see Note 2). 7. Rodent vivarium with a 12-h light/dark cycle, maintained at 21°C. 8. 100-mL graduated (in 1-mL increments) drinking tubes: e.g., glass drinking tubes (Lab Products) or tubes made from 100mL polyethylene graduated cylinders (Fisher Scientific) by cutting off the flange and filing the top flat. 9. Rubber stoppers with sipper tubes (steel-ball tip valves preferred; see Note 3).

2.2. Sweet-Fat Bingeing

1. Sweet-fat nutritionally complete rodent chow (e.g., Research Diets, New Brunswick, NJ, #12451). 2. Adult male rats (e.g., Sprague-Dawley rats) weighing at least 250 g. 3. Standard laboratory rodent chow (e.g., LabDiet #5001, PMI Nutrition International, Richmond, IN; 10% fat, 20% protein, 70% carbohydrate, 3.01 kcal/g). 4. Scale accurate to 0.1 g. 5. Hanging wire-mesh cages or plastic-bottom cages with removable food hoppers (e.g., Allentown Caging Equipment, see Note 2). 6. Housing room with 12-h light/dark cycle, maintained at 21°C. 7. Hopper to provide high-fat diet, or appropriate container if using an alternative diet (see Notes 4 and 5).

358

N.M. Avena et al.

3. Methods 3.1. Sugar Bingeing

1. Acclimate rats to their home-cage environment for at least 5 days prior to the onset of the experiment. 2. Divide rats into experimental and control groups (at least n = 8–10 per group) of similar body weight (30, respectively, has occurred in many countries so rapidly and in so many age brackets that a purely genetic explanation of this “obesity epidemic” is untenable (2). Preclinical models, in which a high degree of genetic and environmental control can be realized, offer important ways to tease apart the intricacies of the problem. The purpose of this chapter is to describe some of these animal models of overeating and obesity. Since rodents are by far the most frequently used and the most


367

368

N.E. Rowland

cost-effective laboratory animals, I restrict the discussion to rats and mice. Animal protocols must be approved by an Institutional Animal Care and Use Committee.

2. Materials This section focuses on three aspects. The first is choosing the type of animal that you will use. The second concerns the environment in which you will house the animal; this is an absolutely crucial aspect that is frequently overlooked by investigators. The third is a short discussion of some types of food that might be used and how to present them to your animals. 2.1. Rat or Mouse?

A mouse is not a small rat. The most common laboratory rats derive from Rattus norvegicus and laboratory mice derive from Mus musculus. Many inbred and outbred strains of these species are available from commercial suppliers. Your Laboratory Animal Resource staff and veterinarians will have a list of approved vendors. Unless there is a specific scientific reason for using a less common species or strain, it is recommended that you choose a species and strain that is common in your field of study so that your results can be easily interfaced with a larger body of published literature (see Note 1). Common outbred rat strains used in feeding research include Sprague-Dawley and Wistar. There are several genetic mutations in rats that are associated with an obese phenotype, the Zucker rat perhaps being the most popular (3). The C57BL/6 strain is the background for many transgenic studies, and they are prone to dietary obesity: most work emphasizes the critical interaction between genotype and diet (2–5). Spontaneous as well as targeted gene mutations in mice lead to marked obesity, including ob/ob, db/db, Ay, MC4R−/−. Unfortunately, mice are notoriously “messy” eaters, their meals are typically less well-defined than in rats, and their small physical size make some physiological studies considerably more challenging (see Note 2).

2.2. The Environment

The environment has a profound impact on energy expenditure, and indirectly affects food intake or body composition. Important aspects include ambient temperature, presence of nesting or bedding material, and level of activity allowed by the cage (e.g., size or exercise devices). The first two of these affect the rate of energy lost as heat from the body. There is considerable variation between facilities, but this variance can be minimized by providing animals a cage made from a poor thermal conductor (e.g., polycarbonate “shoe box” cages) and containing sufficient bedding/nesting material that they can create their own microclimate. Some facilities

24

Animal Models of Overeating

369

provide ventilated racks, but forced air flow creates an unnatural home environment and microclimate for rodents (see Note 3). Exercise can be provided either with a formal device allowing quantification, running wheels being the most common, or in the form of a large cage with enrichment, such as ladders and tubes. It is particularly important that the methods sections of published papers include all of these potentially relevant details. Most mice and rats are nocturnal species, and when a 12:12 light–dark cycle is provided (the most common situation), they eat 60–90% of their food at night when they are awake and active. The common strains of rats and mice are not markedly photoperiodic, so small changes in the light cycle including use of natural lighting should give similar results (see Note 4). 2.3. Food Presentation and Measurement

The choice of food is critical to any experiment involving food intake or energy balance. There are five principal properties of food that should be considered: 1. Texture – For example, liquid, soft, hard, powder, pellet. Harder and larger pellets require more effort gnawing, handling, and chewing than most other forms. 2. Taste or flavor – Rodents, like humans, find sweet and fat tastes to be pleasant and bitter tastes unpleasant. To produce overeating, a palatable diet is essential. 3. Variety – Although it is simplest and most common to provide a single food, providing a variety of palatable foods often stimulates overeating. 4. Nutrient density – Energy yield per gram of food or per mouthful. High fat diets are high in energy density; diets with high water content have low energy density. 5. Nutrient composition – Unless a study involves dietary selection or creation of a deficiency, a diet should be nutritionally complete, including adequate vitamins, minerals, and balanced protein appropriate to the species and age.

2.4. Water Requirement

Water is required for lubrication and digestion of food, and to offset obligatory body water loss, so clean and fresh water should be available regularly, preferably at all times. Either deliberate or inadvertent reduction of water availability or quality will lead to dehydration anorexia (see Note 5).

2.5. Pelleted Food

Pelleted food is most usually presented in hoppers, either in the roof or inside the cage. The animals then gnaw at the food but are unable to grasp it in their paws. True intake is hard to assess because crumbs and spillage can be quite high, is quite variable between individuals, and is essentially impossible to measure if crumbs drop into bedding. Diets can be presented inside the cage, for example

370

N.E. Rowland

in jars, and the animals can handle these foods, but pelleted or powdered food can easily be removed or spilled unless antispill rings are used to essentially prevent the use of the paws (see Note 6). The most accurate measurements can be made using semisolid diets (e.g., moist chow or shortening, which animals can remove with their paws and then lick them clean) or liquid diets which are contained in graduated cylinders with sipper spouts (cautions from Note 5, apply again here). In all of the above cases, the amount consumed is simply a subtraction of initial and final weights or volumes. Intake should be corrected for spillage and, if appropriate, evaporative loss. A 1% accuracy of these measurements is sufficient for most purposes. Intake also can be measured by electronic devices, most of which have the food (or fluid) cup attached to a load cell which sends a continuous signal to a data acquisition system. Provided that the subject neither leans on nor spills from these cups, these provide accurate time-stamped records of when food is removed. The food or fluid has to be in a form (e.g., powder, liquid) that cannot be removed and hoarded, and in this case removal of food is tightly related to consumption. An alternative way of measuring food intake is to have the animal perform a response to obtain a morsel of food or fluid. For example, rodents can be housed in operant behavior chambers and press a lever (the operant) to obtain a small food pellet. Most rodents do not accumulate food pellets under these conditions, so obtaining a pellet is followed closely by consumption, and the timing and number of pellets taken can be recorded precisely by a computer.

3. Methods The choice of a feeding protocol depends largely upon the experimental question. There are two basic types of protocol, ad libitum feeding and time-limited or “binge” access. As its name suggests, an ad libitum protocol gives the animal continuous access to one or more foods and may be associated with the development of obesity, depending on the food(s) available. In a time-limited or binge access protocol, animals have a bland food all the time and in addition short access (e.g., 0–5–2 h/day) to a highly favored or palatable food. This produces a very large meal (the so-called binge). However, animals often reduce their intake of maintenance food over the rest of the 24 h so that little or no excess body weight gain occurs (see Note 7). 3.1. Ad Libitum Protocols: DietInduced Obesity

Most laboratory rodents are provided with continuous access to nutritionally complete and relatively low-fat chow. Chows are made from natural ingredients and typically have ~10% digestible

24


371

energy from fat, ~20% protein, with the balance from complex carbohydrates. They have what is normally considered to be a bland taste and this often is the “control” condition in a study of induced obesity. The rate of weight gain and development of adiposity can be markedly accelerated (diet-induced obesity (DIO)) from the chow condition by providing ad libitum access to an energy dense and/ or varied diet for several weeks (5). A high fat diet is often used, although many highly palatable diets are suitable. Several such diets, typically 45–60% digestible energy as fat, are available from commercial suppliers and have the advantage of being from purified components and similar in protein, vitamin, and salt content as a control or low fat diet. Some strains of rodents are more susceptible to DIO than others (6), and this trait may be selectively bred (2, 5). Typically, one group of animals is exposed to the high fat diet for 6–10 weeks and gains ~25% body weight relative to a control group that is maintained on low fat or chow diet. Longer exposures may be used, but the greatest relative weight gains occur in the first few weeks. Varied or cafeteria or “junk food” diets can also be used to promote obesity (7–9). Food items are often relatively high in fat (e.g., cheese) and presented concurrently, but the weakness is that different individuals make different choices, so introducing uncontrolled or unwanted variance. Further, the various foods most likely differ in macronutrient content and/or protein-to-calorie ratio, so there is no simple or ideally matched control diet protocol. One type of choice protocol gives animals chow plus ad lib access to concentrated sugar solution (10). Under these conditions, the sugar calories seem to overwhelm the internal regulatory mechanisms, animals do not compensate by reducing chow intake, so they gain weight. This has obvious relevance to human consumption of caloric beverages. 3.2. Limited Time or Binge Protocols

Binge eating in humans denotes a state in which eating is “out of control.” Several animal models have been developed that allow for a large food intake in a relatively short period of time, although whether that behavior should be considered out of control is debatable; rodents are incapable of vomiting or purging. These models all use a highly desirable or palatable food to induce robust intake, and the animals normally have a standard diet (chow) available at other times. In most but not all cases chow intake is reduced to compensate accurately for energy consumed during the binge (11–13). One of the apparently critical features of these protocols is that the food for bingeing should be presented in a temporally consistent and therefore predictable manner. Table 1 lists the diets that have been used most commonly in limited time protocols. Animals may take 5–10 days to adapt to these diets (i.e., for intakes to reach stable levels). Thereafter, intakes

Typical formulation

1 Part chow:1 part water

1 Part chow:1 part sweet condensed milk

Supermarket brand (any)

1 Part shortening:1 part sugar

Commercial “treat”

Commercial liquid diet

1 Part sugar:1 part dry milk, in water

Sucrose or glucose

Diet

Moist chow

Chow-milk

Shortening

Sugar-fat diet

Crunchies®

Ensure®

Sweet milk

Sugar solutions

2 mm) to allow effortless licking. We have found that spouts with valves, including ball bearings and some commercial lick recorder spouts can cause significant difficulties for some animals and should be avoided. Curved spouts can develop airlocks unless they are in a vertical orientation. This can be a particular problem when presented overhead through the grill lid of shoebox cages and straight spouts are strongly recommended for this type of cage. If you find that one animal in a group is eating less than the others, the first thing you should check is their water access. 6. Some antispill devices are available commercially. One inexpensive solution for lab do-it-yourself types is to use glass powder jars as the food containers; these are cheap and available in several sizes from lab suppliers and come with plastic screw tops. Then, cut a circular hole (~3 cm diameter) in each lid using a hole-saw bit on a standard electric drill. 7. Animals do not recognize weekends. Most feeding protocols are not suited to a weekend hiatus because that may “undo” what has been accomplished during the regular working week. Instead, staffing should be planned to run these studies 7 days a week, as far as possible on the same schedule. 8. Many studies in this field of study try to allow animals to determine their own meal sizes by providing food that is not preportioned. It is possible, however, that providing food in discrete units (portions) that are “paw-sized” but not as large as a single meal could produce “quantal” eating, much as occurs in humans whose portion sizes are often preselected.

24


375

9. Timing is everything. Animals often show locomotor activity that is anticipatory of a regular feeding, such as a palatable food. Thus, omission of a treat (see Note 7) is not a neutral event for the animal. In this regard, we have recent (unpublished) evidence that mice decrease their intake of bland food in anticipation of a treat. References 1. Kaye, W. (2008) Neurobiology of anorexia and bulimia nervosa. Physiol. Behav. 94, 121–35. 2. Levin, B.E. (2010) Developmental gene x environment interactions affecting systems regulating energy homeostasis and obesity. Front. Neuroendocrinol. 31, 270–83. 3. Aleixandre de Artiñano A., Miguel Castro M. (2009). Experimental rat models to study the metabolic syndrome. Br. J. Nutr. 102, 1246–53. 4. Speakman J., Hambly C., Mitchell S., Król E. (2008). The contribution of animal models to the study of obesity. Lab Animal 42, 413–32. 5. Levin, B.E., Dunn-Meynell, A.A. (2002). Defense of body weight depends on dietary composition and palatability in rats with dietinduced obesity. Am J Physiol Regulat Integ Comp Physiol 282, R46–54. 6. West D.B., Waguespack J., McCollister S. (1995). Dietary obesity in the mouse: interaction of strain with diet composition. Am J Physiol Regulat Integ Comp Physiol 268, R658–65. 7. Rothwell, N.J., Stock, M.J. (1988). The cafeteria diet as a tool for studies of thermogenesis. J Nutr. 118, 925–928. 8. Bayol, S.A., Simbi, B.H., Bertrand, J.A., Strickland, N.C. (2008). Offspring from mothers fed a “junk food” diet in pregnancy and lactation exhibit exacerbated adiposity that is more pronounced in females. J Physiol. 586, 3219–30. 9. Ackroff, K., Bonacchi, K., Magee, M., Yiin, Y-M., Graves, J.V., Sclafani, A. (2007). Obesity by choice revisted: effects of food availability, flavor variety and nutrient composition on energy intake. Physiol Behav 92, 468–78.

10. Sclafani, A., Vigorito, M., Pfeiffer, C.L. (1988). Starch-induced overeating and overweight in rats: influence of starch type and form. Physiol Behav 42, 409–15. 11. Mathes, C.M., Ferrara, M., Rowland, N.E. (2008). Cannabinoid-1 receptor antagonists reduce caloric intake by decreasing palatable food selection in a novel dessert protocol in female rats. Am J Physiol Regulat Integ Comp Physiol 295, R67–75. 12. Levin, B.E. (1994). Diet cycling and age alter weight gain and insulin levels in rats. Am J Physiol Regulat Integ Comp Physiol 267, R527–35. 13. Corwin, R.L., Buda-Levin, A,. (2004). Behavioral models of binge-type eating. Physiol Behav 82, 123–30. 14. Rowland, N.E., Robertson, K.L. (2005). Effect of two types of environmental enrichment for singly housed mice on food intake and weight gain. Lab Animal 34, 29–32. 15. Zheng, H., Shin, A.C., Lenard, N.R., Townsend, R.L., Patterson, L.M., Sigalet, D.L., Berthoud, H.R. (2009). Meal patterns, satiety, and food choice in a rat model of Rouxen-Y gastric bypass surgery. Am J Physiol Regulat Integ Comp Physiol 297, R1273–82. 16. Rowland, N.E., Mukherjee, M., Robertson, K. (2001). Effects of the cannabinoid receptor antagonist SR141716, alone and in combination with dexfenfluramine or naloxone, on food intake in rats. Psychopharmacology 159, 111–6. 17. Glendinning J.I., Breinager L., Kyrillou E., Lacuna K., Rocha R., Sclafani A. (2010). Differential effects of sucrose and fructose on dietary obesity in four mouse strains. Physiol Behav 101, 331–43.

sdfsdf

Chapter 25 The Activity-Based Anorexia Mouse Model Stephanie J. Klenotich and Stephanie C. Dulawa Abstract Animals housed with running wheels and subjected to daily food restriction show paradoxical reductions in food intake and increases in running wheel activity. This phenomenon, known as activity-based anorexia (ABA), leads to marked reductions in body weight that can ultimately lead to death. Recently, ABA has been proposed as a model of anorexia nervosa (AN). AN affects about 8 per 100,000 females and has the highest mortality rate among all psychiatric illnesses. Given the reductions in quality of life, high mortality rate, and the lack of pharmacological treatments for AN, a better understanding of the mechanisms underlying AN-like behavior is greatly needed. This chapter provides basic guidelines for conducting ABA experiments using mice. The ABA mouse model provides an important tool for investigating the neurobiological underpinnings of AN-like behavior and identifying novel treatments. Key words: Activity-based anorexia, Hyperactivity, Anorexia nervosa, Animal model, Mice, Food restriction

1. Introduction 1.1. Activity-Based Anorexia

In 1953, Hall and Hanford observed that rats housed with running wheels and subjected to restricted food access for 1 h a day had significant decreases in body weight and food intake, and a paradoxical increase in running wheel activity (1). Conversely, rats given running wheels and food ad libitum, or food restricted rats housed without running wheels, were able to maintain a normal body weight (1–3). This model of “self-starvation,” later coined the activity-based anorexia (ABA) model, consistently produces rapid decreases in body weight and food intake, hyperactivity, hypothermia, loss of estrus, increases in HPA axis activity, and leads to stomach ulceration and eventually death (2–5). The ABA phenomenon has been observed in many other species besides the rat, such as the hamster, gerbil, guinea pig, chipmunk, pig, and mouse, indicating that ABA behavior is highly conserved across mammalian species (6–9).


377

378

S.J. Klenotich and S.C. Dulawa

The mechanisms that underlie ABA behavior are generally unknown. Nevertheless, several theories have been proposed to explain this paradoxical behavior. During ABA, animals present with a significant drop in body temperature, a symptom also observed in patients with anorexia nervosa (AN). Lambert suggests that hyperactivity develops to counteract the drop in body temperature that arises when animals fail to adjust to food restriction (1993) (10). ABA has also been suggested to result from autoaddiction to endogenous opiods. This theory posits that dysregulation of the opiod system renders hyperactivity and selfstarvation behaviors addictive (11). Another intriguing explanation of ABA behavior comes from the “adapted to flee famine” hypothesis which suggests that hyperactivity and denial of starvation reflect an adaptive mechanism that facilitates migration in response to famine (12). Although each theory presents intriguing arguments to explain ABA behavior, none may fully explain the phenomenon. These theories may not prove to be mutually exclusive, and these processes may work in concert in the development of ABA. 1.2. Anorexia Nervosa

Anorexia nervosa is an eating disorder that affects approximately 0.5–1.0% of females during their lifetime and affects about one tenth of as many males (13). The lifetime mortality rate for AN is approximately 10%, which represents the highest mortality rate of all psychiatric illnesses (14). AN often onsets around midadolescence and is characterized by an refusal to maintain a healthy weight, strong pursuit of thinness despite being underweight, fear of weight gain, preoccupation with food and body shape, and inappropriate assessment of body size. Patients usually have disruption of their menstrual cycle, or amenorrhea, and signs of hypometabolism (13). Moreover, patients often exhibit hyperactivity, which can manifest as extreme exercise or as a general restlessness (15, 16). Patients also have hypercortisolism and increases in corticotrophin-releasing hormone (CRH) in their cerebral spinal fluid (CSF), indicating an overactive hypothalamic-pituitary-adrenal (HPA) response during illness (17, 18). AN is highly comorbid with anxiety disorders. Patients often have one or more anxiety disorders in their lifetime, most commonly obsessive-compulsive disorder or social phobia. Onset of anxiety disorders usually precedes the onset of AN (19). Overall, patients often present with signs of perfectionism, distractibility, obsessionality, anxiety, and compulsivity, which are usually present before AN diagnosis and worsen with illness (13, 19). AN is often a chronic illness with a high rate of relapse (13, 20). About 30–50% of patients relapse within a year of weightrestoration (21, 22). Currently, treatment of AN remains highly limited. Patients show variable improvement following various psychological interventions including cognitive-behavioral therapy,

25

The Activity-Based Anorexia Mouse Model

379

interpersonal therapy, behavioral programs, and family-based therapy (13, 23–26). There are currently no approved pharmacological treatments for AN, although studies examining the effects of the selective serotonin reuptake inhibitor (SSRI) fluoxetine (27, 28) have produced conflicting results. However, recent studies assessing the potential utility of the atypical antipsychotic olanzapine have been promising (29). Considering the high mortality rate associated with AN, studies aimed at identifying potential treatments and the neurobiology underlying this severe disorder are critically needed. 1.3. Utility of an ABA Mouse Model

Since the sequencing of the mouse genome and the widespread availability of numerous inbred strains, the use of mouse models in all facets of basic research has become commonplace. Mice are easily bred, handled, and housed, and their genome can be manipulated to develop knockout or transgenic mice which allow for the study of single genes and their roles in normal or disease processes. The experimental conditions required to assess ABA (discussed further below) require carefully selected experimental and control groups and specialized equipment. The ABA model is a useful tool for studying aspects of AN-like behavior.

1.4. Validity of Animal Modeling When Employing ABA

Developing and using animal models of psychiatric disorders is inherently difficult due to the complex nature of these illnesses. Although a mouse model that recapitulates all of the symptoms a disorder is intuitively appealing, modeling an entire syndrome is practically impossible and also unnecessary for the model to be useful (30). Modeling specific aspects of a disorder can provide insight into the pathophysiology of the disorder and indentify potential treatments. The ABA model has been proposed to provide a model for several aspects of AN, including hyperactivity, selfstarvation, weight loss, amenorrhea, hypothermia, and increased HPA axis activity. Animal models should exhibit predictive validity for the disorder they are intended to model to justify their initial use. That is, the animal model should make accurate predictions about the human phenomenon of interest. Specifically, variables that influence the disorder should influence the dependent variable in a similar fashion. For example, pharmacological treatments that are effective in treating the disorder should also modify the expression of dependent measures (30). Thus, any potential treatments for AN identified in the clinic should also reduce ABA, and vice versa. The ABA model exhibits predictive validity for some aspects of AN in that adolescent mice and rats are more vulnerable to ABA than older rodents ((31–34); unpublished results). Furthermore, female rats and mice are more vulnerable to ABA than male rodents ((35); Fig. 1). Thus, the ABA model can be used as a preclinical tool for studying AN-like behavior.

380


Fig. 1. Sex differences in ABA in Balb/cJ. (a) Cumulative survival of male and female Balbc/J mice during ABA (p = 0.0293, Breslow test). Survival represents time until mouse was removed from ABA (dropout) due to loss of 25% of baseline body weight. (b) Body weight during food restriction before dropout. (c) Food intake during restriction before dropout. (d) Running wheel activity before dropout. N = 30 (15 male, 15 female) Balb/cJ mice.

2. Materials Setting up the ABA mouse model in the lab involves choosing the most appropriate equipment, mouse strain, route of drug administration (if applicable) and experimental design given the aims of the study and the resources of the lab. To date, very few studies have examined ABA using mice (9, 36–39). Here, we present basic guidelines for assessing ABA in mice and provide some of our own experimental results. 2.1. Selecting Mice 2.1.1. Gender

1. To date, most experiments performed using mice have used females, since AN is about ten times more prevalent in girls. 2. Normally, female rats run significantly more than males and reduce their food intake during estrus (40–42). During ABA, female rats continue to run more than males (34, 35). Female rats also eat more than males during ABA, and therefore, females have been reported to be more resistant to ABA in some studies (35). By contrast, some evidence indicates that females are more at risk than males (43), or that no sex difference exists (34).

25


381

3. We recently conducted a study examining the effects of sex on ABA. We used both male and female mice 8–10 weeks of age on a Balb/cJ background. We found that female mice were more vulnerable to ABA, and showed significantly fewer days to lose 25% of initial bodyweight (Fig. 1). Additionally, females lost more weight (p < 0.0001) than male mice even though they did not differ in food intake. Although statistically insignificant, female mice also showed increased running wheel activity in comparison to male mice (p = 0.20). 4. The use of female mice for ABA experiments may more accurately model the clinical epidemiology of AN, allowing inferences to be drawn more readily from mice to humans. Several mouse strains (discussed further below) are commercially available (Harlan Laboratories, Charles River, The Jackson Laboratory). 2.1.2. Age

1. Younger rats are more vulnerable to the ABA paradigm, exhibiting more rapid weight loss than adult rats (31–34). The smaller size of younger animals may contribute to their increased susceptibility to ABA, as rats with higher initial body weights are less susceptible to ABA behavior (44, 45). 2. Younger rats exhibit more running wheel activity during ABA in comparison to older rats (33, 34). 3. Although younger rats are more susceptible to ABA, they also recover from ABA faster in terms of body weight (34). 4. Recently, we have observed the same phenomenon in mice aged 4–6 weeks (our unpublished findings). 5. Since AN onsets in mid-adolescence, the use of adolescent mice in the ABA model may more accurately model AN. Given the accelerated manner in which younger rodents develop ABA, the experimental design of the ABA paradigm can be adjusted to reduce the rate at which young animals progress (see Note 1).

2.1.3. Strain

1. The large number of strains commercially available (Harlan Laboratories, Charles River, The Jackson Laboratory) for laboratory use vary widely in their vulnerability to ABA. The hypothesis being tested should be considered when selecting a strain to work with. 2. Selecting a strain with high ABA is desirable when testing compounds hypothesized to reduce ABA. Furthermore, using a strain that develops high ABA levels may better model AN in humans than strains that are more resistant to ABA. 3. Choosing a strain with intermediate levels of ABA may be desirable when examining the effects of a manipulation, whether pharmacological or genetic, which might either increase or reduce ABA.

382


4. One may compare strains that vary in ABA levels to investigate potential genetic differences underlying this phenomenon. 5. The C57BL/6J inbred mouse strain is relatively resistant to the developing ABA, and does not exhibit the significant increases in running wheel activity that DBA/2J (9), A/J (37, 38), and Balbc/J mice exhibit. C57BL/6J mice also tend to eat more than DBA/2J mice during ABA (9). 6. Vulnerability to ABA may correlate with anxiety levels in inbred mouse strains, since Balbc/J mice are known to be quite anxious (46), while C57BL6/J mice show low levels of anxiety (9). 7. An anxious strain may be desirable to use for ABA studies, since AN patients often exhibit increased anxiety even before the onset of the disorder (13, 19). Therefore, using a naturally anxious mouse strain in ABA could more closely model the human disorder. 8. Initially comparing several mouse strains for their vulnerability to ABA can be useful to identify an optimal strain for further use. 2.2. Housing and Equipment 2.2.1. Caging

1. During ABA, mice should be housed in cages that will be spacious enough to include access to a running wheel, food containers, and water bottles. Depending on the equipment chosen, ABA can easily be performed in standard facility mouse cages (Thoren Caging, Inc., Tecniplast, Allentown, Inc., Animal Care Systems, Inc., Columbus Instruments) (Fig. 2). 2. Normally, mice are housed in groups. However, when conducting ABA studies, individual housing is necessary for individual running wheel activity and food intake measurements to be recorded. Interestingly, there is conflicting evidence as to

Fig. 2. Equipment setup for ABA in standard mouse housing (a) Overhead and side (b) view of cage with wheel (Med Associates, Inc.), food jar and water bottle for singly housed mouse.

25


383

whether group housing rats reduces ABA behavior (34, 45), or exacerbates it (47). 3. The temperature at which animals are housed can also effect the development of ABA. It has been shown that increasing the ambient temperature (32°C) during ABA lowers running wheel activity, increases body weight and food intake, even after rats had reached a 20% drop in initial body weight (48). In the same respect, rats given access to a warm plate during ABA reduced running wheel activity and body weight loss in rats (49). Moreover, rats subjected to ABA in cooler temperatures (19.4°C) had reduced survival rates in comparison to those housed at warmer temperatures (25°C) (50). 4. It is important to choose the ambient temperature at which mice will be exposed to ABA with respect to desired outcome and maintain a consistent temperature to avoid variable results. 2.2.2. Running Wheels

1. A running wheel system should be chosen based on how the investigator intends to record activity (i.e., manually, automatically), the system requirements, and how the animals will be housed with wheels. 2. Fortunately, there are several systems that can record 24 h running wheel activity without need for a human observer to manually tally revolutions. Cages with built in running wheels are commercially available, as are free running wheels which can be placed into standard facility caging (TSE Systems, Inc., Med Associates, Inc., Lafayette Instruments, Columbus Instruments, Tecniplast, Harvard Apparatus, IntelliBio). 3. Wheel systems with external hardware or wireless capabilities are ideal so that mice do not get caught up in equipment, chew wires, or have difficulty running in the space provided. 4. It is important to be able to easily clean and reuse wheels to avoid damage and increase the lifetime of the equipment. 5. The ability to lock wheels at any point during the experiment allows the investigator to regulate wheel access during certain periods of the day. Placing a locked wheel in the cage also creates a nonwheel control group that has the same home cage environment as animal with wheels.

2.2.3. Water Access

1. Water should be easily accessible and consistently available to mice during ABA. Mice can become dehydrated quite easily and significantly increase their drinking levels when they have access to a wheel (51). 2. Water intake can be variable during ABA, as rats drank significantly less water prior to food access and significantly more during food access (52). Others have found a general decrease in water intake during ABA (53).

384


3. Water intake may be a variable of interest and can be manipulated to investigate its effects on the development of ABA. When manipulating water availability during ABA, the investigator should follow guidelines outlined by animal care committees to avoid animal dehydration. 4. Overall, when choosing the caging and wheel apparatus for ABA studies, where and how water will fit into the setup should be considered. 5. We have found that smaller water bottles, which create more room in the cage for a running wheel, are more suited for ABA experiments (Thoren Caging, Inc.) (Fig. 2). 2.2.4. Food Presentation

1. Food can be provided in a small container or jar that the animal can easily fit into and eat within. This setup prevents the spillage of smaller pellets or powder into bedding (see Note 2) (Specialty Bottle, The Jar Store, LLC, SKS Bottle, U.S. Plastics Corp.). 2. The cage may have a specific compartment for food that can be blocked during restriction (Columbus Instruments, IntelliBio). 3. Animals should be acclimated to the method of food presentation before the experiment begins. 4. The type of food given to mice will also be an important consideration. For instance, rats given a sweet, high-fat diet show a reversal of weight loss and an increase in caloric intake during ABA in comparison to standard chow conditions, despite increases in running wheel activity (54). 5. Addition of sucrose, saccharin, or fat to standard chow does not significantly affect the development of ABA (54). 6. Administration of wet chow versus dry standard chow to rats during ABA ameliorated weight loss and increased food intake (52). Rats given wet chow never reached criterion for removal from ABA, whereas all rats given standard chow were removed by day 7. 7. Delivery of standard chow in pelleted or powered form did not affect survival (53) or food intake (47) in ABA. 8. Varying the type of food available during ABA could affect experimental outcome.

3. Methods 3.1. Experimental Design

The ABA model consists of a food restriction period in which animals have access to running wheels. Mice may be exposed to various manipulations including genetic, pharmacological, or

25


385

environmental manipulations. The dependent variables food intake, body weight, running wheel activity, and survival are monitored daily and compared between groups. Employing a carefully planned experimental design is key to obtaining results that address the questions of interest to the investigator. 3.1.1. Acclimation

1. Before beginning ABA, mice should be acclimated to the experimental equipment and single housing. 2. Typically, animals are given about 3 days to acclimate to single housing with a running wheel (9, 48, 55, 56). 3. Interestingly, acclimation to running wheels can also exacerbate subsequent ABA (33, 45).

3.1.2. Food Access

1. Mice can survive for several days when receiving 2–4 h of food access a day. The shorter the duration of food access, the more rapidly ABA will develop and advance (47, 48, 55). Therefore, increasing food access duration will allow animals to survive longer, and allow collection of more data points. 2. Typically, most mouse studies to date have used 2–4 h of food access during ABA ((9, 37–39); our unpublished data). 3. The time of day that animals receive food can affect the severity of ABA. Animals given food access in the light cycle develop ABA behavior much more quickly that those with access in the dark cycle (57). 4. Whether food is given at a fixed time or variable intervals does not affect the initiation of ABA, although presentation of food at irregular intervals does speed up its progression (58). 5. There are conflicting results regarding whether preadaptation to food restriction before wheel access reduces ABA behavior (47, 57, 59). 6. Duration and timing of food access should be chosen with the desired length of survival in mind. For example, to test the hypothesis that a particular drug treatment reduces ABA, a shorter food access period may be desired. However, to assess whether a particular genetic mutation worsens ABA, a longer food access period may be ideal.

3.1.3. Running Wheel Access

1. When running wheel activity increases during ABA, there is a significant increase in activity just prior to the feeding period (53, 57, 60) termed food anticipatory activity (FAA) (61). 2. FAA appears to play an important role in development of ABA, as denying access to wheel running during this time ameliorates ABA behavior (57). 3. Wheel access is an important variable to consider during experimental design and can affect the rate at which ABA develops (see Note 3).

386


3.1.4. Experimental Design: Independent Variables

There are several different independent variables that can be manipulated during an ABA experiment. Food restriction and the presence of a running wheel are both required to produce the ABA phenomenon, and both can be presented in a between-subject or within-subject fashion. 1. A within-subjects design, in which animals first receive food ad libitum and then have restricted access to food, decreases the number of mice and wheels needed and may also increase statistical power. 2. A between-subjects design in which separate groups receive food ad libitum or restricted access reduces the length of the experiment. 3. Other independent variables, such as drug treatments, are difficult to administer in a within-in subjects design and are usually presented in a between-subjects manner. 4. Choosing the appropriate experimental design for the independent variables of interest will depend on each individual variable, practicality, expense, and the animals and equipment available. Although many different experimental designs are possible, an experimental design we have used frequently is presented below as an example (Fig. 3).

3.1.5. Experimental Design: An Example

The present design uses both between- and within-subject factors to increase statistical power, and reduce the number of animals and wheels needed (Fig. 3a). Food access is manipulated in a withinsubjects fashion, with animals first receiving food ad libitum, and then receiving food under restricted conditions (2–4 h daily). Therefore, animals serve as their own internal control with respect to the effects of food restriction on food intake, running wheel activity levels, and body weight. Both wheel access and drug treatment are presented in a between-subjects manner. Thus, for each group with running wheels, there is a corresponding group without wheels. Groups without wheels provide a control for any effects of drug treatment on food intake or bodyweight in the absence of running. Drug treatments are often difficult to administer in a within-subjects design due to carry over effects and the often fast progression of ABA. This experimental design is executed through the protocol below (Fig. 3b): 1. Prior to acclimation, animals should receive any necessary drug pretreatment (if applicable) (see Subheading 3.2). 2. Begin acclimation by singly housing all animals. Animals in the wheel access groups should receive wheels at this time (unlocked). Administer food and water ad libitum. 3. After 3 days of single housing and wheel acclimation, obtain daily measurements of the dependent variables (body weight, food intake, running wheel activity) for 5–7 days (baseline

25


387

Fig. 3. ABA experimental design and timeline example. (a) Experimental design includes animals housed with and without wheels, with or without food restriction, and receiving control or treatment. This strategy employs a withinsubjects for food access conditions, and a between subjects design for wheel condition and treatment condition. (b) Experimental timeline for this design.

measurements). It is best to take these measurements all together, and at the time of day the investigator plans to manipulate food access during restriction to acclimate animals to being handled at this time. 4. Following baseline, begin daily food restriction, or the ABA period. Water is still given ad libitum. Continue taking daily measurements of the dependent variables until animals reach end point. 5. Once animals reach the chosen end point (see Subheading 3.1.6), recovery from ABA (see Subheading 3.1.7) can be evaluated. 3.1.6. Determining End Point

As stated above, mice exposed to food restriction and running wheels will increase their activity levels and decrease their food intake to until death occurs. In general, three signs of death are present 48 h prior to stomach ulceration and death (62). 1. There is a large drop in body weight, which levels off and drops dramatically again before death. 2. Food consumption initially increases day to day, but then drops off rapidly before death.

388


3. Running wheel activity increases very quickly in line with increases in food intake, but drops off dramatically 24 h before death. 4. Defining an end point at which the animals will be removed from ABA is ethically important to reduce suffering and/or examine recovery. Since mice and rats will develop stomach ulcers, and have a low rate of recovery after losing 30% of their initial body weight, most investigators choose to remove animals from ABA when they have lost 25% of their baseline body weight. On the other hand, human AN patients are typically diagnosed when they have lost 15% of their ideal body weight. 5. Regardless of the chosen end point, one should be selected to prevent animals from dying from ABA which is unnecessary and unethical. 3.1.7. Recovery

1. Most investigators define recovery as a return to a stable body weight once unlimited food access is reinstated (3, 57, 63). 2. In addition to weight gain, return of estrus is another sign of recovery (63). 3. Recovery after loss of 25% of initial baseline body weight can be variable, and some mice may not fully recover. 4. Some groups define recovery as a maintenance or increase in body weight during a consecutive 4-day period (3, 52, 53). 5. Recovery from ABA may be based on body weight, or on a predetermined amount of time that must pass before mice are considered “unrecovered.” 6. Locking or removing wheels during recovery will aid in increasing the rate of recovery.

3.2. Drug Treatment in ABA

The ABA model can be used to test potential drug treatments for AN. Furthermore, selective drugs can be used to dissect the neural substrates that modulate ABA. Drugs can be delivered to mice subjected to ABA via different routes of administration which have different advantages and disadvantages. 1. Many drugs can be dissolved in the drinking water. The concentration required to deliver a given dose is determined by measuring the bodyweight, and daily water intake of animals. Although this route of administration is noninvasive and delivers drug in a steady manner, drinking rates during baseline and the food restriction period can vary greatly and alter the target dose (see Note 4). 2. The administration of drug by daily injection ensures the accuracy of the dose delivered. However, some drugs have short half lives, and daily injection does not produce steady-state

25


389

levels for such drugs. Also, daily injections are invasive, and introduce stress into the experiment. Stress derived from manipulations outside of the ABA paradigm can confound results (see Note 5). 3. Osmotic minipumps allow for precise administration of drug that lasts up to several weeks. Delivery of drug via minipumps is relatively stress free following recovery from implantation. However, implantation of minipumps requires a minimally invasive surgery in which animals must be anesthetized. Therefore, animals will need to fully recover (2–3 days) before beginning experimentation. Certain drugs have poor longterm stability when dissolved, or require vehicles incompatible with pumps, and are better administered by injection or drinking water. 3.3. Statistical Analysis 3.3.1. Analysis of Variance

1. During baseline, group means obtained for the dependent measures body weight, food intake, or running wheel activity can be compared using standard repeated-measures analysis of variance (ANOVA), since these dependent measures will be gathered daily for each animal. 2. Repeated-measures ANOVA can also be applied to data collected during the restriction period, but before animals are removed from the experiment. 3. Standard repeated-measures ANOVA can handle a minimally unbalanced design in which few animals have dropped from the study, but the mixed effects model should be used to analyze data with several missing values (see Subheading 3.3.2).

3.3.2. Mixed Effects Model

1. The mixed effects model allows for a more complete analysis of dependent measures through the end of the experiment when all animals have reached end-point criterion. Animals will reach end point intermittently, thus creating datasets with several missing values. 2. The mixed effects model (or mixed ANOVA model) can compare subjects despite unbalanced datasets and is written as: y = Xb + Z g + e The model has both fixed effects parameters (β), random effects parameters (γ), and an error variable (ε) that all vary as a function of each particular case. 3. This model is a generalization of the standard linear model in which errors are permitted to exhibit correlation and nonconstant variability, which would violate assumptions made in standard ANOVA. For more information on this model, see Cnaan et al. (64).

390


3.3.3. Survival Analysis

1. Survival analysis is concerned with studying the time between entry into a study and a defined event. For example, survival analysis can compare the time it takes different groups of animals to reach end-point criteria (e.g., loss of 25% of initial body weight). 2. Kaplan-Meier is one type of survival analysis that can be used to assess group differences in time to dropout. Kaplan-Meier is appropriate when time is the only variable of interest, therefore if other covariates exist, the Cox regression may be more suited for analyses. 3. Kaplan-Meier survival analysis generally outputs results of three statistical comparisons, those being the Log rank test, the Breslow or Wilcoxon test, and the Tarone-Ware test, each of which weight the time points in a different manner. 4. The Log rank test compares equality of survival functions by giving each time point equal weight. 5. The Breslow test compares equality of survival functions by weighing time points with consideration of number of cases present at each time point, and is subject to making more type II errors. Figure 1 shows a typical output from this type of analysis. 6. The Tarone-Ware test compares equality of survival functions by weighing all time points by the square root of the number of cases at each time point and is considered a compromise between Log rank and the less conservative Breslow test.

3.4. Summary and Future Scope

ABA can be induced when mice housed with running wheels are subjected to daily food restriction. The subsequent hyperactivity, reduction in food intake, and extreme body weight loss that can lead to death closely mimics the symptoms of AN observed in humans. The ABA mouse models can be used to identify potential treatments for AN and elucidate the neural substrates of this disorder.

4. Notes 1. The severity of ABA behavior can be ameliorated, and the length of the experiment increased, by reducing running wheel access, or increasing the food access period. Conversely, ABA behavior will develop more severely and more quickly if running wheel access is increased and food access is decreased. 2. The measurement of food intake is often complicated by mice defecating and moving bedding into the food jar. Mice also chew food pellets into very small pieces or powder. We have found that using forceps and a small strainer to sift through the contents of the food jar makes removing bedding and fecal matter much easier, and allows for more accurate data collection.

25


391

3. In many ABA experiments, investigators lock the running wheels during the food access, preventing animals from running during this period. This may ameliorate the development of ABA, as wheel running will not compete with food intake. This procedure can be useful if the investigator wants to extend the time until end point, or increase the rate of recovery from ABA. Alternatively, allowing wheel access during the food access period allows the animal the choice to either run or eat. 4. Administering drugs via the drinking water offers many advantages, such as avoiding daily injections. Nonetheless, during ABA, water intake levels can fluctuate. Therefore, as water intake varies, the dose of the drug received will also fluctuate. Measuring daily water intake and adjusting the concentration of the drug is needed to maintain the desired dose, but can be labor intensive. 5. Using daily injections to administer a drug of interest can have unexpected effects. Certain drugs and vehicles can cause local irritation at the injection site, resulting in changes in behavior. Some drugs may also cause short-term sedation, which can interfere with both feeding and running behavior. If drug must be injected daily, the time of day of the injection should be carefully considered based on potential sedating or activating effects of the drug.

Acknowledgments The authors would like to thank Mariel P. Seiglie for her invaluable technical assistance and for her advice and comments on this manuscript. This work was supported by NIH Grant R01MH079424 and NIH Grant TG2GM07839. References 1. Hall JF, Smith K, Schnitzer SB, Hanford PV (1953) Elevation of activity level in the rat following transition from ad libitum to restricted feeding. J Comp Physiol Psychol 46:429–433. 2. Hall JF, Hanford PV (1954) Activity as a function of a restricted feeding schedule. J Comp Physiol Psychol 47:362–363. 3. Routtenberg A, Kuznesof AW (1967) Selfstarvation of rats living in activity wheels on a restricted feeding schedule. J Comp Physiol Psychol 64:414–421. 4. Epling WF, Pierce WD, Stefan LA (1981) Schedule-induced self-starvation. In: C.M. Bradshaw, E. Szabadi, and Lowe CF (Eds.),

Quantification of steady-state operant behavior (pp. 393–396). Amsterdam: North-Holland. 5. Burden VR, White BD, Dean RG, Martin RJ (1993) Activity of the hypothalamicpituitary-adrenal axis is elevated in rats with activity-based anorexia. J Nutr 123 :1217–1225. 6. Vincent GP, Pare WP (1976) Activity-stress ulcer in the rat, hamster, gerbil and guinea pig. Physiol Behav 16:557–560. 7. Vincent GP, Pare WP, Isom KE, Reeves JM (1977) Activity-stress gastric lesions in the chipmunk (Tanias striatus). Physiol Behav 5: 449–452.

392


8. Treasure JL, Owen JB (1997) Intriguing links between animal behavior and anorexia nervosa. Int J Eat Disord 21:307–311. 9. Gelegen C, Collier DA, Campbell IC, Oppelaar H, van den Heuvel J, Adan RA, Kas MJ (2007) Difference in susceptibility to activity-based anorexia in two inbred strains of mice. Eur Neuropsychopharmacol 17:199–205. 10. Lambert KG (1993) The activity-stress paradigm: possible mechanisms and applications. J Gen Psychol 120:21–32. 11. Marrazzi MA, Luby ED (1986) An auto-addiction opiod model of chronic anorexia nervosa. Int J Eat Disord 5:191–208. 12. Guisinger S (2003) Adapted to flee famine: adding an evolutionary perspective on anorexia nervosa. Psychol Rev 110:745–761. 13. Attia E Anorexia nervosa: current status and future directions. Annu Rev Med 61:425–435. 14. Birmingham CL, Su J, Hlynsky JA, Goldner EM, Gao M (2005) The mortality rate from anorexia nervosa. Int J Eat Disord 38:143–146. 15. Kron L, Katz JL, Gorzynski G, Weiner H (1978) Hyperactivity in anorexia nervosa: a fundamental clinical feature. Compr Psychiatry 19:433–440. 16. Hebebrand J, Exner C, Hebebrand K, Holtkamp C, Casper RC, Remschmidt H, HerpertzDahlmann B, Klingenspor M (2003) Hyperactivity in patients with anorexia nervosa and in semistarved rats: evidence for a pivotal role of hypoleptinemia. Physiol Behav 79:25–37. 17. Kaye WH, Gwirtsman HE, George DT, Ebert MH, Jimerson DC, Tomai TP, Chrousos GP, Gold PW (1987) Elevated cerebrospinal fluid levels of immunoreactive corticotropin-releasing hormone in anorexia nervosa: relation to state of nutrition, adrenal function, and intensity of depression. J Clin Endocrinol Metab 64:203–208. 18. Lawson EA, Klibanski A (2008) Endocrine abnormalities in anorexia nervosa. Nat Clin Pract Endocrinol Metab 4:407–414. 19. Kaye WH, Bulik CM, Thornton L, Barbarich N, Masters K (2004) Comorbidity of anxiety disorders with anorexia and bulimia nervosa. Am J Psychiatry 161:2215–2221. 20. Pike KM (1998) Long-term course of anorexia nervosa: response, relapse, remission, and recovery. Clin Psychol Rev 18:447–475. 21. Carter JC, Blackmore E, Sutandar-Pinnock K, Woodside DB (2004) Relapse in anorexia nervosa: a survival analysis. Psychol Med 34:671–679. 22. Guarda AS (2008) Treatment of anorexia nervosa: insights and obstacles. Physiol Behav 94:113–120.

23. Fisher CA, Hetrick SE, Rushford N Family therapy for anorexia nervosa. Cochrane Database Syst Rev 4:CD004780. 24. Murphy R, Straebler S, Cooper Z, Fairburn CG (2010) Cognitive behavioral therapy for eating disorders. Psychiatr Clin North Am 33:611–627. 25. Bulik CM, Berkman ND, Brownley KA, Sedway JA, Lohr KN (2007) Anorexia nervosa treatment: a systematic review of randomized controlled trials. Int J Eat Disord 40:310–320. 26. Lock J, Agras WS, Bryson S, Kraemer HC (2005) A comparison of short- and long-term family therapy for adolescent anorexia nervosa. J Am Acad Child Adolesc Psychiatry 44:632–639. 27. Walsh BT, Kaplan AS, Attia E, Olmsted M, Parides M, Carter JC, Pike KM, Devlin MJ, Woodside B, Roberto CA, Rockert W (2006) Fluoxetine after weight restoration in anorexia nervosa: a randomized controlled trial. JAMA 295:2605–2612. 28. Kaye WH, Nagata T, Weltzin TE, Hsu LK, Sokol MS, McConaha C, Plotnicov KH, Weise J, Deep D (2001) Double-blind placebo-controlled administration of fluoxetine in restricting- and restricting-purging-type anorexia nervosa. Biol Psychiatry 49:644–652. 29. Bissada H, Tasca GA, Barber AM, Bradwejn J (2008) Olanzapine in the treatment of low body weight and obsessive thinking in women with anorexia nervosa: a randomized, doubleblind, placebo-controlled trial. Am J Psychiatry 165:1281–1288. 30. Geyer M, Markou A (1995). Animal models of psychiatric disorders. In: Bloom F, Kupfer D (Eds.), Psychopharmacology: The Fourth Generation of Progress. Raven Press: New York. pp 787–798. 31. Doerries LE (1996) Gender differences in activity anorexia: Predictable, paradoxical or enigmatic? In: Epling WF, Pierce WD (Eds.), Activity anorexia: Theory, research, and treatment Mahwah, NJ: Erlbaum. pp 69–77. 32. Woods DJ, Routtenberg A (1971) “Selfstarvation” in activity wheels: developmental and chlorpromazine interactions. J Comp Physiol Psychol 76:84–93. 33. Pare WP (1975) The influence of food consumption and running activity on the activity-stress ulcer in the rat. Am J Dig Dis 20:262–273. 34. Boakes RA, Mills KJ, Single JP (1999) Sex differences in the relationship between activity and weight loss in the rat. Behav Neurosci 113:1080–1089. 35. Doerries LE, Stanley EZ, Aravich PF (1991) Activity-based anorexia: relationship to gender and activity-stress ulcers. Physiol Behav 50:945–949.

25


36. Verhagen LA, Egecioglu E, Luijendijk MC, Hillebrand JJ, Adan RA, Dickson SL (2010) Acute and chronic suppression of the central ghrelin signaling system reveals a role in food anticipatory activity. Eur Neuropsychopharmacol 21:384–392. 37. Gelegen C, van den Heuvel J, Collier DA, Campbell IC, Oppelaar H, Hessel E, Kas MJ (2008) Dopaminergic and brain-derived neurotrophic factor signalling in inbred mice exposed to a restricted feeding schedule. Genes Brain Behav 7:552–559. 38. Gelegen C, Pjetri E, Campbell IC, Collier DA, Oppelaar H, Kas MJ (2010) Chromosomal mapping of excessive physical activity in mice in response to a restricted feeding schedule. Eur Neuropsychopharmacol 20:317–326. 39. Lewis DY, Brett RR (2010) Activity-based anorexia in C57/BL6 mice: Effects of the phytocannabinoid, big up tri, open(9)-tetrahydrocannabinol (THC) and the anandamide analogue, OMDM-2. Eur Neuropsychopharmacol 20:622–631. 40. Lambert KG, Kinsley CH (1993) Sex differences and gonadal hormones influence susceptibility to the activity-stress paradigm. Physiol Behav 53:1085–1090. 41. Finger FW (1969) Estrus and general activity in the rat. J Comp Physiol Psychol 68:461–466. 42. Blaustein JD, Wade GN (1976) Ovarian influences on the meal patterns of female rats. Physiol Behav 17:201–208. 43. Pare WP, Vincent GP, Isom KE, Reeves JM (1978) Sex differences and incidence of activitystress ulcers in the rat. Psychol Rep 43:591–594. 44. Persons JE, Stephan FK, Bays ME (1993) Dietinduced obesity attenuates anticipation of food access in rats. Physiol Behav 54:55–64. 45. Boakes RA, Dwyer DM (1997) Weight loss in rats produced by running: effects of prior experience and individual housing. Q J Exp Psychol B 50:129–148. 46. Belzung C, Griebel G (2001) Measuring normal and pathological anxiety-like behaviour in mice: a review. Behav Brain Res 125:141–149. 47. Pare WP, Vincent GP, Natelson BH (1985) Daily feeding schedule and housing on incidence of activity-stress ulcer. Physiol Behav 34:423–429. 48. Gutierrez E, Cerrato M, Carrera O, Vazquez R (2008) Heat reversal of activity-based anorexia: implications for the treatment of anorexia nervosa. Int J Eat Disord 41:594–601. 49. Hillebrand JJ, de Rijke CE, Brakkee JH, Kas MJ, Adan RA (2005) Voluntary access to a warm plate reduces hyperactivity in activitybased anorexia. Physiol Behav 85:151–157.

393

50. Gutierrez E, Vazquez R, Boakes RA (2002) Activity-based anorexia: ambient temperature has been a neglected factor. Psychon Bull Rev 9:239–249. 51. Lambert KG, Peacock LJ (1989) Feeding regime affects activity-stress ulcer production. Physiol Behav 46:743–746. 52. Boakes RA, Juraskova I (2001) The role of drinking in the suppression of food intake by recent activity. Behav Neurosci 115:718–730. 53. Beneke WM, Schulte SE, vander Tuig JG (1995) An analysis of excessive running in the development of activity anorexia. Physiol Behav 58:451–457. 54. Brown AJ, Avena NM, Hoebel BG (2008) A high-fat diet prevents and reverses the development of activity-based anorexia in rats. Int J Eat Disord 41:383–389. 55. Watanabe K, Hara C, Ogawa N (1992) Feeding conditions and estrous cycle of female rats under the activity-stress procedure from aspects of anorexia nervosa. Physiol Behav 51: 827–832. 56. Routtenberg A (1968) “Self-starvation” of rats living in activity wheels: adaptation effects. J Comp Physiol Psychol 66:234–238. 57. Dwyer DM, Boakes RA (1997) Activity-based anorexia in rats as failure to adapt to a feeding schedule. Behav Neurosci 111:195–205. 58. Perez-Padilla A, Magalhaes P, Pellon R (2010) The effects of food presentation at regular or irregular times on the development of activitybased anorexia in rats. Behav Processes 84:541–545. 59. Lett BT, Grant VL, Smith JF, Koh MT (2001) Preadaptation to the feeding schedule does not eliminate activity-based anorexia in rats. Q J Exp Psychol B 54:193–199. 60. Holmes MM, Mistlberger RE (2000) Food anticipatory activity and photic entrainment in food-restricted BALB/c mice. Physiol Behav 68:655–666. 61. Mistlberger RE (1994) Circadian foodanticipatory activity: formal models and physiological mechanisms. Neurosci Biobehav Rev 18:171–195. 62. Pare WP (1980) Psychological studies of stress ulcer in the rat. Brain Res Bull 5 Suppl 1:73–79. 63. Dixon DP, Ackert AM, Eckel LA (2003) Development of, and recovery from, activitybased anorexia in female rats. Physiol Behav 80:273–279. 64. Cnaan A, Laird NM, Slasor P (1997) Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data. Stat Med 16:2349–2380.

sdfsdf

Part V Biomarkers, Neuroendocrine and Inflammatory Profiles Relevant to Neuropsychiatric Disorders

sdfsdf

Chapter 26 Dissociating Behavioral, Autonomic, and Neuroendocrine Effects of Androgen Steroids in Animal Models Amy S. Kohtz and Cheryl A. Frye Abstract Developments in behavioral assessment, autonomic and/or baseline reactivity, psychopharmacology, and genetics, have contributed significantly to the assessment of performance-enhancing drugs in animal models. Particular classes of steroid hormones: androgenic steroids are of interest. Anecdotally, the performance enhancing effects of androgens are attributed to anabolic events. However, there is a discrepancy between anecdotal evidence and investigative data. While some androgen steroids may promote muscle growth (myogenesis), effects of androgens on performance enhancement are not always seen. Indeed, some effects of androgens on performance may be attributable to their psychological and cardiovascular effects. As such, we consider androgen effects in terms of their behavioral, autonomic, and neuroendocrine components. Techniques are discussed in this chapter, some of which are well established, while others have been more recently developed to study androgen action. Androgens may be considered for their positive impact, negative consequence, or psychotropic properties. Thus, this review aims to elucidate some of the effects and/or mechanisms of androgens on behavioral, autonomic, and/or neuroendocrine assessment that may underlie their controversial performance enhancing effects. Key words: Androgen, Anabolic-steroid, Performance enhancement, Affect, Cognition, Myogenesis, Animal model

1. Introduction 1.1. Androgens and Their Pleiotropic Effects

Androgenic steroids, such as testosterone (T), have pleiotropic effects on physiological and behavioral functions across the lifespan. Classically, androgen action is centralized around its influences on male reproduction, gonadal function, and growth. Androgens are observed in adulthood, as they continue to influence behavioral/ psychological processes, such as drive, cognitive functions, and mood, which can be considered positive (neurotropic) or negative (1). Androgens can also alter autonomic functioning, and may have physiological effects, which influence muscle mass, strength, and can be myogenic (muscle growth) or myolytic (muscle


397

398

A.S. Kohtz and C.A. Frye

breakdown). Some of these effects may be mediated by underlying neuroendocrine milieu, which may change and develop across the lifespan, with peaks and troughs brought on by life events. As such, androgens exert diverse and biphasic effects on the brain and body to alter behavioral, autonomic, and/or neuroendocrine processes. These dissociations are important, as strength and myogenesis are features that androgens enhance; however, we need to consider that the physiological effects of androgens are influenced by the psychological effects, in that drive and mood are enhanced, which may influence endurance. It is important to understand performance as a function of tropic events in both the body and brain. Thus, this chapter discusses these three major implications of androgens, and methodologies used to dissociate their effects. 1.2. Androgens During Development

First, it is important to understand the implications of androgens across the lifespan, as changes in androgens across the male lifespan can be indicative of peaks and troughs which subsequently alter many psychological and physiological milestones males experience. During early developmental events, androgens are primarily responsible for the growth and development of the male reproductive system. Activation and expression of the Y chromosome gene, SRY, stimulates androgen production during sexual differentiation, resulting in formation of the testes. Androgens produced by the testes, perinatally serves to masculinize external and internal reproductive structures, as well as the brain. Peripubertally, androgens mitigate body weight and height (2), as well as bone strength (3). Of note, dysregulation of androgens peripubertally has been linked to type-1 diabetes (4). During puberty, androgens promote germ cell differentiation into sperm, a process called spermatogenesis. Spermatogenesis remains an androgen-dependent function across the lifespan of males. Adipose, or fat tissue, is also decreased by androgens, via a recently identified mechanism. Activation of androgen receptors (ARs) inhibits Wnt signaling, thereby inhibiting adipogenesis (5). Similarly, signal transduction through initial AR activation may increase muscle growth (6). Androgens reach their peak levels during young adulthood and then decline decadeby-decade until reaching nadir typically in the eighth decade. Agerelated androgen decline is associated with muscle wasting effects. Thus, androgens influence physiology of males across the lifespan, by developing the reproductive system, increasing weight and height, and bone strength, while decreasing adipose tissues. Androgens exert both positive, and negative, psychological effects across the lifespan. There are gender differences in childhood mood, wherein activity and mood may be influenced by endogenous androgen levels. Male children, who have higher androgen levels, exhibit higher activity and increased happiness, compared to female children (7). Lowered androgen levels have been implicated in some aspects of the onset and incidence of pervasive developmental

26

Androgen Steroids in Animal Models

399

disorders (8, 9). Among adolescents, high levels of androgens have been linked to increased incidence of conduct disorder among girls and boys (10, 11). During adulthood, androgen levels mitigate sexual desire and aggression among adult men (12–14). Among aging men with androgen levels reaching nadir, low levels of T are associated with decrements in cognitive and affective behaviors, as well as sleep perturbations (15). T replacement therapy can be used to improve spatial and working memory, as well as mood, among men with low endogenous androgen levels (16–18). Among hypogonadal men, who have had lower androgen levels across the lifespan, there is an increased incidence of mood disorders, which can be improved by androgen replacement therapy (19–21). Thus, androgens increase positive psychological functions, such as activity, happiness, mood, and cognition, but also increase negative psychological functions, such as conduct disorder and aggression. This chapter aims to discuss effects of androgens, broken down into their psychological effects, physiological effects, and then their neuroendocrine and underlying mechanisms. However, it is important to keep in mind that androgens’ effects are not only diverse, but also controversial in that they may exert positive, negative, or psychotropic effects. As such, this chapter begins by discussing behavioral phenotypes associated with androgens. Historically, physiological effects of androgens have been a large preponderance of their use. As such, the second topic in this chapter assesses effects of androgens on autonomic and physiological function. Third, we discuss neuroendocrine sequelae, as well as methods used to manipulate neuroendocrine sequelae, which have provided evidence for underlying mechanisms involved in androgens psychological and physiological effects. The goal of this chapter is to discuss the discrepancies between the perspectives, and actually investigate findings on androgen use and their varied effects. How sex differences and/or endogenous variations in androgens mediate these processes, how removal of the primary endogenous sources of androgens (the testes) abrogates such effects, and how androgen administration can alter these functions are all discussed. The next section discusses behavioral effects and methodologies of androgen’s effects on affective, cognitive, sexual, aggressive, and reward behaviors. 1.3. Behavioral Effects of Androgens

There are multifaceted behavioral effects of androgens that may influence their performance-enhancing qualities. Androgens may act to increase positive mood and cognition, but also increase aggressive behaviors, while altering the response to drugs of abuse. Behavioral effects of androgens can also vary based on variables including, but not limited to, sex/gender, age, species, and administration paradigm. This section aims to discuss some of these effects, broken down into positive (affect, cognition), negative (aggression), and rewarding/psychotropic (mating, drugs of abuse)

400


behaviors. There is a large body of literature that suggests there are sex differences in positive and negative psychologies, as well as the response to reward and/or drugs of abuse. For example, women, who have lower androgen levels, tend to have higher incidences of mood disorders (anxiety, depression) compared to men, and may respond differently to treatment options (22, 23). There are gender differences in cognitive behaviors, which suggest androgens may influence spatial cognition (24–26). In addition, sex/gender differences suggest women may be more susceptible to psychotropic effects of drugs of abuse (27, 28). Many behavioral tasks can be utilized to assess outcome measures of mood, affect, cognition, mating, and aggression, in rodent models. These measures are also individually sensitive to androgen milieu. Thus, this section aims to differentiate between behavioral phenotypes, which are relevant to androgen replacement therapies, and anabolic–androgenic steroid (AAS) use, and discuss how these behaviors may be influenced by androgen milieu. 1.4. Androgens and Affective States

Data from animal models suggest that androgens may exert positive, neurotropic effects on affect and mood. In rodent models, gonadectomizing (GDX), or removing the primary source of androgens, can be used to manipulate androgens, and alters affective states and response to antidepressants. Our laboratory has seen that fluoxetine (an antidepressant), decreases depressive-like behaviors among intact, but not GDX, male rats (see Fig. 1). Administration of T, or dianabol (a synthetic variant), can reduce anxiety-like behavior, and reverse the negative effects of GDX on anxiety (29–31). Of interest, studies from aged male rodents, suggest that the metabolism of T to 3α-Diol may be important for promoting positive affective states, by reducing anxiety-like and depressive behaviors (32). Thus, androgens may be positive mediators of affective states, which may influence motivational/drive aspects of performance. 1. Elevated plus maze (EPM) measures anxiety-like behaviors in rodent models (33). The EPM is a plus-shaped, elevated maze. It comprisesof two “closed arms,” which are safety zones with walls, opposite two “open arms,” which have no walls. Rats are placed in the center of the maze and the duration of open and closed arm time and entries to arms is measured. This test can measure exploratory and emergence behaviors. Androgens tend to increase exploration and incidence of open arm emergence in the EPM, indicative of anti-anxiety-like effects (34–39). In addition, this phenomenon has been observed under both acute (40) and chronic (41) administration paradigms, across species (37, 38). Thus, androgens can exert antianxiety-like behaviors utilizing this task.

26


401

Fig. 1. Time spent immobile in the forced swim task, indicative of depressive behavior, depicted as a percentage of vehicle administered controls. Male rats were gonadectomized, or sham-surgerized, and administered vehicle, 2.0 mg/kg 3α-Diol, or Fluoxetine, and assessed for depressive-like behaviors in the forced swim task.

2. Porsolts forced swim task (FST) is used to determine depressivelike behaviors in rodent models (42). Rodents are placed in a cylindrical tube they cannot escape or stand in, filled with room temperature water. Time spent struggling (paddling toward the walls) to escape the chamber and swimming (diving, exploration) is recorded. Time spent immobile (floating) is considered an index of depression-like behavior in rodents. Administration of androgen metabolites, but not T, to aged male rats can decrease depressive-like behaviors in the FST (32). However, in younger males, T administration is capable of reducing depressive-like behaviors (43). These data suggest that changes in androgen metabolism across the lifespan may influence depressive-like behaviors among male rats, making age a considerable factor in utilizing this test. 1.5. Androgens and Cognitive Functioning

Data from animal models suggest that androgen steroids exert positive effects on cognition, which may be involved in some of their performance-enhancing qualities. First, there are sex differences in cognitive behaviors of both people and rodents. Men (and male rodents compared to females) typically perform better on spatially oriented cognitive tasks, whereas women tend to perform

402


better on verbally oriented tasks (24–26, 44, 45). Cognitive deficits associated with trisome disorders, appear to be more severe in those with extra female (XXX, XXY), rather than male typical (XYY), chromosomes (46). Second, the removal of endogenous androgens in males reduces performance on cognitive and affective tasks. GDX to male rodents decreases performance on cognitive tasks (47). Third, administering androgens to GDX rodents can reinstate performance to that of intact rodents (30, 47, 48). Systemic, nonaromatizable DHT and 3α-Diol can enhance cognition of GDX rats (31, 39, 47, 49–55). Fourth, androgens may be neuroprotective against age-related cognitive disorders through inhibiting amyloid neuropathies (56). Age-related reductions in brain T are associated with higher incidence/more severe Alzheimer’s-related neuropathologies. As well, higher brain T corresponded to decreased beta-amyloid (57) and administration of T or DHT attenuated beta-amyloid-induced cell death (58). In addition, reduction of AR expression among men and women may increase risk for Alzheimer’s Disease (59). These data suggest that androgens can modulate cognitive performance of intact and/or neurally compromised individuals. Thus, androgens exert positive, neurotropic effects on cognition, which may modulate some of androgens positive performance enhancing qualities. 1. The Morris water maze is a behavioral assay used to assess measures of spatial memory in rodents (60). The Morris water maze utilizes the rodent’s drive to escape water. The apparatus consists of a deep pool of water and a platform located just below the surface. The maze is divided into four quadrants, which can be readily explored by the test subject. Rodents are placed in a quadrant of the water maze and trained to find a hidden platform. The following day, latency to find the hidden platform is recorded as a measure of spatial memory. Androgens may have actions to increase performance in the Morris water maze task (32, 36). Sex differences favor male rodents in performance on the Morris water maze task, such that male rats can have lower latencies to find the hidden platform than do female rats (61). In addition, GDX to male rodents can reduce cognitive performance, and reinstatement of androgen metabolites can ameliorate the negative effects of GDX (32). Thus, androgens may play an integral role in escape-driven cognitive behavior. 2. The object recognition/placement tasks are used to measure spatial memory in rodents primarily based on rodent’s investigation of novelty (62–64). The object recognition/placement apparatus consists of a white, brightly lit open field arena with two identical objects for training (e.g., plastic cones, cylinders, round, or blocks). For testing, one object is switched out for a new object of a different shape (object recognition), or one of

26


403

the objects is moved to the opposite side of the apparatus (object placement). Time spent with the novel, or the moved object, is indicative of spatial memory performance. Administration of androgens or their metabolites can improve performance on these tasks (31, 37, 38). Thus, androgens may play a role in novelty-driven cognitive behavior. 1.6. Androgens and Aggression/ Mating Behaviors

AAS use has been associated with changes in aggression (irritability, anger, violent rages) and may have diverse effects on sexual performance (increased libido and/or erectile dysfunction) in people (65, 66). Among rodents, studies also suggest that androgens modulate aggressive and copulatory behavior (67–69). In support, there are gender differences in aggression, wherein men are more aggressive than women (70). Among rodents, prenatal androgenization increases aggression (71), circulating androgen levels positively correlate with aggression (16) and sex differences in aggression are attenuated by GDX. Similarly, prenatal androgenization can produce male typical mating behaviors in females (72), circulating androgen levels are positively correlated to mating behaviors in male rats (36), and mating can be attenuated by GDX (see Fig. 2). Use of T’s synthetic variants, may also exert effects on androgen-dependent behaviors. Under short-term use in a placebo controlled study, men administered methyltestosterone experienced increases in irritability, violent feelings, and hostility (73). AAS users in relationships report higher incidences of verbal and physical aggression while using AAS versus when they do not use (74). AAS use can enhance sexual desire and pleasure in people (75–77); however, prolonged use and/or withdrawal may result in negative sexual effects, such as decreased testicular weight and erectile dysfunction (78, 79). Thus, androgens influence aggression, and are necessary, among men and male rodents, for sexual function. 1. The resident-intruder task is used to measure aggressive behaviors by inducing a territorial dispute (80). There are many different forms of aggression, classified as predatory, intermale, fearinduced, irritable, and maternal (81). The resident-intruder paradigm, utilizes a male typical behavior, to examine intermale aggressive behaviors. The testing animal is socially isolated for a period of time, prior to testing. On testing day, a novel conspecific is introduced to the test-animals’ homecage, and vocalizations, bites, posture, tail rattling, and body contacts are recorded. Aggressive behaviors can be reduced by GDX in male rats, and reinstated with testosterone administration (82). Increased androgen levels increases aggressive behaviors in the resident–intruder paradigm (83, 84). Of interest, administering androgens to females can increase aggression toward a conspecific; however, this effect is less robust in females than it is in

404


Fig. 2. Rats were intact, gonadectomized (GDX), or GDX and administered testosterone (T). Gonadectomy to male rats reduces sexual function, measured by average frequencies of mounts and intromissions. Reinstatement of circulating testosterone levels, by silastic implant, can ameliorate some of the effects of gonadectomy. Asterisk indicates significant difference from intact male rats.

males (85). Thus, androgen steroids may modulate aggressive behaviors, which are contraindicated with performanceenhancing effects of androgens. 2. Mating is a behavioral measure of interest, as it is both facilitated by, and facilitates, steroid production. Steroid hormones are necessary for mating behaviors to occur in both male and female rodents. For males, latency to, and frequency of, mounts and intromissions, as well as latency to ejaculation are measured as indices of sexual performance. Sexual performance correlates strongly to endogenous androgen concentrations, among males (86). Reinstatement of androgens, or androgen metabolites, to castrated male rats, can reinstate sexual behavior (87, 88). However, engagement in mating among male rodents is highly dependent on whether or not animals are sexually naïve, which may indicate a reciprocal effect of mating–androgen concentrations. Thus, mating influences, and is influenced by androgen steroids. Mating and aggression are both behavioral

26


405

phenotypes that are positively modulated by androgen steroids. With AAS use, there is increased incidence of aggression, and libido may be heightened in some cases. Aggression, however, is contraindicated, to the performance-enhancing properties of androgen steroids. As both mating and aggression can induce reward-like states, or neurobiological changes which are indicative of hedonia, it is important to address hedonia states with respect to androgens. In the next section, we discuss how androgens can alter reward states, and how this is relevant for satisfying biological drives, as well as the implications of androgens in reward during mating and aggression.

2. Androgen Steroids in Hedonic and Reward States

Androgens can enhance, produce, and are secreted during, reward states. Reward states are obtained through satisfying basic biological drives, such as eating, sex, exercise, or positive social stimulation. There is evidence that androgen steroids may mediate aspects of satiety and feeding behaviors. Among male rodents, serum T is increased in response to feeding after periods of food restriction (89). Removal of endogenous androgens in male rodents via GDX can decrease food intake and alter meal size and frequencies (90). However, low T levels are associated with obesity in men (91), suggesting that decreasing androgens in males results in diverging qualities of dysfunction. Administration of T to GDX rodents can reinstate normal feeding behaviors (92). In addition to feeding behaviors, androgenic steroids are integral for male mating behaviors. Serum T is increased in response to mating, and GDX can completely abolish sexual behaviors of male rodents (36). Endogenous androgens play a role in the positive effects of exercise. Among men and male rodents, exercise can result in a significant increase in serum T levels (93). In addition, salivary T is positively correlated to sensation-seeking behaviors among men (94), and T can elicit both a conditioned place preference (CPP) and can be self-administered, among male rodents (54, 55, 95, 96). Thus, androgens may modulate some aspects of reward. Reward states can also be obtained through neural stimulation of the reward circuit, which is how many drugs of abuse are thought to act. Male rodents which “win” territorial disputes have increased AR expression in the ventral tegmental area (VTA) and nucleus accumbens (NAc; 97). Engaging in either aggression or mating may increase mesolimbic dopamine firing (98), a process occurring concomitant with reward and/or administration of drugs of abuse (99). Infusions of T directly to the NAc can condition a place preference (CPP), which is blocked by dopamine receptor antagonists (100), but administration of T does not enhance dopamine in the NAc

406


(101). These data suggest that androgen influences on reward states vary, and may occur through multiple downstream mechanisms. 1. CPP is a procedure used to assess rewarding behaviors and/or learning of rats (55). One side of the chamber is striped, and the other is a solid color. Each chamber can be divided into two equal halves by means of a Plexiglass partition painted with the appropriate stimulus for each side. In our hands, each chamber is suspended in a sound- and light-attenuating container by means of an axel system that allows the chamber to pivot and therefore tip when the animal places the majority of its weight on one side. The location of the animal in the chamber is monitored by a microswitch system (55). Rats are habituated for 2 days and baseline preferences are assessed on the third day. Then, rats are conditioned to their nonpreferred side. On Day 16, rats are tested for their preference. Spending more time in the nonpreferred side of the chamber indicate a CPP. Androgens can induce a CPP, whether administered centrally or peripherally (96). Of interest, CPP has been used to dissociate some effects of androgens. Androgens have a variety of mechanisms by which they exert their effects, and some of the sites of action may have salient reward functions associated with them (96). These mechanisms are discussed later in this review.

3. Androgens May Alter, and Be Altered by, Drugs of Abuse

Androgens, as well as their synthetic counterparts, AAS, may alter and influence hedonia, and as such are implicated as controlled or abused substances. AAS are used both for their performanceenhancing qualities, and may have addictive and/or hedonic qualities which influence their subsequent use. As such, AAS can be a mechanism to study exogenous androgen administration in people. Self-reported changes in mood, behavior, and somatic perception have been associated with AAS use (65, 66, 76). AAS reportedly can produce euphorogenic (positive hedonic) effects, similar to those of drugs of abuse. Of interest, both AAS administration and drugs of abuse alter synthesis of T and its neurosteroid metabolite, 3α-Diol, in the brain (29, 31). T and dianabol increase 3α-Diol levels (29–31). Indeed, like other drugs of abuse, prolonged AAS use can result in dependence, and tolerance (102, 103), and abusers may also often experience stimulant-like withdrawal symptoms, characterized by depressive symptoms. In rodent models, rats can be made to be physically dependent upon AAS (104). These data suggest that androgens and AAS may have hedonic and withdrawal effects similar to that of other drugs of abuse. Of interest, there is evidence that drugs of abuse are influenced by androgens as well. In animal models, drugs of abuse can be used to produce extreme neuroendocrine states, which subsequently influence autonomic

26


407

and behavioral responses. In particular, the methodologies for this section discuss utilizing cocaine and alcohol (EtOH) to alter neuroendocrine states, and thus behavior. 1. Cocaine is a stimulant drug of abuse with salient reward qualities. Cocaine in particular, may alter, and be altered by, endogenous steroids. Primarily, there are sex differences in the response to cocaine, wherein females tend to be more susceptible to the addictive and interoceptive effects of cocaine, than are males. Indeed, testosterone alters cocaine-induced psychomotor behaviors, and sensitivity to the cocaine response (105). However, little data to date examines the role of androgen metabolites in the response to cocaine. Our previous findings, suggested that progesterone and its metabolites, are altered with cocaine administration (106), concomitant with changes in progestogen-dependent behaviors. Our more recent findings suggest that, likewise, T and its metabolites, concomitant with changes in androgen-dependent behaviors, may be altered by cocaine (Fig. 3). Cocaine can be used as a stimulant drug of

Fig. 3. Intact male rats were administered vehicle or cocaine at 5, 10, or 20 mg/kg, prior to 30 min habituation and 15 min of sex testing. Steroid and behavioral data are represented at a percentage of saline administered vehicle controls. Cortex and hypothalamus 3α-Diol were increased at all doses, whereas cortex T was decreased, and hypothalamus T at 20 mg/ kg was increased. Sexual function among all males was decreased in response to cocaine. Asterisk indicates significant difference from vehicle.

408


Fig. 4. Intact male rats were singly-housed for 3 weeks and administered saline vehicle or alcohol (EtOH) at 0.5, 1.0, or 2.0 g/kg, 30 min prior to introduction of a smaller, intruder rat into their home cage. Prefrontal cortex concentrations of T (left ) were reduced, but concentrations of 3α-Diol were increased (middle ), dose-dependently with EtOH administration coincident with enhanced aggression (right ). Asterisk indicates significant difference from vehicle.

abuse to exacerbate some effects of androgens. Examining the behavioral outcomes that result from cocaine-induced increases in bio-available androgens, may elucidate some stimulant mechanisms by which androgens produce hedonic outcomes. 2. Alcohol (EtOH) is a depressant drug of abuse with salient reward qualities. Similar to androgen metabolites, EtOH is a positive allosteric modulator of GABA receptor complexes. EtOH’s actions at GABA have been linked to its aggressioninducing properties (107, 108). Susceptibility to aggressive behaviors while using EtOH has been linked to endogenous steroid concentrations (Fig. 4). EtOH can be used as a depressant drug of abuse to exacerbate some effects of androgens. Like cocaine, EtOH is a hedonic substance. Unlike cocaine, EtOH is a depressant rather than a stimulant. As such, examining behavioral outcomes which may result from EtOH-induced changes in bio-available androgens may elucidate some depressant mechanisms of androgens.

26


409

Fig. 5. Intact male rats were administered vehicle or cocaine at 20 mg/kg, prior to autonomic measurement in the CODA meter. (Left ) Heart rate in beats per minute is shown at 0, 5, and 10 min after injection of cocaine or vehicle. (Right ) Mean blood pressure at 0, 5, and 10 min after injection of cocaine or vehicle. Squares represent vehicle administered groups. Xs represent 20 mg/kg cocaine administered groups. On right, black shapes represent systolic blood pressure, and white shapes represent diastolic blood pressure.

3.1. Summary

These data have discussed behavioral effects of androgens. Androgens can exert positive, neurotropic effects on the brain, increasing cognitive behaviors reducing negative effect, and may have neuroprotective qualities, among rodents. However, with androgen administration, there are also observed increases in aggressive behaviors, and androgens may have addictive qualities. Effects of androgens on some of the above described behaviors, such as mating, aggression, and addiction, may also have a peripheral component. For example, heart rates and blood pressure of male rodents are increased in response to cocaine administration (Fig. 5). In addition, there are extensive myogenic and cardiovascular effects of androgens, which are the primary proponents of their use. We have so far discussed psychological effects of androgens, which may be implicated in their performance-enhancing capabilities, in the following section; we address some of the peripheral effects of androgens.

410


4. Myogenic and Cardiovascular Effects of Androgen Steroids

4.1. Anabolic– Androgenic Steroids

Peripheral effects of androgens can be classified as being anabolic, catabolic, or androgenic. The anabolic effects of androgens include accelerated growth of muscle, bone, and red blood cells, and trophic actions in the brain. Catabolism involves the breakdown of proteins into smaller units, which then provide the energy necessary for anabolic processes. Cortisol, in people, corticosterone, in rats, and adrenaline, are hormones which mediate catabolic processes. During extensive training periods, combined with AAS use, competition for glucocorticoid receptors may cause “anti-catabolic” events, which promote muscle growth (109). However, repeated elevations of serum testosterone by AAS can result in decreased hypothalamic-pituitary-adrenal function, resulting in reduced testosterone production and spermatogenesis with extended use (110). Throughout the lifespan, male body structure develops by a series of anabolic and catabolic events to form the male body structure. This process may be mediated by androgen steroids. One way we can study these effects, is by examining the effects of nonphysiologically relevant levels of androgens (such as in AAS use), on body development. In addition, as AAS are used in the population for their performance-enhancing qualities, it is important to mention some of the varied effects they may have on the body and its functions. AAS are used by people for their performance-enhancing anabolic capabilities to increase strength and body function. Stanozolol, the AAS with the highest anabolic/androgenic ratio, can improve nitrogen balance among postoperative cancer patients (111, 112). After 3 weeks of use, dianabol, an AAS, can significantly increase strength, oxygen uptake, and nitrogen retention (113). In men, androstenedione ingestion can increase serum androstenedione and testosterone concentrations acutely, but not chronically (114, 115). Of interest, men 30–59 years of age exhibit increases in serum testosterone following chronic androstenedione administration (115). High doses of androstenedione in hypogonadal men, increases body mass, muscle strength, and serum testosterone (116). However, there are considerable health risks that have been associated with AAS abuse, which have been attributed to their androgenic and catabolic qualities (65, 77, 109). The masculinizing effects of AAS are particularly acute for women, among whom these traits may be irreversible, including facial hair, voice deepening, and male physique. Among adult men, AAS abuse increases the likelihood of prostate cancer, bone disease, kidney/liver damage, liver cancer, heart disease, and hypertension, occurring. It may also cause suppression of endogenous T production, gynecomastia, testicular atrophy, and decreased spermatogenesis.

26


411

Among adolescent males, AAS abuse hastens the onset of puberty, promotes early baldness, limit stature, and can cause premature growth plate closing. Many of these effects appear contraindicated, when compared to developmental effects of androgens across the lifespan. Thus, these data suggest that the effects of androgens to enhance performance may have negative side effects as well, which are less understood, and tend to appear with extended use. 4.2. Androgen Mediation of Cardiovascular Function

Androgens are known to exert a multitude of effects on cardiac function. Androgens may relax the aorta and coronary arteries, but may also induce vasoconstriction (117–120). Decrements in cardiac function are associated with GDX in male rodents, and can be attenuated by voluntary wheel running, which increases androgen biosynthesis (121). AAS users have impaired heart function, which includes smaller left ventricular dimension with thicker walls, impaired diastolic function, higher peak systolic strain rate, as well as degeneration of cardiac muscle fibers (122). In addition, Stanozolol is fibrinolytic, and can increase risk of myocardial infarction (111, 123) and DHEA can exert some of its ergogenic effects by decreasing body fat (124). Thus, androgens may mediate some aspects of cardiovascular functioning.

4.3. Activation of ARs Alter Myogenesis and PPAR Functions

Androgen steroids have actions to induce myogenesis, and decrease adipogenesis, via their actions at ARs. Androstenedione binds to ARs and upregulates MyoD protein in vitro, suggesting that androstenedione promotion of muscle cell growth may be through ARs (125). Activation of ARs by testosterone produces a subsequent cascade of signaling and transduction, which, in pluripotent muscle precursor cells, can increase expression of MyoD, decrease adipocytes, and inhibit peroxisome proliferators-activated receptor gamma (PPAR), allowing for increased muscle mass and decreased fat volume (5, 126). PPAR is necessary to modify lipid profiles; it suppresses inflammation, protects against hypertension, and can decrease blood pressure (127–130). In addition, PPARs may protect the brain, sex-specific tissues, endothelium, and heart, against ischemia and reperfusion injuries (131–134). These data are of interest because of the link between AR activation and cardiovascular disease. Thus, androgens may modulate autonomic and physiological processes via their actions at ARs.

4.4. In Vivo Model of Cardiovascular Baseline Reactivity

To date, noninvasive measurements of autonomic function in rodents have been difficult and/or unreliable. Recently, our laboratory has been a beta-test site for the Kent Scientific CODA noninvasive blood pressure monitoring system. As such, we have been able to pilot out methods in noninvasive autonomic function measurements. These data were of great interest to us, due to androgen’s influence on the cardiovascular system. One method in particular, is through the use of the CODA meter apparatus.

412


This comprises a holding chamber, tail cuff, and digital analyzer. The rat is placed in the holder. The holder is composed of clear acrylic, which allows the experimenter to view the rat at all times. The CODA holder is large enough to accommodate rats ranging from 100 to 950 g. Similar apparati exist for mice. Rats are not anesthetized, and their tail must extend through the rear hatch opening of the holder. A tail cuff is placed on the rat’s tail. This cuff temporarily occludes blood flow and then upon deflation the volume pressure recording mechanism takes a reading of the blood pressure, flow, volume, and heart rate of the mouse. The volume pressure recording remains the most reliable and accurate method to noninvasively measure vitals on a rat, with 99% correlation rating with other invasive techniques. After each animal the apparatus is cleaned with quatricide, the animal is returned to its home cage with ad libitum access to food and water. This method allows for recording of heart rate, blood pressure, blood flow, and blood volume. Thus, the CODA meter can be used to measure baseline reactivity, which can be indicative of cardiovascular health and can function as an indicator of the “endurance” factor, involved in the performance-enhancing effects of androgens. Our hypothesis was that administering testosterone (which has actions at ARs), or 3α-Diol (which has actions at GABAA receptors (GBRs), to intact male rats, will alter cardiac function. Blood pressure and heart rate were noninvasively measured by determining the tail blood volume with a volume pressure recording sensor and an occlusion tail-cuff (CODA System, Kent Scientific, Torrington, CT). Administration of testosterone yielded increased resting heart rate and decreased pulse pressure (the difference between systolic and diastolic blood pressure) after a single dose (Fig. 6). Interestingly,

Fig. 6. Intact male rats were administered vehicle, testosterone, 17β-Estradiol, or 3α-Diol, prior to autonomic measurement in the CODA meter. (Left ) Heart rate in beats per minute. (Middle ) Bars represent systolic blood pressure, dots represent diastolic blood pressure. (Right ) Mean pulse pressure is represented as a percent change from vehicle administered controls. Asterisk indicates significant differences from vehicle.

26


413

E2 decreased both systolic and diastolic blood pressures. 3α-Diol administration, as hypothesized, did not differ from vehicle on any cardiac measures. In addition, studies in TFM mice lacking a functional AR show reduced cardiac performance, which cannot be rescued with T administration (135). These data suggest that physiological anabolic effects of AAS should be through actions at ARs, and may be independent of 3α-Diol. 4.5. GABAA May Be a Substrate for Regulating Homeostatic Cardiac Function

5. Central and Neuroendocrine Mechanisms for Androgen Actions

5.1. The Androgen Receptor: A Brief Overview

Little data exists suggesting a role for androgen metabolites, such as 3α-Diol, in the physiological and/or autonomic effects of androgen steroids. Administration of muscimol (which acts at a 3α-Diol substrate, GABAA) can attenuate tachycardia produced by experimental stress (136, 137), and diazepam can reduce respiration. Among men, decreases in T due to prostate hyperplasia, aging, or hypogonadism, can increase risk for cardiovascular disease (138–140), possibly via reduction in therapeutic actions of 3α-Diol at GABAA. These data suggest that androgen metabolites may work via GABAA to regulate homeostatic cardiac function. Thus, GABA-modulated homeostatic function may be altered in AAS users, and may partially mediate performance enhancing aspects of androgens, such as endurance.

Androgens exert a plethora of positive and negative effects on behavior and physiology, as described above. In our laboratory, a question of interest is what are the mechanisms by which androgens are capable of dichotomous effects? In this section, we discuss the diversity of the AR, androgen metabolism, and actions of androgen substrates at nonandrogenic sites, as well as methodologies that have been used to dissociate these effects. The AR regulates gene transcription through binding of T, DHT, or their synthetic variants to ARs. It is encoded by a single gene, located on the X-chromosome. Like all nuclear steroid receptors, the AR is a zinc finger transcription factor (141), which allows it to bind to DNA. Binding of a ligand to an AR, AR dimerization, can result in rapid phosphorylation of heat shock protein 27 and 90 (Hsp27, Hsp90). Hsp90 is a chaperone, which alters the conformational structure of DNA-binding proteins (142). Hsp90, not only folds the AR-dimer, such that it can alter DNA, but may also allow for the AR-dimer to be transported from the cytosol into the cell nucleus (143). The AR-dimer binds to either general steroid, or specific androgen, hormone response elements (144), in the promoter region of the steroid-specific gene, to upregulate or

414


downregulate gene transcription. Promoters of cell cycle progression (Cyclin D1, PAK6; 145– 147 ) , sexual differentiation (SRY), co-repressors (HDACs; 148–150), and co-activators, may all be interactive targets for ARs. This process is considered to be strictly nuclear and genomic; however, there can be different actions of ARs, based on location within a cell, and cell type. Studies suggest that there may be extranuclear expression of ARs, including the cytosol (151), membrane (152–154), spine (155), glial cells (156, 157), and on the dendrites and axons of neurons (158). Thus, the diversity of AR signaling pathways may mitigate differences in androgen effects. 5.2. Intracellular ARs, a Substrate for the PerformanceEnhancing Effects of Androgens

Some of androgens’ performance-enhancing effects are mediated through intracellular ARs (159). ARs are widely, but selectively, distributed throughout the brain (160–163). In rats, the medial amygdaloid nucleus, mediating affect, and the hippocampus, mediating cognition, are brain regions rich in ARs (164, 165). GDX to male rodents increases anxiety-like behaviors, a manipulation reversible by T-replacement. Of interest, administering flutamide, an AR antagonist, can attenuate anxiolytic affects of T-replacement, in GDX male rodents (35). Similarly, intrahippocampal administration of flutamide can ameliorate cognitive-enhancing effects of DHTreplacement to GDX male rats (52). However, effects of androgens via ARs may be region, behavior, and life-stage dependent. Remodeling of spine synapses in the prefrontal cortex, but not hippocampus, may be dependent on ARs (166). In addition, administration of T may not reinstate cognitive and affective behaviors in aged male rats; however, will reverse effects of GDX in young male rats (32). These data suggest that actions of ARs are diverse.

5.3. Androgen Receptor Ligands or Selective AR Modulators

One question on the performance-enhancing qualities of androgens is whether or not their actions can be described as being through the AR, or through other substrates. There are many established methods to determine how androgens produce their effects, and ascertain whether these effects are through AR, or non-AR mechanisms. One way, is to examine activation of ARs. This can be done by administering androgen–receptor ligands, such as T or DHT, or a selective AR modulator (SARM) centrally or systemically. Co-administration of an AR ligand, and an aromatase inhibitor (formestane), and/or 5α-reductase inhibitor (finasteride) limits the ability of the androgen to metabolize, and thus blocks their downstream effects (167, 168). Among rodents, administration of finasteride (a 5α-reductase inhibitor), but not formestane (a 3α-hydroxysteroid dehydrogenase inhibitor), decreases prostate weight, both measures of trophic actions of AR activation (Fig. 7). Thus, pharmacological activation of androgens, through activating the AR via ligands, or inhibiting T’s metabolism

26


415

Fig. 7. Prostate weight, depicted as percent vehicle administered intact controls. Gonadectomy to male rats decreases prostate weights, a peripheral measure of androgen activity. Reinstatement by testosterone can ameliorate some effects of gonadectomy. Finasteride, a 5α-reductase inhibitor, but not formestane, an aromatase inhibitor, can decrease prostate weights in intact male rats. Asterisk indicates significant difference from vehicle administered intact male rats.

pathway and restricting its effects to ARs, can provide insight into the intricacies of androgen action. 5.4. Androgen Receptor Antagonism

A second method of examining effects of androgens, which may occur through substrates other than ARs, is to block activation of ARs. Blocking activation of ARs can be done systemically, or targeted to particular brain regions. Administration of steroidal, blocking agents such as spironolactone, cyproterone acetate, or trimethyltrienolone, or nonsteroidal, such as flutamide, bicalutamide, blocking agents, can attain this result (169–171). In addition, administration of progestins at high doses can also block AR activation (172). While inhibiting metabolism of androgens may increase actions at ARs, antagonism of ARs blocks actions specifically at ARs. Thus, AR antagonists can be specifically targeted to block androgen effects at ARs, while preserving effects at downstream substrates.

5.5. Androgen Receptor Knockdown

A third method for dissociating effects of ARs is through knockdown of AR genes or protein. Temporary knockdown of ARs can be obtained through the use of siRNAs and antisense oligonucleotides (ASODNs) (173, 174). Androgen insensitive mice or rats (TFMs), and androgen receptor knockout mice (ARKOs), have been utilized to study lifespan deficits in androgen activity. Thus,

416


AR knockdown provides a cleaner model than do pharmacological agents, to study post-abuse effects of AAS, wherein alterations of the AR may occur. 5.6. TesticularFeminized Mice (TFM; B6-Aw-J. Cg-EdaTa6J+/+ArTfm/J)

Testicular-feminizedmice (TFM; B6-Aw-J.Cg-EdaTa-6J+/+ArTfm/J) is a natural model of androgen-insensitivity, which involves a spontaneous mutation, similar to the androgen-insensitivity syndrome found in people. As the gene encoding for ARs is located on the X-chromosome, mutant TFMs affect only males, whereas females may only be carriers. Hemizygous males appear female, and male reproductive development leads to small testes and lack of accessory organs. TFM colonies exhibit tabby mutations (EdaTa), making wildtypes and knockouts individually identifiable by coat color. The TFM mouse provides a model in which lifetime deficits, similar to that of hypogonadal men, may be studied, thus providing a model to examine non-AR effects of androgens.

5.7. Androgen Receptor Knockout Mice (C57-B6/129/ SvEv loxP-floxed AR)

Unlike TFMs, ARKOs are not a natural model. Instead, ARKOs are a loxP-floxed mutant, and knockouts can be global, or tissue specific. Global ARKO males, similar to TFM males, are infertile and have a female-like appearance (175, 176). Of note, unlike TFMs, global AR knockout females can also be produced, and have similarly androgynous features. Thus, the ARKO mouse allows for conditional knockdown to occur at a chosen time point, in particular tissues, to examine effects of targeted decreases in androgen reactivity.

5.8. Androgen Metabolism

Androgens, and their synthetic variants, can be metabolized into simpler forms that have varied actions through receptors other than the AR. These metabolic events may account for some of androgens’ plethora of effects. Testosterone, and its synthetics, can be metabolized by 5α-reductase enzymes to form 5α-dihydrotestosterone (DHT; 177), which notably has a higher affinity for ARs than does T alone. T may also be metabolized by aromatase to form Estradiol (E2: 178–181), a process which is thought to account for some feminizing effects of AAS. The androgen metabolite, DHT, can also be further metabolized by 3α-hydroxysteroid dehydrogenase to form 3α-androstanediol (3α-Diol) or by 3β-hydroxysteroid dehydrogenase to form 3β-androstanediol (3β-Diol). 3α-Diol and 3β-Diol, unlike T and DHT, do not have intracellular actions via ARs. 3α-Diol can have affinity for neurotransmitter targets, GBRs (182). 3β-Diol has affinity for estrogen-receptor β (ERβ; 183). Of interest, some studies suggest that 3α-Diol may also have actions through ERβ to mediate behavioral and physiological effects of androgens (36, 69). As such, androgens are capable of having actions via multiple substrates; both genomic (ARs) and non-genomic (GBRs, ERβ), which may account for their varied effects. In our laboratory, a

26


417

topic of interest is the extent to which androgens actions in the body and/or brain occur via actions of metabolites or the parent hormone. 1. Hedonic effects of androgens may not occur via genomic substrates Androgens’ hedonic effects may be mediated in part by actions of its metabolites. Infusions of T and/or its metabolites can condition a place preference in rats, when applied to the NAc. AAS can act on the dopamine reward system in a manner similar to cocaine or other stimulants (102, 184–188). Despite widespread evidence of androgens’ hedonic effects, there is evidence that these effects may not be occurring through ARs. Evidence in support includes the following. First, hedonic effects of androgens do not correlate well with actions at ARs. T, its metabolites, and many AAS produce hedonic effects, but not all bind with a high affinity at traditional ARs (189, 190). TFMs and ARKOs will self-administer androgens, suggesting nuclear ARs are not necessary for hedonic effects of androgens (152). In addition, rewarding aspects of T may not only be through ARs, but also actions through estrogen receptors (ERs) (191). Second, androgens can mediate reward behaviors or have hedonic effects without the explicit use of ARs. There are few intracellular ARs in the NA (192); however, T may still have hedonic effects in the NA (54, 55, 95). DHT-BSA, which cannot permeate the membrane and is thus limited to nongenomic activation, will still be self-administered by male hamsters (193). Third, AR antagonists do not block all androgen-dependent behaviors. Co-administration of flutamide and androgens, fail to attenuate androgen-dependent sex behavior (194). As such, ARs may not be a putative substrate for hedonic effects of androgens. 2. GBR agonism and antagonism One nongenomic mechanism by which AAS may produce hedonic effects is through actions at GBRs. Androgens are capable of positively modulating GBRs (195). Steroids that have a 5α-reduced, 3α-hydroxylated structure are the most potent neuroactive steroids, and have biochemical actions similar to GBR agonists. In vitro, they rapidly inhibit tertbutylbicyclophosphorothionate (TBPS) binding to the GABA-operated chloride channel (195), potentiate GABA’s effects on chloride uptake (196), and increase flunitrazepam binding (195). AAS use and withdrawal parallel the effects of GBR agonist and antagonist steroids, respectively (73, 197). Administration of 3α-Diol or muscimol (a GBR agonist) can condition a place preference among rats. Administration of Bicuculline (a GBR antagonist) can ameliorate some effects of 3α-Diol to condition a place preference (Fig. 8; 96). Administration of androsterone

418


Fig. 8. Time spent in seconds on paired side in the conditioned place preference task depicted as a percentage of vehicle– vehicle administered controls. Higher values on this task are indicative of stronger conditioning, or stronger rewarding properties, of the experimental substance.

(GABA agonist) to GDX mice and rats decreases anxiety-like behavior (37, 38). Precisely where on GBRs androgens act is unclear, but like other modulators, they do not activate GBRs directly (196, 198), and instead alter actions of endogenous GABA. Of note, GABA action is altered by conditions that mimic AAS use and abuse (199, 200). As such, metabolites of T may account for some of the rewarding effects of androgens, through their actions at GBRs. 3. Androgen’s hedonic effects may be via its actions at ERs Some effects of androgens may be via ERs. Testosterone can be metabolized via aromatase, to estradiol (E2), which then exerts effects at ERs. In addition, the T metabolites, 3α-Diol and 3β-Diol, may also have actions at ERs, which may account for some observed interoceptive effects of androgens. E2 influences

26


419

responses to drugs of abuse among people and animals (reviewed in ref. 201). Studies suggest that 3β-Diol predominantly has actions as ERβ (183). However, there are two major subtypes of ERs (ERα and ERβ), where 3α-Diol could exert its effects (202, 203). There may be differences in ERs, wherein ERα may modulate peripheral activity, and reproductive function (204–208), whereas ERβ is a central modulator, of cell proliferation, and behavior (209). Our laboratory has previously demonstrated that cognition promoting effects of 3α-Diol replacement in GDX male rats can be attenuated by ERβ, but not ERα, knockdown by ASODNs in the hippocampus (36). Knockdown of ERβ via ASODNs administered intracerebroventricularly increases anxiety-like and depressive behaviors of rats (210). 3α-Diol administration to GDX male mice and rats ameliorates anxiogenic effects of GDX. In addition, among BERKO mice, 3α-Diol is ineffective at reducing anxiety-like behaviors (37, 38). Thus, 3α-Diol’s effects may be through its actions at ERβ. (a) Formestane Formestane can be used to inhibit aromatase. Testosterone, and many other androgens, may, via aromatization to estrogens (211) also stimulate estrogen receptors. Notably, the striatum and NA are concentrated with aromatase (212). Aromatization of androgens may represent an important metabolic event in hedonia. There are higher levels of aromatase in male, compared to female, pig brains (213), and aromatase is concentrated in the limbic system, with lower levels found in cortical regions (214). Aromatase inhibition by formestane decreases sociability and anxiety-like behaviors, concomitant with increases in 5α-reductase activity in the hippocampus and cortex of intact male rats, but not among T administered GDX males (Fig. 9). Of note, formestane is a drug used to treat some forms of hormone-related cancers. Many synthetic AAS are aromatizable (76), a quality responsible for gynecomastia. Formestane can be utilized in rodent models to determine effects of androgens through aromatization to E2. (b) Knockdown of ERb Our laboratory has previously demonstrated though the use of ASODNs specific for ERβ and ERα, that 3α-Diol may exert its effects through actions specifically at ERβ but not ERα (36). In addition, administering 3α-Diol or 3β-Diol to ERβ knock-out mice (BERKOs), does not attenuate effects GDX on anxiety-like behaviors (37, 38). Knockdown of specific substrates of androgen metabolites, such as ERβ is a method that can be used to dissociate some effects of androgens.

420


Fig. 9. Rats were intact, gonadectomized (GDX), or GDX administered testosterone, and administered formestane or vehicle silastic implants. Behavior and 5α-reductase activity depicted as percent vehicle administered intact male rats. Formestane decreased anxiety-like behavior in the elevated plus maze (higher scores are indicative of increased exploration), and decreased 5α-reductase activity in the hippocampus.

5.9. Nonandrogenic Actions of Synthetic Androgens

Effects of AAS are far from purely androgenic. Androgens, synthetic androgens, and their metabolites do not only bind to androgen or estrogen receptors, but also to mineralcorticoid, glucocorticoid, and progestin receptors (215). T can act as a combined agonist–antagonist of the progesterone receptor, and can downregulate progesterone receptor expression in the cytosol (216, 217). In addition, agonist actions of androgens on progesterone receptors may be greater among synthetic androgens compared to natural androgens (218). In vitro androgens may alter smooth muscle calcium sensitization in the presence of AR antagonists (219). These data, combined with data above regarding T metabolites, suggest the effects of AAS may involve actions at multiple genomic and nongenomic substrates.

26


421

6. Discussion This review aimed to elucidate some of the differences between anecdotal evidence of performance enhancing effects of androgen steroids, and their investigated effects. This chapter addressed some methodologies currently used to ascertain differences in behavioral phenotype, peripheral functionality, and neuroendocrine sequelae, as they relate to androgen steroids. Mediation of psychological processes, such as drive, cognition, and mood, has been addressed as a function of behavioral phenotype. Myogenic, myolytic, and cardiac function, have been assessed by baseline reactivity measurements of blood pressure and heart rate in animal models. Pharmacologic and genetic models have elucidated the substrates that may account for these diverse effects. Thus, androgens exert diverse and biphasic effects on the brain and body to alter behavioral, autonomic, and/or processes, of which there is a diverse body of methodologies for investigation. Assessment of affective, cognitive, and rewarding behaviors has provided data on how androgens influence psychological processes. Data utilizing the EPM and forced swim tasks, suggests that androgens may enhance affect, by decrease anxiety-like behaviors and depression among rodents (32, 34–39). Data utilizing the Morris water maze and object recognition/placement tasks suggest androgens and androgen replacement may also increase or reinstate cognitive performance, in rodents (31, 32, 36, 38). However, data utilizing the resident-intruder paradigm provides evidence that androgen may also play a role in aggression (83, 84). In addition, administering stimulant or depressive drugs of abuse produce diverse effects on androgens. Thus, these data suggest that androgen’s effects on psychological factors, such as mood, affect, and cognition, may influence the performance-enhancing qualities observed. Assessment of autonomic function, including cardiovascular and muscular enrichments, has furthered androgen studies. Data suggests that there are biphasic effects of androgens on the periphery. Studies examining effects of AAS suggest that while T may increase heart rate and vascular health; extended use of synthetic androgen variants may increase the risk for heart disease (65, 66, 76, 77, 119, 122). The CODA meter provides baseline reactivity data, which suggests T may also regulate homeostatic cardiac function. Thus, androgens classical anabolic effects have been addressed, as being either strength/muscle promoting, or endurance promoting, both of which are factors which influence androgens performance-enhancing qualities. Neuroendocrine effects of androgens, synthetics, and androgen metabolites, are diverse. There is evidence that T, and its synthetics, act at ARs, which can be nuclear, cytosolic, or membranic

422


(151–155), and that the structure and actions of ARs may be diverse (220). Conversely, T, or its synthetics, can be metabolized to estrogen, or metabolized to 3α- or 3β-Diol, to act at estrogen receptors, or act as GABA modulators (178–183). Pharmacological manipulations of androgen metabolism and action have elucidated substrates by which androgens may act. Use of AR ligands to activate ARs, androgen metabolism inhibitors to inactivate substrates other than ARs, or AR antagonists to inhibit actions at ARs, has allowed us to parse out effects of androgens, which occur at ARs. In addition, the use of genetics models has furthered this research, utilizing the AR insensitive, TFM, and conditional AR knockout, ARKO. Similarly, estrogenic actions of androgens have been assayed through the use of aromatase inhibitors and estrogen receptor ASODNs (36). Although not discussed extensively in this chapter, the prostate is a peripheral tissue of interest, of which its proliferation is heavily dependent on androgen action (See Fig. 7, for a brief review). There is diversity in the substrates by which androgens act, and a wide body of pharmacological and genetic manipulations, which may be used to assess these effects. Thus, tools available in the neuroendocrine sciences can allow for substrates to be identified, which may account for some of the psychological and physiological performance-enhancing effects of androgens. In summary, androgens may have performance-enhancing effects, which are complex in nature, and are not necessarily rooted solely in myogenesis. There are psychological changes that occur with androgen use, which both positively and negatively influence performance. In addition, androgens may have psychotropic qualities, which influence their continued use, and risk for abuse. Myogenesis may occur with androgen administration; however, we have discussed that AAS use may not alone increase myogenesis, and in fact, some anabolic effects of androgens may be through their catabolic actions on adipose tissues. These psychological and physiological effects of androgens may be through multiple genetic, receptor, and endocrine substrates, and may be differentially affected dependent on hormonal sequelae. Thus, androgens have pleiotropic effects on behavioral, autonomic, and neuroendocrine functioning. References 1. Howell S. and Shalet S., (2001) Testosterone deficiency and replacement. Horm Res. 56, 86–92. 2. Dunger, D. B., Ahmed, M.L., and Ong, K.K. (2006) Early and late weight gain and the timing of puberty. Mol Cell Endocrinol. 254, 140–5. 3. Root, A. W. (2002) Bone strength and the adolescent. Adolesc Med. 13, 53–72.

4. Gombos, Z., Hermann, R., Veijola, R., Knip, M., Simell, O., Pollanen, P., and Ilonen, J. (2003) Androgen receptor gene exon 1 CAG repeat polymorphism in Finnish patients with childhood-onset type 1 diabetes. Eur J Endocrinol. 149, 597–600. 5. Singh, R., Artaza, J. N., Taylor, W. E., Braga, M., Yuan, X., Gonzalez-Cadavid, N. F., and Bhasin, S. (2006) Testosterone inhibits

26

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

adipogenic differentiation in 3 T3-L1 cells: nuclear translocation of androgen receptor complex with beta-catenin and T-cell factor 4 may bypass canonical Wnt signaling to downregulate adipogenic transcription factors. Endocrinology. 147, 141–54. Sinha-Hikim, I., Taylor, W. E., GonzalezCadavid, N. F., Zheng, W., and Bhasin, S. (2004) Androgen receptor in human skeletal muscle and cultured muscle satellite cells: upregulation by androgen treatment. J Clin Enndocrinol Metab. 89, 5245–55. Marcus, J., Maccoby, E. E., Jacklin, C.N., and Doering, C.H. (1985) Dev Psychobiol. 18, 327–40. Geier, D. A., Kern, J. K., and Geier, M. R. (2010) The biological basis of autism spectrum disorders: understanding causation and treatment by clinical geneticists. Acta Neurobiol Exp (Wars) 70, 209–26. Whitehouse, A. J., Maybery, M. T., Hart, R., Mattes, E., Newnham, J. P., Soboda, D. M., Stanley, F. J., and Hickey, M. (2010) Fetal androgen exposure and pragmatic language ability of girls in middle childhood: implications for the extreme male-brain theory of autism. Psychoneuroendocrinology 35, 1259–64. Pajer K. Tabbah R., Gardner W., Rubin R. T., Czambel R. K., and Wang Y. (2006) Adrenal androgen and gonadal hormone levels in adolescent girls with conduct disorder. Psychoneuroendocrinology 31, 1245–56. Rowe R., Maughan B., Worthman C. M., Costello E. J., and Angold A. (2004) Testosterone, antisocial behavior, and social dominance in boys: pubertal development and biosocial interaction. Biol Psychiatry 55, 546–52. van Anders SM, Hamilton LD, and Watson NV. (2007) Multiple partners are associated with higher testosterone in North American men and women. Horm. Behav. 51, 454–9. Anderson R. A., Bancroft J., and Wu F. C. (1992) The effects of exogenous testosterone on sexuality and mood of normal men. J Clin Endocrinol Metab. 75, 1503–7. Kuepper Y., Alexander N., Osinsky R., Mueller E., Schmitz A., Netter P., and Hennig J. (2010) Aggression – interactions of serotonin and testosterone in healthy men and women. Behav Brain Res. 206, 93–100. Sternbach H. (1998) Age-associated testosterone decline in men: clinical issues for psychiatry. Am J Psychiatry. 155, 1310–8. Christiansen K., and Knussmann R. (1987) Sex hormones and cognitive functioning in men. Neuropsychobiology. 18, 27–36.


423

17. Janowsky J. S., Chavez B., and Orwoll E. (2000) Sex steroids modify working memory. J Cogn Neurosci. 12, 407–14. 18. Janowsky J. S., Oviatt S. K., and Orwoll E.S. (1994) Testosterone influences spatial cognition in older men. Behav Neurosci. 108, 325–32. 19. Wang C., Alexander G., Berman N., Salehian B., Davidson T., McDonald V., Steiner B., Hull L., Callegari C., and Swerdloff R. S. (1996) Testosterone replacement therapy improves mood in hypogonadal men – a clinical research center study. J Clin Endocrinol Metab. 81, 3578–83. 20. Alexander G. M., Swerdloff R. S., Wang C., Davidson T., McDonald V., Steiner B., and Hines M. (1997) Androgen-behavior correlations in hypogonadal men and eugonadal men. I. Mood and response to auditory sexual stimuli. Horm Behav. 31, 110–9. 21. Basaria S., and Dobs A.S. (2001) Hypogonadism and androgen replacement therapy in elderly men. Am J Med. 110, 563–72. 22. Sloan D. M., and Kornstein S. G. (2003) Gender differences in depression and response to antidepressant treatment. Psychiatr Clin North Am. 26, 581–94. 23. Zender R., and Olshansky E. (2009) Women’s mental health: depression and anxiety. Nurs Clin North Am. 44, 355–64. 24. Williams C. L., and Meck W. H. (1991) The organizational effects of gonadal steroids on sexually dimorphic spatial ability. Psychoneuroendocrinology 16, 155–76. 25. Frick K. M., Burlingame L. A., Arters J. A., and Berger-Sweeney J. (2000) Reference memory, anxiety and estrous cyclicity in C57BL/6NIA mice are affected by age and sex. Neuroscience. 95, 293–307. 26. Johnston A. L., and File S. E. (1991) Sex differences in animal tests of anxiety. Physiol Behav. 49, 245–50. 27. Kosten T. R., Kosten T. A., McDougle C. J., Hameedi F. A., McCance E. F., Rosen M. I., Oliveto A. H., and Price L. H. (1996) Gender differences in response to intranasal cocaine administration to humans. Biol Psychiatry. 39, 147–8. 28. Becker J. B., and Hu M. (2008) Sex differences in drug abuse. Front Neuroendocrinol. 29, 36–47. 29. Bitran D., Hilvers R. J., Frye C. A., and Erskine M. S. (1996) Chronic anabolicandrogenic steroid treatment affects brain GABA(A) receptor-gated chloride ion transport. Life Sci. 58, 573–83. 30. Bitran D., Kellogg C. K., and Hilvers R. J. (1993) Treatment with an anabolic-androgenic

424

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

A.S. Kohtz and C.A. Frye steroid affects anxiety-related behavior and alters the sensitivity of cortical GABAA receptors in the rat. Horm Behav. 27, 568–83. Frye C. A., and Lacey E. H. (2001) Posttraining androgens’ enhancement of cognitive performance is temporally distinct from androgens’ increases in affective behavior. Cogn Affect Behav Neurosci. 1, 172–82. Frye C. A., Edinger K. L., Lephart E. D., and Walf A. A. (2010) 3alpha-androstanediol, but not testosterone, attenuates age-related decrements in cognitive, anxiety, and depressive behavior of male rats. Front Aging Neurosci. 8, 2–5. Walf A. A., and Frye C. A. (2007) The use of the elevated plus maze as an assay of anxietyrelated behavior in rodents. Nat Protoc. 2, 322–8. Edinger K. L., and Frye C. A. (2005) Testosterone’s anti-anxiety and analgesic effects may be due in part to actions of its 5alpha-reduced metabolites in the hippocampus. Psychoneuroendocrinology. 30, 418–30. Edinger K. L., and Frye C. A. (2006) Intrahippocampal administration of an androgen receptor antagonist, flutamide, can increase anxiety-like behavior in intact and DHTreplaced male rats. Horm Behav. 50, 216–22. Edinger K. L., and Frye C. A. (2007) Androgens’ performance-enhancing effects in the inhibitory avoidance and water maze tasks may involve actions at intracellular androgen receptors in the dorsal hippocampus. Neurobiol Learn Mem. 87, 201–8. Frye C. A., Koonce C. J., Edinger K. L., Osborne D. M., and Walf A. A. (2008) Androgens with activity at estrogen receptor beta have anxiolytic and cognitive-enhancing effects in male rats and mice. Horm Behav. 54, 726–34. Frye C. A., Edinger K., and Sumida K. (2008) Androgen administration to aged male mice increases anti-anxiety behavior and enhances cognitive performance. Neuropsychopharmacology. 33, 1049–61. Frye C. A., and Edinger K. L. (2004) Testosterone’s metabolism in the hippocampus may mediate its anti-anxiety effects in male rats. Pharmacol Biochem Behav. 78, 473–81. Aikey JL, Nyby JG, Anmuth DM, and James PJ. (2002) Testosterone rapidly reduces anxiety in male house mice (Mus musculus). Horm Behav. 42, 448–60. Osborne D. M., Edinger K., and Frye C. A. (2009) Chronic administration of androgens with actions at estrogen receptor beta have anti-anxiety and cognitive-enhancing effects in male rats. Age (Dordr). 31, 191–8.

42. Walf A. A., Paris J. J., and Frye C. A. (2009) Chronic estradiol replacement to aged female rats reduces anxiety-like and depression-like behavior and enhances cognitive performance. Psychoneuroendocrinology. 34, 909–16. 43. Buddenberg T. E., Komorowski M., Ruocco L. A., Silva M. A., and Topic B. (2009) Attenuating effects of testosterone on depressive-like behavior in the forced swim test in healthy male rats. Brain Res Bull. 79, 182–6. 44. Frye C. A., and Sturgis J. D. (1995) Neurosteroids affect spatial/reference, working, and long-term memory of female rats. Neurobiol Learn Mem. 64, 83–96. 45. Boyle G. J., Neumann D. L., Furedy J. J., and Westbury H. R. (2010) Sex differences in verbal and visual-spatial tasks under different hemispheric visual-field presentation conditions. Percept Mot Skills. 110, 396–410. 46. Leggett V., Jacobs P., Nation K., Scerif G., and Bishop D. V. (2010) Neurocognitive outcomes of individuals with a sex chromosome trisomy: XXX, XYY, or XXY: a systematic review. Dev Med Child Neurol. 52, 119–29. 47. Frye C. A., and Seliga A. M. (2001) Testosterone increases analgesia, anxiolysis, and cognitive performance of male rats. Cogn Affect Behav Neurosci. 1, 371–81. 48. Kritzer M. F., and Pugach I. (2001) Administration of tamoxifen but not flutamide to hormonally intact, adult male rats mimics the effects of short-term gonadectomy on the catecholamine innervation of the cerebral cortex. J Comp Neurol. 431, 444–59. 49. Benice T. S., and Raber J. (2009) Dihydrotestosterone modulates spatial working-memory performance in male mice. J Neurochem. 110, 902–11. 50. Edinger K. L., and Frye C. A. (2004) Testosterone’s analgesic, anxiolytic, and cognitive-enhancing effects may be due in part to actions of its 5alpha-reduced metabolites in the hippocampus. Behav Neurosci. 118, 1352–64. 51. Edinger K. L., Lee B., and Frye C. A. (2004) Mnemonic effects of testosterone and its 5alpha-reduced metabolites in the conditioned fear and inhibitory avoidance tasks. Pharmacol Biochem Behav. 78, 559–68. 52. Frye C. A., Edinger K. L., Seliga A. M., and Wawrzycki J. M. (2004) 5alpha-reduced androgens may have actions in the hippocampus to enhance cognitive performance of male rats. Psychoneuroendocrinology. 29, 1019–27. 53. Frye C. A., and McCormick C. M. (2000) The neurosteroid, 3alpha-androstanediol, prevents inhibitory avoidance deficits and pyknotic cells in the granule layer of the dentate

26

54.

55.

56.

57.

58.

59. 60.

61.

62.

63.

64.

65.

gyrus induced by adrenalectomy in rats. Brain Res. 855, 166–70. Frye C. A., Park D., Tanaka M., Rosellini R., and Svare B. (2001) The testosterone metabolite and neurosteroid 3alpha-androstanediol may mediate the effects of testosterone on conditioned place preference. Psychoneuroendocrinology. 26, 731–50. Frye C. A., Rhodes M. E., Rosellini R., Svare B. (2002) The nucleus accumbens as a site of action for rewarding properties of testosterone and its 5alpha-reduced metabolites. Pharmacol Biochem Behav. 74, 119–27. Pike C. J., Carroll J. C., Rosario E. R., Barron A. M. (2009) Protective actions of sex steroid hormones in Alzheimer’s disease. Front Neuroendocrinol. 30, 239–58. Rosario E.R., Chang L., Head E.H., Stanczyk F.Z., Pike C.J. (2011) Brain levels of sex steroid hormones in men and women during normal aging and in Alzheimer’s disease. Neurobiol Aging. 32, 604–613. Nguyen TV, Jayaraman A, Quaglino A, Pike CJ. (2010) Androgens selectively protect against apoptosis in hippocampal neurones. J Neuroendocrinol. 22, 1013–22. Raber J. (2008) AR, apoE, and cognitive function. Horm Behav. 53, 706–15. Frye C. A., Sturgis J. D. (1995) Neurosteroids affect spatial/reference, working, and longterm memory of female rats. Neurobiol Learn Mem. 64, 83–96. Kanit, L., Taskiran, D., Yilmaz, O. A., Balkan, B., Demirgoren, S., Furedy, J. J., and Pogun, S. (2000) Sexually dimorphic cognitive styles in rats emerges after puberty. Brain Res Bull. 52, 243–248. Frye C. A., Duffy C. K., and Walf A. A. (2007) Estrogens and progestins enhance spatial learning of intact and ovariectomized rats in the object placement task. Neurobiol Learn Mem. 88, 208–16. Paris J. J., and Frye C. A. (2008) Estrous cycle, pregnancy, and parity enhance performance of rats in object recognition or object placement tasks. Reproduction. 136, 105–15. Walf A. A., Sumida K., and Frye C. A. (2006) Inhibiting 5alpha-reductase in the amygdala attenuates antianxiety and antidepressive behavior of naturally receptive and hormoneprimed ovariectomized rats. Psychopharmacology (Berl). 186, 302–11. Bahrke M. S., Yesalis C. E., and Brower K. J. (1998) Anabolic-androgenic steroid abuse and performance-enhancing drugs among adolescents. Child Adolesc Psychiatr Clin N Am. 7, 821–38.


425

66. Yesalis C. E., Barsukiewicz C. K., Kopstein A. N., and Bahrke M. S. (1997) Trends in anabolic-androgenic steroid use among adolescents. Arch Pediatr Adolesc Med 151, 1197–206. 67. Svare B., Mann M., Broida J., Kinsley C., Ghiraldi L., Miele J., and Konen C. (1983) Intermale aggression and infanticide in aged C57BL/6J male mice: behavioral deficits are not related to serum testosterone (T) levels and are not recovered by supplemental T. Neurobiol Aging. 4, 305–12. 68. Kinsley C., and Svare B. (1988) Prenatal stress alters maternal aggression in mice. Physiol Behav. 42, 7–13. 69. Frye C. A., Van Keuren K. R., and Erskine M. S. (1996) Behavioral effects of 3 alpha-androstanediol. I: Modulation of sexual receptivity and promotion of GABA-stimulated chloride flux. Behav Brain Res. 79, 109–18. 70. Archer J. (1991) The influence of testosterone on human aggression. Br J Psychol. 82, 1–28. 71. Meaney M. J., and McEwen B. S. (1986) Testosterone implants into the amygdala during the neonatal period masculinize the social play of juvenile female rats. Brain Res. 398, 324–8. 72. Rhees R. W., Kirk B. A., Sephton S., and Lephart E. D. Effects of prenatal testosterone on sexual behavior, reproductive morphology and LH secretion in the female rat. Dev Neurosci. 19, 430–7 73. Su T. P., Pagliaro M., Schmidt P. J., Pickar D., Wolkowitz O., and Rubinow D. R. (1993) Neuropsychiatric effects of anabolic steroids in male normal volunteers. JAMA. 269, 2760–4. 74. Choi P. Y., and Pope H. G. Jr. (1994) Violence toward women and illicit androgenic-anabolic steroid use. Ann Clin Psychiatry. 6, 21–5. 75. Greenblatt R. B., and Karpas A. (1983) Hormone therapy for sexual dysfunction. The only “true aphrodisiac”. Postgrad Med. 74, 88–80, 84–9. 76. Bahrke M. S., Yesalis C. E. 3rd, and Wright J. E. (1990) Psychological and behavioural effects of endogenous testosterone levels and anabolic-androgenic steroids among males. Sports Med. 10, 303–37. 77. Bahrke M. S., Yesalis C. E. 3rd, Wright J. E. (1996) Psychological and behavioural effects of endogenous testosterone and anabolicandrogenic steroids. An update. Sports Med. 22, 367–90. 78. Pope H. G. Jr, and Katz D. L. (1994) Psychiatric and medical effects of anabolic-androgenic steroid use. A controlled study of 160 athletes. Arch Gen Psychiatry. 51, 375–82.

426


79. Moss H. B., Panzak G. L., and Tarter R. E. (1993) Sexual functioning of male anabolic steroid abusers. Arch Sex Behav. 22, 1–12. 80. Miczek K. A., Haney M., Tidey J., Vatne T., Weerts E., and DeBold J. F. (1989) Temporal and sequential patterns of agonistic behavior: effects of alcohol, anxiolytics and psychomotor stimulants. Psychopharmacology (Berl). 97, 149–51. 81. Moyer K. E. (1968) Kinds of aggression and their physiological basis. Commun. Behav. Bio. 2, 65–87. 82. Edwards D. A. (1969). Early androgen stimulation and aggressive behavior in male and female mice. Physiology & Behavior, 4, 333–338. 83. Miczek K. A., DeBold J. F., and Thompson M. L. (1984) Pharmacological, hormonal, and behavioral manipulations in analysis of aggressive behavior. Prog Clin Biol Res 167, 1–26. 84. Kubala K. H., McGinnis M. Y., Anderson G. M., and Lumia A. R. (2008) The effects of an anabolic androgenic steroid and low serotonin on social and non-social behaviors in male rats. Brain Res. 26, 21–9. 85. Albert D. J., Jonik R. H., and Walsh M. L. (1993) Influence of combined estradiol and testosterone implants on the aggressiveness of nonaggressive female rats. Physiol Behav. 53, 709–13. 86. Rezek D. L., and Whalen R. E. Male rat brain androgen metabolism and sexual behavior. Neuroendocrinology. 25, 141–9. 87. Morali G., Oropeza M. V., Lemus A. E., and Perez-Palacios G. (1994) Mechanisms regulating male sexual behavior in the rat: role of 3 alpha- and 3 beta-androstanediols. Biol Reprod. 51, 562–71. 88. Parrott R. F. (1974) The effects of various androgens on peripheral structures in the castrated male rat. J Reprod Fertil. 38, 49–57. 89. Howland B. E. (1975) The influence of feed restriction and subsequent re-feeding on gonadotrophin secretion and serum testosterone levels in male rats. J Reprod Fertil. 44, 429–36 90. Asarian L., and Geary N. Modulation of appetite by gonadal steroid hormones. Philos Trans R Soc Lond B Biol Sci. 361, 1251–63. 91. Allan C. A., and McLachlan R. I. (2010) Androgens and obesity. Curr Opin Endocrinol Diabetes Obes.17, 224–32. 92. Gentry R. T., and Wade G. N. (1976) Androgenic control of food intake and body weight in male rats. J Comp Physiol Psychol. 90, 18–25.

93. Elias A. N., and Wilson A. F. (1993) Exercise and gonadal function. Hum Reprod. 8, 1747–61. 94. Campbell B. C., Dreber A., Apicella C. L., Eisenberg D. T., Gray P. B., Little A. C., Garcia J. R., Zamore R. S., and Lum J. K. (2010) Testosterone exposure, dopaminergic reward, and sensation-seeking in young men. Physiol Behav. 99, 451–6. 95. Rosellini R. A., Svare B. B., Rhodes M. E., and Frye C. A. (2001) The testosterone metabolite and neurosteroid 3alpha-androstanediol may mediate the effects of testosterone on conditioned place preference. Brain Res Brain Res Rev. 37, 162–71. 96. Frye C. A. (2007) Some rewarding effects of androgens may be mediated by actions of its 5alpha-reduced metabolite 3alpha-androstanediol. Pharmacol Biochem Behav. 86, 354–67. 97. Fuxjager M. J., Forbes-Lorman R. M., Coss D. J., Auger C. J., Auger A. P., and Marler C. A. (2010) Winning territorial disputes selectively enhances androgen sensitivity in neural pathways related to motivation and social aggression. Proc Natl Acad Sci U S A. 107, 12393–8. 98. Robinson D. L., Phillips P. E., Budygin E. A., Trafton B. J., Garris P. A., and Wightman R. M. (2001) Sub-second changes in accumbal dopamine during sexual behavior in male rats. Neuroreport. 12, 49–52. 99. Robinson T. E., Gorny G., Mitton E., and Kolb B. (2001) Cocaine self-administration alters the morphology of dendrites and dendritic spines in the nucleus accumbens and neocortex. Synapse. 39, 257–66. 100. Wood R. I. (2004) Reinforcing aspects of androgens. Physiol Behav. 83, 279–89. 101. Triemstra J. L., Sato S. M., Wood R. I. (2008) Testosterone and nucleus accumbens dopamine in the male Syrian hamster. Psychoneuroendocrinology. 33, 386–94. 102. Kashkin K. B., and Kleber H. D. (1989) Hooked on hormones? An anabolic steroid addiction hypothesis. JAMA. 262, 3166–70. 103. Wright J. E. (1980) Anabolic steroids and athletics. Exerc Sport Sci Rev. 8, 149–202. 104. Bonson K. R., Johnson R. G., Fiorella D., Rabin R. A., Winter J. C. (1994) Serotonergic control of androgen-induced dominance. Pharmacol Biochem Behav. 49, 313–22. 105. Russo S. J., Sun W. L., Minerley A. C., Weierstall K., Nazarian A., Festa E. D., Niyomchai T., Akhavan A., Jenab S., and Quiñones-Jenab V. (2010) Progesterone does not affect cocaine-induced conditioned place

26

106.

107.

108.

109.

110.

111.

112.

113.

114.

115.

116.

117.

preference or locomotor activity in male rats. Ethn Dis. 20, 73–7. Kohtz A. S., Paris J. J., and Frye C. A. (2010) Low doses of cocaine decrease, and high doses increase, anxiety-like behavior and brain progestogen levels among intact rats. Horm Behav. 57, 474–80. Takahashi A., Kwa C., Debold J. F., and Miczek K. A. (2010) GABA(A) receptors in the dorsal raphé nucleus of mice: escalation of aggression after alcohol consumption. Psychopharmacology (Berl). 211, 467–77. de Almeida R. M., Ferrari P. F., Parmigiani S., and Miczek K. A. (2005) Escalated aggressive behavior: dopamine, serotonin and GABA. Eur J Pharmacol. 526, 51–64. Haupt H. A., and Rovere G. D. (1984) Anabolic steroids: a review of the literature. Am J Sports Med. 12, 469–84. Grokett B. H., Ahmad N., and Warren D. W. (1992) The effects of an anabolic steroid (oxandrolone) on reproductive development in the male rat. Acta Endocrinol (Copenh). 126, 173–8. Helfman T., and Falanga V. (1995) Stanozolol as a novel therapeutic agent in dermatology. J Am Acad Dermatol. 33, 254–8. Hansell D. T., Davies J. W., Shenkin A., Garden O. J., Burns H. J., and Carter D. C. (1989) The effects of an anabolic steroid and peripherally administered intravenous nutrition in the early postoperative period. JPEN J Parenter Enteral Nutr. 13, 349–58. Johnson L. C., and O’Shea J. P. (1969) Anabolic steroid: effects on strength development. Science. 164, 957–9. Earnest C. P., Olson M. A., Broeder C. E., Breuel K. F., and Beckham S. G. (2000) In vivo 4-androstene-3,17-dione and 4-androstene-3 beta,17 beta-diol supplementation in young men. Eur J Appl Physiol. 81, 229–32. Brown G. A., Vukovich M., and King D. S. (2006) Testosterone prohormone supplements. Med Sci Sports Exerc. 38, 1451–61. Jasuja R., Ramaraj P., Mac R. P., Singh A. B., Storer T. W., Artaza J., Miller A., Singh R., Taylor W. E., Lee M. L., Davidson T., SinhaHikim I., Gonzalez-Cadavid N., and Bhasin S. (2005) Delta-4-androstene-3,17-dione binds androgen receptor, promotes myogenesis in vitro, and increases serum testosterone levels, fat-free mass, and muscle strength in hypogonadal men. J Clin Endocrinol Metab. 90, 855–63. Yue P., Chatterjee K., Beale C., Poole-Wilson P. A., and Collins P. (1995) Testosterone relaxes rabbit coronary arteries and aorta. Circulation. 91, 1154–60.


427

118. Costarella C. E., Stallone J. N., Rutecki G. W., and Whittier F. C. (1996) Testosterone causes direct relaxation of rat thoracic aorta. J Pharmacol Exp Ther. 277, 34–9. 119. Chou T. M., Sudhir K., Hutchison S. J., Ko E., Amidon T. M., Collins P., and Chatterjee K. (1996) Testosterone induced dilation of canine coronary conductance and resistance arteries in vivo. Circulation. 94, 2614–2619. 120. Schrör K., Morinelli T. A., Masuda A., Matsuda K., Mathur R. S., and Halushka P. V. (1994) Testosterone treatment enhances thromboxane A2 mimetic induced coronary artery vasoconstriction in guinea pigs. Eur J Clin Invest. 1, 50–2. 121. Hydock D. S., Lien C. Y., Schneider C. M., and Hayward R. (2007) Effects of voluntary wheel running on cardiac function and myosin heavy chain in chemically gonadectomized rats. Am J Physiol Heart Circ Physiol. 293, 3254–64. 122. Hassan N. A., Salem M. F., and Sayed M. A. (2009) Doping and effects of anabolic androgenic steroids on the heart: histological, ultrastructural, and echocardiographic assessment in strength athletes. Hum Exp Toxicol. 28, 273–83. 123. Goldstein D. R., Dobbs T., Krull B., and Plumb V. J. (1998) Clenbuterol and anabolic steroids: a previously unreported cause of myocardial infarction with normal coronary arteriograms. South Med J. 91, 780–4. 124. Nestler J. E., Barlascini C. O., Clore J. N., and Blackard W. G. (1988) Dehydroepiandrosterone reduces serum low density lipoprotein levels and body fat but does not alter insulin sensitivity in normal men. J Clin Endocrinol Metab. 66, 57–61. 125. Fowler N. O., McCall D., Chou T. C., Holmes J. C., and Hanenson I. B. (2004) Electrocardiographic changes and cardiac arrhythmias in patients receiving psychotropic drugs. Am J Cardiol. 37, 223–30. 126. Du J., Zhang L., and Wang Z. (2009) Testosterone inhibits the activity of peroxisome proliferator-activated receptor gamma in a transcriptional transaction assay. Pharmazie. 64, 692–3. 127. Hansmann G., and Zamanian R. T. (2009) PPARgamma activation: a potential treatment for pulmonary hypertension. Sci Transl Med. 1, 12–14. 128. Fruchart J. C., Duriez P., and Staels B. (1999) Peroxisome proliferator-activated receptoralpha activators regulate genes governing lipoprotein metabolism, vascular inflammation and atherosclerosis. Curr Opin Lipidol. 10, 245–57.

428


129. Buchan K. W., and Hassall D. G. (2000) PPAR agonists as direct modulators of the vessel wall in cardiovascular disease. Med Res Rev. 20, 350–66. 130. Ketsawatsomkron P., Pelham C. J., Groh S., Keen H. L., Faraci F. M., and Sigmund C. D. (2010) Does peroxisome proliferator-activated receptor-gamma (PPAR gamma) protect from hypertension directly through effects in the vasculature? J Biol Chem. 285, 9311–6. 131. Wu J. S., Lin T. N., and Wu K. K. (2009) Rosiglitazone and PPAR-gamma overexpression protect mitochondrial membrane potential and prevent apoptosis by upregulating anti-apoptotic Bcl-2 family proteins. J Cell Physiol. 220, 58–71. 132. Wu J., Chen L., Zhang D., Huo M., Zhang X., Pu D., and Guan Y. (2009) Peroxisome proliferator-activated receptors and renal diseases. Front Biosci. 14, 995–1009. 133. Wu J. S., Cheung W. M., Tsai Y. S., Chen Y. T., Fong W. H., Tsai H. D., Chen Y. C., Liou J. Y., Shyue S. K., Chen J. J., Chen Y. E., Maeda N., Wu K. K., and Lin T. N. (2009) Ligand-activated peroxisome proliferatoractivated receptor-gamma protects against ischemic cerebral infarction and neuronal apoptosis by 14-3-3 epsilon upregulation. Circulation. 119, 1124–34. 134. Minutoli L., Antonuccio P., Polito F., Bitto A., Squadrito F., Irrera N., Nicotina P. A., Fazzari C., Montalto A. S., Di Stefano V., Romeo C., Altavilla D. (2009) Peroxisome proliferator activated receptor beta/delta activation prevents extracellular regulated kinase 1/2 phosphorylation and protects the testis from ischemia and reperfusion injury. J Urol. 181, 1913–21. 135. Jones R. D., Pugh P. J., Hall J., Channer K. S., and Jones T. H. (2003) Altered circulating hormone levels, endothelial function and vascular reactivity in the testicular feminised mouse. Eur J Endocrinol. 148, 111–20. 136. Dimicco J. A., and Zaretsky D. V. (2007) The dorsomedial hypothalamus: a new player in thermoregulation. Am J Physiol Regul Integr Comp Physiol. 292, R47–63. 137. Shekhar A., Johnson P. L., Sajdyk T. J., Fitz S. D., Keim S. R., Kelley P. E., Gehlert D. R., and DiMicco J. A. (2006) Angiotensin-II is a putative neurotransmitter in lactate-induced panic-like responses in rats with disruption of GABAergic inhibition in the dorsomedial hypothalamus. J Neurosci. 26, 9205–15. 138. Traish A. M., Feeley R. J., and Guay A. (2009) Mechanisms of obesity and related pathologies: androgen deficiency and endothelial dysfunction

139.

140.

141.

142.

143.

144.

145.

146.

147.

148.

149.

150.

may be the link between obesity and erectile dysfunction. FEBS J. 276, 5755–67. Traish A. M., Saad F., and Guay A. (2009) The dark side of testosterone deficiency: II. Type 2 diabetes and insulin resistance. J Androl. 30, 23–32. Traish A. M., Guay A., Feeley R., and Saad F. (2009) The dark side of testosterone deficiency: I. Metabolic syndrome and erectile dysfunction. J Androl. 30, 10–22. Claessens F., Denayer S., Van Tilborgh N., Kerkhofs S., Helsen C., and Haelens A. (2008) Diverse roles of androgen receptor (AR) domains in AR-mediated signaling. Nucl Recept Signal. 6, 008. Shaknovich R., Shue G., and Kohtz D. S. (1992) Conformational activation of a basic helix-loop-helix protein (MyoD1) by the C-terminal region of murine HSP90 (HSP84). Mol Cell Biol. 12, 5059–68. Zoubeidi A., Zardan A., Beraldi E., Fazli L., Sowery R., Rennie P., Nelson C., and Gleave M. (2007) Cooperative interactions between androgen receptor (AR) and heat-shock protein 27 facilitate AR transcriptional activity. Cancer Res. 67, 10455–65. Shaffer P. L., Jivan A., Dollins D. E., Claessens F., and Gewirth D. T. (2004) Structural basis of androgen receptor binding to selective androgen response elements. Proc Natl Acad Sci U S A. 101, 4758–63. Knudsen K. E., Cavenee W. K., and Arden K. C. (1999) D-type cyclins complex with the androgen receptor and inhibit its transcriptional transactivation ability. Cancer Res. 59, 2297–301. Petre-Draviam C. E., Cook S. L., Burd C. J., Marshall T. W., Wetherill Y. B., and Knudsen K. E. (2003) Specificity of cyclin D1 for androgen receptor regulation. Cancer Res. 63, 4903–13. Urbanucci A., Waltering K. K., Suikki H. E., Helenius M. A., and Visakorpi T. (2008) Androgen regulation of the androgen receptor coregulators. BMC Cancer. 8, 219. Karvonen U., Jänne O. A., and Palvimo J. J. (2006) Androgen receptor regulates nuclear trafficking and nuclear domain residency of corepressor HDAC7 in a ligand-dependent fashion. Exp Cell Res. 312, 3165–83. Björkman M., Iljin K., Halonen P., Sara H., Kaivanto E., Nees M., and Kallioniemi O. P. (2008) Defining the molecular action of HDAC inhibitors and synergism with androgen deprivation in ERG-positive prostate cancer. Int J Cancer. 123, 2774–81. Welsbie D. S., Xu J., Chen Y., Borsu L., Scher H. I., Rosen N., and Sawyers C. L. (2009)

26

151.

152.

153.

154.

155.

156.

157.

158.

159.

160.

161.

162.

163.

Histone deacetylases are required for androgen receptor function in hormone-sensitive and castrate-resistant prostate cancer. Cancer Res. 69, 958–66. Baulieu E. E., Atger M., Best-Belpomme M., Corvol P., Courvalin J. C., Mester J., Milgrom E., Robel P., Rochefort H., and De Catalogne D. (1975) Steroid hormone receptors. Vitam Horm. 33, 649–736. Sato S. M., Johansen J. A., Jordan C. L., and Wood R. I. (2010) Membrane androgen receptors may mediate androgen reinforcement. Psychoneuroendocrinology. 35, 1063–73. Farnsworth W. E. (1990) The prostate plasma membrane as an androgen receptor. Membr Biochem. 9, 141–62. Bottino M. C., and Lanari C. (2010) Extra nuclear localization of steroid receptors and non genomic activation mechanisms. Medicina (B Aires). 70, 173–84. MacLusky N. J., Clark C. R., Shanabrough M., and Naftolin F. (1987) Metabolism and binding of androgens in the spinal cord of the rat. Brain Res. 422, 83–91. García-Ovejero D., Veiga S., García-Segura L. M., and Doncarlos L. L. (2002) Glial expression of estrogen and androgen receptors after rat brain injury. J Comp Neurol. 450, 256–71. DonCarlos L. L., Sarkey S., Lorenz B., Azcoitia I., Garcia-Ovejero D., Huppenbauer C., and Garcia-Segura L. M. (2006) Novel cellular phenotypes and subcellular sites for androgen action in the forebrain. Neuroscience. 138, 801–7. DonCarlos L. L., Garcia-Ovejero D., Sarkey S., Garcia-Segura L. M., and Azcoitia I. (2003) Androgen receptor immunoreactivity in forebrain axons and dendrites in the rat. Endocrinology. 144, 3632–8. Jänne O. A., Palvimo J. J., Kallio P., and Mehto M. (1993) Androgen receptor and mechanism of androgen action. Ann Med. 25, 83–9. Doherty P. C., and Sheridan P. J. (1981) Uptake and retention of androgen in neurons of the brain of the golden hamster. Brain Res. 219, 327–34. Sar M., and Stumpf W. E. (1972) Cellular localization of androgen in the brain and pituitary after the injection of tritiated testosterone. Experientia. 28, 1364–6. Sar M., and Stumpf W. E. (1973) Autoradiographic localization of radioactivity in the rat brain after the injection of 1,2-3 H-testosterone. Endocrinology. 92, 251–6. Sar M., and Stumpf W. E. (1981) Combined autoradiography and immunohistochemistry


164.

165.

166.

167.

168.

169.

170.

171.

172.

173.

174.

429

for simultaneous localization of radioactively labeled steroid hormones and antibodies in the brain. J Histochem Cytochem. 29, 161–6. Kritzer M. F. (1997) Selective colocalization of immunoreactivity for intracellular gonadal hormone receptors and tyrosine hydroxylase in the ventral tegmental area, substantia nigra, and retrorubral fields in the rat. J Comp Neurol. 379, 247–60. Lieberburg I., Maclusky N. J., and McEwen B. S. (1977) 5alpha-Dihydrotestosterone (DHT) receptors in rat brain and pituitary cell nuclei. Endocrinology. 100, 598–607. Hajszan T., MacLusky N. J., and Leranth C. (2008) Role of androgens and the androgen receptor in remodeling of spine synapses in limbic brain areas. Horm Behav. 53, 638–46. Clark R. L., Antonello J. M., Grossman S. J., Wise L. D., Anderson C., Bagdon W. J., Prahalada S., MacDonald J. S., and Robertson R. T. (1990) External genitalia abnormalities in male rats exposed in utero to finasteride, a 5 alpha-reductase inhibitor. Teratology. 42, 91–100. di Salle E., Giudici D., Briatico G., Ornati G., and Panzeri A. (1993) Hormonal effects of turosteride, a 5 alpha-reductase inhibitor, in the rat. J Steroid Biochem Mol Biol. 46, 549–55. Reismann P., Likó I., Igaz P., Patócs A., and Rácz K. (2009) Pharmacological options for treatment of hyperandrogenic disorders. Mini Rev Med Chem. 9, 1113–26. Garcia Valencia V., Sanchez M., Gutierrez M., Cantabrana B., and Hidalgo A. (1991) Effects of steroidal and non-steroidal antiandrogens on the left atrium of the rat in vitro. Gen Pharmacol. 22, 1081–6. Imperato-McGinley J., Sanchez R. S., Spencer J. R., Yee B., and Vaughan E. D. (1992) Comparison of the effects of the 5 alphareductase inhibitor finasteride and the antiandrogen flutamide on prostate and genital differentiation: dose-response studies. Endocrinology. 131, 1149–56. Raudrant D., and Rabe T. (2003) Progestogens with antiandrogenic properties. Drugs. 63, 463–92. Azuma K., Nakashiro K., Sasaki T., Goda H., Onodera J., Tanji N., Yokoyama M., and Hamakawa H. (2010) Anti-tumor effect of small interfering RNA targeting the androgen receptor in human androgen-independent prostate cancer cells. Biochem Biophys Res Commun. 391, 1075–9. Fimmel S., Kurfurst R., Bonté F., and Zouboulis C. C. (2007) Responsiveness to androgens and effectiveness of antisense oligonucleotides

430

175.

176.

177.

178.

179.

180.

181.

182.

183.

184.

A.S. Kohtz and C.A. Frye against the androgen receptor on human epidermal keratinocytes is dependent on the age of the donor and the location of cell origin. Horm Metab Res. 39, 157–65. Yeh S., Tsai M. Y., Xu Q., Mu X. M., Lardy H., Huang K. E., Lin H., Yeh S. D., Altuwaijri S., Zhou X., Xing L., Boyce B. F., Hung M. C., Zhang S., Gan L., and Chang C. (2002) Generation and characterization of androgen receptor knockout (ARKO) mice: an in vivo model for the study of androgen functions in selective tissues. Proc Natl Acad Sci U S A. 99, 13498–503. Zhou X. (2010) Roles of androgen receptor in male and female reproduction: lessons from global and cell-specific androgen receptor knockout (ARKO) mice. J Androl. 31, 235–43. Handa R. J., Pak T. R., Kudwa A. E., Lund T. D., and Hinds L. (2008) An alternate pathway for androgen regulation of brain function: activation of estrogen receptor beta by the metabolite of dihydrotestosterone, 5alphaandrostane-3beta,17beta-diol. Horm Behav. 53, 741–52. Alejandre-Gomez M., Garcia-Segura L. M., and Gonzalez-Burgos I. (2007) Administration of an inhibitor of estrogen biosynthesis facilitates working memory acquisition in male rats. Neurosci Res. 58, 272–7. Ellem S. J., and Risbridger G. P. (2010) Aromatase and regulating the estrogen:androgen ratio in the prostate gland. J Steroid Biochem Mol Biol. 118, 246–51. Lephart E. D., Lund T. D., and Horvath T. L. (2001) Brain androgen and progesterone metabolizing enzymes: biosynthesis, distribution and function. Brain Res Brain Res Rev. 37, 25–37. Séralini G., and Moslemi S. (2001) Aromatase inhibitors: past, present and future. Mol Cell Endocrinol. 178, 117–31. Reddy D. S., and Jian K. (2010) The testosterone-derived neurosteroid androstanediol is a positive allosteric modulator of GABAA receptors. J Pharmacol Exp Ther. 334, 1031–41. Pak T. R., Chung W. C., Lund T. D., Hinds L. R., Clay C. M., and Handa R. J. (2005) The androgen metabolite, 5alpha-androstane3beta, 17beta-diol, is a potent modulator of estrogen receptor-beta1-mediated gene transcription in neuronal cells. Endocrinology. 146, 147–55. Alderson L. M., and Baum M. J. (1981) Differential effects of gonadal steroids on dopamine metabolism in mesolimbic and nigro-striatal pathways of male rat brain. Brain Res. 218, 189–206.

185. Goudsmit E., Feenstra M. G., and Swaab D. F. (1990) Central monoamine metabolism in the male Brown-Norway rat in relation to aging and testosterone. Brain Res Bull. 25, 755–63. 186. Jalilian-Tehrani M. H., Karakiulakis G., Le Blond C. B., Powell R., and Thomas P. J. (1982) Androgen-induced sexual dimorphism in high affinity dopamine binding in the brain transcends the hypothalamic-limbic region. Br J Pharmacol. 75, 37–48. 187. Mitchell J. B., and Stewart J. (1989) Effects of castration, steroid replacement, and sexual experience on mesolimbic dopamine and sexual behaviors in the male rat. Brain Res. 491, 116–27. 188. Moore W. V. (1988) Anabolic steroid use in adolescence. JAMA. 260, 3484–6. 189. Cunningham G. R., Tindall D. J., and Means A. R. (1979) Differences in steroid specificity for rat androgen binding protein and the cytoplasmic receptor. Steroids. 33, 261–76. 190. Verhoeven G., Heyns W., and De Moor P. (1975) Testosterone receptors in the prostate and other tissues. Vitam Horm. 33, 265–81. 191. DiMeo A. N., and Wood R. I. (2006) Selfadministration of estrogen and dihydrotestosterone in male hamsters. Horm Behav. 49, 519–26. 192. Sheridan P. J. (1984) Autoradiographic localization of steroid receptors in the brain. Clin Neuropharmacol. 7, 281–95. 193. Sato S. M., Johansen J. A., Jordan C. L., and Wood R. I. (2010) Membrane androgen receptors may mediate androgen reinforcement. Psychoneuroendocrinology. 35, 1063–73. 194. Erskine M. S. (1983) Effects of an anti-androgen and 5 alpha-reductase inhibitors on estrus duration in the cycling female rat. Physiol Behav. 30(4), 519–24. 195. Majewska M. D., Harrison N. L., Schwartz R. D., Barker J. L., and Paul S. M. (1986) Steroid hormone metabolites are barbiturate-like modulators of the GABA receptor. Science. 232, 1004–7. 196. Im W. B., Blakeman D. P., Davis J. P., and Ayer D. E. (1990) Studies on the mechanism of interactions between anesthetic steroids and gamma-aminobutyric acidA receptors. Mol Pharmacol. 37, 429–34. 197. Masonis A. E., and McCarthy M. P. (1995) Direct effects of the anabolic/androgenic steroids, stanozolol and 17 alpha-methyltestosterone, on benzodiazepine binding to the gamma-aminobutyric acid(a) receptor. Neurosci Lett. 189, 35–8.

26 198. Gee K. W. (1988) Steroid modulation of the GABA/benzodiazepine receptor-linked chloride ionophore. Mol Neurobiol. 2, 291–317. 199. Penatti C. A., Davis M. C., Porter D. M., and Henderson L. P. (2010) Altered GABAA receptor-mediated synaptic transmission disrupts the firing of gonadotropin-releasing hormone neurons in male mice under conditions that mimic steroid abuse. J Neurosci. 30, 6497–506. 200. Clark A. S., Costine B. A., Jones B. L., KeltonRehkopf M. C., Meerts S. H., NutbrownGreene L. L., Penatti C. A., Porter D. M., Yang P., and Henderson L. P. (2006) Sex- and age-specific effects of anabolic androgenic steroids on reproductive behaviors and on GABAergic transmission in neuroendocrine control regions. Brain Res. 1126, 122–38. 201. Carroll M. E., Lynch W. J., Roth M. E., Morgan A. D., and Cosgrove K. P. (2004) Sex and estrogen influence drug abuse. Trends Pharmacol Sci. 25, 273–9. 202. Kuiper G. G., Lemmen J. G., Carlsson B., Corton J. C., Safe S. H., van der Saag P. T., van der Burg B., and Gustafsson J. A. (1998) Interaction of estrogenic chemicals and phytoestrogens with estrogen receptor beta. Endocrinology. 139, 4252–63. 203. Tremblay G. B., Tremblay A., Copeland N. G., Gilbert D. J., Jenkins N. A., Labrie F., and Giguère V. (1997) Cloning, chromosomal localization, and functional analysis of the murine estrogen receptor beta. Mol Endocrinol. 11, 353–65. 204. Basu A., and Rowan B. G. (2005) Genes related to estrogen action in reproduction and breast cancer. Front Biosci. 10, 2346–72. 205. Connor E. E., Wood D. L., Sonstegard T. S., da Mota A. F., Bennett G. L., Williams J. L., and Capuco A. V. (2005) Chromosomal mapping and quantitative analysis of estrogenrelated receptor alpha-1, estrogen receptors alpha and beta and progesterone receptor in the bovine mammary gland. J Endocrinol. 185, 593–603. 206. Hewitt S. C., and Korach K. S. (2003) Oestrogen receptor knockout mice: roles for oestrogen receptors alpha and beta in reproductive tissues. Reproduction. 125, 143–9. 207. Shimizu T., Kamegai J., Tamura H., Ishii S., Sugihara H., and Oikawa S. (2005) The estrogen receptor (ER) alpha, but not ER beta, gene is expressed in hypothalamic growth hormone-releasing hormone neurons of the adult female rat. Neurosci Res. 52, 121–5. 208. Walf A. A., Rhodes M. E., and Frye C. A. (2004) Antidepressant effects of ERbetaselective estrogen receptor modulators in the


209.

210.

211.

212.

213.

214.

215.

216.

217.

218.

219.

220.

431

forced swim test. Pharmacol Biochem Behav. 78, 523–9. Rissman E. F., Heck A. L., Leonard J. E., Shupnik M. A., and Gustafsson J. A. (2002) Disruption of estrogen receptor beta gene impairs spatial learning in female mice. Proc Natl Acad Sci U S A. 99, 3996–4001. Walf A. A., Ciriza I., Garcia-Segura L. M., and Frye C. A. (2008) Antisense oligodeoxynucleotides for estrogen receptor-beta and alpha attenuate estradiol’s modulation of affective and sexual behavior, respectively. Neuropsychopharmacology. 33, 431–40. Graham-Lorence S., Amarneh B., White R. E., Peterson J. A., and Simpson E. R. (1995) A three-dimensional model of aromatase cytochrome P450. Protein Sci. 4, 1065–80. Küppers E. and Beyer C. (1998) Expression of aromatase in the embryonic and postnatal mouse striatum. Brain Res Mol Brain Res. 63, 184–8. Connolly P. B., Roselli C. E., and Resko J. A. (1990) Aromatase activity in adult guinea pig brain is androgen dependent. Biol Reprod. 43, 698–703. McEwen B. S. (1980) Gonadal steroids: humoral modulators of nerve-cell function. Mol Cell Endocrinol. 18, 151–64. Jänne O. A. (1990) Androgen interaction through multiple steroid receptors. NIDA Res Monogr. 102, 178–86. Reel J. R., Humphrey R. R., Shih Y. H., Windsor B. L., Sakowski R., Creger P. L., and Edgren R. A. (1979) Competitive progesterone antagonists: receptor binding and biologic activity of testosterone and 19-nortestosterone derivatives. Fertil Steril. 31, 552–61. Ip M. M., Milholland R. J., Kim U., and Rosen F. (1982) Androgen control of cytosol progesterone receptor levels in the MT-W9B transplantable mammary tumor in the rat. J Natl Cancer Inst. 69, 673–81. Markiewicz L., and Gurpide E. (1997) Estrogenic and progestagenic activities of physiologic and synthetic androgens, as measured by in vitro bioassays. Methods Find Exp Clin Pharmacol. 19, 215–22. González-Montelongo M. C., Marín R., and Gómez T, Díaz M. (2010) Androgens are powerful non-genomic inducers of calcium sensitization in visceral smooth muscle. Steroids. 75, 533–8. Patrão M. T., Silva E. J., and Avellar M. C. (2009) Androgens and the male reproductive tract: an overview of classical roles and current perspectives. Arq Bras Endocrinol Metabol. 53, 934–45.

sdfsdf

Chapter 27 Interleukin-2 and the Septohippocampal System: Intrinsic Actions and Autoimmune Processes Relevant to Neuropsychiatric Disorders John M. Petitto, Zhi Huang, Danielle Meola, Grace K. Ha, and Daniel Dauer Abstract The effects of IL-2 on brain development, function, and disease are the result of IL-2’s actions in the peripheral immune system and its intrinsic actions in the central nervous system (CNS). Determining whether, and under what circumstances (e.g., development, acute injury), these different actions of IL-2 are operative in the brain is essential to make significant advances in understanding the multifaceted affects of IL-2 on CNS function and disease, including psychiatric disorders. For several decades, there has been a great deal of speculation about the role of autoimmunity in brain disease. More recently, we have learned a great deal about the role of cytokines on neurobiological processes, and there have been many studies that have found peripheral immune alterations in patients with neurological and neuropsychiatric diseases. Despite a plethora of published literature, almost all of this data in humans is correlative and much of the basic research has understandably relied on simpler models (e.g., in vitro models). Good animal models such as our IL-2 knockout mouse model could provide valuable new insight into understanding how the complex biology of a cytokine such as IL-2 can have simultaneous, dynamic effects on multiple systems (e.g., regulating homeostasis in the brain and immune system, autoimmunity that can affect both systems). Animal models can also provide much needed new data elucidating neuroimmunological and autoimmune processes involved in brain development and disease. Such information may ultimately provide critical new insight into the role of brain cytokines and autoimmunity in prominent neurological and neuropsychiatric diseases (e.g., Alzheimer’s disease, autism, multiple sclerosis, schizophrenia). Key words: Cytokines, Inflammatory response, Autoimmune, Neuropsychiatric disorders, Animal models


433

434

J.M. Petitto et al.

1. Cytokines and the Brain: Some Foundational Background

Novel research findings suggesting that lymphocytes could secrete classic neuropeptides and that peripheral immunization signals hypothalamic neurons, led to research into the role of cytokines as modulators of neural systems (for reviews see refs. 1, 2). Though early work suggested that brain cytokines had redundant functional properties mirroring their actions in the peripheral immune system, it was appreciated that brain cytokines had selective effects on neurons. A seminal study by Zalcman and colleagues advance that view by demonstrating that IL-1, IL-2, and IL-6 exert cytokine-specific changes in monoamine activity in hypothalamus, hippocampus, and prefrontal cortex (3). Such studies have laid the foundation for the growing body of research that has sought to dissect the potential mechanisms whereby different cytokines can influence the neurobiological processes involved in complex domains of behaviors (e.g., learning and memory) and neuropsychiatric diseases. Much of the attention given to the actions of cytokines in the CNS has focused on pathways that subserve learning and memory and related processes (e.g., sensorimotor gating). Hippocampal long-term potentiation (LTP), an important neurobiological mechanism involved in learning and memory storage, is modulated by several cytokines (4). Probably, the most widely studied cytokine involved in learning and memory is IL-1. Pugh and colleagues (5) showed, for example, that I.C.V. administration of IL-1β impaired contextual fear conditioning but did not change auditory-cue fear conditioning (a form of conditioning that is not dependent on the hippocampus). IL-1 mRNA and protein have been found to be increased in the hippocampus following some forms of peripheral immune system activation such as occurs following LPS administration (6), and learning and memory performance deficits induced by systemic administration of LPS can be antagonized by antibody to the IL-1β (7). This is one known mechanism by which pyrogens induce sickness behavior (e.g., fever, decreased activity and exploration, reduced social interaction, depressive signs and symptoms) that impairs cognitive performance (8, 9). Cytokines derived from peripheral immune cells (and perhaps other tissues in some cases) do not readily cross the blood–brain barrier. The mechanisms of cytokine transport differ for each cytokine (e.g., active vs. passive transport) and affects the degree to which they enter the central nervous system (CNS) (10). Goehler and Colleagues (11) have described how the area postrema acts as an anatomical “interface” between the peripheral immune system and the brain. Though less well studied, afferent sensory fibers of the vagus can carry signals initiated by interleukin-1 to brainstem areas (e.g., nucleus tractus solitarius), and vagal sensory activation

27

Autoimmune Processes in Neuropsychiatric Disorders

435

may occur during infection and provide input to the brain and modify behavior (12, 13). The degree to which other cytokines signal the CNS via the vagus, or other afferent nerves in the periphery that allow animals to adapt to their environment, remains to be determined. A number of cytokines and cytokine receptors are synthesized by endogenous brain cells, and exhibit neuromodulatory and neurotrophic effects that are limited to very specific neural pathways. These same cytokines may also possess more general effects on the brain’s endogenous immune-like cells (e.g., microglia). Cytokine receptors are generally more readily detectable in the brain than cytokines themselves, and it is typically challenging to unequivocally detect cytokines and cytokine receptors using immunohistocytochemistry or to reliably detect cytokine receptors using radioligand receptor binding or autoradiography (14). In situ hybridization has revealed the expression of receptors for IL-1 (15), IL-1R antagonist (16), and IL-6R (17), in the rodent dentate gyrus. Gene expression for IL-2 receptors has also been found throughout CA1-CA4 of the hippocampus and dentate gyrus (14, 18–20). Thus, receptors for these cytokines in the hippocampus place them in a position to influence learning and memory and other related behaviors, and some of the same cytokines that have been found to target receptors in the hippocampus have the capacity to modulate neurobiological processes known to mediate these behaviors. The sections that follow focus on IL-2’s actions in the hippocampus and its effects on cognition, and particularly our laboratory’s research using an animal model to disentangle the complex actions of peripheral and central IL-2 on brain development and autoimmunity. Some of the pathophysiology and neuropathology observed in this model is reminiscent of abnormalities seen in certain neuropsychiatric disorders.

2. IL-2, the Septohippocampal System, and Related Links to Learning and Memory

The initial clue that IL-2 had CNS actions came from cancer patients where their behavior was found to be altered after prolonged exposure; the cytokine induced cognitive dysfunction and other untoward neuropsychiatric side effects at doses significantly above what would be considered physiological (21–23). IL-2 gene expression and protein have been identified in the CNS (18, 24). It is localized in discrete areas of perfused normal rat forebrain including the septohippocampal system and related limbic regions (25, 26) and is present in human hippocampal tissue (27). Depending on the methodology and conditions, the data suggest that microglia, astrocytes, and neurons can produce this cytokine

436

J.M. Petitto et al.

(24, 28–30). Moreover, in culture systems, IL-2 provides trophic support to rat neurons from the hippocampus and medial septum (31, 32), and enhances neurite branching (32, 33). There is now a large body of literature indicating that IL-2 may be involved in CNS development, normal brain physiology and homeostatic repair mechanisms, as well as brain dysfunction and neurodegenerative processes. IL-2 has been implicated in the pathogenesis of several major psychiatric and neurological disorders, including those that exhibit neuropathological alterations of the septohippocampal system (34). The predominant effects of IL-2 in the brain occur in the hippocampal formation where receptors for this cytokine are enriched (19, 20, 25, 35, 36). In postmortem hippocampi of Alzheimer’s disease patients IL-2 levels were found to be elevated compared to controls (27). 2.1. Learning and Memory and IL-2

Animal studies subsequent to the aforementioned clinical observation of untoward cognitive side effects in cancer patients treated with IL-2 substantiated the effects of the cytokine on septohippocampal circuitry. It is noteworthy that IL-2 has been shown to be one of the most potent modulators of acetylcholine (ACh) release from rat hippocampal slices (37). In hippocampal slices, IL-2 modulates acetylcholine in a dose-dependent biphasic manner, potentiating release at very low (fM) concentrations and inhibiting release at higher (nM) concentrations, whereas by contrast, cholinergic interneurons in the striatum do not respond to IL-2 (38). As the hippocampus is essential for spatial learning and memory consolidation, IL-2 appears to alter memory processing via interactions with septohippocampal cholinergic nerve terminals in the hippocampus (28) where it can modify long-term potentiation (39) and influence various parameters of cognitive performance in animals (29, 40–44). Aged mice were found to be particularly vulnerable to repeated dosing of IL-2, exhibiting both memory deficits and neuronal damage that was selective to hippocampus (43). We are not aware, however, of a study that has systematically examined if elderly humans, such as those receiving IL-2 immunotherapy for cancer, are more vulnerable to the effects of IL-2 than younger adults. Chronic dosing of IL-2 nonetheless disrupts the working component of spatial memory in nonaged rats in the Morris water-maze (44).

2.2. IL-2 Deficiency Alters Neurotrophic Factors and Septohippocampal Cytoarchitecture

Although the literature has documented many actions of IL-2 in the brain ranging from trophic actions on cultured neurons to the modulation of neurotransmitters and behavior, virtually all of these studies have used the strategy of administering exogenous IL-2. Most of the available data comes from in vitro studies, and to a lesser degree, from studies in animals where IL-2’s effects on various target behaviors or functional neurobiological outcomes (e.g., LTP in vivo) are used to make inferences about the action of the

27


437

endogenous cytokine. Thus, one of the goals of our research has been to study IL-2 knockout mice to better understand the role of endogenous IL-2 on brain function. We found that IL-2 gene deletion results in impaired learning and memory performance, altered sensorimotor gating, and reductions in hippocampal infrapyramidal (IP) mossy fiber length in mice (45). Elegant research in rodent models has shown that mossy fiber length has been shown to correlate positively with spatial learning ability in a number of studies (46–48). Our research has demonstrated that IL-2 knockout mice also have fewer IP granule cells (49). Since IL-2 has been found to have neurotrophic and neuromodulatory actions on hippocampal neurons in vitro, our data suggests that hippocampal IL-2 may provide trophic support for hippocampal neurons. Absence or impairment of brain IL-2 function may play a key role, for example, in the ongoing increase in dentate granule cells during the first year of life (50, 51) and effect the integrity of axons in the dentate gyrus (52). IL-2 knockout mice had significantly reduced concentrations of brain derived neurotrophic factor (BDNF) protein and increased concentrations of nerve growth factor (NGF) in the hippocampus compared to wild-type littermates (where possible in our work, we attempt to compare littermates so that intrauterine and postnatal experience is controlled). Although our research had shown that receptors for IL-2 are enriched in the hippocampus, including the granule cell layer (GCL) of the dentate gyrus (DG) (19, 20), it was unclear in the literature if IL-2’s trophic effects on neurons in vitro (31–33) operate in vivo, or if IL-2 could modify the expression of brain neurotrophic factors. In fact, we found that the observed differences in the level of BDNF were consistent with our hypothesis that we would find reductions in trophic factors important to hippocampal development and maintenance. BDNF plays a role in the maintenance and repair of septal cholinergic neurons (53–55), can implement a positive feedback mechanism with these neurons to enhance the release of acetylcholine (56), and can also modulate postnatal neurogenesis (57, 58), thus potentially impacting granule cell number. The mechanism of the interaction between IL-2 gene deletion and the reduction of BDNF levels remains unclear. Though BDNF is expressed in the peripheral immune system by lymphocytes, IL-2 does not stimulate its production or release in these cells. IL-2 can, however, upregulate the expression of TrkB, the receptor for BDNF, in lymphocytes (59). Furthermore, some evidence suggests that BDNF can stimulate a positive feedback mechanism of its own via the TrkB receptor in hippocampal neurons (60, 61). IL-2 may therefore potentially lead to a downregulation of the TrkB receptor, thereby partially inhibiting the positive feedback production of BDNF. Our data suggest that IL-2 may have direct and/or indirect effects on BDNF.

438

J.M. Petitto et al.

By contrast to BDNF, NGF protein levels were actually increased in the IL-2 knockout mice. In keeping with the reduction in medial septal cholinergic survival we observed in IL-2 knockout mice (49, 62), it is possible that the hippocampal target neurons in these animals may produce higher protein levels of NGF as a compensatory response. Moderate lesions of rat septohippocampal projections have been shown to result in increased expression of mRNA for NGF, but not BDNF in hippocampal target cells (63). Interestingly, the imbalance that we see in IL-2 knockout mice between BDNF and NGF levels (decreased BDNF and increased NGF concentrations) is also found in the postmortem hippocampus of Alzheimer’s disease brains (64).

3. Peripheral Autoimmunity and the Septohippocampal System

Autoimmunity has been attributed to various clinical syndromes and diseases affecting the CNS. With the exception of multiple sclerosis and myasthenia gravis, however, surprisingly little is known about specific factors and pathways that govern CNS autoimmunity. IL-2 has been implicated in the pathogenesis of CNS autoimmune disease, multiple sclerosis, as well as in schizophrenia and Alzheimer’s disease (65–67). Research examining the actions of IL-2 in the brain has focused almost exclusively on the cytokine’s neuromodulatory and neurotrophic properties. In the immune system, IL-2 is indispensable for maintaining immunological homeostasis (e.g., self-tolerance, T regulatory cell development and function). It is now appreciated that IL-2 is essential for normal T regulatory cell function, which is critical in self-tolerance (68). Targeted gene deletion studies in mice have established that IL-2 deficiency produces the spontaneous development of autoimmune disease affecting several organ systems (e.g., intestines, heart) characterized by T cell infiltration, and in some organs autoantibody deposition as well (69–71). Until recently, it was unknown whether IL-2 deficiency results in the spontaneous development of CNS autoimmunity. Our data and others in the literature led us to hypothesize that IL-2 deficient mice develop a unique form of autoimmunity that selectively targets septal cholinergic projection neurons. Autoimmune-mediated loss of brain septal cholinergic neurons has been found in animals immunized with septal cholinergic hybrid cells (72). As noted above, we had found previously that choline acetyltransferase (ChAT)-positive neurons in the medial septum/vertical diagonal band of Broca (MS/vDB) of IL-2 KO and IL-2 WT littermates on the C57BL/6 background differed as a function of age (73, 74). At 8–12 weeks of age, IL-2 KO mice show considerable evidence of peripheral autoimmunity (e.g., marked splenomegaly). By contrast,

27


439

3-week-old IL-2 KO mice do not yet develop autoimmunity. We hypothesized that the selective loss of septal cholinergic neurons in IL-2 KO mice (i.e., versus no differences compared to WT mice for ChAT-positive neurons in the striatum or in GABAergic neurons in the MS/vDB) was due to autoimmune mediated neurodegeneration that occurs postnatally between weaning and early adulthood. (As noted earlier, medial septal development is essentially complete by embryonic day 17) (75). We quantified CD3+ T cells in the septum, hippocampus, and cerebellum of IL-2 KO and IL-2 WT mice at ages ranging from 2 to 14 weeks. T cells infiltrated the brains of IL-2 deficient mice, but were not selective for the septum. Brain T lymphocyte levels in IL-2 KO mice positively correlated with the degree of peripheral autoimmunity. We did not detect CD19+ B lymphocytes, IgG-positive lymphocytes or IgG deposition indicative of autoantibodies in the brains of IL-2 KO mice. We are currently conducting studies to determine the intrinsic neuroimmunological factors (i.e., chemokines, chemoattractant cytokines) involved in the increased brain T cell trafficking in IL-2 KO mice.

4. The Neuroimmunology of IL-2: Neurological and Neuropsychiatric Diseases

Early neurodevelopmental alterations associated with IL-2 dysregulation may account for pathophysiological abnormalities seen decades later in the mature brain of individuals with neurodevelopmental diseases such as schizophrenia and autism. Some current etiological theories pose that prenatal viral infection and/or the maternal immune response to such a putative agent may serve as an environmental trigger that elicits neuroimmunological and neurobiological changes leading to the expression of schizophrenia in individuals with genetic loading for the disorder. The normal timing during which IL-2 may stimulate neuronal growth and migration during early development may be modified by a developmental event like viral infection or birth trauma in a genetically susceptible individual. In the hippocampus, for example, where IL-2 receptors are enriched, this could contribute to the alterations in this region such as the abnormal orientation of subsets of hippocampal neurons found in the postmortem brains of individuals with schizophrenia. Immunological disturbances in the peripheral immune system during development could also contribute to abnormalities in neurodevelopment. Using animal models to determine when and under what conditions (e.g., development, injury) these different actions of IL-2 are operative in the brain may help to advance our knowledge of the neuroimmunology of several major mental disorders. For several decades, there has been a great deal of speculation about the role of autoimmunity in brain disease. More recently, in

440

J.M. Petitto et al.

the field of neuroimmunology we have learned much about the role of cytokines on neurobiological processes, and there have been many studies that have found peripheral immune alterations in patients with neurological and neuropsychiatric diseases. Despite a plethora of published studies, almost all of this data in humans is correlative and much of the basic research has understandably relied on simpler models (e.g., in vitro models). Thus, informative animal models such as our IL-2 knockout mouse model could provide valuable new insight in understanding how the complex biology of a cytokine such as IL-2 can have simultaneous, dynamic effects on multiple systems (e.g., regulating homeostasis in the brain and immune system, autoimmunity that can affect both systems). We are currently breeding novel congenic mice with and without the IL-2 gene and/or the Rag2 gene (leading to immunodeficiency) and combining these with various leukocyte adoptive transfer manipulations to dissect the relative contributions of IL-2 in the brain versus the peripheral immune system on brain development and neurodegeneration. These experiments should provide essential new information about brain IL-2’s intrinsic actions in the septohippocampal system in vivo. This work may also help advance the field of brain autoimmunity by determining how IL-2 deficiency-induced autoimmune T lymphocytes interact with endogenous brain cells to alter function and promote disease. Moreover, animal models like this may also provide much needed new data elucidating neuroimmunological and autoimmune processes involved in prominent neurological and neuropsychiatric diseases (e.g., multiple sclerosis, Alzheimer’s disease, schizophrenia).

Acknowledgments Funding for this study was provided by NIH RO1NS055018 and RO1NS048472. References 1. Besedovsky, H.O., Del Rey, A., Klusman, I., Furukawa, H., Monge Arditi, G., Kabiersch, A. (1991) Cytokines as modulators of the hypothalamus-pituitary-adrenal axis, Journal of Steroid Biochemistry and Molecular Biology 40, 613–618. 2. Blalock, J.E. (1994) The syntax of immuneneuroendocrine communications, Immunology Today 15, 504–511. 3. Zalcman, S., Green-Johnson, J.M., Murray, L., Nance, D.M., Dyck, D., Anisman, H., Greenberg, A.H. (1994) Cytokine-specific

central monoamine alterations induced by interleukin-1, -2, and -6, Brain Res 643, 40–49. 4. Jankowsky, J., Patterson, P. (1999) Cytokine and growth factor involvement in long-term potentiation, Molecular and Cellular Neuroscience 14, 273–286. 5. Pugh, C.R., Kumagawa, K., Fleshner, M., Watkins, L.R., Maier, S.F., Rudy, J.W. (1998) Selective effects of peripheral lipopolysaccharide administration on contextual and auditory-cue fear conditioning, Brain, behavior, and immunity 3, 212–29.

27


6. Laye, S., Parnet, P., Goujon, E., Dantzer, R. (1994) Peripheral administration of lipopolysaccharide induces the expression of cytokine transcripts in the brain and pituitary of mice, Brain research. Molecular brain research 27, 157–62. 7. Gibertini, M., Newton, C., Klein, T.W., Friedman, H. (1995) Legionella pneumophilainduced visual learning impairment reversed by anti-interleukin-1 beta, Proceedings of the Society for Experimental Biology and Medicine. Society for Experimental Biology and Medicine 210, 7–11 8. Aubert A., Vega C., Dantzer R., Goodall, G. (1995) Pyrogens specifically disrupt the acquisition of a task involving cognitive processing in the rat, Brain, behavior, and immunity 9, 129–48. 9. Dantzer, R., Bluthe, R.M., Gheusi, G., Cremona, S., Laye, S., Parnet, P., Kelley, KW. (1998) Molecular basis of sickness behavior, Annals of the New York Academy of Sciences 856, 132–138. 10. Pan, W., Kastin, A.J. (1999) Penetration of neurotrophins and cytokines across the bloodbrain/blood-spinal cord barrier, Advanced Drug Delivery Review 36, 291–298. 11. Goehler, L.E., Erisir, A., Gaykema, R.P. (2006) Neural-immune interface in the rat area postrema, Neuroscience 140, 1415–34. 12. Goehler, L.E., Lyte, M., Gaykema, R.P. (2007) Infection-induced viscerosensory signals from the gut enhance anxiety: implications for psychoneuroimmunology, Brain Behav Immun 21, 721–26. 13. Maier, S.F., Watkins, L.R. (1998) Cytokines for psychologists: Implications of bidirectional immune-to-brain communication for understanding behavior, mood and cognition, Psychological Review 105(1), 83–107. 14. Petitto, J.M., Huang, Z. (2001) Cloning the full-length IL-2/15 receptor-β cDNA sequence from mouse brain: evidence of enrichment in hippocampal formation neurons, Regulatory Peptides 98, 77–87. 15. Cunningham, E.T.J., Wada, E., Carter, D.B., Tracey, D.E., Battey, J.F., and De Souza, E.B. (1992) In situ histochemical localization of type I interleukin-1 receptor messenger RNA in the central nervous system, pituitary, and adrenal gland of the mouse, Journal of Neuroscience 12, 1101–1114. 16. Licinio, J., Wong, M.L., and Gold, P.W. (1991) Localization of interleukin-1 receptor antagonist mRNA in rat brain, Endocrinology 129, 562–564. 17. Schobitz, B., Voorhuis, D.A., De Kloet, E.R. (1992) Localization of interleukin-6 mRNA and interleukin-6 receptor mRNA in rat brain, Neuroscience Letters 136, 189–192.

441

18. Lapchak, P.A. (1992) A role for interleukin-2 in the regulation of striatal dopaminergic function, Neuroreport 3, 165–168. 19. Petitto, J.M., Huang, Z. (1994) Molecular cloning of a partial cDNA of the interleukin-2 receptor-β in normal mouse brain: in situ localization in the hippocampus and expression by neuroblastoma cells, Brain Research 650, 140–145. 20. Petitto, J.M., Huang, Z., Raizada, M., Rinker, C.M., McCarthy, D.B. (1998) Molecular cloning of the cDNA coding sequence of IL-2 receptor-γ (γc) from human and murine forebrain: expression in the hippocampus in situ and by brain cells in vitro, Molecular Brain Research 53, 152–62. 21. Denicoff, K.D., Rubinow, D.R., Papa, M.Z., Simpson, C., Seipp, C.A., Lotze, M.T., Chang, A.E., Rosenstein, D., and Rosenberg, S.A. (1987) The neuropsychiatric effects of treatment with interleukin-2 and lymphokine-activated killer cells, Annals of Internal Medicine 107, 293–300. 22. West, W.H., Tauer, K.W., Yannelli, J.R., Marshall, G.D., Orr, D.W., Thurman, G.B., and Oldham, R.K. (1987) Constant-infusion recombinant interleukin-2 in adoptive immunotherapy of advanced cancer, New England Journal of Medicine 316, 898–905. 23. Capuron, L., Ravaud, A., Radat, F., Dantzer, R., Goodall, G. (1998) Effects of interleukin-2 and alpha interferon cytokine immunotherapy on the mood and cognitive performance of cancer patients, Neuroimmunomodulation 22, 9. 24. Eizenberg, O., Faber-Elman, A., Lotan, M. and Schwartz, M. (1995) Interleukin-2 Transcripts in Human and Rodent Brains: Possible Expression by Astrocytes, Journal of Neurochemistry 64, 1928–1936. 25. Lapchak, P.A., Araujo, D.M., Quirion, R., and Beaudet, A. (1991) Immunoautoradiographic localization of interleukin 2-like immunoreactivity and interleukin 2 receptors (Tac antigenlike immunoreactivity) in the rat brain, Neuroscience 44, 173–184. 26. Villemain, F., Owens, T., Renno, T., Beaudet, A. (1991) Localization of mRNA for interleukin-2 (IL-2) in mouse brain by in situ hybridization, Soc. Neurosci. Abstr. 17, 1199. 27. Araujo, D.M., Lapchak, P.A. (1994) Induction of immune system mediators in the hippocampal formation in Alzheimer’s and Parkinson’s diseases: selective effects on specific interleukins and interleukin receptors. Neuroscience 61, 745–754. 28. Hanisch, U.K., Quirion, R. (1996) Interleukin-2 as a neuroregulatory cytokine, Brain Research Reviews 21, 246–284. 29. Hanisch, U., Neuhaus, J., Rowe, W., VanRossum, D., Möller T., Kettenmann H., and

442

30.

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

J.M. Petitto et al. Quirion, R. (1997) Neurotoxic consequences of central long-term administration of interleukin-2 in rats, Neuroscience 79, 799–818. Labuzek, K., Kowalski, J., Gabryel, B., Herman, Z.S. (2005) Chlorpromazine and loxapine reduce interleukin-1beta and interleukin-2 release by rat mixed glial and microglial cell cultures, Eur Neuropsychopharmacol 15, 23–30. Awatsuji, H., Furukawa, Y., Nakajima, M., Furukawa, S., Hayashi, K. (1993) Interleukin-2 as a neurotrophic factor for supporting the survival of neurons cultured from various regions of fetal rat brain, Journal of Neuroscience Research 35, 305–311. Sarder, M., Saito, H., Abe, K. (1993) Interleukin-2 promotes survival and neurite extension of cultured neurons from fetal rat brain, Brain Research 625, 347–350. Sarder, M., Abe, K., Saito, H., Nishiyama, N. (1996) Comparative effect of IL-2 and IL-6 on morphology of cultured hippocampal neurons from fetal rat brain, Brain Research 715, 9–16. Hanisch, U., Quirion, R. (1996) Interleukin-2 as a neuroregulatory cytokine, Brain Res. Rev. 21, 246–284. Araujo, D.M., Lapchak, P.A., Collier, B., Quirion, R. (1989) Localization of interleukin-2 immunoreactivity and interleukin-2 receptors in the rat brain: interaction with the cholinergic system, Brain Res 498, 257–266. Hanisch, U., Neuhaus, J., Rowe, W., VanRossum, D., Möller, T., Kettenmann, H., and Quirion, R. (1997) Neurotoxic consequences of central long-term administration of interleukin-2 in rats, Neurosci. 79, 799–818. Hanisch, U.K., Seto, D., and Quirion, R. (1993) Modulation of hippocampal acetylcholine release: a potent central action of interleukin-2, Journal of Neuroscience 13, 3368–3374. Seto, D., Kar, S., Quirion, R. (1997) Evidence for direct and indirect mechanisms in the potent modulatory action of interleukin-2 on the release of acetylcholine in rat hippocampal slices, British journal of pharmacology 120, 1151–1157. Tancredi, V., Zona, C., Velotti, F., Eusebi, F., Santoni, A. (1990) Interleukin-2 suppresses established long-term potentiation and inhibits its induction in the rat hippocampus, Brain Research 525, 149–151. Bianchi, M., and Panerai, A.E. (1993) Interleukin-2 enhances scopolamine-induced amnesia and hyperactivity in the mouse, Neuroreport 4, 1046–1048. Bianchi, M., Ferrario, P., Zonta, N., Panerai, A.E. (1995) Effects of interleukin-1 beta and interleukin-2 on amino acids levels in mouse

42.

43.

44.

45.

46.

47.

48.

49.

50.

51.

52.

53.

cortex and hippocampus, Neuroreport 6, 1689–1692. Mennicken, F., Quirion, R. (1997) Interleukin-2 increases choline acetyltransferase activity in septal-cell cultures, Synapse 26, 175–183. Nemni, R., Iannaccone, S., Quattrini, A., Smirne, S., Sessa, M., Lodi, M., Erminio C., and Canal N. (1992) Effect of chronic treatment with recombinant interleukin-2 on the central nervous system of adult and old mice, Brain Research 591, 248–252. Lacosta, S., Merali, Z., Anisman, H. (1999) Influence of acute and repeated interleukin-2 administration on spatial learning, locomotor activity, exploratory behaviors, and anxiety, Behav Neurosci 113, 1030–1041. Petitto, J.M., McNamara, R., Gendreau, P.L., Huang, Z., Jackson, A. (1999) Impaired learning and memory and altered hippocampal neurodevelopment resulting from IL-2 gene deletion, Journal of Neuroscience Research 56, 441–446. Schöpke, R., Wolfer, D.P., Lipp, H.P., LeisingerTrigona, M.C. (1991) Swimming navigation and structural variations of the infrapyramidal mossy fibers in the hippocampus of the mouse, Hippocampus 3, 315–28. Schwegler, H., Crusio, W.E., Lipp, H.P., Heimrich, B. (1988) Water-maze learning in the mouse correlates with variation in hippocampal morphology, Behav Genet 18, 153–165. Schwegler, H., Crusio, W.E. (1995) Correlations between radial-maze learning and structural variations of septum and hippocampus in rodents, Behav Brain Res 67, 29–41. Beck, R.D., Jr., King, M.A., Ha, G.K., Cushman, J.D., Huang, Z., Petitto, J.M. (2005) IL-2 deficiency results in altered septal and hippocampal cytoarchitecture: relation to development and neurotrophins, J Neuroimmunol 160, 146–153. Altman, J., Bayer, S.A. (1990) Migration and distribution of two populations of hippocampal granule cell precursors during the perinatal and postnatal periods, J Comp Neurol 301, 365–381. Cameron, H.A., McKay, R.D. (2001) Adult neurogenesis produces a large pool of new granule cells in the dentate gyrus, J Comp Neurol 435, 406–417. Schwegler, H., Crusio, W.E., Lipp, H.P., Brust, I., Mueller, G.G. (1991) Early postnatal hyperthyroidism alters hippocampal circuitry and improves radial-maze learning in adult mice, J Neurosci 11, 2102–2106. Alderson, R.F., Alterman, A.L., Barde, Y.A., Lindsay, R.M. (1990) Brain-derived neurotrophic

27

54.

55.

56.

57.

58.

59.

60.

61.

62.

63.


factor increases survival and differentiated functions of rat septal cholinergic neurons in culture, Neuron 5, 297–306. Morse, J.K., Wiegand, S.J., Anderson, K., You, Y., Cai, N., Carnahan, J., Miller, J., DiStefano, P.S., Altar, C.A., Lindsay, R.M., et al. (1993) Brain-derived neurotrophic factor (BDNF) prevents the degeneration of medial septal cholinergic neurons following fimbria transection, J Neurosci 13, 4146–4156. Ward, N.L., Hagg, T. (2000) BDNF is needed for postnatal maturation of basal forebrain and neostriatum cholinergic neurons in vivo, Exp Neurol 162, 297–310. Knipper, M., da Penha Berzaghi, M., Blochl, A., Breer, H., Thoenen, H., Lindholm, D. (1994) Positive feedback between acetylcholine and the neurotrophins nerve growth factor and brain-derived neurotrophic factor in the rat hippocampus, Eur J Neurosci 6, 668–67 Larsson, E., Mandel, R.J., Klein, R.L., Muzyczka, N., Lindvall, O., Kokaia, Z. (2002) Suppression of insult-induced neurogenesis in adult rat brain by brain-derived neurotrophic factor, Exp Neurol 177, 1–8. Lee, J., Duan, W., Mattson, M.P. (2002) Evidence that brain-derived neurotrophic factor is required for basal neurogenesis and mediates, in part, the enhancement of neurogenesis by dietary restriction in the hippocampus of adult mice, J Neurochem 82, 1367–1375. Besser, M., Wank, R. (1999) Cutting edge: clonally restricted production of the neurotrophins brain-derived neurotrophic factor and neurotrophin-3 mRNA by human immune cells and Th1/Th2-polarized expression of their receptors, J Immunol 162, 6303–6306. Canossa, M., Griesbeck, O., Berninger, B., Campana, G., Kolbeck, R., Thoenen, H. (1997) Neurotrophin release by neurotrophins: implications for activity-dependent neuronal plasticity, Proc Natl Acad Sci USA 94, 13279–13286. Saarelainen, T., Vaittinen, S., Castren, E. (2001) trkB-receptor activation contributes to the kainate-induced increase in BDNF mRNA synthesis, Cell Mol Neurobiol 21, 429–435. Beck, R.D., Jr., King, M.A., Huang, Z., Petitto, J.M. (2002) Alterations in septohippocampal cholinergic neurons resulting from interleukin-2 gene knockout, Brain Res 955, 16–23. Hellweg, R., Humpel, C., Lowe, A., Hortnagl, H. (1997) Moderate lesion of the rat cholinergic septohippocampal pathway increases hippocampal nerve growth factor synthesis: evidence for long-term compensatory changes?, Brain Res Mol Brain Res 45, 177–181.

443

64. Hock, C., Heese, K., Hulette, C., Rosenberg, C., Otten, U. (2000) Region-specific neurotrophin imbalances in Alzheimer disease: decreased levels of brain-derived neurotrophic factor and increased levels of nerve growth factor in hippocampus and cortical areas, Arch Neurol 57, 846–851. 65. Merrill, J.E. (1990) Interleukin-2 effects in the central nervous system, Annals of the New York Academy of Sciences 594, 188–199. 66. Quirion, R., Aubert, I., Robitaille, Y., Gauthier, S., Araujo, D.M., Chabot, J.G. (1990) Neurochemical deficits in pathological brain aging: specificity and possible relevance for treatment strategies, Clinical neuropharmacology 13, 73–80. 67. Zalcman, S.S. (2002) Interleukin-2-induced increases in climbing behavior: inhibition by dopamine D-1 and D-2 receptor antagonists, Brain research 944, 157–164. 68. Turka, L.A., Walsh, P.T. (2008) IL-2 signaling and CD4+ CD25+ Foxp3+ regulatory T cells, Front Biosci 13, 1440–1446. 69. Horak, I., Lohler, J., Ma, A., Smith, K.A. (1995) Interleukin-2 deficient mice: a new model to study autoimmunity and self-tolerance, Immunological reviews 148, 35–44. 70. Kundig, T.M., Schorle, H., Bachmann, M.F., Hengartner, H., Zinkernagel, R.M., Horak, I. (1993) Immune responses in interleukin-2deficient mice, Science 262, 1059–1061. 71. Schorle, H., Holtschke, T., Hunig, T., Schimpl, A., Horak, I. (1991) Development and function of T cells in mice rendered interleukin-2 deficient by gene targeting, Nature 352, 621–624. 72. Kalman, J., Engelhardt, J.I., Le, W.D., Xie, W., Kovacs, I., Kasa, P., Appel, S.H. (1997) Experimental immune-mediated damage of septal cholinergic neurons, Journal of neuroimmunology 77, 63–74. 73. Beck, R.D., Jr., King, M.A., Ha, G.K., Cushman, J.D., Huang, Z., Petitto, J.M. (2005) IL-2 deficiency results in altered septal and hippocampal cytoarchitecture: relation to development and neurotrophins, Journal of neuroimmunology 160, 146–153. 74. Beck, R.D., Jr., King, M.A., Huang, Z., Petitto J.M. (2002) Alterations in septohippocampal cholinergic neurons resulting from interleukin-2 gene knockout, Brain research 955, 16–23. 75. Semba, K., Fibiger, H.C. (1988) Time of origin of cholinergic neurons in the rat basal forebrain, The Journal of comparative neurology 269, 87–95.

sdfsdf

Chapter 28 Experimental Schizophrenia Models in Rodents Established with Inflammatory Agents and Cytokines Hiroyuki Nawa and Kiyofumi Yamada Abstract Immune inflammatory processes in prenatal and perinatal stages are suggested to play crucial roles in the vulnerability to schizophrenia. Based upon this immune inflammatory hypothesis for schizophrenia, we have established animal models for this illness by subcutaneously administering cytokines or proinflammatory agents to rodent neonates. These models exhibit various schizophrenia-like behavioral abnormalities after puberty, most of which are sensitive to various antipsychotics. The experimental procedures are all simple and easily utilized by researchers unfamiliar with these models. The behavioral changes are reproducible and remarkable but do not accompany learning deficits. The molecular and cellular targets of these agents have also been investigated and partially characterized, such as the cortical GABAergic system, midbrain dopaminergic system and hippocampal glutamate system. In this chapter, we introduce the details of the procedure and discuss the potential application of these animal models to drug development for schizophrenia. Key words: Epidermal growth factor, Inflammation, Neuregulin-1, Polyriboinosinic-polyribocytidilic acid, Neonate, Prepulse inhibition, Rodent, Schizophrenia, Strain

1. Introduction Proinflammatory molecules/cytokines and their receptors are distributed in various brain regions and influence synaptic transmission as well as neural development. The abnormality in their signaling in human brain is, therefore, likely to lead to perceptual and cognitive impairments such as schizophrenia. Recent epidemiological investigations as well as genetic studies also support this idea. Maternal stress, viral infection, and obstetric complication, which induce inflammatory processes and cytokine gene expression, are suggested to increase the risk for schizophrenia and its related disorders. Three large-scale genome-wide association studies (GWAS) all revealed a


445

446

H. Nawa and K. Yamada

genetic association between a major histocompatibility complex (MHC) region at 6p and schizophrenia. Despite increasing circumstantial evidence for immune inflammatory involvement in schizophrenia, the direct impact of inflammatory agents and cytokines on brain development and cognitive/behavioral traits remains to be characterized experimentally. In the present study, we introduce schizophrenia animal models that can be prepared by simply exposing neonatal rats or mice to various inflammatory agents or cytokines (1–5). The correspondence of fetal development progression in different species is compared using database-driven websites. The programs are based on statistical algorithms that integrate hundreds of empirically derived developing neuronal events in ten mammalian species, including rats, mice, and humans (http://translatingtime.net/). For example, the neurodevelopmental stage of neonatal mice on postnatal day (P) 2–6 roughly corresponds to 20- to 25-week gestation for cortical development and 15–18 weeks for limbic development in humans. The brain developmental stage of newborn rats is roughly equivalent to that of human embryos at 18- to 21-week gestation. Thus, neonatal rodents correspond to the second trimester of pregnancy in humans, when maternal stress and viral infection are suggested to increase the risk of schizophrenia or related psychiatric diseases. In comparison with the protocol for maternal immune challenge during rodent pregnancy, the neonatal immune treatment enables us to assess the direct impact of immune inflammatory agents on host animals without the risk for the miscarriage of offspring following inflammatory stress.


With the given gene–environment interactions, not all strains of mice or rats exhibit behavioral abnormalities following neonatal injection of cytokines or polyriboinosinic-polyribocytidilic acid (polyI:C): 1. Strains must be carefully selected as indicated in Table 1 (see Note 1). 2. Dams of late pregnancy are purchased from venders.

2.2. Proinflammatory Agent and Cytokines

PolyI:C is a synthetic analog of double-stranded RNA that leads to the pronounced but time-limited production of proinflammatory cytokines after administration: 1. Poly I:C (Sigma-Aldrich; St. Louis, MO) dissolved in pyrogenfree saline at a concentration of 0.5 mg/mL (4).

28

Schizophrenia Modeling with Inflammatory Agents

447

Table 1 Differential effects of neonatal EGF and poly I:C treatment on neurobehavioral development Treatment

Strain

LM

Startle

PPI

NORT

PolyI:C PolyI:C

CD1(ICR) C57BL/6

= =

= =

L =

L L

EGF EGF EGF EGF

C57BL/6 DBA/2 ddY C3H/He

= H L =

= H = H

L L = =

ND ND ND ND

ND not determined, PPI prepulse inhibition, LM locomotor activity, NORT novel object recognition (24-h retention) “=” Represents no significant change from vehicle-treated animals. “H” and “L” indicate increased and decreased performance, respectively

2. Recombinant human EGF (Sigma-Aldrich) and (Funakoshi; Tokyo, Japan). One milligram of EGF is sufficient for approximately eight rat models or 60 mouse models (1, 2). 3. The full form of recombinant NRG1 (rNRG1) (type1 β1, GenWay Biotech; San Diego, USA), or from the author (HN) upon request (3), and given to mouse or rat pups at the same dosage as EGF (see Note 2). rNRG1 (dissolved in phosphatebuffered saline; pH 7.3) at a concentration of 40–80 μg/mL and sterilized by passing though a 0.45-μm filter (see Note 3).

3. Methods 3.1. Animals

3.2. Poly I:C Administration

As dams are very nervous soon after delivery (P1), neonatal treatment is initiated from P2. Accordingly, it is better to minimize cage exchanges until the treatment is fully completed. In general, littermates of a dam are separated into two groups and allocated to either an experimental group or control vehicle group. Animals are weaned at P21, and divided by gender at P28. Both groups are derived from at least three different litters to preclude possible differences in individual maternal behavior as a mitigating factor in any subsequent long-lasting changes induced in the offspring. 1. Measure the body weight of each pup at P2, which generally ranges from 2 g (P2) to 3.5 g (P6) for a mouse pup. 2. Mark pups in the experimental group by cutting the ear.

448


3. Using a Hamilton microsyringe (100 μL) with a 5-gauge needle, inject polyI:C solution (0.5 mg/mL),or its vehicle, subcutaneously at the nape of the neck in a volume of 10 μL/g body weight (i.e., a dose of 5 mg/kg). 4. Return pups to their dam immediately after injection. 5. Repeat the injection daily until the pup is P6. 3.3. EGF/NRG1 Administration

1. Measure the body weight of each pup at P2, which generally ranges from 8 g (P2) to 20 g (P10) for a rat pup and from 1.5 g (P2) to 5 g (P10) for a mouse pup. 2. Mark pups in the experimental group by cutting the ear. 3. From the given body weight, calculate the volume of EGF or NRG solution required (0.8–1.0 μg/g body weight). 4. Using a 70% ethanol soaked cotton ball, sterilize the skin at the nape of the neck. 5. Inject EGF/NRG1 solution (0.10–0.25 mL for rats, 0.04– 0.12 mL for mice), or the same volume of vehicle, under the skin at the nape of the neck. 6. Check eyelid opening and tooth eruption (see Note 4). 7. Return pups to their dam immediately after injection. 8. Repeat the injection daily until the pup is P10.

3.4. Neurobehavioral Analysis

1. Prepulse inhibition (PPI) test: Animals are placed in a standard PPI test chamber (San Diego Instruments, San Diego, CA) under moderately bright light conditions (180 lux) and allowed to habituate for 10 min. The pulse used is 120 dB, background noise is 60 dB, and the prepulses are 69–81 dB (1, 4). 2. Social interaction: Mice or rats are individually housed in a home cage for 2 days before the test. The duration of social interaction, aggression, and escape behaviors in response to an unfamiliar intruder mouse is analyzed for 5 min, and this trial is repeated four times with an interval of 30 min between trials (1, 4). 3. Novel object recognition test (NORT): Mice are individually habituated to an open-box (in cm, 30 × 30 × 35 high) for 3 days. During the training session, two novel objects are placed in the open field and the animal is allowed to explore for 10 min under moderate light conditions (10 lux) (4). The time spent exploring each object is recorded. During the retention sessions, the animals are placed back into the same box 1 or 24 h after the training session, one of the familiar objects used during training is replaced by a novel object, and the mice are allowed to explore freely for 5 min. The preference index in the retention session and the ratio of the amount of time spent exploring the novel object over the total time spent exploring both objects is used to measure cognitive function.

28

3.5. Neurobehavioral Consequences


449

1. PolyI:C-treated mice: Neonatal polyI:C treatment in CD1 or C56BL/6 mice transiently increases gene expression of interferon-induced transmembrane protein 3 (IFITM3) in the hippocampus, suggesting a proinflammatory response in the brains of neonatal mice following polyI:C treatment (4). PolyI:C-treated CD1 mice exhibit anxiety-like behavioral changes in an open-field test as well as impairments in social interaction, PPI of the acoustic startle response and object recognition memory in the NORT in adulthood. C56BL/6 mice are generally resistant to polyI:C compared with CD1 mice (Table 1). Haloperidol ameliorates PPI deficits but has no effects on other behavioral abnormalities, whereas clozapine improves all of behavioral deficits in polyI:C-treated CD1 mice. Depolarization-evoked glutamate release in the hippocampus is impaired in polyI:C-treated CD1 mice, suggesting a dysfunction of glutamatergic neurotransmission. Transgenic mice overexpressing a dominant-negative form (DN-DISC1) of disrupted-in-schizophrenia 1 (DISC1), a susceptibility gene for schizophrenia, are an important genetic animal model of mental disorders such as schizophrenia (5). Neonatal polyI:C treatment in DN-DISC1 mice results in synergistic impacts on object recognition memory, spontaneous alternation in the Y-maze, social interaction, and MK-801induced hyperactivity in adulthood as compared to wild-type littermates (C57BL/6 mice) (Table 2). Furthermore, the polyI:C treatment also results in a dramatic reduction of parvalbumin-positive interneurons in the medial prefrontal cortex, one of the best hallmarks for schizophrenia. 2. EGF-treated animals: Neonatal EGF treatment promotes the development of nigrastriatal dopaminergic neurons and increases dopamine synthesis and metabolism (1). In the adult stage, but not in the juvenile stage, EGF-treated rats exhibit an abnormally reduced PPI score (Table 2). In parallel, the abnormality in startle responses worsens during development. In addition, neonatal exposure to EGF persistently affects the social interaction score, but atypical antipsychotics such as clozapine and risperidone ameliorate almost all of their behavioral abnormalities. The EGF-treated animals exhibit smaller brain sizes without any apparent neuronal degeneration (2). The neurobehavioral consequences of EGF treatment differ considerably among the mouse strains, however (Table 1) (2). Neonatal administration of EGF increases locomotion in DBA/2 mice, whereas it decreases behavioral activity in DDY mice. EGF effects on PPI also depend upon the genetic background of the mouse. Only DBA/2 and C57BL/6 mice exhibit PPI defects at the adult stage. Similarly, neonatal EGF treatment produces diverse influences across the strains on

450


Table 2 Neonatal exposure to cytokines and polyI:C on neurobehavioral development in rodents

Poly I:Ca b

PolyI:C/DN-DISC1 EGF

c

NRG-1d

LM

Startle PPI

SI

MAP

MK-801

=

=

Low

Low

=

=

=

=

=

Low

=

Higher

=

High

Low

Low

Higher

ND

=

=

Low

Low

Higher

ND

EGF epidermal growth factor, NRG neuregulin-1 type 1 β1, LM locomotor activity, PPI prepulse inhibition, SI social interaction, MAP methamphetamine sensitivity, MK-801 sensitivity to the NMDA receptor antagonist “=” Represents no significant change from vehicle-treated animals a Tested in CD1 (ICR) mice b Tested in C57/BL6N c Tested in SD rats d Tested in C57BL/6N mice

other behavioral and cognitive functions, such as startle response, contextual fear conditioning, and tone-dependent learning. 3. NRG1-treated C57BL/6 mice: Neonatal NRG1 treatment similarly promotes the postnatal development of dopaminergic neurons and perturbs behavioral development (4). There are significant behavioral impairments in PPI and social interaction (Table 2). In adulthood, NRG1-treated mice exhibit sustained increases in dopamine metabolism and hyperinnervation in the frontal cortex as well as higher sensitivity to methamphetamine. However, learning ability and basal locomotor activity are preserved in this animal model.

4. Notes 1. If you want to make the model in C57BL/6 mice, we highly recommend that researchers use an NIH subline of C57BL/6N mice rather than a Jackson subline of C57BL/6J. C57BL/6J mice tend to display larger litter to litter differences in behavioral traits. 2. Alternatively, the EGF domain peptide of NRG1β1 (heregulin β1) obtained from Peprotech (Rocky Hill, NJ, USA) and given to pups at a dose of 0.3 μg/g weight. However, Her1-treated animals show deficits in hearing ability and not subjected to the behavioral test adopting tone cues (HN unpublished data).

28


451

3. The solution must be aliquoted to avoid repeated freezing and thawing. 4. Peripheral injection of EGF or NRG1 accelerates eyelid opening and tooth eruption of neonatal rodents; thus, these are good indicators that verify the biological activity of EGF and NRG1 (1, 3). References 1. Futamura, T., Kakita, A., Tohmi, M., Sotoyama, H., Takahashi, H., and Nawa, H. (2003) Neonatal perturbation of neurotrophic signaling results in abnormal sensorimotor gating and social interaction in adults: implication for epidermal growth factor in cognitive development. Mol. Psychiatry. 8, 19–29. 2. Tohmi, M., Tsuda, N., Mizuno, M., Takei, N., Frankland, P.W., Nawa, H. (2005) Distinct influences of neonatal epidermal growth factor challenge on adult neurobehavioral traits in four mouse strains. Behav Genet 35, 615–629. 3. Kato, T , Abe, Y., Sotoyama, H., Kakita, A., Kominami, R., Hirokawa, S., Ozaki, M., Takahashi, H., and Nawa, H. (2011) Transient exposure of neonatal mice to neuregulin-1 results in hyperdopaminergic states in

adulthood: implication in neurodevelopmental hypothesis for schizophrenia. Mol. Psychiatry. 16 , 307–320. 4. Ibi, D., Nagai, T., Kitahara, Y., Mizoguchi, H., Koike, H., Shiraki, A., Takuma, K., Kamei, H., Noda, Y., Nitta, A., Nabeshima, T., Yoneda, Y., Yamada, K. (2009) Neonatal polyI:C treatment in mice results in schizophrenia-like behavioral and neurochemical abnormalities in adulthood. Neurosci. Res. 64, 297–305. 5. Ibi, D., Nagai, T., Koike, H., Kitahara, Y., Mizoguchi, H., Niwa, M., Jaaro-Peled, H., Nitta, A., Yoneda, Y., Nabeshima, T., Sawa, A., Yamada, K. (2010) Combined effect of neonatal immune activation and mutant DISC1 on phenotypic changes in adulthood. Behav. Brain Res. 206, 32–37.

sdfsdf

Chapter 29 P11: A Potential Biomarker for Posttraumatic Stress Disorder Lei Zhang, Robert J. Ursano, and He Li Abstract Posttraumatic stress disorder (PTSD) is a chronic and disabling anxiety disorder that occurs after a traumatic event. It is associated with an increased risk of suicide and marked deficits in social and occupational functioning. Currently, the diagnosis for PTSD is established on the basis of a patient’s clinical history, mental status examination, duration of symptoms, and clinician administered symptom checklist or patient self-report. However, there are no available laboratory biomarker tests for PTSD. To begin intervention at the earliest possible time, priority must be given to developing objective approaches to determine the presence of PTSD. Thus, using cutting-edge technology and skill to develop a simple blood test or a biomarker to detect PTSD at its earliest and most treatable stage would benefit both physician and patient. Several technologies and skills have been used in the identification biomarker research. We discuss three major methods in this chapter (blood RNA and DNA purification, chromatin immunoprecipitation, and Western blot), which have been used in our study to determine whether p11 is a potential biomarker for PTSD. Using these procedures will not only enhance the study of the molecular mechanisms of PTSD but also help the translation of basic science to a clinical setting. Key words: PTSD, Biomarkers, P11, Cortisol, Glucocorticoid receptor, Chromatin immunoprecipitation

1. Introduction Posttraumatic stress disorder (PTSD) is an anxiety disorder that occurs after an exposure to a traumatic event, such as military combat, a natural disaster, a terrorist attack, a serious accident, or physical or sexual assault (1). 7.8% of the American people are estimated to experience PTSD at some time in their life (2) and more so for combat-exposed military personnel (3, 4). Unfortunately, there is no objective laboratory biomarker test for PTSD. Currently, clinicians must rely upon symptom checklists, clinical histories, mental status, patient self-reports, and symptom duration to make the diagnosis. To overcome the limitations of current clinical assessment, clinicians


453

454

L. Zhang et al.

need additional tools, not only to enhance their ability to identify the “vulnerable” patient at risk for PTSD, but also to dynamically monitor the clinical condition of individual PTSD patients during treatment. The blood biomarker test has been considered as a potentially convenient tool to aid in PTSD diagnosis. 1.1. The Concept of Biomarkers

The term biomarker (biological marker) was first described in 1989 as a substance used as an indicator of a biologic state. It refers to a Medical Subject Heading term: “measurable and quantifiable biological parameters (e.g., specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, environmental exposure and its effects, disease diagnosis, metabolic processes, substance abuse, pregnancy, cell line development, epidemiologic studies, etc.” Later, a definition of a biomarker was described by an NIH working group as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” (NIH Biomarker Definitions Working Group 2001). Quantitative measures of biological effects that provide informative links between mechanism of action and clinical effectiveness are considered as biomarkers (FDA whitepaper “Innovation or Stagnation” 2004). Biomarkers are also defined as any substance, structure or process that can be measured in the body or its products and can influence or predict the incidence or outcome of disease (WHO International Programme on Chemical Safety). Biomarker research has been pushed forward during the 1990s and since then, the whole field of biomarker research has been drastically changed by the human genome project. The information gained from the human genome project redirected biomarker studies into a whole new era. Highthroughput analytical instruments have been used to screen thousands of genes and proteins simultaneously. Today, biomarkers have been classified into four subgroups including type 0 biomarkers, type 1 biomarkers, surrogate end point-type (type 2 biomarkers), and risk markers.

1.2. Potential Biomarker(s) for PTSD

High-throughput “omic” approaches including genomics, proteomics, and metabolomics have been used in candidate biomarker selection and identification for many diseases (5). However, progress in the search for PTSD biomarkers has been slow and often frustrating because of the complexity of the molecular mechanisms of the disease and the undefined validation process. Potential biomarker(s) for PTSD on the basis of animal research (6) or limited studies in humans have been proposed, but confirmation and validation of their clinical utility have not been accomplished. Appropriate and efficient validation would be expedited with valid animal models,

29

PTSD Biomarker Identification

455

standardized laboratory practice, larger human population-based studies, and repeated sampling of individuals. A strategy used in biomarker development for other illnesses (7) can also be used for development of a blood biomarker test for PTSD. To screen potential biomarkers in the case of PTSD, researchers currently compare gene and protein expression profiles or alteration of gene, protein expression or metabolite levels between PTSD patients and healthy control subjects by using several well developed procedures. Biomarkers may be obtained from saliva, blood, cerebrospinal fluid, urine, and tissues. Biomarkers can be physiological parameters such as blood pressure (8), ECG (9), and heart beat (10), neurotransmitters, such as 5-HT (11), dopamine (12), and GABA (13) or their metabolites, and brain-imaging (14). Biomarkers may indicate PTSD or PTSD characteristics, including the level or type of exposure to traumatic stress. Biomarker may further indicate genetic susceptibility and response to traumatic stress exposure, subclinical or clinical state, and response to therapy. These markers may change during the course of PTSD development or after single or multiple traumatic stresses (Table 1).

Table 1 Potential biomarkers for PTSD Potential biomarker

References

T cell phenotypes

Lemieux et al. (15)

Review on potential biomarkers

Rosen and Lilienfeld (16)

Erythrocyte sedimentation rate, white blood cell count, and cortisol– dehydroepiandrosterone sulfate ratio

Boscarino (17)

Endothelial dysfunction in plasma

von Kanel (18)

Serum interleukin-2 and interleukin-8 levels

Song et al. (19)

Platelet serotonin concentration

Kovacic et al. (11), Pivac et al. (20), Mück-Seler et al. (21), Spivak et al. (22)

Platelet MAO-B activity

Pivac et al. (23)

Circulating cortisol levels

Meewisse et al. (24), Ehlert et al. (25), Heber et al. (26), Glover et al. (27), Yehuda et al. (28)

Glucocorticoid receptor (GCR) expression in lymphocyte

Gotovac et al. (29) (continued)

456

L. Zhang et al.

Table 1 (continued) Potential biomarker

References

WFS1 gene

Kesner et al. (30)

Baseline level of platelet–leukocyte aggregates, platelet CD63 expression, and soluble P-selectin concentration

Vidović et al. (31)

GABA plasma levels

Vaiva et al. (32)

S-100β and neuron-specific enolase

Sojka et al. (33)

NPY expression

Dutton et al. (34)

Myelin basic protein

Wang et al. (35)

C-reactive protein and serum amyloid A

Sondergaard et al. (36)

Urinary dopamine

Glover et al. (27)

Thyroid hormone

Garrison and Breeding (37)

Neopterin

Atmaca et al. (38)

Plasma and cerebrospinal fluid interleukin-6 concentrations

Baker et al. (39), Maes et al. (40)

REM latency

Reist et al. (41), Kauffman et al. (42)

Average heart rate responses to a series of sudden, loud-tone presentations

Pitman et al. (43), Bryant et al. (44)

Mixed lateral preference and parental left-handedness

Chemtob and Taylor (45)

Startle responses

Milde et al. (46)

P11 (S100A10)

Zhang et al. (47), Su et al. (48)

PTSD biomarkers can be indicators of PTSD trait (risk factor or risk marker), disease state (preclinical or clinical), or disease rate (progression). We list biomarkers for PTSD in all possible respects: antecedent, screening, diagnostic, staging, and prognosis in Table 2. 1.3. P11: A Potential Biomarker for PTSD

Compared to other psychiatric and medical illnesses, relatively little work has been directed toward elucidating the molecular mechanisms of posttraumatic psychopathology. There are some association studies for individual molecular targets, but these are inherently limited to the hypothesis-driven search for candidates already implicated through the current framework of biological theorizing. Previously, we had discussed the possibility of identifying molecular targets for PTSD in a genome-wide screen in a validated

29


457

Table 2 Types of biomarkers for PTSD Biomarkers

Function or indicator

Antecedent

Identifying the risk of developing PTSD, changes in response to single or multiple traumatic stress events

Screening

Subclinical PTSD from well-adapted subjects, physiological response

Diagnostic

Recognizing PTSD

Staging

Categorizing PTSD severity

Prognostic

Predicting PTSD course: recurrence and response to treatment

animal model using microarray gene expression profile analysis (6). We decided to test the association of p11, a member of the S100 protein family, with PTSD in our animal model after we demonstrated that mRNA levels of p11 increase in the post-mortem prefrontal cortex (area 46) of PTSD patients (47). Stress induced in rats by three days of inescapable shock increased both p11 mRNA levels in the prefrontal cortex (PFC) and elevated their plasma corticosterone levels. Dexamethasone (Dex), a synthetic glucocorticoid, upregulates p11 expression in SH-SY5Y cells through glucocorticoid response elements (GREs) within the p11 promoter. This upregulation of p11 expression can be attenuated by either a glucocorticoid receptor antagonist, RU486, or mutating two of the three glucocorticoid response elements (GRE2 and GRE3) in the p11 promoter. This work is not only an example of a study of posttraumatic psychopathological mechanisms, but also of the identification of a potential PTSD biomarker, p11. In these studies, we used three major methods (quantitative real time PCR, chromatin immunoprecipitation, and Western blot) to determine p11 gene expression, gene regulation, and protein expression, respectively. The following is a discussion about the materials and methods of these procedures.

2. Materials 2.1. Materials for Blood Sample Collection and RNA Purification

There are several protocols for blood RNA isolation on the market. One of protocols, which has been used and validated in our laboratory is the protocol using the PAXgene Blood RNA System to isolate blood RNA. 1. PAXgene Blood RNA Tube. 2. PAXgene RNA spin columns.

458

L. Zhang et al.

3. PAXgene Shredder spin columns. 4. Proteinase K. 5. Buffers BR1 to BR5. 6. The RNase-Free DNase Set, which contains DNase I, Buffer RDD, and RNase-free water (see Notes 1 and 2). 2.2. Materials for DNA Purification

1. PAXgene Blood DNA Tubes.

2.3. Materials for Chromatin Immunoprecipitation

1. Chromatin Immunoprecipitation (ChIP) Assay Kit from Millipore (Chemicon/Upstate/Linco).

2. PAXgene Blood DNA Kit (see Notes 3–5).

2. Formaldehyde. 3. Glycine (2.5 M make fresh (20× solution)). 4. Protease inhibitor cocktail (PIC). 5. Phenylmethane sulfonyl fluoride (PMSF). 6. Buffer A: 10 mM HEPES, 1.5 mM MgCl2, 10 mM KCl, add fresh 2 mM DTT, 200 μM PMSF, PIC. 7. Buffer C: 20 mM HEPES, 25% glycerol, 0.42 M NaCl, 1.5 mM MgCl2, 0.2 mM EDTA, add fresh 2 mM DTT, 200 μM PMSF, 5 mM NaF, PIC 1×. 8. Elution buffer (1%SDS, 0.1 M NaHCO3). 9. Proteinase K. 10. Phenol/chloroform. 11. 75% Ethanol. 12. Pure water.

3. Methods 3.1. Blood RNA Isolation and Purification

The purification process is designed to provide high-quality RNA from samples that have been stabilized in the reagent of the PAXgene Blood RNA Tube. This system consists of several steps: whole blood collection, nucleic acid stabilization, and RNA purification. By minimizing the unpredictability associated with RNA processing, the system provides enhanced accuracy of intracellular RNA analysis. PAXgene tubes contain a proprietary reagent that immediately stabilizes intracellular RNA for 3 days at room temperature (18–25°C) and 5 days at 2–8°C (see Notes 1 and 2). This system has a specific isolation kit for RNA isolation from these collected blood samples (see Note 3). The following method is adopted from the manufacturer’s protocol (Invitrogen, Inc).

29


459

1. Centrifuge blood sample tubes for 10 min at 3,000–5,000 × g (see Notes 4–6). 2. Remove the supernatant and Add 4 ml RNase-free water to the pellet. 3. Vortex and centrifuge for 10 min at 3,000–5,000 × g. Remove the entire supernatant. Small debris remaining in the supernatant after vortexing but before centrifugation will not affect the procedure. 4. Add 350 μl Buffer BR1 and vortex. 5. Transfer the sample into a 1.5-ml microcentrifuge tube containing 300 μl Buffer BR2 and 40 μl proteinase K. Mix by vortexing for 5 s, and incubate for 10 min at 55°C using a shaker–incubator at 400–1,400 rpm. After incubation, set the temperature of the shaker–incubator to 65°C (for step 20). 6. Transfer the lysate into a PAXgene Shredder spin column (lilac) placed in a 2-ml processing tube and centrifuge for 3 min at maximum speed (but not to exceed 20,000 × g). 7. Transfer the supernatant of the flow-through fraction to a fresh 1.5-ml tube without disturbing the pellet in the processing tube. 8. Add 350 μl ethanol (96–100%). Mix by vortexing and centrifuge briefly (1–2 s at 500–1,000 × g) to remove drops from the inside of the tube lid. 9. Transfer 700 μl sample into the PAXgene RNA spin column (red) placed in a 2-ml processing tube and centrifuge for 1 min at 8,000–20,000 × g. Place the spin column in a new 2-ml processing tube and discard the old processing tube containing flow-through. 10. Transfer the remaining sample into the PAXgene RNA spin column and centrifuge for 1 min at 8,000–20,000 × g. Place the spin column in a new 2-ml processing tube and discard the old processing tube containing flow-through. 11. Transfer 350 μl Buffer BR3 into the PAXgene RNA spin column. Centrifuge for 1 min at 8,000–20,000 × g. Place the spin column in a new 2-ml processing tube and discard the old processing tube containing flow-through. 12. Add 10 μl DNase I stock solution to 70 μl Buffer RDD in a 1.5-ml tube. Mix by gently flicking the tube and centrifuge briefly to collect residual liquid from the sides of the tube. If processing, for example, ten samples, add 100 μl DNase I stock solution to 700 μl Buffer RDD. Use the 1.5-ml tubes supplied with the kit. 13. Transfer the DNase I incubation mix (80 μl) directly onto the PAXgene RNA spin column membrane and place on the benchtop (20–30°C) for 15 min.

460

L. Zhang et al.

14. Transfer 350 μl Buffer BR3 into the PAXgene RNA spin column and centrifuge for 1 min at 8,000–20,000 × g. Place the spin column in a new 2-ml processing tube and discard the old processing tube containing flow-through. 15. Transfer 500 μl Buffer BR4 to the PAXgene RNA spin column and centrifuge for 1 min at 8,000–20,000 × g. Place the spin column in a new 2-ml processing tube and discard the old processing tube containing flow-through. 16. Add another 500 μl Buffer BR4 to the PAXgene RNA spin column. Centrifuge for 3 min at 8,000–20,000 × g. 17. Discard the tube containing the flow-through and place the PAXgene RNA spin column in a new 2-ml processing tube. Centrifuge for 1 min at 8,000–20,000 × g. 18. Discard the tube containing the flow-through. Place the PAXgene RNA spin column in a 1.5-ml microcentrifuge tube and add 40 μl Buffer BR5 directly onto the PAXgene RNA spin column membrane. Centrifuge for 1 min at 8,000– 20,000 × g to elute the RNA. 19. Repeat the elution step (step 18) as described, using 40 μl Buffer BR5 and the same tube. 20. Incubate the eluate for 5 min at 65°C in the shaker–incubator (from step 5) without shaking. After incubation, chill immediately on ice. 21. If the RNA samples will not be used immediately, store at −20 or −70°C. Since the RNA remains denatured after repeated freezing and thawing, it is not necessary to repeat the incubation at 65°C. 3.2. Blood DNA Isolation and Purification

For blood DNA isolation, the PAXgene Blood DNA System can be used. Like the PAXgene Blood RNA System, the PAXgene Blood DNA System is comprised of two integrated components: PAXgene Blood DNA Tubes and the PAXgene Blood DNA Kit. Blood collection and sample processing are integrated into a single standardized system, reducing the risk of sample mix-up and crosscontamination. The DNA purification procedure is streamlined to rapidly achieve reproducible yields of high-quality DNA from each sample. Blood samples are drawn directly into PAXgene Blood DNA Tubes via standard phlebotomy technique. These tubes, based on proven BD Vacutainer™ technology, contain a proprietary additive that provides buffering conditions optimized for subsequent cell lysis and DNA purification. Whole blood DNA stored in PAXgene DNA Tubes is stable for 14 days at room temperature or for 28 days at 2–8°C. For long-term storage, freezing samples at −70 to −80°C is recommended. The DNA purification will take about 1 h for complete processing of eight blood samples. It is approximately 25% faster than standard salting-out methods.

29


461

This system results in high yields of pure, high-molecular-weight DNA. The following method is adopted from the manufacturer’s protocol (Invitrogen, Inc). 1. Add blood sample into a Processing Tube containing 25 ml Buffer BG1. Mix by inverting the tube five times. 2. Centrifuge for 5 min at 2,500 × g. 3. Discard the supernatant. 4. Add 5 ml Buffer BG2 and wash the pellet by vortexing vigorously for 5 s. 5. Centrifuge for 3 min at 2,500 × g. 6. Discard the supernatant and place the tube back in the rack. 7. Add 5 ml Buffer BG3/PreAnalytiX Protease and vortex for 20 s at high speed. 8. Place the tube in a heating block or water bath and incubate at 65°C for 10 min. 9. Vortex again for 5 s at high speed. 10. Add 5 ml isopropanol (100%) and mix by inverting the tube at least 20 times until the white DNA strands clump visibly together. 11. Centrifuge for 3 min at 2,500 × g. 12. Discard the supernatant and leave the tube inverted on a clean piece of absorbent paper for 1 min. 13. Add 5 ml 70% (v/v) ethanol and vortex for 1 s at high speed. 14. Centrifuge for 3 min at 2,500 × g. 15. Discard the supernatant and leave the tube inverted on a clean piece of absorbent paper for at least 5 min. 16. Carefully dab the tube onto absorbent paper to remove ethanol from the rim and leave it inverted for a further 5 min to allow the DNA pellet to dry. 17. Add 1 ml Buffer BG4 and dissolve the DNA by incubating for 1 h at 65°C in a heating block or water bath, followed by incubation overnight at room temperature. 3.3. ChIP Protocol

1. The following method is adopted from the manufacturer’s protocol (Millipore, Inc). Chromatin is first treated with formaldehyde to fix the chromatin-bound proteins to the DNA. 2. The immunoprecipitation is conducted using a specific ChIPgrade antibody. 3. Cross-linking is reversed followed by proteinase K treatment or DNA purification. 4. The purified DNA is analyzed to identify the genomic regions where the specific GR protein was located.

462

L. Zhang et al.

3.3.1. Chromatin Preparation

1. Avoid local artificial cross-links by adding formaldehyde with a final 1% concentration to the culture medium. 2. Incubate cells at 37°C for 10 min. 3. Stop the reaction by adding glycine (2.5 M make fresh (20× solution)) to a final concentration of 0.125 M. 4. Incubate 5 min at RT. 5. Aspirate medium, removing as much as possible. 6. Wash cells 2× with ice-cold PBS containing protease inhibitors (PI). PI = 1 mM PMSF (phenylmethane sulfonyl fluoride) and 1× PIC (Protease Inhibitor Cocktail). 7. Scrape cells into 15-ml conical tube using PBS with PI. 8. Pellet cells at 1,000 rpm 4°C for 5 min. 9. Wash cells 2× with 4 ml of cold PBS + PI at 1,000 rpm 4°C for 5 min. 10. Estimate pellet cell volume (PCV).

3.3.2. Nuclear Pellet Collection

1. Add 5× PVC volume of buffer A 300 μl. Buffer A: 10 mM HEPES, 1.5 mM MgCl2, 10 mM KCl, add fresh 2 mM DTT, 200 μM PMSF, protease inhibiters 1:100. 2. Pipette up and down to resuspend the pellet. 3. Incubate on ice for 10 min. 4. Douse with the 2 ml “B” douser until the cells lyse. Check for nuclei under the microscope using trypan blue after 20 douses. Transfer whole cell lysates (nuclei and cytoplasm) to Eppendorf tubes. 5. Centrifuge at 4°C for 10 min at 3,000 rpm. 6. Collect supernatant (cytoplasmic extract) if you need to and freeze on dry ice, store at −80°C. 7. Respin the pellet at 14,000 rpm, 15 min at 4°C and discard remaining liquid. 8. Lyse nuclei by adding 100 μl PVC and buffer C (2 mM DTT, 200 μM PMSF, 5 mM NaF, Invitrogen protease inhibitor cocktail (PIC) 1:100). Buffer C: 20 mM HEPES, 25% glycerol, 0.42 M NaCl, 1.5 mM MgCl2, 0.2 mM EDTA, add fresh 2 mM DTT, 200 μM PMSF, 5 mM NaF, protease inhibiters 1:100. 9. Freeze nuclei at −80°C for future use.

3.3.3. Sonication Step

1. Add 600 μl of 1% SDS with protease inhibitors to each to bring to final volume of 700 μl. 2. Move to a 4-ml Falcon # 2063 tube with rounded bottom (better for sonication). 3. Sonicate lysate to shear DNA into lengths, being sure to keep samples on ice during sonication. Use five pulses at lowest

29


463

power (#1 on the scale) where each pulse is 10 s, total 50 s, with Sonifier Cell Disruptor 350 (Branson Sonic Power, Smith Kline Co.) (see Note 7). 4. Transfer to an Eppendorf tube and centrifuge for 10 min at 13,000 rpm at 4°C. 5. Transfer the supernatant to a new 14-ml Falcon tube. 6. Discard pellet. 7. Dilute the sonicated nuclear lysates tenfold (6,300 μl) in ChIP Dilution Buffer, adding protease inhibitors as previous. 8. Pre-clear the 7 ml diluted nuclear lysate with 75 μl of Salmon Sperm DNA/Protein A Agarose-50% Slurry for 30 min at 4°C with agitation. 9. Pellet agarose by brief centrifugation 1,000 rpm × 1 min and collect the supernatant fraction and transfer to clean 14-ml Falcon tube. 3.3.4. Immunoprecipitation Step

1. Add the immunoprecipitating antibody using 10 μg for each sample. Incubate overnight at 4°C with rotation. 2. Add Salmon Sperm DNA–Protein A Agarose-50% Slurry, 65 μl, for 1 h at 4°C with rotation to collect the antibody– protein complexes. 3. Pellet agarose by gentle centrifugation (1,000 rpm at 4°C for 1 min) and carefully remove the supernatant that contains unbound, nonspecific DNA. Save, as a precaution. 4. Wash the protein A agarose–antibody–protein complex for 5 min (at 4° unless stated otherwise) on a rotating platform with 1 ml of each of the buffers listed in the order as given below, pellet agarose (1,000 rpm × 1 min), and discard the wash buffer between steps: (a) Low Salt Immune Complex Wash Buffer, one wash. (b) High Salt Immune Complex Wash Buffer, one wash. (c) LiCl Immune Complex Wash Buffer, one wash. (d) TE Buffer, two washes (last wash at RT).

3.3.5. Elution Step

1. Remove TE wash buffer and resuspend the protein A agarose– antibody–chromatin complex by adding 250 μl elution buffer. 2. Freshly prepare elution buffer (1%SDS, 0.1 M NaHCO3). 3. Vortex briefly to mix. 4. Incubate at room temperature for 15 min with rotation. 5. Spin down agarose, and carefully transfer the supernatant fraction (eluate) to another tube and repeat elution. 6. Combine eluates (total volume = ~500 μl).

464

L. Zhang et al.

3.3.6. Reverse Cross-Links

1. Add 20 μl 5 M NaCl to the combined eluates (500 μl). 2. Incubation at 65°C for 4 h. 3. Add 10 μl of 0.5 M EDTA, 20 μl 1 M Tris–HCl, pH 6.5, and 2 μl of 10 mg/ml Proteinase K and incubate for 1 h at 45°C.

3.3.7. DNA Recovery

1. Extract using phenol–chloroform. 2. Precipitate using ETOH. 3. Resuspend in small volume TE buffer (10 μl). 4. Use for PCR amplification.

3.4. Western Blotting

Western blotting is a technique used to identify and locate proteins based on their ability to bind to specific antibodies. It can detect the protein of interest from a mixture of a great number of proteins and give information about the size of the protein (with comparison to a size marker or ladder in kDa), and the information on protein expression (with comparison to a control such as untreated sample or another cell type or tissue). The major steps in Western Blot Analysis are: sample preparation, gel preparation, running gel, transfer of gel, Western blotting readout, and analysis of results. 1. To remove extraneous proteins from the media: For nonadherent cells you can gently pellet them with centrifugation and then wash the pellet with PBS. For adherent cells, simple wash the flask or dish with PBS prior to Western blot. Sample on ice during cell lysis for Western blotting. 2. Add inhibitors (both protease inhibitors and phosphatase inhibitors to do Western blot for phospho-protein). 3. Protein concentration in the samples is determined with a BioRad Protein Concentration Reagent. 4. Equal amounts of total protein (20 μg per lane) are resolvated in 10% SDS polyacrylamide gels (see Note 8). 5. Load molecular weight reference. 6. Run gel at 40 mA (constant current), if available, or else at 100 V (constant voltage). Watch protein marker/ladder or dye front for when to stop gel. Constant current gives better and sharper results. 7. Transfer of proteins to membrane for Western Blotting: Transfer overnight at 35 V or transfer quickly in 1 h at higher voltage. 8. Blocking of membranes allows maximization of signal to noise ratio—Block with 5% Blotto (nonfat dry milk—powder) or 1–5% BSA (bovine serum albumin) for phosphorylated proteins.

29


465

9. Incubate with primary antibody overnight at 4°C under rocking. Protein expression is detected using a 1:500 dilution of mouse anti-p11 monoclonal antibody (BD Transduction Laboratories, Franklin Lakes, NJ, USA). 10. Washing with TBST after primary antibody: Wash 5× for 5 min with TBST. 11. Incubate with a 1:1,000 dilution of horseradish peroxidaseconjugated goat anti-mouse IgG as a secondary antibody (BioRad Laboratories, Hercules, CA, USA) for 1 h at RT. 12. Wash after secondary Antibody. This step is critical. Wash 5× for 5 min with TBST. 13. Assaying for result, ECL (enhanced chemiluminescence) is used and film is exposed and developed. The density values are examined using NIH imaging. The density is used to quantify immunoreactivity in terms of percentage of p11 induction relative to control (nonstressed rats or nontreated cells).

4. Notes 1. To prevent the tubes from cracking, do not freeze tubes upright in a Styrofoam tray. 2. The PAXgene™ Blood RNA Tubes can be stored at −20°C and below. If the tubes are to be kept at temperatures below −20°C, freeze them first at −20°C for 24 h, then transfer them to −70 or −80°C, suitable for longer periods of storage. 3. To thaw the samples in PAXgene™ Blood DNA Tubes, place them in a wire rack in a water bath at 37°C for 15 min and carefully invert the tubes ten times. 4. Thaw blood samples in the PAXgene™ Blood RNA Tubes in a wire rack at ambient temperature (18–25°C) for approximately 2 h. 5. Do not thaw blood samples in the PAXgene™ Blood RNA Tubes at temperatures above 25°C. 6. Carefully invert the blood samples in PAXgene™ Blood RNA Tubes ten times. 7. Sonication conditions may need to be optimized for each cell type and/or sonicator. Analyze by electrophoresis to assess conditions. At present, 200–1,000 bp is optimal. 8. The percentage of acrylamide is important. We used 4–12% acrylamide for the p11 experiment. Load every sample carefully and slowly to prevent sample leaking out of the lane.

466

L. Zhang et al.

Acknowledgments We thank Vivek Jayadeva and Stanley Smerin of USUHS for their assistance with editing the manuscript. References 1. Ursano, R. J., Bell, C., Eth, S., Friedman, M., Norwood, A., Pfefferbaum, B., Pynoos, J. D., Zatzick, D. F., Benedek, D. M., McIntyre, J. S., Charles, S. C., Altshuler, K., Cook, I., Cross, C. D., Mellman, L., Moench, L. A., Norquist, G., Twemlow, S. W., Woods, S., and Yager, J. (2004) Practice guideline for the treatment of patients with acute stress disorder and posttraumatic stress disorder, Am J Psychiatry 161, 3–31. 2. Kessler, R. C., Sonnega, A., Bromet, E., Hughes, M., and Nelson, C. B. (1995) Posttraumatic stress disorder in the National Comorbidity Survey, Arch Gen Psychiatry 52, 1048–1060. 3. Friedman, M. J. (2004) Acknowledging the psychiatric cost of war, The New England journal of medicine 351, 75–77. 4. Hoge, C. W., Castro, C. A., Messer, S. C., McGurk, D., Cotting, D. I., and Koffman, R. L. (2004) Combat duty in Iraq and Afghanistan, mental health problems, and barriers to care, N Engl J Med 351, 13–22. 5. Sinha, A., Singh, C., Parmar, D., and Singh, M. P. (2007) Proteomics in clinical interventions: achievements and limitations in biomarker development, Life Sci 80, 1345–1354. 6. Zhang, L., Zhou, R., Xing, G., Hough, C. J., Li, X., and Li, H. (2006) Identification of gene markers based on well validated and subcategorized stressed animals for potential clinical applications in PTSD, Medical hypotheses 66, 309–314. 7. Schmidt, C. W. (2006) Signs of the times: biomarkers in perspective, Environ Health Perspect 114, A700–705. 8. Kibler, J. L., Joshi, K., and Ma, M. (2009) Hypertension in relation to posttraumatic stress disorder and depression in the US National Comorbidity Survey, Behav Med 34, 125–132. 9. Falconer, E. M., Felmingham, K. L., Allen, A., Clark, C. R., McFarlane, A. C., Williams, L. M., and Bryant, R. A. (2008) Developing an integrated brain, behavior and biological response profile in posttraumatic stress disorder (ptsd), J Integr Neurosci 7, 439–456. 10. Bryant, R. A., Creamer, M., O’Donnell, M., Silove, D., and McFarlane, A. C. (2008) A

11.

12.

13.

14.

15.

16.

17.

18.

19.

Multisite Study of Initial Respiration Rate and Heart Rate as Predictors of Posttraumatic Stress Disorder, J Clin Psychiatry. Kovacic, Z., Henigsberg, N., Pivac, N., Nedic, G., and Borovecki, A. (2008) Platelet serotonin concentration and suicidal behavior in combat related posttraumatic stress disorder, Prog Neuropsychopharmacol Biol Psychiatry 32, 544–551. Hamner, M. B., and Gold, P. B. (1998) Plasma dopamine beta-hydroxylase activity in psychotic and non-psychotic post-traumatic stress disorder, Psychiatry Res 77, 175–181. Geuze, E., van Berckel, B. N., Lammertsma, A. A., Boellaard, R., de Kloet, C. S., Vermetten, E., and Westenberg, H. G. (2008) Reduced GABAA benzodiazepine receptor binding in veterans with post-traumatic stress disorder, Mol Psychiatry 13, 74–83, 73. Morey, R. A., Dolcos, F., Petty, C. M., Cooper, D. A., Hayes, J. P., Labar, K. S., and McCarthy, G. (2008) The role of trauma-related distractors on neural systems for working memory and emotion processing in posttraumatic stress disorder, J Psychiatr Res. Lemieux, A., Coe, C. L., and Carnes, M. (2008) Symptom severity predicts degree of T cell activation in adult women following childhood maltreatment, Brain Behav Immun 22, 994–1003. Rosen, G. M., and Lilienfeld, S. O. (2008) Posttraumatic stress disorder: an empirical evaluation of core assumptions, Clin Psychol Rev 28, 837–868. Boscarino, J. A. (2008) Psychobiologic predictors of disease mortality after psychological trauma: implications for research and clinical surveillance, J Nerv Ment Dis 196, 100–107. von Kanel, R., Hepp, U., Traber, R., Kraemer, B., Mica, L., Keel, M., Mausbach, B. T., and Schnyder, U. (2008) Measures of endothelial dysfunction in plasma of patients with posttraumatic stress disorder, Psychiatry Res 158, 363–373. Song, Y., Zhou, D., Guan, Z., and Wang, X. (2007) Disturbance of serum interleukin-2 and interleukin-8 levels in posttraumatic and

29

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

non-posttraumatic stress disorder earthquake survivors in northern China, Neuroimmunomodulation 14, 248–254. Pivac, N., Kozaric-Kovacic, D., Mustapic, M., Dezeljin, M., Borovecki, A., Grubisic-Ilic, M., and Muck-Seler, D. (2006) Platelet serotonin in combat related posttraumatic stress disorder with psychotic symptoms, J Affect Disord 93, 223–227. Muck-Seler, D., Pivac, N., Jakovljevic, M., Sagud, M., and Mihaljevic-Peles, A. (2003) Platelet 5-HT concentration and comorbid depression in war veterans with and without posttraumatic stress disorder, J Affect Disord 75, 171–179. Spivak, B., Vered, Y., Graff, E., Blum, I., Mester, R., and Weizman, A. (1999) Low platelet-poor plasma concentrations of serotonin in patients with combat-related posttraumatic stress disorder, Biol Psychiatry 45, 840–845. Pivac, N., Knezevic, J., Kozaric-Kovacic, D., Dezeljin, M., Mustapic, M., Rak, D., Matijevic, T., Pavelic, J., and Muck-Seler, D. (2007) Monoamine oxidase (MAO) intron 13 polymorphism and platelet MAO-B activity in combat-related posttraumatic stress disorder, J Affect Disord 103, 131–138. Meewisse, M. L., Reitsma, J. B., de Vries, G. J., Gersons, B. P., and Olff, M. (2007) Cortisol and post-traumatic stress disorder in adults: systematic review and meta-analysis, Br J Psychiatry 191, 387–392. Ehlert, U., Gaab, J., and Heinrichs, M. (2001) Psychoneuroendocrinological contributions to the etiology of depression, posttraumatic stress disorder, and stress-related bodily disorders: the role of the hypothalamus-pituitary-adrenal axis, Biol Psychol 57, 141–152. Heber, R., Kellner, M., and Yehuda, R. (2002) Salivary cortisol levels and the cortisol response to dexamethasone before and after EMDR: a case report, J Clin Psychol 58, 1521–1530. Glover, D. A., and Poland, R. E. (2002) Urinary cortisol and catecholamines in mothers of child cancer survivors with and without PTSD, Psychoneuroendocrinology 27, 805–819. Yehuda, R., Halligan, S. L., and Bierer, L. M. (2002) Cortisol levels in adult offspring of Holocaust survivors: relation to PTSD symptom severity in the parent and child, Psychoneuroendocrinology 27, 171–180. Gotovac, K., Sabioncello, A., Rabatic, S., Berki, T., and Dekaris, D. (2003) Flow cytometric determination of glucocorticoid receptor (GCR) expression in lymphocyte subpopulations: lower quantity of GCR in patients with

30.

31.

32.

33.

34.

35.

36.

37.

38.

39.


467

post-traumatic stress disorder (PTSD), Clin Exp Immunol 131, 335–339. Kesner, Y., Zohar, J., Merenlender, A., Gispan, I., Shalit, F., and Yadid, G. (2009) WFS1 gene as a putative biomarker for development of post-traumatic syndrome in an animal model, Mol Psychiatry 14, 86–94. Vidovic, A., Vilibic, M., Markotic, A., Sabioncello, A., Gotovac, K., FolnegovicSmalc, V., and Dekaris, D. (2007) Baseline level of platelet-leukocyte aggregates, platelet CD63 expression, and soluble P-selectin concentration in patients with posttraumatic stress disorder: a pilot study, Psychiatry Res 150, 211–216. Vaiva, G., Boss, V., Ducrocq, F., Fontaine, M., Devos, P., Brunet, A., Laffargue, P., Goudemand, M., and Thomas, P. (2006) Relationship between posttrauma GABA plasma levels and PTSD at 1-year follow-up, Am J Psychiatry 163, 1446–1448. Sojka, P., Stalnacke, B. M., Bjornstig, U., and Karlsson, K. (2006) One-year follow-up of patients with mild traumatic brain injury: occurrence of post-traumatic stress-related symptoms at follow-up and serum levels of cortisol, S-100B and neuron-specific enolase in acute phase, Brain Inj 20, 613–620. Dutton, M. A., Lee, E. W., and Zukowska, Z. (2006) NPY and extreme stress: lessons learned from posttraumatic stress disorder, Exs, 213–222. Wang, Q., Wang, Z., Zhu, P., and Jiang, J. (2004) Alterations of myelin basic protein and ultrastructure in the limbic system at the early stage of trauma-related stress disorder in dogs, J Trauma 56, 604–610. Sondergaard, H. P., Hansson, L. O., and Theorell, T. (2004) The inflammatory markers C-reactive protein and serum amyloid A in refugees with and without posttraumatic stress disorder, Clin Chim Acta 342, 93–98. Garrison, R. L., and Breeding, P. C. (2003) A metabolic basis for fibromyalgia and its related disorders: the possible role of resistance to thyroid hormone, Med Hypotheses 61, 182–189. Atmaca, M., Kuloglu, M., Tezcan, E., Onal, S., and Ustundag, B. (2002) Neopterin levels and dexamethasone suppression test in posttraumatic stress disorder, Eur Arch Psychiatry Clin Neurosci 252, 161–165. Baker, D. G., Ekhator, N. N., Kasckow, J. W., Hill, K. K., Zoumakis, E., Dashevsky, B. A., Chrousos, G. P., and Geracioti, T. D., Jr. (2001) Plasma and cerebrospinal fluid interleukin-6 concentrations in posttraumatic stress disorder, Neuroimmunomodulation 9, 209–217.

468

L. Zhang et al.

40. Maes, M., Lin, A. H., Delmeire, L., Van Gastel, A., Kenis, G., De Jongh, R., and Bosmans, E. (1999) Elevated serum interleukin-6 (IL-6) and IL-6 receptor concentrations in posttraumatic stress disorder following accidental manmade traumatic events, Biol Psychiatry 45, 833–839. 41. Reist, C., Kauffmann, C. D., Chicz-Demet, A., Chen, C. C., and Demet, E. M. (1995) REM latency, dexamethasone suppression test, and thyroid releasing hormone stimulation test in posttraumatic stress disorder, Prog Neuropsychopharmacol Biol Psychiatry 19, 433–443. 42. Kauffman, C. D., Reist, C., Djenderedjian, A., Nelson, J. N., and Haier, R. J. (1987) Biological markers of affective disorders and posttraumatic stress disorder: a pilot study with desipramine, J Clin Psychiatry 48, 366–367. 43. Pitman, R. K., Gilbertson, M. W., Gurvits, T. V., May, F. S., Lasko, N. B., Metzger, L. J., Shenton, M. E., Yehuda, R., and Orr, S. P. (2006) Clarifying the origin of biological abnormalities in PTSD through the study of identical twins discordant for combat exposure, Ann N Y Acad Sci 1071, 242–254. 44. Bryant, R. A., Salmon, K., Sinclair, E., and Davidson, P. (2007) Heart rate as a predictor

45.

46.

47.

48.

of posttraumatic stress disorder in children, Gen Hosp Psychiatry 29, 66–68. Chemtob, C. M., and Taylor, K. B. (2003) Mixed lateral preference and parental lefthandedness: possible markers of risk for PTSD, J Nerv Ment Dis 191, 332–338. Milde, A. M., Sundberg, H., Roseth, A. G., and Murison, R. (2003) Proactive sensitizing effects of acute stress on acoustic startle responses and experimentally induced colitis in rats: relationship to corticosterone, Stress 6, 49–57. Zhang, L., Li, H., Su, T. P., Barker, J. L., Maric, D., Fullerton, C. S., Webster, M. J., Hough, C. J., Li, X. X., and Ursano, R. (2008) p11 is up-regulated in the forebrain of stressed rats by glucocorticoid acting via two specific glucocorticoid response elements in the p11 promoter, Neuroscience 153, 1126–1134. Su, T. P., Zhang, L., Chung, M. Y., Chen, Y. S., Bi, Y. M., Chou, Y. H., Barker, J. L., Barrett, J. E., Maric, D., Li, X. X., Li, H., Webster, M. J., Benedek, D., Carlton, J. R., and Ursano, R. (2009) Levels of the potential biomarker p11 in peripheral blood cells distinguish patients with PTSD from those with other major psychiatric disorders, Journal of psychiatric research 43, 1078–1085.

Part VI “Omics” Analysis and Systems Biology Applications in Psychiatric Disorders

sdfsdf

Chapter 30 Investigation of Age-Specific Behavioral and Proteomic Changes in an Animal Model of Chronic Ethanol Exposure Antoniette M. Maldonado-Devincci, Stanley M. Stevens Jr., and Cheryl L. Kirstein Abstract Alcohol use during adolescence represents a major health concern given that this is a period in which the brain continues to undergo critical developmental changes. Much behavioral research has been conducted in animal models of alcohol exposure, and a vulnerable period in adolescence has been identified that suggests lasting effects of ethanol exposure during adolescence. However, identification of molecular changes underlying the behavioral outcomes observed as a result from exposure to ethanol during adolescence remains a major technical challenge. In this chapter, we describe a method that allows for assessment of the effects of chronic ethanol exposure during adolescence relative to adulthood through global-scale analysis of protein expression as well as evaluation of behavioral responsivity in adolescent and adult rats. Results from this type of analysis can facilitate identification of age-specific molecular markers associated with behavioral changes following treatment with ethanol or in other animal models of drug abuse. Key words: Ethanol, Proteomics, Mass spectrometry, Behavior, Differential protein expression profiling, Biomarker

1. Introduction Adolescence is a unique time period during which individuals typically experiment with alcohol and consequently are at a greater predisposition to develop alcohol dependency. This developmental period is important since studies show that adults with substance abuse disorders initiate alcohol and drug use in adolescence, a period of considerable brain growth (1). Furthermore, the use of alcohol early in life is a critical predictor of abuse liability later in life for humans (2, 3). To date, little research has focused on understanding the molecular mechanisms of alcohol’s effects in the developing animal, and even less on the effects of adolescent


471

472

A.M. Maldonado-Devincci et al.

ethanol exposure and subsequent adult responses. The need for an adolescent animal model of alcohol abuse that examines both behavioral changes and molecular changes associated with alcohol has been raised (4, 5). Thus, it is critical to examine the lasting behavioral and molecular impact of ethanol exposure during development of brain reward mechanisms and on subsequent function. Adolescents differ from adults in ethanol-induced behavioral responsivity, underscoring the importance of studying adolescence. For example, adolescent animals consume more ethanol than adults (6) and ethanol intake levels are high throughout adolescence and decrease to levels slightly higher than adult comparisons (7). Additionally, ethanol exposure during adolescence potentiates subsequent preference for ethanol in adult mice (8) and developing animals differ from adults in pharmacological sensitivity to ethanol (5) with preweanling rats differing from other ages in ethanol tolerance (9). Adolescent rats develop an ethanol-induced place preference more readily than adult animals (10) and showed a heightened preference for novelty (11). In this chapter, an approach to determine potential age-specific ethanol-induced changes in behavior is described. In order to determine the molecular mechanisms underlying age-specific behavioral changes observed in an animal model after chronic ethanol exposure, proteomics-based analysis can be employed to provide an unbiased global scale assessment of ethanol-induced neuroprotein differential expression. For example, changes in various high-abundance proteins in adolescent rat hippocampus have been observed after chronic alcohol exposure using proteomic analysis by 2D gel electrophoresis (12). A mass spectrometry-based relative protein quantitation approach for the proteomic analysis of brain tissue in an in vivo model of chronic ethanol exposure is described here and is an effective methodology that can complement other proteomics-based techniques such as 2D gel electrophoresis, ultimately to provide a molecular link at the protein level to various age-specific alcohol-induced behavioral outcomes. This approach incorporates either a “label-free” or a chemical tagging method using isobaric tags for relative and absolute quantitation (iTRAQ) (13) depending on the instrumentation that is available for mass spectrometry analysis.

2. Materials 2.1. In Vivo Chronic Ethanol Exposure 2.1.1. Subjects

1. Male Sprague-Dawley rats (Harlan Laboratories, Indianapolis, IN) derived from established breeding pairs are used as subjects. 2. Litters are sexed and culled to ten pups per litter on postnatal day (PND) 1, with the day of birth designated as PND 0.

30

Investigation of Age-Specific Behavioral and Proteomic Changes…

473

Pups remain with their respective dams until PND 21, when pups are pair-housed with same-sex littermates. 3. Animals are maintained on a 12:12 h light:dark cycle (lights on at 07:00 h), in a temperature and humidity-controlled vivarium. Animals are allowed free access to food and water throughout the experiment. No more than one male pup per litter is used in any given condition. Animals are randomly assigned to conditions. Maintenance and treatment of the animals are within the guidelines for animal care by the National Institutes of Health. 2.1.2. In Vivo Ethanol Exposure

1. Diluted ethanol from a 95% stock solution (Pharmaco-Aaper, Shelbyville, KY) to a final concentration of 17% v/v in saline (0.9% NaCl). 2. Saline (0.9% NaCl) is used as a vehicle. 3. Ethanol and saline are intraperitoneally (i.p.) administered isovolumetrically as a 1.5 g/kg dose. This is achieved by multiplying the weight of the animal by 0.01117.

2.2. Behavioral Assessment

1. Locomotor activity assessment: a behavioral video tracking system (Ethovision from Noldus Information Technology, Utrecht, The Netherlands) where the signal is tracked (the movement of the animal is digitally recorded) with a camera suspended above the dimly lit circular open field. 2. The open field area: a black Plexiglas floor (diameter = 96.5 cm) and an opaque circular barrier measuring 45.7 cm high located 60 cm above the floor (see Note 1). The animal is allowed free access to move about the entire area, in which the center of gravity of the animal is recorded (see Note 2).

2.3. Tissue Processing and Protein Sample Preparation

1. Fresh lysis buffer for tissue homogenization: 8 M urea (Thermo Fisher Scientific, Rockford, IL), 0.1% sodium dodecyl sulfate (SDS) in 50 mM triethylammonium bicarbonate (Sigma Aldrich, St. Lois, MO) with protease and phosphatase inhibitors (Halt Protease and Phosphatase Inhibitor Cocktail from Pierce Biotechnology). Store for up to 2 weeks at 4°C. 2. 50 mM tris-(2-carboxyethyl)phosphine (TCEP) and 200 mM methyl methanethiosulfonate (MMTS) in isopropanol for protein reduction and alkylation, respectively. These reagents can be obtained from the iTRAQ reagent kit (AB Sciex, Foster City, CA). 3. Sequencing grade modified trypsin (Promega, Madison, WI) for protein digestion. Prior to use, resuspend 20 μg vial of lyophilized trypsin in 20 μl of Milli-Q®.

474


4. iTRAQ labels and other reagents needed for labeling (e.g., ethanol) are commercially available as a kit (either 4-plex or 8-plex comparison) through AB Sciex. 5. A similar technology named Tandem Mass Tags (TMT) is available as a kit (up to 6-plex comparison) through Thermo Fisher Scientific. 2.4. Liquid Chromatography Tandem Mass Spectrometry Analysis

Major instrumentation for the proteomic analysis of rat brain tissue includes a HPLC system capable of nanoflow rates (250 nl/min) for online reversed-phase HPLC separation of the rat brain protein tryptic digests and a mass spectrometer. For relative protein quantitation by spectral counting, a low-resolution mass spectrometer such as a quadrupole ion trap can be used. However, higher resolution is ideal for analysis of iTRAQ-labeled peptides. Specific items used in the proteomic analysis reported in this chapter are listed below. 1. 1 ml C18 solid phase extraction (SPE) cartridges (Grace, Deerfield, IL) for peptide desalting prior to mass spectrometry analysis. 2. A 75 μm i.d. × 2 cm C18 capillary trap (Proteopep II, New Objective, Woburn, MA) and 75 μm i.d. × 15 cm C18 analytical column (Proteopep II, New Objective, Woburn, MA) using a nanoHPLC system (Eksigent, Dublin, CA). 3. LC-MS/MS analysis for relative quantitation by spectral counting is carried out with a linear ion trap instrument (LTQ XL, Thermo Fisher Scientific). Mass spectrometric analysis for iTRAQ-based quantitation is carried out on a hybrid linear ion trap-Orbitrap mass spectrometer (LTQ Orbitrap XL, Thermo Fisher Scientific) (see Note 3).

2.5. Mass Spectrometric Data Analysis

Several data analysis software packages can be used for processing of mass spectrometric data for relative protein quantitation by either spectral counting or iTRAQ. 1. Standard database search engines for protein identification include Sequest (Thermo Fisher Scientific) and Mascot (Matrix Science). 2. Relative quantitation based on spectral counting as well as iTRAQ is routinely performed by the program Scaffold (Proteome Software, Portland, OR); however, other commercial packages such as the quantitation toolbox in Mascot Distiller (Matrix Science) and Proteome Discoverer (Thermo Fisher Scientific) can be used for iTRAQ data analysis.

30


475

3. Methods 3.1. In Vivo Chronic Ethanol Exposure

1. Beginning on PND 28–29 for adolescents and PND 58–59 for adults, handle all animals for 5 min each day. This handling involves transporting animals from the colony room to the laboratory, where they are weighed and marked for identification purposes. 2. Position animals for an intraperitoneal injection and gently restrain in that position for 30 s twice during the 5 min to allow animals to acclimate to the experimental manipulations. Allow animals to move freely about the hands and arms of the experimenter during the rest of the 5 min. Following these 5 min, return rats to their homecage. 3. Administer ethanol once a day for 21 consecutive days at the dose of 1.5 g/kg or an isovolumetric administration of saline for control animals. On PND 30, PND 36, PND 43, and PND 50, for adolescent rats, and PND 60, PND 66, PND 73, and PND 80, for adult rats, assess behavior (described below) for changes in ethanol-induced or saline-induced locomotor activity. 4. On all intervening days, transport animals from the colony to the laboratory, weigh, and intraperitoneally administer their respective saline or ethanol treatment between PND 30–50 for adolescent animals and PND 60–80 for adult animals.

3.2. Behavioral Assessment

1. On days in which animals undergo behavioral assessment for ethanol-induced or saline-induced changes in locomotor activity, transport animals from the colony room, weigh and immediately introduce to the open field. 2. When animals are introduced to the open field, randomly introduce them into different quadrants, with their head facing the outside barrier. This enables the animal enough time to turn around and approach the center zone. Given that adolescent and adult animals are different sizes, this allows for standardization of the animal approaching the center zone. 3. During the initial 40 min of habituation to the open field, animals do not receive any treatment. After 40 min in the open field, enter the room and remove the animal from the open field. 4. Administer the saline or ethanol dose and quickly return the animals to the open field (see Note 4). Animals remain in the open field for an additional 50 min, in which the behavior is digitally recorded by the video tracking system. 5. Following the 50 min after treatment administration, remove animals from the open field and return to the homecage. 6. Before introduction of the animal to the open field and between trials, clean arena with Quatricide (Pharmacal Research

476


Fig. 1. Data depicted are visualizations of the entire track for an individual animal for the entire arena. Shown is an adolescent animal treated with ethanol for the 1st time (left panel ) and the 21st time (right panel ).

Laboratories, Naugatuck, CT), a deodorizer and disinfectant, and subsequently with 70% ethanol (Pharmaco-Aaper, Shelbyville, KY) to remove any lingering odors. Allow to completely dry before introducing the animal to the open field. 7. Several parameters can be assessed using the tracking system. The entire arena can be digitally zoned to assess changes in behaviors (e.g., the inner center zone and the entire arena). The behavioral parameters include total distance moved in both the entire arena and the inner zone, time in the inner zone and latency to approach the inner zone. Given the center of gravity is used as the point for the tracking signal, animals have to enter from the forepaws forward to be recorded as entering the center zone. Representative animal movement for one adolescent rat after ethanol injection obtained from the video tracking system is shown in Fig. 1. 8. The behavioral trial can be quantified using several parameters, including total distance moved (cm), time in zone (sec), approaches to zone (frequency) and latency to approach the center zone (sec), for the entire trial or across time (e.g., 10 min intervals). The Ethovision software digitally records the trial based on the initial parameters used when setting up the arena, including the proper background for visualizing the animal, even lighting, and the use of nonreflective surfaces. All these factors enable the software to distinguish the animal from the background to quantify the movement of the animal based on the user-entered dimensions utilized when setting up the arena.

30

3.3. Tissue Processing and Protein Sample Preparation 3.3.1. Protein Extraction from Brain Tissue


477

1. On PND 65 for adolescent-exposed rats and PND 95 for adult exposed rats (represents 14 day washout period) (see Note 5), harvest brain tissue and prepare tissue for micro-dissection of relevant regions (see Note 6). 2. Add 2 ml of cold (4°C) extraction buffer (see Subheading 2.2) and homogenize samples using a tissue homogenizer until all tissue is completely disrupted (see Note 7). 3. Disrupt tissue homogenate with six bursts (2 s each) of sonication while on ice. Centrifuge at 20,000 × g for 15 min at 4°C. 4. Once homogenized and sonicated, incubate samples on ice for 30 min to allow for additional protein solubilization. 5. Remove the supernatant taking care not to disturb the pelletted cell debris. Protein samples (supernatant) can be stored at −80°C if stopping at this point. 6. Determine protein concentration of samples with a Bradford or Bradford-like protein assay using BSA as a standard.

3.3.2. Protein Digestion with Trypsin

1. Reduce up to 100 μg of total protein (be sure to have equivalent amounts in control and ethanol-treated groups for adult and adolescent animals—four groups total) by adding 2 μl of the TCEP reducing agent (to every 20 μl of protein solution) followed by incubation at 60 min at room temperature. Alkylate the reduced cysteine residues by adding 1 μl of MMTS solution (to every 20 μl of protein solution + 2 μl reducing agent) and incubate for 10 min at room temperature. 2. Add 5 μl of sequencing grade trypsin solution to the protein samples and then digest samples overnight at 37°C.

3.3.3. Preparation for Label-Free Relative Quantitation

1. Load tryptic digests directly onto a 1-ml preconditioned C18 solid phase extraction column, desalt with three column volume washes of 0.1% TFA, and elute with one column volume of 80% acetonitrile, 0.1% TFA (see Note 8). 2. Dry samples in a vacuum centrifuge and resuspend in 50 μl of 0.1% formic acid in water. Analyze the control (adult and adolescent) and ethanol-treated (adult and adolescent) samples separately by LC-MS/MS (Subheading 3.4) with at least two technical replicates.

3.3.4. iTRAQ Labeling of Protein Digests

1. Following trypsin digestion, reconstitute each iTRAQ reagent in 70 μl ethanol and then add to a maximum of 100 μg of the digested samples (see Note 9). Biological averaging can be accomplished by pooling protein samples from multiple animals in each group if desired. 2. Four iTRAQ reagents (114, 115, 116, and 117) are utilized to label two groups of control (adult and adolescent) and two groups of ethanol-treated (adult and adolescent) samples.

478


In the described experiment, 114, 115, 116, and 117 were used to label the control adolescent, ethanol-treated adolescent, control adult, and ethanol-treated adult groups, respectively. 3. Allow labeling to proceed for 1 h at room temperature. Pool the four samples into one 1.5 ml microcentrifuge tube prior to vacuum centrifugation. 4. Centrifuge pooled samples under vacuum until dryness to rid the sample of organic solvent prior to rpHPLC analysis-tandem mass spectrometric analysis (see Note 8). Resuspend in 50 μl of 0.1% formic acid in water. 3.4. Liquid Chromatography Tandem Mass Spectrometry Analysis

1. Perform online rpHPLC-tandem mass spectrometric analysis of the tryptic digests for label-free analysis using a mass spectrometer equipped with a nanoelectrospray ionization source. The mass spectrometer should be recently tuned (which includes ionization source as well as ion transfer optic parameters) and calibrated with appropriate calibration mixture. 2. Load rat brain protein digest onto a 75 μm i.d. × 2 cm capillary trap and desalt with 3% acetonitrile, 0.1% formic acid for 5 min prior to injection onto a 75 μm i.d. × 15 cm analytical column. Following peptide desalting and injection onto the analytical column, a linear gradient provided by a nanoHPLC system is carried out to 40% acetonitrile, 0.1% formic acid in 120 min at 250 nl/min. 3. The methods presented are for mass spectrometric analysis of rat brain tissue with minimal sample fractionation and will result in the identification of typically 80%) of the major MS/MS fragment ions match predicted a, b, or y ions, internal ions, or precursor ions with loss of trimethylamine. 5. The mass accuracy of the fragment ions is within the accepted specification for the q-TOF instrument used for the analysis. For older q-TOF instruments, this would mean within 50 parts per million; for newer instruments this can be within 10 parts per million or better. 6. A minimum of five fragment ions match b or y ions. For small peptides, this criterion can be a problem. 7. The charge state should be reasonable based on the peptide sequence. For most peptides, this means that the charge state equals the number of TMAB tags plus the number of Arg and His residues, although His residues are not always positively charged and peptides detected with two different charge states usually indicates the presence of a His residue. On occasion, some peptides will pick up an additional proton to give a charge state one higher than the maximum predicted from the number of amines, although this is usually a minor form relative to the ion with the correct charge state.

4. Notes 1. Using low-retention mirofuge tubes and pipette tips is important, as some peptides bind regular tubes and tips and are lost during transfers and labeling steps. Whenever possible,

502

J.S. Gelman et al.

rinse and dry tubes and tips with ultrapure deionized water before use. 2. It is extremely important to clean Centricon filters before filtering peptides. These filters often contain glycerol which needs to be washed off before filtering to avoid sample contamination which will substantially interfere with mass spectrometry. Make sure that filters are covered with ultrapure deionized water, and then run the water through the filters at the designated centrifugal speed. Be sure to empty any remaining water before loading extracts for filtering. 3. Avoiding contaminants is important. Small molecules and polymers can substantially interfere with the MS analysis. Clean water is essential. Some brands of microfuge tubes and filtration devices have polymeric contaminants that appear as polyethylene glycol-related compounds on MS; these contaminant signals usually overwhelm the signals from the tissue-derived peptides. 4. Prepare labeling solutions as well as glycine and hydroxylamine solutions fresh each day. It is extremely important to prepare all solutions (HCl, NaOH, glycine, phosphate buffer, and desalting solutions) with ultrapure deionized water to avoid contamination from small organic molecules that can interfere with mass spectrometry. 5. While the quantitative peptidomics technique is able to identify hundreds of peptides and their specific processing forms from a single LC-MS/MS run, the method does not detect every peptide in the sample. For example, peptides lacking an N-terminal free amine (due to post translational modification such as acetylation or pyroglutamylation) that also lack an internal lysine residue are not labeled by the TMAB reagent. These peptides are therefore present as single peaks, and no information on relative levels can be obtained using this method. In other cases, intrinsic factors can cause low ionization efficiency of certain peptides during mass spectrometry. The mass–charge ratios used in these studies (typically 300– 1,700 m/z) excludes very small peptides as well as large peptides that contain few positive charges so that the m/z is greater than 1,700. Finally, the dynamic range of peptide levels in biological samples varies beyond the dynamic range of the mass spectrometry equipment and low abundance peptides are not detectable above the background.

Acknowledgments The development of the techniques described in this chapter was supported by National Institutes of Health grant DA-04494

31

Quantitative Peptidomics in Psychiatric Disorders

503

(L.D.F.). Some of the mass spectrometry was performed in the Dalton Mass Spectrometry Laboratory at the Institute of Chemistry, University of Campinas, Brazil, supported by FAPESP, INCT Bioanalitica, and CNPq. References 1. Hokfelt, T., Bartfai, T., and Bloom, F. (2003) Neuropeptides: opportunities for drug discovery, Lancet Neurol 2, 463–472. 2. Strand, F. L. (2003) Neuropeptides: general characteristics and neuropharmaceutical potential in treating CNS disorders, Progress in drug research. Fortschritte der Arzneimittelforschung 61, 1–37. 3. Rotzinger, S., Lovejoy, D. A., and Tan, L. A. Behavioral effects of neuropeptides in rodent models of depression and anxiety, Peptides 31, 736–756. 4. Hokfelt, T., Broberger, C., Xu, Z. Q., Sergeyev, V., Ubink, R., and Diez, M. (2000) Neuropeptides-an overview, Neuropharmacology 39, 1337–1356. 5. Ishida, H., Shirayama, Y., Iwata, M., Katayama, S., Yamamoto, A., Kawahara, R., and Nakagome, K. (2007) Infusion of neuropeptide Y into CA3 region of hippocampus produces antidepressant-like effect via Y1 receptor, Hippocampus 17, 271–280. 6. Che, F. Y., Vathy, I., and Fricker, L. D. (2006) Quantitative peptidomics in mice: effect of cocaine treatment, J Mol Neurosci 28, 265–275. 7. Decaillot, F. M., Che, F. Y., Fricker, L. D., and Devi, L. A. (2006) Peptidomics of Cpefat/fat mouse hypothalamus and striatum: effect of chronic morphine administration, J Mol Neurosci 28, 277–284. 8. Fricker, L. D., Lim, J., Pan, H., and Che, F. Y. (2006) Peptidomics: identification and quantification of endogenous peptides in neuroendocrine tissues, Mass Spectrom Rev 25, 327–344. 9. Gray, T. S., and Morley, J. E. (1986) Neuropeptide Y: anatomical distribution and

10.

11.

12.

13.

14.

15.

16.

17.

possible function in mammalian nervous system, Life sciences 38, 389–401. Morano, C., Zhang, X., and Fricker, L. D. (2008) Multiple isotopic labels for quantitative mass spectrometry, Analytical chemistry 80, 9298–9309. Che, F. Y., Lim, J., Pan, H., Biswas, R., and Fricker, L. D. (2005) Quantitative neuropeptidomics of microwave-irradiated mouse brain and pituitary, Mol Cell Proteomics 4, 1391–1405. Svensson, M., Skold, K., Svenningsson, P., and Andren, P. E. (2003) Peptidomics-based discovery of novel neuropeptides, Journal of proteome research 2, 213–219. Paxinos, G., and Franklin, K. B. (2001) The Mouse Brain in Stereotaxic Coordinates, Academic Press, San Diego. Julka, S., and Regnier, F. (2004) Quantification in proteomics through stable isotope coding: a review, Journal of proteome research 3, 350–363. Zhang, R., Sioma, C. S., Thompson, R. A., Xiong, L., and Regnier, F. E. (2002) Controlling deuterium isotope effects in comparative proteomics, Analytical chemistry 74, 3662–3669. Che, F. Y., and Fricker, L. D. (2005) Quantitative peptidomics of mouse pituitary: comparison of different stable isotopic tags, J Mass Spectrom 40, 238–249. Lee, J. E., Atkins, N., Jr., Hatcher, N. G., Zamdborg, L., Gillette, M. U., Sweedler, J. V., and Kelleher, N. L. (2010) Endogenous peptide discovery of the rat circadian clock: a focused study of the suprachiasmatic nucleus by ultrahigh performance tandem mass spectrometry, Mol Cell Proteomics 9, 285–297.

sdfsdf

Chapter 32 ADHD Animal Model Characterization: Transcriptomics and Proteomics Analyses Yoshinori Masuo, Junko Shibato, and Randeep Rakwal Abstract Mechanisms underlying behavioral abnormalities of patients with attention-deficit hyperactivity disorder (ADHD) disorder are still unknown. It is worth clarifying alterations in the brain of animal models for ADHD. The animals with neonatal treatment with 6-hydroxydopamine (6-OHDA) and congenic wiggling (Wig) rats show motor hyperactivities during a period of darkness at 4 weeks of age. In rats with 6-OHDA lesions, subcutaneous injection of methamphetamine attenuates hyperactivity, the reverse of its effect in Wig rats. To understand mechanisms underlying such behavioral abnormalities, transcriptomics and proteomics analyses may provide novel information in brain research. The expression of genes and proteins in brain regions can be measured by DNA microarray and two-dimensional gel electrophoresis, respectively. We have shown different expressions of genes and proteins in brains of rats with neonatal 6-OHDA lesions and Wig rats. Key words: Attention-deficit hyperactivity disorder, 6-hydroxydopamine, Wig, DNA array, Gel-based proteomics, Two-dimensional gel electrophoresis

1. Introduction Patients with attention-deficit hyperactivity disorder (ADHD) show motor abnormalities, especially hyperactivity in inappropriate settings during childhood. The etiology of this developmental disorder remains unknown. Several kinds of animal models for ADHD have been described (1). It was first reported that rats with the intracisternal administration of the neurotoxin, 6-hydroxydopamine (6-OHDA), during the neonatal period showed motor hyperactivities during the juvenile period (4–5 weeks of age), which corresponds to preadolescence in humans (2, 3). The hyperactivity resulting from the induction of neonatal 6-OHDA lesions was diminished by psychostimulants, similar to some population of ADHD patients (4, 5). However, symptoms and drug-responsiveness


505

506

Y. Masuo et al.

Fig. 1. Transcriptomics (DNA microarray) at a glance. The Agilent platform is used.

show huge variation in ADHD. Recently, the congenic wiggling (Wig) rat (6) has been suggested to be a kind of ADHD model according to several parameters in Wig rats at 12–14 weeks of age. However, spontaneous motor activity (SMA) has not been investigated during the juvenile period and alterations in the brain. We have demonstrated that Wig rats show motor hyperactivities during a period of darkness at 4–5 weeks of age, similar to rats with neonatal 6-OHDA lesions (7). Subcutaneous injection of methamphetamine accelerates hyperactivity in Wig rats (8), while it attenuates that in 6-OHDA-lesioned rats. To understand mechanisms underlying such different behavior, omics analyses of their brains could be strong tools. Transcriptomics analysis using DNA microarray (Fig. 1) and reverse transcription-polymerase chain reaction (RT-PCR) allow clarifying alterations in the expression of multiple genes in brain regions (9). Proteomics analysis by twodimensional gel electrophoresis (2D-GE; Fig. 2) followed by mass spectrometry reveals changes in protein expression in brain regions (Fig. 3) (9–11).

32

Proteomics and Transcriptomics Analysis of ADHD

507

Fig. 2. Proteomics (2D-GE) at a glance. The IPG system (GE Healthcare) is used in conjunction with either precast (GE Healthcare) or hand-cast (Nipon Eido) polyacrylamide gels.

Fig. 3. The brain regions. Cerebral cortex, striatum, and the midbrain of the rat are shown.


1. Wistar rats are purchased from Clea Japan (Tokyo, Japan). 2. Wig rats are donated from Hokkaido University. These animals are derived from Long Evans Cinnamon (LEC) rats, an animal model for Wilson’s disease, in which accumulated cupper in the liver because of a lack of ceruloplasmin (6). In 1995, four LEC rats (two males and two females) showed distinctive

508

Y. Masuo et al.

motor abnormalities and were named “Wig,” since they shook their heads during walking (wiggling) and twisted their bodies when lifted by the tail. The Wig strain was then established by transferring the gene from the LEC to the Wistar KingAptekman/Hokkaido (WKAH) strain with normal metabolism in copper. 2.2. Subjects and Drugs

1. Pregnant female Wistar rats are purchased 2 weeks post coitus. 2. Saline (0.9% NaCl) is prepared, i.e., NaCl dissolved in Water at 9 g/L, or purchased commercially. 3. Desipramine (Sigma-Aldrich, St. Louis, MO) is dissolved in Saline at 2.5 mg/mL. 4. 0.04% ascorbic acid in Saline containing is prepared (0.4 g/L). 5. 6-OHDA hydrobromide (Sigma-Aldrich) is dissolved in 0.04% ascorbic acid at 15 mg/mL. 6. Methamphetamine (MAP) (Philopon, 3 mg MAP/mL) is purchased from Dainippon Pharmaceutical (Osaka, Japan), and diluted in saline at 0.4 mg/mL.

2.3. Spontaneous Motor Activity

1. The Supermex system (Muromachi Kikai, Tokyo, Japan) is an activity-monitoring system that enables an investigator to perform a multichannel measurement (12). A Supermex sensor (83 × 53 × 35 mm in width × depth × height and 100 g in weight) located in the center of the ceiling of a sound-attenuating chamber (45 × 50 × 35 cm in internal width × depth × height) monitors motion in multiple zones of the home cage through an array of Fresnel lenses. The sensor detects any object with a temperature at least 5°C higher then background. 2. A personal computer with CompACT AMS software (Muromachi Kikaki).

2.4. Brain Dissection

1. Some sheets of tissue paper (KimWipe) are put on glass plate placed on crashed ice. Tissue papers are wet with Saline solution. 2. Scalpel #11 is suitable for dissecting rat brain regions. 3. Two microspatulas made of stainless-steel are useful to assist dissection with a scalpel.

2.5. Transcriptomics Experiments 2.5.1. Preparation of Tissue Powders, RNA Extraction and Quality Check

1. Mortar and Pestle (Ceramic); keep clean/washed and autoclaved/sterile in clean containers or boxes. 2. Liquid nitrogen and container/box for storing/keeping liquid nitrogen. 3. Spatulas (stainless-steel) and magnetic stirrers; keep clean/ washed and autoclaved/sterile in clean containers or boxes. 4. NeoPro gloves (Order no. NPG-888-M/S/XS, Microflex Corporation, Reno NV).

32


509

5. Sterile 2.0-mL clear microtubes (MCT-200-C; Catalog no. 311-10-051, Axygen Scientific, Union City, CA). 6. Sterile 1.5-mL clear microtubes (MCT-150-C; Catalog no.311-08-051, Axygen). 7. QIAGEN RNeasy Mini Kit (Catalog no. 74104, QIAGEN Sciences, Maryland); store at room temperature. 8. UltraPURE Distilled Water DNAse, RNAse Free (Catalog no. 10977-015, GIBCO/Invitrogen, Paisley, UK/Grand Island, NY); store at room temperature. 9. Formamide (Deionized; Catalog no. F9037, Sigma); store at room temperature. 10. Agarose (Fine powder; Code no. 02468-66, Nacalai Tesque, Kyoto, Japan); store at room temperature. 11. 50× TAE buffer (Code no. 313-90035, NipponGene, Tokyo, Japan); store at room temperature. 12. Mupid-ex electrophoresis system (ADVANCE, Tokyo, Japan). 13. Ethidium bromide (EtBr solution; Catalog no. 315-90051, Wako Pure Chemical Industries Ltd., Tokyo, Japan); store at 4°C. 14. MOPS (3-Morpholinopropanesulfonic acid; Catalog no. 34108241, Dojindo Laboratories, Kumamoto, Japan); store at room temperature. 15. 3M Sodium acetate (Catalog no. 316-90081, WAKO); store at room temperature. 16. Glycerol (Catalog no. 070-04941, WAKO); store at room temperature. 17. 0.5M EDTA (pH 8.0; Catalog no. 311-90075, WAKO); store at room temperature. 18. Formaldehyde solution (Catalog no. 063-04815, WAKO); store at room temperature. 19. Ethanol (Catalog no. 054-07225, WAKO); store at room temperature. 20. Chloroform (Catalog no. 018-02606, WAKO); store at room temperature. 21. 2-Mercaptoethanol (2-ME; Catalog no. 21438-82, Nacalai Tesque); store at 4°C. 22. pH FIX 4.5–10.0 (Ref no. 92120, MACHEREY-NAGEL, GmbH & Co. KG, Duren, Germany); store at room temperature. 23. Pipetteman (Gilson Inc., Middleton, Wisconsin) and tips (Gilson; sterile). 24. NanoDrop (Thermo Fisher Scientific Inc., MA) (Fig. 1).

510

Y. Masuo et al.

2.5.2. DNA Microarray

1. QIAzol Lysis Reagent (Catalog no. 79306, QIAGEN); store at 4°C. 2. A rat 44K whole genome oligo DNA microarray chip (G4131A or G4131F; Agilent Technologies Inc., Palo Alto, CA); store at room temperature. 3. Gene Expression Hybridization Kit (Catalog no. 5188-5242, Agilent, Cedar Creek, TX); store at room temperature. 4. Gasket (Part no. G2534-60011, Agilent); store at room temperature. 5. Wash Buffer 1 (Catalog no. 5188-5325, Agilent, Wilmington, DE); store at room temperature. 6. Wash Buffer 2 (Catalog no. 5188-5326, Agilent); store at room temperature. 7. RNase-Free DNase set (Catalog no. 79254, QIAGEN GmbH, Hilden, Germany); store at 4°C. 8. Quick Amplification Labeling Kit (Catalog no. 5190-0424, Agilent); store at −20/40°C. 9. Cyanine CTP Dye Pack (Catalog no. 5188-1170-P, Agilent); store at −20/40°C. 10. RNA Spike-In Kit (Catalog no. 5188-5279, Agilent); store at −80°C. 11. 20-slide staining dish (Glass; Catalog no. 50026564, Wheaton, Millville, NJ) and slide rack (stainless-steel). 12. Big Air Blower (Catalog no. E-6073RL, ETSUMI, Tokyo, Japan). 13. Microarray hybridization chamber (Part no. G2534-60001, Agilent). 14. DNA Microarray Hybridization Oven (Part no. G2545A and G2530-60029, Agilent) (Fig. 1). 15. Agilent Microarray scanner G2565BA (Agilent) (Fig. 1). 16. Software—Agilent Feature Extraction ver.8.1.1.1 or ver 9.5.1 (Agilent).

2.5.3. Semiquantitative RT-PCR

1. AffinityScript QPCR cDNA Synthesis Kit (Catalog no. 600559, Agilent Technologies—Stratagene Products, La Jolla, CA); store at −20/40°C. 2. EmeraldAmpPCR Master Mix (Code no. RR300A, TAKARA Biotechnology (Dalian) Co., Ltd., China); store at −20/40°C.

2.6. Proteomics Experiments

1. Mortar and Pestle (Ceramic); keep clean/washed and autoclaved/sterile in clean containers or boxes.

2.6.1. Preparation of Tissue Powders

2. Spatulas (Sterile), and liquid nitrogen and container/box for keeping liquid nitrogen. 3. Sterile 1.5- and 2.0-mL clear microtubes (Axygen).

32 2.6.2. Extraction of Total Protein


511

1. TCAAEB [acetone (Catalog no. 012-00343, Wako) containing 10% (w/v) trichloroacetic acid (TCA; Catalog no. 20402405, Wako), and 0.07% 2-ME)]. Composition—10% (w/v) TCA: 10 g, 0.07% 2-ME: 70 mL in 100 mL acetone final volume; store at 4°C. 2. Wash buffer: acetone containing 0.07% 2-ME, 2 mM EDTA. Composition—0.07% 2-ME: 70 mL, 2 mM EDTA (500 mM EDTA stock): 400 mL, 1 EDTA-free proteinase inhibitor cocktail tablet (Catalog no. 11873 580 001, Roche Diagnostics GmbH, Mannheim, Germany) in 100 mL acetone final volume; store at 4°C. 3. LB-TT: 7M urea (Catalog no. 35940-65, Nacalai Tesque), 2M thiourea (Catalog no. T7875-100G, Sigma), 4% (w/v) CHAPS (Catalog no. C3023-5G, Sigma), 18 mM Tris–HCl (pH 8.0), 14 mM trizma base (Catalog no. 35434-34, Nacalai Tesque), two EDTA-free proteinase inhibitor cocktail, 0.2% (v/v) Triton X-100 (R; Catalog no. 282103, Sigma-Aldrich), containing 50 mM dithiothreitol (DTT; Catalog no. D9779-5G, Sigma). The details for preparation of LB-TT are given in Fig. 4. 4. 2D Clean-Up Kit (Catalog no. 80-6484-70, GE Healthcare Bio-Sciences AB, Uppsala, Sweden). 5. Coomassie Plus™ protein assay kit (Catalog no. 23238, Thermo Scientific, Rokford, IL); store at 4°C.

2.6.3. Two-Dimensional Gel Electrophoresis

1. IPG strip gels (GE Healthcare); store at −20/40°C. 2. IPGphor unit (GE Healthcare) (Fig. 2). 3. 12.5% homogenous and 12–14% gradient precast polyacrylamide gels (PAGs; GE Healthcare). For precast gels, store at 4°C. 4. Nihon Eido (Tokyo, Japan) sodium dodecyl sulfate-PAG electrophoresis (SDS-PAGE) vertical electrophoresis unit. 5. LB-TT containing 0.5% (v/v) pH 4–7 IPG buffer and DTT; store at −20/40°C. 6. Bromophenol blue (BPB; Catalog no. 05808-32, Nacalai Tesque). 7. Cover fluid (Catalog no. 17-1335-01, GE Healthcare). 8. Equilibration buffer: 50 mM Tris–HCl (pH 8.8), 6M urea, 30% (v/v) glycerol, 2% (w/v) SDS (Catalog no. 161-0301, BIO-RAD) containing 2% (w/v) DTT; store at −20/40°C. 9. Equilibration buffer supplemented with 2.5% (w/v) iodoacetamide (Catalog no. 093-02152, WAKO). 10. Cathode running buffer: 0.025M Tris, 0.192M glycine (Catalog no. 075-00616, WAKO) and 0.2% (w/v) SDS. 11. Overlay agarose solution: 60 mM Tris–HCl, pH 6.8, 60 mM SDS, 0.5% (w/v) agarose, 0.01% (w/v) BPB; store at −20/40°C.

512

Y. Masuo et al.

Fig. 4. Scheme for preparation of LB-TT.

12. Lower anode buffer contained 0.05M diethanolamine (Catalog no. 111-42-2, WAKO) and 0.05M acetic acid (Catalog no. 010-00241, WAKO). 13. SDS-PAGE: 4% T, 2.6% C stacking gels, pH 6.8 and 12.5% T, 2.6% C separating gels, pH 8.8. The % T is the total monomer concentration expressed in grams per 100 mL and % C is the percentage cross-linker.

32


513

14. 0.125M Tris–HCl, pH 6.8. 15. 0.375M Tris–HCl, pH 8.8. 16. DualColor PrecisionPlus Protein™ Standard Protein Markers (Catalog no. 131-0374, BIO-RAD); store at −20/40°C. 2.6.4. Protein Visualization and Spot Quantitation

1. Silver nitrate (Plus One Silver Staining Kit Protein; GE Healthcare); store at 4°C. 2. ImageMaster 2D Platinum software ver. 5.0 (GE Healthcare) or LUDESI image analysis service (http://www.ludesi.com). 3. Gel picker (One Touch Spot Picker, P2D1.5 and 3.0, The Gel Company, San Francisco, CA).

2.7. Proteomics with Mass Spectrometry

1. Destain solution: 30 mM potassium ferricyanide (Sigma-Aldrich, St. Louis, MO) in 100 mM sodium thiosulfate (Merck, Darmstadt, Germany).

2.7.1. MALDI-TOF-MS

2. 200 mM ammonium bicarbonate (Sigma; and hereafter called AMBIC). 3. 50 mM AMBIC containing 0.2 mg modified trypsin (Promega, Madison, WI). 4. C18 nanoscale (porus C18) column (homemade). 5. Matrix solution: 70% acetonitrile (Merck), 0.1% TFA (Merck), 10 mg/mL alpha-cyano-4-hydroxycinnamic acid (Sigma). 6. MALDI-TOF-MS Manchester, UK).

(Model

M@LDI-R;

Micromass,

7. Trypsin autodigestion product (m/z 2211.105). 2.7.2. Q-TOF-MS/MS

1. 5% formic acid. 2. Methanol–H2O–formic acid (50/49/1, v/v/v). 3. Precoated borosilicate nanoelectrospray needles (EconoTip™, New Objective). 4. Q-TOF2 MS (Micromass). 5. MassLynx (Ver. 3.5) Windows NT PC system.

2.7.3. nESI-LC-MS/MS

1. 100 mM AMBIC. 2. Acetonitrile (Catalog no. 012-19851, WAKO). 3. 10 mM DTT. 4. 50 mM iodoacetamide. 5. 20 mM AMBIC containing 15 ng/mL sequence grade modified trypsin (17,000 U/mg; Promega). For Trypsin; store at −80°C. 6. 20 mM AMBIC. 7. 0.5% trifluoroacetic acid (TFA) in 50% acetonitrile.

514

Y. Masuo et al.

8. LCQ Deca linear ion trap mass spectrometer (nESI-LC-MS/ MS; Thermo Electron, Waltham, MA). On-line capillary LC includes a monolithic reverse-phase trap column (0.2 mm × 5 cm, MonoCap for fast-flow, GL Science, Tokyo, Japan) and a fastequilibrating C18 capillary column (monolith-type column; i.d, 0.1 mm; length, 50 mm; GL Science). 9. Solvent A: H2O–acetonitrile–formic acid, 98/2/0.1 (v/v). 10. Solvent B: H2O–acetonitrile–formic acid, 10/90/0.1 (v/v). 11. Fused-silica Fortis Tip emitter (150 mM OD, 20 mM ID; AMR Inc., Tokyo, Japan) 2.8. 1D-GE, Subcellular Fractionation and Western Analysis

1. ProteoExtract Subcellular Proteome Extraction Kit (EMD Chemicals Inc., Darmstadt, Germany). 2. LB-TT, Coomassie Plus™ Protein Assay Kit, BPB, and 12.5% PAGs (hand-cast or precast; Catalog no. 2331820, ATTO e-PAGEL E-T12.5L, ATTO, Tokyo, Japan). 3. SDS sample buffer: 62 mM Tris (pH 6.8), 10% (v/v) glycerol, 2.5% (w/v) SDS, and 5% (v/v) 2-ME. 4. Running buffer composed of 0.025 M Tris, 0.192 M glycine, and 0.2% (w/v) SDS. 5. Polyvinyldifluoride (PVDF) membrane (NT-31, 0.45 mM pore size; Nihon Eido). 6. Semidry blotter (Nihon Eido). 7. Primary antibodies (Abcam Ltd., Cambridgeshire, UK, and/ or Custom antibodies). 8. Secondary antibody (anti-Rat IgG-H&L, Horseradish peroxidase linked whole antibody; from rabbit; GE Healthcare); store at 4°C. 9. The ECL+plus Western Blotting Detection System (GE Healthcare, Little Chalfont, Buckinghamshire, UK); store at 4°C. 10. X-ray film (X-OMAT AR, Kodak, Tokyo, Japan); store in the dark at room temperature.

3. Methods Investigation of an animal model for ADHD requires numerous approaches, such as preparation of animal models, behavioral experiments, dissection of the brain, and omics analyses. It is important to note that each of the steps involved in the experiment must be carefully planned and executed. This is necessary to avoid any mistakes, especially at the omics analyses step, as any error can

32


515

be costly. The cost of performing the DNA microarray and proteomics experiments are to be carefully considered before initiating the experiment. Other than that a good experimental strategy must be in place before starting the research. The outcome of both the transcriptomics and proteomics analyses ultimately will depend on the starting material and sample preparation. The results of these analyses will give a global profile of gene and protein changes in the samples being analyzed. 3.1. Animals

1. The animals are housed in a transparent plastic home cage (24 × 30 × 18 cm in width × depth × height) with tap water and laboratory diet (Oriental Yeast, Tokyo, Japan) ad libitum under specific-pathogen-free conditions in an animal room at 23 ± 2°C and a relative humidity of 50 ± 20%. The animal rooms are illuminated from 07:00 to 19:00 h (12-h cycles) (see Note 1).

3.2. 6-OHDA Treatment

1. Neonatal male pups are randomly assigned to lactating dams, with 5–7 pups per dam. 2. 5-day-old pups, each weighing approximately 10 g, are injected intraperitoneally with desipramine at 25 mg/kg (100 mL of prepared solution for 10 g, b.w.). 3. 30 min later, 10 mL of 6-OHDA solution are administered intracisternally. Vehicle (saline containing 0.04% ascorbic acid) alone is injected under similar conditions after injection of desipramine. 4. The pups are returned to the nursing dams until they are weaned at 3 weeks of age. All the rats are maintained in 12 h light–dark cycles, illuminated from 07:00 to 19:00 h.

3.3. Spontaneous Motor Activity (SMA)

1. At 4–5 weeks of age, single rats are placed in a transparent plastic home cage within a sound-attenuating chamber with a Supermex sensor. The sensor output is automatically transmitted to a personal computer, where it is converted to the number of movements, recorded, and analyzed using CompACT AMS software. 2. SMA is measured over 24 h, starting at 18:00, with darkness from 19.00 to 7.00 and light from 7:00 to 19:00. SMA in rats with neonatal 6-OHDA lesions and Wig rats are compared with those in each controls: rats treated with the vehicle for 6-OHDA and WKAH rats, respectively. 3. In some experiments, MAP are injected subcutaneously, 30 min prior to the start of dark phase to evaluate the effects of MAP in the first few hours of the dark cycle. The dose of MAP is 4 mg/kg, i.e., injection of 0.1 mL MAP solution is adequate for 10 g, body weight.

516

Y. Masuo et al.

3.4. Brain Dissection

1. Rats are decapitated at 4 weeks of age. Whole brains are rapidly removed and placed on an ice-cold glass plate with the ventral surface upward (8) (see Note 2). 2. The olfactory tubercles are dissected from both hemispheres. A transverse cut is made at the level of the posterior limb of the frontal cortex. 3. The frontal cortex is separated from the olfactory bulb, and the olfactory bundle is removed from the hypothalamus. 4. The remaining brain is turned over and both hemispheres are separated, to the depth of the corpus callosum. After the lateral ventricle is exposed, the striata and cortices are removed from the thalamus. 5. The striatum in each hemisphere is gently separated from the cortex with two microspatulas, and cut into dorsal and ventral parts if necessary. The core and shell of the nucleus accumbens are included in the ventral striatum. 6. By transverse cut at the level of the posterior limb of the mammillary body, the thalamus and hypothalamus are removed. The midbrain, containing the substantia nigra and ventral tegmental area, is then removed. 7. Tissue samples (brain regions; see Fig. 3) are frozen in liquid nitrogen; store at −80°C.

3.5. Transcriptomics Experiments 3.5.1. Preparation of Tissue Powders, RNA Extraction and Quality Check

1. Frozen brain regions are respectively placed in liquid nitrogen, and ground thoroughly to a very fine powder with a mortar and pestle (Fig. 5) (see also the work conducted by Masuo and coworkers (10); (see Note 3). 2. For extraction of RNA and protein, approximately 100 mg powder is used. 3. Good quality total RNA is extracted as per the modified/optimized protocol used by our group, and which is detailed in Fig. 6 (see Note 4). 4. The quality of RNA is the single most important factor in determining the outcome of any transcriptomics analysis, and for this the yield and RNA purity is determined spectrophotometrically (NanoDrop) and visually confirmed using formaldehydeagarose gel electrophoresis (Fig. 7) (see Note 5).

3.5.2. DNA Microarray

1. Total RNA from each (150 ng) of the three brain regions (frontal cortex, striatum and midbrain) is pooled together into one master total RNA mix (450 ng), and labeled with Cy-3 or Cy-5 using an Agilent Low RNA Input Fluorescent Linear Amplification Kit. It should be mentioned that we now routinely use 800 ng total RNA for most experiments, i.e., a single array, instead of 400 ng used previously.

32


517

Fig. 5. The brain (rat) grinding protocol.

2. Fluorescently labeled targets of control and Wig samples are hybridized to the same microarray slide with 60-mer probes. A flip labeling (dye-swap or reverse labeling with Cy3 and Cy5 dyes) procedure is followed to nullify the dye bias associated with unequal incorporation of the 2 Cy dyes into cDNA (13–15). The use of a dye-swap approach (9, 16, 17) provides a very stringent selection condition for changed genes rather than simply doing 2 or 3 replicates, which overlook the dye bias. 3. The strategy/design of the microarray experiment is presented in Fig. 8. A rat 44K whole genome oligo DNA microarray chip is used. Hybridization and wash processes are performed according to the manufacturer’s instructions, and hybridized

518

Y. Masuo et al.

Fig. 6. Total RNA extraction protocol optimized for the rat brain.

32


Fig. 7. Formaldehyde gel electrophoresis for determining the good quality of extracted total RNA.

519

520

Y. Masuo et al.

Fig. 8. The DNA microarray experimental workflow.

microarrays are scanned using an Agilent Microarray scanner G2565BA. 4. For detection of significant differentially expressed genes between ADHD model and control rat samples, each slide image is processed by Agilent Feature Extraction ver.8.1.1.1. This software measures Cy3 and Cy5 signal intensities of whole probes. Dye-bias tends to be signal intensity-dependent; therefore, this software selects a probe set by rank consistency filter for dye-normalization, and the normalization is done by LOWESS (locally weighted linear regression) and it calculates log ratio of dye-normalized Cy3- and Cy5-signal, and final error of log ratio and significant value (P-value) based on propagate error model and universal error model. The threshold of significant differentially expressed genes determines p-value 50 nga

Based on manufacturers’ specifications

544

P.P. Sanna et al.

3. Methods The present methods are in use in our labs for the analysis of laser-microdissected brain regions, subregions, and neuronal populations using the Leica AS LMD® for gene expression analysis. Protection of RNA from degradation is a key to the success of the procedure. As reviewed below, for RT-PCR analysis, commercial products exist that allow one to straight-forwardly extract and quantitate specific genes from small total RNA samples. For microarray analyses, different options exist if analysis of miRNA and DNA is also desired and for different microarray platforms. For instance, because of the small amounts of total RNA obtained by laser microdissection, we obtained very good results with strategies consisting of two rounds of in vitro transcription (IVT). These methods produce 3¢ biased targets that are most effective on microarray platforms with a 3¢ biased design. We previously showed that results with RNA samples subjected to one or two rounds of IVT were highly correlated on this type of array (3). Conversely, methods have also been established to amplify the whole transcriptome and can be used to generate targets for profiling laser-microdissected RNA samples on microarrays targeting the whole transcript such as Affymetrix Exon and Gene ST arrays and for use with degraded and archival RNA. Overall, while the strategies reviewed in the present chapter are only a partial list based on the methods in use in our labs, they support that a large selection of methods and commercial products is currently available which allows one to implement routine gene quantitation and profiling from laser-microdissected brain regions, subregions, and neuronal populations. 3.1. Laser Microdissection Procedure

1. The UV laser in the Leica AS LMD® can be moved throughout the field of view by computer using the mouse to outline the desired cut on the microscope field displayed on the computer screen. 2. When a satisfactory outline is obtained, the operator can command the laser by software to microdissect the area of interest. Realtime laser cutting is also possible with later models. 3. The microdissected tissue attached to its membrane support is collected by gravity in the caps of 200 ml microcentrifuge tubes containing RNA extraction buffer. 4. Four 200 ml microcentrifuge tubes can be placed in a rack holder built into the motorized stage, allowing one to simultaneously dissect and individually pool up to four brain regions or cell populations from multiple tissue sections. 5. The dissection of most of the brain subregions of interest to neuroscience research (e.g., cortical subregions; shell and core

34

Gene Profiling in Individual Cells in Drug Abuse and Schizophrenia Animal Model

545

subregions of the nucleus accumbens (NA); the medial, lateral, basolateral, and central amygdala nuclei; dorsolateral, mediolateral, ventral BNST subregions; etc.) require low magnification (4×–10×) optics. 6. As the UV laser is delivered through the microscope lens, its power is increased by the magnification power of the lens, thus cutting efficiency is reduced at lower magnifications. For this reason, Leica has introduced a new series of laser microdissection-dedicated objectives for optimal UV transmission. This line of lenses, called SmartCut, includes objectives with magnifications of 6.3×, 40×, and 63×, and a 150× dry high magnification objective for single-cell dissection without using oil (see Note 1). For laser microdissection at low magnification, we also use a Zeiss 5× Fluar lens that is engineered for maximal UV transmission. These lenses allow for efficient cutting at low magnification without the need for multiple cutting to completely dissect the regions of interest. 3.2. Laser Microdissection of Brain Regions

1. The condenser of the Leica AS LMD® is optimized for the noncover slipped tissue sections that are used for laser microdissection and provides sufficient contrast to allow for dissection of brain regions and subregions using anatomical landmarks in unstained sections (3). Therefore, we generally use the present protocol for the dissection of brain regions and subregions without prior staining. 2. If staining is required, e.g., for brain regions with limited tissue texture, counterstaining by brief exposure to 0.1% toluidine blue (5) can be used before dehydration in graded ethanol solutions. Hematoxylin or cresyl violet can also be used for counterstaining (10–14). 3. While tissue dehydration provides some protection from degradation of RNA, to minimize RNA degradation and the resulting variability in RNA quality and yield, animals can be perfused intracardiacly with an ice-cold commercial RNA protectant, RNA later (Ambion) diluted 10% in PBS (3). This dilution reduces the density and viscosity of the undiluted solution allowing it to penetrate the brain microvasculature and reduce its effect of shrinking the tissue, which interferes with reliable and reproducible identification of the brain regions of interest. 4. Following perfusion, brains are then rapidly removed (see Note 2) and frozen by immersion in 2-methylbutane in an ethanol/dry ice bath. Frozen tissue is stored at −80°C until sectioning (see Note 3). 5. We use PENfoil slides for laser microdissections. These are microscope slides comprising a rigid perimeter frame surrounding

546

P.P. Sanna et al.

a very thin transparent foil insert on which tissue sections are mounted. The foil insert is composed of polyethylene naphthalate (PEN), which is absorptive in the UV-A range facilitating laser microdissection with UV laser systems (see Note 4). Other supports are also available through Leica. Leica AS LMD® uses a UV laser to cut through the tissue and the foil support. 6. For laser microdissection of brain and subregions, we cryostat section the tissue at 30–60 mm thickness and brush-mount sections onto PENfoil slides. Thicker sections allow one to reduce the laser dissection time, but they can be more difficult to mount flat, and to reduce anatomical resolution. 7. After brush-mounting sections, they are quickly thaw-mounted on the PENfoil slides and collected in a covered slide box kept inside the cryostat while sectioning. 8. Sections are then ethanol dehydrated by placing for 20 s each in graded ethanol solutions (75, 95, 100%) and then air-dried for 1 min before proceeding to laser microdissection. Similar results are also obtained by placing the slides in a vacuum desiccator jar containing dry ice in the bottom compartment and desiccating overnight. 9. The next morning the vacuum is gently released and the slides are sectioned one at a time, while the remaining slides are stored under vacuum. 3.3. Laser Microdissection of Neuronal Populations

1. For laser microdissection of individual neurons, brain tissue is sectioned to 20 mm thickness and mounted on PENfoil slides (see Note 5). 2. Tissue is then immersed in graded ethanol as described above, and stained briefly with 0.1% toluidine blue. This staining method allows differentiation of neurons from glial cells using morphological criteria such as size, the presence or absence of visible cytoplasm, and the distribution of chromatin within the nucleus (15, 16). 3. This procedure yields a good RNA recovery (6) and can be applied successfully to human brain samples (5). Since human dopaminergic neurons contain neuromelanin, they can be visualized for laser microdissection without staining (17). 4. If specific immunofluorescence staining prior to laser microdissection is required for the identification of specific cell types, various strategies have been devised (18–20). In particular, a method for reversibly fixed tissue with dithio-bis (succinimidyl propionate) (DSP), also known as Lomant’s reagent, allows to protect RNA in tissue sections during immunostaining (19). Transgenic mice expressing fluorescent proteins under specific promoters can also be used for cell-type identification without further staining.

34

Gene Profiling in Individual Cells in Drug Abuse and Schizophrenia Animal Model

547

5. Cells are then microdissected at high magnification using the Leica AS LMD®. To minimize variability, we collect pools of 100–250 cells from multiple fields of approximately 40 consecutive tissue sections, e.g., ten fields from four sections each. 3.4. RNA Extraction and Amplification

1. RNA extraction. All of the kits listed in Table 1 can be used for the extraction of RNA from laser-microdissected brain regions or pools of 100–250 cells as outlined above. The Arcturus Picopure RNA Isolation Kit (Arcturus) and the RNeasy Micro Kit from Qiagen (Valencia, CA, USA) are highly consistent kits for total RNA recovery of total RNA from samples as little as single cells (see Note 6). However, neither of these kits is designed for recovery of miRNA. The MirVana miRNA isolation kit (Ambion) and the RecoverAll Total Nucleic Acid Isolation Kit (Ambion) can be used to isolate both total RNA and miRNA for RT-PCR and microarray analyses. The former is designed for samples of 100 cells or more. The latter also allows for DNA recovery and is designed to extract nucleic acids from fixed tissue sections. 2. cDNA synthesis. For cDNA synthesis for RT-PCR, we use the iScript cDNA synthesis kit (Biorad) and the SuperScript® III First-Strand Synthesis System (Invitrogen), both of which are effective over a broad range of total RNA inputs in the range of 100 fg to 1 mg (see Note 7). The iScript cDNA synthesis kit (Biorad), by means of both oligo (dT) and random primers, efficiently generates cDNAs twofold, but this depends on dataset) are reported after correction using the differential protein-expression profiling results from multiple biological replicates in addition to manual data interrogation and validation by alternate biochemical approaches (see Note 13). 7. Use Cytoscape equipped with the BiNGO plug-in to determine statistically overrepresented or underrepresented gene ontology (GO) categories of the entire HAPI cell proteomic dataset or of the differentially expressed proteins in HAPI cells after ethanol exposure. Appropriate parameters for selection in this analysis include hypergeometric statistical test, significance level of p < 0.05, and correction for multiple term testing by Benjamini and Hochberg false discovery rate corrections. Download GO annotations from the current GOA Rat file in order to create a reference set for the rat protein database used. Example of GO data obtained for the entire HAPI cell proteomic dataset (~ 1,000 proteins identified) is shown in Fig. 3.

562

B. Liu et al.

a

Cellular Assembly & Organization 18%

Protein Synthesis 16%

Cell Death 26%

Cell-to-Cell Signaling & Interaction 3%

Molecular Transport 12%

Cell Morphology 11% Protein Trafficking 7%

Cell Signaling 4%

Increased ROS

Decreased ROS

AIFM1, ARHGDIB, BAX, CARD9, CAT, PNPT1, RAC1, RAC2, SLC25A10, VDAC1, HSD17B10

ALDH2, SOD1, ANXA1, CAT, TRAP1, YWHAZ

Free Radical Scavening 3%

b PM, 47

Vesicle, 55 Cytoskeleton, 74 Cytosol, 83 ER, 35

Nucleus, 202 Mitochondrion, 83

Fig. 3. (a) Overrepresented biological processes identified for the entire HAPI proteome dataset. An example for the biological process, free radical scavenging, is shown, where proteins listed represent those implicated in the modulation of reactive oxygen species (ROS) production. (b) Protein localization as identified by BiNGO. The data point indicates the number of proteins found in the combined dataset. PM and ER denote plasma membrane and endoplasmic reticulum, respectively.

4. Notes 1. As with most, if not all, immortalized cell lines, HAPI microglial cells cannot be continuously propogated in culture. For each round of SILAC labeling experiment, microglial culture is started with a new cryopreserved vial of HAPI cells.

35

Proteomics of Ethanol-Induced Protein Expression in Microglia

563

2. An analytical HPLC can also be used in which the flow rate is split from the normal operating range (0.2–1 ml/min) to 250 nl/min using an appropriate splitting mechanism. 3. Prolonged exposure of cells to trypsin should be avoided. A 2-min contact time is usually sufficient to dislodge the cell monolayer. Tapping a few times on the side of the flask with one hand while holding the flask with the other hand, after the 2-min trypsin treatment, helps ensure the dislodge of most cells (>99%). 4. HAPI microglial cells have a doubling time of approximately 18–20 h under the stated culture conditions. 5. To ensure complete labeling of HAPI cell proteins with the stable isotope-labeled amino acids, take an aliquot containing a small number of cells (corresponding to approximately 1 μg of total protein) for mass spectrometric analysis following procedures outlined in Subheadings 3.3–3.5. It is important that labeling is complete (based on the absence of lower mass isotopes of the labeled peptide—i.e., peaks lower in mass than the predicted monoisotopic peak) before starting ethanol exposures. 6. A 3-day treatment period for immortalized HAPI microglial cells is generally the longest to administer because of the continuing doubling of cells in DMEM with 5% FBS. Longer treatment times are not desirable because cells tend to overgrow and become partially starved for nutrients and start to be negatively affected by metabolic wastes. 7. Other protein and/or peptide fractionation approaches can be used at this point. For example, molecular weight (MW) fractionation at the protein level using 1D SDS-PAGE can be performed on pooled control and ethanol-treated cell lysates. With this method, the gel lane can be sliced into 10–20 MW fractions, where the proteins can be digested in-gel with trypsin. 8. A larger i.d. column allows for a higher peptide digest loading capacity if necessary. Additionally, a longer column or adjustment of gradient conditions (e.g., longer gradient) can improve peptide fractionation efficiency in order to further reduce sample complexity before mass spectrometric analysis. The tradeoff is proteome coverage versus overall sample analysis time. 9. Several high-resolution mass spectrometers (e.g., hybrid quadrupole time-of-flight instruments) are commercially available that can provide the appropriate mass resolution and accuracy to carry out SILAC-based quantitative proteomics experiments. Data-dependent (or information-dependent) acquisition parameters shown in this section are for an Orbitrap mass spectrometer and these standard parameters can be optimized accordingly depending on instrument type.

564

B. Liu et al.

10. There are multiple databases that can be used for the database search. We have used organism-specific International Protein Index databases from the European Bioinformatics Institute. Taxonomy-specific searches can also be performed with general databases (e.g., SwissProt or the NCBI nonredundant database). Sequest and Mascot represent commonly used commercially available search algorithms; however, other opensource and public search algorithms are available, such as X! Tandem (The Global Proteome Machine Organization) and the Open Mass Spectrometry Search Algorithm (NCBI). 11. When using urea in the protein extraction buffer, it is important to consider carbamylation of basic residues since this can occur readily at higher temperatures or if the urea solution has degraded over time. Chemical artifacts introduced by modification of buffer components by the user should be considered carefully. Also, given that arginine can be metabolically converted to proline, artifact introduction can complicate data analysis for protein identification by database searching as well as quantitation of SILAC-labeled peptide pairs based on this metabolic conversion. Therefore, careful consideration should be made for quantitation of proline-containing peptides. 12. Careful consideration should be made for protein isoforms and posttranslational modifications when carrying out peptide quantitation. 13. While proteomic data has been consistently demonstrated to provide accurate relative quantitation, results should be validated by performing western blots for selected proteins whose expression is modified and at least one whose expression was unaltered. Western blots should be performed on a subsample of the initial cell lysate that was used for proteomic analysis before trypsin digestion.

Acknowledgments We thank Amanda Edson and Jean Horak for technical assistance and the Florida Center of Excellence for Drug Discovery and Innovation Proteomics Facility for providing access to analytical instrumentation for proteomics analysis. References 1. Bates, M. E., Bowden, S. C., and Barry, D. (2002) Neurocognitive impairment associated with alcohol use disorders: implications for treatment. Exp. Clin. Psychopharm. 10, 193–212.

2. Nixon, K. (2006) Alcohol and adult neurogenesis: roles in neurodegeneration and recovery in chronic alcoholism. Hippocampus 16, 287–295.

35

Proteomics of Ethanol-Induced Protein Expression in Microglia

3. Harper, C. (1998) The neuropathology of alcohol-specific brain damage, or does alcohol damage the brain? J. Neuropath. Exp. Neur. 57, 101–110. 4. Blanco, A. M., Valles, S. L., Pascual, M., and Guerri, C. (2005) Involvement of TLR4/type I IL-1 receptor signaling in the induction of inflammatory mediators and cell death induced by ethanol in cultured astrocytes. J. Immunol. 175, 6893–6899. 5. Crews, F. T., Bechara, R., Brown, L. A., Guidot, D. M., Mandrekar, P, Oak, S., et al. (2006) Cytokines and alcohol. Alcohol Clin. Exp. Res. 30, 720–730. 6. McDonough, K. H. (2003) Antioxidant nutrients and alcohol. Toxicology 189, 89–97. 7. He, J., and Crews, F. T. (2008) Increased MCP-1 and microglia in various regions of the human alcoholic brain. Exp. Neurol. 210, 349–358. 8. Qin, L., He, J., Hanes, R. N., Pluzarev, O., Hong, J. S., and Crews, F. T. (2008) Increased systemic and brain cytokine production and neuroinflammation by endotoxin following ethanol treatment. J. Neuroinflamm. 5, 10. 9. Aloisi, F. (1999) The role of microglia and astrocytes in CNS immune surveillance and immunopathology. Adv. Exp. Med. Bio. 468, 123–133.

565

10. Streit, W. J., Walter, S. A., and Pennell, N. A. (1999) Reactive microgliosis. Prog. Neurobiol. 57, 563–581. 11. Liu, B., and Hong, J. S. (2003) Role of microglia in inflammation-mediated neurodegenerative diseases: mechanisms and strategies for therapeutic intervention. J. Pharmacol. Exp. Ther. 304, 1–7. 12. Liu, B., Gao, H. M, and Hong, J. S. (2003) Parkinson’s disease and exposure to infectious agents and pesticides and the occurrence of brain injuries: role of neuroinflammation. Environ. Health Perspect. 111, 1065–1073. 13. Ong, S. E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., et al. (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 1, 376–386. 14. Cheepsunthorn, P., Radov, L., Menzies, S., Reid, J. and Connor, J. R. (2001) Characterization of a novel brain-derived microglial cell line isolated from neonatal rat brain. Glia 35, 53–62. 15. Zhang, P., Hatter, A., and Liu, B. (2007) Manganese chloride stimulates rat microglia to release hydrogen peroxide. Toxicol. Lett. 173, 88–100.

sdfsdf

Chapter 36 Systems Biology in Psychiatric Research: From Complex Data Sets Over Wiring Diagrams to Computer Simulations Felix Tretter and Peter J. Gebicke-Haerter Abstract The classification of psychiatric disorders has always been a problem in clinical settings. The present debate about the major systems in clinical practice, DSM-IV and ICD-10, has resulted in attempts to improve and replace those schemes by some that include more endophenotypic and molecular features. However, these disorders not only require more precise diagnostic tools, but also have to be viewed more extensively in their dynamic behaviors, which require more precise data sets related to their origins and developments. This enormous challenge in brain research has to be approached on different levels of the biological system by new methods, including improvements in electroencephalography, brain imaging, and molecular biology. All these methods entail accumulations of large data sets that become more and more difficult to interpret. In particular, on the molecular level, there is an apparent need to use highly sophisticated computer programs to tackle these problems. Evidently, only interdisciplinary work among mathematicians, physicists, biologists, and clinicians can further improve our understanding of complex diseases of the brain. Key words: Molecular psychiatry, Neurotransmitter, Molecular networks, Data analysis, Modeling, Computer simulations

1. Introduction Psychiatric research has to put together “soft” data, such as reports on subjective experiences or clinical observations, and biological data that are gathered by sophisticated technologies. However, the approach to reduce mental phenomena to biomolecular properties of the brain has its practical limitations: the amount of data that can be generated by high-throughput tools cannot be analyzed adequately without special mathematical procedures that are adapted to complexity analysis and/or nonlinear behavior. This issue is the aim of “Systems Biology” that is not only interested in


567

568

F. Tretter and P.J. Gebicke-Haerter

Table 1 Checklist of some symptoms for psychiatric clinical examination (reproduced from ref. 3 with kind permission from Wiley-Blackwell) Consciousness : Wakefulness, orientation, concentration, attention Perception: Illusions, hallucinations as pathological function Thinking: Thought disorder, delusions as pathological function Speech: Aphasia as pathological function Memory: Working memory, short-term memory, long-term memory (amnesia as pathological function) Emotions : Acute or sustained anxiety, depression, mania, dysphoria, etc. Motivation: Incentive, sexual interests, interests, hobbies Motor behavior: Coordination, goal-directed movements

data analysis, but also in construction of computational models of biological functions. The way of systemic thinking can be applied successfully in psychiatric research. 1.1. Methodological and Philosophical Aspects of Psychiatry

Psychiatry is concerned with the diagnosis, causes, and treatment of mental disorders. In clinical practice, the psychiatrist has to explore various single mental functions, such as consciousness, perception, thinking, memory, affective behavior, etc., regarding their functional level and order (see Table 1). Several symptoms, such as acoustic hallucinations and delusions, can be related to a mental illness, such as schizophrenia. However, hallucinations, delusions, and other symptoms are not specific for any mental illness. For instance, LSD, phencyclidine (PCP), or cocaine can induce hallucinations and/or delusions, a mental state that is classified as a drug-induced psychosis (1). Such findings show that mental disorders are related to biological mechanisms. Therefore, for biological psychiatry, it is important that symptoms are correlated to biological peculiarities. On the other hand, some biological properties are specific for mental disorders. These properties are called “endophenotypes” (2). Despite substantial progress in the precision of psychiatric methods and concepts especially by biological psychiatrists, a lot of questions were raised if psychiatry can be an objective “discipline” (4). At first, it is questionable if psychiatry can be practiced “objectively” without a “subject” that is suffering from mental dysfunctions and is reporting about its experiences. It seems not to be possible to reduce the mental sphere to an observational level of behavior in a sufficient way (5). At present, only a few mental functions, such as working memory, can be tested in an objective way (see below).

36

Systems Biology and Psychiatry

569

Fig. 1. Working memory in a functionalistic input–output view: a persisting response to brief stimulus and pathological patterns a: (a) weak onset, (b) weak response level, (c) fast decline, (d) prolonged response; modified from refs. 3 and 8; modified reproduction with kind permission by Wiley-Blackwell Publisher.

Another question of scientific value is related to the validity of diagnosis with the aim to distinguish a “normal” way of perceiving, thinking, memorizing, etc., from “pathological” perceiving, thinking, and memorizing as in most cases no objective technology can be used. Especially in case of delusion, the relation to “reality” is hard to be determined. 1.2. Functional Definitions of Mental States

Some progress has been made regarding a functionalistic turn in psychopathology that is based on the behavioristic input–output analysis (6, 7). For instance, for the “operational definition” of working memory and its deficiencies, a fruitful conception has been developed. In this view, a memory function can be characterized as a prolonged reaction to a brief stimulus. Regarding this view, a working memory function is a transient storage of information (e.g., location of a visual stimulus in space) of intermediary use in complex information processing. In consequence, a brief sustained, but finally finished, memory function becomes pathological if it appears too late and/or too weak and when it lasts too short or too long as illustrated in Fig. 1 (8).

1.3. Quantification of Mental States and Disorders

Standardized rating scales help to obtain a maximum of unbiased and quantitative evaluations of the psychopathological status and the success of therapeutic intervention (9). For instance, for mood states, the Hamilton Depression scale (HAMAD) is used for rating of depressive states and the Hamilton Anxiety Scale (HAMA) for scaling of anxiety states. The cognitive functions regarding schizophrenia can be quantified by the Positive and Negative Syndrome Scale (PANSS). Changes of the scores of rating scales over time are considered as indicators of efficacy of respective treatments. Some functions, such as “working memory” or “directing attention,”

570


can be defined by computer-based tests (e.g., Wisconsin Card Sorting Test and Stroob test). Additionally, evoked potentials can be used to test the functionality of information processing. Because of low specificity, reliability, and validity of psychopathological measurement procedures, the status of psychiatry as a clinical science of mental disorders is not satisfying. For this reason, biological measures seem to be helpful (10).

2. Biological Psychiatry of Mental Disorders

3. Molecular Psychiatry and the “Epistemic Cycle”

The German psychiatrist Wilhelm Griesinger proposed that “mental disorders are brain disorders” (11). In this way, the aim of biological psychiatry or neuropsychiatry is to understand mental disorders on a (neuro-) biological basis. Today, the subject of biological psychiatry is extensively defined—the nervous system, the endocrine system, the immune system, etc. From these systems, we have many data that are biological correlates of mental disorders. Brain-related data are mainly based on the application of methods, such as positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI) (12) and recording of electrical brain signals (EEG, EP), etc. (13). Each technique provides different information about the relationship between brain structure and function. Methods that have a spatial resolution of some cubic millimeters and that represent the spatial density of molecular structures, such as receptors, are of special importance for clinical research. This, in combination with recording techniques of electrical brain signals that represent the real-time state, steadily increases the understanding of brain processes and their pathology. For example, PET scans show activity at brain molecular sites or receptors. If this technique is combined with a highly detailed MRI image of brain structure, it is possible to identify more precisely where in the brain the activity is localized (see ref. 12). It must be mentioned here that for crucial aspects of mental disorders animal experiments are an important additional tool to develop an integrative view of the brain (14).

At present, the most important research strategy in psychiatry is related to molecular biology and biochemistry. Genomics and proteomics are considered as very promising fields in the area of biological psychiatry (15, 16). Increasingly, molecular psychiatry is facing huge amounts of data that cannot be understood without

36


571

using multidisciplinary approaches. Even upon use of sophisticated mathematical data analysis of computer-based models, appropriate reduction of data complexity seems to be quite complicated. Nevertheless, the ultimate challenge is to reconstruct the wholebrain functions on the basis of biomolecular mechanisms and to “explain” macrofunctions of the brain (e.g., hallucinations, working memory deficiencies) by molecular mechanisms (classical micro/macro problem in thermodynamics; compare 17). In a biosystemic view, the temporal structure of regional and local activation patterns of the brain is of central interest. Along these lines, the knowledge of molecular mechanisms must be related to neuronal properties, such as synaptic transmission and properties of neuronal networks. Altogether, the aim is to reconstruct the brain on the basis of its myriads of molecular parts (Fig. 2). An approach to do so can be called “systems neuropsychiatry”

Fig. 2. The “epistemic cycle” and “systems neuropsychiatry” (modified from refs. 3, 17). (a) The top-down reductionistic research paradigm of classical biological psychiatry—in search of the “master molecules.” (b) The bottom-up research strategy of theoretical neuropsychiatry: explaining macrophenomena by microphenomena—genes are induced that modulate synaptic processes. These determine the properties of neurons which then shape and modify neuronal networks, etc. The complexity problem and the need for systems thinking considering “emergence” phenomena arise.

572


as it attempts to understand the brain and related structures on both a macroanatomic and molecular levels (18; Fig. 2). In order to briefly characterize this approach, a short excursion to systems science is made.

4. “Systems Neuropsychiatry” 4.1. Systems Thinking

Systems thinking understands an object under study as being composed of elements and their relations. It aims to understand systems based on their matter, energy flows, and signaling networks. Systems thinking is mainly routed in conceptions developed by Norbert Wiener (19) and Ludwig von Bertalanffy (20). The academic development of systemic thinking sometimes is named “systems science.” Basic concepts are related to terms, like system, structure, element, relation, function (dysfunction), equilibrium, nonequilibrium, attractor, dynamics, nonlinearity, stability, fluctuation, complexity, robustness, etc. “Dynamics” and “complexity” are central issues (21–25). Basic methods are mathematics for data analysis and modeling, computer simulations for virtual experiments (in silico), and the methodology of stepwise modeling (not only intuitive “boxology” of wiring diagrams). Some theories, such as catastrophe theory, chaos theory, or complexity theory, provide new concepts that can be used to characterize the observed type of dynamics of the system under study. We think that systems biology (and ecology) will be the fields, where the most fruitful advancements in theory of biosystems are going to be developed. Systemic models that represent systems thinking are based on concepts, like feedback loops, artificial neuronal networks, etc. Modeling is important for systems thinking, as it is believed that we are only able to understand the reality by constructing maps and models (constructivistic epistemology). In this view, modeling is a procedure that starts with qualitative concepts and ends up in mathematical models that can be tested by computer experiments (in silico experiments). Additionally, these models should help to explore the real systems (e.g., neurons) in experimental setups. With new data, the models are modified again and new computer simulations can be performed. By iterative development of the models, a “viable” concept of the functional structure of the respective system is generated. Some well-known paradigms are the “small world models,” complex concepts, such as “self-organization,” or technical systems as the laser. Formal models in ecology, like predator–prey models, or models for turbulent fluids in chemistry, fluctuations and avalanches in physics, etc. are further issues of systemic thinking.

36


573

Finally, it should be mentioned here that cybernetics and systems science after booming in the 1960s and 1970s were substituted by informatics using the concept of “artificial neuronal networks” (see ref. 26, 27), and now “Computational (Neuro) Science” is the dominating field of modeling complex dynamical systems (28, 29). Similarly, “complexity science” is booming now (30). Systems thinking is only slowly finding its way into medicine (31–33), whereas a systemic view in molecular biology now is rising and recently is called “Systems Biology” (see ref. 34–40). We think that systems biology seems to be the best basis for a new molecular neuropsychiatry. This view could be called “systems neuropsychiatry” (15, 16, 41, 42). 4.2. Systems Biology

What is systems biology? Systems biology as a new approach in molecular biology/biochemistry starts up with a new perspective that is basically characterized by the application of new mathematical tools for the analysis of complex data sets as they are generated by high-throughput technologies, such as microarray technologies. Such tools are mainly sophisticated multivariate statistics and graph theory (43, 44). Additionally, formal models are developed for cognitive management of analyses of complex systems that can be conducted by computer experiments as an additional instrument for exploratory research (in silco modeling). Therefore, both mathematical modeling and consecutive computer-based simulation experiments are essential tools of systems biology. In that respect, a very useful definition of systems biology by the National Institute of Health (NIH) can be quoted (45): (Systems Biology is) … a discipline at the intersection of biology, mathematics, engineering, and the physical sciences that integrates experimental and computational approaches to study and understand biological processes in cells, tissues, and organisms. Studies at the systems level are distinguished not only by their quantitative nature in data collection and mathematical modeling, but also by their focus on interactions among individual elements such as genes, proteins, and metabolites. These studies often integrate data from multiple levels of the biological information hierarchy in an environmental and evolutionary context and pay particular attention to dynamic processes that vary in time and space. Successive iterations of experiment and theory development are characteristic of systems biology. When applied to human health, systems biology models are intended to predict physiological behavior in response to natural and artificial perturbations and thereby contribute to the understanding and treatment of human diseases.

4.3. Practice of Systems Biology in Psychiatry

Experimental molecular biology aims at a systemic view to put together several research fields: genomics, proteomics, transcriptomics, etc.—these are the main fields of present research that could have benefits from a systemic perspective. These fields have huge data sets that can be analyzed by several mathematical methods (e.g., graph theory) that allow to identify biomolecular clusters

574


Fig. 3. Molecular biology related to fields, like genomics, proteomics, and transcriptomics. Different databases and indicators can be used in an integrated way for clinical psychiatry and for exploratory modeling (from ref. 46; reproduced from ref. 46) with kind permission by Thieme Publisher).

and that might enable systemic understanding of the cell (46). The next step of a systemic view in neuropsychiatry can be seen in the development of new markers that indicate a certain mental disorder. In this context, it is aimed to develop a diagnostic procedure in psychiatry that is based mainly on biomarkers as shown in Fig. 3. 4.4. Analyzing Genome and Epigenetic Mechanisms

At present, a simple unidirectional action of the genes is not the leading idea for understanding the molecular world of the cell anymore. Instead, the epigenetic control of gene expression is of increasing interest. This top-down flow of molecular action encompasses a picture of circular causality in molecular biology of the brain. Epigenetic mechanisms encompass various secondary modifications of DNA, such as methylation, acetylation, and poly-ADPribosylation, which are catalyzed by respective enzymes (47, 48). Furthermore, similar modifications occur on DNA-associated histones. Histone acetylation appears to be a major mechanism for transcriptional activation. Transcription factors activated by, for example, hormones attract histone acetyltransferase (HAT) which adds an acetyl group to the amino group of lysine residues in core histones, blocking the positive charge and relieving DNA condensation. Inactivation of an entire chromosome is linked to substantial decreases in the acetylation state of core histones. Activities of the enzymes attaching or removing those residues are highly dependent on environmental impact. These modifications do not change the DNA sequences of respective genes, but can highly influence their activation. Due to their influence on gene transcription, metabolic-level consequences on the protein expression are to be

36


575

expected. As generally accepted, health and disease depend on both the genetic predisposition and the environment the individual is exposed to. Environment-induced modifications of gene expression are highly relevant in research of brain disorders. Patterns of these modifications can be studied on the whole genome or on specific, selected genes of interest. Here, we want to describe a comprehensive experimental approach to analyze DNA and histone methylation patterns. 4.5. DNA Methylation Patterns Applying Methylation-Specific PCR

1. Bisulfite Treatment The first step in methylation-specific PCR (MSP) involves the chemical conversion of all unmethylated cytosines to uracil. Methylated cytosines remain unaltered in the process. In subsequent PCRs, unmethylated cytosines/uracils are replaced by thymine. Therefore, the sequence of the DNA after bisulfite treatment is different depending on the original methylation state of the DNA. The base exchange is revealed by use of methylation-specific oligonucleotide primers for the genes of interest. Control methylated DNA is created by treating genomic DNA with SssI methyltransferase in the presence of a methyl donor S-adenosyl-methionine. Multiplex PCRs are performed according to Dahl and Guldberg (49). 2. PCR with Methylation-Specific Primer Sets In this reaction, it is determined which sequence is present after bisulfite treatment. For this purpose, primers to the unmethylated and methylated sequences are designed in such a way that mismatches are created depending on which sequence is present to prevent mispriming between the primer sets and the undesired target DNA. A typical experiment involves performing two PCR reactions using the same bisulfite-treated template DNA. One reaction uses primers designed to anneal to the sequence present if the DNA is unmethylated. The other reaction includes primers designed to anneal to the sequence if the DNA is methylated. All experiments can be done in a multiplex format (49). 3. Gel Analysis The PCR products are run on an agarose gel stained to visualize the DNA. If the sample DNA was originally unmethylated prior to modification, only the primer set made for the unmethylated stretch of DNA produces an amplification product. Conversely, a product will be produced only with the primer set made for the methylated stretch of DNA if the DNA was originally methylated. 4. Chromatin Immunprecipitation Chromatin immunprecipitation (ChIP) can be performed on selected brain regions that are excised, lysed in an appropriate buffer, and DNA is sheared by ultrasonication. The cleared

576


lysates with fragmented DNA (approx 500–800 bp) are then incubated either with antibodies specific for DNA-associated proteins, e.g., for transcription factors or for histones (H1, H3, H4 acetylated each). Protein G-precipitated material is then digested with proteinase K and RNAse H. Then, DNA is extracted with phenol/chloroform/isoamyl-alcohol and the extract precipitated with ethanol. This DNA can be used for gene-specific analyses of genes of interest, using qPCR, or for ChIP-chip analyses. In this case, precipitated DNA is blunted and amplified by ligation-mediated PCR (LM-PCR). This DNA is then probed on a custom DNA microarray (e.g., from Nimblegen®) containing more than 1,500 annotated promoters. 5. Data Analysis One of the crucial determinants of molecular biology is that several thousands of data are generated by effective highthroughput methods, such as microarrays, but there is no sufficient formal analytical method that seems appropriate to detect the hidden relational structure of the data. For instance, tools of multivariate statistics that identify clusters of activated genes can detect coincidence of activated genes. The strength of coactivation or suppression can be expressed by graph theoretical tools that enable representing the multiple interrelations by graphical trees (see Figs. 4 and 5).

Fig. 4. Part of a microarray scanned at two wavelengths depicting differential intensity patterns of green (control) and red (disease) spots. Each spot represents one gene. Hybridization times (or periods) required for one experiment are independent from the number of spots due to highly parallel reactions of targets with probes. Therefore, several ten- or even hundred thousands of genes can be interrogated simultaneously within approx. 24 h (reproduced from ref. 16 with kind permission by Thieme Publisher).

36


577

Fig. 5. Graph theoretically based tree representing protein–protein interactions (35, p. 317 reproduced from ref. 35 with kind permission by Wiley Publisher).

5. Methods of Systems Biology Modeling

The next step after identifying interactions between units of interest is to determine the direction of flow of action and its strength, duration, and other quantitative properties. This leads to the field of modeling (50, 51). Modeling of the internal structure of systems starts with verbal hypotheses that can be represented by a wiring diagram as they can be seen in publications in neurobiology and that is demonstrated later. These wiring diagrams represent results of empirical research and can be classified as graphic representations of “qualitative models.” They are extracts of otherwise verbally expressed knowledge on the subject. In this process, appropriate visualization of the results of data analysis and modeling and simulation of complex systems can greatly aid in fostering interdisciplinary communication in theoretical biology (23, 52). This can be facilitated in part by specialized software packages that use graphical user interfaces (see below). Those graphics can be used as a basis for “quantitative modeling” by mathematical formalization. Usually, mathematical models of dynamic molecular systems are based on differential equations (53, 54). At this step, the kinetics and the strengths of the actions and interactions have to be determined and a heuristically fruitful mathematical model has to be constructed (54). Then, a computerized model can be generated with subsequent simulations that demonstrate the temporal course of action of the various components of the system (55). Subsequently,

578


Fig. 6. Steps of systemic modeling: Critical steps are the formalization and computerization of the model (modified from ref. 56).

questions arising from those simulations have to be answered by new experiments in the laboratory (see Figs. 1 and 5). These iterative steps of systemic modeling are core features of modeling as a heuristic exploratory function—if appropriate data are not available, exploratory modeling can help to clarify the experimental focus to obtain relevant information of the system under study (see Fig. 6). Thus, it must be emphasized here that the unresolved epistemic challenge to understand complex dynamic systems at present only allows constructing of “exploratory” and not “explanatory” models (5, 56, 57). 1. Simulation Software for Systems Biology Mathematical modeling in biological sciences and in interdisciplinary context might have advantages if the modeling procedure is based on visual symbols (icons) that represent mathematical operators or equations. This enables interdisciplinary discussion of the model structure also without formal mathematical argumentation. In line with this, special software allows to construct systemic models intuitively by using icons (Stella®, Vensim®, Cell designer®, PathwayLab®, etc.). Other programs additionally offer templates that allow entering

36


579

Table 2 Common software packages used in systems biology (modified from ref. 60) Software

Description

Comments

Mathematica®

Powerful computer algebra system

Widely used, several special software packages, e.g., for neural networks

Matlab®/Simulink® Powerful computer algebra system

Widely used, also icon-based modeling possible

Stella®

Graphic interface

Based on system dynamics method

Vensim®

Graphic interface

Freeware, based on system dynamics method

E-cell®

Simulates cellular processes, deterministic and stochastic modeling, different timescales

Based on three object classes as substances, reactor, and system; open source: http://www.dev.e-cell.org

V-Cell

Modeling and Simulation Framework

The Virtual Cell requires Java, provided by National Institute of Health; download: http://www.nrcam.uchc. edu/

M-Cell

Monte Carlo Simulator of Cellular Microphysiology

Information: http://www.mcell.cnl.salk. edu

CellDesigner®

Graphic interface with many icons for proteins, receptors, channels, etc.

Download: http://www.systems-biology.org

SimCell®

Cellular automata-based simulation

Download: http://www.Wishart. biology.ualberta.ca

Gepasi®

Modeling biochemical reactions, input via notation similar to chemical reactions

Metabolic control analysis, linear stability analysis can be done; free software: http://www. Gepasi.org

PathwayLab®

Complex software; based on Mathematica

Graphic input and biochemical equations; commercial software

Neuron®

Specialized software for neurons, modeling ion channels, and electrical activity

Widely used in computational neuroscience; no special adaptation to systems biology; http://www.neuron.duke. edu

biochemical equations in the model (58; see Table 2). For instance, the concept of an integral and differential equation in some programs (e.g., Stella®, Vensim®) is represented by the metaphor of a bath tube: the current level of water is the result of inflows minus outflows plus the initial level (integral equation) or by the present rate of change that is equal to present inflow minus outflow (difference or differential equation). Such didactic concepts are essential for applications of computational sciences in biological disciplines. In introductory textbooks (comp. 51), but also in scientific context, some authors systematically use graphic icons to describe the formal relations between variables.

580


In line with this, the “optimal” software package should allow to develop graphical pathways very easily. These diagrams should correspond to conventional biochemical formulas and drawings. Additionally, these diagrams should be transformed automatically to mathematical equations. The solutions of the equations should be presented by visualizations of the time course of the intensity of the variables and/or derived measures (phase diagrams). Changes of the model should be possible on the level of the equations as well as on the level of the diagram. Databases should be importable. 2. Software Selection for Systems Biology Currently, all these goals cannot be reached by any one program. Therefore, systems biologists still have to make selections from several software packages in order to find the best solution for their specific analytical problems (59) as shown in Table 2. For students and beginners in computer-assisted modeling, the programs Matlab® and—even more easy to be learned—Stella® might be helpful to explore the behavior of complex dynamic systems. One advanced tool is PathwayLab®. It is related to the powerful computer algebra system Mathematica® that has links to Java. On the single-cell level, some advanced programs, such as V-Cell®, E-Cell®, CellDesigner®, or M-Cell®, are being used. A higher level of complexity in a given biological system may be modeled by SimCell®, a cellular automata-based simulation system that allows dynamic and stochastic modeling of almost any cellular processes, including real-time monitoring and animation of the (molecular) system. For an exchange of models, the community of systems biologists has introduced the Systems Biology Workbench (SBW). It is based on a common language to achieve that goal. Specifically, models can be written in Systems Biology Markup Language (SBML) with several modules that allow describing the basic components and processes that are depicted in the model. It provides a common platform that can be used freely for academic purposes. The European Molecular Biological Laboratory (EBML) and others provide comprehensive databases for molecular systems biology modeling.

6. Systemic Concepts in Neuropsychiatry: Applications 6.1. Schizophrenia Model

The key question of a theory of brain activity is related to the task to describe temporal structures of spatial patterns of activation and to understand the interplay of microstructures and macrostructures. Systemic thinking in neuropsychiatry means the structural and functional identification of feedback and feed-forward loops in

36


581

Fig. 7. Hypothetical global circuitry for positive symptoms (reproduced from ref. 63 with kind permission by Thieme Publisher).

the brain and their embedment in complex neural networks (compare 61). Some progress is made in schizophrenia research. 1. A Qualitative Model of Global Circuits and Positive Symptoms Regarding the task to analyze a complex dynamic network by selection of significant subsystems, the global circuitry that is hypothetically involved in positive symptoms of schizophrenia (hallucinations, delusions) was identified by Arvid Carlsson (62, 63). For instance, acoustic hallucinations as overactivation of auditory cortex can occur if the filtering function of the thalamus is reduced by disinhibition. This disinhibition can be induced by a hyperactivation of the dopaminergic system that originates in the substantia nigra (SN) and/or in the ventral tegmental area (VTA) brain regions and is coupled with striatal structures by inhibitory acting dopamine D2 receptors (see Fig. 7). First attempts of a systemic explication of this model show the utility of this concept, although important data still are missing to validate the model (64). As a next step in modeling, we have to conduct exploratory computer simulations of this model. Similar models are already published (65). Additionally, new global models should represent the current discussion of the neural circuitry involved in schizophrenic symptoms that includes several other structures and transmitter systems (66). 2. Computational Modeling of Working Memory Working memory is impaired in schizophrenia. This is in line with investigations and experiments in human subjects that showed that too much dopamine in prefrontal cortex (as

582


Fig. 8. Inverted u-function of working memory function depending on the level of dopamine (reproduced from ref. 8 with kind permission by Thieme Publisher).

it occurs after cocaine or amphetamine application) induces attention deficits, whereas low dopamine (as it is observed in Morbus Parkinson) diminishes the retention or intermediate storage of information (67, 68). These observations can be summarized by an inverted u-relation between dopamine transmission and memory function (see Fig. 8). Computational modeling of working memory functions of prefrontal cortical neural networks is already quite sophisticated. Models with quite simple structures can exhibit naturalistic behavior (compare Fig. 9). By variation of coupling parameters, functional memory deficits can also be modeled. These network models are composed of several hundred modules that reflect the relevance of inhibitory couplings. Some models use only one class of inhibitory neurons (69); others integrate three types of these neurons (70–74) as shown in Fig. 9. These models can reflect the properties of activation and inhibition of the networks by simulating a spatial activation profile. Regarding schizophrenia, the ratio of dopamine D1 receptors to D2 receptors seems to determine the filtering properties of the networks: D1 dominance sharpens the profile, whereas D2 dominance bears a risk of distraction of attention and therefore results in a weak working memory function (see Fig. 10). 6.2. Modeling of Synaptic Transmission

Modeling of neural networks by artificial neural network models must be made more precise by integration of models of the synapse (75). This is important because the patterns of connectivity codetermine the dynamic properties of this network. However, this aim is very ambitious as any synapse is a complex network of feed-forward

36


583

Fig. 9. Structure of different modules of artificial cortical network models (reproduced from ref. 8 with kind permission by Thieme Publisher). (a) Modules with one type of inhibitory neurons used by Durstewitz et al. (69). (b) Module with three types of inhibitory neurons used by Wang et al. (71). P pyramidal cell, IN inhibitory neuron, DTC dendritetargeting cell, ITC interneuron-targeting cell, STC soma-targeting cell.

Fig. 10. Display of states of artificial networks with two optional conditions in prefrontal cortex in terms of processing of memory-related information (after 66, 69, 74, 78; from (8, generated with Mathematica®; reproduced with kind permission by Thieme Publisher). (a) Focused activation of nodes of network being correlated with strong working memory function. This means that D1 receptors prevail in the network, showing a single, strong, and sustained center of activity. (b) Multifocal activation of the network is caused by functional dominance of D2 receptors. However, they show multiple, weaker, and short-lived centers of activation. This multifocal activation of the network is incompatible with strong working memory performance.

and feedback loops. This is important as conceiving the synapse as a system of interactive, molecular networks is relevant for understanding actions of psychopharmaceutical drugs. This view could markedly influence the development of new (and better) drugs (76, 77). Several steps of transformation of electrical signals to chemical signals and back to electrical signals have to be represented in the models. Synthesis, transport, storage, release, receptor coupling,

584


Fig. 11. Wiring diagram of processes related to dopamine-based neurotransmission (from ref. 80; reproduced with kind permission by Thieme Publisher). Legend: Bold arrows indicate flow of molecules, thin arrows denote elevation/activation of the targeted component, and bars indicate reduction/inhibition. D1R receptor of dopamine D1 family, D2R receptor of dopamine D2 family.

reuptake, degradation, postsynaptic molecular processes, and their feedback are processes that characterize synaptic signal transmission. Only very first steps of integrating knowledge of single mechanisms by computational modeling can be seen (78, 79) (see Fig. 11). Although quite a lot of mechanisms are known, we are far away from understanding the dynamics of synapses completely. It should be mentioned here that some attempts have been made to establish a “Molecular Systems Biology of the Synapse” (76, 77, 80).

36

6.3. The Neuron as a Molecular Network


585

Today, psychiatry is already aiming to relate mental disorders to neurons. For instance, for schizophrenia, a deficiency of inhibitory neurons is discussed (81). In that respect, the molecular biology of the neuron is one of the most developing fields of research. 1. Input sites—Receptors and Intracellular Signaling Networks One crucial molecular structure of the neurons are receptors, some of them are even located extrasynaptically. Activation of receptors evokes several fast and/or slow conducting pathways that are diverging and converging and that induce changes of cellular activity. Several feedback loops back to the membrane level control the membrane potential (see Fig. 12). It is known that receptors that have a specific affinity for a specific transmitter, such as dopamine, interfere with many different signaling pathways: dopamine D1 receptors can stimulate PKA via cAMP and exert cross talks to other pathways. Dopamine D2 receptors are inhibiting cAMP, PKA, etc. In consequence, dopamine in the synaptic cleft can activate and inhibit cAMP depending on the temporal pattern of occupation of the respective receptors. Regarding these findings, it becomes clear that only computer simulations help us to understand the complexity of intracellular signaling mechanisms.

6.4. Modeling Signal Transduction Networks Relevant in Schizophrenia

The relevance of the dopamine system to understand the pathology of schizophrenia is also emphasized by the specific analysis of dopamine-induced activation of D1 and D2 receptors and the resultant intracellular signal transduction. At the first level of

Fig. 12. Intracellular loops of signal transduction pathways that connect molecular signaling and electrical properties of the cell (80; reproduced from ref. 80 with kind permission by Thieme Publisher).

586


Fig. 13. Simplified scheme of molecular network of signal transduction cascades of D1 and D2 receptor signaling, with various steps of processing converging on DARPP-32 (from 83, 84, modified from ref. 80; reproduced with kind permission by Thieme Publisher). Comment: PP2A acts as an (indirect) activator of PKA by double-serial inhibition. Legend: Abbreviations (top down): Ca2+ calcium ion, cAMP cyclic adenosine monophosphate, CaM Calmoduline, PKA protein kinase A, PDE1 phosphodiesterase 1, PP2B protein phosphatase 2B, PP2A protein phosphatase 2A, DARPP dopamine-and cyclic adenosine monophosphate (cAMP)-regulated phosphoprotein, PP1 protein phosphatase 1.

transduction (adenylyl cyclase), both receptor types have antagonistic effects, but after about four steps on the stage of PKA they exert synergistic effects. Moreover, effects on DARPP-32 as an integrator of different signaling cascades are evident (Fig. 13). However, the graphic representation of the different diverging and converging pathways and feedback loops alone cannot describe the in vivo behavior of this molecular network because the different kinetics and feedback loops influence the behavior in a way that may only be explored by computer-based modeling and simulation (82). Some years ago, Lindskog et al. (83, 84) constructed a computational model that includes effects of NMDA receptor activation. In their in silico experiments, they could reproduce the above-described antagonistic and synergistic effects of dopamine

36


587

Fig. 14. “In silico” test of the model of signal transduction. Different inputs can result in similar outputs (from 83, reproduced modified from ref. 60 with kind permission from Thieme Publisher). (I) Strong transformation of fast (pulsatile) dopamine signal (solid line, (a)) over triangular signal of cAMP (b) to saw tooth-like signal of protein kinase A (c). (II) Low transformation of slow (triangular) dopamine signal (stippled line, (a)) with similar curve at the stage of cAMP (b) and strong amplification of PKA (c).

receptor activation on the various levels of signal transduction. For instance, their computer experiments showed that a strong and fast pulsatile dopamine signal is transformed to a triangular signal systematically at the level of cAMP and PKA (see Fig. 14, bold lines; comp. 84). By contrast, a slow and weak signal can be enhanced stepwise and result in similar output (Fig. 14, stippled lines). This example shows how mathematical modeling in systems biology can advance our understanding of molecular events in the neuron. However, there are still additional immediate effects brought about, e.g., by various phosphorylation events occurring within ion channels via kinases. This aspect would lead to an understanding of dynamic changes in membrane potential, which, in turn, influence actions of various receptors. Apart from that, thinking in multidimensional molecular networks should also include long-term effects of PKA-induced transcriptional and translational changes. This example of a systems biology approach of the neuron is believed to greatly improve our understanding of the dynamic action of agonists and antagonists as well as of the origin of mental disorders.

7. Heuristic Models: “The Neurochemical Mobile”

Aiming a systems biology of the brain it seems to be useful to discuss several observations in a metaphorical conceptual framework of a “neurochemical mobile.” This represents the concept of a dynamic balance of neurotransmitter actions. In this framework, mental disorders can be described by a sustained dysbalance of activity of the transmitter systems with focal dysfunctions. The basic constellation is that the norepinephrinergic system and the cholinergic system oppose each other in their effects to a common target (e.g., heart). On the side of the norepinephrinergic system, serotonin and dopamine are acting as opponents of norepinephrine.

588


Fig. 15. The heuristic scheme of a “neurochemical mobile.” Opposing neurochemical transmission systems with activating (+) and inhibitory (−) effects on cellular activities (reproduced from ref. 80 with kind permission by Thieme Publisher). Legend: NA norepinephrine, noradrenalinme, Ach acetylcholine, 5HT serotonin, DA dopamine, Glu glutamate, GABA gamma-amino-butyric acid; activating receptors(R); a1 alpha1 nordepinephrinergic receptors, 5HT2 R type 2A serotonerigic receptors, nACh R nicotinergic acetylchloline receptors, AMPA R alpha-Amino-3-Hydroxy-5-Methyl-4-IsoxazolPropionacid receptor, GABAB R presynaptic GABA receptors, inhibition of GABA release, D1 R dopamine D1 receptors; inhibiting receptors (R); a2 alpha2 nordepinephrinergic receptors, 5HT1 R type 1A serotonerigic receptors, mACh R muscarinergic acetylchloline receptors, D2 R dopamine D2 receptors, GABAA R GABA A receptors, mGlu1,2 metabotropic glutamate receptors.

They also oppose each other with respect to their effects on local neuronal networks. On the side of acetylcholine, glutamate and GABA act as opponents of acetylcholine and that also have opposing effects to each other (Fig. 15). Taking into account that the receptor subtypes determine the final function of the respective transmission system, a complex picture of the global transmission arises (see Fig. 15). The heuristic value of this simple model is that most of the singular hypotheses of the neurochemical basis of mental disorders can be integrated. For instance, focusing on the neurochemistry of schizophrenia, several hypotheses can be related to each other. A dopamine hyperfunction (62) also—at least partially—can be related to a serotonin hyperfunction (85). In this case, the scale pans on the left side of the scale, representing dopamine, are larger and therefore they also pull down the scale pans that represent serotonin. As a consequence, the right part of the scale is elevated. This is in line with an elevation of the scale pans of glutamate and GABA that indicates a glutamate hypofunction (86, 87) and a GABA hypofunction (81) that is postulated for schizophrenia. Within the concept of “circular causality,” the causation can also be focused on the right side of the scale, starting with the glutamate hypothesis (88).

36


589

The mobile also allows representing treatment options: antipsychotic action can be expected by antagonists of dopamine and/or serotonin transmission, and by agonists of glutamate and/ or GABA as effective antipsychotic substances that block D2 receptors and 5HT2 receptors. In addition, benzodiazepines can be useful in treatment of an acute schizophrenic episode by enhancing the GABAergic system. Additionally, the framework of the mobile allows us to understand depression as a hypofunction of the norepinephrine and serotonin system or as a hyperfunction of the acetylcholine system.

8. Conclusion At the level of the molecular psychiatry of the synapse, the classic electrophysiologically dominated “Computational Neuroscience” can be combined with Systems Biology. Collecting biochemical data alone does not succeed in a deeper understanding of the biological mechanisms that determine mental disorders. A programmatic and systematic approach that aims for an integral theoretical understanding of differential organizational levels of the brain seems to be fruitful. This is in line with the application of more sophisticated mathematical tools to detect complex latent relations between molecular networks. Systemic studies should focus on the dynamics of chemical and electrical signaling networks. Finally, the Systems Biology of the synapse is a crucial step in this direction, especially in the fields of neuroscience and psychiatry. In summary, by using systems biology approaches, it will be possible to greatly improve our understanding of spatiotemporal interactions in the nervous (and other) systems on various levels. In addition, it enables us to develop new types of psychiatric medications that are specifically tailored to the network dynamics and that influence the different modules in nerve cells in a more efficient manner. For this reason, theoretical psychiatry could benefit from exchange with systems biology. However, major achievements can only be made, if researchers from different disciplines, like psychiatrists, neurobiologists, chemists, and computational scientists, collaborate toward this purpose. References 1. Sadock, B. J., Sadock, V. A. (ed.) (2005) Kaplan`s and Sadock’s Synopsis of Psychiatry. Wolters Kluwer, New York. 2. Puls, I., and Gallinat, J. (2008) The concept of endophenotypes in psychiatric diseases meeting the expectations?, Pharmacopsychiatry 41 Suppl 1, S37–43.

3. Tretter, F. Gebicke-Haerter, P. (2010) Neuropsychiatry – Subject, Concepts, Methods and Computational Model, in Systems Biology in Psychiatric Research (Tretter, F., Gebicke-Haerter, P.J., Mendoza, E.R., Winterer, G. eds), pp. 27–80, Wiley-Blackwell, Weinheim.

590


4. Jaspers, K. (ed.) (1913, 1997) General Psychopathology - Volumes 1 & 2. Johns Hopkins University Press. Baltimore and London. 5. Tretter, F. (ed.) (2010) Philosophical Aspects of Neuropsychiatry, in Systems Biology in Psychiatric Research (Tretter, F., GebickeHaerter, P.J., Mendoza, E.R., Winterer, G. eds), pp. 3–26, Wiley-Blackwell, Weinheim. 6. Taylor MA, Vaidya NA (ed.) (2009) Descriptive Psychopathology. Cambridge University Press, Cambridge Mass. 7. Bennett, M. R. & Hacker, P. M. S. (eds,) (2003) Philosophical Foundations of Neuroscience. Malden (Mass.): Blackwell Publishing. 8. Tretter F., Albus M. (2007) “Computational Neuropsychiatry” of Working Memory Disorders in Schizophrenia: The Network Connectivity in Prefrontal Cortex - Data and Models. Pharmacopsychiatry 40, S2–S16. 9. Burt, T., Sederer, L., Isgack, WW (eds.) (2002) Outcome Management in Psychiatry: A Critical Review. Washington, DC: American Psychiatry Press. 10. Andreasen, N. (ed.) (2004) Brave New BrainConquering Mental Illness in the Era of the Genome. Oxford Univ. Press, New York. 11. Griesinger W (ed.) (1882) Mental Pathology and Therapeutics. William Wood & Co., New York. 12. Vernalaken, I., Gruender, G., Cumming, P. (2010) Progress in Psychopharmacology through Molecular Imaging, in Systems Biology in Psychiatric Research: (Tretter, F., GebickeHaerter, P.J., Mendoza, E.R., Winterer, G. eds), pp.189-206Wiley-Blackwell, Weinheim. 13. Michel, Ch. M., Koenig, T., Brandeis, D., Gianotti, L. R. R., Wackermann, J. (eds) (2009) Electrical Neuroimaging. Cambridge University Press, New York. 14. Koch M. (ed.) (2006) Animal Models of Neuropsychiatric Diseases. Imperial College Press, London. 15. Gallinat J, Obermayer, K, Heinz A (2007) Systems Neurobiology of the Dysfunctional Brain. Pharmacopsychiatry Suppl. 1:S40–S44. 16. Gebicke-Haerter, P. J. (2008) Systems biology in molecular psychiatry, Pharmacopsychiatry 41 Suppl 1, S19–27. 17. Tretter, F., and Gebicke-Haerter, P. J. (2009) Philosophy of neuroscience and options of systems science, Pharmacopsychiatry 42 Suppl 1, S2–S10. 18. Meyer-Lindenberg, A., and Weinberger, D. R. (2006) Intermed.iate phenotypes and genetic mechanisms of psychiatric disorders, Nat Rev Neurosci 7, 818–827.

19. Wiener, N. (ed.) (1948) Cybernetics. MIT press, Cambridge, Mass. 20. Bertalanffy, L.V. (ed.) (1968) General System Theory. Braziller, New York. 21. Watts, D. J., and Strogatz, S. H. (1998) Collective dynamics of ‘small-world’ networks, Nature 393, 440–442. 22. Strogatz, S.H. (ed.) (2001) Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry and Engineering g (Studies in Nonlinearity). The Perseus Books Group, New York. 23. Periwal V, Szallasi Z, Stelling J. (2006) System modelling in Cellular Biology, in System Modeling in Cellular Biology (Szallasi, Z., Stelling, J. & Periwal, V., ed.), pp. 7–14, The MIT Press, Cambridge, Mass. 24. Quarteroni, A., Formaggia, L., Veneziani, A. (eds) (2006) Complex Systems in Biomed. icine. Springer, Berlin. 25. Stelling, J, Sauer, U. J. Doyle, F J Doyle, J.(2006) Complexity and Robustness of cellular Systems, in System Modeling in Cellular Biology (Szallasi, Z., Stelling, J. & Periwal, V., ed.), pp. 3–18, The MIT Press, Cambridge, Mass. 26. Arbib M A, Grethe JS. (eds) (2001) Computing the Brain: A Guide to Neuroinformatics. Academic Press, San Diego. 27. Arbib MA (ed.) (2002) The Handbook of Brain Theory and Neural Networks. MIT Press: Cambridge, Mass. 28. Dayan, P. Abbott L. (ed.) (2005) Theoretical Neuroscience. Computational and Mathematical Modeling of Neural Systems. MIT Press, Cambridge, Mass. 29. Freeman, W. J. (ed.) (2000). Neurodynamics: An Exploration in Mesoscopic Brain Dynamics. Springer, Berlin. 30. Boccara N (2004) Modeling Complex Systems. Springer, Berlin. 31. Tretter, F. (1989): System-wissenschaft in der Med.izin. Deutsches Ärzteblatt 43, 3198–3209. 32. Ahn, A. C., Tewari, M., Poon, C. S., and Phillips, R. S. (2006) The limits of reductionism in medicine: could systems biology offer an alternative?, PLoS Med. 3, e208. 33. Ahn, A. C., Tewari, M., Poon, C. S., and Phillips, R. S. (2006) The clinical applications of a systems approach, PLoS Med. 3, e209. 34. Kitano, H. (2002) Systems biology: a brief overview, Science 295, 1662–1664. 35. Kitano, H. (2002) Computational systems biology, Nature 420, 206–210. 36. Klipp E, Herwig R, Kowald A, Wielring C, Lehrach H (eds) (2005) Systems Biology in

36

37.

38.

39.

40. 41.

42.

43.

44.

45.

46.

47.

48.

Practice: Concepts, Implementation and Application. Wiley-VCH, Weinheim. Klipp E, Liebermeister, W., Herwig R, Wierling C, Kowald, A, Lehrach H, Herwig R (ed.) (2009) Systems Biology: A textbook. Wiley-VCH, Weinheim. Helms, V. (ed.) (2008): Principles of Computational Cell Biology: From Protein Complexes to Cellular Networks. Wiley-VCH, Weinheim. Noble, D. (2006) Multilevel Modelling in Systems Biology: From Cells to Whole Organs. The Role of Modeling in Systems Biology, in System Modeling in Cellular Biology (Szallasi, Z., Stelling, J. & Periwal, V., ed.), pp. 297–312, The MIT Press, Cambridge, Mass. Noble, D. (2008) Music of Life: Biology beyond Genes. Oxford Univ. Press, New York. Tretter, F., Gallinat, J., Muller, W. E. (2008) Systems biology and psychiatry: the functional architecture of molecular networks in mental disorders- data and models, Pharmacopsychiatry 41 Suppl 1, S1. Tretter, F., Gebicke-Haerter, P. J., Albus, M., an der Heiden, U., and Schwegler, H. (2009) Systems biology and addiction, Pharmacopsychiatry 42 Suppl 1, S11–31. Matthaeus F., Smith, A., Gebicke-Haerter, P. (2010): Some Useful Mathematical Tools to Transform Microarray Data into Interactive Molecular Networks, in Systems Biology in Psychiatric Research (Tretter, F., GebickeHaerter, P.J., Mendoza, E.R., Winterer, G. (eds) pp. 277–300, Wiley-Blackwell, Weinheim. Smith, J., Huett, M-T. (2010) Network Dynamics as an Interface between Modeling and Experiment in Systems Biology, in Systems Biology in Psychiatric Research (Tretter, F., Gebicke-Haerter, P.J., Mendoza, E.R., Winterer, G. (eds) pp 243–270, WileyBlackwell, Weinheim. NIH, National Institute of Health (2007) Systems Biology http://www.nigms.nih.gov/ Initiatives/SysBio/. Reckow, S., Gormanns, P., Holsboer, F., and Turck, C. W. (2008) Psychiatric disorders biomarker identification: from proteomics to systems biology, Pharmacopsychiatry 41 Suppl 1, S70–77. Sananbenesi, F., and Fischer, A. (2009) The epigenetic bottleneck of neurodegenerative and psychiatric diseases, Biol Chem 390, 1145–1153. Zhubi, A., Veldic, M., Puri, N. V., Kadriu, B., Caruncho, H., Loza, I., Sershen, H., Lajtha, A., Smith, R. C., Guidotti, A., Davis, J. M., and

49.

50.

51.

52.

53.

54.

55.

56.

57.

58.

59. 60.

61.


591

Costa, E. (2009) An upregulation of DNAmethyltransferase 1 and 3a expressed. in telencephalic GABAergic neurons of schizophrenia patients is also detected. in peripheral blood lymphocytes, Schizophr Res 111, 115–122. Dahl, C., and Guldberg, P. (2007) A ligation assay for multiplex analysis of CpG methylation using bisulfite-treated. DNA, Nucleic Acids Res 35, e144. Shiflet, AB, Shiflet GW (2006) Introduction to Computational Science. Princeton University Press, Princeton. Fishwick P. A. (ed.) (2007) Handbook of Dynamic System Modeling. Chapman & Hall, New York. Szallasi Z, Stelling J, Periwal V (2006) (ed.) System Modeling in Cellular Biology. MIT Press, Cambridge, Mass. Conrad E.D., Tyson J. J. (2006) Modeling Molecular Interaction Networks with Nonlinear Ordinary Differential Equations., in System Modeling in Cellular Biology. (Szallasi Z, S. J., Periwal V, ed.), pp. 97–124, MIT Press, Cambridge, Mass. Paulsson, J., Elf, J. (2006) Modeling Molecular of Intracellular Kinetics, in System Modelling in Cellular Biology (Szallasi Z, P. V., Stelling ed.), pp. 149–176 Cambridge Ma. Kell, D. B., Knowles, J.D. (2006) The Role of Modeling in Systems Biology in System Modeling in Cellular Biology (Szallasi, Z., Stelling, J. & Periwal, V., ed.), pp. 3–18, The MIT Press, Cambridge, Mass. Tretter, F., and Scherer, J. (2006) Schizophrenia, neurobiology and the methodology of systemic modeling, Pharmacopsychiatry 39 Suppl 1, S26–35. Voit, E. O., Qi, Z., and Miller, G. W. (2008) Steps of modeling complex biological systems, Pharmacopsychiatry 41 Suppl 1, S78–84. Finney A., Hucka M., Borstewin J., Keating SM., Shapiro BE., Matthews J Kovitz Bl., Schilstra MJ., Funahashi A., Doyle J., Kitano H. (2006) Software Infrastructure for Effective Communication and reuse of Computational Models, in System Modeling in Cellular Biology (Szallasi, Z., Stelling, J. & Periwal, V., ed.), pp. 297–312, The MIT Press, Cambridge, Mass. Kitano H. (ed.) (2001) Foundations of Systems Biology. MIT Press, Cambridge, Mass. Tretter, F., and Albus, M. (2008) Systems biology and psychiatry - modeling molecular and cellular networks of mental disorders, Pharmacopsychiatry 41, Suppl 1, S2–S18. ed.elman G M, T. G., (ed.) (2000) A Universe Of Consciousness How Matter Becomes Imagination, Basic Books, New York.

592


62. ed.elman G M, T. G. (2000) A Universe Of Consciousness How Matter Becomes Imagination,, Basic Books, New York. 63. Carlsson, A. (1988) The current status of the dopamine hypothesis of schizophrenia, Neuropsychopharmacology 1, 179–186. 64. Carlsson, A. (2006) The neurochemical circuitry of schizophrenia, Pharmacopsychiatry 39 Suppl 1, S10–14. 65. Tretter F, Müller W, Carlsson A (2006). Systems Science, Computational Science and Neurobiology of Schizophrenia. Pharmacopsychiatry 39, 1–2. 66. Berns, G. S., and Sejnowski, T. J. (1998) A computational model of how the basal ganglia produce sequences, J Cogn Neurosci 10, 108–121. 67. Winterer, G. (2006) Cortical microcircuits in schizophrenia--the dopamine hypothesis revisited., Pharmacopsychiatry 39 Suppl 1, S68–71. 68. Goldman-Rakic, P. S. (1999) The physiological approach: functional architecture of working memory and disordered. cognition in schizophrenia, Biol Psychiatry 46, 650–661. 69. Goldman-Rakic, P. S., Muly, E. C., 3rd, and Williams, G. V. (2000) D(1) receptors in prefrontal cells and circuits, Brain Res Brain Res Rev 31, 295–301. 70. Durstewitz, D., Seamans, J. K., and Sejnowski, T. J. (2000) Neurocomputational models of working memory, Nat Neurosci 3 Suppl, 1184–1191. 71. Brunel, N., and Wang, X. J. (2001) Effects of neuromodulation in a cortical network model of object working memory dominated. by recurrent inhibition, J Comput Neurosci 11, 63–85. 72. Wang, X. J., Tegner, J., Constantinidis, C., and Goldman-Rakic, P. S. (2004) Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory, Proc Natl Acad Sci U S A 101, 1368–1373. 73. Wang, X. J. (2006) Toward a prefrontal microcircuit model for cognitive deficits in schizophrenia, Pharmacopsychiatry 39 Suppl 1, S80–87. 74. Seamans, J. K., Durstewitz, D., Christie, B. R., Stevens, C. F., and Sejnowski, T. J. (2001) Dopamine D1/D5 receptor modulation of excitatory synaptic inputs to layer V prefrontal cortex neurons, Proc Natl Acad Sci U S A 98, 301–306. 75. Winterer, G., and Weinberger, D. R. (2004) Genes, dopamine and cortical signal-to-noise

76. 77.

78.

79.

80.

81.

82.

83.

84.

85.

86.

87.

88.

ratio in schizophrenia, Trends Neurosci 27, 683–690. Abbott, L. F., and Regehr, W. G. (2004) Synaptic computation, Nature 431, 796–803. Grant, S. G. (2003) Systems biology in neuroscience: bridging genes to cognition, Curr Opin Neurobiol 13, 577–582. Pocklington, A. J., Cumiskey, M., Armstrong, J. D., and Grant, S. G. (2006) The proteomes of neurotransmitter receptor complexes form modular networks with distributed. functionality underlying plasticity and behaviour, Mol Syst Biol 2, 2006 0023. Qi, Z., Miller, G. W., and Voit, E. O. (2010) Computational modeling of synaptic neurotransmission as a tool for assessing dopamine hypotheses of schizophrenia, Pharmacopsychiatry 43 Suppl 1, S50–60. Best, J., Reed., M., and Nijhout, H. F. (2010) Models of dopaminergic and serotonergic signaling, Pharmacopsychiatry 43 Suppl 1, S61–66. Tretter, F. (2010) Mental illness, synapses and the brain--behavioral disorders by a system of molecules within a system of neurons?, Pharmacopsychiatry 43 Suppl 1, S9–S20. Fernandez, E., Schiappa, R., Girault, J. A., and Le Novere, N. (2006) DARPP-32 is a robust integrator of dopamine and glutamate signals, PLoS Comput Biol 2, e176. Lindskog, M., Kim, M., Wikstrom, M. A., Blackwell, K. T., and Kotaleski, J. H. (2006) Transient calcium and dopamine increase PKA activity and DARPP-32 phosphorylation, PLoS Comput Biol 2, e119. Lindskog, M. (2008) Modelling of DARPP-32 regulation to understand intracellular signaling in psychiatric disease, Pharmacopsychiatry 41, Suppl 1, S99–S104. Aghajanian, G. K., and Marek, G. J. (2000) Serotonin model of schizophrenia: emerging role of glutamate mechanisms, Brain Res Brain Res Rev 31, 302–312. Moghaddam, B., and Homayoun, H. (2008) Divergent plasticity of prefrontal cortex networks, Neuropsychopharmacology 33, 42–55. Moghaddam, B. (2003) Bringing order to the glutamate chaos in schizophrenia, Neuron 40, 881–884. Benes, F. M. (2009) Neural circuitry models of schizophrenia: is it dopamine, GABA, glutamate, or something else?, Biol Psychiatry 65, 1003–1005.

Chapter 37 Data Mining in Psychiatric Research Diego Tovar, Eduardo Cornejo, Petros Xanthopoulos, Mario R. Guarracino, and Panos M. Pardalos Abstract Mathematical sciences and computational methods have found new applications in fields like medicine over the last few decades. Modern data acquisition and data analysis protocols have been of great assistance to medical researchers and clinical scientists. Especially in psychiatry, technology and science have made new computational methods available to assist the development of predictive modeling and to identify diseases more accurately. Data mining (or knowledge discovery) aims to extract information from large datasets and solve challenging tasks, like patient assessment, early mental disease diagnosis, and drug efficacy assessment. Accurate and fast data analysis methods are very important, especially when dealing with severe psychiatric diseases like schizophrenia. In this paper, we focus on computational methods related to data analysis and more specifically to data mining. Then, we discuss some related research in the field of psychiatry. Key words: Data mining, Machine learning, Psychiatry, Drug efficacy, Schizophrenia

1. Introduction Data mining has been applied increasingly in the field of medicine over the last few years. Generally speaking, data mining can be described as the area of applied mathematics that tries to extract information from large datasets, often stored in huge computer databases. The methodological protocols (i.e., algorithms) are “born” from the interplay of different disciplines, such as statistics, artificial intelligence, and optimization. In the recent years, although both the number of challenges and algorithms that are specifically related to biomedical/clinical problems (1–4) have been increasing, data mining is still used for a broad range of applications that cover a large spectrum of science and engineering areas, like economics, machine vision, agriculture (5), etc. However,


593

594

D. Tovar et al.

novel data acquisition methods and new technological advances generate new computational challenges and problems. Psychiatry is a field of medicine that specializes in studying and curing mental disorders. As every other branch of medicine, psychiatry includes patient monitoring, animal studies, and in vivo and in vitro research studies, which always generate large amounts of data. The data are usually collected in the form of questionnaires, biometric data, or even microarray data matrices. After acquisition, datasets are stored in computer databases also known as data warehouses, where data is extracted, transformed, loaded, and aggregated. Most data acquisition methods (especially these that deal with microarray and sequencing technologies) result in the accumulation of vast amounts of data. In these cases, by just making empirical observations, even the most experienced clinical scientist fails to analyze them properly and draw safe conclusions. At this point, mathematical modeling and data mining should be employed in order to assist with these complicated tasks. In this paper, we explain the most representative data mining algorithms, and give examples of successful data mining projects applied in psychiatry research.

2. Methods Data mining is a very general term, and covers a large number of methods that originate from different branches of statistics and computer science. Some of them have empirical and some other solid mathematical foundations. In any case, these algorithms are usually judged by the accuracy of the results they produce, as well as their ability to assist the experienced clinical scientists. Next, we discuss some of the best-studied and applied data mining methodologies grouped in categories. 1. Data preprocessing includes all algorithms responsible for data preparation. Time-series filtering, outlier detection, data cleaning algorithms, and data normalization algorithms fall in this category. Proper data preprocessing is essential for a more efficient performance of learning algorithms. 2. Machine learning (ML): Learning from data is the most important part of data mining. Machine learning is a set of algorithms that have a dataset as input and also may be some information about it. The output of ML is a set of rules that let us make inference about any new data point. 3. Unsupervised learning (UL), sometimes also known as clustering, aims to find associations between data points (clusters). Clustering is usually performed when no information is given about the structure of the dataset. It can be used for

37

Data Mining Methods in Psychiatry

595

Fig. 1. General supervised learning process. The data are used in order to train an algorithm, for which some parameters have been selected first (through a model selection algorithm). Then, the trained model is used in data with unknown labels.

exploratory purposes (e.g., identify specific data structure that can be used for more efficient supervised algorithm design). For a more extensive tour to data clustering, we refer the reader to (6). 4. Supervised learning (SL) is one of the most well-known data mining algorithms. SL algorithms are given a set of data points (data samples) with known properties (features) and the classes they belong (labels). Then, the SL algorithm trains a model which at the end of the training phase is capable of deciding on the identity of new data points with unknown labels (test dataset). In this category, one can include the artificial neural networks, Bayesian classifiers, k-nearest neighbor classification, genetic algorithms, and others (7). If the samples contain qualitative feature values, then the rule-based classification can be employed (8, 9). Especially for the two-class general case binary classification, one of the most commonly used approaches is Support Vector Machine (SVM) (see Note 1). Originally proposed by Vapnik (10), SVM aims to determine a separation hyperplane from the training dataset. SVM possesses a solid mathematical foundation in optimization theory. A scheme summarizing the general supervised learning idea is shown in Fig. 1. If the two classes of data cannot be discriminated with a linear hyperplane, then the problem can be addressed as a nonlinear classification problem. Such problems can be attacked using the so-called kernel trick. In this case, original datasets are embedded in higher dimension spaces, where perfect linear separation can be achieved (11). The combined use of supervised classification methods with kernels is the most common way to address data mining problems. Finally, in order to use these packages, the user must possess some software programming skills, i.e., MATLAB (see Note 2). 5. Semi-supervised learning lies in between supervised and unsupervised learning. In this case, class labels are known only for a portion of available data and some partial information is given to the algorithm usually in the form of pairwise constraints (e.g., points a and b belong/do not belong to the same class). The goal in this case is to achieve optimal utilization of this information in order to obtain the highest predictive accuracy.

596

D. Tovar et al.

6. Biclustering tries to find associate groups of features with corresponding groups of samples. In this way, one can decide on the most important features that are responsible for a group of samples with specific characteristics. It has been extensively used in microarray data analysis for associating genes with specific phenotypes. There are numerous algorithmic approaches to biclustering, ranging from greedy algorithms, spectral biclustering, column reordering, and 0–1 fractional programming. For a more mathematically rigorous review about biclustering and their applications, we refer the reader to these references (12, 13). It is worth mentioning that biclustering can have either a supervised or an unsupervised version. 7. Feature selection consists of determining the most important properties (features) of each data point (sample) that are used for training. For example, given a set of people (i.e., sample) and some of their features like weight, height, eye color, and hair color, we wish to distinguish the infants from the adults. A feature selection algorithm tries to select a small subset of features that have the largest combined discriminatory power (in this case, may be weight and height). In case of problems described by hundreds or thousands of characteristics, feature selection permits to reduce the number of variables, with a great advantage in terms of computational time needed to obtain the solution. Examples of algorithms for feature selection include the “RFE” and “Relief” described in reference 14. Here, we need to point out the difference between feature selection and feature extraction. Feature extraction consists of the construction of some features that do not necessarily belong to the set of the original features. The significant reduction of the original number of features, due to a feature selection or feature extraction algorithm is called dimensionality reduction, which is essential in order to improve the processing time. A standard method for feature extraction is the principal component analysis as shown in Fig. 2.

Fig. 2. A model of change feature selection/extraction strategy. The initial set of features is fed to a feature selection/ extraction algorithm. The reduced set of features is used for learning, and based on the performance of the training phase one may reexamine the feature selection/extraction process.

37


597

8. Data visualization/representation: This last branch of data mining deals with methods, where the extracted information can be represented to/visualized by the end user. Massive datasets need special types of algorithms for analysis and representation (15). One common way to represent information and potential relationship between entities is through graphs (also referred to as networks). Network representation can be very useful in understanding the dynamics that govern a system. Software packages, like “Cytoscape software” (16), deal with representation of complex biological data. Two other topics related to data mining and more specifically to the supervised machine learning component of the process are the model selection and the cross validation of the learning scheme (see Note 3). Model selection is related to the “tuning” of the model itself in terms of the parameter selection. The most common method employed in this case is a uniform search over a grid spanned by the parameters. Lately, there have been proposed some more advanced model selection methods based on uniform design theory (17). Taken together, cross validation of a model is very important, especially when one wants to statistically assure the independence of the output model accuracy from the specific properties of training and testing datasets. For this, the given data are partitioned many times in testing and training datasets using some resampling approach. The reported accuracy of the method is the average accuracy of all of the cross-validation repetitions. Cross-validation methods usually vary by their strategy for partitioning the original data. Most of the well-studied cross-validation techniques include k-fold, leave-one-out, and hold-out cross validation. All the described methods are implemented in many opensource problem-solving environments, like R (http://www.rproject.org), (http://www.cs.waikato.ac.nz/ml/weka), Octave (http://www.gnu.org/software/octave/), and Weka (http:// www.cs.waikato.ac.nz/ml/weka) (see Note 4). They provide simple graphical user interfaces that can also be used by nonexpert users.

3. Methods and Applications of Data Mining 3.1. Applications in Psychiatry

The aforementioned technology of data mining and its application are applied in psychiatric research. One of the most important problems in psychiatry is to diagnose and/or assess the disease accurately. Another important aspect is the running time of the computational algorithm. Ultimately, clinical society desires noninvasive data acquisition methods in combination with

598

D. Tovar et al.

accurate analysis protocols that can run in a timely manner in a not-so-demanding hardware configuration. Thus, we need to emphasize that the purpose of this paper is to give an overview with some illustrative applications of the field rather than trying to cover, and include, the full spectrum. 3.2. Data Mining in MRI Medical Imaging

One of the primary sources of data used by expert clinician is medical imaging. Magnetic resonance imaging (MRI) is one of the most widely used medical imaging techniques. In one study, Arnborg et al. used MRI scans taken from control subjects and patients with schizophrenia (18). The MRI scans are turned into 3D images and processed by the BRAINS software. The sample size included 144 subjects, 63 suffering from schizophrenia and 81 controls. Analysis of the different scans is performed through Bayesian modeling. The outputs of this analysis are networks whose nodes are connected by a variable covariate. The long-term goal of the study is to provide a modeling network to identify the underlying mechanism, which causes a mental disease. The networks produced from the physiological data measurements in the form of MRI correlate different parts of the brain. Bayesian modeling has been employed even in more recent studies in order to model, understand, and evaluate the nature of schizophrenia (19, 20).

3.3. Voice RecognitionAssisted Diagnosis

Data mining can be utilized for mental disease diagnosis using noninvasive data. For example, Diederich et al. used an SVM approach in order to distinguish between schizophrenia patients and controls (21). The data used for this classification task are voice samples from patients and control. Subjects are given a story and a group of semantic words that they had to use, and then they were asked to tell a story about it. This was done in order to constrain the number of different words subjects used. SVM achieved 77% accuracy and the systems performance was increased when only the 100 most frequently used words were used. Authors suggest fusion of the proposed speech recognition method with other datasets that would incorporate facial movement, medical imaging (e.g., MRI), and biological data (e.g., microarrays).

3.4. Psychoactive Drug Efficacy Assessment

Data mining has been also applied in the area of drug effect assessment. In one study, Kafkafi et al. uses a data mining algorithm in order to assess the efficacy of three kinds of psychopharmacological drugs: psychomotor stimulant, opioid, and psychotomimetic (22, 23). Animals were dosed with these drugs and then their movements were recorded. Based on the path they follow, several features were extracted which were then given into the supervised learning algorithm. The data mining algorithm (“Pattern Arrays”—PA) is used in order to determine the optimal predictors for each type of drug. The hypothesis is that the different types of psychoactive drugs produce different behavioral profiles that can be captured and

37


599

analyzed by movement. In general, drug efficacy assessment is a crucial and complicated task. The discovery of a therapeutic agent and the understanding of the whole underlying mechanism is a challenging optimization problem. For a more comprehensive review on this topic, we refer the reader to reference 24. 3.5. Data Mining and Network Analysis in EEG

Another common noninvasive and low-cost technique for acquiring useful data for diagnosis is the electroencephalogram (EEG). EEG recordings are scalp recordings of the brain electric potential that is produced as a result of brain neural oscillations. Quantitative EEG analysis is a field with many open computational problems (2, 25, 26). One thoughtful way for representing EEG data is by using a network (or graph) representation. Usually, nodes of such networks are electrode sites of the brain, whereas the edges correspond to some kind of generalized similarity measure. Theoretical foundations of such similarity across measures can be found in linear or nonlinear time-series analysis literature. The dynamic alterations of such networks that are induced due to some pathology or as a result of some treatment effect can be indicative of the complicated underlying mechanism. The changes between networks of different classes can be measured by graphing theoretic quantitative measures. Network modeling and analysis have also been used for other pathological conditions that affect brain function, like epilepsy or Alzheimer’s disease. In another study, Sakkalis et al. used wavelet coherence as a measure of synchrony and compared the networks between schizophrenia and control subjects. They define the quantitative measures used for capturing the network’s structure as the average degree of the graph, the clustering coefficient, and the average shortest path length (27). Preliminary results indicate that all three measures take lower values for patients with schizophrenia. The software tool developed for this study is described in 28. Another area of quantitative EEG analysis, where data mining and mathematical theory of optimization have been successfully applied, is epilepsy research. Traditionally, experienced, boardcertified electroencephalographers manually examine long-term EEG recordings and asses the severity of the recorded epileptogenic activity. This is a slow, expensive, and tedious process. Manual scoring is always subject to human errors that are related to experience and fatigue of the clinician. Sometimes, quantitative patterns might be very well hidden, making it impossible even to the most experienced observer to mine them. Automated analysis and quantification of patterns and trends that are “hidden” in EEG recordings is a very important problem in quantitative EEG analysis. Epilepsy researchers, especially, want to find features that precede the occurrence of seizures and thus propose efficient predictive algorithmic schemes. The ultimate goal is to provide a full system able to predict and anticipate seizure activity.

600

D. Tovar et al.

Several researchers have employed nonlinear time-series analysis and deterministic chaos-based approaches in order to establish biomarkers to predict the evolution of an epileptic seizure. Some of the most notable approaches toward epileptic seizure prediction algorithm have been demonstrated by Iasemidis et al. who employed short-term Lyapunov exponents and optimization process in order to propose the optimal EEG-based biomarker for this problem (29). Other approaches include correlation dimension (30), phase synchronization (31), similarity index (32), and other methods. For more extensive review of epileptic seizure prediction literature, we refer the reader to references 33 and 34. 3.6. Information Extraction Through Tree Mining

Medical record data mining represents another area for research. Medical record data is represented in the form of a decision tree. The trees that belong to subjects of the same category are mined to determine the common patterns among them. In their work, Hadzic et al. employed XML modeling and tree mining in order to extract patterns that are able to provide useful information about mentally ill patients (35). In another study, the IMB3-Miner algorithm has been used (36); this analysis includes subtrees (smaller trees that are contained in the original trees) characterizing each class specifically. The XML database modeling in conjunction with data mining can provide future online tools for identifying the cause and factors that are mostly related to disease progression, which can yield better early-stage diagnosis and better treatment planning. The same authors in 37, 38 introduce an online system called thinking PubMed, whose goal is to properly extract and represent information stored in large databases like PubMed related to mental diseases.

4. Conclusion In this chapter, we give a brief overview of data mining with discussion of some of its most prominent applications in psychiatric research. It is really very interesting to observe the development of techniques that combine traditional medical practice and stateof-the-art machine learning techniques. This leads to the development of automatic or semiautomatic software and systems able to assist and support clinician’s profession, by extracting and representing knowledge in a user-friendly way, for an accurate and efficient diagnosis. Nevertheless, despite the progress and the success stories of many researchers applying computational tools in the medical field, there is still a gap between mathematics and medicine. The most important burden, which arises in every multidisciplinary collaborative research, is to overcome the technical language barrier between researchers and to be able to communicate

37


601

mathematical ideas to medical professionals easier and vice versa. It is our belief that computational and clinical science should go hand in hand for the mutual benefit of both.

5. Notes 1. All the methods described in this chapter are usually implemented in practice through software programming languages. For SVM classification software, there are several open-source implementations like libSVM or SVMlite. In order to use these packages, the user must possess some software programming skills, i.e., MATLAB. 2. One of the most complete data mining software suite for Matlab is the open-source toolbox Matlab Arsenal. This toolbox includes a large number of functions related to data clustering; feature extraction, and feature selection. The installation and use are straightforward, requiring basic Matlab programming knowledge. 3. Graph drawing and visualization tools are becoming more and more popular every day as there are needs for massive graph representation. The mentioned open-source package Cytoscape (that is mentioned in the chapter) is one of them. It is worth noting that this package is not only used for graph drawing, but also allows for some pretty sophisticated data analysis methods. Thanks to the developer’s platform that comes with it, programmers can develop and add data analysis protocols written in Java and add them as plug-ins to the main program. 4. Another data analysis mentioned in the text is Weka. This is another open-source data mining toolbox developed from University of Waikato. It is written in Java and it offers a number of functions related to data mining. Thus, it can be used by programmers in order to add Weka functionality in for their application. For users less experienced with programming, Weka offers a user interface named “Weka Knowledge Explorer” that offers a large variety of windowed user-friendly options for data analysis and plotting. References 1. Alves, C. J. S., Pardalos, P. M., and Vicente, L. N. (2008) Optimization in medicine, 1st ed., Springer, New York. 2. Chaovalitwongse, W. A., Pardalos, P. M., and Xanthopoulos, P., (Eds.) (2010) Computational Neuroscience, Vol. 38, Springer, New York.

3. Pardalos, P. M., and Romeijn, H. E. (2009) Handbook of Optimization in Medicine, Springer, New York. 4. Seref, O., Kundakcioglu, O. E., and Pardalos, P. M. (2007) Data mining, systems analysis, and optimization in biomedicine : Gainesville,

602

5. 6. 7. 8.

9.

10. 11.

12.

13.

14.

15.

16.

17.

18.

19.

D. Tovar et al. Florida, U.S.A., 28–30 March 2007, American Institute of Physics, Melville, N.Y. Mucherino, A., Papajorgji, P., and Pardalos, P. M. (2009) Data Mining in Agriculture, Springer. Jain, A. K., and Dubes, R. C. (1988) Algorithms for clustering data, Prentice Hall. Bishop, C. M. (2006) Pattern recognition and machine learning, Springer, New York. Quinlan, J. R. (1992) C4.5: Programs for Machine Learning, Morgan Kaufmann, San Mateo, CA. Quinlan, J. R. (1996) Improved use of continuous attributes in C4.5, J Artif Intell Res 4, 77–90. Vapnik, V. N. (1995) The nature of statistical learning theory, Springer, New York. Shawe-Taylor, J., and Cristianini, N. (2004) Kernel methods for pattern analysis, Cambridge University Press, Cambridge, UK ; New York. Busygin, S., Prokopyev, O., and Pardalos, P. M. (2008) Biclustering in data mining, Comput Oper Res 35, 2964–2987. Xanthopoulos, P., Boyko, N., Fan, N., and Pardalos, P. M. (2010) Biclustering: algorithms and applications in data mining and forecasting, in Encyclopedia of Operations Research and Management Science (Wiley, Ed.), p to apprear. Guyon, I., and Elisseeff, A. (2003) An introduction to variable and feature selection, Journal of Machine Learning Research 3, 1157–1182. Abello, J., Pardalos, P. M., and Resende, M. (2002) Handbook of massive datasets, Kluwer Academic Publisher, Dordrecht, The Netherlands. Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., and Ideker, T. (2003) Cytoscape: A software environment for integrated models of biomolecular interaction networks, Genome Res 13, 2498–2504. Huang, C. M., Lee, Y. J., Lin, D. K. J., and Huang, S. Y. (2007) Model selection for support vector machines via uniform design, Comput Stat Data An 52, 335–346. Arnborg, S., Agartz, I., Hall, H., Jönsson, E., Sillén, A., and Sedvall, G. (2002) Data mining in schizophrenia research – preliminary analysis., in Principles of Data Mining and Knowledge Discovery (Elomaa, T., Mannila, H., and Toivonen, H., Eds.), pp 27–38, Springer. Hall, H., Lawyer, G., Sillen, A., Jonsson, E. G., Agartz, I., Terenius, L., and Arnborg, S. (2007) Potential genetic variants in schizophrenia: A Bayesian analysis, World J Biol Psychia 8, 12–22.

20. Lawyer, G., Nyman, H., Agartz, I., Arnborg, S., Jönsson, E. G., Sedvall, G. C., and Hall, H. (2006) Morphological correlates to cognitive dysfunction in schizophrenia as studied with Bayesian regression, BMC psychiatry 6:31. 21. Diederich, J., Al-Ajmi, A., and Yellowlees, P. (2007) E-x-ray: Data mining and mental health, Appl Soft Comput 7, 923–928. 22. Elmer, G. I., and Kafkafi, N. (2009) Drug Discovery in Psychiatric Illness: Mining for Gold, Schizophrenia Bull 35, 287–292. 23. Kafkafi, N., Yekutieli, D., and Elmer, G. I. (2009) A Data Mining Approach to In Vivo Classification of Psychopharmacological Drugs, Neuropsychopharmacol 34, 607–623. 24. Enna, S. J., and Williams, M. (2009) Challenges in the Search for Drugs to Treat Central Nervous System Disorders, J Pharmacol Exp Ther 329, 404–411. 25. Pardalos, P. M. (2004) Quantitative neuroscience : models, algorithms, diagnostics, and therapeutic applications, Kluwer Academic, Boston. 26. Pardalos, P. M., and Príncipe, J. C. (2002) Biocomputing, Kluwer Academic, Dordrecht ; Boston, Mass. 27. Sakkalis, V., Oikonomou, T., Pachou, E., Tollis, I., Micheloyannis, S., and Zervakis, M. (2006) Time-significant wavelet coherence for the evaluation of schizophrenic brain activity using a graph theory approach, in Proceedings of 28th Annual International Conference of IEEE EMBS, New York, NY., pp 4265–4268. 28. Oikonomou, T., Sakkalis, V., Tollis, I., and Micheloyannis, S. (2006) Searching and visualizing brain networks in schizophrenia, in Biological and Medical Data Analysis (Maglaveras, N. a. C., Ioanna and Koutkias, Vassilis and Brause, Rüdiger, Ed.), pp 172–182, Springer. 29. Iasemidis, L. D., Shiau, D. S., Pardalos, P. M., Chaovalitwongse, W., Narayanan, K., Prasad, A., Tsakalis, K., Carney, P. R., and Sackellares, J. C. (2005) Long-term prospective on-line realtime seizure prediction, Clin Neurophysiol 116, 532–544. 30. Lehnertz, K., and Elger, C. E. (1998) Can epileptic seizures be predicted? Evidence from nonlinear time series analysis of brain electrical activity, Phys Rev Lett 80, 5019–5023. 31. Mormann, F., Lehnertz, K., David, P., and Elger, C. E. (2000) Mean phase coherence as a measure for phase synchronization and its application to the EEG of epilepsy patients, Physica D 144, 358–369. 32. Le Van Quyen, M., Martinerie, J., Baulac, M., and Varela, F. (1999) Anticipating epileptic seizure in real time by a nonlinear analysis of

37

33.

34. 35.

36.

similarity between EEG recordings, Neuroreport 10, 2149–2155. Mormann, F., Andrzejak, R. G., Elger, C. E., and Lehnertz, K. (2007) Seizure prediction: the long and winding road, Brain 130, 314–333. Sackellares, J. C. (2008) Seizure prediction, Epilepsy Currents 8, 55–59. Hadzic, M., Hadzic, F., and Dillon, T. (2008) Tree Mining in mental health domain, in Hawaii International Conference on System Sciences, Proceedings of the 41st Annual, pp 230–230. Tan, H., Dillon, T. S., Hadzic, F., Feng, L., and Chang, E. (2005) MB3-Miner: mining eMBedded subTREEs using tree model guided


603

candidate generation, in Proceedings of the 1st International Workshop on Mining Complex Data 2005 in conjunction with ICDM 2005 pp 103– 110, Houston, TX. 37. Hadzic, M., D’Souza, R., Hadzic, F., and Dillon, T. (2008) Synergy of Ontology and Data Mining: Increasing Value of the Mental Health Information within PubMed database, in Proceedings of the Second IEEE International Digital Ecosystems and Technology Conference, pp 600–603. 38. Hadzic , M., D’Souza , R., Hadzic , F., and Dillon, T. (2008) Thinking PubMed: an Innovative System for Mental Health Domain, in Proceedings of the 21st IEEE International Symposium on Computer-Based Medical Systems.

sdfsdf

INDEX A ABA. See Activity-based anorexia Active coping ..................................................................... 40 Activity-based anorexia (ABA)................................ 377–391 Acute.... ........................................... 4, 35, 36, 38, 39, 70–72, 104, 106, 110, 115, 136, 156, 157, 171, 172, 193, 258, 269, 270, 272, 274, 276, 400, 410, 568, 589 Adaptive decision making ........................................... 85–99 Addiction................................. 34–41, 44, 86, 165, 206, 234, 243–254, 258, 279, 304, 316, 321, 324, 330, 331, 351–362, 378, 409, 487 ADHD. See Attention-deficit hyperactivity disorder Adolescent cannabis exposure.................................. 231–240 Affect........................................11, 14, 18, 33–35, 37, 39, 53, 56, 58, 65, 75, 86, 91, 108, 117, 135, 151, 157, 189, 190, 236, 248, 258, 269, 304, 315, 318, 351, 352, 368, 378, 384, 385, 399–402, 414, 416, 421, 422, 434, 438, 440, 449, 459, 484, 532, 533, 563, 568, 599 Alcohol dependence .................................................. 43, 205–228 exposure ..................................................... 205–228, 472 AN. See Anorexia nervosa Anabolic–androgenic steroid (AAS) .......400, 403, 405, 406, 410–411, 413, 416–422 Androgen................................................................. 397–422 Animal models ..........................................3–5, 8–13, 15–21, 32–42, 58–60, 65–76, 85, 103–121, 125–140, 146, 165, 193–200, 206, 232–234, 239, 257–267, 269, 273, 330, 351–362, 367–375, 379, 397–422, 435, 439, 440, 446, 449, 450, 454, 457, 471–484, 487–502, 505–529, 531, 542 Animal welfare ................................................ 158, 190, 274 Anorexia nervosa (AN) ............................378–382, 388, 390 Antagonism of apomorphine-induced hypothermia ....... 116 Anxiety disorders .............................. 8, 39–41, 59, 378, 453, 487, 531, 532 like behavior ............................ 7, 36, 126, 127, 132, 136, 137, 217, 218, 223, 400, 414, 418–421, 449 Anxiolytic .............................................40, 41, 180, 189, 414 Apoptosis......................................................................... 269 Array..... .......................43, 323, 508, 516, 544, 548, 549, 598 ASST. See Attention set-shift task

Assumptions ............................... 6, 9, 53, 105, 120, 137, 389 Attention-deficit hyperactivity disorder (ADHD) ............................................. 165, 505–529 Attention set-shift task (ASST) ...........86–88, 91–94, 97, 98 Autoimmune ....................................................... 4, 433–440 Avoidance .....................40, 58, 107, 114–115, 132, 138, 177, 178, 186, 188, 531

B Bay K 8644 drug.............................................68, 73–76, 156 Behavioral economics ...................................... 304, 316–317 Behavioral pharmacology .........................304, 321, 322, 324 Binge.... ................................34, 35, 218, 220, 280, 292, 301, 356–358, 360, 361, 370, 372, 373 eating.... ......................................351–355, 359, 362, 371 Biomarker .......... 6, 7, 9, 14, 16, 330, 331, 453–465, 574, 600 discovery ............................................................ 531–538

C Cannabinoid, drug addiction ............231, 233, 234, 237–240 Caspase-3 ........................................................ 195, 199, 200 CellDesigner® ......................................................... 578–580 ChIP. See Chromatin immunoprecipitation Choice behavior........................................................... 85, 95 Chromatin immunoprecipitation (ChIP) ........458, 461–464, 575, 576 Chronic chronic caffeine model ................................................. 71 chronic mild stress (CMS).....................37–39, 109–111, 120, 131, 134–137 chronic restraint stress (CRS) .................................... 112 chronic unpredictable stress (CUS) ............. 37, 108–109 Circadian ...................................... 33, 37, 253, 292, 293, 301 Cognition ................6, 87, 148, 399–402, 414, 419, 421, 435 Cognitive flexibility ........................................................... 86 Comorbidity ..................................... 6, 9–10, 21, 32, 33, 138 Computer simulations ............................................. 567–589 Conditioned stimulus (CS) ............................................... 58 Consciousness.................................................................. 568 Content validity ................................................................. 60 Cortisol/dehydroepiandrosterone-sulfate ratio ................ 455 Cost-benefit ............................................................ 100, 165 Craving ......................36, 39, 41–43, 206, 234, 258, 352, 354

Firas H. Kobeissy (ed.), Psychiatric Disorders: Methods and Protocols, Methods in Molecular Biology, vol. 829, DOI 10.1007/978-1-61779-458-2, © Springer Science+Business Media, LLC 2012

605

PSYCHIATRIC DISORDERS: METHODS AND PROTOCOLS 606 Index C-reactive protein (CRP) ................................................ 456 CS. See Conditioned stimulus Cyclic adenosine monophosphate response element binging (CREB) protein .................... 36, 69 Cytokines ................................................ 434–440, 445–451

D Data analysis.................................... 119, 161, 167, 170–172, 183–185, 287–289, 300, 312, 314, 316–317, 322, 474, 479–482, 497–499, 521, 536–538, 554–555, 560–562, 564, 568, 571, 572, 576–577, 596, 601 Data mining ............................................................ 593–601 Decision-making ......................................... 85–99, 165–175 Defensive burying........................................................ 39–41 Depression ..................................... 3, 7, 9, 11, 15, 16, 37–39, 58, 59, 103–121, 125–140, 180, 232, 258, 351, 400, 401, 421, 487, 488, 533, 568, 569, 589 2D-GE. See Two-dimensional gel electrophoresis Diagnostic and statistical manual of mental disorders (DSM) ........................ 4–6, 8–11, 13, 16, 21, 35, 244 Dietary ethanol intake ............................................. 214–218 Diet-induced obesity (DIO).................................... 370–371 Differential protein expression profiling .......................... 561 DIO. See Diet-induced obesity Discrete trials................................................... 262, 291–301 DNA array..... ...................................................................... 549 methylation.................................................. 20, 575–577 microarray ....................................................13, 506, 510, 515–521, 544, 547, 549, 576 Dogs.... ........................................................................ 58, 59 Dopamine ...................................7, 17, 18, 44, 66, 68–72, 74, 75, 87, 121, 127, 193, 200, 260, 269, 270, 353, 405, 417, 449, 450, 455, 456, 546, 581, 582, 584–589 Dose..... ................................. 70–73, 75, 116, 120, 121, 128, 129, 135, 156, 157, 161, 172, 173, 185, 190, 196, 200, 218–220, 222, 227, 228, 234, 236, 239, 240, 245, 247, 249, 250, 253, 260, 265, 270–277, 279, 280, 285–290, 293, 294, 299–301, 303, 304, 309–318, 322, 324–326, 388, 391, 407, 408, 410, 412, 415, 435, 436, 448, 450, 473, 475, 515, 598 Drinking .................................34, 42, 71, 110, 114, 120, 126, 133, 139, 206, 209, 215, 223, 226, 227, 279, 352, 357, 358, 360–362, 383, 388, 389, 391 Drug addiction alcohol ......................................................................... 35 cocaine ........................................................... 35, 36, 316 nicotine ........................................................................ 35 opioids ......................................................................... 35 Δ9-tetrahydrocannabinol (THC) ................................. 35 Drug efficacy ........................................................... 598–599

E Early environmental deprivation model .......... 68, 70–71, 73 E-cell® ..................................................................... 579, 580 EEG. See Electroencephalogram EES. See Experimental autoimmune encephalitis Effort.... ..............................5, 6, 8, 10, 11, 18, 21, 51, 86–89, 93–95, 129, 267, 369, 374 Effortful t-maze task (ETT) ......................87–89, 91, 94–95 EGF. See Epidermal growth factor Electrode implantations........................................... 259–262 Electroencephalogram (EEG) ......................... 570, 599–600 Elevated plus maze (EPM)..........................39–40, 112, 127, 132, 136, 138, 210, 211, 223, 400, 420, 421, 531, 533 Endophenotypes ........................... 11, 13, 14, 16–18, 37, 568 Endothelial dysfunction .................................................. 455 Epidermal growth factor (EGF).............................. 447–451 Epilepsy ........................................................................... 599 Epistemic cycle ........................................................ 570–572 EPM. See Elevated plus maze Erythrocyte sedimentation rate ....................................... 455 Escalating dose ................................................ 270–272, 275 Ethanol ................................................ 43, 95, 120, 151, 183, 205–209, 212–228, 233, 259–261, 265, 331, 337, 448, 458, 459, 461, 471–484, 509, 528, 542, 545, 546, 551–564, 576 Ethology ...................................................................... 40, 59 ETT. See Effortful t-maze task Experimental autoimmune encephalitis (EES) ...................4 Expression ..................................5, 11–14, 16, 18, 20, 42, 55, 65–70, 72–74, 76, 109, 157, 160, 161, 244, 330, 331, 343, 379, 398, 402, 405, 411, 414, 420, 435, 437–439, 445, 449, 455–457, 464, 465, 472, 482, 484, 506, 510, 529, 532–534, 541, 544, 547–549, 551–564, 574, 575

F Fear...... ...............................6, 10, 39, 40, 177–179, 186, 378, 403, 434, 450, 531 Feasibility studies............................................................... 58 Food restriction ..............86, 90–91, 168, 244, 248, 378, 380, 384–388, 390, 405 Forced swim test (FST) ...........................9, 17, 37, 104–106, 119, 126–128, 130–136, 139, 401

G GABA. See γ-Aminobutyric acid γ-aminobutyric acid (GABA) ........................7, 40, 212, 408, 412, 413, 417, 418, 422, 439, 455, 456, 491, 588, 589 plasma levels .............................................................. 456 GCR. See Glucocorticoid receptor Gel analysis.............................................................. 340, 575

PSYCHIATRIC DISORDERS 607 Index Gel-based proteomics .............................................. 505, 530 Gene profiling ......................................................... 541–549 Generalizability ........................................................... 53, 54 Genetic pathways ........................................................ 12–13 Genomics ......................................... 454, 537, 570, 573, 574 Gepasi® ........................................................................... 579 Glucocorticoid receptor (GCR) ................ 7, 20, 73, 74, 410, 455, 457, 461 Grounded theory ............................................................... 52

H Haloperidol ................................ 72, 193–197, 199, 200, 449 Heuristic models ..................................................... 587–589 High anxiety-related behavior (HAB)......132, 531–534, 537 High-fat diet .................................... 357, 360, 369, 371, 384 Hippocampus .....................7, 10, 17, 20, 109, 117–119, 338, 414, 419, 420, 434–439, 449, 472, 480, 482, 483, 490 Hold down .............................................................. 279–290 HPRT knockout mice ........................................... 68, 74, 75 HTP induced head-twitches ........................................... 115 6-Hydroxydopamine (6-OHDA) ....................68–72, 75, 76, 156, 505, 506, 508, 515 Hyperactivity ............................. 39, 160, 179, 190, 377–379, 390, 449, 505, 506

I ICD. See International classification of diseases ICSS. See Intracranial self-stimulation IL-2 deficiency ................................................ 436–438, 440 In-depth interview................................................. 52, 54, 55 Inflammation ................................................... 200, 330, 411 neuregulin-1 .......................................447, 448, 450, 451 Proinflammatory response ............................................... 449 In-silico .................................... 532, 533, 537, 572, 586, 587 Interleukin-1 ........................................................... 434, 435 Interleukin-2 ................................................... 433–440, 455 Interleukin-8 ................................................................... 455 International classification of diseases (ICD)................................ 4–6, 8–11, 13, 16, 21, 244 Intoxication ..................................................34, 35, 219, 228 Intracranial self-stimulation (ICSS) .......35, 36, 38, 257–267 In vitro ................................15, 32, 35, 42–44, 411, 417, 420, 436, 437, 440, 544, 594 In vivo.................................... 32, 43, 44, 353, 411–413, 436, 437, 440, 472–473, 475, 532, 586, 594 Isobaric tags for relative and absolute quantitation (iTRAQ) labeling ........................472–474, 477–479, 481–484 iTRAQ labeling. See Isobaric tags for relative and absolute quantitation (iTRAQ) labeling

L LAB. See Low anxiety-related behavior Laser capture microdissection ..................................... 541–549

microdissection .................................................. 541–549 pressure catapulting ................................................... 541 Learned helplessness (LH) ....... 106–107, 118, 120, 131, 134 models.. . ...................................................................... 37, 59 Lesch-Nyhan syndrome ................. 65, 66, 68, 69, 72, 74, 75 Liquid chromatography tandem mass spectrometry (LC/MS) analysis ........................331, 474, 478, 496, 497, 500, 554, 558–560 Locomotor activity (LM) ................................120, 133, 137, 321–327, 375, 447, 450, 473, 475 Low anxiety-related behavior (LAB)............... 531–534, 537

M Machine learning (ML) .................................. 594, 597, 600 MALDI-TOF-MS ......................................... 513, 525, 526 Mass spectrometry (MS) .................................331, 332, 338, 340, 342–344, 472, 474, 477–482, 484, 488, 489, 492, 493, 495–497, 499–502, 506, 513–514, 525–527, 532, 533, 535, 536, 538, 552, 554, 558–561, 564 Maternal deprivation ................................................. 37, 113 Mathematica ................................................... 579, 580, 583 Matlab.. ....................................................579, 580, 595, 601 M-cell.... .................................................................. 579, 580 Memory ................................................. 7, 10, 112, 135, 136, 145, 146, 149, 152, 206, 236, 399, 402, 403, 434–438, 449, 568, 569, 571, 581–583 Mental illness ................3–6, 8–17, 19–21, 56, 103, 106, 568 Methamphetamine (METH) ................................35, 76, 87, 269–277, 450, 506, 508, 515 Methodology ...............15, 35, 43, 52, 87, 134, 435, 472, 572 Mice... . ......................... 4, 5, 8, 12–14, 17, 40, 59, 68, 73–76, 89, 90, 104–106, 115, 116, 118–120, 145, 146, 157, 166, 177–190, 206–209, 215, 220, 221, 223, 225–227, 368, 369, 373, 375, 377–391, 412, 413, 415, 416, 418, 419, 436–440, 446–450, 465, 472, 488, 490, 492, 493, 496, 497, 531–534, 536, 538, 544, 546, 547 Microarray ........................................... 11–13, 457, 506, 510, 515–521, 544, 547–549, 573, 576, 594, 596, 598 Microglia ......................................................... 435, 551–564 ML. See Machine learning Modeling ..................................... 4, 9, 32, 33, 41–44, 86–87, 125–140, 165–175, 243–254, 379–380, 445–451, 572–574, 577–587, 594, 598–600 Molecular networks ..................................583, 585–587, 589 Molecular psychiatry ....................................... 570–572, 589 Motivation ........................................... 35–38, 40, 41, 58, 91, 99, 148, 206, 244, 248–250, 254, 258–260, 301, 353, 361, 400, 568 Motor behavior........................................................ 236, 568 mRNA ......................................................353, 434, 438, 457 MS. See Mass spectrometry Myelin basic protein ........................................................ 456 Myogenesis ...................................................... 398, 411, 422

PSYCHIATRIC DISORDERS: METHODS AND PROTOCOLS 608 Index N Naturalistic ....................................... 51, 54, 59, 67, 113, 582 Neonate ..................................................................... 68, 237 Neopterin ........................................................................ 456 Network analysis ..................................................... 599–600 Neural stem cell (NSC) ........................................... 6, 17, 18 Neuroadaptations face .............................................................................. 35 validity ......................................................................... 35 Neurobiochemical/drug-induced model .................. 115–117 Neurobiochemical model......................................... 115–117 Neurobiological substrates ................................................. 39 Neurochemical mobile............................................. 587–589 Neurodevelopment ........................................4–8, 11, 13, 14, 18–21, 65, 66, 68, 231, 236, 431, 446 Neurogenesis ................................................... 103–121, 437 Neuroimmunology .................................................. 439–440 Neuron-specific enolase ................................................... 456 Neuropeptides ......................................................... 487–502 Neuropeptide Y (NPY ) expression .................................. 456 Neuroplasticity ...................................... 42, 72, 73, 103, 106, 107, 109–116, 120, 121 and neurogenesis ..............................104, 105, 108, 117–119 Neuropsychiatric disorders .......................232, 239, 433–440 Neuroscience .................................. 10, 31, 41, 544, 579, 589 Neurotoxicity ............................................270, 272, 273, 552 Neurotransmitter .........................................66, 85, 359, 416, 436, 455, 487, 551, 587 Nicotine anabasine ................................................................... 254 anatabine ................................................................... 254 cotinine .............................................................. 254, 334 myosmine .................................................................. 254 nornicotine ................................................................ 254 reinstatement ......................................247, 248, 251–252 withdrawal ................................................. 252, 257–267 Nicotinic acetylcholine receptors (nAChRs) ........... 244, 258 NIH. See Novelty-induced hypophagia 15 N incorporation rate...................................... 533, 535, 538 15 N metabolic labeling ............................................. 532–535 N-Methyl-δ-aspartate (NMDA) ......................7, 43, 72, 73, 76, 149, 156, 450, 586 Normal anxiety-related behavior (NAB) ......... 531–534, 538 Novel environment tests ...............................60, 73, 113, 121 Novelty-induced hypophagia (NIH) ................ 13, 113–114, 158, 340, 450, 454, 465, 573 NPY expression. See Neuropeptide Y (NPY ) expression NSC. See Neural stem cell

O Obsessive-compulsive disorder ............................ 39, 40, 378 6-OHDA. See 6-Hydroxydopamine Olfactory bulbectomy model ..................................... 37, 115

Operant behavior ...................... 253, 258, 260, 323, 326, 370 Operant chambers .................................89, 90, 97, 246–248, 250–252, 277, 284–286, 298, 300, 308, 309 Osmotic minipump implantations................................... 260 Oxidative damage ............................................ 197, 269, 270 Oxidative stress.........................................200, 270, 330, 551

P Passive avoidance test .............................................. 114–115 PathwayLab®........................................................... 578–580 Pavlov, I.P........................................................................... 58 P11 biomarker ......................................................... 453–465 Pemoline model ......................................71–73, 76, 155–161 Peptidase.......................................................................... 487 Peptidomics ............................................................. 487–502 Perception ....................................... 5, 56, 182, 367, 406, 568 Performance enhancement ......................399, 401, 402, 405, 409, 410, 412–414, 421, 422 Perinatal....................................................232–237, 330, 398 Phobic disorders ................................................................ 39 Platelet cd63 expression .......................................................... 456 leukocyte aggregates .................................................. 456 MAO-β activity......................................................... 455 serotonin concentration ............................................. 455 Pluripotent stem cells .................................................. 13–15 PND. See Post-natal day Polyriboinosinic-polyribocytidilic acid (PolyI:C) ...................................................... 446–450 Post-natal day (PND) ................................18, 233, 235–240, 446, 472, 473, 475, 477, 533, 534 Posttraumatic stress disorder (PTSD) ..........39, 59, 453–465 PPI. See Prepulse inhibition Prader-willi syndrome ....................................................... 65 Preclinical model ............................ 32, 42, 44, 156, 321, 367 Predictive validity .......................... 3–5, 8, 13, 15, 18, 21, 34, 36, 37, 39, 41, 110, 156, 379 Prenatal cannabis exposure ...................................... 231–240 Prenatal stress models .............................................. 112–113 Prepulse inhibition (PPI)................................7, 17, 447–450 Price.................................................... 57, 303, 304, 316, 317 Protease .....................333, 338, 458, 461–464, 473, 490, 554 Proteomics.............................................. 4, 324, 329–346, 454, 471–484, 505–529, 531–538, 551–564, 570, 573, 574 Psychiatric disorders ADHD ...................................................... 165, 505–529 anxiety disorders .......................... 8, 39–41, 59, 378, 453, 487, 531, 532 autism ...................................................3, 13, 65, 66, 439 mood disorders .....................................13, 118, 399, 400 schizophrenia ......................................... 3, 4, 7, 9, 11–13, 15–17, 39, 165, 232, 438–440, 445–451, 541–549, 568, 569, 580–582, 585–587, 598, 599

PSYCHIATRIC DISORDERS 609 Index Psychostimulants amphetamine ............................... 74, 136, 156, 172, 179, 185, 186, 259, 327, 354, 582 cocaine ..................................... 35, 36, 42, 247, 250, 259, 279–301, 303–318, 321–327, 354, 407–409, 417, 488, 568, 582 methamphetamine ...........................35, 76, 87, 269–277, 450, 506, 508, 515 PTSD. See Posttraumatic stress disorder

Q Q-TOF-MS/MS ..................................................... 513, 525 Qualitative ................................... 49–60, 171, 497, 572, 577, 581, 595 Quantitative......................................... 49–60, 340, 454, 457, 487–502, 569, 573, 577, 599 proteomics ..........................................483, 531–538, 563

R Rats............................... 8, 35, 59, 68, 86, 104, 126, 145, 156, 166, 177, 194, 206, 231–240, 243–254, 258, 270, 279–301, 303–318, 323, 331, 352, 368, 377, 400, 435, 446, 457, 472, 505, 542, 552 Reinforcer ...............................35, 90, 99, 247, 249, 250, 253, 260, 285, 291, 299, 309, 317, 352 Reinforcing efficacy ......................................................... 303 Reinforcing strength ........................................................ 303 Reliability ...................................... 5, 6, 9, 34, 37–39, 50, 53, 54, 121, 132, 133, 159, 189, 326, 570 Repeated .......................................... 8, 33, 34, 38, 40, 72, 73, 112, 121, 135, 137, 149–151, 156, 157, 160, 166, 171–173, 179, 187, 205, 206, 208, 220, 222, 228, 262, 263, 267, 270, 272, 274, 276, 322, 324–326, 330, 340, 354, 389, 410, 436, 448, 451, 455, 460, 494, 495, 548 Research domain criteria (RdoC) .......................... 10–11, 16 Reserpine reversal test ............................................. 116–117 Reverse transcriptase-coupled PCR (RT-PCR) ..... 506, 510, 521, 544, 547 Reward ........................................ 6, 7, 10, 33–39, 86–96, 98, 99, 120, 165, 166, 169, 170, 174, 175, 206, 244, 245, 247–249, 258–260, 263, 264, 277, 352, 353, 399, 400, 405–408, 417, 418, 421, 472 Risk................................................ 6–13, 16, 19–21, 86, 104, 136, 155, 165–175, 179, 211, 218, 219, 231, 232, 330, 351, 360, 380, 402, 410, 411, 413, 421, 422, 445, 446, 454, 456, 457, 460, 582 Risky decision making ............................................. 165–175 Rodent... ............................................ 6, 8, 12, 15–19, 35, 38, 40, 85–99, 104, 105, 109, 112, 113, 125, 135, 145, 147, 149–151, 161, 165–175, 177–190, 206, 207, 209, 218, 222, 226–228, 232–239, 244, 245, 247, 252, 253, 258, 293, 321–327, 330, 331, 334, 354, 355, 357–360, 367, 369–371, 373, 374, 379, 381,

400–406, 409, 411, 414, 419, 421, 435, 437, 445–451, 541

S S-100β.............................................................................. 456 SD rats. See Sprague–Dawley (SD) rats Second-hand smoke (SHS) ............................. 257, 329–346 Seizures..............211–212, 217, 218, 220–223, 286, 599, 600 Self-administration ................................34–36, 42, 237, 239, 244–253, 260, 272, 273, 275, 279–301, 303–318, 326, 331 Self-injurious behaviour (SIB)..................... 65–76, 155–161 Seligman, M.E.P.......................................................... 58, 59 Sensitization .............................. 44, 189, 206, 217, 220–221, 322–325, 327, 352, 354, 420 Sensory-motor ................................................. 148, 184, 188 Septohippocampal system ....................................... 433–440 Serum amyloid A ............................................................ 456 SHS. See Second-hand smoke SIB. See Self-injurious behaviour SimCell® ................................................................. 579, 580 Simulink® ........................................................................ 579 SMA. See Spontaneous motor activity Social interaction test ...........................39, 59, 134, 137–138 Soluble P-selectin concentration ..................................... 456 Somatic signs of withdrawal .................................... 257–267 Spatial discrimination .............................................. 147–149 Spatial water maze (SWM) ............................. 145–147, 149 Spectral counting ......................................474, 478–481, 484 Spontaneous motor activity (SMA)................. 506, 508, 515 Sprague–Dawley (SD) rats ..............................126, 139, 157, 174, 232, 234, 246, 250, 274, 323, 331, 334, 357, 359, 361, 368, 450, 472 Stable isotope labeling with amino acids in cell culture (SILAC) .................................... 551–564 Startle responses .............................................. 449, 450, 456 Step-down passive avoidance test .................................... 114 Step-through passive avoidance test ........................ 114–115 Stimulant ................................. 120, 136, 258, 269, 292, 322, 406–408, 417, 421, 598 Strain............................................... 41, 67, 91, 97, 120, 126, 130–132, 134, 135, 137–139, 146, 157, 174, 177, 178, 180, 186, 187, 232, 234, 236, 244–246, 252, 276, 368, 369, 371, 373, 374, 379–382, 411, 446, 447, 449, 483, 508 Stress.... ......................................6, 36, 59, 67, 104, 127, 145, 171, 189, 200, 217, 239, 251, 258, 270, 330, 355, 373, 389, 413, 445, 453–465, 487, 538, 551 Striatum..................................10, 66, 68, 197, 199, 200, 270, 331, 419, 436, 439, 483, 490, 507, 516, 521 Subcortical circuitry........................................................... 31 Substance abuse ................................... 7, 9, 11, 39, 243, 351, 454, 471 Sucrose preference test .....................110, 111, 134, 136–138

PSYCHIATRIC DISORDERS: METHODS AND PROTOCOLS 610 Index SWM. See Spatial water maze Synaptic transmission .........................44, 445, 571, 582–584 Systems biology ....................................................... 567–589 Systems neuropsychiatry.......................................... 571–577

T Tail suspension test (TST) .........................37, 106, 221, 533 Tardive dyskinesia (TD) .......................................... 193–200 T cell phenotypes ............................................................ 455 TD. See Tardive dyskinesia Δ9-Tetrahydrocannabinol (THC) ...................... 35, 231–240 The chronic caffeine model ............................................... 71 The environmental deprivation model ............ 68, 70–71, 73 The pemoline model ..............................71–73, 76, 155–161 Threshold procedures ...................................... 262, 303–318 Thyroid hormone ............................................................ 456 Titration .................................. 221, 289, 290, 304, 310, 314, 316, 317 TMAB isotopic tags. See Trimethylammoniumbutyryl (TMAB) isotopic tags Tobacco ..................................... 58, 232, 243, 244, 251–254, 257–259, 329–346 Toxicity ....................................................116, 234, 273, 276, 292, 293, 301, 551 Transcriptomics ........................................505–529, 573, 574 Tree mining ..................................................................... 600 Trimethylammoniumbutyryl (TMAB) isotopic tags ..................................488, 489, 491–502 TST. See Tail suspension test

Two-dimensional gel electrophoresis (2D-GE) .............................................472, 506, 507, 511–513, 522, 523, 527, 532

U Ultrasonic vocalization(USV)...................210, 217, 354, 533 Unconditioned stimulus (UCS) ................................. 58, 107

V Validity ................................................ 3–5, 8, 13, 15–18, 21, 32–43, 50, 53, 60, 110, 112, 156, 178, 226, 239, 379–380, 569, 570 V-cell.... ................................................................... 579, 580 Vensim ..................................................................... 578, 579 Visual discrimination reversal learning (VDRL) task ..................................87, 89–91, 95–97

W WFS1 gene...................................................................... 456 White blood cell count .................................................... 455 Wig........................................... 506–508, 515, 517, 524, 527 Withdrawal ............................................... 35, 36, 38, 40, 43, 110, 189, 205, 206, 210–212, 217–221, 223, 226–228, 244, 252, 257–267, 286, 322, 331, 352, 354, 355, 361, 403, 406, 417

Y Yohimbine toxicity potentiation test................................ 116

Psychiatric Disorders: Methods and Protocols

Hemoglobin Disorders. Molecular Methods and Protocols

Psychiatric Disorders - Trends and Developments

Psychiatric Disorders and Diabetes Mellitus

Biomarkers for Psychiatric Disorders

Hemoglobin Disorders: Molecular Methods and Protocols (Methods in Molecular Medicine)

Psychiatric Genetics. Methods and Reviews

Memory Disorders in Psychiatric Practice

Psychiatric and Cognitive Disorders in Parkinson's Disease

Psychiatric and Cognitive Disorders in Parkinson's Disease

Dopamine and Glutamate in Psychiatric Disorders

Estrogen Effects in Psychiatric Disorders

Calpain Methods and Protocols

Neurodegeneration Methods and Protocols

Mitosis Methods and Protocols

Proteomics: Methods and Protocols

Glycomics: Methods and Protocols

Immunocytochemical Methods and Protocols

Immunotoxin Methods and Protocols

Immunocytochemical Methods and Protocols

Cytoskeleton Methods and Protocols

Drosophila. Methods and Protocols

Biofuels. Methods and Protocols

Nuclease Methods and Protocols

Connexin Methods and Protocols

Lipidomics: Methods and Protocols

Bioluminescence Methods and Protocols

Polyamines: Methods and Protocols

Complement Methods and Protocols

Connexin Methods and Protocols

Bioluminescence. Methods and Protocols

Psychiatric Disorders: Methods and Protocols

Hemoglobin Disorders. Molecular Methods and Protocols

Psychiatric Disorders - Trends and Developments

Psychiatric Disorders and Diabetes Mellitus

Biomarkers for Psychiatric Disorders

Hemoglobin Disorders: Molecular Methods and Protocols (Methods in Molecular Medicine)

Psychiatric Genetics. Methods and Reviews

Memory Disorders in Psychiatric Practice

Psychiatric and Cognitive Disorders in Parkinson's Disease

Psychiatric and Cognitive Disorders in Parkinson's Disease

Dopamine and Glutamate in Psychiatric Disorders

Estrogen Effects in Psychiatric Disorders

Calpain Methods and Protocols

Neurodegeneration Methods and Protocols

Mitosis Methods and Protocols

Proteomics: Methods and Protocols

Glycomics: Methods and Protocols

Immunocytochemical Methods and Protocols

Immunotoxin Methods and Protocols

Immunocytochemical Methods and Protocols

Cytoskeleton Methods and Protocols

Drosophila. Methods and Protocols

Biofuels. Methods and Protocols

Nuclease Methods and Protocols

Connexin Methods and Protocols

Lipidomics: Methods and Protocols

Bioluminescence Methods and Protocols

Polyamines: Methods and Protocols

Complement Methods and Protocols

Connexin Methods and Protocols

Bioluminescence. Methods and Protocols

Recommend Documents