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Contributors
Robert A. Adler, Hunter Holmes McGuire VA Medical Center and Virginia Commonwealth University School of Medicine, Richmond, VA, USA
of Internal Medicine, Katholieke Universiteit Leuven, Leuven, Belgium Adele L. Boskey, Starr Chair in Mineralized Tissue Research and Director, Musculoskeletal Integrity Program, Hospital for Special Surgery, New York; Professor of Biochemistry, Weill Medical College of Cornell University; Professor, Field of Physiology, Biophysics and Systems Biology, Graduate School of Medical Sciences of Weill Medical College of Cornell University; Professor, Field of Biomedical Engineering, Sibley School, Cornell Ithaca; Adjunct Professor, School of Engineering, City College of New York, NY, USA
Matthew R. Allen, Departments of Anatomy and Cell Biology, Indiana University School of Medicine, Indianapolis, IN, USA Shreyasee Amin, Division of Rheumatology, College of Medicine, Mayo Clinic, Rochester, MN, USA Diana M. Antoniucci, University of California, San Francisco; Physicians Foundation of California Pacific Medical Center, Division of Endocrinology, Diabetes and Osteoporosis, San Francisco, CA, USA
Roger Bouillon, Laboratory of Experimental Medicine and Endocrinology (LEGENDO), Katholieke Univeriteit Leuven (KUL), Leuven, Belgium
Andre B. Araujo, New England Research Institutes, Inc., Watertown, MA, USA
David B. Burr, Departments of Anatomy and Cell Biology and Orthopaedic Surgery, Indiana University School of Medicine; Department of Biomedical Engineering, IUPUI, Indianapolis, IN, USA
Laura A.G. Armas, Creighton University Osteoporosis Research Center, Omaha, NE, USA
Melonie Burrows, Department of Orthopaedics, University of British Columbia; Centre for Hip Health and Mobility, Vancouver, Canada
Giampiero I. Baroncelli, Department of Obstetrics, Gynecology and Pediatrics, 2nd Pediatric Unit, ‘S. Chiara’ Hospital, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
Filip Callewaert, Center for Musculoskeletal Research, Leuven University Department of Experimental Medicine, Katholieke Universiteit Leuven, Leuven, Belgium
Silvano Bertelloni, Department of Obstetrics, Gynecology and Pediatrics, 2nd Pediatric Unit, ‘S. Chiara’ Hospital, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
Geert Carmeliet, Laboratory of Experimental Medicine and Endocrinology (LEGENDO), Katholieke Univeriteit Leuven (KUL), Leuven, Belgium
Shalender Bhasin, Section of Endocrinology, Diabetes and Nutrition, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA
Luisella Cianferotti, Department of Endocrinology and Metabolism, University of Pisa, Pisa, Italy
John P. Bilezikian, Department of Medicine, Division of Endocrinology, Metabolic Bone Diseases Unit, College of Physicians and Surgeons, Columbia University, New York, NY, USA
Juliet Compston, University of Cambridge School of Clinical Medicine, Cambridge, UK Felicia Cosman, Regional Bone Center Helen Hayes Hospital, West Haverstraw, New York; Department of Medicine, Division of Endocrinology, Metabolic Bone Diseases Unit, College of Physi cians and Surgeons, Columbia University, New York, NY, USA
Neil C. Binkley, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA Steven Boonen, Center for Musculoskeletal Research, Department of Experimental Medicine, Katholieke Division of Geriatric Medicine, Leuven University Hospital, Department
Serge Cremers, Division of Endocrinology, Department of Medicine, Columbia University, New York, NY, USA
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Contributors
K. Shawn Davison, Laval University, Quebec City, PQ, Canada David W. Dempster, Department of Pathology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
Deborah T. Gold, Duke University Medical Center, Durham, NC, USA X. Edward Guo, Department of Biomedical Engineering, Columbia University, New York, NY, USA
John A. Eisman, Bone and Mineral Research Program, Garvan Institute of Medical Research; University of New South Wales; St Vincent’s Hospital, Sydney, NSW, Australia
Patrick Haentjens, Center for Outcomes Research, University Hospital Brussels, Vrije Universiteit Brussel, Brussels, Belgium
Ghada El-Hajj Fuleihan, Calcium Metabolism and Osteo porosis Program, American University of Beirut Medical Center, Beirut, Lebanon
Johan Halse, Department of Endocrinology and Internal Medicine, Aker University Hospital, Oslo; Spesialistsenteret Pilestredet Park, Oslo, Norway
Erik Fink Eriksen, Department of Endocrinology and Internal Medicine, Aker University Hospital, Oslo; Spesialistsenteret Pilestredet Park, Oslo, Norway
David J. Handelsman, Department of Andrology, ANZAC Research Institute, Concord Hospital, University of Sydney, Sydney, NSW, Australia
Murray J. Favus, Section of Endocrinology, Diabetes, and Metabolism, University of Chicago, Chicago, IL, USA
Elizabeth M. Haney, Oregon Health and Science University, Portland, OR, USA
Dieter Felsenberg, Zentrum Muskel- & Knochenforschung, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Freie Universität & Humboldt-Universität Berlin, Berlin, Germany Serge Ferrari, Service of Bone Diseases, Department of Rehabilitation and Geriatrics, WHO Collaborating Center for Osteoporosis Prevention, Geneva University Hospital, Geneva, Switzerland David P. Fyhrie, David Linn Chair of Orthopaedic Surgery, Lawrence J. Ellison Musculoskeletal Research Center, Department of Orthopaedic Surgery, The University of California, Davis; The Orthopaedic Research Laboratories, Sacramento, CA, USA Patrick Garnero, INSERM Research unit 664 and Synarc, Lyon, France
David A. Hanley, University of Calgary, Calgary, AB, Canada Robert P. Heaney, Creighton University Osteoporosis Research Center, Omaha, NE, USA Ravi Jasuja, Section of Endocrinology, Diabetes and Nutrition, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA Helena Johansson, WHO Collaborating Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield, UK John A. Kanis, WHO Collaborating Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield, UK
Luigi Gennari, Deparment of Internal Medicine, Endocrine, Metabolic Sciences, and Biochemistry, University of Siena, Italy
Jean-Marc Kaufman, Ghent University Hospital, Department of Endocrinology and Unit for Osteoporosis and Metabolic Bone Diseases, Gent, Belgium
Piet Geusens, Department of Internal Medicine, Subdivision of Rheumatology, Maastricht University Medical Center, Maastricht, The Netherlands; Biomedical Research Institute, University Hasselt, Belgium
Robert Klein, Bone and Mineral Unit, Oregon Health & Science University and Portland VA Medical Center, Portland, OR, USA
Vicente Gilsanz, Director, Childrens Imaging Research Program, Childrens Hospital Los Angeles, Professor of Radiology and Pediatrics, University of Southern California, Los Angeles, CA, USA Monica Girotra, Memorial Sloan-Kettering Cancer Center; Joan and Sanford I. Weill Medical College of Cornell University, New York, NY, USA Andrea Giusti, Department of Gerontology & Musculo Skeletal Sciences, Galliera Hospital, Genoa, Italy
Stavroula Kousteni, Division of Endocrinology, Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY, USA Diane Krueger, University of Wisconsin, Madison, WI, USA Kishore M. Lakshman, Section of Endocrinology, Dia betes, and Nutrition, Division of Endocrinology & Metabolism, Boston University School of Medicine, Boston Medical Center, Boston, MA, USA
Andrea Giustina, Department of Endocrinology & Metabolic Diseases, Leiden University Medical Center, Leiden, The Netherlands
Thomas F. Lang, Professor in Residence, Department of Radiology and Biomedical Imaging, and Joint Bioengineering Graduate Group, University of California, San Francisco, San Francisco, CA, USA
Stefan Goemaere, Ghent University Hospital, Department of Endocrinology and Unit for Osteoporosis and Metabolic Bone Diseases, Gent, Belgium
Bruno Lapauw, Ghent University Hospital, Department of Endocrinology and Unit for Osteoporosis and Metabolic Bone Diseases, Gent, Belgium
Contributors Joan M. Lappe, Creighton University Osteoporosis Research Center, Omaha, NE, USA Benjamin Z. Leder, Endocrine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Willem Lems, Department of Rheumatology, Vrije Universiteit Amsterdam; VU Medisch Centrum, Amsterdam, The Netherlands X. Sherry Liu, Departments of Medicine and Biomedical Engineering, College of Physicians and Surgeons, Columbia University, New York, NY, USA Shi S. Lu, Regional Bone Center, Helen Hayes Hospital, West Haverstraw, New York, NY, USA Heather M. Macdonald, Schulich School of Engineering, University of Calgary, Calgary, Canada Christa Maes, Laboratory of Experimental Medicine and Endocrinology (LEGENDO), Katholieke Universiteit Leuven (KUL), Leuven, Belgium Ann E Maloney, Maine Medical Center Research Institute, Scarborough, ME, USA Peggy Mannen Cawthon, San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA Claudio Marcocci, Department of Endocrinology and Metabolism, University of Pisa, Pisa, Italy Lynn Marshall, Department of Medicine, Bone and Mineral Unit, Department of Public Health and Preventive Medicine, Oregon Health & Science University, Portland, OR, USA Gherardo Mazziotti, Department of Medical and Surgical Sciences, University of Brescia, Italy Eugene V. McCloskey, WHO Collaborating Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield, UK Heather A. McKay, Department of Orthopaedics, University of British Columbia; Centre for Hip Health and Mobility; Department of Family Practice, University of British Columbia, Vancouver, Canada Christian Meier, Division of Endocrinology, Diabetes and Clinical Nutrition, University Hospital Basel, Basel, Switzerland Paul D. Miller, University of Colorado Health Sciences Center, Medical Director, Colorado Center for Bone Research, Lakewood, CO, USA Bismruta Misra, College of Physicians and Surgeons, Columbia University, New York, NY, USA
xi
Stefano Mora, Departments of Radiology and Pediatrics, Childrens Hospital Los Angeles, Los Angeles, California, USA; Laboratory of Pediatric Endocrinology, BoNetwork, San Raffaele Scientific Institute, Milan, Italy Tuan V. Nguyen, Bone and Mineral Research Program, Garvan Institute of Medical Research; University of New South Wales; St Vincent’s Hospital, Sydney, NSW, Australia Anders Oden, WHO Collaborating Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield, UK Claes Ohlsson, Center for Bone Research, Department of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden Terence W. O’Neill, Epidemiology arc Unit, University of Manchester, Manchester, UK Eric S. Orwoll, Bone and Mineral Unit, Oregon Health & Science University, Portland, OR, USA Socrates E. Papapoulos, Department of Endocrinology & Metabolic Diseases, Leiden University Medical Center, Leiden, The Netherlands René Rizzoli, Division of Bone Diseases [WHO Collaborating Center for Osteoporosis Prevention] Department of Rehabilitation and Geriatrics, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland Clifford J. Rosen, Maine Medical Center Research Institute, Scarborough, ME, USA Martin Runge, Aerpah Clinic Esslingen, Esslingen, Germany John T. Schousboe, Park Nicollet Health Services, Minneapolis; Division of Health Policy & Management, School of Public Health, University of Minnesota, MN, USA Ego Seeman, Endocrine Centre, Heidelberg Repatriation Hospital/Austin Health, Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia Markus J. Seibel, Bone Research Program, ANZAC Research Institute, The University of Sydney, Sydney, NSW, Australia Deborah E. Sellmeyer, Metabolic Bone Center, The Johns Hopkins Bayview Medical Center, Baltimore, MD, USA Elizabeth Shane, Columbia University College of Physi cians & Surgeons, New York, NY, USA Jay R. Shapiro, Bone and Osteogenesis Imperfecta Programs, Kennedy Krieger Institute; Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, MD, USA Shonni J. Silverberg, Division of Endocrinology, Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY, USA
xii
Contributors
Stuart L. Silverman, Cedars-Sinai/UCLA and the OMC Clinical Research Center, Los Angeles, CA, USA Rajan Singh, Section of Endocrinology, Diabetes and Nutrition, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA Emily M. Stein, Columbia University College of Physicians & Surgeons, New York, NY, USA Thomas W. Storer, Section of Endocrinology, Diabetes and Nutrition, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA Pawel Szulc, INSERM Research Unit 831, Hôspital Edouard Heriot, Lyon, France Mahmoud Tabbal, Calcium Metabolism and Osteoporosis Program, American University of Beirut Medical Center, Beirut, Lebanon Youri Taes, Ghent University Hospital, Department of Endocrinology and Unit for Osteoporosis and Metabolic Bone Diseases, Gent, Belgium Charles H. Turner, Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis; Department of Biomedical Engineering, IUPUI, IN, USA Liesbeth Vandenput, Center for Bone Research, Department of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden Dirk Vanderschueren, Center for Musculoskeletal Research, Leuven University Department of Experimental Medicine, Katholieke Universiteit Leuven, Leuven, Belgium
Katrien Venken, Center for Musculoskeletal Research, Leuven University Department of Experimental Medicine, Katholieke Universiteit Leuven, Leuven, Belgium Lieve Verlinden, Laboratory of Experimental Medicine and Endocrinology (LEGENDO), Katholieke Universiteit Leuven (KUL), Leuven, Belgium Annemieke Verstuyf, Laboratory of Experimental Medicine and Endocrinology (LEGENDO), Katholieke Universiteit Leuven (KUL), Leuven, Belgium Qingju Wang, Endocrine Centre, Heidelberg Repatriation Hospital/Austin Health, Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia Connie M. Weaver, Department of Foods and Nutrition, Purdue University, West Lafayette, IN, USA Felix W. Wehrli, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA Sunil J. Wimalawansa, Professor of Medicine, Endo crinology & Metabolism; Director, Regional Osteoporosis Center, Department of Medicine, Robert Wood Johnson Medical School, New Brunswick, NJ, USA Kristine M. Wiren, Bone and Mineral Unit, Oregon Health & Science University; Portland VA Medical Center, Portland, OR, USA Roger Zebaze, Department of Endocrinology and Medicine, Austin Health, University of Melbourne, Melbourne, Victoria, Australia Hua Zhou, Regional Bone Center, Helen Hayes Hospital, West Haverstraw, New York, NY, USA
Foreword
The field of osteoporosis has grown enormously over the last 4 decades, with a focus upon the issues that relate to skeletal health in women. It was only about 15 years ago that the scientific community began to acknowledge that osteoporosis in men is also important. The first edition of Osteoporosis in Men, published in 2001, was a seminal event in that it called attention to the problem in an organized series of articles on male skeletal health and bone loss. Now, with this second edition of Osteoporosis in Men, further progress in this area is emphasized with particular emphasis on new knowledge that has appeared during the last decade. Osteoporosis in men is heterogeneous with many etiologies to consider besides the well known roles of aging (Sections 1-4) and sex steroids (Sections 6-8). The roots of the problem in some individuals can be back dated to the pre-pubertal and pubertal growth periods that determine the acquisition of peak bone mass. In addition, Osteoporosis in Men, second edition, deals exhaustively with important clinical issues. Nutritional considerations, the clinical and economic burden of fragility fractures, and diagnostic approaches are particularly strong aspects of the text (Sections 5, 7, 9). These chapters transcend, in part, the specific focus of the volume, making it a useful resource and a valuable reference for an audience not necessarily well-informed in bone and mineral disorders. The last section of Osteoporosis in Men, second edition, highlights therapeutic approaches. Treatment options are less well defined in men than in women because virtually all of the clinical trials involving men have been much smaller and
shorter in duration with surrogate, instead of fracture, endpoints. With this smaller database, it nevertheless appears that men respond to available pharmacological approaches to osteoporosis in a similar manner to women (Section 10). Available clinical data support the efficacy of these therapies in men with both primary and secondary osteoporosis. Finally, Osteoporosis in Men, second edition provides a view of the future, underscoring a number of unresolved issues to be included in the agenda for future research in this area. These include discussions related to an appropriate BMD-based definition for male osteoporosis, a further understanding of the factors implicated in age-related bone loss and idiopathic osteoporosis in men, and randomized-controlled studies directly assessing fracture risk reduction, particularly for non vertebral fracture. In all these areas, more definitive information is needed. This thorough and comprehensive book integrates new, accessible and informative material in the field. It will help investigators, as well as practitioners and students, to improve their understanding of male skeletal health and bone loss. The additional knowledge, assembled in such a readable manner, should help us achieve one of our ultimate goals-better care of men with osteoporosis. Gerolamo Bianchi, MD Department of Locomotor System Division of Rheumatology Azienda Sanitaria Genovese Genova, Italy
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Preface to the Second Edition
The first edition of Osteoporosis in Men was published in 1999, about 15 years after the earliest publications on the subject. Over the past decade, we have witnessed a surge of further interest in the subject of male osteoporosis. This second edition of Osteoporosis in Men is, thus, timely. In the second edition, we have made major additions to reflect increased areas of new knowledge, including genetics and inherited disorders. Previous topics are updated and extended to make them timely also. New topics include:
The increased scope of the book is the result of contributions from prominent experts in the field, including many who contributed chapters to the first edition. New authors also have provided novel insights for the second edition. Editorial responsibilities were shared by the three of us. As was the goal before, Osteoporosis in Men, Second Edition, is meant to be useful to a broad audience, including students of the field as well as those already knowledgeable. We have sought to summarize a compendium of information intersecting general and specific areas of interest. This volume will make apparent that information available concerning osteoporosis in men still lags behind what we know about osteoporosis in women. On the other hand, major advances in our understanding of the male skeleton in health and in disease are being translated into practical approaches to their clinical management. We hope this second edition provides a valuable reference source for you and that it also will serve to stimulate further advances in the field.
Important basic processes including bone biochemistry and remodeling Mechanical properties and structure Genetics and inherited disorders Growth and puberty Nutrition, including calcium, vitamin D, protein and other factors Sex steroids in muscle and bone Assessment of bone using DXA, CT, ultrasound, biochemical markers Sarcopenia and frailty Diagnostic approaches Treatment approaches including bisphosphonates, parathyroid hormone, androgens and SARMS and newer agents.
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Eric Orwoll Portland, Oregon
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John Bilezikian New York, New York
A key element of the book continues to be sex differences in bone biology and pathophysiology that can inform our understanding of osteoporosis in both men and women.
Dirk Vanderschueren Leuven, Belgium
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Chapter
1
The Biochemistry of Bone: Composition and Organization Adele L Boskey Starr Chair in Mineralized Tissue Research and Director, Musculoskeletal Integrity Program, Hospital for Special Surgery, New York; Professor of Biochemistry, Weill Medical College of Cornell University; Professor, Field of Physiology, Biophysics and Systems Biology, Graduate School of Medical Sciences of Weill Medical College of Cornell University; Professor, Field of Biomedical Engineering, Sibley School, Cornell Ithaca; Adjunct Professor, School of Engineering, City College of New York, USA
Introduction
tubular (long and short) bones such as the femur and digits, respectively, and the flat bones, such as the calvaria in the skull. Slightly better resolved, at the millimeter level, are the components of the bones, the cortices that surround the marrow cavity, the cancellous bone within the marrow cavity, the marrow cavity itself, the cartilaginous ends, etc. At the micrometer to millimeter level are the individual interconnecting struts of the trabeculae, the lamellae and the osteons that surround the vascular canals. The cells and the composite matrices also can be visualized as part of this microstructure. Finally, at the nanometer level, bone consists of an organic matrix made mainly from collagen fibrils and noncollagenous proteins, lipids, nanometer size mineral crystals (discussed below) and water. There is also heterogeneity in both the size of the collagen fibrils and the composition and sizes of the crystals deposited on this matrix [3, 4]. This heterogeneity is important for the mechanical competence of the tissue [5]. To understand the process of mineralization, knowledge of the cells and the extracellular matrices of bone is required.
As detailed throughout this book, osteoporosis is characterized by increased risk of fracture due to changes in the ‘quality’ of bone [1]. To appreciate why bone becomes weaker or less resilient to fracture with age in both men and women and in individuals of different races, a general knowledge of bone development and age-dependent changes is necessary. In line with the theme of this book, it is noted that there are both age- and sex-dependent differences in bone properties and composition, some related to the rate at which bones develop in boys and girls, some related to the impact of genes on the X-chromosome which produce proteins important for bone development and/or metabolism and some due to the direct effect of sex steroids on bone cells [2]. To appreciate the discrete differences between bone structure and composition in men and women this chapter reviews the basics of bone composition and organization and the mineralization process from the point of view of sexual dimorphism, where such differences between men and women are recognized. Emphasis is placed on those factors that contribute to bone strength; geometry, architecture, mineralization, the nature of the organic matrix and tissue heterogeneity.
Bone Cells Within the bone matrix are the cells that are responsible for bone formation and bone turnover. Three key cells are of mesenchymal origin – chondrocytes, osteoblasts and osteocytes. The chondrocytes that form cartilage within the epiphysial growth plates produce a matrix that can be mineralized, regulate the flux of ions that facilitate the mineralization of that matrix and orchestrate the remodeling of that matrix and its replacement by bone [6]. The other mesenchymal derived bone cells are the osteoblasts and osteocytes [7]. As seen in the electron micrograph in Figure 1.1,
Bone organization Bone Heterogeneity The structure of bone appears different depending on the scale at which it is examined. At the centimeter level, whole bone can be viewed as an organ, for example, the Osteoporosis in Men
Copyright 2009, 2010 Elsevier, Inc. All rights of reproduction in any form reserved.
Osteoporosis in Men
Osteoclasts
Osteoblast
Bone 50 Microns
0.5 µm
Osteocyte
Figure 1.1 Transmission electron micrograph showing osteoblasts lining the bone surface in an adult male Sprague-Dawley rat. Inside the bone are the osteocytes, connected to one another by canaliculae. The banded pattern of the collagen is also visible. Magnification is marked on the figure. Courtesy of Dr Stephen B. Doty, Hospital for Special Surgery, New York.
osteoblasts line the surface of the mineralized bone. They synthesize new matrix and regulate the mineralization and turnover of that matrix. Once these osteoblasts become engulfed in mineral they become osteocytes and connect with one another by long processes (canaliculae) (see Figure 1.1). The osteocytes are the cells that sense mechanical signals and then convey them through the matrix. Osteocytes produce many of the same proteins as osteoblasts, but the relative concentrations of these proteins are not the same and the ways in which these cells use regulatory pathways differ. As reviewed in detail elsewhere [8], the osteoblasts use the WNT/beta-catenin pathway [9] to regulate synthesis of new bone; the osteocytes use the WNT/beta-catenin pathway to convey mechanical signals. Osteoblasts synthesize more alkaline phosphatase, more type I collagen and more bone sialoprotein than osteocytes, while osteocytes specifically produce sclerostin, a glycoprotein that is a WNT and BMP antagonist, and produce high levels of dentin matrix protein 1 [8]. Sclerostin, an osteocytes specific protein, inhibits osteoblast differentiation and, based on the significant increase in bone mineral density in the sclerostin knockout mouse [10], is believed to be important in determining the high bone mass phenotype [11]. This increase in bone mass was noted to be comparable for both sexes [10]. There is sexual dimorphism in the density of osteocytes, as females gain osteoclast lacunar density with increasing age, while males show a decrease in this parameter [12]. This may explain why bone loss in women results in a decrease
Figure 1.2 Transmission electron micrograph of an osteoclast on the bone surface of a 70-year-old woman. The ruffled borders sealing the cell to the mineralized surface are indicated along with the magnification. Courtesy of Dr Stephen B. Doty, Hospital for Special Surgery, New York.
in trabecular number, while in males there is a thinning of trabeculae [13]. Some of the other functions of osteoblasts and osteocyte proteins will be discussed later. The cells responsible for the turnover of bone, the osteoclasts, are of hematologic and macrophage origin [14]. As seen in the electron micrograph in Figure 1.2, these multinucleated giant cells attach to the surface of the bone via a ‘ruffled border’. They receive signals from osteoblasts that control bone remodeling and regulate the turnover of the mineralized matrix. They remove bone by producing acid and couple that with the transport of chloride out of the cell. The acid dissolves the mineral (see below) and, after the mineral is removed, release proteolytic enzymes that degrade the matrix. During the dissolution of the matrix, signaling molecules communicate with the osteoblasts and new bone formation is triggered. Androgens and estrogens inhibit osteoclast activity to different extents [15] explaining some of the sexual dimorphism in osteoclast activity. There are a number of other cells in bone, marrow stromal cells, pericytes, vascular endothelial cells, fibroblasts, etc that function as stem cells [16] but their properties are beyond the scope of this chapter and will not be discussed here.
Skeletal Development The shapes of male and female adult bones are different and, for archeologists, form the basis for the identification of sexes in skeletal remains [17]. The early development of the skeleton contributes markedly to these sexual differences. During development, bone structure changes in length and width and there is a concomitant alteration in tissue density, resulting in a bone that is optimally designed to bear the loads imposed on it [18]. In the long and short tubular bones, endochondral
C h a p t e r 1 The Biochemistry of Bone: Composition and Organization l
ossification, in which a cartilage model becomes calcified and is replaced by bone, provides the basis for longitudinal growth, while widening of the bones takes place by apposition on already formed bone in the periosteum concurrent with removal of the inner (endosteal) surfaces. Endochondral ossification starts during embryogenesis and continues throughout childhood and into adolescence, peaking during the ‘growth spurt’. The rate at which changes in bone geometry occur depends on genetics, the environment and hormonal signals [19, 20]. With the exception of individuals with rare genetic mutations, the process of endochondral ossification terminates during adolescence with the closing of the growth plate. This generally occurs in girls around age 13 and in boys around age 18 [21]. In contrast, there is a report of a man who had a bone age of 15, based on bone mineral density (BMD), at age 28 and lacked closed epiphyses and had continued linear growth into adulthood due to a mutation in his estrogen-receptor alpha (ERalpha) gene [22]. His testosterone levels were reported as normal. Other related cases with abnormalities in the ability to synthesize estrogen (aromatase deficiency) had a similar phenotype, but longitudinal growth could be modulated with estrogen treatment [23]. During aging, at least in mice [24] and, most likely, in humans [25], there is a decrease of bone formation (osteogenesis) and an increase of fat cell formation (adipogenesis) in bone marrow. There is also a difference between aging patterns in bones of men and women. In general, in both sexes, bone strength is maintained by the process of remodeling, removal of bone by osteoclasts and formation of new bone by osteoblasts. These coupled processes [26] are not equivalent in men and women. Testosterone decreases this pathway in men [27], perhaps contributing to the delayed start of agedependent bone loss in males relative to females. In women, menopause-related estrogen deficiency leads to increased remodeling [28] and, with age, bone loss is accelerated and bone loss exceeds formation, causing cortices to being thinner and more porous and trabeculae to become disconnected and thinner. In men, the changes in remodeling lead to bone loss occurring later in life [29]. Concurrent bone formation on the periosteal surface during aging occurs to a greater extent in men than in women, thus diminishing some of the bone loss [30]. In a cross-sectional study of older men and women [29], men had significantly larger cross-sectional bone sizes than women which, in turn, was associated with decreased compressive strength indices at the spine, femoral neck and trochanter and bending strength indices at the femoral neck.
Bone composition: the bone composite Independent of age, state of development, race and sex, bone is a composite material consisting of mineral crystals
1.5 µm
Figure 1.3 Transmission electron micrograph of a section of bone from the tibia of an adult male mouse. The electron dense mineral crystals can be seen to lie parallel to the collagen fibril axis. Courtesy of Dr Stephen B Doty, Hospital for Special Surgery, New York.
deposited in an oriented fashion on an organic matrix. The organic matrix is predominately type I collagen, but there are also non-collagenous proteins and lipids present. The non-collagenous proteins account for a small percentage of the bone matrix, yet they are important for regulating cell– matrix interactions, matrix structure, matrix turnover and the biomineralization process. Knowledge about the functions and critical status of these proteins has come from studies of mutant animals (naturally occurring and those made by genetic manipulation), cell culture studies [31] and analyses of the proteins’ activity in the absence of cells.
The Mineral The mineral component of the bone composite is an analogue of the naturally occurring mineral hydroxyapatite. Bone hydroxyapatite is comprised of nanometer sized crystals [32]. These crystals have the approximate chemical composition Ca5(PO4)3OH but are carbonate-substituted and calcium and hydroxide deficient [33]. The individual crystals have a broad range of sizes, depending on the age of the bone and the health of the subject, but are always oriented parallel to the long fiber axis of the collagenous matrix (Figure 1.3). There is a broad distribution of the amount of mineral in the matrix, again varying with age, environment and disease. The average amount of mineral in the matrix can be measured by burning off the organic matrix (ash weight) or by radiographic measurement of density (bone mineral density or bone mineral content). There is some sexual dimorphism in the ash weight in bones of egg-laying
Osteoporosis in Men
chicks, with males having, on average, a greater mineral content in any given bone than age matched female bones [34] but, in humans of the same race, the ash content of adult male and female bones is similar [35], perhaps because there is a well defined maximum amount of mineral that can fit into the bone matrix. Only in osteomalacia and related diseases is the mineral content reduced and that occurs in both sexes. Bone mineral density measured by computed tomography, tends to be higher in males than females at each stage of life, but differences are removed when corrected for bone length and cortical thickness [29, 36, 37]. The composition of bone hydroxyapatite varies with age, diet and health due to the substitution of foreign ions and vacancies into the crystal lattice and to the absorption of these ions on the surface of the crystals. The substituted ions also have been reported to differ when male and female mouse bones are compared, although the number of such studies is limited. When attention is paid to the sex of the animal, compositional studies show differences in mineral content and composition [38]. The effects of sex steroids on bone development can explain many of these differences. For example, assessing the effects of sex hormones on bone composition Ornoy et al. [39] compared a variety of compositional parameters in gonadectomized mice treated with male and female sex steroids. While the investigators found that tibial mineral content (ash weight) was comparable in all the groups, Ca and P content increased after ovariectomy. Estradiol treatment increased mineral content and bone Ca and P in ovariectomized and in intact females and orchiectomized mice, while testosterone had smaller effects.
The Extracellular Matrix Collagen provides the oriented template or scaffold upon which these mineral crystals are deposited. The collagen is predominately type I, a triple helical collagen, with the individual chains having the amino acid sequence (X-YGly)n, where X and Y are any amino acids, often proline and hydroxyproline, and glycine is the only amino acid small enough to fit in the center of the triple helix [40]. The importance of type I collagen for the proper mineralization of the matrix is seen in the different osteogenesis imperfecta diseases, a set of diseases, reviewed elsewhere [41], caused by mutations that lead to altered quantity or quality (composition) of type I collagen and result in brittle bones. There are also other collagen types in bone, including fibrillar type III collagen and non-fibrillar type V collagens [42]. No sex dependent differences in the distribution of collagen types have been reported, however, there are differences in the non-collagenous proteins that are found associated with the collagen matrix. In the next section, these non-collagenous proteins will be presented as families, with emphasis on their roles in mineral formation and turnover and other ways in which they might affect sexual dimorphism in bone strength.
The Non-Collagenous Proteins: Gla Proteins The most abundant non-collagenous protein in vertebrates is a small protein, osteocalcin, also known as bone gla protein [40]. This small (5.7 kDa) protein has three gammacarboxy-glutamic acid residues, with a high affinity for hydroxyapatite and calcium as demonstrated by its crystal and nuclear magnetic resonance (NMR) structures [43, 44]. Osteocalcin is frequently used as a biomarker for bone formation [45], although it is also released from bone and hence can reflect remodeling rather than only formation. In studies where bone tissue osteocalcin levels and serum osteocalcin levels were compared as a function of age and sex, the levels in men exceeded those in women at all ages until age 60, when levels in women increased and then decreased, reflecting age-dependent increases in bone remodeling [46, 47]. This most likely is an estrogendetermined effect as, in the rat, estrogen treatment is associated with a decrease in osteocalcin [48]. Knockout mice lacking osteocalcin have thickened bones and, thus, it was initially suggested that osteocalcin was important for bone formation [49]. Further studies led to the suggestion that osteocalcin was important for osteoclast recruitment [50], a suggestion supported by in vitro and in vivo assays [40]. Most recently, Karsenty’s group has suggested, from studies in wildtype as well as osteocalcin knockout mice, that the uncarboxylated form of osteocalcin acts as a hormone, regulating glucose levels in cultures of pancreatic cells and in the skeleton [51]. The role of osteocalcin in glucose metabolism is suggested by the observation that osteoblastic bone formation is negatively regulated by the hormone leptin. Leptin, secreted by fat cells (adipocytes), has multiple hormonal functions including, but not limited to: appetite suppression, initiation of puberty in girls and acceleration of longitudinal bone growth in mice, although the data on bone formation have suggested a bimodal pattern [52]. In humans, a recent report showed postmenopausal women with type 2 diabetes had reduced osteocalcin levels [53]. In addition to the identification of osteocalcin as a hormone with a postulated role in metabolic syndrome, readers are reminded that the osteocalcin knockout has a bone phenotype, there is some sex specificity to osteocalcin’s action in bone [48] and polymorphisms in the osteocalcin gene have been associated with osteoporosis [54–56]. The second gamma-carboxyglutamic acid containing protein in bone (predominantly in cartilage) and in soft tissues is matrix-gla protein (MGP). MGP is a hydrophobic protein [40] containing five gamma-carboxyglutamate residues that is important for inhibition of soft tissue calcification, as can be seen in the knockout mice where, when MGP is ablated, the animals have excessive cartilage calcification, denser bones and young animals succumb to calcification of the blood vessels and esophagus [57, 58]. Both the full length protein and its component peptides can inhibit hydroxyapatite formation and growth in culture [59]. MGP is more abundant in
C h a p t e r 1 The Biochemistry of Bone: Composition and Organization l
soft tissues than in bone, hence it is not surprising that polymorphisms in MGP are not associated with bone density or fracture risk [56].
Non-Collagenous Proteins: Siblings There is a family of proteins found in bone that have been named the SIBLING proteins (small integrin binding ligand N-glycosylated) [60]. These proteins are all located on the same chromosome, all have RGD-cell binding domains, all are anionic and all are subject to multiple post-translational modifications including phosphorylation and dephosphorylation, cleavage and glycosylation [61]. Each is found in multiple tissues in addition to bone and each has signaling functions in addition to interacting with hydroxyapatite and regulating mineralization (Table 1.1). The SIBLING proteins include osteo pontin (bone sialoprotein 1), dentin matrix protein 1 (DMP1), bone sialoprotein (BSP2), matrix extracellular phosphoglycoprotein (MEPE) and the products of the dspp gene, dentin sialoprotein (DSP) and dentin phosphoprotein (DPP).
Osteopontin is the most abundant of the SIBLING proteins and has the most widespread distribution. In solution [73, 74], in a variety of cell culture systems [75, 76], in animals in which gene expression has been ablated [71] and in models of pathologic calcifications [77], bone osteopontin is an inhibitor of mineralization. When this glycoprotein is highly phosphorylated it can promote hydroxyapatite formation, most likely due to small conformational changes occurring on binding to the mineral surface [78]. Osteopontin is also involved in the recruitment of osteoclasts and in regulating the immune response [79]. Bone specific conditional knockout of osteopontin results in impaired osteoclast activity at all ages [72], but sexual dimorphism was not noted. Dentin matrix protein 1 is a synthetic product of growth plate chondrocytes and of osteocytes, although it was first cloned from dentin [40]. DMP1 is not usually found in an intact form but rather it is found as three smaller peptides, an N-terminal peptide, a C-terminal peptide and an N-terminal protein that has a glycosaminoglycan chain attached [65]. It is the only one of the SIBLING proteins to date that has been
Table 1.1 Bone non-collagenous matrix proteins* whose modification (deletion (KO) or overexpression (TG)) creates a bone phenotype Protein or gene
Genotype
Bone phenotype
Proposed function
Biglycan [62]
KO
Decreased mineral content Increased crystal size in young animals Females less affected
Regulation of mineralization
Bone sialoprotein [63]
KO
Variable
Decorin [62]
KO
Dentin matrix protein-1 [64, 65]
KO
Weaker bones Thinner collagen fibrils Impaired mineralization Altered osteocyte function
Dentin sialophosphoprotein gene (dspp) [66] Matrix gla protein [57]
KO
Initiation of mineralization Signaling Regulation of collagen fibrillogenesis Regulation of mineralization Signaling response to load Phosphate regulation Regulation of initial calcification
Matrix extracellular phosphoglycoprotein [67, 68]
KO
KO
Osteocalcin [49, 50]
TG KO
Osteonectin [69, 70]
KO Bone specific KO
Osteopontin [71, 72]
KO Bone specific KO
*
Increased collagen maturity and crystallinity in young male and female mice Excessive vascular and cartilage Prevent excessive calcification calcification Hypermineralization Regulation of PHEX activity
Hypomineralization Thicker bones, smaller crystals suggest impaired turnover Males/females differ Altered collagen maturity Decreased bone density, increased bone fragility Increased bone density, larger crystals, resistant to turnover Increased bone density
Enzymes, growth factors and cytokines that affect bone are excluded from this table.
Regulation of mineralization Regulation of bone turnover Glucose regulation Regulation of collagen fibrillogenesis Regulation of bone formation Osteoclast recruitment Inhibition of mineralization Osteoclast recruitment
Osteoporosis in Men
associated with a bone disease (autosomal hypophosphatemic rickets) [80]. The intact protein appears to inhibit mineralization, as does the glycosylated N-terminal fragment, but the phosphorylated cleaved fragments can promote mineralization [81, 82]. The knockout mouse has defective mineralization, supporting a role for DMP1 as a nucleator [64], although it appears equally important as a signaling molecule [8]. Bone sialoprotein (BSP) is a specific product of bone forming cells. There are low levels in other mineralized tissues, such as calcified cartilage and dentin. In solution, BSP is a hydroxyapatite nucleator [83, 84], implying a role in in situ mineralization. In culture, BSP facilitates osteo blast differentiation and maturation [85] and thereby stimulates mineralization. The BSP knockout is viable, but has a variable phenotype. In the youngest animals, the bones are shorter, narrower and less mineralized, supporting the in vitro findings. As the animals age, the mineralization normalizes, but the mice have impaired osteoclast activity, as they are resistant to bone loss by hind-limb suspension [63]. These data support the hypothesis that because mineralization is such an important process, it is crucial to have multiple pathways to support mineralization. BSP activity may be different in males and females as knockdown of the estrogen receptor alpha gene in a model of cartilage induced osteoarthritis resulted in decreased expression of BSP, implying some gender specificity to the expression of this protein [86] and studies in chick osteoblasts had previously demonstrated a response of BSP expression to estrogen-like molecules [87]. Matrix extracellular phosphoglycoprotein (MEPE) is made in bone, dentin and also exists in serum as smaller peptides [67]. The MEPE peptides are effective inhibitors of hydroxyapatite formation and growth, while unpublished studies show the intact protein, in phosphorylated form, promotes hydroxyapatite formation. Following gene ablation, the knockout animals have excessive mineralization while the transgenic animal, in which MEPE is overexpressed is hypomineralized [67]. This protein is one of the substrates for PHEX (phosphate regulating hormone with analogy to endopeptidase on the X-chromosome). PHEX is defective in hypophosphatemic rickets, presumably because where normally PHEX binds to MEPE and degrades its inhibitory peptides, in the mutant, this ability to degrade the peptides is absent and the inhibition persists [68]. Thus, MEPE is an important regulator of calcification. Because PHEX is on the X-chromosome, hypophosphatemic rickets is more prevalent and more severe in males than in females, although the female HYP mice have a bone phenotype, but it is less severe than that of the males [88]. Dentin sialophosphoprotein is expressed as a gene, dspp, but an intact protein has not yet been isolated. Its major components, dentin sialoprotein (DSP) and dentin phosphophoryn (DPP) are found mainly in dentin, but the gene is expressed in bone [61], and the dspp gene knockout has a detectable bone phenotype [66]. Both DSP and DPP can
regulate mineralization in vitro, thus it is not surprising that the knockout has impaired mineralization both in bone and in dentin.
Non-Collagenous Proteins: SLRPS Small leucine rich proteoglycans (SLRPS) are the major bone glycoproteins [40]. While small amounts of large aggregating proteoglycans (such as aggrecan and epiphican) are resident in bone as part of residual calcified cartilage, the majority of the bone proteoglycans are smaller. These SLRPS include decorin (the major SLRP produced by osteoblasts), biglycan, osteoadherin, lumican, fibromodulin and mimecan [89]. Each of these proteins binds to collagen and regulates collagen fibrillogenesis, thus they have an important effect on the bone composite and the mechanical strength of bone. In addition, biglycan and decorin are important for regulating cellular activity, perhaps due to the binding of growth factors, and decorin, biglycan and mimecan can regulate hydroxy apatite formation [90]. The properties and functions of these proteins in bone as adapted from these reviews are summarized in Table 1.2, while Table 1.1 includes the properties of the knockouts that had bone phenotypes.
Non-Collagenous Proteins: Matricellular Proteins Another protein family whose members are found in bone are the so-called ‘matricellular proteins’, named so because they regulate the interactions between the cells and the extracellular matrix. The members of this family found in mineralized bone (as distinct from cartilage) include: osteonectin (SPARC), the matrillins, the thrombospondins, the tenascins, the galectins, periostin and osteopontin and BSP (SIBLINGs). Each of these proteins is expressed in higher amounts during development than in adult life, but they are all upregulated during wound repair (callus formation) in the adult. As noted from studies of mice lacking these proteins, or combinations thereof, matricellular proteins affect postnatal bone structure and turnover when animals are challenged by aging, ovariectomy, mechanical loading and fracture healing regeneration but do not have a visible phenotype during normal development [96].
Non-Collagenous Proteins: Other In addition to the families of bone matrix proteins noted above, there are other extracellular matrix proteins that are found in glycosylated and phosphorylated form in bone. These include BAG-75 (which is found at the initial sites of mineralization in culture) [97], SPP24 (that regulates the formation of bone via inhibition of BMP-induced osteoblast differentiation) [98] and others proteins that serve as signaling molecules or have other functions that are still being investigated [40].
C h a p t e r 1 The Biochemistry of Bone: Composition and Organization l
Table 1.2 Small leucine rich proteoglycans (SLRPs) found in bone* Protein
Structure
Proposed functions
Biglycan
2 GAG chains/protein core
Decorin
Generally 1 GAG chain/protein core
Osteoadherin [91]
Keratan sulfate proteoglycan
Fibromodulin
4 Keratan sulfate chains in its leucine rich domain Possesses a unique stretch of aspartate residues at its N terminus Derived from bone tumor Also called osteogenic factor
Binds and releases growth factors Cell differentiation Initiates mineralization Expression depressed in patient’s with Turner’s syndrome Regulates collagen fibrillogenesis Binds and releases growth factors Facilitates osteoblast differentiation and maturation Regulates HA proliferation Regulation of collagen fibrillogenesis
Asporin [92] Osteoglycin/mimecan
Lumican
Keratan sulfate proteoglycan
Osteomodulin [93] Periostin (osteoblasts-specific factor 2) [94]
Keratan sulfate proteoglycan SLRP made in primary osteoblasts
Tsukushin [95]
353 amino acid protein upregulated by estrogen – has phosphorylation sites
Negative regulator of osteoblast maturation and mineralization Induces osteogenesis Regulation of collagen fibrillogenesis Regulation of mineralization Regulation of collagen fibrillogenesis Regulation of mineralization Regulates osteoblast maturation Regulates intramembranous bone formation Regulates collagen fibrillogenesis BMP inhibitor Regulates mineralization
*
Adapted from OMIM: On Line Mendelian Inheritance in Man: http://www.ncbi.nlm.nih.gov/sites/entrez/OMIM unless otherwise noted.
Other Matrix Components Within the extracellular matrix are other proteins including enzymes (Table 1.3), growth factors and other signaling molecules, as well as lipids that are important for regulating cell–cell communication and mineral deposition. The actions of lipids in bone are reviewed in detail elsewhere [40, 103, 104]. The importance of lipid rafts (caveolin) is seen in the caveolin knockout mouse that has increased bone density and matures more rapidly than control mice [105]. There have not yet been reports of sex-dependent differences in these mice, although lipid metabolism is different in men and women.
How bones change with age A key event in the transition from the embryo to the adult is the development of mineralized structures. The cells that deposit the matrix, regulate the flux of ions and control the interaction between the matrix components orchestrate these processes. As shown by Figure 1.3, the mineral in bone is deposited in an oriented fashion on the collagen matrix. It is widely recognized, as reviewed elsewhere [33, 40], that the collagen provides a template for mineral deposition, but the extracellular matrix proteins regulate
the sites of initial mineral deposition and control the extent to which the crystals can grow in length and in width. The collagenous matrix is mineralized to a certain extent during development (primary mineralization) and, as the individual ages, the rest of the matrix becomes mineralized (secondary mineralization). A variety of signals, discussed elsewhere in this book, activate the osteoclast to remove bone and this removal exposes stimuli that activate osteo blasts to lay down a new bone matrix, with the matrix proteins mentioned above regulating these processes. With age, the resorption process exceeds the formative one and this occurs earlier in women then in men. Mouse models in which specific matrix proteins are ablated or inserted provide information both on the sexual dimorphic responses of these proteins, but also on the age-related changes. Mice, in general, achieve their peak bone mass at 16–18 weeks of age, depending on the sex and background. Although the functions of many of these proteins are redundant, because they are so essential for the development of the animal, examining knockout and transgenic animals (see Table 1.1) and the phenotypic appearance of their bones provides clues into the activities of these proteins. The only knockouts that totally lack bone are the osterix [106] and the Runx2 knockouts [107], although the retinoblastoma tumor suppressor gene knockout has severely impaired osteogenesis [108]. The knockout
Osteoporosis in Men
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Table 1.3 Some key enzymes* involved in modifying bone structure in health and disease Enzyme
Substrate/activity
Effect on bone properties
Bone specific alkaline phosphatase [99] Hydrolyzes phosphate esters Bone morphogenetic protein 1/tolloid Cleaves matrix proteins including [100] removing pro-peptides form fibrillar collagens Cathepsin K [101] Demineralized matrix Cl-channel and ATPase [101] PHEX [67, 68] Protein kinases [31] Phosphoprotein phosphatases [31] Procollagen peptidases [48] Tartrate resistant acid phosphatase [102]
Transports Cl ions out of osteoclasts Cleaves ASARM peptides Add phosphate moieties Removes phosphate moieties Removes terminal peptides from collagen Phosphoesters
Stimulates new bone formation Modulates activity of matrix proteins – turning inhibitors into activators and vice versa preparing matrix for mineral deposition Osteoclast enzyme – when defective results in osteopetrosis When blocked get osteopetrosis Removes inhibitors of mineralization Activates some proteins/inactivates others Activates some proteins/inactivates others When defective bone fails to cross-link properly resulting in reduced mechanical strength Marker of osteoclast activity
*
Excludes enzymes involved in protein synthesis.
and overexpression of other bone proteins and ‘critical’ signaling pathways have altered bone properties but none seem to be mandatory, most likely due to the redundancy of the function of these proteins. However, from the analyses of the cell culture and altered phenotype in the animals having too little or too much of these proteins, the following can be identified as important for the formation of the mineralized matrix: type I collagen, bone sialoprotein, dentin matrix protein1, BAG-75, osteopontin, PHEX and alkaline phosphatase. The sequence in which they act is not yet clear.
Acknowledgments Dr Boskey’s data as reported in this review were supported by NIH Grants DE04141, AR037661, AR041325 and AR046121. Dr Boskey appreciates the collaboration of Dr Steven B Doty who provided the images for this chapter.
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53. J.A. Im, B.P. Yu, J.Y. Jeon, S.H. Kim, Relationship between osteocalcin and glucose metabolism in postmenopausal women, Clin. Chim. Acta. 396 (2008) 66–69. 54. A. Gustavsson, P. Nordström, R. Lorentzon, U.H. Lerner, M. Lorentzon, Osteocalcin gene polymorphism is related to bone density in healthy adolescent females, Osteoporos. Int. 11 (2000) 847–851. 55. H.Y. Chen, H.D. Tsai, W.C. Chen, J.Y. Wu, F.J. Tsai, C.H. Tsai, Relation of polymorphism in the promotor region for the human osteocalcin gene to bone mineral density and occurrence of osteoporosis in postmenopausal Chinese women in Taiwan, J. Clin. Lab. Anal. 15 (2001) 251–255. 56. J.G. Kim, S.Y. Ku, D.O. Lee, et al., Relationship of osteocalcin and matrix Gla protein gene polymorphisms to serum osteocalcin levels and bone mineral density in postmenopausal Korean women, Menopause 13 (2006) 467–473. 57. G. Luo, P. Ducy, M.D. McKee, et al., Spontaneous calcification of arteries and cartilage in mice lacking matrix GLA protein, Nature 386 (1997) 78–81. 58. M. Murshed, T. Schinke, M.D. McKee, G. Karsenty, Extracellular matrix mineralization is regulated locally; different roles of two gla-containing proteins, J. Cell Biol. 165 (2004) 625–630. 59. L.J. Schurgers, H.M. Spronk, J.N. Skepper, et al., Posttranslational modifications regulate matrix Gla protein function: importance for inhibition of vascular smooth muscle cell calcification, J. Thromb. Haemost. 5 (2007) 2503–2511. 60. N.S. Fedarko, A. Jain, A. Karadag, L.W. Fisher, Three small integrin binding ligand N-linked glycoproteins (SIBLINGs) bind and activate specific matrix metalloproteinases, FASEB J. 18 (2004) 734–736. 61. C. Qin, O. Baba, WT. Butler, Post-translational modifications of sibling proteins and their roles in osteogenesis and dentinogenesis, Crit. Rev. Oral. Biol. Med. 15 (2004) 126–136. 62. A.L. Boskey, M.F. Young, T. Kilts, K. Verdelis, Variation in mineral properties in normal and mutant bones and teeth, Cells Tissues Organs 181 (2005) 144–153. 63. L. Malaval, N.M. Wade-Guéye, M. Boudiffa, et al., Bone sialoprotein plays a functional role in bone formation and osteoclastogenesis, J. Exp. Med. 205 (2008) 1145–1153. 64. Y. Ling, H.F. Rios, E.R. Myers, Y. Lu, J.Q. Feng, A.L. Boskey, DMP1 depletion decreases bone mineralization in vivo: an FTIR imaging analysis, J. Bone Miner. Res. 20 (2005) 2169–2177. 65. C. Qin, R. D’Souza, J.Q. Feng, Dentin matrix protein 1 (DMP1): new and important roles for biomineralization and phosphate homeostasis, J. Dent. Res. 86 (2007) 1134–1141. 66. K. Verdelis, Y. Ling, T. Sreenath, et al., Dspp effects on in vivo mineralization, Bone 43 (2008) 983–990. 67. PS. Rowe, The wrickkened pathways of FGF23, MEPE and PHEX, Crit. Rev. Oral. Biol. Med. 15 (2004) 264–281. 68. W.N. Addison, Y. Nakano, T. Loisel, P. Crine, M.D. McKee, MEPE-ASARM peptides control extracellular matrix mineralization by binding to hydroxyapatite: an inhibition regulated by PHEX cleavage of ASARM, J. Bone Miner. Res. 23 (2008) 1638–1649. 69. A.L. Boskey, D.J. Moore, M. Amling, E. Canalis, A.M. Delany, Infrared analysis of the mineral and matrix in bones of osteonectin-null mice and their wildtype controls, J. Bone Miner. Res. 18 (2003) 1005–1011.
70. F.C. Mansergh, T. Wells, C. Elford, et al., Osteopenia in Sparc (osteonectin)-deficient mice: characterization of phenotypic determinants of femoral strength and changes in gene expression, Physiol. Genomics 32 (2007) 64–73. 71. A.L. Boskey, L. Spevak, E. Paschalis, S.B. Doty, M.D. McKee, Osteopontin deficiency increases mineral content and mineral crystallinity in mouse bone, Calcif. Tissues Int. 71 (2002) 145–154. 72. A. Franzén, K. Hultenby, F.P. Reinholt, P. Onnerfjord, D. Heinegård, Altered osteoclast development and function in osteopontin deficient mice, J. Orthopaed. Res. 26 (2008) 721–728. 73. A.L. Boskey, M. Maresca, W. Ullrich, S.B. Doty, W.T. Butler, C.W. Prince, Osteopontin-hydroxyapatite interactions in vitro: inhibition of hydroxyapatite formation and growth in a gelatin-gel, Bone Miner. 22 (1993) 147–159. 74. G.K. Hunter, C.L. Kyle, H.A. Goldberg, Modulation of crystal formation by bone phosphoproteins: structural specificity of the osteopontin-mediated inhibition of hydroxyapatite formation, Biochem. J. 300 (1994) 723–728. 75. S. Jono, C. Peinado, C.M. Giachelli, Phosphorylation of osteo pontin is required for inhibition of vascular smooth muscle cell calcification, J. Biol. Chem. 275 (2000) 20197–20203. 76. A.L. Boskey, S.B. Doty, V. Kudryashov, P. Mayer-Kuckuk, R. Roy, I. Binderman, Modulation of extracellular matrix protein phosphorylation alters mineralization in differentiating chick limb-bud mesenchymal cell micromass cultures, Bone 42 (2008) 1061–1071. 77. W. Jahnen-Dechent, C. Schäfer, M. Ketteler, M.D. McKee, Mineral chaperones: a role for fetuin-A and osteopontin in the inhibition and regression of pathologic calcification, J. Molec. Med. 86 (2008) 379–389. 78. A. Gericke, C. Qin, L. Spevak, et al., Importance of phosphorylation for osteopontin regulation of biomineralization, Calcif. Tissues Int. 77 (2005) 45–54. 79. M. Scatena, L. Liaw, C.M. Giachelli, Osteopontin: a multifunctional molecule regulating chronic inflammation and vascular disease, Arterioscler. Thromb. Vasc. Biol. 27 (2007) 2302–2309. 80. J.Q. Feng, L.M. Ward, S. Liu, et al., Loss of DMP1 causes rickets and osteomalacia and identifies a role for osteocytes in mineral metabolism, Nat. Genet. 38 (2006) 1310–1315. 81. G. He, S. Gajjeraman, D. Schultz, et al., Spatially and temporally controlled biomineralization is facilitated by interaction between self-assembled dentin matrix protein 1 and calcium phosphate nuclei in solution, Biochemistry 44 (2005) 16140–16148. 82. P.H. Tartaix, M. Doulaverakis, A. George, et al., In vitro effects of dentin matrix protein-1 on hydroxyapatite formation provide insights into in vivo functions, J. Biol. Chem. 279 (2004) 18115–18120. 83. G.K. Hunter, H.A. Goldberg, Nucleation of hydroxyapatite by bone sialoprotein, Proc. Natl. Acad. Sci. USA. 90 (1993) 8562–8565. 84. G.S. Baht, G.K. Hunter, H.A. Goldberg, Bone sialoproteincollagen interaction promotes hydroxyapatite nucleation, Matrix Biol. 27 (2008) 600–608. 85. J.A. Gordon, C.E. Tye, A.V. Sampaio, T.M. Underhill, G.K. Hunter, H.A. Goldberg, Bone sialoprotein expression enhances osteoblast differentiation and matrix mineralization in vitro, Bone 41 (2007) 462–473.
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86. E. Bonnelye, N. Laurin, P. Jurdic, D.A. Hart, J.E. Aubin, Estrogen receptor-related receptor-alpha (ERR-alpha) is dysregulated in inflammatory arthritis, Rheumatology (Oxf) 47 (2008) 1785–1791. 87. R. Yang, L.C. Gerstenfeld, Structural analysis and characterization of tissue and hormonal responsive expression of the avian bone sialoprotein (BSP) gene, J. Cell. Biochem. 64 (1997) 77–93. 88. A. Boskey, K. Verdelis, A. Frank, Y. Fujimoto, L. Spevak, T. Carpenter, PHEX transgene corrects mineralization defects in 9 month old hypophosphatemic mice, Calcif. Tissues Int 84 (2009) 126–127. 89. M.F. Young, Y. Bi, L. Ameye, et al., Small leucine-rich proteoglycans in the aging skeleton, J. Musculoskelet. Neuron. Interact. 6 (2006) 364–365. 90. R.J. Waddington, H.C. Roberts, R.V. Sugars, E. Schänherr, Differential roles for small leucine-rich proteoglycans in bone formation, Eur. Cells Mater. 6 (2003) 12–21. 91. A.P. Rehn, R. Cerny, R.V. Sugars, N. Kaukua, M. Wendel, Osteoadherin is upregulated by mature osteoblasts and enhances their in vitro differentiation and mineralization, Calcif. Tissues Int. 82 (2008) 454–464. 92. S. Chakraborty, J. Cheek, B. Sakthivel, B.J. Aronow, K.E. Yutzey, Shared gene expression profiles in developing heart valves and osteoblast progenitor cells, Physiol. Genomics 35 (2008) 75–85. 93. K. Ninomiya, T. Miyamoto, J. Imai, et al., Osteoclastic activity induces osteomodulin expression in osteoblasts, Biochem. Biophys. Res. Commun. 362 (2007) 460–466. 94. T.G. Kashima, T. Nishiyama, K. Shimazu, et al., Periostin, a novel marker of intramembranous ossification, is expressed in fibrous dysplasia and in c-Fos-overexpressing bone lesions, Hum. Pathol. (15 September, 2008) [Epub ahead of print]. 95. K. Ohta, G. Lupo, S. Kuriyama, et al., Tsukushi functions as an organizer inducer by inhibition of BMP activity in cooperation with chordin, Dev. Cell 7 (2004) 347–358. 96. A.I. Alford, K.D. Hankenson, Matricellular proteins: extracellular modulators of bone development, remodeling, and regeneration, Bone 38 (2006) 749–757.
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97. R.J. Midura, A. Wang, D. Lovitch, D. Law, K. Powell, J.P. Gorski, Bone acidic glycoprotein-75 delineates the extracellular sites of future bone sialoprotein accumulation and apatite nucleation in osteoblastic cultures, J. Biol. Chem. 279 (2004) 25464–25473. 98. C. Sintuu, S.S. Murray, K. Behnam, et al., Full-length bovine spp24 [spp24 (24-203)] inhibits BMP-2 induced bone formation, J. Orthopaed. Res. 26 (2008) 753–758. 99. J.L. Millán, Alkaline phosphatases: structure, substrate specificity and functional relatedness to other members of a large superfamily of enzymes, Purinerg. Signal. 2 (2006) 335–341. 100. D.R. Hopkins, S. Keles, DS. Greenspan, The bone morphogenetic protein 1/Tolloid-like metalloproteinases, Matrix Biol. 26 (2007) 508–523. 101. H.K. Väänänen, T. Laitala-Leinonen, Osteoclast lineage and function, Arch. Biochem. Biophys. 473 (2008) 132–138. 102. J.D. Kaunitz, D.T. Yamaguchi, TNAP, TrAP, ecto-purinergic signaling, and bone remodeling, J. Cell. Biochem. 105 (2008) 655–662. 103. M. Goldberg, A.L. Boskey, Lipids and biomineralizations, Prog. Histochem. Cytochem. 31 (1996) 1–187. 104. K. Podar, K.C. Anderson, Caveolin-1 as a potential new therapeutic target in multiple myeloma, Cancer Lett. 233 (2006) 10–15. 105. J. Rubin, Z. Schwartz, B.D. Boyan, et al., Caveolin-1 knockout mice have increased bone size and stiffness, J. Bone Miner. Res. 22 (2007) 1408–1418. 106. K. Nakashima, X. Zhou, G. Kunkel, et al., The novel zinc finger-containing transcription factor osterix is required for osteoblast differentiation and bone formation, Cell 108 (2002) 7–29. 107. Q. Tu, J. Zhang, J. Paz, K. Wade, P. Yang, J. Chen, Haploinsufficiency of Runx2 results in bone formation decrease and different BSP expression pattern changes in two transgenic mouse models, J. Cell Physiol. 217 (2008) 40–47. 108. S.D. Berman, T.L. Yuan, E.S. Miller, E.Y. Lee, A. Caron, J.A. Lees, The retinoblastoma protein tumor suppressor is important for appropriate osteoblast differentiation and bone development, Molec. Cancer Res. 6 (2008) 1440–1451.
Chapter
2
Bone Remodeling: Cellular Activities in Bone Hua Zhou1, Shi S Lu1 and David W. Dempster2 1
Regional Bone Center, Helen Hayes Hospital, West Haverstraw, New York, NY, USA Department of Pathology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
2
Introduction
where removal of old bone is coupled in space and in time by replacement by new bone [6, 7].
Bone remodeling is a fundamental process by which the mammalian skeleton tissue is continuously renewed to maintain the structural, biochemical and biomechanical integrity of bone and to support its role in mineral homeostasis. The process of bone remodeling is achieved by the cooperative and sequential work of groups of functionally and morphologically distinct cells, termed basic multicellular units (BMUs) or bone remodeling units (BRUs). Changes in the population and/or activities in any component of the BMUs disrupts the harmony of the cellular efforts and leads to changes in bone mass and strength. The cellular activities of bone remodeling units vary within and among the different bones of the skeleton and this variation changes with age, underlying the mechanism of agerelated bone loss. This chapter reviews current concepts of bone remodeling with respect to its cellular mechanism, physiological functions and anatomic variation in cellular behavior.
Activation Activation is the term used to describe the process of converting a resting bone surface into a remodeling surface. In the human adult skeleton, a new BRU is activated about every ten seconds [3]. Activation involves recruitment of mononuclear osteoclast precursors from hematopoietic origin, penetration by osteoclast precursors through gaps in the bone lining cell layer, fusion of the precursor cells to form multinucleated osteoclasts and functional osteoclasts adhering to mineralized bone matrix [8, 9]. Two cytokines, receptor activator of nuclear factor kappa B ligand (RANKL) and macrophage colony-stimulating factor (M-CSF), are essential and sufficient for osteoclastogenesis [10–12]. RANKL and M-CSF are produced by marrow stromal cells and their derivative osteoblasts in response to pro-resorption stimuli, such as parathyroid hormone (PTH), 1,25(OH)2D, interleukin-1 (IL-1) and interleukin-6 (IL-6), and play a crucial role in the formation, activation, activity and life span of osteoclasts (Figure 2.2). The activation of sites on the bone surface is either targeted or random. Selective remodeling targets specific sites where the osteocytes have sensed a change in mechanical strain or matrix damage in the form of microcracks and have conveyed signals to the surface to initiate targeted remodeling. However, most remodeling sites are likely to be random [13, 14].
Cellular mechanism of bone remodeling Bone remodeling takes place on bone surfaces and is achieved by multicellular units, BMUs [1, 2] or bone remodeling units, BRUs [3], the latter term being used here. The process of remodeling consists of four sequential and distinct phases of cellular events: activation, resorption, reversal and formation [2, 4, 5] (Figure 2.1A–E). The microanatomic basis of BRUs is osteonal units in intracortical bone (Figure 2.1G) and discrete osteonal units or packets in endocortical and cancellous bone (Figure 2.1F),
Osteoporosis in Men
Resorption Osteoclasts affix themselves to the bone matrix through integrins such as 3 [15, 16]. The adherence to bone induces ruffled membrane formation and creates an annular
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Copyright 2009, 2010 Elsevier, Inc. All rights of reproduction in any form reserved.
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Osteoporosis in Men (A)
(B)
(C)
(D) O L MB
(E)
Cancellous bone remodeling unit
(F)
(G)
Resorption
Reversal
Formation
Cortical bone remodeling unit
Figure 2.1 Light photomicrographs of the principal phases of the remodeling cycle in cancellous bone of human iliac crest biopsy specimens. (A) Resorption. Several multinucleated osteoclasts are seen in excavating a Howship’s lacuna. (B) Reversal. The Howship’s lacuna contains no osteoclasts but small mononucleated cells in contact with the scalloped surface. (C) Formation. A sheet of plump osteo blasts is seen depositing osteoid (O) on top of mineralized bone (MB). Note the reversal line (L) and osteocyte lacunae (arrowheads) in the mineralized matrix. (D) A later stage of formation where the osteoblasts have become flattened lining cells. Matrix production has ceased, but a thin layer of osteoid still remains to be mineralized. (E) Resting. No remodeling activity is in progress but a layer of attenuated cells lines the surface. Cross-sectional diagrams of BRUs in cancellous bone (F) and cortical bone (G). The arrows indicate the direction of movement through space. Note that the cancellous BRU is essentially one half of the cortical BRU. (A–E, from Dempster DW. Bone remodeling. In Disorders of bone and mineral metabolism. 2nd edn, (eds) Coe F, Favus MJ, pp 315–343, 2002. Lippincott Williams & Wilkins, Philadelphia: with permission. F,G, from Seibel MJ, Robins SP, Bilezikian JP. (eds) Dynamics of bone and cartilage metabolism, 2nd edn, pp 377–389, 2006. Academic Press, New York with permission).
C h a p t e r 2 Bone Remodeling: Cellular Activities in Bone l
17
Prostaglandins, multiple hormones, cytokines, ILs and vitamin D E2 Stromal/osteoblastic cells
GCs
T T
TGFβ IFNγ
T OPG, RANKL, M-CSF
TNFα, IL-1, IL-6, IL-7, other ILs
RANKL TNFα
HSC M-CSF c-Fms– RANK–
c-Fms+ RANK–
c-Fms+ RANK+
M-CSF + RANKL T OPG
Figure 2.2 Role of cytokines, peptide and steroid hormones and prostaglandins in the osteoclast formation and activation. Hematopoietic stem cells (HSCs) express c-Fms (receptor for M-CSF) and RANK (receptor for RANKL) and differentiate to osteoclasts. Marrow mesenchymal cells respond to a range of stimuli by secreting a mixture of pro- and anti-osteoclastogenic factors, the latter consisting primarily of OPG. (From Ross FP. Osteoclast biology and bone resorption. In Primer on the metabolic bone diseases and disorders of mineral metabolism, 6th edn, (ed.) Favus MJ, pp 30–35, 2006. American Society for Bone and Mineral Research, Washington, with permission).
sealing zone, forming a hemivacuole between the osteoclast itself and the bone matrix and isolated from the surrounding extracellular space (Figure 2.3A, B). By means of membrane-bound proton pumps and chloride channels, the osteoclast secretes hydrochloric acid, as well as acidic proteases such as cathepsin K, TRACP, MMP9, MMP13 and gelatinase into the hemivacuole (see Figure 2.3A, B) [17, 18]. The acidified solution in the resorbing compartment mobilizes the mineralized component of the matrix and the proteolytic enzymes, which are most active at low pH, degrade the organic constituents of the matrix. This pro cess creates the crescent-shaped resorption cavities called Howship’s lacunae on the cancellous bone surface (see Figure 2.1A and F) and the cutting cones of the evolving Haversian systems within cortical bone (see Figure 2.1G). Generally, the resorption is accomplished by multinucleated osteoclasts, but both in vivo and in vitro evidence suggests that mononucleated cells are also capable of excavating bone and forming resorption cavities and cutting cones [19, 20]. The fate of the osteoclast at the conclusion of the resorption phase is unclear, but at least some undergo apoptosis [21].
Reversal During this phase, the resorption lacuna is occupied by mononuclear cells, including monocytes, osteocytes that
were liberated from bone by osteoclasts and pre-osteoblasts that are being recruited to couple the resorption phase with the formation phase (see Figure 2.1B, F, G) [22]. The mechanism of osteoblast coupling and the exact nature of the coupling signals are currently undefined, but there are a number of interesting hypotheses. One plausible theory is that osteoclastic bone resorption liberates growth factors from the bone matrix and that these factors serve as chemo attractants for osteoblast precursors and then enhance osteoblast proliferation and differentiation. Bone matrixderived growth factors, such as transforming growth factor- (TGF-), insulin-like growth factors I and II (IGF-I and II), bone morphogenetic proteins (BMPs), platelet-derived growth factors (PDGF) and fibroblast growth factor (FGF) are all possible contenders for such coupling factors [23–27]. Another attractive premise is that the coupling of bone formation to resorption is a strain-regulated phenomenon [28]. As bone remodeling units penetrate through cortical bone, strain levels are reduced in front of the osteoclasts, but are increased behind them. Similarly, in cancellous bone, strain is posited to be higher at the base of the Howship’s lacunae and lower in the surrounding bone. It is argued that this gradient of strain leads to sequential activation of osteoclasts and osteoblasts, with osteoclasts being activated by reduced strain and osteoblasts, in turn, by increased strain. This hypothesis may account for alignment of osteons along the dominant loading direction of the
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Osteoporosis in Men
bone [29, 30]. Furthermore, osteoclast to osteoblast forward and reverse signaling has recently been implicated in the coupling mechanism [31, 32].
Formation
Sealing zone (A)
Ruffled border
Sealing zone
Bone
HCO3-Cl-
Cath K
H+HCO3-Cl-
αvβ3
H+ ClBone
Nuclei
TGN Microtubles
Signaling ruffled membrane
αvβ3
(B)
Bone
Figure 2.3 (A) Transmission electron microphotograph of a multinucleated osteoclast in rat bone. Note the extensive ruffled border, sealing zones and the partially degraded matrix between the sealing zones. (B) Diagram illustrating the primary mechanisms of osteoclastic bone resorption. (From Ross FP. Osteoclast biology and bone resorption. In Primer on the metabolic bone diseases and disorders of mineral metabolism, 6th edn, (ed.) Favus MJ, pp 30–35, 2006. American Society for Bone and Mineral Research, Washington, with permission).
Osteoblasts are recruited and differentiate from mesenchymal precursors. There is a gradient of differentiation as the osteoblastic precursors reach the bone surface to refill the resorption cavity and the osteoblast phenotype becomes fully expressed (Figure 2.4A) [33]. Bone matrix formation is a two-stage process in which osteoblasts initially synthesize the organic matrix, called osteoid, and then regulate its mineralization (Figure 2.4B). Osteoid consists of collagenous proteins, predominantly type I collagen, accounting for 90% of the organic matrix, with non-collagenous proteins making up the remaining 10%, including glycoproteins (i.e. alkaline phosphatase and osteonectin), Gla-containing proteins (i.e. osteocalcin and matrix Gla protein) and others (e.g., proteolipids) [34]. Osteoid is deposited on the bone surface in curved sheets called osteoid lamellae, following the contours of the underlying mineralized bone (see Figure 2.4B). Once the collagenous organic matrix is synthesized, osteoblasts trigger the mineralization process, which occurs after a delay of about 20 days, called the mineralization lag time. This is accomplished by the release of small, membranebound matrix vesicles that establish suitable conditions for initial mineral deposition by concentrating calcium and phosphate ions and enzymatically degrading inhibitors of mineralization, such as pyrophosphate and proteoglycans that are present in the extracellular matrix [35]. During this period, the osteoid undergoes a variety of biochemical changes that render it mineralizeable. The mineral content of the matrix increases rapidly to 75% of the final mineral content over the first few days, called primary mineralization, but it may take as long as a year for the matrix to reach its maximum mineral content, called secondary mineralization [36]. The mineral crystals within bone are analogous to the naturally occurring geologic mineral, hydroxyapatite (Ca10[PO4]6[OH]2), including numerous ions which are not found in pure hydroxyapatite, such as HPO42, CO32, Mg2, Na, F and citrate, adsorbed to the hydroxyapatite crystals [34]. As bone formation continues, osteoblasts that have reached the end of their synthetic activity embed themselves in the matrix, becoming osteocytes (see Figure 2.4A). Osteocytes are regularly dispersed throughout the mineralized matrix and maintain intimate contact with each other, as well as to the cells on the bone surface, through gap junctions between their slender, cytoplasmic processes or dendrites, which pass through the bone in small canals called canaliculi (Figure 2.5). Osteocytes function as an extensive 3-dimensional network of sensor cells, or ‘syncytium’, which can detect a change in mechanical strain in bone and respond by transmitting signals to the lining
C h a p t e r 2 Bone Remodeling: Cellular Activities in Bone l
19
OS MS MB
pOB OB OS pOCY OCY
MB
(A)
(B)
Figure 2.4 (A) Light photomicrograph of a human bone biopsy stained with Goldner’s trichrome. Osteoblastic lineage in a gradient differentiation: osteoblastic precursors (pOB) reach the bone surface → mature osteoblasts (OB) filling in a resorption cavity → pre-osteocytes (pOCY) become incorporated into osteoid (OS) matrix → osteocytes (OCY) embedded within the mineralized bone (MB). (B) Fluorescent photomicrograph of dog bone. Two steps of bone formation: osteoid matrix forming on bone surface (OS), mineralizing surface (MS) and mineralized bone (MB). (See color plate section).
(A)
(B)
Figure 2.5 (A) Transmission and (B) scanning electron micrographs showing osteocyte processes communicating with cells on the bone surface. (From Marotti G. et al. The structure of bone tissues and the cellular control of their deposition. Ital J Anat Embryol 1996;101:25-79, with permission).
cells on the bone surface to initiate targeted remodeling or to regulate resorption and formation in the newly initiated bone remodeling cycle [37]. Osteocytes die by apoptosis, which occurs with aging, immobilization, microdamage, lack of estrogen, glucocorticoid excess and in association with pathological conditions, such as osteoporosis and osteoarthritis [38]. Osteocyte apoptosis has also been suggested to play an important role in targeting bone remodeling following the observation that osteocyte apoptosis occurs in association with areas of microdamage and that this is followed by osteoclastic resorption to begin the replacement of the mechanically challenged bone [39]. Osteoblasts suffer one of three fates during and at the end of the bone formation phase of the remodeling cycle: many become incorporated into the matrix they formed and differentiate into osteocytes; some convert into lining
cells on the bone surface at the termination of formation; and the remainder die by apoptosis. Bone lining cells were once thought to serve primarily to regulate the flow of ions into and out of the bone extracellular fluid serving as the blood–bone barrier. It has recently been appreciated that, under certain circumstances, for example, stimulation by PTH or mechanical force, bone lining cells can revert back to functional osteoblasts [40, 41]. Another recently discovered important function of the lining cells is to create specialized compartments in cancellous and cortical bone where bone remodeling takes place [42] (Figure 2.6). The end result of a completed remodeling cycle by a BRU is the production of a new osteon (Figure 2.7A, B). The remodeling process is similar in cancellous and cortical bone with the remodeling unit in cancellous bone being equivalent to half of a cortical remodeling unit [43] (see Figure 2.1F, G).
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The difference between the volume of bone removed by osteoclasts and replaced by osteoblasts during BRU remodeling cycle is termed ‘bone balance’. As will be discussed later, the bone balance varies with the anatomical location of the bone surface as well as with gender, age and disease.
Physiological functions of bone remodeling The primary functions of bone remodeling are presumed to be maintenance of the mechanical competence of bone by continuously replacing fatigued bone with new, mechanically sound bone and to preserve mineral homeostasis by continuously mobilizing the skeletal stores of calcium and phosphorus
OC
Figure 2.6 Light photomicrograph of a human bone biopsy stained with toluidine blue. An osteoclast (OC) is resorbing bone within a specialized compartment formed by a dome-shaped layer of lining cells (arrows). (See color plate section).
(A)
to the circulation. It has also been suggested that there must be other, as yet known functions or reasons why the human skeleton undergoes such extensive remodeling [44]. Like all load-bearing structural materials, the skeleton is subjected to fatigue damage as it ages and undergoes repetitive mechanical challenges. Older bone displays increased mineralization density as secondary mineralization continues and the water content diminishes, which causes the matrix to become more brittle [45]. In addition, aging is associated with biochemical changes in the bone matrix constituents, such as accumulation of non-enzymatic glyca tion end products [46] and increased cross-linking of collagen [47]. These changes render the bone more susceptible to mechanical damage and fracture. It has also been demonstrated that osteocytes that have undergone apoptosis leave empty lacuna that may become occluded by mineralized debris [48] and that fatigue microcracks increase in number with bone age and are spatially associated with missing osteocytes [49]. Moreover, the fact that resorption cavities are frequently located close to bone microcracks [50, 51] provides compelling evidence that targeted remodeling is activated in response to the appearance of such microcracks. The skeleton is the greatest repository of mineral ions, such as Ca, Mg and P, in the human body and plays an important role in mineral homeostasis by coordinated interplay with the intestine, the site of net ionic absorption, and the kidney, the site of net ionic excretion. Longterm mineral homeostasis is achieved by the BRUs, which mobilize skeletal mineral to blood during bone resorption and return the mineral back to the skeleton during bone formation. However, at least two other mechanisms allow the skeleton to participate in mineral homeostasis: the blood– bone barrier maintained by the bone lining cells and the percolation of bone extracellular fluid through osteocyte lacuno-canalicular network.
(B)
Figure 2.7 (A) Completed basic structural units in cancellous bone and (B) cortical bone. The arrowheads delineate reversal lines. (From Dempster DW. Bone remodeling. In Osteoporosis: etiology, diagnosis, and management, 2nd edn, (eds) Riggs BL, Melton LJ, pp 67–91, 1995. Raven Press, New York, with permission.) (See color plate section).
C h a p t e r 2 Bone Remodeling: Cellular Activities in Bone l
In the regulation of calcium homeostasis, a fall in serum Ca2 concentration is detected by the parathyroid cell plasma membrane Ca-sensing receptor (CaSR), which leads to an increase in parathyroid hormone release. Parathyroid hormone acts to mobilize calcium by three mechanisms: PTH regulates the outflow of calcium from bone by stimulating the resorptive activity in existing BRUs, an acute response, and by stimulating the activation of new BRUs and increasing bone turnover, a long-term response [52]. PTH also stimulates renal tubular reabsorption of calcium and regulates the calcium blood–bone equilibrium through the lining cells on quiescent bone surfaces. Finally, PTH increases intestinal absorption of calcium by enhancement of 1,25 dihydroxyvitamin D synthesis [53, 54]. The involvement of the skeleton in phosphate homeo stasis is achieved in a similar manner. A fall in plasma phosphate concentration stimulates 1,25-dihydroxyvitamin D production in the kidney which, in addition to increasing phosphate absorption from gut, stimulates bone remodeling to mobilize phosphate from the skeleton. Clearly, phosphate cannot be withdrawn from the skeleton without being accompanied by calcium and vice versa. However, the unnecessary increase in calcium or phosphate, respectively, can be compensated by the enhanced renal excretion of calcium or phosphate. As discussed earlier in the chapter, minerals are transferred into bone during the formation phase of the remodeling cycle. Because bone formation is usually tightly coupled with bone resorption, bone remodeling does not generally lead to a net transfer of mineral to or from the blood in the long run. However, an increase in remodeling rate does transiently mobilize significant amounts of mineral into the blood, because it takes a much longer time for newly formed bone to reach the same mineral content as that removed during bone resorption [55]. By analogy to financial transactions, when calcium is urgently needed, it may be withdrawn rapidly from the bone bank and then paid back gradually later. This allows the skeleton to participate in calcium homeostasis without permanently compromising its structural integrity. However, with advancing age, the intestinal absorption of calcium declines and, ultimately, the mechanical competence of the skeleton is compromised to maintain an adequate serum calcium level.
Variation in bone remodeling activity throughout the skeleton The bone turnover rate varies substantially within and among the different bones of the skeleton. It has often been asserted that cancellous bone has higher turnover than cortical bone [56], which is true when one compares central cancellous bone with peripheral cortical bone. This is generally attributed to the four to five times higher surface-to-volume
21
ratio in the typical cancellous bone than in the typical cortical bone [57, 58] and to the close correspondence in cancellous bone tissue between marrow cellularity, blood flow and remodeling activity [59]. But this view fails to consider the geometrical and biological factors that influence bone turnover [56, 59]. The subdivisions within the bone consist of four distinct surfaces or ‘envelopes’: periosteal, Haversian or intracortical, cortical-endosteal or endocortical and cancellous [4, 56]. The evaluation of the activity of BRUs on each subdivision provides a histological estimation of bone turnover with the measurement and calculation of the tetracycline-based bone formation rate and activation frequency. Such data are available for the ilium and the rib in the human skeleton. In the iliac bone of healthy postmenopausal white women, bone turnover is 8.4% per year in the subperiosteal envelope, 5.9% per year in the intracortical envelope and 33.7% per year in the subendocortical envelope. The bone turnover in the total cortical bone is 7.7% per year and in the cancellous bone it is 17.7% per year [56, 58, 60, 61]. In the cortical bone of the sixth rib, mean bone turnover after 50 years is 4% per year [62]. Differences in cellular activity in BRUs among the anatomic subdivisions within the bone determines the net difference between the volume of bone removed and replaced by each BRU. In the Haversian or intracortical envelope, the net bone balance is slightly negative, particularly in the inner half of the cortex, which leads to a decrease in the radial rate of closure of osteons [62], an increase in the Haversian canal diameter, a decrease in osteon wall thickness and an increase in the number of resorption cavities that are abandoned in the reversal phase and remain unfilled [63–66]. In the periosteal envelope, each BRU deposits slightly more bone than it removes. Conversely, in the endocortical envelope, less bone is laid down than resorbed and the deficit here is greater than the slight positive balance in the periosteal envelope, which reduces the thickness of cortex [60, 67, 68]. In the cancellous bone envelope, there is a shortfall in the amount of bone replaced compared to that removed, which causes thinning of trabeculae making them more vulnerable to perforation by osteoclasts [60, 67, 68]. With aging, the effects of these small increments and decrements of bone mass accumulate. The net bone balance on each envelope provides a BRUbased explanation for the long-established facts concerning the changes in three-dimensional geometry of bones as a function of age [4]. Both the positive bone balance on the periosteal surface and the negative balance on the endocortical surface increase their respective circumferences, with the latter moving outward at a greater rate than the former, which consequently reduces cortical thickness. The cortical porosity increases by 1–2% in the outer half of the cortex and by 5–10% in the inner half due to the negative bone balance on the Haversian surface. The increase in the osteoclast resorption cavity depth, together with the negative bone balance on the endocortical surface and the
22
Osteoporosis in Men
increase in cortical porosity, leads to the creation of large voids in the inner third to half of the cortex. Ultimately, the inner cortex resembles the cancellous bone in structure, a process called cortical bone cancellization, which contributes to the thinning of cortex. In cancellous bone, the negative bone balance in BRUs is manifested in a reduction of the completed wall thickness of cancellous bone packets, which is partially the cause of the gradual age-related bone loss that occurs in both sexes [69, 70]. There have been relatively few assessments of the regional variation in bone remodeling and turnover throughout the skeleton. Some attention has been given to the relationship between the standard biopsy site in the iliac crest and other skeletal sites [71]. As evaluated by histomorphometry, the bone turnover rate in ilium is about double that in the vertebral body [3]. Based on the measurement of osteoid and osteoblast-covered surface, Krempien and colleagues found a marked disparity among four different skeletal sites, with an implied rank order of remodeling rate as follows: iliac crest lumbar vertebra femoral head distal femur [72]. The histomorphometric analysis of tetracycline-labeled bone samples has been the most reliable way to assess regional differences in remodeling rate but, obviously, is not practical for studies in living subjects. However, there is one case report [73] of an elderly osteo porotic woman who died suddenly before a scheduled bone biopsy for which she had been pre-labeled with tetracycline. Twenty-four skeletal sites were sampled at autopsy and bone formation rates were found to vary widely from a high of 37% per year in the iliac crest to a low of less than 2% per year in the 10th thoracic vertebra. Significant variations were also found between bones within fairly localized regions of the skeleton, e.g. from one vertebra to the next, or between the right and left iliac crest. The tetracyclinebased bone formation rate in cortical bone of rib, a oncefavored biopsy site, is 3–4% year, which is about twice that in cortical bone elsewhere in the skeleton [3].
References 1. H.M. Frost, Dynamics of bone remodeling, in: H.M. Frost (Ed.), Bone Biodynamics, Little Brown & Co, Boston, 1964. 2. H.M. Frost, Bone Remodeling and Its Relationship to Metabolic Bone Disease, Charles C Thomas, Springfield, 1973. 3. A.M. Parfitt, The physiological and clinical significance of bone histomorphometric data, in: R.R. Recker (Ed.), Bone Histomorphometry: Techniques and Interpretation, CRC Press, Boca Raton, 1983, pp. 143–223. 4. H.M. Frost, Intermediary Organization of the Skeleton, CRC Press, Boca Raton, 1986. 5. R. Baron, Importance of the intermediate phases between resorption and formation in the measurement and understanding of the bone remodeling sequence, in: P.J. Meunier (Ed.), Bone Histomorphometry. Proceedings of the 2nd International workshop, Société de la Nouvelle Imprimerie Fournie, Toulouse, 1977, pp. 179–183.
6. H.M. Frost, Bone Remodeling Dynamics, Charles C Thomas, Springfield, 1963. 7. H.M. Frost, The Laws of Bone Structure, Charles C Thomas, Springfield, 1964. 8. P. Tran Van, A. Vignery, R. Baron, An electron microscopic study of the bone-remodeling sequence in the rat, Cell Tissue Res. 225 (1982) 283–292. 9. P. Tran Van, A. Vignery, R. Baron, Cellular kinetics of the bone remodeling sequence in the rat, Anat. Rec. 202 (1982) 441–451. 10. W.J. Boyle, W.S. Simonet, D.L. Lacey, Osteoclast differentiation and activation, Nature 423 (2003) 337–342. 11. T. Suda, N. Takahashi, N. Udagawa, E. Jimi, M.T. Gillespie, T.J. Martin, Modulation of osteoclast differentiation and function by the new members of the tumor necrosis factor receptor and ligand families, Endocr. Rev. 20 (1999) 345–357. 12. F.J. Pixley, E.R. Stanley, CSF-1 regulation of the wandering macrophage: complexity in action, Trends Cell Biol. 14 (2004) 628–638. 13. D.B. Burr, Targeted and nontargeted remodeling, Bone 30 (2002) 2–4. 14. A.M. Parfitt, Targeted and nontargeted bone remodeling: relationship to basic multicellular unit origination and progression, Bone 30 (2002) 5–7. 15. R.O. Hynes, Integrins: bidirectional, allosteric signaling machines, Cell 110 (2002) 673–687. 16. F.P. Ross, S.L. Teitelbaum, 3 and macrophage colonystimulating factors: partners in osteoclast biology, Immunol. Rev. 208 (2005) 88–105. 17. S.L. Teitelbaum, F.P. Ross, Genetic regulation of osteoclast development and function, Nat. Rev. Genet. 4 (2003) 638–649. 18. J.M. Delaisse, T.L. Andersen, M.T. Engsig, K. Henriksen, T. Troen, L. Blavier, Matrix metalloproteinases (MMP) and cathepsin K contribute differently to osteoclastic activities, Microsc. Res. Tech. 61 (2003) 504–513. 19. E.F. Eriksen, Normal and pathological remodeling of human trabecular bone: three-dimensional reconstruction of the remodeling sequence in normals and in metabolic bone disease, Endocr. Rev. 7 (1986) 379–408. 20. D.W. Dempster, C. Hughes-Begos, K. Plavetic-Chee, et al., Normal human osteoclasts formed from peripheral blood monocytes express PTH type 1 receptors and are stimulated by PTH in the absence of osteoblasts, J. Cell Biochem. 95 (2005) 139–148. 21. H.C. Blair, S. Simonet, D.L. Lacey, M. Zaidi, Osteoclast biology, in: R. Marcus, D. Feldman, D.A. Nelson, C.J. Rosen (Eds.) Osteoporosis, third ed., Elsevier Academic Press, Burlington, 2008, pp. 71–89. 22. R. Baron, A. Vignery, P. Tran Van, The significance of lacunar erosion without osteoclasts: studies on the reversal phase of the remodeling sequence, Metab. Bone. Dis. Relat. Res. 2S (1980) 35–40. 23. L.F. Bonewald, G.R. Mundy, Role of transforming growth factor beta in bone remodeling, Clin. Orthoped. Relat. Res. 250 (1990) 261–276. 24. S. Mohan, D.J. Baylink, Insulin-like growth factor system components and the coupling of bone formation to resorption, Hormone. Res. 45 (Suppl. 1) (1996) 59–62. 25. J.M. Hock, M. Centrella, E. Canalis, Insulin-like growth factor I (IGF-I) has independent effects on bone matrix formation and cell replication, Endocrinology 122 (1998) 254–260.
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26. J. Fiedler, G. Roderer, K.P. Gunther, R.E. Brenner, BMP-2, BMP-4, and PDGF-bb stimulate chemotactic migration of primary human mesenchymal progenitor cells, J. Cell Biochem. 87 (2002) 306–312. 27. H. Tanaka, A. Wakisaka, H. Ogasa, S. Kawai, C.T. Liang, Effects of basic fibroblast growth factor on osteoblast-related gene expression in the process of medullary bone formation induced in rat femur, J. Bone. Miner. Metab. 21 (2003) 74–79. 28. T.H. Smit, E.H. Burger, Is BMU-coupling a train-regulated phenomenon? A finite element analysis, J. Bone Miner. Res. 15 (2000) 301–307. 29. T.H. Smit, E.H. Burger, J.M. Huyghe, A case for straininduced fluid flow as a regulator of BMU-coupling and osteonal alignment, J. Bone Miner. Res. 17 (2002) 2021–2029. 30. E.H. Burgher, J. Klein-Nulend, T.H. Smit, Strain-derived, canalicular fluid flow regulates osteoclast activity in a remodelling osteon – a proposal, J. Biomech. 36 (2003) 1453–1459. 31. T.J. Martin, N.A. Sims, Osteoclast-derived activity in the coupling of bone formation to resorption, Trends. Molec. Med. 11 (2005) 76–81. 32. M.A. Karsdal, K. Henriksen, M.G. Sorensen, et al., Acidification of the osteoclastic resorption compartment provides insight into the coupling of bone formation to bone resorption, Am. J. Pathol. 166 (2005) 467–476. 33. J.B. Lian, G.S. Stein, Osteoblast biology, in: R. Marcus, D. Feldman, D.A. Nelson, C.J. Rosen (Eds.) Osteoporosis, Elsevier Academic Press, London, 2008, pp. 93–150. 34. W. Zhu, P.G. Robey, A. Boskey, The regulatory role of matrix proteins in mineralization of bone, in: R. Marcus, D. Feldman, D.A. Nelson, C.J. Rosen (Eds.) Osteoporosis, Elsevier Academic Press, London, 2008, pp. 191–240. 35. H.C. Anderson, Matrix vesicles and calcification, Curr. Rheumatol. Rep. 5 (2003) 222–226. 36. R. Amprino, A. Engstrom, Studies on x-ray absorption and diffraction of bone tissue, Acta. Anat. 15 (1952) 1–22. 37. L.F. Bonewald, M.L. Johnson, Osteocytes, mechanosensing and Wnt signaling, Bone 42 (2008) 606–615. 38. L.F. Bonewald, Osteocytes, in: R. Marcus, D. Feldman, D.A. Nelson, C.J. Rosen (Eds.) Osteoporosis, Elsevier Academic Press, London, 2008, pp. 169–189. 39. B.S. Noble, N. Peet, H.Y. Stevens, et al., Mechanical loading: biphasic osteocyte survival and targeting of osteoclasts for bone destruction in rat cortical bone, Am. J. Physiol. Cell. Physiol. 284 (2003) C934–C943. 40. H. Dobnig, R.T. Turner, Evidence that intermittent treatment with parathyroid hormone increases bone formation in adult rats by activation of bone lining cells., Endocrinology 136 (1995) 3632–3638. 41. J.W. Chow, A.J. Wilson, T.J. Chambers, S.W. Fox, Mechanical loading stimulates bone formation by reactivation of bone lining cells in 13-week-old rats, J. Bone Miner. Res. 13 (1998) 1760–1767. 42. E.M. Hauge, D. Qvesel, E.F. Eriksen, L. Mosekilde, F. Melsen, Cancellous bone remodeling occurs in specialized compartments lined by cells expressing osteoblastic markers, J. Bone Miner. Res. 16 (2001) 1575–1582. 43. A.M. Parfitt, Osteonal and hemiosteonal remodeling: the spatial and temporal framework for signal traffic in adult bone, J. Cell Biochem. 55 (1994) 273–276.
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44. J.D. Currey, Bone: Structure and Mechanics, Princeton University Press, Princeton, 2002. 45. H.M. Frost, Micropetrosis, J. Bone Joint Surg. 42 (1980) 138–143. 46. D. Vashishth, G.J. Gibson, J.L. Khoury, M.B. Schaffler, J. Kimura, DP. Fyhrie, Influence of nonenzymatic glycation on biomechanical properties of cortical bone, Bone 28 (2001) 195–201. 47. A.J. Bailey, Changes in bone collagen with age and disease, J. Musculoskelet Neuron Interact. 2 (2002) 529–531. 48. S. Qiu, S. Palnitkar, D.S. Rao, A.M. Parfitt, Age and distance from the surface but not menopause reduce osteocyte viability in human cancellous bone, Bone 31 (2002) 313–318. 49. S. Qiu, D.S. Rao, D.P. Fyhrie, S. Palnitkar, A.M. Parfitt, The morphological association between microcracks and osteocyte lacunae in human cortical bone, Bone 37 (2005) 10–15. 50. S. Mori, D.B. Burr, Increased intracortical remodeling following fatigue damage, Bone 14 (1993) 103–109. 51. D.B. Burr, M.R. Forwood, D.P. Fyhrie, R.B. Martin, M.B. Schaffler, C.H. Turner, Perspective: bone microdamage and skeletal fragility in osteoporotic and stress factures, J. Bone Miner Res. 12 (1997) 6–15. 52. A.M. Parfitt, Renal bone disease: a new conceptual framework for the interpretation of bone histomorphometry, Curr. Opin. Nephrol. Hypertension. 12 (2003) 387–408. 53. AM. Parfitt, Calcium homeostasis, J. Musculoskelet Neuron Interact. 4 (2004) 109–110. 54. A.M. Parfitt, Misconceptions (3): calcium leaves bone only by resorption and enters only by formation, Bone 33 (2003) 259–263. 55. D.W. Dempster, Bone remodeling, in: F. Coe, M.J. Favus (Eds.) Disorders of Bone and Mineral Metabolism, second ed., Lippincott Williams & Wilkins, Philadelphia, 2002, pp. 315–343. 56. A.M. Parfitt, Misconceptions (2): turnover is always higher in cancellous than in cortical bone., Bone 30 (2002) 807–809. 57. J. Foldes, A.M. Parfitt, M.-S. Shih, D.S. Rao, M. Kleerekoper, Structural and geometric changes in iliac bone: relationship to normal aging and osteoporosis, J. Bone Miner. Res. 6 (1991) 759–766. 58. Z.H. Han, S. Palnitkar, D.S. Rao, D. Nelson, AM. Parfitt, Effect of ethnicity and age or menopause on the structure and geometry of iliac bone, J. Bone Miner Res. 11 (1996) 1967–1975. 59. A.M. Parfitt, Skeletal heterogeneity and the purposes of bone remodeling: implications for the understanding of osteo porosis, in: R. Marcus, D. Feldman, D.A. Nelson, C.J. Rosen (Eds.) Osteoporosis, third ed., Elsevier Academic Press, Burlington, 2008, pp. 71–89. 60. Z.H. Han, S. Palnitkar, D.S. Rao, D. Nelson, A.M. Parfitt, Effects of ethnicity and age or menopause on the remodeling and turnover of iliac bone: implications for mechanisms of bone loss, J. Bone Miner Res. 12 (1997) 498–508. 61. R. Balena, M.S. Shih, A.M. Parfitt, Bone resorption and formation on the periosteal envelope of the ilium: a histomorphometric study in healthy women, 7 (1992) 1475–1482. 62. H.M. Frost, Tetracycline-based histological analysis of bone remodeling, Calcif. Tissue Res. 3 (1969) 211–237. 63. R.B. Martin, J.C. Picket, S. Zinaich, Studies of skeletal remodeling in aging men., Clin. Orthoped. 49 (1980) 268–282. 64. J.S. Arnold, M.H. Bartley, S.A. Tont, DP. Jenkins, Skeletal changes in aging and disease, Clin. Orthoped. 49 (1966) 17–38.
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65. J. Jowsey, Studies of Haversian system in man and some animals, J. Anat. 100 (1966) 857–864. 66. Z.F. Jaworski, P. Meunier, H.M. Frost, Observations on 2 types of resorption cavities in human lamellar cortical bone., Clin. Orthoped. Relat. Res. 83 (1972) 279–285. 67. A.M. Parfitt, Bone remodeling: relationship to the amount and structure of bone, and the pathogenesis and prevention of fractures, in: B.L. Riggs, L.J. Melton (Eds.) III Osteoporosis: Etiology, Diagnosis and Management, Raven Press, New York, 1988, pp. 45–93. 68. A.M. Parfitt, The cellular basis of bone remodeling: the quantum concept re-examined in the light of recent advances in cell biology, Calcif. Tissue. Int. 36 (1984) 537–545. 69. P. Lips, P. Courpron, P.J. Meunier, Mean wall thickness of trabecular bone packets in the human iliac crest: changes with age., Calcif. Tissue Res. 26 (1978) 13–17.
70. J. Kragstrup, F. Melsen, L. Mosekilde, Thickness of bone formed at remodeling sites in normal human iliac trabecular bone: variations with age and sex, Metabol. Bone Dis. Relat. Res. 5 (1983) 17–21. 71. D.W. Dempster, The relationship between iliac crest bone biopsy and other skeletal sites, in: M. Kleerekoper, S. Krane (Eds.) Clinical Disorders of Bone and Mineral Metabolism, Mary Ann Liebert, New York, 1988. 72. B. Krempien, F.M. Lemminger, E. Ritz, E. Weber, The reaction of different skeletal sites to metabolic bone disease – a micromorphometric study, Klin. Wochenschr. 56 (1978) 755–759. 73. J. Podenphant, U. Engel, Regional variations in histomorphometric bone dynamics from the skeleton of an osteoporotic women, Calcif. Tissue Int. 40 (1987) 184–188.
Chapter
3
Assessment of Bone Turnover in Men Using Biochemical Markers Patrick Garnero1,2 and Pawel Szulc3 1
INSERM Research Unit 664, Lyon, France Synarc, Lyon, France 3 INSERM Research Unit 831, Lyon, France 2
Introduction
New biochemical markers of bone metabolism and new assays
Bone remodeling is the result of two opposite activities, the production of new bone matrix by osteoblasts and the destruction of old bone by osteoclasts. The rate of bone production and destruction can be evaluated by either measuring predominantly osteoblastic or osteoclastic enzyme activities or by assaying bone matrix components released into the bloodstream and eventually excreted in the urine. They have been separated into markers of formation and resorption, but it should be kept in mind that, in diseases where both events are coupled in time and space at the level of the basic multicellular unit and change in the same direction, any marker will reflect overall rate of bone turnover. The clinical utility of biochemical markers has been extensively evaluated in postmenopausal osteoporosis [1, 2], but data in men osteoporosis are more limited. At present, the biochemical markers which are the most specific and established for bone formation include serum osteocalcin, bone alkaline phosphatase (bone ALP) and the procollagen type I N-terminal propeptide (PINP) [1, 2]. For the evaluation of bone resorption, most assays are based on the detection in serum or urine of type I collagen fragments, which account for 90% of the organic bone matrix. These include the cross-links pyridinoline (PYD) and deoxypyridinoline (DPD), the telopeptides of type I collagen generated by cathepsin K (CTX, NTX) and by matrix-metalloproteases (CTX-MMP or ICTP) and fragments of the helical portion of type I collagen molecule (helical peptide) [2]. The individual measurement of most of these biochemical markers can be achieved with high throughput and analytical precision on automated platforms [3, 4].
Osteoporosis in Men
Although current biochemical markers have demonstrated clinical utility in the differential diagnosis of metabolic bone diseases and in predicting fracture risk and response to treatment in postmenopausal osteoporosis, they do have some limitations. Current biochemical markers of bone resorption are based primarily on type I collagen, which is not bone-specific but rather widely distributed in several other body tissues. Some of the type I collagen-based bone resorption markers are characterized by significant intrapatient variability, which impairs their use in individual patients. The systemic levels of biochemical markers reflect global skeletal turnover and do not provide distinct information on the remodeling of different bone envelopes, i.e. trabecular, cortical and periosteal. Further, their relative contribution to skeletal turnover may vary with aging, disease and treatment. Finally, current markers mostly reflect quantitative changes of bone turnover and do not provide information on the structural abnormalities of bone matrix properties which are an important determinant of bone fragility, especially toughness. Recently, new biochemical markers have been investigated to address some of these limitations (Table 3.1), although their clinical utility in assessment of bone turnover abnormalities in postmeno pausal and male osteoporosis is limited.
Non-Collagenous Bone Proteins Although the vast majority of bone matrix is composed of type I collagen molecules, about 10% of the organic phase is comprised of non-collagenous proteins, some of them
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Osteoporosis in Men Table 3.1 New candidate biochemical markers of bone metabolism by category
Non-collagenous proteins of bone matrix and fragments
Osteoclastic enzymes
Regulators of osteoclast-osteoblast differentiation/activity
Bone sialoprotein Osteopontin
TRAPC5b
OPG/ RANK-L (osteoclast)
Periostin Urinary mid-molecule osteocalcin fragments
Cathepsin K Wnt signaling molecules (Dkkl/sFRP) Sclerostin (osteoblast)
Collagen posttranslational modifications Non enzymatic glycation – mediated modifications of collagen (eg. pentosidine, vesperlysine, GOLD, MOLD, CML)
Type I collagen C-telopeptide isomerization (/ CTX ratio)
TRACP5b: tartrate resistant acid phosphatase isoenzyme 5b OPG: osteoprotegerin; RANK-L: receptor activator of nuclear factor kB ligand; Wnt Wingless, Dkk-1: Dicckops-1, sERP: soluble Frizzled-related protein, GOLD (glyoxal-derived lysine dimer), MOLD (methylglyoxal-derived lysine dimer), CML (carboxymethyllysine).
being almost specific for bone tissue. It has been suggested that the measurement of these proteins or fragments thereof could represent specific biochemical markers of bone turnover. Bone sialoprotein (BSP) is an acidic, phosphorylated glycoprotein of 33 kDa (glycosylated: 70–80 kDa) which contains an RGD integrin binding site. Although BSP is relatively restricted to bone, it is also expressed by tropho blasts and is strongly upregulated in a variety of human primary cancers, particularly those that metastasize to the skeleton [5]. A small amount of BSP is released in the circulation and, as such, is a potential marker of bone turnover [6]. Serum BSP levels are increased in malignant bone diseases, in postmenopausal osteoporosis and are decreased by antiresorptive treatments [6]. However, because of its tight association with circulating factor H, accurate measurement of serum BSP remains challenging. Other non-collagenous proteins include osteopontin, which belongs to the small integrin-binding ligand N-linked glycoprotein (SIBLING) family like BSP [7] and periostin, a secreted glutamic acid (Gla) adhesion molecule with preferential distribution in the periosteum envelope. They have been identified specifically as potentially useful in cancer-induced bone diseases [8]. Clinical data in other metabolic bone diseases, including male osteoporosis, are currently unavailable. Although most of the newly synthesized osteocalcin is captured within bone matrix, a small fraction is released into the blood where it can be detected by immunoassays. Circulating osteocalcin comprises different immunoreactive forms including the intact molecule and fragments of different sizes [9]. The majority of these fragments is generated from in vivo degradation of the intact molecule and, thus, also reflects bone formation. In vitro studies suggest, however, that some osteocalcin fragments could also be released from osteoclastic degradation of bone matrix [10] and, thus, may reflect, in part, bone resorption. Elevated levels of urinary osteocalcin fragment levels were reported in
osteoporotic postmenopausal women and values decreased after one month of treatment with the bisphosphonate alendronate [11]. This contrasts with the absence of significant change in serum total osteocalcin levels. Urinary osteocalcin fragment levels were found to be associated with BMD loss and fracture risk in older post-menopausal women [12, 13], but no data have been reported in men.
Osteoclastic Enzymes TRACP 5b Acid phosphatase is a lysosomal enzyme which is present primarily in bone, prostate, platelets, erythrocytes and spleen. Bone acid phosphatase is resistant to L ()-tartrate (TRACP), whereas the prostatic isoenzyme is inhibited by TRACP. Acid phosphatase circulates in blood and shows higher activity in serum than in plasma because of the release of platelet phosphatase activity during the clotting process. In normal plasma, TRACP corresponds to isoenzyme 5. Isoenzyme 5 is represented by two subforms, 5a and 5b. TRACP 5a derives mainly from macrophages and dendritic cells, whereas TRACP 5b is more specific for osteoclasts [14]. These two subforms differ by their carbohydrate content including sialic acid and mannose residues [15], optimal pH and specific activity. TRACP 5a is a monomeric protein, whereas TRACP 5b is cleaved into two subunits. Total plasma TRACP activity is measured by colorimetric assays. However, the lack of specificity of plasma TRACP activity for the osteoclast, its instability in frozen samples and the presence of enzyme inhibitors in serum are drawbacks which have limited the development of clinically useful enzymatic TRACP assays. To overcome these limitations, different immunoassays for serum tartrate TRACP, which preferentially detect isoenzymes 5a and 5b, have been developed. The first assay for TRACP 5b which was developed uses antibodies that recognize both intact and fragmented TRACP 5a and 5b. The selectivity of this assay
C h a p t e r 3 Assessment of Bone Turnover in Men Using Biochemical Markers l
for TRACP 5b is partly achieved by performing measurements at optimal pH for TRACP 5b activity [16]. More recently, a new immunoassay using two monoclonal antibodies raised against purified bone TRACP 5b with limited cross-reactivity for TRACP 5a has been described [17]. One antibody captures active intact TRACP 5b while the second eliminates interference of inactive fragments. We found that this new enzyme-linked immunosorbent assay (ELISA) for TRACP 5b is highly sensitive to detect increased bone turnover following menopause and is also very responsive to alendronate therapy [18]. Serum TRACP 5b is likely to reflect mostly the number and the activity of the osteoclasts. It may thus provide information on the bone resorption process which is complementary to that provided by collagen-related markers [19]. Another advantage of serum TRAPC 5b relates to its limited diurnal variation and negligible effect of food intake. These features result in lower intra-patient variability for TRACP 5b than for collagen-based biochemical markers. However, the magnitude of changes observed following bisphosphonate treatment in postmenopausal women is also lower for TRACP 5b than for collagen markers [16]. Data on serum TRACP 5a isoenzyme are more limited and there is no yet commercially available assay. A recent study showed that serum TRACP 5a was significantly increased in patients with rheumatoid arthritis (RA), especially in those presenting with nodules, whereas TRACP 5b was only marginally increased and was not associated with nodules [20]. It has also been reported that the alendronate induced a marked decrease in serum TRACP 5b, but had no effect on serum TRACP 5a [21]. These data indeed support the view that TRACP 5a is likely to reflect inflammatory macrophage activity, whereas TRACP 5b is an indicator of osteoclast activity. Cathepsin K The enzyme cathepsin K is a member of the cysteine protease family that, unlike other cathepsins, has the unique ability to cleave both helical and telopeptide regions of type I collagen [22]. The enzyme is produced as a 329 amino acid precursor procathepsin K, which is cleaved into its active form with a length of 215 amino acids. This cleavage event takes place in vivo within the low pH bone resorption lacunae. Commercially, two assays measuring respectively the enzymatic activity and the protein concentration of cathepsin K in serum are available. Clinical data on serum cathepsin K are still limited. In both healthy women and men, serum cathepsin K decreases with age, contrasting with age-associated increased bone resorption [23]. Increased serum cathepsin K levels have been reported in patients with active RA [24], patients with Paget’s disease of bone [25] and in postmenopausal women with fragility fractures [26]. Because circulating concentrations of cathepsin K are very low and current available assays lack
27
sensitivity, accurate measurements of this enzyme remain challenging.
Regulators of Osteoclastic and Osteoblastic Activity RANK-L AND OPG The RANK-L/RANK/OPG system is one of the main regulators of osteoclast formation and function [27]. In healthy men, serum OPG increases with age and modestly correlates with parathyroid hormone (PTH) and total deoxy pyridinoline, but not with BMD [28]. Although the major contribution of this pathway in postmenopausal bone loss has been clearly established in various animal and clinical models, the serum measurement of RANK-L and OPG remains difficult. Indeed, at present it remains unclear what proportion of circulating OPG is monomeric, dimeric or bound to RANK-L and which of these forms is the most biologically relevant to measure. The same issues arise for the measurements of circulating RANK-L which, in its free form, has barely detectable levels in healthy individuals. It is also unlikely that circulating levels of OPG and RANK-L reflect adequately local bone marrow production. These limitations probably explain the conflicting data available on the association of circulating OPG and RANK-L with BMD and biochemical markers of bone turnover in postmenopausal women and elderly men [29]. Wnt signaling molecules The Wnt signaling pathway plays a pivotal role in the differentiation and activity of osteoblastic cells [30]. There are 19 closely related Wnt genes that have been identified in humans. The primary receptors of Wnt molecules are the seven-transmembrane Frizzled related proteins (FRP), each of which interacts with a single transmembrane low density lipid (LDL) receptor-related protein 5/6 (LRP5/6). Different secreted proteins, including soluble FRP-related proteins (sFRP), Wnt inhibitory factor-1 (WIF1) and Dickkopfs (Dkk) – isoforms 1, 2, 3, and 4 – prevent ligand-receptor interactions and consequently inhibit the Wnt signaling pathway. Alterations of the Wnt signaling pathway and its regulatory molecules including Dkk-1 and sFRP have been shown to play an important role in bone turnover abnormalities associated with osteoporosis, arthritis, multiple myeloma and bone metastases from prostate and breast [31]. Immunoassays for circulating Dkk-1 have recently been developed. Serum Dkk-1 levels have been reported to be increased in clinical situations characterized by depressed bone formation such as multiple myeloma [32]. Circulating levels are also higher in diseases characterized by focal osteolysis, such as multiple myeloma [32], bone metastases from breast or lung cancer [33, 34] and RA [35]. In RA patients, we found that increased levels were associated with a faster radiological progression [36]. Conversely, in
28
Osteoporosis in Men Helical domain
N-telopeptide
N+ α1 α1
OH
C-telopeptide
PYD DPD
K
CTX sequence: EKAHDGGR
O
OH
O OH N N α H H O
O
OH
α CTX (native)
H N
β
N H
OH
O
O
β CTX (isomerized)
Figure 3.1 Schematic representation of C-telopeptide isomerization in type I collagen molecules. Type I collagen is constituted by the association in triple helix of two alpha 1 and one alpha 2 chains except of the two ends (N and C-telopeptides). In bone matrix, type I collagen is subjected to different post-translational modifications including (1) the trivalent crosslinks by pyridinoline (PYD) and deoxypyridinoline (DPD) which make bridges between 2 hydroxylysine residues within the telopeptides of one collagen molecule and one hydroxylysine (PYD) or lysine (DPD) in the helical region of a second collagen molecule and the non-enzymatic isomerization of aspartic acid (D) occurring in the 8 amino acid sequence (CTX) within the C-telopeptides of alpha 1 chains. Isomerization is a spontaneous posttranslational modification which converts the native CTX (CTX) to its isomerized (CTX) form in which the peptide bond between D and the adjacent glycine (G) is made through the carboxyl group in position . The urinary ratio / CTX provides a biological index of type I collagen maturation.
patients with osteoarthritis of the hip, a clinical situation characterized by focal sclerosis of subchondral bone, lower serum Dkk-1 levels have been shown to be associated with a decreased risk of joint destruction [37]. At the present time there are no data on circulating Dkk-1 in postmenopausal or male osteoporosis. Similar to the assessment of OPG and RANK-L, it is possible that circulating Dkk-1 does not reflect adequately local bone dynamics. Another issue with the determination of serum Dkk-1 is the fact that Dkk-1 is in platelets and, thus, can be released in the serum during the process of clotting [38], confounding the interpretation of circulating levels. More recently, an immunoassay measuring sclerostin, an osteocyte secreted factor inhibiting the Wnt signaling pathway, has been developed on a multiplex platform (Meso Scale Discovery, Gaithersburg, MA), but no data on circulating levels have yet been reported.
Post-Translational Modifications of Bone Type I Collagen Post-translational modifications of type I collagen, especially those derived from non-enzymatic age-related processes, have been suggested to reflect age-related changes of
the mechanical properties of bone tissue. Non-enzymatic modifications include the advanced glycation end products (AGE) such as the cross-link pentosidine and the isomerization of aspartic acid residues. This latter modification results in the conversion of the native alpha form of CTX ( CTX) to its beta isomerized peptide ( CTX) (Figure 3.1). A series of ex-vivo studies [39] performed on animal or human bone specimens has shown that changes in pentosidine and CTX isomerization were associated with mechanical properties independently of BMD. The ratio between urinary CTX and CTX provides a non-invasive tool which allows for the detection of alterations in bone matrix maturation. Increased urinary / CTX ratio has been reported in conditions characterized by localized increased bone turnover, such as Paget’s disease and metastatic bone diseases [40, 41], consistent with the presence of ‘younger’ poorly matured type I collagen molecules in the affected bone sites. Immunohistochemistry studies also showed altered CTX isomerization in the abnormal woven matrix, which is comprised of younger, poorly matured collagen molecules [40, 41]. A recent study found increased urinary / CTX ratio in the type I collagen genetic disorder osteogenesis imperfecta, which may be indicative of the qualitative defects of bone tissue observed in these
C h a p t e r 3 Assessment of Bone Turnover in Men Using Biochemical Markers l
29
Table 3.2 Type I collagen and the risk of fracture in older men: The Mr Os study RR of fracture (95% Cl), age and clinic adjusted
RR of fracture, age, clinic and hip BMD adjusted
Non-spine
Non-spine
Hip
Hip
CTX/cr
1.43(1.10;1.86)
1.91(1.14;3.20)
1.10(0.83;1.50)
1.02(0.56;1.85)
CTX / CTX ratio
1.11(0.84;1.48) 1.40(1.07;1.82)
1.22(0.70;2.11) 1.93(1.14;3.28)
0.89(0.66;1.18) 1.37(1.05;1.80)
0.72(0.39;1.33) 1.85(1.00;3.40)
Mr Os study included 5995 men (mean age at baseline: 73.7 years). During the 5 yr follow-up, 431 men documented non-spine fractures. Baseline urine was available on 427 fracture cases, including 80 hip fractures and on 1013 randomly selected subjects. The table shows the risk of non-spine and hip estimated by Cox models for baseline urinary excretion of CTX corrected for creatinine, CTX corrected for creatinine and the / CTX ratio. From Bauer et al. Osteoporosis Int 2008; 19, supp. 2;S244 (with permission).
patients [42]. In postmenopausal women, it was found that increased urinary / CTX ratio was significantly associated with increased fracture risk independently of both hip BMD and overall bone turnover. More recently, a high / CTX ratio was shown to be predictive of non-spine and hip fracture, independent of hip BMD, in elderly men participating in the Mr Os study (Table 3.2) [43]. The effects of antiresorptive therapy and PTH on urinary / CTX ratio in postmenopausal women have recently been investigated in post hoc analyses of interventional studies. The bisphosphonates, alendronate at a dose of 10 or 20 mg/ day and ibandronate, both induce a decrease of / CTX ratio, suggesting increased bone collagen maturation [44]. Such changes were not observed with treatments that are less potent suppressors of bone turnover, such as raloxifene [44] or calcitonin [45]. Conversely, treatment with PTH 1-84 for 1 year, followed by 1 year of placebo or alendronate was associated with an increase of / CTX ratio [46], suggesting the formation of younger, less mature bone matrix with PTH. All together, these data suggest that the urinary / CTX ratio may indeed reflect alterations of bone collagen maturation in women and men with osteoporosis and provide additional information on bone strength that is not captured by BMD or conventional bone turnover markers.
New technologies for discovery and assay bone markers The currently available bone markers have been developed using a conventional candidate approach based on known physiopathological pathways, enzymes from osteoblast or osteoclast and proteins purified from bone matrix. It is likely that the improvement of proteomic technologies, such as surface enhanced laser desorption ionization (SELDI) and matrix-assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF), coupled with bioinformatics, will provide a means to analyze a broad array of proteins and to identify novel markers. Such a strategy has recently been applied to define a serum biomarker profile which was able to differentiate postmenopausal women with high
or low bone turnover [47]. Ultimately, such strategies may result in identifying a panel of a few independent markers which, when combined, may improve the sensitivity and specificity to detect patients at high fracture risk. Multiplex automated technologies allowing the simultaneous measurement of these biochemical markers in a low sample volume will then be required for easy use. Illustrating this point, an automated platform with high analytical precision has been recently developed for the simultaneous measurements of osteocalcin, CTX, PINP and PTH in only 20 microliters of serum [48].
Factors influencing BTM levels in men Bone turnover is subject to the influence of many factors, some of which have been comprehensively examined. Strong correlations between bone turnover marker (BTM) levels in male twins indicate that hereditary factors are an important determinant of the bone turnover rate in men [49]. By contrast, ethnic differences in the BTM levels are relatively weak [50]. Bone turnover demonstrates circadian variation. For most BTM, acrophase (peak time) is similar in both sexes. In contrast, the average concentration (mesor) and magnitude of diurnal variation (amplitude) vary between men and women [51]. Levels of most BTMs increase during the night and attain highest values between 04:00 and 06:00 hours. Circadian variation is greater for bone resorption than for bone formation. In men, diurnal variation is similar for different bone resorption markers. Variation of bone formation is lower – 5 to 20%. Mechanisms that govern circadian variability of BTM are not known. Food consumption accentuates circadian variation of bone resorption, whereas fasting significantly attenuates the circadian pattern probably due to the increased secretion of glucagon-like peptide-2 which is stimulated by food intake [52]. It suggests that the circadian variation of bone resorption is only partly inherent and, to a major extent, determined by the exogenous nutritional regulation.
30
Osteoporosis in Men
Data on the seasonal variation of BTM in men are limited. However, some studies show increased bone resorption in winter in older but not in younger men [53]. The winter increase in bone turnover is believed to be related to vitamin D deficiency and secondary hyperparathyroidism. Therefore, it is more prominent in the elderly who are more likely to become vitamin D deficient. Low 25-hydroxyvitamin D and high PTH levels are also associated with higher BTM levels regardless of the season in older men. This association is observed especially in institutionalized persons who have severe vitamin D deficiency, high PTH concentration and markedly increased BTM levels [54]. Sex steroid hormones are major determinants of bone turnover in older men. Low concentration of the bioavailable fraction of 17-estradiol is strongly associated with higher levels of the markers of bone formation and bone resorption and this effect is observed in men from the general population [55, 56]. In contrast to the bioavailable fraction, total 17-estradiol is not correlated with BTM levels. Men with overt hypogonadism, as defined by a decreased concentration of total, free or bioavailable testosterone, had slightly higher levels of bone resorption markers but not of bone formation markers [57]. By contrast, in the general population, the association between the testosterone level (free, bioavailable) and the BTM levels is weak or not significant. Interventional studies also show that 17-estradiol inhibits bone resorption in men much more strongly than testosterone [58]. In this short-term study (3 weeks), it could also be shown that 17-estradiol and, to a lesser extent, testosterone are direct stimulators of bone formation. Tobacco smoking was associated with slightly higher levels of bone resorption markers but not of bone formation markers [59]. It suggests that elevated bone resorption not matched by a parallel increase in bone formation could underlie tobacco-induced bone loss. However, specific mechanisms responsible for the increase in bone resorption in smokers are not elucidated. This mechanism could include vitamin D deficiency, hypercortisolemia, increased catabolism of 17-estradiol, stimulation of bone resorbing cytokines by components of smoke, as well as other factors which are more frequently observed in smokers, although not induced by smoking itself (e.g. low body mass index, high alcohol intake, sedentary lifestyle). Most studies show that alcohol abuse is associated mainly with the inhibition of bone formation (confirmed by bone histomorphometry) and lower concentrations of bone formation markers (especially OC) [60, 61]. By contrast, data on bone resorption markers levels are divergent. These data suggest that an imbalance between bone resorption and lowered bone formation may underlie the low BMD observed in those who abuse alcohol. However, data on bone resorption should be interpreted cautiously. Heavy drinkers often have lower muscle mass associated with lower urinary creatinine excretion. In these persons, adjustment of the urinary excretion of bone resorption markers for urinary creatinine may falsely increase their levels. Ethanol withdrawal results in
a progressive normalization of bone turnover rate [62]. The actions of alcohol on bone include the following potential mechanisms: a direct effect of ethanol on bone cells, undernourishment, hepatic cirrhosis, hypogonadism, vitamin D deficiency, hypercortisolemia [63]. Any one or combination of these discrete mechanisms could be responsible for negative calcium balance in alcoholism. Immobilization is associated with an acceleration of bone turnover, especially of bone resorption. The rapid increase in bone resorption is observed very early during experimental bed rest in young healthy men and is not followed by a parallel increase in bone formation [64]. During the first weeks after acute spinal cord injury, bone resorption increases dramatically to several times higher than the upper limit of the normal range, whereas bone formation increases only slightly [65]. It suggests a severe imbalance between these two processes which probably underlies the rapid bone loss associated with immobilization. In elderly persons with prolonged, very low physical activity (including the sick and bedridden), bone turnover rate is higher – both bone formation and bone resorption [66, 67]. In this group, there are probably several mechanisms responsible for the increase in bone turnover: immobility itself, underlying diseases, undernourishment or vitamin D deficiency due to a very low sunlight exposure. Leisure daily physical activity has no major effect on bone turnover. By contrast, regular intensive sport training in young healthy men (long distance runners, premier league soccer players) is associated with accelerated bone turnover [68, 69]. Prostate cancer is frequent in men. During its natural course, bone metastases often develop and are associated with higher BTM levels, mainly ICTP, bone ALP, NTX and --CTX (native non-isomerized CTX-I reflecting the most recently synthesized type I collagen molecules) and, to a lesser extent, P1NP, -CTX or OC [70]. In these patients, bone resorption is increased to a greater extent than bone formation. High ICTP levels suggest an important role of matrix metalloproteinases in the formation of bone metastases [71]. BTM levels increase sharply with the spread of bone metastases. Elevated BTM levels (NTX, bone ALP) were associated with a higher risk of the skeletal-related events (e.g. pathological fractures, spinal cord compression) regardless of the presence of bone metastases or treatment status [70, 72]. Some kinds of androgen deprivation therapy (ADT) used in the therapy of prostate cancer (analogues of luteinizing hormone-releasing hormone, orchiectomy) promptly increase bone turnover resulting in rapid bone loss. In men without bone metastases, BTM increases during the first months, then stabilize at the higher level [73]. Bone resorption increases more than bone formation. Anti-resorptive treatment (neridronate, pamidronate) initiated simultaneously with ADT prevented the increase in BTM [74]. In men who had previously received ADT, bisphosphonates decreased elevated BTM levels in men who did not have
C h a p t e r 3 Assessment of Bone Turnover in Men Using Biochemical Markers l
progression of bone disease, but not in men who experienced a progression of disease [75, 76]. Other anti-resorptive medications (estrogens, raloxifene, diethylstilbesterol) also decreased BTM (or prevented their increase) in men on ADT. Also, in men with metastatic prostate cancer treated with ADT, bisphosphonates induced rapid and protracted inhibition of bone resorption [77]. Corticosteroids are the principal group of drugs increasing the risk of osteoporosis. They promptly inhibit bone formation, a fall in the OC concentration being consistently most significant and most rapid followed by a delayed and weaker decrease in the levels of PICP, PINP and bone ALP [78, 79]. Bone resorption can increase, especially after treatment exceeding 3 months, but data are less consistent. Interestingly, OC concentration increased significantly and normalized after withdrawal of the long-term corticosteroid therapy [80]. Inhaled corticosteroids induced a small but statistically significant decrease in the OC concentration but did not influence other BTM levels [81]. In the analysis of the effect of corticosteroids on BTM, it should be noted that their effect depends on the age of patients and the underlying disease. In bronchial asthma, changes in the BTM reflect the undesirable effect of corticosteroids on bone turnover, while chronic inflammatory diseases, such as rheumatoid arthritis, may themselves induce changes in bone turnover. In these patients, higher bone resorption may confound the effect of corticosteroids on BTM. Corticosteroid-treated patients usually have more severe underlying disease than patients who do not receive corticosteroids. In the longitudinal studies, changes in BTM reflect mainly both the pharmacologic effect of corticosteroids and the severity of the disease at baseline.
Clinical applications of bone turnover markers in male osteoporosis Association of bone mineral density and bone loss with the BTM levels Young men achieve their peak areal bone mineral density (aBMD) in young adulthood. Attainment of peak BMD (growth arrest, consolidation) is associated with a reduction in bone turnover and a decrease in BTM levels. However, the age of peak aBMD varies according to the skeletal site (from 20 to 25 years at the hip, up to 40 years at distal radius). This is probably the reason why, in young men, the correlation of BTM with aBMD and trabecular microarchitectural parameters is weak or, most frequently, not significant [82, 83]. In older men, who are in the phase of bone loss, BTM levels are weakly but significantly correlated with aBMD [82, 83]. The older the age group, the stronger is the correlation, probably signifying age-related acceleration of bone loss in men. The difference between average aBMD in men with low and high BTM levels was greater at the predominantly trabecular
31
skeletal sites than for the predominantly cortical sites. In this group, BTM correlated weakly but negatively with trabecular bone volume and trabecular number. In older men, higher BTM levels are associated with slightly more rapid bone loss in some [84, 85], but not all [86] studies. These data suggest that bone loss in men is determined mainly by an acceleration of bone turnover driven by a slight increase in bone resorption which is not matched by a parallel increase in bone formation. This imbalance results in age-related bone loss. However, the link between BTM levels and remodeling events were studied mainly in women and it is not certain that they can be directly extrapolated in men. In some men, osteoblast insufficiency may be a main determinant of bone loss. To our knowledge, no study has reported lower aBMD and slower bone loss in men with low concentrations of bone formation markers. Continuous periosteal apposition influences bone size, aBMD and calculated rates of bone loss. However, it is not reflected by BTM levels. Therefore, increased BTM levels seem to reflect mainly bone loss at endosteal surfaces [84]. However, methodological limitations of the applied approach should be recognized. The calculation of endosteal bone loss has been based on the geometric approximations and has not been confirmed by a more direct method. In men, bone loss is slow, especially before the age of 70. Therefore, its individual values during a short-term follow up may be biased by a measurement error, especially in men less than 70. By contrast, a single BTM measurement does not necessarily reflect the bone turnover rate during a long-term follow up. BTM levels reflect the overall rate of bone turnover, whereas the rate of bone loss may vary according to the skeletal site. At every skeletal site, bone metabolism is influenced by systemic factors (e.g. hormones) and by local factors (e.g. mechanical load) which may differently affect the bone turnover and the rate of bone loss according to the skeletal site. Furthermore, data concerning the lumbar spine are inconclusive because its aBMD increases with age due to progression of osteoarthritis. Thus, the weak overall correlation between bone loss and BTM in men may result from both biological determinants and methodological limitations.
Prediction of the Fragility Fractures by BTM in Elderly Men Few studies have assessed the use of BTM for the prediction of osteoporotic fractures in men. In a prospective nested case-control study from the Dubbo cohort (cases – 50 men with incident symptomatic low trauma fractures; controls – 101 men free of any bone disease who did not take any medication affecting bone disease and had not had fractures in the past), increased serum ICTP concentration (fourth quartile) was associated with an almost threefold higher risk of fracture [87]. ICTP remained predictive of fractures after adjustment for aBMD and other confounders. It predicted all fractures analyzed jointly as well as
32
Osteoporosis in Men
hip fractures, vertebral fractures and other fractures analysed separately. Serum CTX and PINP concentrations did not predict fractures. However, this study has several limitations. Exclusion from the control group of men with prevalent fractures and concomitant major diseases, mainly bone diseases, can overestimate the difference between the groups. Ascertainment of the incident vertebral fractures was suboptimal. Time of blood sampling was not standardized, which can affect markedly CTX levels. In the MINOS cohort composed of 790 men aged 50–85 years and followed up from 3 to 90 months, 77 incident fractures (including 27 radiographically determined vertebral fractures) occurred in 74 men [84]. None of the large panel of BTM measured at baseline (OC, bone ALP, PINP, serum and urinary CTX, free and total DPD) predicted fractures regardless of the statistical model used (continuous log-transformed BTM levels, various thresholds, adjustment for confounders including aBMD, analysis limited to major fragility fractures). The principal limitation of this study was the low number of the incident fractures. The large dropout for longitudinal spine x-rays could underestimate the number of incident vertebral fractures. In two prospective nested case-control analyses from the Mr OS cohort composed of men aged 65 years and older and followed up for 5 years on average (cases – 427 men with incident non-spine fractures; controls – 943 and 1013 randomly selected men, respectively), increased serum concentrations of PINP, TRACP5b and CTX as well as increased urinary excretion of CTX and of CTX (highest quartile) were each not independently associated with the risk of hip or non-spine fractures in multivariate models adjusted for other confounders including femoral neck aBMD [43, 85]. By contrast, as previously indicated, increased / CTX ratio was associated with a twofold higher risk of hip and non-spine fracture also after adjustment for BMD [43]. BTM levels reflect overall bone turnover rate, whereas the / CTX ratio is supposed to reflect the degree of collagen maturation. The fact that the increased / CTX ratio, but not the conventional BTM, predicted fracture suggests that impaired collagen maturation may be associated with an increased bone fragility in elderly men independent of BMD and overall bone turnover rate. Increased levels of conventional BTM do not seem to be useful to predict fractures in older men in contrast to women. Several possible hypotheses can be put forward to explain this observation. Negative results may be related to the markers themselves. In older men, bone formation markers remain stable or increase only in very old men and are much lower than in postmenopausal and older women [88]. Importantly, even in women, bone formation markers were less predictive of fracture than bone resorption markers [1, 2]. Bone resorption increases with age in men, but urinary DPD excretion is markedly lower in older men than in women of similar age [88]. It suggests that few men can have BTM levels sufficiently high to affect substantially
bone strength. Thus, the so-called ‘increased bone turnover’ defined by the highest quartile may correspond to lower BTM levels and lower rate of bone turnover in absolute terms (e.g. number of bone remodeling units) and, consequently, to a lower damage of bone tissue in men than women (smaller bone loss from the peak bone mass, less cortical thinning, less deterioration of the trabecular microarchitecture, smaller deficit in bone mineralization). Furthermore, it has not yet been proven that the relationship between bone turnover rate and the loss of bone mass and strength is the same in men and in women. It is not clear whether the same BTM reflect similarly the degradation of bone matrix in both sexes. Urinary DPD excretion increases with age in men. This increase is also observed for DPD adjusted for the glomerular filtrate volume, which indicates that it is not an apparent increase due to the agerelated decrease in muscle mass and urinary creatinine [83]. By contrast, age-related increase in the serum and urinary levels of NTX and CTX is weaker or not significant in men (in contrast to women) [83, 89], whereas serum ICTP increases [86]. Thus, enzymatic mechanisms and principal products of degradation of bone type I collagen may be different in men and in women. Bone turnover rate reflects mainly metabolic status of the trabecular bone. However, men have larger bones and higher cortical mass which can have a strong protective effect but is not reflected by the BTM levels. The peri osteal apposition can also reduce the loss of bone strength and again, it is not reflected by the BTM levels [84]. Furthermore, the above studies have assessed mainly or exclusively non-spine fractures. However, vertebral fractures may be more dependent on bone fragility, whereas non-spine fractures may depend more on the trauma. It should be also recognized that a fracture is a rare event and a long-term follow up is needed to collect a number of fractures high enough to attain sufficient statistical power. However, the predictive power of a single BTM measurement may decrease with time in long-term studies. Other studies also need to be mentioned. In men aged 70 and over, baseline carboxylated OC (COC) to total OC ratio (COC/TOC) was lower in those who subsequently sustained a fracture than in men who did not [90]. In men and women analyzed jointly, low COC/TOC predicted fractures in a short-term but not in long-term study, however, these data were not adjusted for aBMD. Vitamin K is necessary for the gammacarboxylation of OC. Therefore, decreased COC/TOC may reflect vitamin K deficit. However, it is not clear if this association reflects the effect of vitamin K on bone metabolism or is a by-stander of the association between nutritional deficits and increased bone fragility. Homocysteine (Hcy) is not a marker of bone turnover, however, it has appeared as an indicator of fracture risk and this association was stronger in men than women [91, 92]. However, high Hcy concentration was predictive of fractures mainly in old and frail elderly. High Hcy concentration
C h a p t e r 3 Assessment of Bone Turnover in Men Using Biochemical Markers
33
l
was associated mainly with increased risk of hip fracture and some of these analyses were not adjusted for aBMD. Thus, Hcy may simply reflect poor health status, unhealthy lifestyle and nutritional deficits that influence aBMD, risk of fall and mortality. Hcy has been supposed to be a marker of the ultrastructure of collagen, because it inhibits lysyl oxidase, an enzyme necessary for the synthesis of cross-links [93]. Impairment of collagen cross-linking may interfere with bone mineralization, compromise trabecular organization and reduce bone strength [94]. Hcy also stimulates differentiation and function of osteoclasts [95]. Thus, the mechanism underlying the association between the Hcy level and fracture risk remains to be elucidated: impairment of the ultrastructure of bone collagen matrix, increased bone turnover, lower aBMD, nutritional deficits, or frailty due to the poor general health status and propensity to fall? In summary, the currently available BTM levels are not independently related to the risk of fragility fracture in men. From the pathophysiological point of view, it suggests that higher bone turnover rate (as assessed in comparison with the levels observed in older men) is not associated with the increased fragility in older men. From the clinical point of view, it means that the measurement of BTM levels cannot be recommended for the assessment of the fracture risk in older
men in clinical practice. Biochemical assessment of qualitative modifications of bone matrix, which may be associated with higher bone fragility in men, needs further studies.
Effect of anti-osteoporotic treatment on BTM in men Data on the changes induced by anti-osteporotic treatment in men are limited because there are few studies on the pharmacological treatment of osteoporosis in men.
Testosterone Replacement Therapy (TRT) Effect of testosterone replacement therapy (TRT) on bone turnover in hypogonadal men depends on the initial hormonal status, normalization of testosterone level during treatment and the treatment duration. TRT is efficient in men with overt hypogonadism, but not in men with borderline decreased testosterone concentration. TRT is not efficient if testosterone level has not been normalized. The effect of TRT may also depend on the initial BMD and bone turnover rate. TRT reduces bone resorption moderately but promptly and significantly (Figure 3.2) [96, 97]. The decrease was
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Figure 3.2 Effect of transdermal testosterone (T) gel and testosterone patch treatment on urinary N-terminal crosslinking telopeptide of type I collagen / creatinine ratio and serum osteocalcin concentration in 227 hypogonadal men aged 19 to 68 (mean SE). The subjects were initially (days 0 to 90) randomized to three groups: T patch (closed triangles), T gel 50 mg/day (closed squares), and T gel 100 mg/day (closed circles) (left panel of each graph). Based on the serum T levels, the dose of T gel was adjusted upwards or downwards to 75 mg/day at day 90 if the serum T level was below or above the adult male range, respectively: T gel 50 to 75 mg/day (open squares), T gel 100 to 75 mg/day (open circles) (right panel of each graph). (Wang et al. Effects of transdermal testosterone gel on bone turn over markers and bone mineral density in hypogonadal men. From Wang et al., Clin Endocrinol 2001; 54:739–750 (with permission).
Osteoporosis in Men
Anti-Resorptive Treatment Studies in men concern principally alendronate and risedronate, which increase aBMD and decrease BTM. Both eugonadal and hypogonadal men were recruited for these studies. Bisphosphonates induce a rapid decrease in BTM levels, detected after 1 month of treatment [99, 100]. After 3–12 months, decrease in BTM levels attains 50–60% for bone resorption and 15–40% for bone formation (Figure 3.3) [99, 101]. Then, BTM levels remain stable. Decrease in BTM is comparable for 5 and 10 mg alendronate and 5 mg risedronate. In osteoporotic men, treatment with 35 mg risedronate weekly decreased serum bone ALP concentration by 25–30%, serum CTX concentration by about 50% and urinary NTX excretion by about 35% [102]. This decrease was observed after 3 months of treatment (earliest time point tested), then BTM levels remained relatively stable. In patients receiving at least 7.5 mg oral prednisone daily, alendronate and risedronate decreased BTM in patients receiving glucocorticoids for less than 3 months and in patients treated for more than 6 months. However, BTM were analyzed jointly in both sexes. In hypogonadal osteoporotic men receiving an adequate TRT, alendronate decreased urinary DPD excretion promptly and rapidly [103]. In men with Klinefelter’s syndrome, intravenous ibandronate decreased the bone turnover rate and increased
Placebo 5 mg of alendronate 10 mg of alendronate
50 Urinary N-Telopeptides of Types I Collagen (pmol of bone collagen equivalents/µmol of creatinine)
significant for more specific bone resorption markers such as DPD or NTX-I, but not for hydroxyproline which is not specific for bone and poorly sensitive. Decrease in the urinary excretion of bone resorption markers per mg urinary creatinine is partly related to the increase in muscle mass induced by testosterone. Therefore, data expressed per glomerular filtrate volume and serum markers of bone resorption can be more reliable, although experimental data are limited. The overall effect of TRT on bone formation markers, as presented in the metaanalysis of Isidori et al., was not significant [98]. However, these data should be interpreted cautiously. Apart from the aforementioned general limitations, the dynamics of bone formation during TRT should be taken into account. Bone formation markers increase during the first months of TRT, then plateau [96, 97]. This increase may reflect the direct stimulatory effect of TRT on bone formation. Later, TRT-induced decrease in bone resorption was followed by a decrease in bone formation which may reflect general slow down of bone turnover. These studies present certain limitations. Groups are small and heterogeneous (etiology, age of diagnosis of hypogonadism, age at the beginning of the study, duration of TRT before the study, doses of TRT and way of administration, degree of normalization of the testosterone level, duration of TRT during the study). A placebo group is not always included. TRT-induced increase in aBMD may reflect mainly the stimulation of bone formation in young men and the inhibition of bone resorption in the elderly.
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Figure 3.3 Effects of alendronate on biochemical markers of bone resorption in 259 patients (top panel) and bone formation in 264 patients (bottom panel) receiving an average daily dose of at least 7.5 mg of prednisone (or its equivalent). All values are means (SE). The solid horizontal lines indicate the mean reference values for premenopausal women, and the dotted horizontal lines 1 SD above and below the mean. The values were significantly decreased at 48 weeks in the patients receiving 5 mg of alendronate and those receiving 10 mg (P 0.001). From Saag et al. N Engl J Med. 1998; 339:292–299 (with permission).
aBMD [104]. However, after withdrawal of the treatment, BTM levels returned to the pretreatment levels and aBMD decreased. In a group of human immundeficiency virus (HIV)-infected men treated with highly active antiretroviral therapy who had BMD T-score 0.5, annual zoledronate administration decreased urinary NTX excretion by about 60% and serum concentrations of OC and CTX by 50–60% compared to the placebo group (OC and CTX-I were not measured at baseline) [105]. In 28 men with idiopathic osteoporosis, nasal calcitonin 200 IU daily administered for 1 year reduced bone turnover [106]. Decrease in bone resorption was significant after 3 months and attained 50% after 12 months. It was followed by a milder decrease in bone formation markers which became significant after 6 months.
C h a p t e r 3 Assessment of Bone Turnover in Men Using Biochemical Markers l
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P � 0.001 TPTD20 vs 40 (Bone ALP, PICP, NTX, CTX); P < 0.01 (TDPD) at all timepoints after baseline
Figure 3.4 Median percent changes from baseline in biochemical markers of bone formation (top) and resorption (bottom) from baseline to endpoint for observed cases at 1, 3, 6, and 12 months. (Bone ALP – bone alkaline phosphatase, PlCP – procollagen I carboxy-terminal, NTX/CR – urinary N-telopeptide/creatinine ratio, fDPD/CR – free deoxypyridinoline/creatinine ratio, TPTD20 – teriparatide 20 g; TPTD40 – teriparatide 40 g). From Orwoll et al. J Bone Miner Res 2003; 18:9–17 (with permission).
Treatment with Bone Formation Stimulating Agents Effect of recombinant human parathyroid hormone (1–34) (rhPTH-[1–34]) on BTM levels was assessed in two randomized placebo-controlled studies [107, 108]. Markers of bone formation increase rapidly with a significant increment of PINP after 1 month of treatment followed by an increase in bone resorption markers (Figure 3.4). This rapid increase in bone formation indicates that rhPTH-(1–34) directly stimulates osteoblastic cells. After 6–9 months of treatment, BTM attain the maximum (50–250% above baseline), then slightly decrease but remain elevated. By contrast, during combined treatment (alendronate and rhPTH-[1–34]) started 6 months after the beginning of the anti-resorptive treatment, the increase in the serum concentrations of the bone formation markers induced by rhPTH(1–34) were lower and the increase in aBMD at the spine
and femoral neck was less than after rhPTH-(1–34) alone [109] (Figure 3.5). In growth hormone (GH) deficient men, recombinant human GH increases bone resorption and bone formation [110, 111]. BTM increase after 4 days of treatment, attain peak values (50–300% above baseline) after 6– 12 months, then decrease. BTM decrease despite sustained elevated histomorphometric parameters of bone formation and resorption. During GH therapy, changes in BTM and aBMD did not correlate, probably because BTM increase from the beginning of treatment, whereas aBMD decreases slightly then increases. A similar pattern of changes in BTM levels (increase then decrease) was found in adults independent of the etiology of GH deficiency. The studies on GH treatment present several limitations including small groups, both sexes analyzed jointly, no placebo group in most cases, different doses of GH, different regimens and treatment duration. Thus, these results should be interpreted cautiously.
Osteoporosis in Men
36
Serum osteocalcin
400
Serum PNP 1200
300 Percent change
Serum N-telopeptide
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1000 800
200
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100
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12 18 24 Time (months)
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–100
–100 0
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Figure 3.5 Mean percent change from baseline for serum OC, P1NP, and NTX in men receiving alendronate alone (square), human PTH(1–34) alone (rhombus), or both (circle). PTH was begun at month 6. Data are plotted as the mean (SE). Error bars that are not seen are contained within the symbols. From Finkelstein JS et al. J Clin Endocrinol Metab 2006; 91:2882–2887 (with permission).
The data on the BTM levels during the anti-osteoporotic treatment are limited. Overall, they show that the treatmentinduced changes in the BTM levels are similar in men and women. However, potential use of the BTM in the monitoring of the anti-osteoporotic treatment in clinical practice has not been studied specifically in men. For instance, it has not been assessed if the change in the BTM levels can be used for the prediction of the increase in BMD or the decrease in the fracture risk during the treatment. There is also no study which has assessed the potential use of BTM to improve the compliance to the anti-osteoporotic treatment in men.
Conclusion Studies carried out during recent years have improved our knowledge about BTM in men and their age-related changes. Bone loss in men is correlated significantly with the BTM levels at baseline. It indicates that high bone turnover is a determinant of the accelerated bone loss in men. This correlation is poor and BTM measurements cannot be used for the prediction of the accelerated bone loss in men similarly to the data found in women. Weakness of the association between the BTM levels and the rate of bone loss can depend on the methodological problems. However, it can also reflect the weakness of the concept of bone loss calculated using BMD meaured by dual-energy x-ray absorptiometry (DXA). Conventional BTM do not predict fractures in older men. However, it is not clear if it reflects the real lack of the impact of the bone turnover rate on bone fragility in men. Men have higher skeletal mass and a milder age-related acceleration of bone turnover than women. Thus, it is plausible that only a few men attain the bone turnover rate which is dangerous for bone solidity, however, in this group, high bone turnover may be a real determinant of the increase in bone fragility. Data on
the biochemical bone markers which reflect qualititative aspects of bone tissue are scanty. Few studies concern the effect of the anti-osteoporotic medications on BMD and fracture risk specifically in men. Overall, the effect of these drugs on BTM levels is similar in men as in women. However, there are no studies which have assessed the potential utility of the BTM in the evaluation of the efficacy of the anti-osteroporotic treatment in men, e.g. is the treatment-induced change in the BTM levels predictive of the subsequent increase in BMD and of the subsequent decrease in the fracture incidence (as it has been observed in post-menopausal women)? In particular, it is not known if the BTM can be used to improve persistence with the anti-osteoporotic treatment in men.
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90. H. Luukinen, S.M. Kakonen, K. Pettersson, et al., Strong prediction of fractures among older adults by the ratio of carboxylated to total serum osteocalcin, J. Bone Miner. Res. 15 (2000) 2473–2478. 91. R.R. McLean, P.F. Jacques, J. Selhub, et al., Homocysteine as a predictive factor for hip fractures in elderly persons, N. Engl. J. Med. 350 (2004) 2042–2049. 92. R.A.M. Dhonukshe-Rutten, S.M.F. Pluijm, L.C.P.G.M. de Groot, P. Lips, J.H. Smit, W.A. van Staveren, Homocysteine and vitamin B12 status relate to bone turnover markers, broadband ultrasound attenuation, and fractures in healthy elderly people, J. Bone Miner. Res. 20 (2005) 921–929. 93. B. Raposo, C. Rodriguez, J. Martinez-Gonzalez, L. Badimon, High levels of homocysteine inhibit lysyl oxidase (LOX) and downregulate LOX expression in vascular endothelial cells, Atherosclerosis 177 (2004) 1–8. 94. M. Khan, M. Yamauchi, S. Srisawasdi, et al., Homocysteine decreases chondrocyte mediated matric mineralization in differentiating chick limb-bud mesenchymal cell micro-mass cultures, Bone 28 (2001) 387–398. 95. M. Herrmann, T. Widmann, G. Colaianni, S. Colucci, A. Zallone, W. Herrmann, Increased osteoclast activity in the presence of increased homocysteine concentrations, Clin. Chem. 51 (2005) 2348–2353. 96. J.K. Amory, N.B. Watts, K.A. Easley, et al., Exogenous testosterone or testosterone with finasteride increases bone mineral density in older men with low serum testosterone, J. Clin. Endocrinol. Metab. 89 (2004) 503–510. 97. C. Wang, R.S. Swerdloff, A. Iranmanesh, et al., Effects of transdermal testosterone gel on bone turnover markers and bone mineral density in hypogonadal men, Clin. Endocrinol. 54 (2001) 739–750. 98. A.M. Isidori, E. Giannetta, E.A. Greco, et al., Effects of testosterone on body composition, bone metabolism and serum lipid profile in middle-aged men: a meta-analysis, Clin. Endocrinol. 63 (2005) 280–293. 99. K.G. Saag, R. Emkey, T.J. Schnitzer, et al., Alendronate for the prevention and treatment of glucocorticoid-induced osteoporosis, N. Engl. J. Med. 339 (1998) 292–299. 100. S. Wallach, S. Cohen, D.M. Reid, et al., Effects or risedronate treatment on bone density and vertebral fracture in patients on corticosteroid therapy, Calcif. Tissue. Int. 67 (2000) 277–286. 101. E. Orwoll, M. Ettinger, S. Weiss, et al., Alendronate treatment of osteoporosis in men, N. Engl. J. Med. 343 (2000) 604–610. 102. S. Boonen, E.S. Orwoll, D. Wenderoth, K. Stoner, R. Eusebio, P.D. Delmas, Once-weekly risedronate in men with osteoporosis: results of a 2-year, placebo-controlled, doubleblind, multicenter study, J. Bone Miner. Res. 24 (2009) 719–725. 103. I. Shimon, V. Eshed, R. Doolman, B.A. Sela, A. Karasik, I. Vered, Alendronate for osteoporosis in men with androgenrepleted hypogonadism, Osteoporos. Int. 16 (2005) 1591–1596. 104. J.J. Stepan, P. Burckhardt, V. Hána, The effects of threemonth intravenous ibandronate on bone mineral density and bone remodeling in Klinefelter’s syndrome: the influence of vitamin D deficiency and hormonal status, Bone 33 (2003) 589–596.
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105. M.J. Bolland, A.B. Grey, A.M. Horne, et al., Effects of intravenous zoledronate on bone turnover and BMD persist for at least 24 months, J. Bone Miner. Res. 23 (2008) 1304–1308. 106. G.P. Trovas, G.P. Lyritis, A. Galanos, P. Raptou, E.A. Constantelou, A randomized trial of nasal spray salmon calcitonin in men with idiopathic osteoporosis: effects on bone mineral density and bone markers, J. Bone Miner. Res. 17 (2002) 521–527. 107. E.S. Orwoll, W.H. Scheele, S. Paul, et al., The effect of teriparatide [human parathyroid hormone (1–34)] therapy on bone density in men with osteoporosis, J. Bone Miner. Res. 18 (2003) 9–17. 108. E.S. Kurland, F. Cosman, D.J. McMahon, C.J. Rosen, R. Lindsay, J.P. Bilezikian, Parathyroid hormone as a therapy
for idiopathic osteoporosis in men: effects on bone mineral density and bone markers, J. Clin. Endocrinol. Metab. 85 (2000) 3069–3076. 109. J.S. Finkelstein, B.Z. Leder, S.A. Burnett, et al., Effects of teriparatide, alendronate, or both on bone turnover in osteoporotic men, J. Clin. Endocrinol. Metab. 91 (2006) 2882–2887. 110. N. Bravenboer, P.J. Holzmann, J.C. ter Maaten, L.M. Stuurman, J.C. Roos, P. Lips, Effect of long-term growth hormone treatment on bone mass and bone metabolism in growth hormonedeficient men, J. Bone Miner. Res. 20 (2005) 1778–1784. 111. A.M. Ahmad, J. Thomas, A. Clewes, et al., Effects of growth hormone replacement on parathyroid hormone sensitivity and bone mineral metabolism, J. Clin. Endocrinol. Metab. 88 (2003) 2860–2868.
Chapter
4
Fundamentals of Mineral Homeostasis K. SHAWN Davison1 and DAvid A. Hanley2 1
Laval University, Quebec City, PQ, Canada University of Calgary, Calgary, AB, Canada
2
Introduction
secretion, nerve conduction, muscular contraction, glycogen metabolism, coagulation and plasma membrane adhesion. P is a fundamental component of cellular structure and activity, involved in most energy releasing (adenosine tri phosphate → adenosine diphosphate) or producing (adeno sine diphosphate → adenosine triphosphate) biochemical interactions. Mg acts as an essential cofactor in a number of biological systems that regulate enzyme activities and neuromuscular function. The intricate maintenance of homeostasis often calls for rapid, minute changes in mineral concentration both inside and outside the cells. Given adequate dietary intakes, bone, the intestine and the kidneys are primarily responsible for the maintenance of ECF mineral concentrations within appropriate limits, with both parathyroid hormone (PTH) and 1,25(OH)2 vitamin D3 (1,25D or calcitriol) playing important roles in regulation of these tissues. The precise control of mineral balance afforded from this system per sonifies biological elegance.
The skeleton is a resilient composite of organic and inorganic materials intricately intertwined into a dynamic structure that serves essential mechanical and metabolic functions. The organic materials, most notably type I collagen, pro vide a ductile lattice to which the inorganic components adhere to provide stiffness and resistance to compression. The purpose of this chapter is briefly to review the body’s acquisition and maintenance of the inorganic minerals that compose the skeleton and identify aspects relevant to male skeletal physiology. For the most part, the differences between male and female mineral physiology occur during adolescent growth and after menopause, so most of what is detailed here will not emphasize differences in bone home ostasis between men and women. Of the inorganic constituents of bone, three minerals stand alone in their importance: calcium (Ca), phosphorus (P) and magnesium (Mg). In this discussion, concentra tions of P will be substituted by concentrations of inorganic phosphate (PO4 or Pi) since P does not exist freely in the body. The maintenance of homeostasis for Ca, Pi and Mg is of paramount importance, because these minerals function as essential cofactors and regulators of numerous metabolic processes within the body. The skeleton plays a leading role as a vast, accessible storehouse that ensures essential metabolic functions can continue normally in the blood, extracellular fluid (ECF) and soft tissues. The hydroxy apatite crystal (HAP) is the fundamental inorganic build ing block of bone and is composed primarily of Ca and Pi [Ca10(Pi)6(OH2)]. Mg, while not integrated within the HAP crystal, is found adhering to it, often in a state of equili brium with ECF Mg. Ca is a critical constituent for several important meta bolic functions including cell division, cell adhesion, protein Osteoporosis in Men
Total body stores of essential minerals Calcium The total body stores of Ca for a healthy adult man or woman are approximately 1 kg, ranging higher or lower depending on an individual’s body size and overall degree of bone mineralization. The skeleton possesses about 99% of the body’s calcium within its HAP crystals, with the remainder found in the ECF and soft tissues (10 g). During normal states of bone turnover, approximately 500 mg of Ca is liberated from the skeleton daily with roughly an equal amount reinvested. The ionized fraction 41
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Osteoporosis in Men
42
↑ PTH
Releases calcium and phosphate
Bone
Parathyroid glands sense low blood Ca++ ↑Calcitriol (1,25(OH)2D)
Increased blood Ca++
Sunlight or diet Vitamin D
25(OH)D
Kidney
Calcitriol (1,25(OH)2D)
Liver ♦ Increases calcitriol formation ♦ Decreases excretion of calcium ♦ Increases excretion of phosphate
G-I tract
Increased absorption of calcium and phosphate
Figure 4.1 Hormonal regulation of extracellular calcium. Ca, calcium; PTH, parathyroid hormone; G-I tract, gastrointestinal tract.
of Ca is the metabolically significant fraction responsible for its biologic action.
Phosphate In the healthy adult, there is approximately 550 g of Pi in the total body, with approximately 85% of the total bound with Ca in the HAP crystal and the remaining 15% found in the soft tissues as phosphate esters. A relatively small amount of Pi is found in the ECF – approximately 0.1% of the total.
Magnesium Total body stores of Mg are approximately 25 g in a healthy adult with about 66% located within the skele ton, 33% found in intracellular fluid and 1% in the ECF. Approximately 55% of Mg is in the ionized state, 30% is bound onto a protein and 15% is complexed with other anions. Ionic Mg is primarily responsible for the majority of biochemical activity within the body. Intracellular, soft tissue or total body Mg status is difficult to ascertain within an individual since serum ionized or total Mg reflects only ECF Mg, a miniscule fraction of the total.
Extracellular mineral metabolism – circulating levels Calcium Approximately 900 mg of Ca is found within the different compartments of the extracellular pool in a healthy adult. Ca is purposefully transported among dynamic pools of Ca in blood, bone and from within cells depending on the
particular metabolic needs at any given moment. The move ment of Ca through the ECF is tightly controlled through the coordination of endocrine cells which express the cal cium-sensing receptor (CaSR), modulating the production of hormones which then act on specific cells in kidney, bone and gut to allow for coordinated maintenance of ECF Ca concentrations (Figure 4.1). The prime regulator of ECF Ca is PTH. In optimum (zero) balance within the adult skeleton, bone resorption and formation are equivalent at about 500 mg/d and the net quantity of Ca absorbed by the intes tine each day (200 mg) is also excreted by the kidney into urine (Figure 4.2). Thus, under normal circumstances, net Ca absorption provides a surplus of Ca that considerably exceeds systemic requirements. Dietary intake and the skeletal requirements for Ca fluc tuate widely daily and throughout the lifespan. There is an active coordination of Ca among the intestine, kidneys and the skeleton while the concentration of Ca within the blood is maintained within a narrow range under normal circum stances since serum Ca concentration plays a large role in cellular function. In the ECF compartment, both the ionized and complexed Ca are ultrafilterable which means that they can easily cross semi-permeable membranes. Intestinal Absorption of Calcium Ingestion of Ca-containing foods or supplements is the singular source of Ca for the body. In a typical North American or European diet, dairy products make up the bulk of foods that are responsible for providing Ca to the body, although Ca is found, in lower concentrations, in many other food sources. The intake of Ca can vary widely as can the body’s requirements for this mineral. About 20–60% of the ingested Ca is absorbed, depending on skel etal requirements, age, calcium intake, vitamin D status and
C h a p t e r 4 Fundamentals of Mineral Homeostasis l
43
Ca 1000 mg/d
Dietary intake
Bone (1 kg Ca)
Bone formation and resorption Ca 500 mg/d
Intestine
Extracellular fluid Ca
Intestinal absorption Ca 200 mg/d
Fecal excretion Ca 800 mg/d
Tubular reabsorption Ca 9,800 mg/d Kidney Filtered load Ca 10,000 mg/d
Urinary excretion Ca 200 mg/d Ca 1000 mg/d
Figure 4.2 Calcium balance. Ca, calcium.
the bioavailability of Ca from foods [1]. The duodenum and the jejunum provide vast surface area for the absorption of dietary Ca, accounting for an estimated 90% of the total Ca absorbed. As an individual ages past young adulthood, there is a decrease in the efficiency of the intestinal absorption of Ca, with only an approximate 20–45% of the dietary load of Ca absorbed in older men and women [2]. This decreased abil ity to absorb Ca with aging necessitates increasing dietary intakes as one ages in order to ensure a relatively constant Ca absorption, which is reflected in Ca intake guidelines. Conversely, during periods of very high demand of Ca, such as during rapid skeletal growth and mineralization during childhood and adolescence and during pregnancy and lacta tion in women, the intestinal absorption efficiency can be increased dramatically with as high as 55–70% of dietary calcium absorbed in children and young adults. Generally, when Ca intake falls below 200 mg/d, a nega tive Ca balance occurs where more Ca is leaving the body through the bowels and kidneys than is being absorbed through the intestines. In adults, at least 400 mg/d is needed to obtain zero Ca balance. There is a curvilinear relationship between net calcium absorption and calcium intake which reflects the sum of two absorptive mechanisms – a cellmediated, 1,25D-dependent saturable active transport mecha nism and a passive, diffusional paracellular absorption that is driven by transepithelial electrochemical gradients [1]. When Ca intake is increased past zero balance, there is a decrease in absorption efficiency, with absorption begin ning to plateau at approximately 1000 mg/d. When dietary intake of Ca drops, there is a subsequent increase in the Ca
absorption efficiency causing a greater proportion of the ingested dietary Ca to be retained. In periods of reduced dietary intake or increased skeletal or metabolic demand, 1,25D stimulates the small intestine to increase its effi ciency of Ca absorption. This stimulation involves upregu lation of the active transport of Ca across the duodenum and jejunum. During these periods of upregulation of intestinal absorption, efficiency can shift from 25–45% to 55–70% and result in absorption of a far greater propor tion of the dietary load. Conversely, when dietary Ca intake is high and skeletal and metabolic demands are being met, there is a consequent decrease in the Ca absorption in the intestines. The Ca passed in the feces contains both the unab sorbed fraction of dietary intake, but also Ca that is secreted as part of pancreatic and bile juices as well as through mucosal secretion. Estrogens or hormonal changes during pregnancy or lactation have distinct, vitamin D-independ ent effects at the genomic level on active duodenal calcium absorption mechanisms, mainly through a major upregula tion of the calcium influx channel CaT1. The estrogen effects seem to be mediated solely by estrogen receptor alpha [3]. Renal Transport of Calcium The kidney plays a critical role in the maintenance of Ca homeostasis and over 270 mmol (10 g) of Ca is filtered each day, which represents a larger volume than the entire Ca composition of the ECF and far more than net intesti nal calcium absorption of about 200 mg/d. Of this 10 g of calcium, approximately 1000 mg is directly under the con trol of PTH-regulated reabsorption in the distal nephron
44
Osteoporosis in Men
allowing for intricate control of calcium concentrations within the ECF. In order for a neutral Ca balance to be obtained, approximately 98% of the filtered load must be reabsorbed along the renal tubule. The ultrafilterable com partment of Ca is the complexed and ionized fraction and is freely filtered by the glomerulus, with a Ca concentration of about 1.5 mmol/L. Within the kidney, approximately 70% of the filtered Ca load is passively reabsorbed, following sodium, in the proxi mal tubule. Approximately 20% is reabsorbed in the loop of Henle, with very little reabsorbed in the thin descend ing and the thin ascending limb – the majority occurs in the thick ascending limb (TALH) where paracellular Ca reabsorption is mediated by Na-K-2 Ca transporter. In the TALH, Ca concentration is monitored via the basolateral membrane cells which contain CaSRs. When the CaSR senses an increase in the peritubular Ca, a lumen positive voltage is induced, which then results in reduced Ca reab sorption, thereby decreasing urinary Ca concentration. The major site of physiologic regulation of urine Ca excretion by PTH is the distal convoluted tubule (DCT), which can reabsorb about 8% of the filtered Ca load. In the DCT, there is active Ca reabsorption moving against an electrochemical gradient. This active transport is respon sive to a low Ca diet, 1,25D and low levels of estradiol to elicit increased Ca conservancy in the kidney and also is the process in which PTH plays a pivotal role. The Ca enters across the apical membrane through the highly selec tive renal epithelial calcium channel 1 (TRPV5), which is selectively more permeable to Ca as opposed to sodium. Once within the cell, cytosolic Ca diffusion is facilitated by Ca binding to calbindin 28 kDa and calbindin 9 kDa. Active release of Ca across the distal nephron plasma membrane is accomplished by the Na–Ca exchanger and a Ca-ATPase (PMCA1b). While Ca generally mirrors Na movement throughout the kidney, in the DCT, reabsorption and excre tion of the two can be actively dissociated if metabolic demands warrant (PTH stimulation in response to low ECF Ca), or treatment with a thiazide diuretic is initiated. The collecting duct absorbs 5% of the filtered load with the final urine content ending up with about 2% of the fil tered load, which can be higher or lower depending on the metabolic and skeletal needs of the body. If dietary Ca is increased, approximately 6–8% of the increase appears in the urine. Reabsorption in the kidney can be affected by a number of factors allowing for intricate control of Ca balance. Volume expansion increases urine Ca and Na excretion through decreased proximal tubule ion reabsorption; volume contraction causes the opposite reactions. Hypercalcemia increases ultrafilterable Ca, decreases the glomerular fil tration rate (GFR) and decreases proximal tubule, TALH and distal convoluted tubule Ca reabsorption resulting in a greater Ca than Na excretion. Ca activation of CaSR in the TALH also decreases Ca reabsorption.
Skeletal Calcium One of the most metabolically important roles that the skele ton plays is as a ‘calcium bank’ which can be drawn upon for maintenance of ionized Ca in the serum. Ultimately, mechanisms of mineral homeostasis will operate to main tain ECF Ca which occurs at the expense of reduced bone mineral content. Serum Calcium Ca is brought into the serum through ingestion of Cacontaining foods by way of intestinal absorption or through bone resorption in the event of low dietary availability or by renal reabsorption. Excess Ca is eliminated from the serum primarily through filtration through the renal glomer ulus and secreted along various segments of the nephron. Modest amounts are secreted into the intestine and skin losses are minimal. The other major repository for calcium is bone and, failing that, precipitation with an anion (usually phosphate) into soft tissues. The concentration of ECF calcium is approximately 103 M, with 50% of the fraction ionized, 40% protein-bound and 10% complexed with citrate or Pi ions. About 90% of the protein-bound Ca is bound to albumin, with the remain der bound to globulins. Total Ca concentration in normal serum is between 8.5 and 10.5 mg/dL (2.12–2.62 mmol/L in SI units), above which is considered hypercalcemic and below hypocalcemic. The normal concentration of ionized Ca is 4.65–5.25 mg/dL (1.16–1.31 mmol/L). Of the two meas ures of serum Ca, the more reliable, and biologically active, measure of is that of ionized Ca: total Ca concentration is easily affected by changes in serum protein concentrations, whereas ionized Ca remains relatively stable during fluctua tions in serum protein levels. Since 90% of the protein-bound Ca is bound to albumin, alterations in serum albumin result in dramatic changes in serum calcium measurements. Further, since Ca is prima rily bound to the carboxyl group in albumin, its binding is highly pH dependent. Thus, when acute acidosis is present, this decreases the binding of Ca to albumin which results in increased ionized Ca; the opposite is seen in acute alkalo sis. At pH 7.4, each gram per deciliter (10 g/L in SI units) of albumin binds 0.8 mg/dL (0.2 mmol/L) of Ca and this calculation can be used to correct the total serum Ca con centration in patients with abnormally low levels of circu lating albumin. Major shifts in serum protein or pH require direct measurement of the ionized Ca level to determine the true level of physiologically relevant serum Ca.
Phosphorus The extracellular pool of P (orthophosphate) is approxi mately 550 mg. Like Ca, this pool is in dynamic equilib rium with entry and exit via the intestine, kidney, bone and soft tissues (Figure 4.3). An adequate serum P is needed to
C h a p t e r 4 Fundamentals of Mineral Homeostasis l
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P 1240 mg/d
Dietary intake
Bone
Bone formation and resorption P279 mg/d Secretion Intestine Net intestinal absorption P 868 mg/d
Extracellular fluid P
Tubular reabsorption P 4,960 mg/d Kidney Filtered load P 5,828 mg/d
Urinary excretion P 868 mg/d
Fecal excretion P 372 mg/d P 1240 mg/d
Figure 4.3 Phosphorus balance. P, phosphorus.
ensure sufficient ions to be available for normal mineraliza tion. In zero balance, fractional net phosphorus absorption is about two-thirds of P intake; this amount represents the vast excess over systemic requirements and this excess is excreted into the urine. Concentrations of Pi are less rigidly maintained than that of Ca and Mg. Pi serum fluctuates widely based on sex, age, diet, growth rate and hormone levels. Serum levels of Pi are primarily regulated via changes in the efficiency of reabsorption of filtered Pi in the kidneys and are hormo nally mediated. Intestinal Absorption of Phosphorus Phosphate is found in almost all food groups, as it is a major constituent of all cells. Intake of Pi is seldom less than 620 mg/d as absorption is directly related to dietary Pi ingestion. Pi negative balance typically occurs at intakes lower than 310 mg/d, which is usually only observed during strict caloric restriction. With typical dietary intakes (775– 1860 mg/d) approximately 60–80% of ingested Pi is absorbed in the intestine and passed into the circulatory system. The absorption of phosphate in the intestine is far less rigidly regulated than that of Ca. Passive transport in the intestine is mediated via luminal Pi concentration as well as an active, cell-mediated Pi transport that is regulated by 1,25D. Transepithelial Pi transport must overcome existing electrochemical gradients as the ion moves from the intes tinal lumen into the enterocyte. Entry through the brush border is through an energy dependent transport process or through a secondary active transport process coupled to the flux of another ion such as sodium.
Renal Transport of Phosphorus The concentration of ECF Pi is primary regulated via the kidney with about 85% being ultrafiltrable. In the kid neys, the threshold Pi reabsorption in the proximal tubule is essentially the setpoint that defines the fasting serum Pi concentration, which is also, not coincidentally, the set point regulated by PTH. Urine Pi excretions total about 750–1000 mg/d depending on dietary intake and metabolic demand. Approximately 85% of the Pi reabsorption occurs in the proximal tubule with the rate-limiting step located in the apical domain of the proximal tubule cells, which is also the site of active Na–Pi transport. Thus, about 12.5% glomerular filtrate is excreted in the urine. Skeletal Phosphorus Low Pi concentrations may create suboptimal concentra tions and impair mineralization. Adequate Pi is needed to maintain Pi Ca ion product sufficient to support bone mineralization. Pathologically high Pi leads to extraskeletal ossification. Serum Phosphorus P in serum is primarily as inorganic Pi. Within the blood, 55% of the Pi is ionized, 10% is protein-bound and the remaining complexed with sodium, Ca, and Mg.
Magnesium ECF Mg is approximately 250 mg and in bidirectional equilibrium with Mg fluxes across the intestine, kidney,
46
Osteoporosis in Men Mg 300 mg/d
Dietary intake
Bone and soft tissues Net 0 mg/d
Secretion Intestine Net intestinal absorption Mg 100 mg/d
Extracellular fluid Mg
Tubular reabsorption Mg 1,900 mg/d Kidney Filtered load Mg 2,000 mg/d
Urinary excretion Mg 100 mg/d
Fecal excretion Mg 200 mg/d
Mg 300 mg/d
Figure 4.4 Magnesium balance. Mg, magnesium.
bone and soft tissues (Figure 4.4). In zero balance, the Mg derived from the net intestinal absorption, approximately 100 mg/day, represents a systemic surplus and is quantita tively excreted. The protein-bound fraction of Mg is bound to the carboxyl groups of albumin and is influenced by pH, similarly to that of calcium. The ionized fraction of Mg is biologically active. Intestinal Absorption of Mg As a major intracellular cation, Mg is found in many food sources and Mg intake is generally adequate, as it is proportional to caloric intake. Net intestinal Mg absorp tion increases in direct proportion to dietary Mg intake. It takes 28 mg/d of Mg of absorption to exceed excretion. During usual intake (168–720 mg/d) fractional absorption is 35–40%. Pi forms a non-absorbable complex with Mg and thereby decreases Mg absorption. Reductions in Mg intestinal absorption can also occur with disease or chronic laxative abuse. Different from Ca and P intake, Mg intake is not under significant regulation by 1,25D. In the small intestine and colon, absorptive and secretory Mg fluxes have voltage dependent and independent components – both through cel lular and paracellular pathways. In the intestinal lumen, Mg concentration drives passive diffusional absorption along the paracellular pathway. Renal Transport of Mg Ionized and complexed Mg is about 70% of the total serum Mg and constitutes the ultrafilterable portion. Urinary Mg
averages about 24 mmol/d, therefore about 95% GFR is reabsorbed before excretion. The kidney is responsible for regulating the serum Mg concentration by a setpoint trans port maximum (Tm)-limited process similar to the setpoint for Pi, except that the TmMg is not hormonally regulated. ECF concentration of ionized Mg is tightly regulated by the tubular threshold or maximum for Mg in the nephron. About 15% of the reabsorption of Mg occurs at the proxi mal tubule and about 70% at the cortical TALH. Mg may stimulate the basolateral membrane CaSR which decreases renal Mg reabsorption. The distal convoluted tubule accounts for about 10% of Mg resorption through a trans cellular transport process. Renal Mg reabsorption is highly regulated, with a number of factors that may increase or decrease tubular resorption. Since there is little distal tubule reabsorption, ECF volume expansion decreases Mg reabsorption and increases urine Mg excretion. Hypermagnesemia increases urine Mg excretion at least in part through activation of CaSR. Skeletal Mg Although a significant portion of total body magnesium resides in the skeleton, the skeleton does not play a major role in magnesium regulation. Serum Mg Blood levels of Mg are not as tightly regulated as Ca, but rather fluctuate with the influx and efflux across the ECF with changes in intestinal Mg absorption, net renal reab sorption and resorption and formation of bone mineral.
C h a p t e r 4 Fundamentals of Mineral Homeostasis l
Intracellular mineral metabolism Calcium Intracellular Ca functions include contributing stability to plasma membranes by binding to phospholipids in the lipid bilayer and by regulating the permeability of plasma membranes to sodium ions. A reduction in ionized Ca con centration increases sodium permeability and enhances the excitability of all excitable tissues; an increase in sodium content has the opposite effect. The function of the cell largely dictates the cell Ca homeostasis with differences in cells responsible for muscle excitation and contraction, signal transduction, mediating signals from an activated plasma membrane receptor for the synthesis and release of hormones, neurotransmitters and kinase phosphorylation. Serum Ca concentration of ionized Ca is approximately 103 M, while the ionized cytosolic Ca concentration is approximately 106 M, resulting in an approximate 1000fold gradient that strongly favors the movement of calcium from the ECF to within the cell. Further, the cell interior possesses a slightly negative charge with a differential elec tric charge across the plasma membrane (50 mV) gradi ent, further supporting diffusion to the cell. In order for the cell to maintain this gradient, a strong system of active transport exists to maintain cellular Ca concentrations at an optimal level to avoid cell death, which occurs if intracellu lar Ca is not maintained in the micromolar range. The maintenance of optimal intracellular Ca concen trations is regulated by a number of intracellular func tions. A system of energy-dependent active transport exists across the plasma membrane as an ATP-driven calcium pump quickly to expunge Ca from within the cell once concentrations become elevated beyond normal levels. A separate system of sodium–calcium exchangers is also employed to ensure that Ca concentrations remain in the normal range. Further, active uptake of Ca into organelles, such as the endoplasmic reticulum and the mitochondria, occurs to remove Ca from the cytosol; in fact, the mito chondria and microsomes can contain up to 99% of the intracellular Ca, bound largely to organic and inorganic phosphates. Should Ca concentration levels drop below optimal within the cytosol, Ca can be rapidly released from the organelles to facilitate a rebalancing of cytosolic Ca. The Ca capacity of these organelles is such that it can replenish cytosolic Ca levels approximately 500 times. There are also receptors on the plasma membrane that, when activated, result in the pulsed release of Ca from the organelles. Movement of Ca to within the organelles occurs through both cell-binding proteins and calcium transport proteins. Lastly, within the cytosol, there is a system of Ca buffering, where Ca binds to other cytoplasmic constitu ents or a specific Ca-binding protein to deal with elevated levels of Ca.
47
At the intestinal cellular level, transcellular calcium trans port is stimulated by 1,25D and upregulation of the vitamin D receptor (VDR). VDR-mediated increased expression of a number of vitamin-D dependent genes produce proteins that participate in the active transport process. Calcium influx across the brush border membrane is facilitated by the channel created by the calcium transport protein I (TRPV6) which is induced by 1,25D and estradiol, independently through their cognate receptors.
Phosphorus The gradients for Pi across the plasma membrane are mod est with an ECF concentration of Pi approximately 104 M and cytosolic Pi approximately 2 104 M. The trans port of Pi ions across the plasma membrane and across the membranes of the organelles is passive, but largely depends on the concomitant movement of cations, in most cases Ca2. Serum Pi decreases postprandially and during IV glu cose infusion, therefore, there is insulin-mediated Pi entry into the cells as well. While the concentration of Pi ions within the cytosol is quite low, the mitochondrial concen tration is quite high, generally as calcium Pi salts, reflective of the importance of the mitochondria in ATP energy pro duction. Intracellularly, Pi is almost always bound or exists as phospholipids forming cell membranes, organic phos phate esters or as phosphorylated intermediate molecules involved in a large number of cellular processes – the most common being that of ADP–ATP. Phosphate esters play a very important role in cellular metabolism: purine nucle otides provide the cell with stored energy; phosphorylated intermediates are involved in energy conservation and transfer; phospholipids are major constituents of cell mem branes; and the phosphorylation of proteins is an important means of regulating their function.
Magnesium Within the cell, Mg is the most abundant divalent cation and the second most abundant intracellular cation after potas sium. Mg concentration is strictly controlled within the cytosol and ECF at approximately 5 104 M, both con centrations controlled by factors that currently are not well understood. Cytosolic unbound, ionized Mg constitutes 5–10% of the total cellular Mg. Similar to Ca, Mg concen tration within the cells is partially regulated by its uptake into the organelles. Approximately 60% of cellular Mg is found within the mitochondria where it acts as an essential cofactor in a number of enzyme systems including almost all enzymes involved in the transfer of phosphate groups, transport and all functions that require ATP. Outside the mitochondria, Mg is involved as a cofactor in enzyme sys tems for replication, transcription and translation of genetic information.
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Mineral ion balance Mineral exchange systems in the intestine, kidney and bone are required in order to ensure precise control and sufficient concentrations of essential minerals. A number of hormone systems, most notably PTH and 1,25D, play primary roles in the regulation of these mineral-balancing systems. There is increasing evidence that fibroblast growth factor-23 is a major Pi-regulating hormone. In general, there are states of neutral, positive or negative mineral ion balance. In neutral (or zero) balance, mineral intake and bone accretion are equal to bone resorption and the losses excreted. Neutral mineral balances are generally observed in men who are under 65 years of age and in nonpregnant premenopausal women after peak bone mass had been achieved. Early studies have suggested that a thresh old of Ca intake (approximately 1000 mg/day) is needed to maintain a neutral or positive calcium balance and that menopause may increase that requirement [6]. Full Ca bal ance studies are rarely done today and differences in cal cium balance between adult men and women have not been consistently documented. As children progress through adolescence, however, males seem to have a higher Ca intake [7, 8] and also retain more Ca. One recent study of 3week dietary Ca retention in adolescent boys [9] suggested greater retention for the same intake than was seen in a similar study of adolescent girls [10]. In a study of children from Saskatchewan [11], daily Ca retention during the ado lescent growth spurt was estimated to be 359 mg/d for boys (199–574 mg/d) and 284 mg/d for girls (171–459 mg/d). In states of positive balance, mineral intake and accre tion exceed mineral losses. Positive mineral balance is only observed during skeletal growth and during recovery from periods of bone loss. Lastly, in negative balance, min eral losses exceed mineral intake and accretion. Negative mineral balance occurs often during the menopause and in estrogen deficiency, during chronic glucocorticoid ther apy, with hyperthyroidism and with vitamin D deficiency. A common consequence of negative mineral balance is bone loss. With a normal diet, the supply of minerals through absorption in the intestine is more than sufficient for met abolic and accretion needs. The primary regulator of ECF mineral homeostasis is the renal tubule through alterations in the amounts of mineral reabsorbed.
Calcium Balance Serum Ca concentration is tightly regulated by hormonal activity and PTH is the primary regulator of serum Ca. The integrated actions of PTH on distal tubule calcium reabsorp tion, bone resorption and vitamin D mediated intestinal Ca absorption finely regulate ionized Ca concentration to the extent that there is rarely a fluctuation of more than 0.1 mg/dL from the setpoint value at any given time of the day.
The parathyroid chief cell is exquisitely sensitive to ionized serum Ca concentration, through its CaSR on the plasma membrane, and is capable of responding to decreases in Ca concentration by releasing PTH to elicit increases in serum Ca. If Ca concentration is too high in the serum (hypercalcemia), there is a suppression of CaSR signaling and a subsequent decrease in PTH release, with increased intracellular degradation of PTH to biologi cally inactive fragments [12]. There is also stimulation of the distal nephron CaSR which then reduces the net tubule reabsorption of Ca resulting in increased Ca losses into the urine. Sustained hypocalcemia can eventually lead to par athyroid (PT) cell proliferation and an increase in the total secretory capacity of the PT gland, whereas vitamin D reduces PTH synthesis and PT cell proliferation. Distal tubule reabsorption and osteoclastic bone resorption are the primary players in minute-to-minute calcium homeos tasis. Of the two, the impact of PTH on the kidney is quan titatively more important: approximately 1000 mg of Ca is daily under the control of PTH as it passes through the distal nephron. PTH has a major role in ensuring Ca balance and fine tuning by stimulating both renal Ca reabsorption (prima rily the proximal tubule) and excretion (distal tubule). This is a classical short loop system where the Ca that is released via PTH is immediately sensed by the PT where adjustments in PTH secretion can then be made to bring the system into bal ance; these adjustments in reabsorption of Ca can occur within minutes of sensing low concentrations of Ca. PTH causes Ca sparing in the kidney by way of enhanced renal tubule rea bsorption of Ca with concomitant inhibition of Pi reabsorp tion resulting in phosphaturia. PTH related peptide (PTHrP) mimics the action of PTH in the nephron. PTH increases the net Ca reabsorption, but patients with primary hyperparathy roidism are often hypercalciuric, because increased tubule Ca reabsorption leads to hypercalcemia and an increased filtered load of Ca resulting in hypercalciuria. Pi administration can reduce urine Ca excretion though an increased distal calcium reabsorption and stimulation of PTH. Dietary Pi deprivation causes hypercalciuria in part by actions in the distal nephron. PTH increases bone resorption resulting in Ca and Pi release from the skeleton. There has been speculation that part of the impact of PTH on bone resorption is through activation of the osteocytes which, in turn, may act on either the osteoblast or osteoclast cell lines. These changes in Ca availability in the serum via the bone can occur in minutes to hours following stimulation. There is also a long-loop system that increases Ca con centration with vitamin-D mediated Ca absorption from the intestine providing feedback to the PT cells. When PTH rises in response to hypocalcemia, in the proximal tubule, PTH promotes 1- hydroxylase conversion of 25-OH vitamin D to 1,25D, which then increases intestinal Ca absorption and, to a lesser extent, renal phosphate reabsorption. Renal 1- hydroxylase is also stimulated directly by hypocalcemia and hypophosphatemia. This system is important for bringing
C h a p t e r 4 Fundamentals of Mineral Homeostasis l
dietary Ca and phosphate into the system, but maximal adjustments via 1,25D and the intestinal absorption system take 24–48 hours to manifest fully and have little to do with minute-to-minute regulation of ECF Ca. 1,25D action in the kidney is not well understood, although it is recognized that deficiencies in 1,25D decrease Ca reabsorption independent of PTH. Calcitriol increases expression of CaSR which then decreases calcium reab sorption. Calbindin 28 kDa levels increase and may also increase Ca reabsorption. 1,25D is responsible for miner alization of bone and for intestinal absorption of Ca and Pi and for maintaining them at levels that facilitate deposi tion into the bone matrix in appropriate quantities. A major indirect role of 1,25D is to mobilize Ca stores when dietary Ca is insufficient to maintain normal ECF calcium concen tration. Calcitriol enhances osteoclastic bone resorption by binding with receptors in the pre-osteoblastic stromal cell line and stimulating the RANK/RANKL system to enhance the proliferation, differentiation and activation of the osteo clastic system from its monocyte precursors. Acute and chronic metabolic acidosis increases urine Ca excretion and alkalosis decreases urine Ca excretion. Endogenous acid production from metabolism of sulfurcontaining amino acids found in animal proteins contrib utes to post-prandial increases in urine Ca. Although these short-term changes in calcium excretion may cause a nega tive Ca balance and increases in bone turnover in the short term, there is little evidence for long-term reduction in bone mass due to dietary acid load [13].
Phosphorus Balance The kidney plays the dominant role in systemic Pi homeo stasis and holds the serum Pi concentration at a value very close to the tubular P threshold or TmP/GFR. Since the normal efficiency and lack of fine regulation of Pi absorp tion in the intestine, only in unusual circumstances is the systemic supply of Pi a limiting factor in Pi homeostasis. With a normal dietary intake, 1,25D does not stimulate jejunal Pi absorption, however, during states of vitamin D deficiency or with chronic renal failure with impaired 1,25D production, administration of 1,25D can stimulate net Pi absorption. 1,25D supports net intestinal Pi absorp tion through enhanced cellular brush border Pi uptake. This uptake process is saturable with an affinity coefficient of 1.0 mM and is present in the proximal duodenum, jejunum and, to a lesser extent, the distal ileum. Net Pi absorption does not occur in the colon. In hypophosphatemia, there is a stimulation of 1,25D production in the kidney, an enhanced mobilization of P and Ca from the bone and an increase in TmP/GFR. The increased 1,25D leads to increased Pi and Ca absorption in the intestine and provides additional stimulus for Pi and Ca mobilization from bone. The increased flow of Ca and Pi from the bone inhibits the release of PTH which diverts the
49
flow of Ca into the urine and further increases TmP/GFR. The net change is an increase in serum Pi without a change in ionized Ca concentration in the serum. There are two major mechanisms whereby the renal loss of phosphate will protect against hyperphosphatemia. Recently, FGF-23 has been identified as a phosphate-regu lating hormone. It is produced primarily in bone by cells of the osteoblast lineage (osteoblast progenitors, osteoblasts, and osteocytes) and regulates renal phosphate transport and 1,25D synthesis. In response to hyperphosphatemia, increased FGF-23 secretion from bone results in increased phosphate excretion and decreased renal synthesis of 1,25D [4]. Hyperphosphatemia is also corrected by increased PTH secretion djue to the effect of phosphate on serum Ca. The mineral ion product (Ca P) is generally a biologic con stant in the sense that an increase in the concentration of one mineral will result in the reciprocal change in the other. Thus, an acute increase in serum Pi concentration produces a transient decrease in Ca concentration and a stimulation of PTH secretion, which then reduces the TmP/GFR and leads to a readjustment in serum Pi and Ca concentrations.
Magnesium Balance Mg serum levels are regulated primarily by the quantitative influx and efflux of Mg rather than an elaborate hormonal system like that which has evolved for Ca. There appears to be no important systemic or hormonal regulation of Mg con centration in the ECF. Blood ionized Mg is less potent than Ca concentration in regulating PTH secretion. The levels are regulated primarily in the kidney at the level of renal tubu lar reabsorption. Instead, control seems to be as fluxes at the intestine, kidney, intracellular fluids and perhaps the skeleton. The kidney is the prime regulator of serum Mg concentration. Absorptive and secretory Mg fluxes across both the small intestine and colon are largely voltage dependent. Therefore, there are large paracellular pathways of Mg transport that are primarily driven by the luminal Mg concentration. The Mg ion channel TRPM6 is important in the regulation of Mg homeostasis, but the regulator of TRPM6 is unknown. Fractional absorption of Mg is approximately 30%. In dietary Mg excess, a smaller proportion may be absorbed and, in times of deficiency, the opposite. Mg absorption in the small intestine is not well understood, but appears to happen via both passive and facilitated, but not active, elements. These elements do not seem to be sensitive to PTH, calcitonin or 1,25D; thus, net Mg absorbed appears to primarily be a function of dietary Mg intake.
Summary Homeostasis of Ca, Pi and Mg is essential for normal functioning of the body. The gut, kidneys, bone and cells work in a coordinated fashion to ensure that mineral
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levels remain stable whenever possible. PTH and 1,25D play critical roles in the maintenance of specific mineral concentrations despite frequently changing dietary intakes and metabolic and growth demands.
References 1. R.C. Khanal, I. Nemere, Regulation of intestinal calcium transport, Annu. Rev. Nutr. 28 (2008) 179–196. 2. J.M. Wishart, F. Scopacasa, M. Horowitz, et al., Effect of perimenopause on calcium absorption: a longitudinal study, Climacteric 3 (2) (2000) 102–108. 3. S.J. Van Cromphaut, K. Rummens, I. Stockmans, et al., Intestinal calcium transporter genes are upregulated by estrogens and the reproductive cycle through vitamin D receptor-independent mechanisms, J. Bone Miner. Res. 18 (10) (2003) 1725–1736. 4. S.M. Burnett, S.C. Gunawardene, F.R. Bringhurst, H. Juppner, H. Lee, J.S. Finkelstein, Regulation of C-terminal and intact FGF-23 by dietary phosphate in men and women, J. Bone Miner. Res. 21 (8) (2006) 1187–1196. 5. J. Marks, L.J. Churchill, E.S. Debnam, R.J Unwin, Matrix extracellular phosphoglycoprotein inhibits phosphate trans port, J. Am. Soc. Nephrol. 19 (12) (2008) 2313–2320. 6. R.P. Heaney, J.C. Gallagher, C.C. Johnston, R. Neer, A.M. Parfitt, G.D. Whedon, Calcium nutrition and bone health in the elderly, Am. J. Clin. Nutr. 36 (5 Suppl.) (1982) 986–1013.
7. K. Bialostosky, J.D. Wright, J. Kennedy-Stephenson, M. McDowell, CL. Johnson, Dietary intake of macronutrients, micronutrients, and other dietary constituents: United States 1988–94, Vital Health Stat. 11 (245) (2002) 1–158. 8. R.B. Ervin, C.Y. Wang, J.D. Wright, J. Kennedy-Stephenson, Dietary intake of selected minerals for the United States pop ulation: 1999–2000., Adv. Data 27 (341) (2004) 1–5. 9. M. Braun, B.R. Martin, M. Kern, et al., Calcium retention in adolescent boys on a range of controlled calcium intakes, Am. J. Clin. Nutr. 84 (2) (2006) 414–418. 10. L.A. Jackman, S.S. Millane, B.R. Martin, et al., Calcium retention in relation to calcium intake and postmenarcheal age in adolescent females, Am. J. Clin. Nutr. 66 (2) (1997) 327–333. 11. D.A. Bailey, A.D. Martin, H.A. McKay, S. Whiting, R. Mirwald, Calcium accretion in girls and boys during puberty: a longitudinal analysis, J. Bone Miner. Res. 15 (11) (2000) 2245–2250. 12. D.A. Hanley, K. Takatsuki, J.M. Sultan, A.B. Schneider, L.M. Sherwood, Direct release of parathyroid hormone fragments from functioning bovine parathyroid glands in vitro, J. Clin. Invest. 62 (6) (1978) 1247–1254. 13. T.R. Fenton, M. Eliasziw, A.W. Lyon, S.C. Tough, D.A. Hanley, Meta-analysis of the quantity of calcium excretion associated with the net acid excretion of the modern diet under the acid-ash diet hypothesis, Am. J. Clin. Nutr. 88 (4) (2008) 1159–1166.
Chapter
5
The Mechanical Properties of Bone David P. Fyhrie David Linn Chair of Orthopaedic Surgery, Lawrence J. Ellison Musculoskeletal Research Center, Department of Orthopaedic Surgery, The University of California, Davis; The Orthopaedic Research Laboratories, Sacramento, California, USA
The idea of hierarchy in bone mechanics
Introduction The mechanical properties of bone include all of the properties measured and all of the mathematical complexities developed by engineers to understand and use solid materials to build houses, cars and electronics. Fortunately, only some of the mechanical properties and almost none of the mathematical complexity are needed to understand the important functional properties of bone. In life, the important mechanical properties result in a bone that is strong, tough and sufficiently long lived that it does not hurt or break when we use it! Whole bone properties come both from the structure (the anatomy) and the material properties of the hard tissue. This chapter will consider the effects of anatomy first and then examine key mechanical properties of the hard tissue that are essential to function. The goal for this chapter is to understand the mechanical properties of bone without the engineering complexity. The chapter uses example mechanical tests as illustrations and relegates mathematical analysis to separate sections. If you do not need to understand how to calculate a modulus or failure stress, you can skip the mathematics and (I hope!) the examples will ensure that the concepts are still clear. This is an idiosyncratic attempt to provide a guide to the important bone mechanical properties. It is not a listing of measured properties, nor a complete mathematical treatment of the subject. Rather, I sought to provide examples and explanations to help with understanding how bone mechanical properties arise from the molecular constituents. The reference list is not intended as a review of the literature, but I have tried to be topical, up-to-date and fair to the many investigators working in the field. Osteoporosis in Men
A detailed understanding of the effect of structure on mechanical properties of a bone is as variable as their shapes. From the bones of the inner ear to the femur, the shape (the anatomy) and loading on the bones determine the average stresses and strains in the hard tissue. At a smaller level, the structures of the hard tissue itself (the histological microstructure and molecular ultrastructure) determine how the average stress and strain in the tissue are distributed in the molecular elements. Consequently, the sizes of the structures from gross anatomy down to the molecular organization affect the stress and strain distribution at smaller and smaller levels. The observation that a descending series of sizes in the structures (e.g. anatomical, histological, molecular) all contribute to the mechanical properties is often presented in shorthand as, ‘Bone is a hierarchical material’ [1, 2]. This is a useful concept and helps with the understanding of bone mechanics since there is a large literature on the properties of man-made hierarchical composites. A weakness of the analogy is that the hierarchy in man-made composites is designed into the material and design is a concept inappropriate for an evolved structure such as bone. In evolved materials, the different sized patterns in the molecular components survive from generation to generation for unknown reasons. What can be said with certainty is that the mechanical properties created from the material patterns we see in bone do not (usually) contribute to death before successful reproduction. Bone as an evolved material simultaneously uses all structural sizes from the quantum mechanical to the anatomical in order to provide sufficient function to the organism. 51
Copyright 2009, 2010 Elsevier, Inc. All rights of reproduction in any form reserved.
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Osteoporosis in Men 140 120
Load (N)
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0
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Figure 5.1 Load (force) displacement curve for three-point bending of a canine rib. This curve is typical of not only bending but most other mechanical test methods.
Anatomical structural effect Understanding (or analyzing) how the anatomical structure of each particular bone provides function to the body is far beyond this chapter. Fortunately, bending of a tubular cortical bone and compression or tension of a bone specimen are fairly easy to present mathematically and cover a large fraction of the cases where a bone fails during function.
Long Bone in Bending There are many cases of bending of bones in the skeleton. In most cases, the bending is very complex, such as for the femoral shaft when running. Simple bending, such as of the femoral neck during standing, is the rare exception. To illustrate the effect of anatomical structure on the bending properties of a bone, I shall resort to a simplified form called three-point bending. Three-point bending is a mechanical test where an isolated long bone (or a beam-like specimen of tissue) is pressed between one central point and two evenly spaced lateral points (Figure 5.1). The loading points can be knife edges, cylinders or rollers (to choose between these options for bone see [3]). The configuration of the loading causes bending of the specimen and, usually, failure at the midpoint. For the example here, (data provided by Matt Allen, Indiana University), the rib of a dog was compressed in displacement control while simultaneously recording the force and displacement of the test (see Figure 5.1). These are the only data needed to determine the structural properties of the bone during the test. The slope (the stiffness) of the force-displacement test is nearly constant (the linear
region) when the material is not damaging (Figure 5.2). The force and displacement at which significant damage initiates (the yield point) can be estimated by various means [4, 5] and the maximum load point is determined directly from the force data. The events in the load-displacement data are predictable. Initially, the load increases non-linearly, caused by settling of the specimen against the grips. These data are artifacts and were removed from the graph. Then, there is a nearly linear region where the load and the displacement increase proportionally. When damage begins, the load and displacement cease being proportional. This region begins at the yield point (or the proportional limit). (If the specimen is unloaded after the yield point it will have a reduced stiffness, but will unload to close to the original length. This is a material behavior called ‘Elastic-perfect damage’ [6, 7]. Finally, the maximum load is achieved and (in displacement control) the load decreases. The linear region, yield point and maximum load are present in many different mechanical tests, regardless of their geometry. This is because they result from characteristics of the material, rather than from the shape of the specimen. The dependence of the sequence of events in the test of the whole rib on the material means that almost all that you need to know about bone during a single load is revealed by the bending test: 1. if you load bone below the yield point it is not damaged and it acts as a linear spring that has deformation proportional to the load 2. loading beyond the yield point (the proportional limit) permanently damages the material, reducing stiffness
C h a p t e r 5 The Mechanical Properties of Bone l
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Constant slope (linear) region.
95% secant line.
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Figure 5.2 The force–displacement curve (black) from initial contact till just past maximum load. The dashed line is the slope of the curve calculated using Excel. The stiffness is the slope of a linear fit to the straight part of the curve and the 95% secant line is that line with the slope reduced by 5%. The yield point and maximum point are determined from the intersection of the secant line with the load line and the maximum force, respectively.
3. with continued loading a maximum load is reached, after which there is a reduction in the highest load that the bone can support.
strain.) For a normal stress applied to a linear material, stress is proportional to the strain as:
These observations are valid both at the structural and the material level of the bone. If all we cared about was how stiff and strong the rib was as a structure in three-point bending, we would be done. But, of course, this bending test example is too specific to one bone and one testing laboratory to be generally useful. Therefore, further analysis of the data is needed in order to estimate the mechanical properties of cortical bone in the rib. The next section is such an analysis – but you can skip it if you are not interested in calculating material properties from a bending test.
Stress, Strain, Toughness and Linear Isotropic Moduli To convert the force and displacement of a specific structural test of a bone into material properties that can be compared between different laboratories, three important concepts are needed. The first two are normalizations of the force and displacement. The normalization of force is stress (Figure 5.3) defined as the force-per-unit-area. The normalization of the displacement is the strain which is the displacement divided by the appropriate size of the specimen (see Figure 5.3). There are three normal stresses and three shear stresses at each point in a material. Similarly, there are three normal strains and three shear strains (see [8] for outstanding detail on stress and
Stress (Young’s Modulus) Strain. Similarly, for a simple shear stress:
Stress (Shear Modulus) Strain.
The Young’s modulus (E) is related to the shear modulus (G) through the formula,
E 2G(1 ν)
where is the Poisson’s ratio. For most materials, when a compressive normal stress is applied to a cube, the compressive strain is accompanied by a lateral expansion of the material. Poisson’s ratio is the ratio of the lateral to the normal strain under a normal stress. Only two of the linear isotropic properties (E, G, ) are independent of each other, so if you know two, the third is easily calculated. A very important property of bone is the energy absorbed prior to failure, which is called toughness. From basic physics, the energy absorbed is the integration of the applied force as a function of the displacement. The units of energy are: 1 Joule 1 Newton-meter. On a force versus displacement curve (see Figure 5.1), the toughness (or energy) is the area under the curve. The same integration can be performed for a stress–strain curve, but then the energy units are in Joules/m3. The concept tough is paired with brittle. This pair of words
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Osteoporosis in Men Normal Force δn
Shear Area
δs
Height
Normal Stress = Normal force/Area δn Strain
Shear stress = Shear force/Area δs Strain
Figure 5.3 The simple engineering definitions of stress and strain. Stress and strain are normalizations of force and displacement.
refers to materials that absorb large or small amounts of energy before failure, respectively. The concept of toughness is needed later to understand the importance of different components of bone ultrastructure. Material Properties from A Three-point Bending Test To calculate material properties from a mechanical test, it is always necessary to perform a stress analysis. For the threepoint bending test, the model for the structure is a simply supported beam loaded in the center. To convert the force and displacement of the mechanical test into stress and strain, the experimental data are matched to a theoretical stress analysis and the material properties are calculated. A three-point bending test is often analyzed using linear beam theory [9]. To do this, three structural measurements are needed: 1. the distance between the loading points (L) 2. the distance from the centroid of the cross-section to the outer fiber of the beam (c) 3. the second moment of the area around the centroid in the direction of bending (Ic). (This parameter is also called the cross-sectional moment of inertia and often abbreviated CSMI.) From the force (F) and deflection of the beam (), the axial normal strain (e, see Figure 5.3), axial normal stress (, see Figure 5.3) and Young’s modulus (E) are calculated using: Mc Ic M ( F/ 2)( L/ 2) c Dy / 2 Ee
E
FL3 48 I c
where L is the distance between the loading points, Dy is the diameter of the cross-section in the direction of bending and Ic is the second moment of area of the cross-section in
Figure 5.4 The shaft of the femur can be approximated as a cylinder with inner radius RI and outer radius RO. The second moment of area (Ic) is proportional to the difference between the 4th power of the bone’s outer and inner radii: Ic (/4) (RO4 RI4). An interesting exercise is to prove to yourself that a small change in the outer radius has a much larger effect on the second moment than the same change in the inner radius because of the fourth power. As a result, as endosteal expansion occurs during life, the bending stiffness of the bone can be restored by placing a smaller amount of bone tissue at the periosteum.
the direction of bending. To use these equations, the diameter and the second moment must be measured. Second Moment of Area The second moment of the area of the cross-section (Ic) and the diameter of the cross-section (Dy) are measurements from the bone that contribute to structural stiffness. The diameter does not require any explanation, but the second moment of area is not intuitive. A detailed explanation of the second moment should remain in a book on strength of materials [9]. A brief description is that the second moment is proportional to the integrated moment over the area caused by the stresses when it is assumed that the stresses are linearly distributed. There are two key observations: 1. the second moment scales as the fourth power of the diameter of the bone (Figure 5.4) 2. there are computer programs available to calculate the second moment from digital images of a bone cross-section (http://www.hopkinsmedicine.org/fae/MMacro.htm).
C h a p t e r 5 The Mechanical Properties of Bone l
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Lower Threshold
Figure 5.5 Using the program MomentMacro (provided by Dr Chris Ruff, http://www.hopkinsmedicine.org/fae/MMacro.htm), the second moment of inertia of the canine rib was calculated for a range of lower image thresholds, keeping the upper threshold at 255. This demonstrates the strong dependence of second moment on the thresholds used to prepare the bone image. This is very important, since the accuracy of all calculated values from the bending test are strongly dependent on an accurate second moment.
The second moment of area has a very large effect on the modulus calculated from a bending test. Therefore, accurately measuring the second moment is very important. A primary effect on the value of the second moment is the threshold used to create the binary digital image used in the calculation. For the rib of our example, the image had grayscale values from 0 to 255. The second moment of the cortical bone is sensitive to the lower threshold even when the upper threshold is fixed at 255 (pure white; Figure 5.5). The threshold used by the contributors of these data (Allen et al. 2008) (thanks to Drs Allen and Burr) resulted in Ic 9.62 mm4. Since the second moment is very sensitive to the shape of the cross-section, it is important to understand how investigators choose their image threshold when interpreting bone mechanical property data. The Final Calculations For the three-point test of the example rib, the collected data were: L 25 mm; Ic 9.62 mm4; Dy 4.44 mm; Fyield 82 N; yield 0.40 mm; Fmaximum 116 N. Therefore, the properties are: E yield (82 N)(25 mm)3 /[ 48(9.62 mm 4 )(0.40 mm ) yield
6936 N/mm 2 6.9 GPa [(82 N)(25 mm)/ 4][(4.44 mm)/ 2]/ 9.62 mm 4 118 N/mm 2 118 MPa
e 118 MPa/(6936 MPa) 0.017 2% yield maximum [(116 N)(25 mm ) / 4][(4.44 mm)/ 2] / 9.62 mm 4 167 N/mm 2 167 MPa. This analysis assumed that strain () was linearly distributed across the cross-section, that the material was uniform, with stress () proportional to strain ( E), that the neutral axis of the cross-section passes through the centroid and that the Young’s modulus (E) was uniform. These assumptions may or may not be appropriate for any particular mechanical test and errors caused by the actual experiment violating the assumptions can be large. To understand the detailed bases of these assumptions and to discover other mechanical analysis methods with fewer assumptions, please see a good book on beam theory [9]. (Also consider working with an experienced mechanical engineer to develop experiments!) A final note for the bending test is that the stress calculated from the maximum load and displacement is called the modulus of rupture. The modulus of rupture is always larger than the actual stress in the tissue because, at the time of maximum load, the distribution of stress in the cross-section is no longer linear. As a result, maximum stresses calculated using a bending test can only be compared between identical tests – they are not actually material properties. On the other hand, the stress, strain and modulus at yield
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are consistent estimates of the material properties and can be compared between different tests and laboratories. Further Complications in the Relationship Between Stress and Strain For a linear material that follows Hooke’s Law (Ut tensio, sic vis: or, E), the Young’s modulus (E) is a constant, but it does not necessarily have the same value for different loading directions. Imagine that the normal stress cube of Figure 5.3 is turned so that the load is applied to a different face. For a linear material, the stress will be proportional to strain, but E (Young’s modulus) can be different for each direction of loading. This is true for all the normal loading directions and for all the shear loading directions. If all of the possible combinations of loading direction are accounted for, there can be 21 independent material properties! This is more than we can measure effectively and more than are actually needed for most bone tissue. The most generally useful model for bone is the orthotropic model, which has nine independent material properties. This is still too many for easy measurement and the transversely isotropic (five material constants) and cubic (three independent properties) are occasionally used. However, the overwhelmingly most popular model is the isotropic model, with only two independent material properties. Unfortunately, the isotropic model is not a very good approximation of the direction dependence of material properties, but it is easier to use in calculations. Some of the interesting details of these material models are available in a good book on composite materials [11] or in a large number of papers published in the biomechanics literature [12–15].
Vertebra in Compression The main observations from the bending test, that there is a linear region and a damage region for the tissue separated
by a yield point, are also valid for compression of bones. As an example, the force and displacement in compression for the T12, L1 and L2 vertebral centra from an individual are presented in Figure 5.6. Although the magnitudes of the displacements and forces in these compression tests are different from those of the three-point bending test of the canine rib, the main features of the test – linear region, yield point and maximum load – are identical. Therefore, the mechanical behavior of a vertebral centrum in compression, a structure filled almost completely with cancellous bone, is homologous to the behavior of a tube of cortical bone (the rib) in bending. The similarity is because the mechanical behavior of cancellous bone in compression is largely determined by the hard tissue of the trabeculae. The hard tissue of the trabeculae is essentially identical to cortical bone at the molecular level, therefore, the main features of failure of the vertebrae are the same as those of the rib. A significant difference between compression of a vertebra and bending of a rib, however, is that there is not any simple method to calculate the stress and strain in the trabeculae. Many investigators have worked to develop the computational methods needed to estimate stress and strain in cancellous bone tissue [16–22], but these calculations are not important to our goal of understanding the main features of bone’s mechanical properties.
Cancellous Tissue in Simple Compression and Tension One way to simplify the analysis of cancellous bone is to cut small specimens from the tissue, then compress or pull on them until they break. The force displacement curves for tests from small specimens of cancellous bone look very similar to the results for whole vertebral centra. The material properties are calculated from the force and
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Figure 5.6 Force and displacement for three human vertebrae compressed to failure. The data were kindly provided by Yener Yeni, Henry Ford Hospital. The same features of nearly linear region, yield and ultimate points appear as in the test of the canine rib.
C h a p t e r 5 The Mechanical Properties of Bone l
d isplacement data as if there are no holes in the cancellous tissue. Material properties calculated in this way are called apparent mechanical properties. There is a huge literature on the apparent mechanical properties of cancellous bone [23–26]. As an example, Weaver and Chalmers [27] measured the apparent compressive strength for a single ½ inch cube (1.25 cm) from the center of the third lumbar vertebra collected post-mortem from 137 individuals. Their results clearly show the dependence of the apparent compressive strength on age (Figure 5.7). An important observation is that cancellous bone is similar to an engineering foam. These are materials created by ‘foaming’ a solid engineering material – e.g. bubbling gas through molten metal while it cools. There are standardized testing protocols for foams, such as the cube compression test. In addition, there is a specialized literature on cancellous bone testing that presents methods for accurate testing [24, 27–30]. Regardless of the details of the testing protocol, however, almost all of the mechanical properties of foams (and of cancellous bone) are power functions of the apparent density which is defined as the weight of the specimen divided by its volume. Young’s modulus, yield and maximum stress of cancellous bone all can be approximated by a power function of apparent density: Property K(Apparent density)B, where K and B are fitting constants. The values of these fitting constants depend on animal species, the anatomical site from which the specimen was cut, direction of loading, the mineralization of the tissue, whether the specimen was loaded in compression, tension or shear and many other factors [23, 24, 26, 31]. (Cancellous bone tissue has differing strength in tension and compression [32], so direction of loading is quite important. See below for an example for cortical bone.) Analysis of foams suggests that 2 B 3 [33]
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and values of the exponent in this range are often observed for experimental data from cancellous bone. Even with the simplification of ignoring the holes, any further progress on explaining the mechanical properties of cancellous bone immediately leads to a great proliferation of details that are not relevant here. However, a final point to make is that the radiodensity of cancellous bone is directly related to the apparent density of the tissue. This is why a computed tomography (CT) scan (which measures the radiodensity using x-rays) can be used to predict material properties using a function such as: Property k(radio density)b. Where the constants k and b differ from the formula based on apparent density. The relationship between radiodensity and apparent density of bone is part of the explanation of why bone mineral density (BMD) measured using dual-energy x-ray absorptiometry (DXA) is correlated to bone mechanical properties and to a fracture risk.
Cortical Tissue in Simple Compression and Tension: Asymmetry of Strength An example of mechanical testing that illustrates strength asymmetry is from a pair of cylindrical ‘dog bone’ specimens of bovine cortical bone in compression and tension, respectively (Figure 5.8). Results for this pair of specimens are typical and consistent with the previous examples. For both compression and tension, there is a linear region, a point where non-linearity becomes significant (yield point) and a peak load. An important similarity between the specimens is that the slope of the linear region (the Young’s modulus) is the same in compression and tension (this is a generally observed phenomenon). An important difference between the specimens is that the yield and peak stresses are larger in compression than in tension. This is not an
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Figure 5.7 Ultimate stress for ½ inch (1.25 cm) cubes of human vertebral cancellous bone in compression (data hand digitized from [27]). Male and female specimens are mixed, but showed no differences. This illustrates the concept of apparent failure stress and also the strong dependence of bone strength on age before and after the years of peak strength.
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the microscopic organization of the molecules into trabeculae, marrow spaces, osteons and the other features of bone tissue that many are familiar with. In the first part of this section we shall discuss how the ultrastructure affects material properties and then briefly discuss the role of microstructure on mechanical properties.
250 Compression
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Figure 5.8 Stress and strain for bovine cortical bone specimens in tension and compression. The slopes of the linear region (Young’s modulus) are similar, but the yield and ultimate stresses are different. Also, notice that the total area under the curves is very different.
accident of the two particular specimens used to make the figure. Cortical bone is stronger in compression than in tension [13, 23, 26] – it is asymmetric in strength. Similar to cancellous bone, the mechanical properties of cortical bone are a power function of the apparent mineral percentage of the tissue. Mineral percentage is often measured as the ash fraction of the tissue, which is the weight of the specimen after ashing in a muffle furnace divided by the dry weight of the specimen before ashing. The exponent for the power law for cortical bone mechanical properties is reported as variably between 2.79 and as high as 10.27, depending on testing conditions and covariates that are measured [34]. The key observation is that very small changes in mineralization cause very large changes in mechanical properties. As an aside, these data for cortical bone (kindly provided by Deepak Vashishth, Rensellaer Polytechnic University) are from bovine specimens loaded slowly. The slow loading allows the organic matrix to stretch (to creep) in tension. In compression, the mineral crystals constrain the creep, reducing the maximum strain. The mechanical properties of bone are affected by cross-linking of the organic matrix [35–37] which is an ultrastructural phenomenon.
Ultrastructure and microstructure and effects on mechanical properties The mechanical properties of bone seen in the force displacement examples are expressions of the mechanical properties of the hard tissue. The properties of the hard tissue arise from the molecular structure and, at a larger size,
The hard tissue of bone is a composite of a protein matrix, a mineral matrix and water, bonded together largely by covalent, ionic and hydrogen bonds [31]. The protein matrix is largely composed of type I collagen, the mineral is a highly substituted form of hydroxyapatite and the water is, of course, actually a complex solution containing many different species of ions, large and small proteins. (As a matter of definition, the word ‘composite’ is reserved for combinations of at least two distinct materials that have recognizable interfaces between them.) The relative importance of the mineral, collagen and water to bone mechanical properties is easily illustrated with simple experiments.
Experiment 1 Demineralization The role of mineral is revealed using dog-bone tensile specimens demineralized using ethylenediaminetetra-acetic acid (EDTA) or other means [38–40]. The resulting collagenous bone matrix specimens were broken wet in tension (Figure 5.9). For comparison, results for an undemineralized specimen are also presented (unpublished data, D Vashishth, Resellaer Polytechnic University). The demineralized tissue is fairly strong, fairly tough (the absorbed energy was 2500 J/ m3 versus 4100 J/m3 for the two specimens of Figure 5.9), has a far larger failure strain and is much more compliant. This simple comparison suggests that the collagen fibers are a primary source of bone strength and toughness, analogous to man-made continuous fiber composites.
Experiment 2 Deproteinization (Ashing) The importance of the protein matrix is emphasized again when 2 mm 2 mm square beams of equine cortical bone are broken in three-point bending with a 20 mm length between the knife edges (Figure 5.10). Removal of the organic material and water by ashing a specimen reduced the strength of the remaining mineral matrix by about a factor of 5, the failure displacement by about a factor of 10 and the energy to failure (toughness) by a factor of about 100. This is a profound effect considering that the stiffness of the ashed bone beam was similar to that of untreated bone.
C h a p t e r 5 The Mechanical Properties of Bone l
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180 160 Mineralized bovine cortical bone Energy density to failure: 4100 J/m3
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Figure 5.9 Tensile failure of a mineralized (data from Deepak Vashishth, RPI) and demineralized (data digitized from [39]) dog-bone specimens of bovine cortical bone. Demineralization greatly reduces modulus (slope) and reduces ultimate strength, but greatly increases the maximum strain. The toughness (energy absorbed before failure) is lower in the demineralized specimen by a factor of about two.
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Figure 5.10 2 mm 2 mm 20 mm equine cortical bone beams in bending to failure. Drying makes a specimen somewhat stiffer and stronger. Ashing makes the specimen much weaker but leaves the stiffness roughly unchanged. The absorbed energy to failure is reduced by about 100-fold by ashing. These data are similar to those published by Yan et al [41].
Experiment 3 Drying Removing the water from a three-point bending specimen using 16 hours of vacuum increased the peak strength approximately 20%, increased the stiffness, decreased the toughness (energy absorption) by about a factor of three and greatly decreased the post-yield deformation of the specimen (see Figure 5.10). Water is a solvent and acts as a plasticizer for the collagen fibrils, making them more flexible than when dry. Similar to drying, substituting a less polar solvent, such as alcohol, for the water causes the tissue to
be stronger and more brittle [42, 43], [Jordan McCormack, unpublished data]. The nature of the non-covalent bonding between collagen and mineral is another topic of significant interest [44–48] but beyond the goals here.
Synthesis of the Experiments The different results of the three illustrative experiments are summarized in a tri-axial plot of the weight fraction of the components of cortical bone specimens (Figure 5.11) [89]. Removing the mineral from human femoral tissue would
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1.0
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0.5 Galapagos tortoise femur
Dry: Strong, Stiff and Brittle Human femur Strong, stiff and tough
Demineralize: strong, flexible and tough
Bovine Tibia Ash+Dry: Weak, stiff and brittle
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Figure 5.11 A tri-axial illustration of how drying, ashing or demineralization would move a specimen as a function of composition and the effects of the modification of strength, modulus and toughness. Redrawn after Zioupos et al. [89].
move the specimen to the right onto the ‘Demineralized’ axis, where it would be very flexible, yet fairly strong and tough. Removing the collagen and water would move the specimen to the lower left corner of the ‘Ashed’ axis and make it stiff, very weak and very brittle. Removing just the water would displace the specimen leftward to the ‘Dry’ axis where it would be stiff, strong and relatively brittle. The conclusions are:
link of bone, so when bone is loaded, the mineral fails first. Despite inherent mechanical weakness in tension, the mineral protects the collagen fibrils from the hostile environment of the body, keeps the fibers in the appropriate position so that load is efficiently distributed and provides stiffness to the composite that permits load-bearing without undue deformation.
1. the collagenous matrix is essential for strength and toughness 2. water enhances the plasticity of the collagenous matrix, increasing the post-yield strain 3. mineral is the primary contributor to stiffness, but is very weak and brittle in the absence of the collagen matrix.
The Key Role of the Collagenous Bone Matrix
The ultrastructure of bone is similar to a high-performance continuous fiber composite. In continuous fiber composites, almost all of the load carrying capacity is provided by the fibers. In bone, the collagen fibrils are the continuous fiber phase and the mineral is the matrix that binds the fibrils together. The functions of the mineral matrix in bone (and the matrix of man-made composites) are to hold the fibers together and to distribute the loading among the fibers to prevent local overloading. The mineral matrix is the weak
Removing any of the components of bone had a significant effect on the mechanical properties, but the runaway ‘winner’ for the size of its effect was the organic matrix. This is consistent with the highly increased risk-of-fracture in patients with collagen I defects, such as osteogenesis imperfecta [49] and also with the strong deleterious effect on bone strength of high doses of gamma radiation [50–52]. A critical role of the collagenous matrix of bone in determining mechanical properties may help explain why x-ray determination of bone shape and density can only explain a portion of fracture risk – the quality of the protein matrix is invisible to these methods. As a result, any genetic, exogenous or age-related effect that weakens the collagenous matrix can be expected to have a highly deleterious effect on bone strength.
C h a p t e r 5 The Mechanical Properties of Bone l
Covalent cross-linking among the collagen molecules and fibrils has a strong effect on the mechanical properties of the collagenous matrix. There are various cross-link types, including the pyridinoline cross-links formed consequent to action of the lysyl oxidase enzyme. These cross-links are very important to bone functional properties and tend to: 1. increase the ultimate stress 2. decrease the ultimate strain of the protein matrix. Blocking the action of lysyl oxidase significantly affects bone, skin and other tissues containing pyridinoline crosslinks [53]. As a general observation, any cross-link reduces the extractability of bone collagen [54–56] (i.e. makes it less soluble). It is not surprising, therefore, that the action of cross-linking is opposite of the action of water, resulting in bone matrix that is less plastic. Other covalent cross-links, for example those consequent to age-related non-enzymatic glycation [57, 58] have similar effects on collagen mechanical properties. This could help explain the significant decrease in the extractability of the protein matrix of bone with age. Of course, there are a very large number of other ultrastructural features that change the ability of the collagen matrix to carry load. These include the number and size of collagen fibrils [59, 60], whether the collagen is lamellar or woven [61] and the organization of collagen fibrils in the lamellae [62]. For example, unpublished data from my laboratory suggest that osteoporotics with fractures have poorly defined lamellae compared to normals. The importance of collagen organization to bone mechanical properties and disease is currently an area of active research.
Mineral Crystals and An Ultrastructural Model for Bone The typical single mineral crystal that can be extracted from bone is very small, approximately 5 nm 5 nm 40 nm [31]. The nanometer size and regular shape of the single crystals attracts engineers to theoretical models where crystals interact with the organic matrix by shear stresses [63]. Since the individual crystals are stiff and very strong, these shear lag models have adjustable parameters in the thickness and strength of the organic (shear) interface to tune the model to fit real bone mechanical behavior. This approach to modeling bone is very similar to models of nacre, where the crystals are much larger than in bone and the organic component is very thin relative to the crystal thickness. The shear lag model is a powerful, mechanistic model for nacre [64]. It is not clear, however, that the actual mechanisms of stress transfer in bone mimic those in nacre. For example, if the crystals in bone were truly separated from each other, then deproteinization by ashing might tend to create a nanosand rather than a ceramic-like mineral matrix with nearly the same modulus as whole bone.
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My opinion is that it is very revealing that ashing destroys the strength and toughness of normal bone, but that the stiffness of the remnant mineral ceramic remains similar to normal bone. A model that is consistent with these observations is that a continuous, open-celled, nano-porous mineral matrix creates the bone stiffness and the organic matrix acts to bridge nano-cracks in the mineral, preventing crack propagation and creating the toughness and strength missing from the mineral alone [65, 66]. The organic matrix weaves through the entire mineral volume at the nanoscopic level. In other words, bone is a high performance continuous-fiber nano-composite with the collagen matrix as the fiber and nano-porous mineral as the matrix. The doublenetwork model for crack propagation [67] and mechanical properties [68, 69] may be the appropriate starting point for mathematically modeling the properties of bone as opposed to starting with a shear lag approach. The effect of drying on bone properties suggests that the intimate bonding between the mineral and protein matrices might be by hydrogen bonds, but calcium bonds and ‘glue’ have also been proposed [46]. The mathematical behavior of this type of composite structure is similar to a shear lag model, but the details of stress transfer rely upon the tensile properties of the bridging collagen fibers rather than upon their shear properties. The key to this model is that the fibers bridge nanocracks in the mineral and cause propagation to become more difficult as the crack extends. This property of increasing resistance to crack propagation with crack extension is important to bone function and will be further discussed below.
Cancellous Microstructure An immense amount of research has been done in the last 50 years on the effects of cancellous bone microstructure on bone mechanical properties. A key and repeated observation is: the microstructural features of normal cancellous bone are very highly correlated to apparent density. Why apparent density is such a powerful predictor of microstructure and mechanical properties is tied up with very interesting details of how stress and strain are distributed in mechanical foams [33], how the trabecular organization creates mechanical anisotropy that orients with the habitual loading directions [70, 71] and a vast number of other topics of both biological and mechanical interest. I recommend starting with the excellent book of Currey [26]. There is a lifetime of reading available. One potentially useful observation is that cancellous bone strength is predicted fairly well by Young’s modulus [26, 72]. It is, in principle, possible to measure bone modulus non-destructively in vivo. Therefore, there is a potential to predict bone strength using the correlation between the two material properties. Unfortunately, the relationship between modulus and strength does not hold when the bone
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ultrastructure is abnormal. For example, in patients with collagen defects, such as osteogenesis imperfecta or with other collagen damage (or, for that matter, for ashed bone), the relationship between modulus and strength is not normal. Since apparent density (or volume fraction) of bone is highly correlated to the microstructural morphology, the universal age-related decline in bone density causes significant changes in tissue microstructure [73]. From the mechanical properties point-of-view, about the most detrimental change is transection of trabecular elements by osteoclastic resorption [74]. Cutting trabecular elements has a much greater effect in decreasing mechanical properties than does the thinning of elements. Preventing trabecular perforation is, therefore, one of the best means to slow the loss of mechanical properties with aging. Because of the different age-dependent histories of remodeling activation with age between men and women, treatment to reduce remodeling activation and element perforation will occur at different ages between the sexes. Perforation is only one example of how the history of remodeling affects cancellous bone strength. Other changes in the cancellous structure affected by remodeling include trabecular thickness, mean age of the tissue, degree of mineralization, density of cement lines and accumulation of other changes in the bone ultrastructure resulting from differences in osteoblast function in the aged organism.
Microstructural Effects in Cortical Bone As noted earlier in the chapter, the mechanical properties of normal cortical bone are related to the mineral content of the tissue as: Mechanical properties C(Ash Fraction)D, where ash fraction is the weight of the bone after ashing divided by the dry weight. The mineralization of osteoid increases nonlinearly to a near steady state over time in living bone [31], but mineralization increases further if the osteocytes die [75, 76]. This occurs in both cancellous and cortical bone: the interiors of trabeculae are more highly mineralized than the surfaces [77] and the interstitial regions of cortical bone are more mineralized than the osteons [78]. Therefore, for any particular bony site the mechanical properties are in constant flux due to (at least) changes in the local mineralization. In reality, the empirical power law for mechanical properties subsumes a huge number of details of how the mechanical properties arise from the complex interplay of collagen, mineral, lamellae, osteons, cement lines and the other features of cortical bone. One of the important features of cortical bone mechanical properties is that primary bone is typically stronger and stiffer but has a shorter fatigue life and lower toughness than does remodeled secondary bone [31]. As a consequence, remodeling is a causal factor in the age-related changes in cortical bone mechanical properties. Although the changes in morphology caused by remodeling are different in cortical bone than in cancellous bone, the rate
at which changes accumulate in both tissues depends upon the remodeling activation frequency. Sex, genetics, general health and other factors such as diet and exercise all affect remodeling activation. Therefore, remodeling related mechanical changes will differ between individuals and sites within a particular bone. An important consequence of Haversian remodeling in cortical bone is the creation of cement lines between the new osteon and the older tissue. The cement line is a weak interface in the tissue and cracks in the bone matrix will tend to be trapped by the cement line interface [31]. When trapped, cracks turn to run along the length of the osteon, preventing the formation of a larger crack that might grow into a macroscopic fracture. This power of osteons and cement lines to control damage and provide enhanced tolerance of bone to damage was recognized many years ago by F. Gaynor Evans [79]. His concept was that osteons in remodeled (secondary) cortical bone are analogous to a ‘bundle of sticks’ in bending. In bending, the ‘sticks’ shear relative to each other and dissipate energy by rupture of the cement lines and by friction [80]. The detailed mechanism is redirection of cracks down the long axis of osteons. A larger number of osteons is associated with larger bending toughness and longer fatigue life [26, 31]. In a long bone, the osteons are largely aligned with the axis of the bone. As a consequence, the weak cement-line interfaces are also lined up with the bone axis. Due to the alignment of the weak interfaces, the strength of remodeled cortical bone is more anisotropic (i.e. it is weaker in lateral and radial tension) than is primary bone. Primary bone is also weaker in radial and lateral tension compared to axial, but this arises from the inherent properties of the primary lamellae as opposed to the cement lines. Mathematical descriptions of the anisotropy of strength can become quite challenging [81, 82] and will not be reviewed here.
Strain rate, fracture propagation toughness and fatigue Much of bone function is explained by modulus and strength under a single load. For a better understanding, however, there are several other important mechanical properties to examine. In this section, three will be presented.
Strain Rate Bone mechanical properties are significantly affected by loading rate. With increase in loading from slow (0.08/s) to fast loading (17/s), modulus tended to increase, yield and failure strength increased up to 1/s then fell and the strain at yield remained unchanged up to 10/s, but decreased subsequently [83]. These strain rate effects can be significant and are often represented mathematically as an additional factor
C h a p t e r 5 The Mechanical Properties of Bone l
in apparent density power laws for properties: Property A(strain rate)B(apparent density)C. The strain rate exponent is usually fairly small. With B 0.05 [84], the predicted relative effect of strain rates 1/s and 0.08/s is a 13% increase in the mechanical properties ((1/0.08)0.05 1.13). The effect of strain rate is reduced by ovariectomy in sheep [85], but it is unknown whether this is important in humans.
Fracture Toughness and Damage Fracture toughness is the resistance of bone to the propagation of an existing crack. This is a different property from toughness, which is the amount of energy absorbed before failure. There are three fracture toughness values for initiation of crack propagation (two in shear and one in tension) and, also, three fracture toughness values related to the continuation of crack propagation once it is initiated. A very important property of bone is that the force to propagate a crack increases as the crack grows [86]. Technically, this is called a rising R-curve, which always struck me as about the most obscurant phrase in the mechanical properties lexicon. Regardless, the benefit to an organism of a rising R-curve is that as a crack elongates, it becomes more and more difficult to continue propagation. For tensile cracks, increasing resistance to crack propagation comes from unbroken ligaments that pass between the crack faces (Figure 5.12). At the tip of the crack, the protein matrix also bridges across the faces. If the crack in the mineral is small enough, it will be completely bridged by the protein matrix. Most fracture toughness theories were developed for metals and do not include the concept of propagating
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compression cracks. In bone, however, compressive cracks form by collapse of the ultrastructure in apparent kink bands (Figure 5.13) [80]. The density of a compressive crack appears to be lower than the adjacent material, suggesting that the kink bands open voids in the tissue. Microporous materials, such as snow, fracture in compression along an anti-crack [87], but this has not been tested for applicability to the nano-porous structure of bone. Both the initiation and propagation fracture toughness of bone are highly dependent upon properties of the collagenous matrix. Damage to the collagen matrix can reduce fracture toughness and, particularly, propagation toughness, to such an extent that normal function is essentially impossible. The examples of osteogenesis imperfecta and ashing discussed above demonstrate this. Any other agerelated degradation of the collagen matrix, such as cleavage by oxygen free radicals or increased cross-linking by non-enzymatic glycation, can be expected significantly to change bone fracture properties from those of a normal young adult.
Fatigue and Fatigue Damage The last of the three more complex mechanical properties to discuss here is fatigue. In essentially all materials, stresses far below the yield stress create changes in the molecular structure of the material that are small, but permanent. For any single small load, the change in the material is so small that it is not detectable by our mechanical test systems. However, with a sufficient number of small loads the changes accumulate and a degradation of the material properties becomes
Figure 5.12 A relatively large tensile crack in iliac cancellous bone imaged by quantitative backscattered electron imaging. Arrows indicate unbroken ligaments (bridges) that slow crack propagation and toughen the bone material.
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Figure 5.13 Compressive microcracks in iliac cancellous bone imaged by quantitative backscattered electron imaging. Arrows indicate three sites where cracks cause bulging of the matrix into the marrow space. The linear portions of the crack are lighter than the remainder of the matrix consistent with micro-voids opening in the tissue due to kink-band formation in the compressive failure zone.
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Figure 5.14 Number of cycles to failure in reversed tension as a function of stress. Cycles of life increase very quickly with decreased stress. Data digitized from Currey [26].
detectable. Details of this process are complex and depend on the material type, but a repeated observation for bone is that even very small loads cause the accumulation of microcracks in the hard tissue. The accumulated damage reduces the modulus and strength of bone tissue relatively slowly at first but, eventually, a critical number of loadings have passed and the material degrades extremely rapidly. The total number of loading cycles to cause failure depends on the magnitude of the load (Figure 5.14) in a highly non-linear fashion.
The importance of fatigue loading and damage to bone function are hard to overstate. A condition where bone damage accumulates is after avascular necrosis of the femoral head. In a few months or years, the dead cancellous bone of the femoral head fails in fatigue, creating the classic crescent sign. The importance of this is that the dead bone was not weaker than living bone – at least initially. The failure of the dead tissue is caused by the accumulation of damage that occurs under normal function but which would
C h a p t e r 5 The Mechanical Properties of Bone l
be repaired in a living bone. The prevention of damage accumulation by bone turnover is the last, and perhaps one of the more important, topics to discuss.
The complete dependence on damage repair for mechanical function In itself, repair is not a mechanical property of bone. However, it is a key property of the living bone that makes it difficult to predict fracture risk. For example, consider a pair of identical twins who live similar lives. If one suffers an occult avascular necrosis of the femoral head, he will accrue a femoral head fracture and the other brother will not. This is not surprising, but it is unpredictable without knowing that one brother has a dead femoral head. Next consider a case of identical quintuplets: one receives a sufficient dose of bisphosphonate to eliminate completely all remodeling; one receives no bisphosphonate and the other three brothers receive intermediate drug doses. The greatly overdosed brother has a virtual avascular necrosis of the femoral head and an eventual fracture would be expected. However, of the three brothers with intermediate doses, who will fracture his femoral head and who will not? Whatever the correct answer, it is not determined by the mechanical properties of their identical femoral heads. Clearly, damage repair is crucial to bone strength. Fortunately, clinical results and animal experiments [10, 88] show that significant reduction of remodeling by bisphosphonates can be tolerated. However, if remodeling is completely suppressed, damage accumulation is uncontrolled and fracture can result. To date, the effects of remodeling suppression are not fully understood.
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Chapter
6
Essentials of Bone Biology: Assessment of Bone Architecture Thomas F. Lang Professor in Residence, Department of Radiology and Biomedical Imaging, and Joint Bioengineering Graduate Group, University of California, San Francisco, San Francisco, CA, USA
Introduction
two dimensional, such as DXA or radiography. Volumetric imaging methods, such as quantitative computed tomography or magnetic resonance imaging, can capture the threedimensional bone structure with resolution sufficient to differentiate the cortex from the medullary cavity or, in the case of high resolution peripheral quantitative computed tomography (HR-pQCT) or high resolution magnetic resonance imaging (HR-MR), to depict the network of trabecular bone and the thickness of the cortical bone. Until relatively recently, non-invasive imaging of bone has focused on density measurement. Areal bone mineral density (aBMD) measurements by DXA provide the primary clinical surrogate measure for bone strength. In DXA studies, a one standard-deviation (SD) reduction in femoral BMD compared to age-matched normal BMD was found to result in an approximately threefold increase in fracture risk, depending on the femoral subregion assessed [9, 10]. In addition to BMD, geometric measurements, such as hip axis length or increased trochanteric width, extracted from DXA images and pelvic radiographs [11, 12], have also been documented to confer risks for hip fracture. Compared to DXA, which is an estimate of total areal bone density, QCT provides measurements of cortical and trabecular volumetric bone density [13]. Individual subregions based on trabecular and cortical compartments have been established in epidemiologic studies as independent predictors of hip fracture risk [14] and have been shown to demonstrate differential responses to pharmacologic interventions in osteo porosis [15]. Although BMD measures, whether by DXA or QCT, have strong associations with incident and prevalent fracture, they are poor fracture predictors on an individual basis. Many individuals with high BMD sustain fractures and many with low BMD do not. Further, changes in BMD do not appear to account for the large changes in fracture
Osteoporosis is one of the major public health problems facing the elderly population [1] and it results in an annual cost of 2.4 billion dollars in the state of California alone [2]. Hip fractures are the most serious manifestation of osteoporosis. Hip fracture alone affects over 250 000 elderly in the USA annually, resulting in a 20% mortality rate and substantial loss of quality of life [3]. The number of osteoporotic fractures is expected to increase as the population ages. Skeletal fractures occur when the loading forces exerted on bone exceed the strength of the bone structure. The risk factors for fractures tend to center around three different mechanisms of action: the risk of a fall or another event exerting a large force on the skeletal structure; the nature of the applied load; and the structural strength of the bone with respect to that loading condition. Bone strength under any loading scenario depends on the three-dimensional distribution of material properties, essentially the bone size, the bone shape and the material properties, elastic modulus and material strength, at each point in the structure [4]. Image-based methods, in that they provide information on both bone material properties and geometry, have become the primary method for assessment of bone strength. Imaging-based methods can be used to capture measures of bone size and architecture, such as cross-sectional area, volume, width or network connectivity, which act as surrogates rather than estimators of bone strength, or methods such as dual-energy x-ray absorptiometry (DXA) hip strength analysis [5] or finite element modeling [4, 6–8], which use point estimates of material properties across the bone structure directly to calculate mechanical properties such as moment of inertia, section modulus or whole bone strength. These methods can be
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risk associated with pharmacologic interventions. Over time, these findings and others have led to the investigation of other skeletal factors not captured in BMD measurements, including measures of bone macroarchitecture, such as bone shape and size, and microarchitecture related to the microstructure of trabecular and cortical bone. This review shall focus on imaging methods for quantification of bone architecture and estimation of strength and other mechanical properties. The review will be structured by imaging modality, starting with two-dimensional DXA and radiographic imaging and continuing to CT and MRI. Each section will be divided into measures of bone geometry and architecture and methods by which the images can be used to estimate bone strength and mechanical properties.
DXA and radiographic imaging Dual x-ray absorptiometry (DXA) was introduced in the late 1980s and has become the mainstay of osteoporosis diagnosis and clinical evaluation worldwide. In the DXA concept, x-rays with a bimodal energy spectrum, obtained either by rare-earth filtration [16] of an x-ray tube, or rapid switching of kVp [17], is passed through the body. By measuring the attenuation of x-rays within each energy and referring these measurements to calibration standards, it is possible to measure the mass of bone in grams at each point or pixel of the projectional image. An areal bone density in g/cm2 is obtained by determining a region of interest, such as the lumbar spine or the femoral neck, and dividing the total mass in g summed across all the pixels in the region by the region’s area in cm2. Starting in the early 1990s, prospective studies have documented the association of areal BMD with incident osteoporotic fracture and have documented therapy responses to anti-resorptives and other osteoporosis medications [18]. DXA has been widely adopted in the clinical setting due to its low cost, high reliability and a radiation dose which is close to daily background radiation and much smaller than that received during a transatlantic flight. Although it is a versatile technique with wide clinical acceptance, DXA is hindered by several technical limitations which compromise its clinical efficacy and utility for research studies. First, the projectional nature of DXA results in areal BMD measures that scale with bone size: of two bones with the same volumetric BMD but different volumes, the larger bone will have the greater apparent areal BMD. Second, the areal BMD measure integrates cortical and trabecular compartments, which QCT studies have shown to have distinct associations with incident hip fracture and with therapy. Third, DXA is unable to account for sclerotic deposits which may overlay bone, such as osteophytes in the vertebrae and hips. Finally, DXA is unable to take into account trabecular microstructure, both because of the projectional nature of the imaging and particularly
because of the limited spatial resolution. Because of these and other limitations, DXA is a relatively poor fracture risk estimator for individuals in so far as there are a large number of subjects with areal BMD consistent with healthy status who incur fractures and others considered osteoporotic who remain fracture-free. Some of the limitations of DXA are addressed in the new FRAX calculations of fracture risk, which take into account both areal BMD as well as a host of clinical factors that may affect skeletal properties not measured by DXA.
Hip Strength Analyses (HSA) HSA techniques are employed to derive estimates of bone dimensions and strength using DXA images. There are two extant HSA approaches which are implemented on commercial DXA systems: Hologic DXA machines use the implementation developed by Beck and co-workers [19] and GE-Lunar systems employ the methodology described by Yoshikawa et al [20]. Based on the cross-sectional moment of inertia (CSMI), which is obtained from the supero-lateral antero-medial profile through the femoral neck, and indices of femoral neck length and neck-shaft angle, both techniques can estimate indices of femoral neck bending rigidity. By dividing the distance between the femoral neck neutral axis position and the periosteal neck edge into the CSMI, it is also possible to estimate a section modulus, another estimate of femoral neck bending rigidity. The Hologic program also estimates a cross-sectional area (CSA) and an endosteal diameter, which are derived parametrically from the areal BMD. These estimates are based on assumptions of a constant mineralization, a circular femoral neck shape and a fixed proportion of bone mass distributed between the cortical and trabecular compartments. The assumptions implicit in HSA signify that caution should be used in interpreting changes in such indices as a function of treatment, as parathyroid hormone (PTH) treatment or anti-resporptive treatment can change the areal BMD and mineralization of bone as well as differentially alter the trabecular and cortical envelopes. HSA measures have been found to be associated with incident risk of hip fracture, but these measures do not appear to predict hip fractures independently of or better than BMD [21, 22]. Standard pelvic radiographs using traditional screen film systems have been used to assess proximal femoral structure since the advent of the Singh Index in the late 1980s [23, 24]. The Singh Index was developed on the premise that hip fracture risk may depend on the integrity of the bands of load-bearing trabeculae that are clearly evident in the radiographs. The Singh Index is computed as a six level grade of the integrity of five anatomic groups of trabeculae, with level VI denoting the clear visibility of all trabecular groups and level 1 denoting the clear visibility of only the principal compressive band. Data relating geometric measurements from pelvic radiographs to incident
C h a p t e r 6 Essentials of Bone Biology: Assessment of Bone Architecture l
hip fracture were obtained in the early 1990s in the Study of Osteoporotic fractures. Glüer et al compared baseline pelvic radiographs in 162 women who had incurred an incident hip fracture to 162 randomly selected non-fractured controls and observed that subjects with fractures had lower indices of cortical thickness in the femoral shaft and neck, a wider trochanteric region and lower Singh scores for the tensile groups of proximal femoral trabeculae [11]. A multi variate model composed of all four measures predicted hip fractures as well as hip BMD. By digitizing standard radiographs, or using digital radiography systems, it is possible to employ image processing and segmentation to extract information on the trabecular network and cortical parameters that can be used to predict femoral strength. Some of this work is currently under clinical evaluation to be introduced commercially. This not only includes a computer system for analysis of femoral radiographs, but radiographic analyses based on x-rays of the hand and wrist, which have also been found to yield variables that are predictive of hip and other osteoporotic fractures.
Computed tomography (CT) CT is a three-dimensional x-ray absorptiometric measurement which provides the distribution of linear attenuation coefficient in a thin cross-section of tissue. The cross-section of the object being scanned is contained within a fan of xrays defined between the edges of the detector array and an x-ray point source. The x-ray attenuation of the patient is measured along ray-paths corresponding to the lines defined between individual detector elements and the x-ray source. Along the length of the scanning system, the x-ray beam is shaped to radiate a relatively thin ‘slice’ of tissue, ranging from m in the case of micro CT, hundreds of m in the case of high resolution CT systems and millimeters in the case of clinical scanners. The fan of x-rays circumscribes a circular field of view, which is itself contained within a square image matrix, which typically consists of two-dimensional arrays of square pixel elements, or ‘pixels’. Because the image represents a slice of tissue, the picture elements have a thickness and, thus, are volume elements, or ‘voxels’. The dimensions of the voxels may be adjusted depending on the size of the organ being imaged. Depending on the type of scanner, the voxel dimensions range from the m level to roughly 1 mm ‘in plane’ and up to several mm in slice thickness. The CT image is acquired when the x-ray source and detector rotate around the patient and the absorption is continuously measured for each detector element. Through a 360-degree source-detector rotation, each voxel is intersected by several ray-paths. The x-ray absorption measurements taken at the different angles are recorded in a computer and combined in a process known as back-projection to calculate the linear attenuation coefficient at each voxel. In the resulting
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CT image, the voxel values are based on the linear attenuation coefficients. Because these linear attenuation coefficients depend on the effective x-ray energy (which varies between CT scanner models and different kVp settings of the same scanner), a simple scale, known as the Hounsfield scale, is used to standardize them. The gray-scale value of each voxel is represented as a Hounsfield Unit (HU), which is defined as the difference of the linear attenuation coefficient of a given voxel from that of water, divided by the linear attenuation coefficient of water. The HU scale is a linear scale in which air has a value of 1000, water 0, muscle 30, with bone typically ranging from 300 to 3000 units. The value of the Hounsfield unit for a given tissue type depends on several technical factors. First, if the sizes of the structures in the tissue are smaller than the dimensions of the voxel, the HU value is subject to partial volume averaging, in which the HU value is the average HU of the constituent tissues of the voxel, weighted by their volume fractions. For example, a 0.78 mm 0.78 mm 10 mm voxel of trabecular bone is a mixture of bone, collagen, cellular marrow and fatty marrow and HU is the volume-weighted average of these four constituents. Beam hardening is a second source of variation in HU. In a CT image, the result of this is that for the same tissue, attenuation coefficients at the outside of the patient are systematically higher than those in the interior. Although manufacturers of CT equipment have implemented beam-hardening corrections, the efficacy of these corrections varies between manufacturers and between technical settings on different machines. Image data for multiple slices are acquired with motion of the patient table through the CT gantry. In older models of CT scanners, the patient table stepped in discrete increments and a 360° rotation of the source/detector was performed at each position. Helical CT scanning was introduced in the early 1990s. In this scanning approach, the detector and x-ray tube rotates while the table moves continuously, resulting in acquisition of a volume of data. The x-ray spot describes a spiral trajectory, with use of interpolation to fill in data between the arms of the spiral. Introduction of this technology resulted in significant reductions in image acquisition time [25, 26] and, combined with the advent of powerful, inexpensive computer workstations, has enabled the clinical development of volumetric QCT analyses of the spine and hip as will be discussed in the following sections. In the late 1990s and early 2000s, the first multidetector CT systems were introduced and are expected to have an important impact in skeletal assessment. In multidetector systems, the single detector array is replaced by a series of detector segments, allowing for the reduction of imaging time and improved usage of radiation dose. Initial multidetector systems featured 4–16 detector rows and the newer systems feature 64 rows of detector data, with recent introduction of 256-detector systems. The newest multidetector systems allow for acquisition of CT cross-sections of submillimeter thickness, resulting in the ability to acquire high quality
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volumetric scans with the resolution along the table axis comparable to the in-plane spatial resolution. As will be described later, this technology will allow for improved analyses of skeletal sites such as the proximal femur, which must be resampled through oblique reformations of the scan data.
Assessment of bone mineral density: quantitative computed tomography (QCT) CT BMD assessment is based on quantitative analysis of the HU in volumes of bone tissue. Typically, the BMD is quantified using a bone mineral reference phantom that is scanned simultaneously with the patient. In order to minimize the impact of beam hardening, the calibration phantom is placed as close as possible to the vertebrae and is normally located under the lumbar spine of the patient. The calibration standard originally developed by Cann et al at UCSF, and which is currently marketed by Mindways (South San Francisco, CA, USA) consists of an acrylic wedge containing cylinders of solutions with varying concentrations (200 mg/cm3, 100 mg/cm3, 50 mg/cm3, 0 mg/cm3) of dipotassium hydrogen phosphate in water [27]. An additional cylinder contained alcohol as a reference material for fat. A solid calcium hydroxyapatite-based calibration standard was later developed by Image Analysis (Columbia, KY, USA) and by Siemens Medical Systems (Erlangen, Germany). The Image Analysis standard consists of rods with varying concentrations (200 mg/cm3, 100 mg/cm3 and 50 mg/cm3) of calcium hydroxyapatite mixed in a waterequivalent solid resin matrix [28]. During the analysis of the QCT image, regions of interest are placed in each of the calibration objects and linear regression analysis is used to determine a relationship between the mean HU measured in each region and the known concentrations of bone-equivalent material. This calibration relationship is then used to convert the mean HU in the patient region of interest (e.g. vertebra or proximal femur) into a concentration (reported in mg/cm3, i.e. the mass of bone per unit tissue volume) of bone equivalent material in the region of interest. Unlike areal bone mineral density, the QCT density measurement is independent of bone size and, thus, is more robust measure for comparisons of bone density between populations and potentially for growing children as well. The major source of error in the QCT bone measurement is the phenomenon of partial volume averaging. Because the voxel dimensions in QCT measurements (0.8–1.0 mm in the imaging plane, 3–10 mm slice thicknesses) are larger than the dimensions and spacing of trabeculae, a QCT voxel includes both bone and marrow constituents. Thus, a QCT measurement is the mass of bone in a volume containing bone, red marrow and marrow fat. A single-energy QCT measurement is capable of determining the mass of bone in a volume
consisting of two components (e.g. bone and red marrow), but not in a three-component system. Resolving the mass fractions of bone, red marrow and marrow fat in the QCT voxel requires a dual-energy QCT measurement. Because fat has a HU value of 200, compared to 30 HU for red marrow and 300–3000 HU for bone, the presence of fat in the QCT volume reduces the depresses the HU measurement. Thus, the presence of marrow fat causes single-energy QCT to underestimate the mass of bone per unit tissue volume, an error which can be corrected using dual-energy acquisitions. The effect of marrow fat on QCT measurements is larger at the spine than at the hip or peripheral skeletal sites. Whereas the conversion from red to fatty marrow tends to finish by the mid-20s in the hip and peripheral skeleton, the vertebrae show a gradual age-related increase in the proportion of fat in the bone marrow which starts in youth and continues through old age [29]. The inclusion of fatty marrow in the vertebral BMD measurement results in accuracy errors ranging from 5 to 15% depending on the age group. However, because the increase in marrow fat is age-related, single energy CT data can be corrected using age-related reference databases and the residual error is not considered to be clinically relevant. Provided that the QCT scan is acquired at low effective energies (i.e. 80–90 kVp), the population SD in marrow fat accounts for roughly 5 mg/cm3 of the 25–30 mg/cm3 population SD in spinal trabecular BMD. This residual error is not considered large enough to merit clinical use of dualenergy techniques, which are more accurate, but which have larger radiation doses and precision errors.
Measurement of structure and BMD using volumetric CT images of the spine and hip Almost all CT scanners in current clinical practice are multidetector models, allowing acquisition of multiple crosssectional images, or ‘slices’, in a single rotation of the detector array. Multidetector systems in current clinical use range from 4- and 8-detector systems up to 256 detector systems with total widths up to 15 cm. The advent of multidetector CT allows for acquisition of large scan volumes within time periods of seconds. The speed of scanning reduces the procedure time to the time required to position the patient on the table and define an anatomic volume for acquisition. The ability rapidly to image and reconstruct large volumes of tissue has made feasible the application of threedimensional (3D) CT-based analytic methods to clinical osteoporosis assessment and to research in osteoporosis. For assessment of the central skeleton, analytic methods have been developed which quantify structural and density measurements from 3D reconstructions of whole vertebrae and proximal femora. One of the most powerful applications of helical CT scanning and three-dimensional image analysis
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is for assessment of bone mineral density, geometry and strength of the proximal femur. Analysis approaches range from assessment of density, geometry and macrostructural processes based on reconstruction of cross-sections and volumes of femoral neck tissue to finite element modeling approaches to model the strength of the hip based on bone geometry and material properties mapped from CT image values. Densitometric and structural assessments based on volume reconstructions of the proximal femur based on CT scans have been developed at the University of California, San Francisco (UCSF) [30, 31], the University of Erlangen [32, 33], the Mindways Company [34], Image Analysis [35] and the Mayo Clinic [36]. The approaches developed at UCSF and University of Erlangen involve reformatting of the QCT scans along the femoral neck axis and segmentation of the entire proximal femoral envelope, with combinations of mathematical morphology and thresholding, and edge detection approaches to derive the cortical envelope for volume and thickness assessments. The computer algorithm described by Kang et al carries out volumetric analyses of the femoral neck [32, 33] and the approach described by Lang et al at UC San Francisco (Figure 6.1) processes three-dimensional CT images of the proximal femur to measure bone mineral density in the femoral neck, the total femur and in a region which combines the trochanteric and intertrochanteric subregions similar to those of DXA systems [30, 31]. Within each anatomic subregion, the density, mass and volume are computed for the cortical and trabecular components as well as for the integral bone envelope. For trabecular BMD measurements, the precision of this method in vivo was found to range from 0.6% to 1.1% depending on the volume of interest assessed [30]. Both the Erlangen and UCSF approaches carry out geometric and structural analyses of the minimum femoral neck cross-section, computing crosssectional area, estimates of cortical volume and thickness
Femoral neck
Trochanteric
Total femur
Figure 6.1 Proximal femoral integral regions of interest derived from volumetric QCT (red) overlaid on a 3D reconstruction of CT scan data (green). (See color plate section).
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and moments of inertia for strength estimation. The approach for proximal femoral analysis developed at the Mayo clinic [36, 37] does not reconstruct the whole proximal femoral volume, a single cross-section of the femoral neck is reconstructed and measures of integral, cortical and medullary density and cross-sectional area are computed in addition to bending and axial compressive strength indices.
Findings based on volumetric QCT analyses While earlier studies using QCT have documented that density and structural measures are associated with proximal femoral strength in vitro [30], recent data have confirmed that measures of density and structure are associated with hip fracture in vivo. A recent cross-sectional study comparing women imaged within 48 hours of a hip fracture to age and body-size matched controls, showed that hip fracture was significantly associated with reduced vBMD in the cortical, integral and trabecular compartments, as well as reduced measures of cortical volume and thickness [38]. Two interesting findings of the study were that fracture status was associated with increased femoral neck cross-sectional area, consistent with an earlier finding of increased proximal femoral intertrochanteric width from pelvic radiographs in the Study of Osteoporotic Fractures [39]. The study also found that measures of cortical geometry and trabecular vBMD were independently associated with hip fracture. QCT was also employed to characterize the association of femoral neck density and geometry parameters with incident hip fracture in men in the prospectively designed Mr Os study. Black et al reported that the percentage of proximal femoral tissue volume occupied by cortical tissue, a measure of cortical thickness, and the cross-sectional area of the femoral neck, were both associated with incident hip fracture in men aged 69–90 years, independently of BMD measured either volumetrically by QCT or areally by DXA [14]. The percentage cortical volume in the femoral neck was a particularly powerful predictor, with a one standard deviation reduction increasing the relative risk of fracture nearly three-fold. Interestingly, however, the predictive power for incident hip fracture of QCT BMD and the independently associated geometric parameters in a multivariate model were not better than that of hip DXA. This may be because, as described earlier, areal BMD by hip DXA comprises information regarding bone density and bone size, both of which are hip fracture risk factors. A new approach to incorporating both hip BMD and 3D geometric information into the prediction of hip fracture risk has been proposed by Li et al [40]. Using the CT scans from the cross-sectional study in Chinese women described above, they first employed an intersubject image registration approach to register all of the scans onto a common
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hip coordinate system, creating a voxelized 3D model of the entire cohort. Li et al then divided the cohort into training and test subgroups, with each subgroup containing half of the fracture and control subjects, and with a voxel-based model for each subgroup. Within the training subgroup, they carried out an analysis of variance (ANOVA) to determine which voxels in the training 3D model were most highly correlated with hip fracture status. This resulted in a region of interest corresponding to voxels with highest association with hip fracture. They then mapped this region into the scans of the test subject and compared BMD measured in that region between the fracture subjects and control, observing that it tended to be more strongly associated with hip fracture status than standard regions of BMD assessment, such as femoral neck or total femur [41]. In addition to fracture status, recent studies have delineated the correlation of these measures to age [37, 42], drug treatment [15, 43] and changes in mechanical loading [44]. Using volumetric QCT in a seminal cross-sectional study of aging, Riggs et al compared measures of proximal femoral volumetric density, cortical geometry and femoral neck cross-sectional area between young normal and aging subjects of the Rochester Study [37]. In addition to powerful age-related declines across multiple indices of volumetric cortical and trabecular bone mineral density and cortical thickness, they observed higher femoral neck cross-sectional areas in the older subjects, supporting the idea of periosteal apposition as a compensation for age-related bone loss [37, 45, 46]. Consistent findings of age-related increases in measures of femoral neck, femoral shaft and vertebral cross-sectional area were supported by other cross-sectional studies reported by Sigurdsson et al, who studied a cohort of Icelandic men and women aged 66–90 years [45], by Marshall et al, who studied aging American men [46, 47] and by Meta et al, who compared young and elderly American women [42]. At the present time, several studies have documented the response of bone density and structure variables measured by QCT to pharmacologic interventions. There have been several studies in which QCT has been employed to characterize the differential effects of PTH treatment on cortical and trabecular bone. In the proximal femur, studies of PTH 1-84 and teriparatide (12 and 18 months respectively) have shown concurrent increases in trabecular volumetric BMD and decreases in cortical volumetric BMD [15, 43]. Black et al have reported that one year of PTH 1-84 therapy resulted in an increase of cortical tissue volume consistent with increased amount of cortical tissue having low mineralization [15, 43]. Studies of anti-resorptive medications have reported smaller increases in proximal femoral trabecular and cortical bone mineral density by QCT, although, in these cases, positive changes have been associated with increases in both compartments. QCT based studies of information regarding the response of proximal femoral density and structure variables to changes in mechanical loading have been provided by two
longitudinal studies of astronauts undergoing and recovering from spaceflights of roughly six-month duration on the International Space Station. Lang et al reported that crews on long-duration spaceflight lose, on average, 1–2.7% of their proximal femoral bone mass per month of spaceflight, depending on anatomic subregion and compartment [31]. A study following the same subjects one year after their return from their mission observed that, while indices of bone mass recovered nearly completely, indices of volumetric bone mineral density only recovered to a small extent and that this discrepancy could be explained by an increase in the bone size during the year after flight, supporting the idea that periosteal apposition could be a response to resumed weight bearing after the loss of large amounts of bone during the flight [44].
3D QCT of the vertebrae In the spine, the use of volumetric QCT measurements impacts precision more than discriminatory capability. Their ability to improve the precision of spinal measurements relates to the use of three-dimensional anatomic landmarks to guide the placement of volumes of interest and to correct for differences in patient positioning which affect single slice scans. Currently, single-slice QCT techniques are highly operator dependent, requiring careful slice positioning and angulation as well as careful region of interest placement. Lang et al developed a volumetric spinal QCT approach in which an image of the entire vertebral body (Figure 6.2) is acquired and anatomic landmarks such
3Dtrab
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Figure 6.2 QCT vertebral regions of interest. Top row of images are three-dimensional regions and bottom row are standard trabecular and integral bone regions defined on the mid-vertebral cross-section. (See color plate section).
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as the vertebral endplates and the spinous process are used to fix the 3D orientation of the vertebral body, allowing for definition of new trabecular and integral regions which contain most of the bone in the vertebral centrum, as shown in Figure 6.2 [48]. Although measuring a larger volume of tissue may enhance precision, these new regions are highly correlated with the mid-vertebral subregions assessed with standard QCT techniques and may not contain significant new information about vertebral strength. Consequently, volumetric studies of regional BMD, which examine specific subregions of the centrum that may vary in their contribution to vertebral strength, and studies of the cortical shell, the condition of which may be important for vertebral strength in osteoporotic individuals, are of interest for future investigation.
Finite element modeling (FEM) FEM is a mathematical technique used by engineers to evaluate the strength of complex structures such as engine parts, bridges and, more recently, bones. The structure is divided into ‘finite elements’ (discrete pieces of the structure) to form an ‘FE mesh’ so that it can be analyzed. The advantage of using FEM in this study is that this method can account for the material heterogeneity and irregular geometry of the femur, factors that cannot be considered using other approaches. Until recently, it has not been possible to analyze individual bones due to the extraordinary amount of labor involved in generating the FE mesh. Not only does the complex 3-D geometry need to be defined, but the material properties, which vary dramatically within the bone, must be specified. As a result, researchers have often spent months, or even years, to create just one FE model and, even then, the model often lacked adequate refinement. To address this problem, researchers have developed methods to derive finite element models from CT scans of the hip and spine. These methods involve volumetric QCT whole hip [4, 49–52] or whole vertebra images [6, 7, 53] obtained with 1-mm or 3-mm slice thickness. The finite element modeling application involves three steps. First, the bone geometry information is obtained by determining the outer boundaries of the proximal femora or vertebra on each imaged crosssection on the stack of cross-sections which encompass the bone. Next, material properties, such as elastic modulus and strength, are computed for each voxel within the bone boundaries. These are computed using parametric relationships between BMD and material properties obtained by scanning and then mechanically testing samples of trabecular and cortical bone. Once the material properties and bone geometry have been defined, load vectors are applied, which simulate the forces applied to bone in normal loading, or in traumatic events such as falls. Keyak et al have developed an automated, CT scan-based method of generating patientspecific FE models of the hip [4, 49, 50]. This method takes
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advantage of the voxel-based nature of quantitative CT scan data to achieve fully automated mesh generation and, more significantly, to allow heterogeneous material properties to be specified. The FE models can be analyzed using a loading condition simulating a load on the femur in a single-legged gait or a fall backwards and to the side with an impact on the greater trochanter. For each voxel, elastic modulus and strength are estimated as material properties and the factor of safety (FOS) is determined as the strength at each element divided by the stress, with FOS 1 representing mechanical failure. A fracture is considered to occur if 15 contiguous elements fail. The outcome variable produced by the modeling technique is failure load, which is defined as the load magnitude required to produce a fracture. This procedure has been extensively tested in vitro, with high correlations to measured failure load for both loading conditions (r 0.95 and 0.96 for fall and stance loading conditions, respectively [4]). In addition to their close correlation with fracture load, the FE models depict areas of high strain which occur at the sites where the bones fracture in vitro and where fractures occur in vivo. The application of FEM to clinical studies has been limited in the past, but is now growing with the wide employment of CT scanning in clinical osteoporosis research. Orwoll et al recently reported that proximal femoral strength and the ratio of applied load to proximal femoral strength were strongly associated with incident hip fracture in elderly men [8]. In particular, load to strength ratio remained strongly and significantly associated with incident hip fracture even after areal BMD was taken into account. Keaveny et al reported on the use of FEM to estimate changes of proximal femoral strength associated with one year’s administration of PTH 1-84, alendronate, and a combination of these two therapies [54]. In the second year of the study, the PTH group was split into alendronateand placebo-treated subgroups and the combination and alendronate groups were also followed up with alendronate. For the first year of treatment, both the PTH and alendronate group showed small but significant increases of femoral strength from baseline and, in the second year, femoral strength continued to increase for all groups but the placebo group, with the group initially treated by PTH showing the largest overall change in strength. It seems that the relatively modest increases in strength reported for the PTH group are consistent with the idea that PTH treatment has an initially negative effect on cortical bone, which counteracts the large increases in trabecular bone mineral density. Keaveny et al recently applied FEM to compare the effects of teriparatide and alendronate on estimated vertebral strength and vertebral bone density [7] and Lian et al employed FEM to compare estimated proximal femoral strength between subjects with glucorticoid-induced osteoporosis and age-matched controls [55]. In addition to studies of fracture risk and drug treatment, FEM of the hip has also been used to study the effect of mechanical unloading of the proximal femur in long-duration spaceflight. Keyak et al reported that crew
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members undergoing International Space Station missions of 6 months average length showed loss of proximal femoral strength on the order of 2–2.6%/month of flight, which is roughly double the rate of bone loss reported for studies of integral bone density by DXA and QCT [56]. Figure 6.3 shows an example of the application of single-legged stance and posterolateral fall loading conditions to a finite element model of the proximal femur, as computed by Keyak.
been employed to gain insight into the effects of aging [59, 60], menopause [61] and drug treatments [62–67]. In addition to benchtop devices capable of imaging human bone specimens and whole animal bones in vitro and rodents in vivo, there are also systems available for imaging the structure of peripheral bones in humans in vivo. Norland-Stratec have developed devices that can image skeletal sites such as the forearm, femur and tibia at voxel sizes of 200–800 MA and radiation doses from 2 to 30 Sv, depending on the site being imaged [68–69]. Although not capable of imaging trabecular architecture, these systems have been widely used to study structural properties of peripheral skeletal sites such as cross-sectional moment of inertia, cross-sectional area and cortical area [70–72]. More recently, Scanco has developed a peripheral QCT system which can obtain an isotropic spatial resolution of 100 M with an effective radiation dose less than 10 mSv per measurement [58]. This device can assess compartmental bone density as well as indices of apparent trabecular and cortical microstructure with good precision (4%). For a typical scan session of 9 mm with 110 sections, the scan time is on the order of 3 minutes, which can result in motion artifacts that may require rescanning. Recent studies have shown cross-sectional association between indices of trabecular and cortical structure assessed at the distal radius and tibia with prevalent femoral neck [71] and vertebral fracture [72] which were independent of areal BMD of the spine. At this juncture, this device does not yet have data confirming ability to predict fracture in the prospective setting, nor are there any published studies of response of the trabecular and cortical microstructure parameters to drug treatment. Figure 6.4 shows images obtained by a desktop microCT device and by the high resolution pQCT device developed by Scanco. Magnetic resonance imaging (MRI) provides a method for imaging bone structure in primarily peripheral skeletal sites that does not require ionizing radiation [73–77]. In MRI
MicroCT methods While QCT using whole body CT scanners allows for differential assessment of the cortical and trabecular compartments and estimates of bone strength using the information on material properties and geometry derived from the scans, these images do have sufficient spatial resolution to quantify accurately the properties of the thin proximal femoral cortices and cannot be used to study the characteristics of trabecular microarchitecture. Specialized scanners have been developed to measure trabecular and cortical properties at extremely high spatial resolutions (5–20 M) in specimens and animals and at somewhat lower resolution (50–100 M) at peripheral skeletal sites in vivo in humans. Benchtop microCT scanners have been developed for characterization of human and animal bone specimens as well as live animals [57, 58]. These scans may be employed to derive morphologic properties of the trabecular network, including bone volume/total volume, trabecular surface area, trabecular size and spacing, as well as porosity. The parameters quantified from microCT images have been based on histomorphometric definitions proposed by Parfitt and studies have shown a high correlation between measurements from 3D microCT images and parameters assessed by standard histomorphometry. Trabecular structure measures based on biopsies have
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Figure 6.3 Proximal femoral finite element models showing (A) application of loading forces (red arrows) in a single legged stance and (B) a fall to the side with an impact on the posterolateral aspect of the lesser trochanter (Courtesy of J Keyak University of California, Irvine). (See color plate section).
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imaging, the body part of interest is placed in a strong external magnetic field and protons contained in the body’s tissues are excited by a series of pulses from a radiofrequency coil placed on the site of interest. An image is generated by detection of the pulses of energy produced by the protons as they decay back from the excited state. The strength of MRI is its ability to depict soft tissues, which contain lipids and other components which are proton rich. Since hydrocarbons and other proton-rich compounds are scarce in skeletal tissue, bone manifests as a signal void in MRI images.
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For high-resolution skeletal imaging, MRI is most often applied at peripheral skeletal sites where a high signal to noise ratio is obtained because of the thin soft tissue layer interposed between the bone of interest and the radiofrequency coil. Thus, for skeletal structure assessment, MRI has generally been performed for the calcaneus [74, 75, 78], distal radius [79], phalanges [80] and, more recently, the trochanteric portion of the proximal femur [81–83]. Using surface coils in conjunction with 1.5 T and 3 T whole body scanners, voxels sizes of 150–300 M in plane and 300–500 M slice thickness are typically obtained. Because the trabecular thickness is of the order of 150 mM with a spacing on the order of 300 mM, these measurements are used to derive apparent rather than direct estimates of trabecular structure. Studies have shown these measures to correlate strongly with microCT measures obtained at higher spatial resolution and MRI has been widely used in clinical research studies. MRI based indices of trabecular structure obtained at the distal radius, calcaneus and phalanges have been shown to reflect menopause-, age- and treatmentrelated changes and limited cross-sectional studies have shown associations between alterations of indices of apparent trabecular microstructure and prevalent vertebral fracture [84, 85]. The development of new radiofrequency coils and sequences have made possible imaging of trabecular structure of trabeculae in the region of the hip close to the body surface. Further improvements may become possible through imaging at 7 T and use of parallel imaging to increase efficiency of data collection. Figure 6.5 shows high-resolution MRI images of the distal radius and proximal femur.
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Figure 6.4 Micro CT image (Scanco 40) of cubic specimens from the distal radius from a non-osteoporotic (A) and (B) osteo porotic human donors obtained at 10 M spatial resolution; (C) shows a scan through the distal radius in a young healthy volunteer obtained with the ScanCo XtremeCT at 82 M voxel size. (Courtesy of Dr. G. Kazakeia, University of California, San Francisco).
Improvements in imaging technology and image processing techniques have made it possible to extend clinical osteoporosis research beyond bone mineral density into indices of bone structure. These techniques range from estimates made on relatively crude imaging technologies, such as DXA and radiographic imaging, to more sophisticated approaches based on images from volumetric CT acquisitions. These measures range from estimates of sectional strength estimates from cross-sections through the femoral neck and indices of apparent cortical thickness and volume, to finite element modeling methods which take into account the full 3D information on the bone geometry and material properties to estimate the whole bone strength. Although the resolution of CT scanners has improved greatly due to the introduction of multidetector systems, the images are still not of sufficient quality directly to assess trabecular microstructure and cortical thickness. To this end, microCT has become available for high-resolution scanning of bone specimens and live animals and high-resolution devices such as the XtremeCT HR-PQCT device have been developed
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Figure 6.5 High-resolution MRI images obtained through the distal radius for (A) a young normal subject and (B) a 76-year old osteoporotic subject; (C) shows an example of an MRI image through the proximal femur employed for structural assessments which are currently in an exploratory stage. (Courtesy of Dr. S. Majumdar, University of California, San Francisco).
for estimates of trabecular texture and cortical structure at peripheral skeletal sites.
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6. R.P. Crawford, W.S. Rosenberg, T.M. Keaveny, Quantitative computed tomography-based finite element models of the human lumbar vertebral body: effect of element size on stiffness, damage, and fracture strength predictions, J. Biomech. Eng. 125 (2003) 434–438. 7. T.M. Keaveny, D.W. Donley, P.F. Hoffmann, B.H. Mitlak, E. V. Glass, J.A. San Martin, Effects of teriparatide and alendronate on vertebral strength as assessed by finite element modeling of QCT scans in women with osteoporosis, J. Bone Miner. Res. 22 (2007) 149–157. 8. E.S. Orwoll, L.M. Marshall, C.M. Nielson, et al., Finite element analysis of the proximal femur and hip fracture risk in older men, J. Bone Miner. Res. (2008). 9. S.R. Cummings, D.M. Black, M.C. Nevitt, et al., Bone density at various sites for prediction of hip fractures: the study of osteoporotic fractures, Lancet 341 (1993) 72–75. 10. A.M. Schott, C. Cormier, D. Hans, et al., How hip and wholebody bone mineral density predict hip fracture in elderly women: the EPIDOS prospective study, Osteoporos. Int. 8 (1998) 247–254. 11. C.C. Glüer, S.R. Cummings, A. Pressman, et al., Prediction of hip fractures from pelvic radiographs: the study of osteo porotic fractures, J. Bone Miner. Res. 9 (1994) 671–677. 12. K.G. Faulkner, S.R. Cummings, C.C. Glüer, L. Palermo, D. Black, H.K. Genant, Simple measurement of femoral
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geometry predicts hip fracture: the study of osteopotic fractures, J. Bone Miner. Res. 8 (1993) 1211–1217. H.K. Genant, C.E. Cann, B. Ettinger, G.S. Gordan, Quantitative computed tomography of vertebral spongiosa: a sensitive method for detecting early bone loss after oophorectomy, Ann. Int. Med. 97 (1982) 699–705. D.M. Black, M.L. Bouxsein, L.M. Marshall, et al., Proximal femoral structure and the prediction of hip fracture in men: a large prospective study using QCT, J. Bone Miner. Res. 23 (2008) 1326–1333. D.M. Black, S.L. Greenspan, K.E. Ensrud, et al., The effects of parathyroid hormone and alendronate alone or in combination in postmenopausal osteoporosis, N. Engl. J. Med. 349 (2003) 1207–1215. R.B. Mazess, B. Collick, J. Trempe, H. Barden, J. Hanson, Performance evaluation of a dual energy x-ray bone densitometer, Calcif. Tissue Int. 44 (1989) 228–232. J.A. Stein, J.L. Lazewatsky, A.M. Hochberg, Dual energy x-ray bone densitometer incorporating an internal reference system, Radiology 165 (P) (1987) 313. D. Black, S. Cummings, D. Karpf, et al., Randomised trial of effect of alendronate on risk of fracture in women with existing vertebral fractures, Lancet 348 (1996) 1535–1541. T.J. Beck, B.R. Christopher, K.E. Warden, W.W. Scott, G.U. Rao, Predicting femoral neck strength from bone mineral data: a structural approach, Invest. Radiol. 25 (1990) 6–18. T. Yoshikawa, C.H. Turner, M. Peacock, et al., Geometric structure of the femoral neck measured using dual-energy x-ray absorptiometry, J. Bone Miner. Res. 9 (1994) 1053–1064. S. Kaptoge, T.J. Beck, J. Reeve, et al., Prediction of incident hip fracture risk by femur geometry variables measured by hip structural analysis in the study of osteoporotic fractures, J. Bone Miner. Res. 23 (2008) 1892–1904. F. Rivadeneira, M.C. Zillikens, C.E. De Laet, et al., Femoral neck BMD is a strong predictor of hip fracture susceptibility in elderly men and women because it detects cortical bone instability: the Rotterdam study, J. Bone Miner. Res. 22 (2007) 1781–1790. S.H. Patel, K.P. Murphy, Fractures of the proximal femur: correlates of radiological evidence of osteoporosis, Skeletal Radiol. 35 (2006) 202–211. Y.M. Singh, A.R. Nagrath, P.S. Maini, Changes in trabecular pattern of the upper end of the femur as an index of osteoporosis, J. Bone Joint Surg. 52A (1970) 457–467. W.A. Kalender, A. Polacin, Physical performance of spiral CT scanning, Med. Phys. 18 (1991) 910–915. W.A. Kalender, W. Seissler, E. Klotz, P. Vock, Spiral volumetric CT with single-breath-hold technique, continuous transport and continuous scanner rotation, Radiology 176 (1990) 181–183. C.E. Cann, H.K. Genant, Precise measurement of vertebral mineral content using computed tomography, J. Comp. Assist. Tomogr. 4 (1980) 493–500. K.G. Faulkner, C.C. Glüer, S. Grampp, H.K. Genant, Cross calibration of liquid and solid QCT calibration standards: corrections to the UCSF normative data, Osteo. Int. 3 (1993) 36–42. M. Dunnill, J. Anderson, R. Whitehead, Quantitative histological studies on age changes in bone, J. Pathol. Bacteriol. 94 (1967) 275–291.
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30. T.F. Lang, J.H. Keyak, M.W. Heitz, et al., Volumetric quantitative computed tomography of the proximal femur: precision and relation to bone strength, Bone 21 (1997) 101–108. 31. T. Lang, A. LeBlanc, H. Evans, Y. Lu, H. Genant, A. Yu, Cortical and trabecular bone mineral loss from the spine and hip in long-duration spaceflight, J. Bone Miner. Res. 19 (2004) 1006–1012. 32. Y. Kang, K. Engelke, W.A. Kalender, A new accurate and precise 3-D segmentation method for skeletal structures in volumetric CT data, IEEE Trans. Med. Imaging 22 (2003) 586–598. 33. Y. Kang, K. Engelke, C. Fuchs, W.A. Kalender, An anatomic coordinate system of the femoral neck for highly reproducible BMD measurements using 3D QCT, Comput. Med. Imaging Graph. 29 (2005) 533–541. 34. Mindways Software Inc.2009. www.qct.com 35. Image Analysis. 2009. www.image-analysis.com 36. J.J. Camp, R.A. Karwoski, M.C. Stacy, et al., A system for the analysis of whole-bone strength from helical CT images, Proc. SPIE 5369 (2004) 74–88. 37. B.L. Riggs, L.J. Melton 3rd, R.A. Robb, et al., Populationbased study of age and sex differences in bone volumetric density, size, geometry, and structure at different skeletal sites, J. Bone Miner. Res. 19 (2004) 1945–1954. 38. X. Cheng, J. Li, Y. Lu, J. Keyak, T. Lang, Proximal femoral density and geometry measurements by quantitative computed tomography: association with hip fracture, Bone 40 (2007) 169–174. 39. C.C. Gluer, S.R. Cummings, A. Pressman, et al., Prediction of hip fractures from pelvic radiographs: the study of osteoporotic fractures. The Study of Osteoporotic Fractures Research Group, J. Bone Miner. Res. 9 (1994) 671–677. 40. W. Li, I. Kezele, D.L. Collins, et al., Voxel-based modeling and quantification of the proximal femur using inter-subject registration of quantitative CT images, Bone 41 (2007) 888–895. 41. W. Li, J. Kornak, T. Harris, et al., Identify fracture-critical regions inside the proximal femur using statistical parametric mapping, Bone 44 (2009) 596–602. 42. M. Meta, Y. Lu, J.H. Keyak, T. Lang, Young-elderly differences in bone density, geometry and strength indices depend on proximal femur sub-region: a cross sectional study in Caucasian-American women, Bone 39 (2006) 152–158. 43. M.R. McClung, J. San Martin, P.D. Miller, et al., Opposite bone remodeling effects of teriparatide and alendronate in increasing bone mass, Arch. Intern. Med. 165 (2005) 1762–1768. 44. T.F. Lang, A.D. Leblanc, H.J. Evans, Y. Lu, Adaptation of the proximal femur to skeletal reloading after long-duration spaceflight, J. Bone Miner. Res. 21 (2006) 1224–1230. 45. G. Sigurdsson, T. Aspelund, M. Chang, et al., Increasing sex difference in bone strength in old age: the age, gene/environment susceptibility-Reykjavik study (AGES-REYKJAVIK), Bone 39 (2006) 644–651. 46. L.M. Marshall, T.F. Lang, L.C. Lambert, J.M. Zmuda, K.E. Ensrud, E.S. Orwoll, Dimensions and volumetric BMD of the proximal femur and their relation to age among older US men, J. Bone Miner. Res. 21 (2006) 1197–1206. 47. L.M. Marshall, J.M. Zmuda, B.K. Chan, et al., Race and ethnic variation in proximal femur structure and BMD among older men, J. Bone Miner. Res. 23 (2008) 121–130.
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48. T.F. Lang, J. Li, S.T. Harris, H.K. Genant, Assessment of vertebral bone mineral density using volumetric quantitative CT, J. Comput. Assist. Tomogr. 23 (1999) 130–137. 49. J.H. Keyak, Improved prediction of proximal femoral fracture load using nonlinear finite element models, Med. Eng. Phys. 23 (2001) 165–173. 50. J.H. Keyak, S.A. Rossi, K.A. Jones, C.M. Les, H.B. Skinner, Prediction of fracture location in the proximal femur using finite element models, Med. Eng. Phys. 23 (2001) 657–664. 51. D.D. Cody, G.J. Gross, F.J. Hou, H.J. Spencer, S.A. Goldstein, D.P. Fyhrie, Femoral strength is better predicted by finite element models than QCT and DXA, J. Biomech. 32 (1999) 1013–1020. 52. D.D. Cody, F.J. Hou, G.W. Divine, D.P. Fyhrie, Short term in vivo precision of proximal femoral finite element modeling, Ann. Biomed. Eng. 28 (2000) 408–414. 53. K.G. Faulkner, C.E. Cann, B.H. Hasegawa, Effect of bone distribution on vertebral strength: assessment with patientspecific nonlinear finite element analysis, Radiology 179 (1991) 669–674. 54. T.M. Keaveny, P.F. Hoffmann, M. Singh, et al., Femoral bone strength and its relation to cortical and trabecular changes after treatment with PTH, alendronate, and their combination as assessed by finite element analysis of quantitative CT scans, J. Bone Miner. Res. 23 (2008) 1974–1982. 55. K.C. Lian, T.F. Lang, J.H. Keyak, et al., Differences in hip quantitative computed tomography (QCT) measurements of bone mineral density and bone strength between glucocorticoid-treated and glucocorticoid-naive postmenopausal women, Osteoporos. Int. 16 (2005) 642–650. 56. J.H. Keyak, A.K. Koyama, A. Leblanc, Y. Lu, T.F. Lang, Reduction in proximal femoral strength due to long-duration spaceflight, Bone 44 (2009) 449–453. 57. A. Laib, O. Barou, L. Vico, et al., 3D micro-computed tomography of trabecular and cortical bone architecture with application to a rat model of immobilisation osteoporosis, Med. Biol. Eng. Comput. 38 (2000) 326–332. 58. A. Laib, H.J. Häuselmann, P. Rüegsegger, In vivo high resolution 3D-QCT of the human forearm, Technol. Hlth. Care 6 (1998) 329–337. 59. W.Q. Cui, Y.Y. Won, M.H. Baek, et al., Age-and regiondependent changes in three-dimensional microstructural properties of proximal femoral trabeculae, Osteoporos. Int. 9 (2008) 1579–1587. 60. D.M. Cooper, C.D. Thomas, J.G. Clement, A.L. Turinsky, C.W. Sensen, B. Hallgrimsson, Age-dependent change in the 3D structure of cortical porosity at the human femoral midshaft, Bone 40 (2007) 957–965. 61. M.P. Akhter, J.M. Lappe, K.M. Davies, R.R. Recker, Transmenopausal changes in the trabecular bone structure, Bone 41 (2007) 111–116. 62. R.R. Recker, P.D. Delmas, J. Halse, et al., Effects of intravenous zoledronic acid once yearly on bone remodeling and bone structure, J. Bone Miner. Res. 23 (2008) 6–16. 63. R.R. Recker, L.G. Ste-Marie, B. Langdahl, D. Masanauskaite, D. Ethgen, P.D. Delmas, Oral ibandronate preserves trabecular microarchitecture: micro-computed tomography findings. From the Oral Ibandronate Osteoporosis Vertebral Fracture Trial in North America and Europe Study, J. Clin. Densitom. 12 (2009) 71–76.
64. J. Fox, M.A. Miller, R.R. Recker, S.P. Bare, S.Y. Smith, I. Moreau, Treatment of postmenopausal osteoporotic women with parathyroid hormone 1-84 for 18 months increases cancellous bone formation and improves cancellous architecture: a study of iliac crest biopsies using histomorphometry and micro computed tomography, J. Musculoskelet. Neuronal Interact. 5 (2005) 356–357. 65. B. Borah, T.E. Dufresne, E.L. Ritman, et al., Long-term risedronate treatment normalizes mineralization and continues to preserve trabecular architecture: sequential triple biopsy studies with micro-computed tomography, Bone 39 (2006) 345–352. 66. B. Borah, E.L. Ritman, T.E. Dufresne, et al., The effect of risedronate on bone mineralization as measured by micro-computed tomography with synchrotron radiation: correlation to histomorphometric indices of turnover, Bone 37 (2005) 1–9. 67. T.E. Dufresne, P.A. Chmielewski, M.D. Manhart, T.D. Johnson, B. Borah, Risedronate preserves bone architecture in early postmenopausal women in 1 year as measured by three-dimensional microcomputed tomography, Calcif. Tissue Int. 73 (2003) 423–432. 68. JL. Ferretti, Perspectives of pQCT technology associated to biomechanical studies in skeletal research employing rat models, Bone 17 (1995) 353S–364S. 69. J.L. Ferretti, R.F. Capozza, J.R. Zanchetta, Mechanical validation of a tomographic (pQCT) index for noninvasive estimation of rat femur bending strength, Bone 18 (1996) 97–102. 70. P. Schneider, C. Reiners, G.R. Cointry, R.F. Capozza, J.L. Ferretti, Bone quality parameters of the distal radius as assessed by pQCT in normal and fractured women, Osteoporos. Int. 12 (2001) 639–646. 71. L. Vico, M. Zouch, A. Amirouche, et al., High-resolution pQCT analysis at the distal radius and tibia discriminates patients with recent wrist and femoral neck fractures, J. Bone Miner. Res. 23 (2008) 1741–1750. 72. E. Sornay-Rendu, J.L. Cabrera-Bravo, S. Boutroy, F. Munoz, P.D. Delmas, Severity of vertebral fractures is associated with alterations of cortical architecture in postmenopausal women, J. Bone Miner. Res. 24 (2009) 737–743. 73. S. Majumdar, Magnetic resonance imaging for osteoporosis, Skeletal Radiol. 37 (2008) 95–97. 74. S. Majumdar, H. Genant, A. Gies, G. Gugliemi, Regional variations in trabecular structure in the calcaneus assessed using high resolution magnetic resonance images and quantitative image analysis, J. Bone Miner. Res. 8 (1993) s351. 75. S. Majumdar, M. Kothari, P. Augat, et al., High-resolution magnetic resonance imaging: three-dimensional trabecular bone architecture and biomechanical properties, Bone 22 (1998) 445–454. 76. F.W. Wehrli, J.C. Ford, C. Kaut-Watson, Quantitative MR: a new method for in vivo characterization of trabecular bone structure, Radiology 177 (P) (1990) 245. 77. F.W. Wehrli, H.K. Song, P.K. Saha, A.C. Wright, Quantitative MRI for the assessment of bone structure and function, NMR Biomed. 19 (2006) 731–764. 78. J.S. Bauer, R. Monetti, R. Krug, et al., Advances of 3T MR imaging in visualizing trabecular bone structure of the calcaneus are partially SNR-independent: analysis using simulated noise in relation to micro-CT, 1.5T MRI, and biomechanical strength, J. Magn. Reson. Imag. 29 (2009) 132–140.
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79. M. Hudelmaier, A. Kollstedt, E.M. Lochmuller, V. Kuhn, F. Eckstein, T.M. Link, Gender differences in trabecular bone architecture of the distal radius assessed with magnetic resonance imaging and implications for mechanical competence, Osteoporos. Int. 16 (2005) 1124–1133. 80. B. Stampa, B. Kuhn, C. Liess, M. Heller, C.C. Gluer, Characterization of the integrity of three-dimensional trabecular bone microstructure by connectivity and shape analysis using high-resolution magnetic resonance imaging in vivo, Top. Magn. Reson. Imag. 13 (2002) 357–363. 81. R. Krug, S. Banerjee, E.T. Han, D.C. Newitt, T.M. Link, S. Majumdar, Feasibility of in vivo structural analysis of highresolution magnetic resonance images of the proximal femur, Osteoporos. Int. 16 (2005) 1307–1314. 82. J. Blumenfeld, C. Studholme, J. Carballido-Gamio, D. Carpenter, T.M. Link, S. Majumdar, Three-dimensional
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image registration of MR proximal femur images for the analysis of trabecular bone parameters, Med. Phys. 35 (2008) 4630–4639. 83. T.M. Link, V. Vieth, R. Langenberg, et al., Structure analysis of high resolution magnetic resonance imaging of the proximal femur: in vitro correlation with biomechanical strength and BMD, Calcif. Tissue Int. 72 (2003) 156–165. 8 4. T.M. Link, S. Majumdar, P. Augat, et al., In vivo high resolution MRI of the calcaneus: differences in trabecular structure in osteoporosis patients, J. Bone Miner. Res. 13 (1998) 1175–1182. 85. S. Majumdar, T.M. Link, P. Augat, et al., Trabecular bone architecture in the distal radius using magnetic resonance imaging in subjects with fractures of the proximal femur. Magnetic Resonance Science Center and Osteoporosis and Arthritis Research Group, Osteoporos. Int. 10 (1999) 231–239.
Chapter
7
Skeletal Growth in Males Qingju Wang and Ego Seeman Endocrine Centre, Heidelberg Repatriation Hospital/Austin Health, Department of Medicine, the University of Melbourne, Melbourne,Victoria, Australia
Introduction
2. age-related decay of the skeleton affects a smaller proportion of the male population than it does in the female population because men do not undergo a comparable midlife reduction in sex hormone levels [12, 13]. Therefore, their skeletons are not exposed to the high bone remodeling that drives structural decay in the face of a negative bone multicellular unit (BMU) balance.
Fewer men than women sustain fractures during advancing age, but fragility fractures are common in men and confer a sufficiently high morbidity, mortality and cost to the community to regard this as a public health problem [1–3]. The reasons underlying the lower incidence of fractures in men than in women are incompletely understood because the reasons why any individual sustains a fracture are poorly understood. For example, the majority of fragility fractures in the population occur in persons without osteoporosis [4, 5]. Over 60% of all fractures occur in men without osteoporosis and the structural basis underlying this bone fragility has received limited attention in women and none in men [4, 5]. While sex differences in bone size are said to explain differences in fracture incidence, this has not been tested experimentally [6]. Indeed, larger bones are loaded by larger muscles so that, at least in young adulthood, the stress imposed on bone is no different in males and females [7]. Asians have a smaller skeleton and lower bone mineral density (BMD) even after adjusting for height and weight, yet fracture rates in Asians are lower, not higher than in Caucasians [8, 9] and women with hip fractures and their daughters have larger femoral neck diameter than age matched controls [10]. When comparing women and men with fractures with their corresponding controls, or with each other, little insight into structural differences are present that explain the sex differences in fragility – both men and women with fractures have comparable deficits in bone structure relative to controls without fractures and bone morphology in men and women with fractures is similar [11]. The two most reasonable explanations for the lower incidence of fractures in men than in women are that:
As a consequence of growth-related and age-related factors, there are fewer men than women in the population susceptible to fractures should a fall occur. This chapter is confined largely to a discussion of the attainment of structural differences in males relative to females that we propose will protect their skeleton from net age-related bone loss which, although less than in women, is still substantial.
Growth in stature Stature increases due to the growth of the trunk and lower extremities of different growth velocities. In prepubertal years, growth velocity of leg length is twice that of sitting height increasing the proportion of stature in favor of the lower extremities [14]. Growth velocity of tibia and femur remains unchanged after entering puberty and decelerates later in puberty while that of trunk accelerates [15–17]. The pubertal growth spurt (11 years in girls and 13 years in boys) is largely truncal and postpubertal growth is mostly growth in the trunk (Figure 7.1) [15, 16, 18]. The upper extremities follow a similar growth pattern as the lower extremities [17, 19]. The growth velocity of tibia or femur is not greater in boys than girls [15–17, 20]. The longer extremities in adult males is due to the 2 years longer prepubertal growth than in females, not due to more rapid growth [20]. By contrast, the tempo of trunk growth may be slightly greater in pubertal boys than girls (Table 7.1) [20].
1. peak structural features achieved during growth in men makes their skeleton less susceptible to age-related decay Osteoporosis in Men
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Copyright 2009, 2010 Elsevier, Inc. All rights of reproduction in any form reserved.
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Figure 7.1 The growth velocity of stature, sitting height, femur and tibia length. The pubertal growth spurt is truncal. (From Anderson J Bone Joint Surg 1965;47A:1554-64 [16] and J Bone Joint Surg 1963;45A:1–14 [15]). Table 7.1 Sex-difference in pubertal growth of stature and segments (mean 6 SD) Height
Age at take off (yr) Age at peak velocity (yr) Peak velocity (size/yr) Size at take off (size) Adult size (cm) Adolescent gain (cm)
Sitting Height
Leg-Length
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Female
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Female
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Female
12.05 0.85 13.91 0.84 8.80 1.05 146.09 6.33 173.64 6.11 27.56 3.54
10.30 0.95 11.89 0.90 8.13 0.78 137.91 7.02 163.16 5.94 25.25 4.14
12.12 0.86 14.25 0.87 4.54 0.67 77.31 3.22 92.71 3.26 15.40 2.34
10.38 1.00 12.21 0.96 4.02 0.47 74.07 2.93 87.60 2.92 13.53 2.42
12.01 0.90 13.58 0.79 4.25 0.70 68.83 3.81 80.94 3.87 12.11 2.25
10.18 0.94 11.59 0.93 4.25 0.62 64.03 4.83 75.53 3.96 11.50 2.55
Modified from Tonner JM et al. Annals of Human Biology 3(2): 109–26.
The elongation of a long bone differs proximally and distally. Serial measurement of the distance of the distal and proximal ends of long bones to their nutrient foramina in the diaphyseal cortex showed that the growth plates of the tibia and femur at the knee contribute more to their elongation. In the upper extremities, the growth plates distant from the elbow contribute more to long bone growth [17, 19]. The different growth patterns of axial and peripheral skeleton have clinical implications. The effects of illness during growth depend on the maturational stage at the time of exposure, not just the ‘severity’ of the illness. As longitudinal growth is more rapid in the appendicular than axial skeleton before puberty, illness may produce greater deficits in appendicular morphology [21]. Illness during late puberty may produce greater deficits in the axial than the appendicular morphology. This regional specificity in growth and the effects of illness are obscured by the study of standing height or BMD alone. Disease interrupting
growth may be more deleterious on morphology at the proximal than distal humerus and distal femur than proximal femur by preferentially blocking more of the growth at regions growing faster.
Growth in bone structure As long as bone elongates, bone diameter also increases by periosteal apposition. Variance in bone length, like standing height, is largely genetically determined. For reasons that are unclear, bone lengths do not differ between children with cerebral palsy and controls after adjustment of bone age [22]. This is not the case for bone diameter. Binkely et al report that tibial length did not differ, but tibial shaft periosteal circumference was reduced by one-third in nonambulatory patients with cerebral palsy relative to controls
C h a p t e r 7 Skeletal Growth in Males l
[23]. This suggests that mechanical stimulation plays a role in the growth of bone width. Racket sport players training during or before puberty have a larger humeral midshaft diameter, while those starting training after puberty have no larger humeral diameter but a smaller medullar cavity suggesting periosteal apposition, while still active, can respond to loading during growth, but later, loading has little effect while endocortical apposition or prevention of endocortical resorption by loading may benefit cortical thickness [24–26]. Whether the benefit of greater periosteal apposition and greater net cortical thickness achieved by the latter or by endocortical modeling/remodeling is sustained into adulthood is uncertain, but evidence is available suggesting maintenance for some years after cessation of sporting activity [27, 28]. Loading is accommodated by modifying the shape of bone during growth, not just its mass [29, 30]. More mass means greater weight, greater maintenance cost and reduced mobility so lightness is an advantage and is achieved by modifying bone shape, varying the distribution of mass in space, not just increasing mass. Variance in bone shape, while believed to be largely the result of differing loading patterns is probably also largely explained by genetic variation. Difference in rates of focal periosteal apposition around a bone perimeter modifies its shape [31]. For example, the cross-section of the tibial shaft becomes more elliptical with advanced age in pubertal girls, due to greater periosteal apposition at anterior and posterior regions than at the medial and lateral regions. Similarly, the shape of the radius in growing goats is more circular and becomes elliptical in adulthood [29, 30]. No study has examined the bone shape under different loading circumstances. It is also not clear,
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whether the shape of bone can be modified after completion of growth when periosteal apposition has slowed down. As males have a 2-year longer growth period than females, their bone cross-sectional size becomes larger mainly after puberty (some differences in bone diameter may be present at birth) [32, 33]. The difference in duration of prepubertal growth accounts for the majority of the sex differences in bone mass, because for a given pubertal stage, periosteal apposition rate differs little, if any, by sex [34]. Despite the larger bone size in males, cortical thickness of the long bone does not differ substantially by sex before or after puberty, owing to the medullar contraction in females in late puberty and continued medullar expansion in males during puberty [32, 33]. Unlike the diaphysis, where bone diameter increases by periosteal apposition, periosteal resorption models the flasklike shape of the metaphysis while cortical thickening occurs by trabecular condensation [35]. The wide metaphysis is resorbed on its periosteal surface by resorptive modeling or remodeling to fit the slender diaphysis, a process that may increase metaphyseal cortical porosity (Figure 7.2). This increased cortical porosity with a temporary decrease in cortical thickness may contribute to fracture risk during the pubertal growth spurt [36, 37]. Although bone size increases during childhood and puberty, trabecular morphology remains relatively constant during growth. For example, Rauch et al and Moyer-Mileur et al reported that the trabecular vBMD of the distal radius and tibia, measured using peripheral quantitative computed tomography (pQCT), did not increase from 5 to 20 years of age [38, 39]. Byers et al examined the histomorphometry of the growth plate at the costochondral junction from birth to adolescence and reported bone volume fraction in the
A B
C D
A: Metaphyseal site of periosteal resorption B: Metaphyseal site of endocortical apposition C: Diaphyseal site of periosteal apposition D: Diaphyseal site of endocortical resorption
Figure 7.2 Different cortical morphology at the metaphysis and diaphysis due to different osteogenesis. Metaphyseal cortex is derived from coalesced trabeculae at the endocortical surface, while diaphyseal cortex is formated by periosteal apposition (P and E in the right panel represent periosteal and endocortical surface. (From Cadet et al J Bone Joint Surg 2003;85A(9):1739–48 [35]. Reprinted with permission).
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secondary spongiosa was stable from 3 years of age onwards [40] (Figure 7.3). These observations draw attention to the complexities of the formation of trabecular bone at this region. Further studies are needed to elucidate the development of trabecular structure during childhood. We reported trabecular bone fraction (BV/TV), measured using high-resolution pQCT, in the distal radius is independent of age from 7 up to 20 years of age in females with only modest increases in males (unpublished observations). Trabecular BV/TV was greater in males than females after puberty due to greater trabecular thickness in males, with no difference in trabecular number between the sexes [41]. Thicker trabeculae are more connected, there is less surface available for remodeling, protecting the trabeculae from being resorbed (because remodeling requires a surface to be initiated upon). A similar situation is seen between races. African Americans have thicker trabeculae, less surface and lower bone remodeling [42]. Thicker trabeculae are also more likely to thin than perforate during aging; this will result in less loss of strength because a reduction in trabecular density by loss of connectivity has more deleterious effects on strength than the same loss of trabecular density by thinning of trabeculae [13]. The origin of sex differences in trabecular thickness is not known. Whether this is the result of differences in growth plate-derived primary trabeculae or due to differences in the synthesis of secondary trabeculae is not known.
Trabecular BV/TV (%)
In contrast to little or no sex difference in long bone diameter before puberty, vertebral body cross-section is larger in boys than girls before puberty (15%) and the sex difference increases at maturity (25%) due to a longer prepubertal growth period as well as a later growth deceleration within their puberty in males [6, 43, 44]. The sex difference in axial bone diameter but less so at the appendicular sites before puberty may be due to differing prenatal sex steroid exposure as supported by the longer axial but not limb length in male than female neonates [45, 46]. Vertebral vBMD does not increase until late puberty and there is no difference in total or trabecular vBMD of the vertebral body between sexes at any growing stage [6, 43, 44], implying similar trabecular architecture in the vertebral body, contrasting to appendicular sites where males have thicker trabeculae [41].
Skeletal fragility has its origin early in life Bone traits such as size, shape, vBMD and cortical thickness track during adulthood. Differences in these traits in adulthood originate during growth [47, 48]. The magnitude of the variance or dispersion of bone traits around their age-specific mean is large; 1 SD is about 10–15% of the mean. Thus,
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Figure 7.3 Secondary spongiosa at the costochondral junction underneath the growth plate. There is little change in the architecture of the secondary spongiosa from early in life. (Modified from Byers et al Bone 27:495–501 [40]. Reprinted with permission).
C h a p t e r 7 Skeletal Growth in Males l
individuals at the 95th and 5th percentiles for bone size or mass differ by 50%. The variance in the rate of bone loss is about an order of magnitude less (1 SD 1% of the mean) [49]. So the difference in the percentile location of a trait established at the completion of growth is likely to be a more important determinant of fracture risk in old age than differences in rates of bone loss for many years. The position of an individual’s bone trait in the population distribution is established early in life – probably before puberty. In the study by Loro et al, percentile ranking of traits including size and vBMD of vertebral body, total cross-sectional area and cortical bone area of femoral midshaft at Tanner stage 2 was unchanged in the next 3 years and 60–90% of the variance at maturity was accounted for by the variance before puberty [50]. Ruff examined the tracking of femoral and humeral strength from infancy through adolescence in 10 boys and girls. Although sample size was small, ranking at 17 years was established at least before 6 years of age [51]. Similarly, Cheng et al report that an individual’s peak bone mass (PBM) correlated to the body length at 1 year of age and this correlation was not different to that between PBM and peak body height suggesting that the individual’s PBM was largely determined during the first year of life [52]. Twin and family studies suggest that genetic factors explain 60–80% of the variance in PBM, the amount of mass present at completion of linear and radial bone growth [53]. Whether this is the case for bone size, cortical thickness and trabecular BV/TV is not known. Physical activity during growth may contribute to the variance in bone traits but individuals differ more in their genetic makeup than differences in physical activity so the latter is still likely to only account for a small proportion of total variance. Nevertheless, intermittent skeletal stresses caused by muscular contractions in utero modulate cartilage growth, ossification and bone modeling and remodeling [54, 55]. Low skeletal mass and strength in newborns with neuromuscular disease-induced fetal immobility is well documented [56, 57]. In children with cerebral palsy, the trabecular bone structure and bone width are underdeveloped [58]. Ruff studied the femoral and humeral length and strength from early in life and found that the ratio of femoral and humeral length in human infants is close to that in adults, while the ratio of femoral and humeral strength only started to develop at 1 year of age, when walking begins, and increased rapidly from 1 to 3 years, then more slowly to mid- adolescence [59].
Modeling and remodeling – machinery of tracking Variance in bone remodeling as determined using circulating bone markers is largely genetically determined [60]. During aging, the lower the remodeling rate the lower the rate of
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loss [61]. During growth, low remodeling rate is associated with higher vBMD and high remodeling associated with the opposite. Slemenda et al demonstrated that black children accumulated approximately 10% greater bone mass by the end of puberty and had 50% lower concentration of osteocalcin and tartrate-resistant acid phosphatase (TRAP) throughout growth than white children; within a race, children with a lower concentration of these bone resorption markers had greater bone mass, while there was no difference left after controlling for TRAP between or within races, indicating remodeling rate during growth accounts for the difference in bone mass and structure between races and within a race [62]. Mora et al reported that high resorption markers pyridinoline and deoxypyridinoline were associated with low vertebral cancellous vBMD, low femoral mid-shaft cortical vBMD and smaller femoral mid-shaft cross-section in children. Serum osteocalcin was negatively associated with cortical vBMD [63]. Using pQCT, we found that high TRAP level was associated with larger marrow size and low vBMD of the tibial midshaft in a given bone cross-section [31]. Thus, the rate of bone modeling and remodeling during growth contributes to peak structural development and the position of bone traits in their population distribution; a high rate of remodeling constructs a more ‘empty’, lighter bone with thinner cortices and perhaps thinner, less connected trabeculae with a large surface area. While this may be advantageous in producing a lighter skeleton, as age advances, this structural design may be disadvantageous and the larger surface area exposes the bone to more intense remodeling and so bone loss as each remodeling event removes bone.
Bone growth and GH-IGF-I/sex hormones Growth hormone (GH) augments longitudinal bone growth by binding to its receptor at two main sites: the liver and the growth plate. In liver, it stimulates the production of insulinlike growth factor I (IGF-I) which is transported to the growth plates via the circulation to stimulate the proliferation and hypertrophy of chondrocytes. At the growth plate, GH stimulates the proliferation of prochondrocytes and the local production of IGF-I. Thus, direct effects and indirect effects via its systemic or local production of IGF-I are necessary for optimal growth [64]. IGF-I is the essential factor for the maintenance of intra uterine growth independently of GH, as seen in the severely compromised growth in mice and human fetuses with a mutated IGF-I gene, in contrast to normal weight and length at birth in mice and human with GH deficiency [65–67]. IGF-II also plays critical roles during intrauterine growth, especially at the early stage of gestation [68].
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In the first year of life, GH is elevated, decreases in midchildhood and reaches a peak at mid-puberty, at 11–12 years in girls and at 13–14 years in boys [69], coinciding with the two periods of rapid growth. The infancy growth spurt is mainly the result of growth in the legs, while the growth spurt in puberty is mainly truncal. The higher growth potential of long bones during infancy than puberty and the increased sex hormone levels during puberty promoting truncal growth may partly explain the different growth patterns of the axial and appendicular skeleton under high levels of GH. Growth in the leg and trunk are similarly associated with IGF-I in boys and diminished in children with GH deficiency or GH resistance [14]. The GH/IGF-I axis is likely to be one of the major mediators in the prepubertal growth in which there is no difference between normal children and children with androgen/estrogen receptor insensitivity [70, 71]. After entering puberty, testosterone directly, or indirectly via estradiol, stimulates the excretion of GH which induces the pubertal growth spurt in the spine. The direct effect, if any, of testosterone on the growth plate is unclear. Testosterone exerts no effect on the longitudinal bone growth in gonadohypophysectomized growing rats with or without GH while exerting a dose-dependent effect in gonadectomized rats suggesting testosterone affects longitudinal growth mainly via GH by modulating the hypothalamopituitary function [72–74]. Testosterone does not affect the production of IGF-I or the abundance of IGF-I receptor in liver or the growth plate [75]. Testosterone may modulate the effect of GH on the growth plate, but this remains controversial. The cessation of longitudinal growth in later puberty is not due to GH/IGF-I or testosterone, but the direct effect of estradiol (E2) on the growth plate in both sexes [73]. E2 at high levels in puberty promotes epiphyseal fusion, probably by inhibiting the proliferation of chondrocytes and promoting apoptosis [76]. Linear growth into adulthood continues in male and female patients with estrogen receptor resistance or aromatase deficiency, and aromatase inhibitors in pubertal boys with short stature increase their predicted adult height by delaying bone age [70, 77–79]. E2 promotes the pituitary production of GH [80, 81]. The effect of E2 on systemic and local production of IGF-I remains controversial. Ovariectomy in rats increases serum IGF-I and E2 administration reduces it [82]. Moreover, acute and chronic exposure to E2 may have a different effect. GH-induced hepatic IGF-I production is not affected by acute E2 but is reduced by chronic E2 administration [83]. Inconsistent with this, one recent study reported that E2 promotes the hepatic production of IGF-I independent of GH [84]. In the growth plate, local production of IGF-I is reported not to be affected by E2 which contrasts to its effect in utero [76, 82] . GH/IGF-I promotes periosteal apposition, as seen in acromegaly [85]. Exercise has profound effects on periosteal apposition during growth but not thereafter [86], perhaps partly due to interaction with this axis. GH deficiency
does not appear to affect the cortical vBMD in prepubertal children or apparent vBMD of diaphysis [87]. It is unclear whether GH/IGF-I affects the growth in trabecular architecture. In adult and animal studies, trabecular structure dose not differ between GH deficient patients or animals and controls, suggesting GH/IGF-I has little effect on the internal bone structure [84, 88]. The lower aBMD in GH deficiency children is almost, if not totally, due to their shorter stature than controls. As GH modifies body composition, with relatively more fat mass in GH deficiency children, their aBMD is also likely to be underestimated [89]. The increased rate of bone remodeling associated with GH/IGF-I excess, such as in acromegalic patients, does not appear to be associated with increased or decreased vertebral vBMD [90]. The changed bone status in patients with GH deficiency or excess can be more attributable to comorbidities than GH/IGF-I itself. Further study with advanced high-resolution imaging modalities is needed to investigate the effect of GH on the trabecular structure in children.
Summary There is little difference in skeletal structure in prepubertal males and females. As bone length increases during growth, the diameter of a bone cross-section increases with expansion of the medullary cavity so that there is little change in apparent vBMD in the vertebral body or long bones. Trabecular architecture, such as its BV/TV, thickness, number and separation may remain largely unchanged from as early as 2 years of age. At puberty, due to a longer duration of prepubertal growth in males than in females, sex differences in bone size appear, but not in cortical thickness. Trabecular architecture also differs by sex at maturity in favor of males having thicker trabeculae. An individual’s position of bone structural traits, such as bone size, cortical thickness and especially the trabecular BV/TV in their population distribution probably is established before puberty. That is, an individual’s position for their bone structural strength, whether at the 95th or 5th percentile at the completion of growth has its origin before puberty. The variance in bone traits is an order magnitude greater than the variance in rates of structural decay so that peak structural strength established at the completion of growth is likely to be an important determinant of skeletal fragility in adulthood.
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Chapter
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Pubertal Growth of the Male Skeleton Stefano Mora1,2 and Vicente Gilsanz3,4 1
Departments of Radiology and Pediatrics, Children’s Hospital Los Angeles, Los Angeles, California, USA Laboratory of Pediatrics Endocrinology, BoNetwork, San Raffaele Scientific Institute, Milan, Italy 3 Children’s Imaging Research Program, Children’s Hospital Los Angeles, Los Angeles, California, USA 4 University of Southern California, Los Angeles, California, USA 2
Introduction
and physeal plates of bone to define their proximity to full maturity. Assessments of skeletal maturation are frequently used as a diagnostic tool to evaluate clinical conditions associated with generalized growth abnormalities, to monitor response to medical treatment and to determine the growth potential of children. Although measures of skeletal maturation are often confused with measures of skeletal growth, growth and maturation reflect different processes; growth represents a quantitative increase in size or mass, while maturation is a sequence of changes that lead to a highly organized, specialized and mature state. Skeletal maturation is a temporal process only loosely linked to chronological age and, while expressed in years and months, there is no constant relationship between bone and chronological age. Moreover, skeletal maturation is only related to bone size in very general terms. Indeed, children with the same bone age may have very divergent bone dimensions and chronological age associated to full skeletal maturity varies greatly among subjects. There are several methods to assess skeletal maturity, but the most commonly used in clinical practice is the atlasbased technique of Greulich and Pyle [2], followed by the Tanner–Whitehouse bone-specific scoring technique [3] and the Fels method [4]. All use left hand and wrist radiographs to estimate a bone age, but the former differs in concept and method from the latter two. The Greulich-Pyle atlas is founded on the assumption that the skeleton matures in a uniform fashion and is based on a reference collection of radiographs from normal Caucasian children of high socioeconomic status at different chronological ages [2]. With the advent of digital imaging, multiple attempts have been made to develop image-processing techniques that automatically extract the key morphological features of ossification in the bones to provide a more effective and scientific approach to skeletal maturity assessments. However, the design of computer
Puberty encompasses major physical, emotional and psychological events that guide the transition from childhood to adulthood. It is a highly variable period influenced by many genetic, hormonal, nutritional, environmental and socioeconomic factors [1]. The pubertal process includes major changes in sexual development and body composition and is the time of greatest postnatal growth after infancy stages. These changes are regulated by the interaction of several organs in the hypothalamic–pituitary end organs axis for growth hormone (GH) and insulin-like growth factor-I (IGF-I) and in the hypothalamic–pituitary–gonadal axis for gonadotropins and sex hormones. At puberty, a yet undefined set of signals promotes the pulsatile release of gonadotropin releasing hormone (GnRH) by the hypothalamus. The increase in GnRH results in the production of luteinizing hormone (LH) and follicle stimulating hormone (FSH) by the pituitary gland and increased sex steroids by the gonads. Meanwhile, the coordinated secretion of GH releasing hormone (GHRH) and somatostatin from the hypothalamus promotes the increased release of GH by the pituitary gland. GH acts on local tissues to produce IGF-I which, in conjunction with sex steroids, induces the pubertal growth spurt. Boys achieve peak velocity, at about 9 cm per year, between 13 and 14 years of age. The later onset and longer duration of the growth spurt and the higher values for peak velocity in boys, when compared with girls, results in adult males being taller than adult females at skeletal maturity, which is achieved soon after sexual development.
Skeletal maturation Skeletal maturity is a measure of development incorporating the size, shape and degree of mineralization of the epiphyses
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algorithms capable of automatically rendering bone age has been impeded by the complexity of evaluating the wide variations in bone mineralization tempo, shape and size encompassed in the large number of ossification centers in the hand and wrist. Recently, these obstacles were circumvented through the selection of an alternative approach: the creation of artificial, idealized, sex- and age-specific images of skeletal development. The models were generated through rigorous analyses of the maturation of each ossification center in the hands and wrists of healthy children and the construction of virtual images that incorporate composites of the average development for each ossification center in each age group [5]. As an alternative to atlas-based techniques, other methods were developed that independently assess the maturation of each bone. The result of such a system would provide maturity standards for each bone considered. A diffuse method based on these principles was conceived by Tanner and Whitehouse and named TW after their initials. The original system (TW1) was refined and published as TW2 and, recently, as TW3 [3]. They defined a series of eight maturity indicators for each bone of the hand and wrist and nine for the radius. These maturity indicators were then evaluated not in relation to chronological age, but in relation to their appearance within the full passage of each specific bone from immaturity to maturity. The Fels method is less frequently used and differs in the chronological ages at which assessments are possible, maturity indicators and the scale of maturity [4]. These methods for assessment of skeletal maturity are difficult to compare. A small study found that the method of Greulich and Pyle was as reproducible as the TW2 method [6]. In contrast, another study assessed 362 bone ages by the same methods and concluded that they do not give equivalent bone age estimates and that the TW2 method was more reproducible. A more recent study compared the atlas-based and bone-specific techniques using a large sample of children aged 2 to 15 years [7]. The study demonstrated that bone age was closer to chronological age using the Fels method and that the greatest difference was observed using the Greulich-Pyle method, both in boys and girls. Another issue pertains to the use of images and standards derived from populations of a specific socioeconomic and ethnic background to assess skeletal maturity of children of different origins or race. Indeed, ample data indicate significant variations in the tempo of skeletal maturity in children of different ethnic, social and economic backgrounds. The appropriateness of the old standards has been questioned [8, 9] and the need for specific standards not only for contemporary children, but also for different populations or ethnic groups within a specific geographical region became imperative for an accurate assessment of skeletal maturity. Are skeletal and pubertal maturations related events? In many pathological conditions, there is a clear association between the rate of skeletal maturation and the pubertal
stage of development. Conditions that delay skeletal maturation are associated with a postponed onset of puberty [10], while conditions that accelerate skeletal maturation advance the onset of pubertal development [10]. This synchrony between different maturational processes has suggested the concept of ‘tempo’ to refer to the whole process of maturation [11]. This concept has been challenged by the observation that the concordance between skeletal maturation and hypothalamic–pituitary–gonadal axis was not present in normal children. A recent study tried to assess whether the age at onset of puberty correlates with skeletal maturation in healthy boys, as it does in boys with abnormal maturational tempo [12]. The data showed a lack of correlation between skeletal age and chronological age at onset of puberty. This finding seems thus to contradict the notion that skeletal maturation governs the onset of puberty. Taken together, all available data seem to indicate that several diverse factors (nutritional, genetic, endocrine) may intervene in regulating skeletal and pubertal maturation. However, while they promote synchrony between maturational processes, whenever there is a perturbation of development tempo, they appear to act independently in normal physiological conditions. Further studies are needed to elucidate the mechanisms that promote concordance between growth, bone age and puberty in some cases, but not in normal boys. Females, at any age, have advanced bone age when compared with boys. The difference is present at birth and persists throughout growth, although it is slightly more pronounced after the onset of puberty [2, 8]. Moreover, the skeletal maturation process lasts longer in boys than in girls. The reasons for these gender discrepancies in skeletal maturity remain unknown. However, the description of the estrogen receptor- and - [13] and the recently reported estrogen receptor GRP30 expression [14] in human chondrocytes support the possible role of estrogen in regulating skeletal maturation in girls. The role of estrogen in girls’ skeletal maturation has been provided by a model in which patients with XY genotype carried disruptive mutations in the androgen receptor gene (AIS) and, consequently, a complete resistance to endogenous androgen, leaving estrogen the only functional sex steroid [15]. From the normal pubertal growth in individuals with complete AIS, it is clear that estrogen alone is sufficient to support normal pubertal skeletal growth. In contrast, androgen alone is not sufficient to grant a normal skeletal development, as characterized by a girl with aromatase deficiency [16].
Bone measurement techniques in children The development of precise non-invasive methods for measuring bone mineral content has significantly improved our
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ability to study the influence of genetic and environmental factors on the attainment of bone. These techniques have not only helped to quantify the loss of bone associated with the various disorders that cause osteopenia in children, but have also improved our understanding of the childhood antecedents of a condition that happens to manifest in adults – osteoporosis. Dual-energy x-ray absorptiometry (DXA) is, by far, the most widely used technique for measuring bone acquisition in children due to its low cost, minimal radiation exposure, accessibility and ease of use. The availability of DXA has resulted in many large-scale studies of the genetic and environmental determinants of areal bone mineral density (aBMD) in healthy children. Although DXA studies in pediatrics have provided much information regarding changes in aBMD over time, there is still considerable confusion over the interpretation of DXA measures. Most growth-related increases in DXA aBMD values are due to increases in the size, rather than the density, of the bone and gender differences in aBMD values are also largely due to greater bone size in males [17]. The confounding effect of skeletal geometry on DXA measures is gaining much recognition. Recently, it was suggested that major errors in interpretation occur when using this technique in pediatric populations, leading to the overdiagnosis of osteoporosis in growing subjects. Indeed, several investigators have proposed that osteoporosis should not be diagnosed based on DXA densitometry criteria alone [18, 19]. In addition, while, in adults, DXA aBMD is a powerful predictor of fracture and is used to define osteoporosis, there is insufficient pediatric evidence to determine aBMD standard deviation (SD) criteria for osteopenia and osteoporosis as indicated by the World Health Organization (WHO). Hence, it is recommended that, when reporting DXA results in subjects under 20 years of age, it is more appropriate to define a Zscore of less than 2.0 as low bone density, rather than using the WHO classification for osteoporosis [18]. Attempts to overcome this disadvantage with the use of correction factors; i.e. the squared root of the projected area, the height of the subject, the width of the bone, assuming the cross-sectional area of the vertebrae is a cube, a cylinder with a circular base or a cylinder with an elliptic base area [20], etc., are subject to error, as there is no closed formula that defines the size of the vertebrae. Similarly, formulas have been proposed for the femur and the mid-radius, which are also prone to error, especially during growth when there are changes in the size, as well as the shape, of the bone [20]. In a recent study, vertebral bone density was measured using both DXA and computed tomography (CT) in 400 children (100 each, healthy and sick boys and girls) [21]. The results indicated that DXA measures of aBMD underestimate bone accretion in children and adolescents. On average, three times as many subjects were determined to
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have low bone density (Z-score 2.0 for chronological age) by DXA than by CT; this was true for both healthy (2% versus 7%) and sick (10.5% versus 31%) children. While DXA and CT Z-scores were related, almost 50% of the variability remained even after age and anthropometric measures were taken into account. Hence, many children are identified as having low bone density by DXA, but not by CT. In contrast, quantitative CT (QCT) using conventional CT scanners or peripheral QCT (pQCT) scanners provides three-dimensional images, allowing for volumetric density measures, an evaluation of bone morphology and an independent assessment of trabecular and cortical bone. Because of its porosity and large surface area, trabecular bone has greater turnover and is a better indicator of bone remodeling than cortical bone. Trabecular bone density determinations by pQCT are commonly obtained by a single scan at a relative location, such as 4 or 8% length of the radius or tibia [22, 23], or a fixed location, such as 10 mm from the end of the growth plate [24]. Whereas available data indicate that the short-term reproducibility of these measurements is excellent [20], positioning is critical and, due to the variability of trabecular bone density throughout the metaphysis, any offset in the location to be scanned would significantly influence the values obtained [25]. Additionally, the large range of metaphyseal morphology among subjects, diseases and ages limits comparative cross-sectional studies and interpretation of the same scan location in longitudinal examinations. Previous studies using pQCT in children have investigated the effects of age or maturity related growth, gender differences, physical activity, disease, geometry and strength [22, 23, 26–28]. These studies used a variety of methods, such as measurements at 4 or 10% length of the radius or tibia or at a fixed length 10 mm distal to the growth plate. More recent studies, using high-resolution pQCT, have scanned 9-mm-thick sections of long bones to assess trabecular microarchitecture [29]. The results of a recent study highlight the limitations of current pQCT methodology using single scans as outcome measures in cross-sectional and longitudinal studies assessing trabecular bone density and highlight the need for developing pQCT acquisition techniques that provide more reproducible determinations in the appendicular skeleton of children [30]. The significant variability in metaphyseal morphology, length of the metaphysis, overall trabecular mean density and gradient in trabecular bone density from the physeal plate to the shaft of the bone among growing subjects account for the large intra- and inter-subject variability in bone density measures. Subjects in this study showed a substantial range of variability from a 1-mm offset slice positioning with an average of 6.9 mg/cm3 or 16.8%. In addition, longitudinal assessments showed that the slopes of the density curve drastically changed in some children, even over a short period of 6 months.
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Skeletal changes during puberty Longitudinal Growth Skeletal size and shape change dramatically during the pubertal period due to genetic, hormonal and mechanical influences. Bone growth involves changes in length and width by means of longitudinal bone formation and periosteal bone formation versus endosteal bone resorption, respectively. Longitudinal bone growth occurs through the addition of cartilage tissue to the growth plates at the proximal and distal ends of the long bones and vertebrae [31]. The growth plate consists of three distinct cellular layers: the resting zone; the proliferative zone; and the hypertrophic zone [32]. The resting and proliferative zones consist of chondrocytes arranged in columns parallel to the long axis of the bone. Chondrocytes replicate repeatedly in the proliferative zone. However, chondrocytes located in the farthest part from the epiphysis cease dividing and enlarge to become hypertrophic cells. Throughout the growth plate, chondrocytes synthesize and secrete cartilage matrix. The hypertrophic zone is invaded by osteoclasts and differentiating osteoblasts, coming from the adjacent metaphyseal bone, that transform the cartilage into bone tissue [31, 32]. Therefore, new bone is formed progressively at the bottom of the growth plate, resulting in bone elongation. Recent evidence indicates that the resting zone contains unipotent, chondrogenic stem-like cells that are able to generate new columnar proliferative and hypertrophic chondrocytes [33]. The major systemic hormones that regulate longitudinal bone growth during childhood are GH and IGF-I, thyroid hormones and glucocorticoids and, during puberty, sex steroids. For decades, it was accepted that estrogen, in girls, and androgen, in boys, were the primary sex steroids regulating pubertal growth. This vision has been radically changed recently and now it is clear that both androgen and estrogen play an important role in regulating boys’ longitudinal growth (see Chapter 9 for a comprehensive review).
Bone Density Bone mass increases throughout childhood and adolescence and reaches its peak shortly after sexual and skeletal maturity. The greater bone mass in men than women has been documented by means of neutron activation analysis, measurement of the calcium content of selected regions of the skeleton and the techniques of radiogrammetry and absorptiometry [34–36]. Of the two components of bone mass, bone density and bone size, the latter is responsible for the gender differences in bone mass. Neither CT measures of the tissue density of cancellous bone (a reflection of the size and number of trabeculae),
nor CT values for the material density of bone (a reflection of its degree of mineralization) differ substantially between men and women [37, 38]. Differences in morphology of cancellous and cortical bone must be considered for the appropriate interpretation of bone density data. Cancellous bone exists as a three-dimensional lattice of plates and columns (trabeculae). The trabeculae divide interior volume of the bone into intercommunicating pores, which are filled with a variable mixture of red and yellow marrow. Because of the relatively small size of trabeculae when compared to the pixel, the CT unit of measurement, values for cancellous bone density reflect not only the amount of mineralized bone and osteoid, but also the amount of marrow per pixel [39]. Similar limitations apply to in vitro determinations of the volumetric density of trabecular bone which are obtained by washing the marrow from the pores of a specimen of cancellous bone, weighing it and dividing the weight by the volume of the specimen, including the pores. Bone density determinations of cancellous bone are, therefore, directly proportional to the bone volume fraction and inversely proportional to the porosity of the bone. The relatively large coefficient of variation for values of cancellous bone density reflects the considerable variation in the dimensions of the pores throughout the vertebral body. In contrast, in young subjects with non-porous bone, measurements of cortical bone density reflect the material density of bone and are primarily based on the degree of mineralization if the cortex is sufficiently thick to circumvent volume averaging errors [40]. These measurements are analogous to in vitro determinations of the intrinsic material density of bone, which are commonly expressed as the ash weight per unit volume of bone. On average, values for cortical bone density are eight times higher than those for cancellous bone density, a finding consistent with histomorphometric studies indicating an equivalent difference in the porosity of these two forms of a structural organization of bone tissue. Otherwise, cancellous bone can be viewed as a porous structure comprised of bone tissue with the same mechanical properties and composition as cortical bone [41]. Regardless of gender, the tissue density of cancellous bone increases during puberty (Figure 8.1). Although the factors that account for the increase in cancellous bone density remain to be determined, it is reasonable to suspect that they are, in part, mediated by the actions of sex steroids. It should be stressed that neither before nor after completion of puberty does cancellous bone density (CBD) differ in men and women and that the small gender differences in the temporal sequence of CBD likely reflect gender differences in the appearance of sexual characteristics and the accelerated growth spurt. While, for both sexes, growth acceleration begins in early adolescence, typically, peak growth velocity in boys is reached 2 to 3 years later and boys continue growing for approximately 2 to 3 years longer than girls [42] (see Figure 8.1). Interestingly, the
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Figure 8.1 Mean and standard deviations of vertebral cancellous bone density (CBD) in males and females. CBD increases and reached peak values earlier in females than in males.
d ifferences between males and females in the commencement of increases in CBD parallel the differences in the tempo of peak height velocities.
Bone Size Gender differences in bone mass are a result of differences in bone size that evolve during growth [38, 43]. Several reports indicate that, throughout childhood and adolescence, girls have smaller vertebral body dimensions compared to boys of similar age, degree of sexual development and anthropometric measures [17, 43, 44]. On average, the cross-sectional area of the vertebral bodies is 11% smaller in prepubertal girls than in prepubertal boys matched for age, height and weight [17, 43]. While it is commonly believed that sex differences in skeletal morphology and physiology occur at or around puberty [45], this notion is challenged by the finding of sex differences in bone size prior to the pubertal period [46, 47]. The gender disparity increases with growth and is greatest at skeletal maturity, when the cross-sectional dimensions of the vertebrae are about 25% smaller in women than in men, even after taking into consideration differences in body size [38]. The smaller vertebral size is probably key to the four- to sevenfold higher incidence of vertebral fractures in elderly women, as compared to men [48]. Vertebral size has been demonstrated to be an important determinant of vertebral fractures in elderly women with osteoporosis. A small vertebral body imparts a mechanical disadvantage that increases
the stress within the spine and becomes increasingly important as bone density declines with age [49]. In the appendicular skeleton, cross-sectional growth is primarily related to body weight. Some reports indicate that the cross-sectional and cortical bone areas of the femoral shaft do not differ between males and females matched for age, height and weight [17], a notion consistent with analytical models proposing that long bone cross-sectional growth is strongly driven by mechanical loads [50]. In contrast, other studies suggest that boys have larger femur cross-sectional area and cortical bone area than girls, measured both with QCT and magnetic resonance imaging [51] and that the total bone cross-sectional area and the cortical area measured at the tibial midshaft by pQCT are greater in boys than in girls during puberty [27]. Even in the appendicular skeleton, larger bone dimensions confer a greater mechanical resistance to stress, thus reducing fracture risk in males. The greater male bone size primarily results from enhanced periosteal bone formation, affected by both androgen and estrogen [52]. Periosteal bone formation is significantly reduced following androgen deficiency in growing male rats, while it is increased in estrogen-deficient female rats leading to the traditional view of stimulatory androgens in males versus inhibitory estrogens in females on periosteal growth [53]. The role of estrogen and androgen in the regulation of bone accretion is review in Chapter 9. The available data indicate that periosteal bone formation in males may not be solely dependent on androgen action, but also, at least in part, on estrogen action [54].
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Peak bone mass The amount of bone in the skeleton, at any age, is the result of the amount of bone gained during growth, from uterine life to skeletal maturity, and the loss of bone that occurs with aging. Bone acquisition during adolescence is the main contributor to peak bone mass (PBM) which, in turn, is a major determinant of osteoporosis and fractures in the elderly, most commonly in the vertebrae [55]. Because current treatment for osteoporosis in elderly subjects does not significantly restore loss of bone, efforts are being directed toward developing preventive measures that increase bone mass before it reaches its peak. Because of difficulties in longitudinally studying subjects from childhood to an elderly age, the contention that senile osteoporosis is the result of inadequate bone acquisition during growth remains unproven. This notion is supported, however, by data showing that there is a strong resemblance between mother–daughter bone traits and that this resemblance is present even before the daughters have begun puberty [56, 57]. Additional support for this concept comes from the knowledge that genes associated with the normal variations in bone mass in elderly women are also related to variations in bone density in children [58–60]. If bone loss were the exclusive determinant of late life bone mass, one would not expect such a strong resemblance in bone traits between girls and their mothers or an association between candidate genes and bone mass to be depicted in childhood. Data from previous investigations showing strong correlations between yearly bone mass measurements in prepubertal girls, suggest that bone traits can be tracked during growth [56]. Thus, the genetic control of bone phenotypes associated with fragility fractures in the elderly appears to be expressed very early in life and is tightly maintained throughout childhood and adolescence. The time of life in which PBM is attained has been the subject of considerable controversy, with estimates for the axial skeleton ranging from soon after the completion of sexual and skeletal maturity at the end of the 2nd decade to the 5th decade of life. Most, but not all, indicate that bone mass does not significantly increase after the third decade [61]. However, DXA bone values are influenced by changes in body size and soft tissue composition around the bone measured [62, 63], which may account for the conflicting results of previous studies. Moreover, it is likely that the timing of peak values differs between the axial and appendicular skeletons. Bone mass achieves peak values by the end of the second decade of life. Studies in women using CT have demonstrated that the density and the size of vertebral bone reach their peak soon after the time of sexual and skeletal maturity [38, 43, 64], corroborating anatomical data indicating trabecular bone loss as early as the third decade of life and no change in the cross-sectional area of the
vertebral body from 15 to 90 years of age [37, 65, 66]. The results of a recent study in the axial skeleton indicate that CT values for vertebral bone mineral content and bone density reach their peak around the time of sexual maturity and cessation of longitudinal growth. In contrast, DXA values for vertebral bone mineral content and bone mineral density continued to increase beyond sexual and skeletal maturity (Figure 8.2). The data regarding whether vertebral size in men continues to grow after cessation of longitudinal growth is controversial; while some investigators find no change in the cross-sectional areas of the vertebral bodies after skeletal maturity, others have suggested that vertebral cross-sectional area increases with age throughout adulthood [37, 67]. In the appendicular skeleton, the range of ages published in cross-sectional studies for the timing of PBM has varied significantly, from 17–18 years of age to as late as 35 years of age [68, 69]. Longitudinal DXA studies indicate that the rate of increase in skeletal mass slows markedly in late adolescence and that peak values in the femoral neck, like those in the spine, are achieved near the end of puberty in normal females [70–72]. It should, however, be stressed that, in both men and women, the cross-sectional dimensions of the long bones in the appendicular skeleton continue to grow throughout adulthood and into old age by subperiosteal bone apposition. This increase in bone width occurs in all sample populations studied [73].
Conclusion The main areas of progress in osteoporosis research during the last decade have been the general recognition that this condition, which is the cause of so much pain in the elderly, has its roots in childhood and the identification of the structural basis accounting for much of the variations in bone strength among humans. Considerable progress has been made in elucidating the basis for the gender differences in bone strength and the greater incidence of fragility fractures in elderly women when compared to men. Available data indicate that there is very little difference in measures of cancellous bone density in the vertebral body between sexes. In contrast, females have a smaller vertebral cross-sectional area when compared with males, even after accounting for differences in body size; a gender difference that becomes most apparent after puberty. Hence, vertebral fractures are likely more common in women than in men because women have smaller vertebrae. Although at present, the reasons for the reported gender differences in the incidence of hip fractures have yet to be clearly defined, it is tempting to think that complete phenotypic characteristics responsible for variations in femoral strength will be soon delineated. Such knowledge will provide a more rational way to identify those subjects prone to develop
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Figure 8.2 Box and whisker plots of CT cancellous bone density (BD) and bone mineral content (BMC) of the third lumbar vertebra (A) and DXA values for bone mineral density (BMD) and BMC (B) showing no changes between baseline and follow-up values by CT, but highly significant changes when using DXA.
fractures and towards whom osteoporosis prevention trials should be geared.
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30. D.C. Lee, V. Gilsanz, TAL. Wren, Limitations of peripheral quantitative computed tomography metaphyseal bone density measurements, J. Clin. Endocrinol. Metab. 92 (2007) 4248–4253. 31. HM. Kronenberg, Developmental regulation of the growth plate, Nature 423 (6937) (2003) 332–336. 32. B.C. van der Eerden, M. Karperien, JM. Wit, Systemic and local regulation of the growth plate, Endocr. Rev. 24 (6) (2003) 782–801. 33. V. Abad, J.L. Meyers, M. Weise, et al., The role of the resting zone in growth plate chondrogenesis, Endocrinology 143 (5) (2002) 1851–1857. 34. M. Trotter, RR. Peterson, Weight of the skeleton during postnatal development, Am J Phys Anthropol 33 (1970) 313–324. 35. S.M. Garn, J.M. Nagy, ST. Sandusky, Differential sexual dimorphism in bone diameters of subjects of European and African ancestry, Am. J. Anthropol. 37 (1972) 127–130. 36. J.A. DePriester, T.J. Cole, NH. Bishop, Bone growth and mineralization in children aged 4 to 10 years, Bone Min. 12 (1991) 57–65. 37. L. Mosekilde, L. Mosekilde, Sex differences in age-related changes in vertebral body size, density and biomechanical competence in normal individuals., Bone 11 (2) (1990) 67–73. 38. V. Gilsanz, M.I. Boechat, R. Gilsanz, M.L. Loro, T.F. Roe, WG. Goodman, Gender differences in vertebral sizes in adults: biomechanical implications, Radiology 190 (1994) 678–682. 39. H.K. Genant, K. Engelke, T. Fuerst, et al., Noninvasive assessment of bone mineral and structure: state of the art, J. Bone Miner. Res. 11 (1996) 707–730. 40. T.N. Hangartner, V. Gilsanz, Evaluation of cortical bone by computed tomography, J. Bone Miner. Res. 11 (1996) 1518–1525. 41. J.K. Gong, J.S. Arnold, SH. Cohn, Composition of trabecular and cortical bone, Anat. Rec. 149 (1964) 325–331. 42. A.V. Marcell, Adolescence, in: R.M. Kliegman, H.B. Jenson, R.E. Behrman, B.F. Stanton (Eds.) Nelson Textbook of Pediatrics, eighteenth ed., Saunders Elsevier, Philidelphia, 2007, pp. 60–65. 43. V. Gilsanz, M.I. Boechat, T.F. Roe, M.L. Loro, J.W. Sayre, WG. Goodman, Gender differences in vertebral body sizes in children and adolescents., Radiology 190 (1994) 673–677. 44. V. Gilsanz, D.L. Skaggs, A. Kovanlikaya, et al., Differential effect of race on the axial and appendicular skeletons of children, J. Clin. Endocrinol. Metab. 83 (1998) 1420–1427. 45. S.P. Garnett, W. Hogler, B. Blades, et al., Relation between hormones and body composition, including bone, in prepubertal children, Am. J. Clin. Nutr. 80 (4) (2004) 966–972. 46. E.M. Clark, A.R. Ness, JH. Tobias, Gender differences in the ratio between humerus width and length are established prior to puberty, Osteoporos. Int. 18 (4) (2007) 463–470. 47. H. Hasselstrom, K.M. Karlsson, S.E. Hansen, V. Gronfeldt, K. Froberg, LB. Andersen, Sex differences in bone size and bone mineral density exist before puberty. The Copenhagen School Child Intervention Study (CoSCIS), Calcif. Tissue. Int. 79 (1) (2006) 7–14. 48. S.R. Cummings, J.L. Kelsey, N.C. Nevitt, KJ. O’Dowd, Epidemiology of osteoporosis and osteoporotic fractures, Epidemiol. Rev. 7 (1985) 178–208.
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49. V. Gilsanz, M.L. Loro, T.F. Roe, J. Sayre, R. Gilsanz, E. Schulz, Vertebral size in elderly women with osteoporosis: mechanical implications and relationship to fractures, J. Clin. Invest. 95 (1995) 2332–2337. 50. M.C.H. Van der Meulen, G.S. Beaupre, D.R. Carter, Mechanobiologic influences in long bone cross-sectional growth, Bone 14 (1993) 635–642. 51. W. Hogler, C.J. Blimkie, C.T. Cowell, et al., A comparison of bone geometry and cortical density at the mid-femur between prepuberty and young adulthood using magnetic resonance imaging, Bone 33 (5) (2003) 771–778. 52. E. Seeman, Clinical review 137: sexual dimorphism in skeletal size, density, and strength, J. Clin. Endocrinol. Metab. 86 (10) (2001) 4576–4584. 53. R.T. Turner, G.K. Wakley, KS. Hannon, Differential effects of androgens on cortical bone histomorphometry in gonadectomized male and female rats, J. Orthop. Res. 8 (4) (1990) 612–617. 54. V. Rochira, L. Zirilli, B. Madeo, et al., Skeletal effects of long-term estrogen and testosterone replacement treatment in a man with congenital aromatase deficiency: evidences of a priming effect of estrogen for sex steroids action on bone, Bone 40 (6) (2007) 1662–1668. 55. J.P. Bonjour, G. Theintz, F. Law, D. Slosman, R. Rizzoli, Peak bone mass, Osteoporos. Int. 4 (Suppl. 1) (1994) 7–13. 56. S. Ferrari, R. Rizzoli, D. Slosman, JP. Bonjour, Familial resemblance for bone mineral mass is expressed before puberty, J. Clin. Endocrinol. Metab. 83 (1998) 358–361. 57. E. Seeman, J.L. Hopper, L.A. Bach, et al., Reduced bone mass in daughters of women with osteoporosis, N. Engl. J. Med. 320 (1989) 554–558. 58. J. Sainz, J.M. Van Tornout, M.L. Loro, J. Sayre, T.F. Roe, V. Gilsanz, Vitamin D receptor gene polymorphisms and bone density in prepubertal girls, N. Engl. J. Med. 337 (1997) 77–82. 59. J. Sainz, J.M. Van Tornout, J. Sayre, F. Kaufman, V. Gilsanz, Association of collagen type 1 a1 gene polymorphism with bone density in early childhood, J. Clin. Endocrinol. Metab. 84 (1999) 853–855. 60. S. Ferrari, R. Rizzoli, T. Chevalley, D. Slosman, J.A. Eisman, JP. Bonjour, Vitamin-D-receptor-gene polymorphisms and change in lumbar-spine bone mineral density, Lancet 345 (1995) 423–424. 61. T.A. Wren, X. Liu, P. Pitukcheewanont, V. Gilsanz, Bone acquisition in healthy children and adolescents: comparisons of DXA and CT measures, J. Clin. Endocrinol. Metab. 90 (2005) 1925–1928.
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62. P. Tothill, M.A. Laskey, C.I. Orphanidou, M. van Wijk, Anomalies in dual energy X-ray absorptiometry measurements of total-body bone mineral during weight change using Lunar, Hologic and Norland instruments, Br. J. Radiol. 72 (859) (1999) 661–669. 63. C. Formica, M.L. Loro, V. Gilsanz, E. Seeman, Inhomogeneity in body fat distribution may result in inaccuracy in the measurement of vertebral bone mass, J. Bone Miner. Res. 10 (1995) 1504–1511. 64. V. Gilsanz, D.T. Gibbens, T.F. Roe, et al., Vertebral bone density in children: effect of puberty, Radiology 166 (1988) 847–850. 65. J.K. Weaver, J. Chalmers, Cancellous bone: its strength and changes with aging and an evaluation of some methods for measuring its mineral content. I. Age changes in cancellous bone, J. Bone Joint Surg. 48A (1966) 289–298. 66. W.A. Merz, RK. Schenk, A quantitative histological study on bone formation in human cancellous bone, Acta. Anat. 76 (1970) 1. 67. M.S. Dunnill, J.A. Anderson, R. Whitehead, Quantitative histological studies on age changes in bone, J. Path. Bact. 94 (1967) 275–291. 68. R.R. Recker, K.M. Davies, S.M. Hinders, R.P. Heaney, M.R. Stegman, D.B. Kimmel, Bone gain in young adult women, J. Am. Med. Assoc. 268 (1992) 2403–2408. 69. V. Matkovic, T. Jelic, G.M. Wardlaw, et al., Timing of peak bone mass in Caucasian females and its implication for the prevention of osteoporosis, J. Clin. Invest. 93 (1994) 799–808. 70. J.P. Bonjour, G. Theintz, B. Buchs, B. Slosman, R. Rizzoli, Critical years and stages of puberty for spinal and femoral bone mass accumulation during adolescence, J. Clin. Endocrinol. Metab. 73 (1991) 555–563. 71. P.W. Lu, J.N. Briody, G.D. Ogle, et al., Bone mineral density of total body, spine, and femoral neck in children and young adults: a cross-sectional and longitudinal study, J. Bone Miner. Res. 9 (1994) 1451–1458. 72. G. Theintz, B. Buchs, R. Rizzoli, et al., Longitudinal monitoring of bone mass accumulation in healthy adolescents: evidence for a marked reduction after 16 years of age at the levels of lumbar spine and femoral neck in female subjects, J. Clin. Endocrinol. Metab. 75 (1992) 1060–1065. 73. A.M. Parfitt, Genetic effects on bone mass and turnoverrelevance to black/white differences, J. Amer. Coll. Nutr. 16 (1997) 325–333.
Chapter
9
The Effects of Sex Steroids on Bone Growth Giampiero I. Baroncelli and Silvano Bertelloni Department of Obstetrics, Gynecology and Pediatrics, 2nd Pediatric Unit, ‘S. Chiara’ Hospital, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
Introduction
and estrogens cannot be considered as only ‘male’ or ‘female’ hormones, respectively. Indeed, androgens may act as prohormones of estrogens even within bone. Sex steroids influence not only the accrual of bone mass and bone mineral density (BMD) but also skeletal sex dimorphism [4–6]. This chapter will focus on the main effects of sex steroids on the biological processes involved in bone growth in both sexes, emphasizing gender differences.
Bone growth includes the progressive incremental changes in length, size and mass, associated with changes in bone geometry/width, that physiologically occur throughout the development of the individual (Figure 9.1). As already recognized in the 1940s by Albright and Reifenstein [1], sex steroids regulate skeletal growth and maturation in both men and women. Both androgens and estrogens and their respective receptors have specific actions on different bone envelopes during growth in both sexes [2]. Androgen receptor (AR), estrogen receptor- (ER-) and (ER-) are expressed in human, rat and mouse osteoblasts, osteoclasts, osteocytes and growth plate chondrocytes, thereby supporting the concept that the action of sex steroids on the skeleton may be exerted by a direct stimulation of their receptors [3]. However, androgens
Longitudinal and radial bone growth Longitudinal bone growth depends on endochondral bone formation which basically involves two steps. The first step is characterized by addition of cartilage tissue to the growth plates of long bones. In the second step, the cartilaginous scaffold is transformed into bone tissue at the adjacent metaphyses. The resulting primary spongiosa consists of trabeculae which contain a core of mineralized cartilage surrounded by mineralized bone tissue. This type of bone is turned over very rapidly through the coordinated action of osteoclasts and osteoblasts [7]. Radial bone growth occurs by the process of bone modeling which involves coordinated action of osteoclasts and osteoblasts sitting on opposite sites of bone. During radial growth, osteoblasts are typically located on the outer (periosteal) surface of a bone cortex, where they deposit bone matrix and later mineralize it. Thereby, the outer circumference of a long bone or vertebral body is increased. At the same time, osteoclasts located on the inner (endocortical) surface of the cortex resorb bone, increasing the marrow cavity. Net bone mass increases rapidly during modeling since osteoclasts remove less bone tissue than is deposited by osteoblasts [7–9].
Growth in width
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Figure 9.1 Physiologic processes involved in bone growth occurring in childhood and adolescence. Osteoporosis in Men
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Finally, the bone tissue produced either by endochondral ossification or by modeling is continuously turned over in a process defined remodeling [7, 9, 10]. Remodeling consists of successive cycles of bone resorption and formation on the same bone surface; the basic features of this process are the same for both trabecular and cortical bone [7, 10]. A group of osteoclasts removes a small quantity of bone tissue which, after a reversal phase, is replaced by a team of osteoblasts. The entire group of cells involved in this process is named a remodeling unit or basic multicellular unit. The link between osteoblast activity and previous osteoclast action is known as ‘coupling’. The process of bone remodeling has a crucial role in bone maintenance during life. These biological processes, as well as their effects on bone structure, are illustrated in Figure 9.2; these mechanisms are the means by which sex dimorphism may arise.
Effects of Sex Steroids (Including their Interaction with the GH-IGF-I axis) on Longitudinal Bone Growth Sex steroids may have a direct action on chondrocytes via AR, ER- or ER- [2, 11]. The AR has been found in all layers of the growth plate at different ages without significant gender variation [12–14]. Dihydrotestosterone (DHT), the 5-reduced and non-aromatizable metabolite of testosterone, regulates proliferation and differentiation of human epiphyseal chondrocytes in vitro, probably via the stimulation of local insulin-like growth factor-I (IGF-I) synthesis as well as IGF-I receptor expression [14, 15]. In rats, the sex-specific response of osteochondral growth zone chondrocytes to testosterone also requires further metabolism of the hormone to DHT [16]. ERs have been demonstrated in all maturational zones of the growth plate during
development and puberty, but there is conflicting evidence on the effect of estrogens on chondrocyte proliferation and differentiation [14]. Some of these discrepancies may be explained by the ability of chondrocytes to synthesize estrogens locally [17]. Studies in rats have shown that estrogens inhibit chondrocyte cell division in the proliferative zone of the growth plate [18] and that the age-related decrease in size of the hypertrophic chondrocytes is increased by estrogens [14, 19]. Estrogens probably have separate and independent effects on chondroblast proliferation and epiphyseal fusion. Their action on proliferation also appears to be biphasic with stimulation by low levels and inhibition by high levels of estrogen, respectively. In both males and females, the process of inhibition of chondrocyte proliferation predominates in late puberty leading to cessation of growth and epiphyseal fusion. Indeed, growth velocity rapidly decreases in tall girls treated with high-dose estrogens. During puberty, not only sex steroids, but also the pulsatile secretion of growth hormone (GH) increases (1.5- to 3-fold) along with a greater than threefold increase in serum IGF-I concentrations. Moreover, this increase of GH secretion during puberty shows a sex dimorphism that parallels the change in growth velocity [14]. GH acts on bone tissue both directly through a specific receptor on chondrocytes on the growth plate and osteoblasts, and indirectly by IGF-I. Therefore, longitudinal growth may depend on the interaction between sex steroids and GH-IGF-I axis. In fact, estrogen stimulation of longitudinal growth is largely dependent on GH and GH and estrogen levels are positively correlated in prepubertal children [14, 20] and throughout normal female puberty [21]. Moreover, in peripubertal children, estrogens also increase GH sensitivity [14, 22]. Testosterone increases growth velocity in association with an increase in
Trabecular structure
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Figure 9.2 Mechanisms by which bone growth in length and width may occur (from Schoenau et al [7], reproduced with permission).
C h a p t e r 9 The Effects of Sex Steroids on Bone Growth l
Bone mass acquisition during childhood and adolescence
the GH-IGF-I axis. However, such an action is primarily due to its conversion to estrogen following aromatization [14, 23]. On the other hand, non-aromatizable androgens (DHT and oxandrolone) may increase growth velocity independently of GH-IGF-I action, possibly via a direct action on the AR within the growth plate cartilage [3]. Sex steroids have a fundamental role in inducing sex dimorphism during puberty according to chronologic age and pubertal stage. Growth velocity spurt occurs earlier in girls than in boys (age 12.0–12.5 years and 14.0–14.5 years, respectively) with a peak at pubertal Tanner stage B2 and G3, respectively [24]. It has therefore been widely accepted that estrogens are the primary hormones that mediate pubertal bone growth in both sexes. The dimorphic pattern of body and bone growth may be related to the delayed achievement of adequate estrogen levels in boys (following aromatization of testosterone). Indeed, estrogen concentrations during peak height velocity are similar in boys and girls and correlate not only with testosterone levels in boys, but with bone age as well [25]. Some clinical and experimental data suggest that the deceleration of longitudinal growth in late puberty is not due to a systemic (hormonal) mechanism but probably related to a local (paracrine) mechanism within the growth plate [14, 26]. Nevertheless, at the end of puberty, ER- activation appears to be involved in epiphyseal growth plate closure in both sexes [2], as indicated by some observations in patients with aromatase deficiency or ER- disruption (see Chapter 5). The mechanism of ‘growth plate senescence’, as well as the role of estrogen in this process is, however, incompletely understood. According to Parfitt [27], epiphyseal fusion marks but does not determine growth cessation. In fact, epiphyseal fusion follows but does not precede cessation of growth.
In both sexes, bone mass progressively increases during childhood, with a rapid gain during puberty. However, some gender differences in the accrual of bone mass are evident. At birth and during prepubertal years, males and females have similar values of total body bone mass (bone mineral content, BMC) and lumbar BMD [28–32], measured by dual energy x-ray absorptiometry (DXA), until the age of approximately 8 years. Thereafter, the values become higher in females than in males as the result of the earlier onset of the pubertal growth spurt whereas, in the late adolescence, total bone mass in boys exceeds that measured in girls. Figures 9.3 and 9.4 show, respectively, the pattern of total body bone mass and lumbar BMD during childhood and adolescence in both sexes. 3400
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Figure 9.3 Centile curves for total body bone mass (BMC), by DXA measurements, according to age in boys (solid lines) and girls (dashed lines) during childhood and adolescence (from Mølgaard et al [30], reproduced with permission).
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Figure 9.5 Mean and standard deviations of vertebral trabecular bone density, by QCT measurements, in male and female subjects aged 7–20 years. Trabecular bone density increases and reaches peak values earlier in female than in male subjects. Because trabecular bone density does not correlate with age for male subjects aged 7–11 and 17–20 years and for female subjects aged 7–10 and 15–20 years, the values in these age groups were equalized. Values at 7 and 20 years represent the mean for subjects 5–7 years of age and 20–21 years of age, respectively (from Gilsanz et al [34], reproduced with permission). BMC TB velocity curve cubic spline 450 Boys Age of peak 14.05 Peak value 408 Size adjusted 394
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The higher bone mass in boys than in girls can be explained by differences in bone size related to gender and not to differences in bone density [6, 7, 33]. In young adulthood, men and women have similar volumetric BMD, but men have bigger bones than women due to the process of periosteal apposition [6] (see Chapter 4). Volumetric BMD is independent of age for the vertebral body, at least until puberty [34], then it increases comparably by gender (Figure 9.5). The number of trabeculae at the growth plates does not increase with age [35]. At puberty, trabecular BMD increases by increasing the size and thickness of the trabeculae plates to a similar degree in boys and girls [36]. Approximately 40% of bone mass is accumulated during adolescence [37, 38]. Moreover, on average, 26% of peak bone mass is acquired during the 2-year period across peak height velocity [37], suggesting a clear relationship between the increase of sex steroids, linear growth and bone growth. At peak height velocity, boys and girls reached 90% of their adult height but only 57% of their bone mass. Sex differences in timing and magnitude of bone mass accrual with respect to the gain of longitudinal growth during puberty have been shown. Peak total bone mass accrual occurs approximately 1.6 years earlier in girls than in boys (age 12.50.90 [meanSD] and 14.10.95 years, respectively) and is less in girls than boys (32567 g/year and 40950 g/ year, respectively) [39, 40] (Figure 9.6). In boys, the greatest difference between height and BMD gains is more pronounced at the lumbar spine and femoral neck than at the femoral midshaft; in girls, the difference appears to be of a lower magnitude than in males [41]. Furthermore, according to Forwood et al [42], peak linear growth (height and femur length) precedes the peak rate of growth in bone
Age PHV 13.44 yrs
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Figure 9.6 Total body peak bone mass velocity (BMCTB) curve illustrating velocity at peak and ages at peak BMC and peak height velocities (PHV) by chronologic age for boys and girls (from Bailey et al [39], reproduced with permission).
strength variables (cross-sectional area and subperiosteal width assessed by DXA) at femoral neck by 6.5 months and by 8.4 months for boys and girls, respectively. Therefore, the timing of axial and appendicular bone mass acquisition differs between boys and girls, apparently due to the different onset and progression of puberty [36, 43].
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Figure 9.7 Variations of periosteal and medullary diameter (upper panel of the figure) and cross-section of cortical (black) and medullary (white) areas (lower panel of the figure), from infancy to young adulthood at metacarpal bones in both sexes (modified from Seeman [6], reproduced with permission).
In both sexes, the maximal gain of BMD occurs at pubertal stages 3–4 at the lumbar spine and at pubertal stages 2–3 at the femoral neck or midshaft [37, 41, 44]. In both sexes, the accrual of bone mass abruptly decreases in late adolescence. It has been calculated, by DXA measurements, that at least 90% of peak bone mass at the lumbar spine and femoral neck is acquired within the second decade of life [37, 44, 45]. However, in other skeletal sites, such as the radius, skull or whole body, peak bone mass (assessed by DXA) is reached later, around 35 years [31, 45]. In both sexes, a similar pattern has been reported at the proximal phalanges of the hand as assessed by quantitative ultrasound measurement [46, 47].
Changes in bone size by periosteal expansion during growth Individual bone size is determined by absolute and relative movements of both periosteal and endosteal surfaces. These changes in bone size influence bone geometry, cortical bone mass and thickness, as well as the diameter of medullary cavity. At the second metacarpal bone, periosteal apposition increases bone width during the prepubertal years in both sexes, resulting in a slightly higher periosteal diameter in boys than girls, whereas only small changes occur at the medullary area up to puberty [6, 36, 48, 49]. In the first two
years life, an initial resorptive phase with a slightly greater diameter in males than in females is followed by a childhood appositive phase with a similar medullary diameter between males and females [6, 36, 48, 49]. At puberty, the development of cortical bone takes a gender-specific course. In fact, in boys, periosteal apposition and endocortical resorption continue causing enlargement of bone diameter, cortical thickening and increased medullary cavity diameter. In girls, periosteal apposition also increases, but to a lesser extent than in boys, whereas endocortical bone formation is stimulated resulting in cortical thickening and reduced medullary cavity. Although cortical thickness is similar in males and females, the cortical bone mass is greater in males because of the greater periosteal perimeter [6, 36, 48, 49]. In Figure 9.7 the pattern of periosteal and medullary diameters measured at the second metacarpal bone from infancy to young adulthood is illustrated. These observations at the second metacarpal bone are largely confirmed by peripheral quantitative computed tomography (pQCT) measurements at the 65% site of the proximal radius in children and adolescents [50]. By the age of 15 years, girls have almost completed periosteal apposition; in boys, the maximum diameter is only reached at 21 years without evident pubertal acceleration. Moreover, according to Neu et al [50] periosteal apposition rate at the proximal radius was similar to the iliac periosteal formation rate in children, as measured by histomorphometry [35]. In contrast to the results at the second metacarpal bone [48, 49] and at the femoral diaphysis [43], but in agreement with
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Figure 9.8 Mean BTT values in male and female subjects from infancy to young adulthood (A) and during prepuberty and the main periods of puberty (B) (modified from Baroncelli et al [58], reproduced with permission).
radiogrammetric measurements obtained at the proximal radius [51], no significant changes in medullary area were documented in females. In contrast to girls, medullary area increases with age in boys [50, 52]. Therefore, these data indicate that, at the proximal radius, the endocortical surface appears to remain stable in females, whereas considerable endocortical resorption occurs in males. In weight-bearing skeletal regions, such as femur, only small or no changes in cross-sectional area and cortical bone area, as assessed by QCT, have been reported in prepubertal children, with no difference between boys and girls [33, 43]. However, Högler et al [53] showed, by DXA and magnetic resonance imaging, that mid-femoral cortical thickness increased between prepuberty and adulthood in both sexes, with males having higher values of total, cortical and medullary areas than females, suggesting that periosteal expansion is slightly predominant over net endocortical resorption. The sex-specific increase in medullary area was nearly identical with the increase in mid-femoral medullary area assessed by QCT [54]. In addition, Looker et al [55] also reported gender difference in cortical thickness at the femoral neck and proximal shaft. A longitudinal study by pQCT in girls showed that growth velocity of total cross-sectional area and total bone mass at the distal radius peaked at 16 and 9 months, whereas at the tibial shaft they peaked at 20 and 10 months before menarche, respectively. The growth velocity of cortical cross-sectional area of the tibial shaft peaked at 13 months before menarche and then decreased. Moreover, during puberty, the cortical cross-sectional area/total cross-sectional
area ratio increased, whereas the medullary cross-sectional area/total cross sectional area ratio decreased [56]. These data are similar to those observed at the second metacarpal bone and at the mid-femoral shaft [43, 57]. Quantitative ultrasound (QUS) measurements at the proximal phalanges of the hand showed that the QUS variable defined as BTT (bone transmission time, expressed as s), which reflects cortical bone mass, cortical thickness and cortical area, progressively increases during childhood in both sexes, with slightly higher values in males than in females during infancy and childhood and with an earlier increase in girls at the onset of puberty compared with boys [58]. Moreover, the analysis of the BTT pattern during puberty further reveals that boys have higher values than girls, mainly in late puberty [58] (Figure 9.8), likely reflecting a greater perimeter of the bigger bone as documented earlier at the second metacarpal bone [48, 49]. In conclusion, a longer period of bone accumulation in males than in females as a consequence of a longer prepubertal longitudinal growth and a more pronounced periosteal expansion during puberty may explain the differences in bone mass between sexes [6, 36].
Mechanisms Regulating Periosteal and Endosteal Expansion During Growth The mechanism(s) regulating the sex-dependent periosteal and endosteal surface changes occurring during growth are not well defined. Some potential hypotheses are summarized in Table 9.1 [59].
C h a p t e r 9 The Effects of Sex Steroids on Bone Growth l
Table 9.1 Theories on the sex-dependent periosteal and endosteal surface changes occurring during growth Theory
Possible mechanisms
Hormonal
Sex steroids can have a different action on bone surface according to sex Mechanostat Mechanical strain regulates the morphology of bone geometry MechanoSex steroids, in particular estrogen, modulate hormonal the response of mechanical strain regulating the morphology of bone geometry Sizostat Some genetic factors can regulate bone growth in width to reach a pre-programmed size, independent of mechanical requirements
Hormonal Factors: Sex Steroids and the GH-IGF-I axis The sex dimorphism in bone mass and size suggests that sex steroids are key regulators of bone mineral accumulation and geometry during puberty. According to observations in gonadectomized rats, androgens mainly stimulate periosteal bone formation in males and estrogens inhibit periosteal expansion in females [60]. The variation in cortical bone volume after gonadectomy appears primarily related to changes in periosteal bone formation and not (or to a lesser extent) to changes of the inner endocortical perimeter [61]. Based on the skeletal response to estrogen therapy in a 17-year-old boy with congenital aromatase deficiency (see Chapter 5), Bouillon et al [62] suggested that androgens alone are not sufficient to drive periosteal expansion and that estrogen therapy is able to stimulate periosteal apposition. Therefore, exposure to estrogens appears to be essential for the male pubertal periosteal bone expansion as well. A unifying hypothesis could be that estrogens rather than androgens are driving periosteal bone apposition, with a biphasic, dose dependent effect of estrogens. Assuming a dose–response relationship between estradiol levels and bone expansion in both sexes, stimulation would occur at low levels, as is the case in males and in early pubertal girls, whereas increasing exposure to higher concentrations of estrogens, as occurs in late puberty and in adulthood in females, would inhibit periosteal growth [62]. This assumption is consistent with both the lifelong slow periosteal bone expansion in males and the resumption of bone expansion after menopause [36]. Estrogens may induce periosteal bone formation in both sexes through ER-, whereas inhibition of periosteal expansion could be primarily an ER- effect, according to observations of increased periosteal expansion in female ER- knockout mice [3, 63]. Some data indicate that testosterone and other androgens have a crucial role on periosteal growth with actions mediated by both the AR and ERs after aromatization to estrogen [23]. Compared with women, men exhibit more periosteal expansion because they are more exposed to the
111
stimulatory effects of androgens and less exposed to the inhibitory effects of estrogens. On the other hand, periosteal apposition in women may be enhanced by androgens, as it is in men [64]. This hypothesis is in keeping with the demontration of increased bone size and bone mass in women with polycystic ovary syndrome that is characterized by androgen excess [65, 66]. Wang et al [67], in a study at tibial shaft by pQCT, showed that estrogens inhibited bone resorption during the rapid growth occurring before menarche; by contrast, after menarche the higher estrogen concentrations promoted bone formation. At the periosteal surface, testosterone promoted bone formation, whereas estrogens did not affect it. Therefore, these data do not support the view that estrogens inhibit bone formation at the periosteal surface. In addition to linear growth, the GH-IGF-I axis regulates bone mass gain and bone modeling and remodeling [68] according to some studies in GH-deficient children [68, 69]. Furthermore, the interaction between GH-IGF-I axis and sex steroids plays a crucial role in regulating bone metabolism. According to a study on femoral mid-shaft geometry in rats [61], gonadectomy had no net effect on the endocortical surface in males but abolished endocortical bone acquisition in females. GH deficiency halved periosteal bone formation and had no net effect on the endocortical surface in males, but abolished bone acquisition on both surfaces in females. Therefore, periosteal growth is independently and additively stimulated by androgens and GH in males, inhibited by estrogen and stimulated by GH in females. The role of the GH-IGF-I axis in bone sex dimorphism is largely unknown in humans. The similar degree of reduction in lumbar BMD between boys and girls with GH deficiency [68] could suggest that sex dimorphism in bone mass as well as in body composition could be primarily due to sex steroids [70]. ‘Mechanostat’ Theory (The Utah Paradigm) Based on the ‘mechanostat’ theory, skeletal growth is fully regulated by a dominant feed-back system (the ‘mechanostat’) that senses mechanical strain generated by muscle contraction and skeletal loading. These mechanisms are able to adapt bone tissue to the processes of modeling and remodeling [71, 72]. Although the mechanisms of action of the ‘mechanostat’ are not defined, there is strong evidence that mechanical forces do play a major role in determining periosteal bone development via osteocytes, bone lining cells or other cells in the marrow [72]. Mechanical strain is primarily dependent on muscle mass and strength and, to a lesser extent, on body weight. During puberty, it has been demonstrated that muscle mass contributes to the variability of bone mass by 6–12% in boys and 4–10% in girls [73]. Rauch et al [74] demonstrated, by DXA scans, that muscle strength and
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Males Age PHV 13.45y
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100 BMC Age peak 14.11 y Peak value 404 g
LBM Age peak 13.75 y Peak value 8550 g
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9 10 11 12 13 14 15 16 17 18 19 Age in y
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Age PHV 11.80 y
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LBM Age peak 12.19 y Peak value 5050 g BMC Age peak 12.69 y Peak value 318 g
5000
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Total body BBC velocity in g per y
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Total body BBC velocity in g per y
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Total body LBM velocity in g per y
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0 9 10 11 12 13 14 15 16 17 18 19 Age in y
Figure 9.9 Velocities of total body lean body mass (LBM) and bone mass (BMC) accretion during the pubertal growth spurt in males (left panel) and females (right panel). The age at peak height velocity (PHV) is shown as a reference point for pubertal development (from Rauch et al [74], reproduced with permission).
bone strength are closely correlated between them and that the pubertal peak velocity in lean body mass accretion precedes the pubertal peak velocity in bone mass accretion by an average of 0.51 years in girls and by 0.36 years in boys (Figure 9.9). Moreover, Macdonald et al [75], by pQCT measurements, showed that sex dimorphism in tibial bone strength and its components (geometry and density) is already evident in pre- and early pubertal boys and girls. However, it should be taken into consideration that these data do not establish a direct cause-and-effect relationship between muscle force and bone strength. In fact, the development of muscle mass and bone mass during growth, and mainly during puberty, is influenced by several factors, including genetic and hormonal factors. Based on the ‘mechanostat theory’, sex differences in bone size may be largely explained. Mechanical loads on bones deform or strain them and larger loads cause bigger strains. Where strains exceed a modeling threshold range, modeling slowly increases bone strength to reduce later strains towards that range, otherwise mechanically controlled modeling turns off. When strains stay below a lower remodeling threshold range, disuse-mode remodeling permanently removes bone, but only next to or close to marrow. At any rate, it is possible that there is some form of positional cue that is responsible for the ‘setpoint’ threshold for mechanical loading at each location in the skeleton, so that architecture is optimized to habitual strains experienced for each of those locations. That implies that
a site-specific customary strain stimulus exists for each site within the skeleton and it is that combination of different strain parameters to which the modeling and remodeling processes are directed [76]. It is hypothesized that the setpoint of the mechanostat in girls is lower than that of boys; as a consequence, a lower mechanical strain is sufficient to activate modeling in girls [77]. ‘Mechano-Hormonal’ Theory Some observations suggest that the ‘bone–muscle unit’ could be regulated by sex steroids [78, 79] and the GH-IGFI axis [80]. Figure 9.10 shows some possible interactions between mechanical strain and hormones, as described by Rauch and Schoenau [81] and Petit et al [82]. Testosterone has a profound anabolic effect on muscle mass at puberty; this effect is mainly evident in boys who have a muscle mass gain about of 35% more than girls [83]. Skeletal muscle has many ARs and testosterone stimulates the muscle mass independently of IGF-I production [83, 84]. A regulating effect of testosterone on the setpoint of the mechanostat is not demonstrated. Some studies [77–79] suggested that the main effect of estrogens on the bone–muscle unit is in decreasing the mechanical setpoint of the mechanostat, thereby increasing the responsiveness of the periosteum to load. As a consequence, customary loading may cause a greater bone mass. Conversely, withdrawal of estrogens (due to menopause or amenorrhea) may reduce the sensitivity to loading inducing
C h a p t e r 9 The Effects of Sex Steroids on Bone Growth l
Bone strength
Mechanostat model*
Tissue strain
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Material strength
Geometry
Regulatory feedback loop Signaling pathways Osteocyte sensing
Osteoblasts
Sensitivity set-points Signaling pathways
Osteoclasts
Growth in bone length change in muscle load
Genetics, hormones, nutrition, environment
Challenges
Modulators
Figure 9.10 Possible interactions among mechanical and hormonal factors involved in bone development based on mechanostat theory (from Rauch and Schoenau [81] and Petit et al [82], reproduced with permission).
bone loss, as the concurrent loading is not sufficient to counter this change in mechanosensitivity [85]. Accordingly, the rise in estrogen levels during puberty could lead to the deposition of additional bone mass in order to satisfy the anticipated physiological needs of the subsequent reproductive period [77–79]. However, a study in mice [86] showed that the responsiveness of periosteal bone to load was decreased by estrogens and not increased. In additon, Järvinen et al [87] observed that the skeletal response of estrogen-depleted female rats to exercise was higher compared with their estrogenrepleted counterparts. In humans, some studies showed more beneficial effects on periosteal bone in prepubertal girls (low estrogen) than in postpubertal girls (high estrogen), suggesting that the responsiveness of periosteal bone to load could be reduced by estrogens [43, 88, 89]. Although the theories on the role of estrogens in periosteal bone expansion seem to be contradictory, according to Venken et al [59], they could reflect different exposure to endogenous estrogens. Low levels of estrogen could increase the mechanical sensitivity of the periosteum and/ or affect systemic IGF-I concentrations. Alternatively, higher concentrations of estrogen could inhibit periosteal bone expansion and its interaction with mechanical loading. Furthermore, it should be considered that the interaction between estrogens and mechanical loading may be not only restricted to a potential role of different exposure to estrogen concentrations, but also to the role of the ER and ER- and their different actions on male and female skeleton during loading [59]. It has been hypothesized that ER- could stimulate bone formation on the endocortical
surface, whereas ER- may act as an antimechanostat [90]. In fact, disruption of ER- increased periosteal bone formation following loading in female mice but not in male mice [86]; this may suggest that estrogen signaling through ER suppresses the loading response in the female skeleton. Therefore, periosteal bone apposition may be not only dependent on the combined action of hormonal or mechanical stimuli but also on their mutual interactions; mechanical loading is strongly stimulatory for bone but it seems to be sex steroid hormone-dependent. GH could decrease the bone mechanostat setpoint and reinforce the effect of mechanical loading on bone formation [80, 91], as suggested by the evidence that men with GH deficiency have reduced muscle mass associated with a high risk of fractures [92]. Moreover, the GH-IGF-I axis may have an important role in regulating periosteal bone expansion, as demonstrated by the fact that GH receptor and IGF-I genedisrupted mice show extremely short and thin bones [93]. Genetic Factors (‘Sizostat’ Hypothesis) The Sizostat hypothesis sustains that a master gene or a set of genes can regulate bone growth in width to reach a preprogrammed size, independent of mechanical requirements and hormonal influences [94]. As a consequence, in an individual who is genetically destined to have a wide leg, the genetic growth program will make bones and muscles grow to reach the pre-programmed size [95]. Muscle and bone growth would independently follow a genetic script but would not have a functional link.
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Table 9.2 Effects of sex steroids deficiency/action on linear growth, pubertal growth spurt, bone maturation, BMD, bone geometry and muscle mass Pubertal Unfused Bone age BMDa growth epiphyses spurt
Disorder
Hormone Clinical deficiency/ phenotype deficient action
Congenital aromatase deficiency (in men, n 7) Estrogen resistance syndrome (in a man) Complete androgen insensitivity syndrome
Estrogen deficiency
Eunuchoid Increased No proportion, genu valgum
Yes
Delayed
Reduced Reduced
Reduced
Estrogen resistance
Eunuchoid Increased No proportion, genu valgum
Yes
Delayed
Reduced Unknown
Unknown Unknown
Androgen resistance
No
Not delayed
Reduced Unknown
Unknown Normal for females, but reduced for males
5reductase deficiency
DHT deficiency
Normal female with absent pubic and axillary hair and primary amenorrhea Female/ ambiguous (at birth)d
Linear growth
Normalc
Yes
Normal
Unknown No
Cortical CrossMuscle thicknessb sectional Massa areab
Unknown Normale Unknown
Unknown
Unknown Unknownf
a
Assessed by DXA; assessed by pQCT; c intermediate between those predicted for females and males; d virilization after puberty if gonads are not removed; e in individuals raised as males, intact testes, spontaneous high-normal testosterone values and low DHT values; f male appearance after puberty in individuals raised as males and with spontaneous testosterone secretion. b
Relevant clinical observations on the sex steroids’ effect on bone growth Clinical observations in patients with altered secretion or action of sex steroids strongly support their role on bone growth, skeletal maturation and bone mass accrual. Hypogonadal patients have reduced BMD which improves following hormonal replacement therapy [5]. In untreated patients suffering from hypogonadotrophic hypogonadism, such as Kallman’s syndrome, linear growth continues until the third decade, resulting in taller than average final height and abnormal body proportions with relatively longer bones at the lower body segment [14]. Moreover, boys with primary hypogonadism, such as Klinefelter syndrome (47, XXY), have taller than average final height as well as a variable degree of BMD reduction (25–40%) that seems to be related to the degree of hypogonadism. Cortical bone appears also more affected than trabecular bone in these patients [96]. Males with estrogen insensitivity secondary to a mutation in the ER gene or impaired estrogen biosynthesis due to hereditary aromatase deficiency have reduced BMD, delayed skeletal maturation and persistent skeletal growth into adult life. These ‘experiments of nature’ show that androgens alone do not promote epiphyseal maturation and
that estrogens have a fundamental role not only in pubertal development and linear growth, but also in the acquisition of bone mass in both girls and boys [5, 23, 97]. A positive effect of estrogen treatment in improving lumbar and femoral BMD and linear growth in a boy with congenital aromatase deficiency [62] also indicates that estrogens have a critical role in male skeletal growth and bone mass acquisition and that estrogens may regulate pubertal periosteal bone expansion associated with the male bone phenotype. Complete androgen insensitivity syndrome offers a unique opportunity to assess the consequences of a total lack of androgen action on bone growth. The syndrome is caused by mutations in the AR, thereby producing complete lack of target tissue response to high-normal endogenous androgens. Despite subnormal estrogen concentrations for females, these patients are usually taller than normal males. Although estrogen concentrations are able to induce a normal pubertal growth spurt and feminization, bone mass accretion is likely impaired in these androgen resistant patients, suggesting that not only estrogen but also androgen exerts a direct role in BMD acquisition [5, 98–101]. Moreover, the evidence that lean body mass in women with complete androgen insensitivity syndrome is reduced when compared with control men [102] could indicate a role of an impaired mechano-hormonal system on bone growth
C h a p t e r 9 The Effects of Sex Steroids on Bone Growth
115
l
Table 9.3 Principal effects of sex steroids on bone growth and maturation and muscle mass independent of sex Hormone
Linear growth
Pubertal growth spurt
Body proportions
Epiphyseal closure
Bone mass acquisition
Periosteal geometry
Endosteal geometry
Muscle mass acquisition
Estrogens Androgens
/ *
/
, Stimulation; , no effect. The number of symbols reflects the degree of stimulation for comparison between estrogen and androgen only in general terms. *At least in part, this effect could be due to aromatization to estrogens.
in these subjects. In contrast, patients suffering from 5reductase deficiency do not have reduction of BMD compared with standardized male values, suggesting that testosterone itself and/or low levels of DHT are sufficient for the acquisition of a normal BMD [99]. A study by Han et al (103) of patients affected by complete androgen insensitivity syndrome and gonadal dysgenesis with 46, XY karyotype (Swyer’s syndrome) or 46, XX karyotype suggested that androgens rather than sex chromosomes may have a role in protecting BMD in women with complete androgen insensitivity syndrome and that androgens likely exert their greatest effects on bone mass acquisition in the early period of life. Table 9.2 summarizes the main effects of sex steroids deficiency/action on linear growth, pubertal growth spurt, bone maturation, BMD and bone geometry. These data indicate that, in both sexes, estrogens have a primary role on bone mass accumulation during puberty and skeletal consolidation after puberty, but an independent participation of androgens in these processes likely occurs. However, it should be considered that testosterone represents the necessary substrate for aromatization to estrogens, so that it has an important indirect role in regulating bone surfaces modeling.
Conclusions Sex steroids play a fundamental role in the regulation of bone growth and skeletal dimorphism. Estrogens appear to be important for bone development not only in girls but also in boys. Table 9.3 summarizes the principal effects of estrogens and androgens on bone growth and maturation and muscle mass. The pubertal growth spurt, epiphyseal fusion, body proportion and endosteal geometry seem to be mainly regulated by estrogens, whereas periosteal geometry and muscle mass are mainly regulated by androgens.
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97. L. Zirilli, V. Rochira, C. Diazzi, G. Caffagni, C. Carani, Human models of aromatase deficiency, J. Steroid. Biochem. Mol. Biol. 109 (2008) 212–218. 98. S. Bertelloni, G.I. Baroncelli, G. Federico, M. Cappa, R. Lala, G. Saggese, Altered bone mineral density in patients with complete androgen insensitivity syndrome, Horm. Res. 50 (1998) 309–314. 99. V. Sobel, B. Schwartz, Y.S. Zhu, J.J. Cordero, J. ImperatoMcGinley, Bone mineral density in the complete androgen insensitivity and 5-reductase-2 deficiency syndromes, J. Clin. Endocrinol. Metab. 91 (2006) 3017–3023. 100. D.L. Danilovic, P.H. Correa, E.M. Costa, K.F. Melo, B.B. Mendonca, IJ. Arnhold, Height and bone mineral density in androgen insensitivity syndrome with mutations in the androgen receptor gene, Osteoporos. Int. 18 (2007) 369–374. 101. M.B. Oakes, A.D. Eyvazzadeh, E. Quint, YR. Smith, Complete androgen insensitivity syndrome. A review, J. Pediatr. Adolesc. Gynecol. 21 (2008) 305–310. 102. E. Dati, G.I. Baroncelli, S. Mora, et al., Body composition and metabolic profile in women with complete androgen insensitivity syndrome, Sex Dev. (2009) in press. 103. T.S. Han, D. Goswami, S. Trikudanathan, S.M. Creighton, GS. Conway, Comparison of bone mineral density and body proportions between women with complete androgen insensitivity syndrome and women with gonadal dysgenesis, Eur. J. Endocrinol. 159 (2008) 179–185.
Chapter
10
Nutritional Basis of Skeletal Growth CONNIE M. Weaver1 and Elizabeth M. Haney2 1
Department of Foods and Nutrition, Purdue University, West Lafayette, Indiana, USA Department of Medicine, Oregon Health and Science University, Portland, Oregon, USA
2
Introduction
energy intake from diet records average 35 20% less than true energy intake under weight stable conditions determined by doubly labeled water in overweight adolescent boys and girls [3]. If 35% of calories are underreported, associated nutrients must also be underreported. Furthermore, there are wide variations in nutrient intake, within individuals. An example of the calcium intake of a 14-year-old adolescent determined from diet records taken monthly over 3 years is given in Figure 10.1. The range in calcium intake was 30 to 2895 mg/d. The mean intake was 786 511 mg/d but the variation was so large, it could hardly be interpreted as a habitual calcium intake. For the entire 140 cohort aged 6–14 years, the variance over 2 years was 135 374 mg for within subject and 25 708 for between subjects [5]. About 22 food records would be required to limit attenuation to 90%, but accurately assessing mean reported intake is not equivalent to accuracy of actual mean intake nor does it imply that intake is in steady state. Given the variability in intake of any one nutrient or food over time and the variability of co-ingested nutrients and foods which can also impact skeletal acquisition compounded by our inability to assess accurately consumption, the premier approach to evaluating the contribution of any nutrient or food is through controlled feeding studies. Controlled feeding studies can be conducted for sufficiently long periods in animal studies to monitor changes in bone. However, it is not practical in humans to control diet sufficiently long to measure changes in bone. Subjects can be randomized to dietary supplements or diet prescriptions, but rarely are there sufficient resources or subject commitment to provide a completely controlled diet over the years required to see changes in bone mass or quality. Shorter-term approaches are available to predict impact of diet on bone. Because 99% of the calcium in the body resides in the skeleton, determining whole body calcium retention through metabolic balance studies and calcium turnover rates through calcium isotopic tracer studies are good surrogates for bone
Many factors influence skeletal growth and ultimate peak mass acquired by adulthood. Genetics is thought to contribute 60–80% of peak bone mass and lifestyle factors 20–40% [1, 2]. Genes that control body size are undoubtedly influential in controlling skeletal growth. Crude markers for genetic differences include race and gender, the focus of this book. Lifestyle factors include all of the cultural exposures and individual choices that influence skeletal growth, notably physical activity and diet, the focus of this chapter. The interplay of these nature–nurture factors is what we strive to understand, but methodological limitations thwart our attempts. In this chapter, the influence of nutrition and the interaction of diet and exercise in the development of male peak bone mass will be reviewed, recognizing that the evidence for boys is much less than for girls. Skeletal fragility, which occurs naturally during the pubertal growth spurt or due to pediatric disorders, will also be discussed.
Assessing the role of nutrition in skeletal acquisition Diet is a highly variable and complex behavior to study. There are some characteristics common to individual cultures that can greatly influence bone health, i.e. the low dairy, high salt, plant-based diets of many Asian populations in contrast to high dairy and meat-based diets of many Western populations. However, increasingly, we mix cultural menus on a regular basis as ethnic foods are so accessible. For example, Sushi bars are now common in grocery stores in the USA, a very recent phenomenon. Current diet assessment methodology is poorly equipped to determine the nutrient intake or diet patterns of individuals. Self-reported Osteoporosis in Men
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Dietary calcium mg/d
3000 2500 2000 1500 1000 500 0 0
5
10
15
20
25
30
35
40
Figure 10.1 Dietary calcium from monthly food records in a 14-year-old adolescent [4].
Relative role of nutrition in skeletal requisition In the introduction, the reported proportional contribution of genetic:lifestyle factors was 60–80:20–40%. One wonders if the inability to measure accurately lifestyle factors or their tendency to change considerably on a daily basis and throughout the lifespan relative to genetic contributors diminishes our ability to determine their relative importance. In controlled feeding metabolic studies, calcium intake explained 12.3% of skeletal calcium retention and race explained 13.7% in black and white adolescent girls [8]. Thus, this diet factor of calcium intake in an otherwise consistent 4-day cycle diet had nearly as great an impact as genetics, indicated through race, on skeletal calcium accretion. The relative influence of sex compared to other predictors of skeletal calcium accretion in puberty, including calcium intake, regulators of calcium metabolism, hormones, physical activity, measures of body size and measures of sexual maturity was recently reported [9]. This example of diet–gene contribution to skeletal calcium accretion is from metabolic balance studies in pubertal children conducted by the Weaver laboratory. The primary question addressed in the study of boys was whether boys needed more calcium than girls to achieve their larger skeletons or if they utilize calcium more efficiently. The bulk of skeletal calcium accretion occurs during the pubertal growth spurt. The higher total body bone mineral content (TB BMC) accretion rates in boys compared to girls is shown
450 400
Girls age of peak 12.54 peak value 325 g/y
350 TB BMD velocity in g per
balance and turnover rates [6, 7]. In order for bone mass to change, first, calcium metabolism must be perturbed. The metabolic balance approach is the only method that has been used to study a range of nutrient intakes in attempt to determine optimal intakes for skeletal accretion and will be described in the next section and further in the section on calcium.
Boys age of peak 14.05y peak value 400 g/y
300 250 200 150 100 50 0
9 10 11 12 13 14 15 16 17 18 19 Age in years
Figure 10.2 Total body bone mineral content (TB BMC) accretion rates, age of peak velocity, and peak value as a function of age in boys and girls [10].
in Figure 10.2. This figure is derived from the longitudinal bone densitometry data in Canadian white boys and girls of Bailey et al [10]. This shows that the average peak velocity in bone mineral acquisition is higher in boys than girls and occurs about a year and a half later. Approximately one-fourth of peak bone mass is accumulated in the two years surrounding this peak. Thus, the influence of calcium intake on calcium retention was determined in white girls aged 12–14 years and boys aged 13–15 years [11]. Calcium retention was determined through metabolic balance studies using controlled diets which varied over a range of calcium intakes supplied through fortified juice. The subjects lived on the University campus for two three-week periods separated by a washout period in which each subject received
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1300
Ca retention (mg/day)
1100 Boys
900 700 500 300
Girls
100 –100 –300 500
700
900
1100
1300
1500
1700
1900
2100
2300
Ca intake (mg/day)
Figure 10.3 Scatterplot and predicted curves of calcium retention as a function of calcium intake in adolescent white boys () and girls (). Boys retained 171 38 mg/d more calcium than girls across the range of calcium intakes. [11].
a lower and higher intake assignment. Duplicate diet composites were analyzed for calcium as well as all urine and feces in 24-hour pools. Urinary and fecal compliance was monitored by urinary creatinine and recovery of a nonabsorbable fecal marker. Calcium retention was determined by subtracting excretion from intake. Figure 10.3 shows that calcium retention in boys was higher than girls across the range of calcium intakes by a constant amount of 171 38 mg/d. Thus, boys were more efficient than girls at calcium utilization for bone acquisition throughout the range of calcium intakes studied. Because of constant differences due to sex across calcium intake, a simple gender term could be used in the non-linear regression model of the form:
Y o e L / (1 e L ) 3 g
where Y is the mean Ca retention for a given Ca intake, L 1(1 2xy), x is Ca intake and g is gender coded as 0 for girls and 1 for boys. The implication of this gender term is that boys and girls can be studied together for calcium retention without requiring two cohorts, which would double the sample size. When the value for peak TB BMC accretion per year in boys in Figure 10.2 is converted to mg Ca retention per day knowing that calcium is a constant percent of BMC, the value for calcium retention is 359 mg/d. The mean selfreported calcium intake of the boys in that cohort [12] was 1140 392 mg/d. Using our non-linear regression model, a calcium intake of 1140 mg/d would correspond to a mean Ca retention of 442 mg/d which is remarkably close to the value observed by Bailey et al [10] considering their lack of controlled diet and errors associated with self-reported intakes as well as the short-term nature of our metabolic balance studies.
A secondary analysis of this study explored predictors of calcium retention in boys [11]. Dietary calcium intake, hormonal status (parathyroid hormone (PTH), insulin-like growth factor I (IGF-I) and IGF-I binding protein (IGF-IBP), vitamin D metabolites and sex steroids), biochemical markers of bone metabolism, habitual physical activity, physical fitness, habitual calcium intake, sexual maturity, body consumption and anthropometric measures of body size were all tested in the model for their influence on calcium retention. Dietary calcium explained 21.7% of Ca retention and serum IGF-I explained an additional 11.5%. The effect of serum IGF-I is shown in Figure 10.4. For each unit increase in log IGF-I, there is a 144 mg/d increase in mean calcium retention. IGF-I is a major regulator of longitudinal bone growth through stimulating proliferation and differentiation of chondrocytes at the epiphyses [13]. Serum IGF-I closely matches peak bone accretion rates [14]. None of the other factors measured contributed additional explanation for calcium retention. Thus, diet and an indicator of sexual maturity, which is under the influence of genetic programming, explained 33.2% of the variation in Ca retention in this cohort of adolescent boys. We must look further to explain the rest of the variation in calcium retention.
Micronutrients and bone growth Bone is a living tissue and all essential nutrients are required for bone growth. In this section, the role of the major micronutrients involved will be discussed, focusing primarily on those nutrients with concern about intakes.
Osteoporosis in Men
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Mean Ca retention (mg/d)
1000
800
IGF 1 (ng/mL) 600
600
350 200
400
200
0 600
800 1000 1200 1400 1600 1800 2000 2200 Mean Ca intake (mg/d)
Figure 10.4 Predicted calcium retention across calcium intakes as a function of serum IGF-I in male adolescents. Contours describe serum IGF-I levels of 200, 350 and 600 ng/mL which correspond to z-scores of 1, 0 and 2, respectively, r2 0.332, P 0.002 [9].
Calcium Calcium is the largest contributor to bone mineral content. It exists in hydroxyapatite crystals, which contribute to bone strength, and acts as a reserve to maintain serum calcium levels within a narrow range during periods of dietary calcium inadequacy. Calcium intakes fall below recommended levels for much of the world’s population. Males consume more calcium than females because they consume more calories on average. Nevertheless, calcium intakes in males are especially inadequate during pubertal growth. In an evaluation of adequacy of calcium intakes in 20 countries, Looker [15] compared average intakes against their respective country requirements. For adolescent males, 65% on average reach their country specific calcium recommendations which range from 500 to 1300 mg/d. Calcium requirements are well established for American white boys [11, 16]. Figure 10.3 shows that the plateau intake for maximal calcium retention in adolescent boys is not significantly different from 1300 mg/d previously reported for adolescent girls [17]. Recommended calcium intakes for children aged 4–8 years is 800 mg/d, but this too was based on data in girls as no balance studies were available for boys. Calcium requirements for other subpopulations need to be determined. Most (72%) of dietary calcium comes from dairy products [18]. Children who do not choose calcium rich foods are often not compliant with supplements. Furthermore,
calcium intake is a marker for other nutrients [18], but this would not be true when calcium is ingested in the form of supplements. It is important to establish good dietary habits early because calcium intake in adolescents tracks (r 0.43) into adulthood for males [19]. There are few randomized controlled trials (RCTs) of calcium intake that include boys (Table 10.1). In the study of identical twins [20], a 3-year calcium intervention increased bone mineral density (BMD) only in the prepubertal children. Another study of white prepubertal boys showed a relatively short intervention of 800 mg calcium daily for 8.5 months showed a trend toward improved BMD [23]. In Chinese 7 year olds, a one-year calcium intervention increased lumbar spine BMC and area, but not proximal femoral neck [21]. In African children, midshaft radius BMC and BMD were significantly increased by a oneyear calcium supplementation [22]. In white boys from the UK, randomization to 1 g calcium supplementation for 13 months increased height by 0.4% (P 0.0004) and lean mass by 1.3% (P 0.02) as well as BMC 1–3% and bone area of several sites [24]. A similar study [25] in 16–18year-old girls showed calcium supplementation increased bone mineral mass, but not bone size or height, in contrast to boys. However, the effect of calcium supplement on growth may be more related to the timing of the intervention relative to peak BMC accretion rather than differences in gender responsiveness. Figure 10.2 illustrates that 16–18-year-old girls have moved past their peak accretion period unlike boys. The authors projected that the observed increases in BMC with calcium supplementation (about 0.2 SD), if maintained into adulthood, would lower fracture risk by about 15%.
Vitamin D Requirements for vitamin D have not been established by rigorous evidence of the relationship of status to a functional indicator. There has been much speculation that vitamin D insufficiency in children is widespread based on adult cut off levels for serum 25(OH)D levels [26, 27]. However, serum 25(OH)D levels have not positively predicted calcium absorption or retention in children [27–30]. There have been no vitamin D intervention trials on bone in boys.
Magnesium and Phosphorus Both of these minerals comprise substantial portions of bone mineral. There are no concerns regarding deficiencies of these minerals in children. Severe magnesium deficiency results in structural changes that diminish bone volume [31]. Phosphorus intake excess combined with a low calcium intake has been a concern, as a low Ca/P ratio alters bone mineralization and bone turnover [32]. Cola beverages contain high levels of phosphate which have been negatively
Table 10.1 Differences in mean changes in bone mineral content and bone mineral density in calcium treated versus placebo groups in randomized, controlled trials in boys Source
Ref. Subject. Age (y) Sex Race/ no. no location
Length Calcium study intake (months) Controls (mg/day)
Calcium Site intake Treatment (mg/day)
Johnston et al, 1992
20
140 twins 6–14
F/M White, IN 36
908
1612
Lee et al, 1995
21
109
F/M Asian, China
571
1363
7
18
Midshaft radius Distal radius* Lumbar spine Femoral neck Ward’s triangle Greater trochanter Distal radius Lumbar spine
22
160
8.3–11.9 F/M Black, Gambia
12
342
1056
Bass et al, 2007
23
88
7–11
8.5
934
800 (milk minerals)
24
143
16–18
M
White, Australia
White, UK
13
1283
1858
BMD BMD BMD BMD BMD BMD
17.7% 21.5% 20.1% 15.3% 15.4% 18.1%
15.2% 18.2% 19.5% 14.9% 14.2% 17.11%
BMC Area BMC Area BMC
15.92 (T) vs 14.95% (P) gain, P 0.53 7.74 (T) vs 6.00% (P) gain, P 0.081 20.92 (T) vs 16.34% (P) gain, P 0.035 11.16 (T) vs 8.71% (P) gain, P 0.049 24.19 (T) vs 23.42% (P) gain, P 0.37
Proximal femoral neck Midshaft radius BMC BMD Non-exercise: Femur Tibia–fibula Exercise: Femur Tibia–fibula Whole body Lumbar spine
Total hip Femoral neck Intertrochanter *
Placebo (P)
3.0 1.4 (T-P), P 0.034 4.5 0.9 (T-P), P 0.0001
BMC BMC
1.1% (TvsP, P 0.06 1.4% (T vs P), P 0.11
BMC BMC
2.0% (T vs P, or No exercise), P 0.03 3% (T vs P), P 0.02
BMC BMC Bone area BMC BMC BMC
1.3% (TvsP), P 0.02 2.5% (TvsP), P 0.004 1.5% (TvsP), P 0.0003 2.3% (TvsP), P 0.01 2.4% (TvsP), P 0.01 2.7% (TvsP), P 0.01
Difference between groups significant for percent increase at distal radius (3.3, 95% CI 1.2–5.5). Difference between groups for midshaft radius was 2.5 (95% CI 0–4.9) and for the average of 6 sites was 1.4 (95% CI 0–2.5). All other between group differences were not significant. T: treatment; p: placebo; BMC: bone mineral content; BMD: bone mineral density; M: male; F: female; UK: United Kingdom; IN: Indiana, USA.
l
Prentice et al, 2005
M
Treatment (T)
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Dibba et al, 2000
Measure Group mean increase
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associated with bone gain in children [33]. However, the displacement of milk by beverages which lack the nutrient package of milk is more detrimental to bone than their phosphate content.
Dietary patterns and bone growth The formative years are the period of greatest skeletal growth, but also are when lifelong eating and exercise habits are set. Food is the most adequate source of nutrients and health promoters. Penetration of supplement use among children is low. Recommended food patterns by the 2005 Dietary Guidelines Advisory Committee for Americans considered bone health [18]. Many other Western countries are influenced by these guidelines which used both an evidencebased approach to determine the relationships of dietary intakes and bone health and other measures of health as well as a food modeling approach to achieve intakes of nutrients recommended by the Institute of Medicine [16] within one’s energy requirements. Adequate energy and macronutrients as well as micronutrients previously discussed are required for optimal growth. The role of dietary protein on bone health is discussed in another chapter, but more research is needed in children. Dietary habits including salt intake and foods which contain enhancers and inhibitors of mineral absorption also play a role in bone health.
Milk and Milk Products Milk consumption is associated with overall diet quality. Adequate milk intake in children is associated with adequacy of several other micronutrients including calcium, potassium, magnesium, zinc, iron, riboflavin, vitamin A, folate and vitamin D [34]. The Dietary Guideline for Americans recommends 2 cups of milk per day for children between ages of 2 and 8 years and 3 cups per day over age 8 [18]. It is difficult to meet vitamin D, calcium and potassium requirements without milk. Among 2364 children aged 9–18 (1154 males) who reported no dairy intake in the NHANES 2001–2002 study, only one child achieved adequate calcium intake without use of calcium fortified foods. Children with dairy-free diets had approximately half the calcium intake of those whose diet included dairy products [35]. Children may avoid milk products because of intolerance or allergy, dislike and/or alternative choices (soft drinks) or religious customs. Children who avoid milk are more likely to have low calcium intakes and sustain forearm fractures [36]. Likewise, children who avoid milk demonstrate significant declines in lumbar spine BMD after 2 years of follow up [37]. The detrimental effect of low milk intake on bone may be lower for boys than it is for girls. A case control
study of 34 girls and 57 boys aged 2.5–20 with cow’s milk allergy compared to those without resulted in an odds ratio for fracture of 4.6 (P 0.013) for girls and 1.3 (NS) for boys [38]. Two large cohort studies have evaluated milk and soft drink intake by dietary assessment and reported on bone group. Among 220 boys and girls aged 8–14, replacing milk with soft drinks was more detrimental to bone gain by girls than by boys [38]. Among 591 boys and 774 girls either 12 or 15 years old, consumption of soft drinks was associated with lower BMD at the dominant heel for girls but not boys and no difference in forearm BMD for either sex, after adjustments [39]. An RCT of high milk intake versus high meat intake (identical protein amounts in the two diets) among 8-yearold boys showed that increased milk intake decreases bone turnover among boys after 7 days, likely through increased serum IGF-I. Those randomized to milk had significantly higher calcium intakes over the 7 days and serum osteocalcin and serum C-terminal cross-linking telopeptide of collagen 1 (CTX) decreased [40].
Salt Dietary salt has a detrimental effect on growing bone through increasing urinary excretion. In fact, dietary salt is the largest known predictor of urinary calcium excretion [41].
Enhancers and Inhibitors of Mineral Absorption The presence of enhancers and inhibitors of mineral absorption in diets can alter the demand for mineral important to bone. Oxalic acid, found in spinach, rhubarb and some seeds and other plant sources, is a potent inhibitor of calcium absorption. Calcium from spinach is absorbed approximately one-tenth as efficiently as milk calcium because the calcium oxalate salt in spinach is largely indigestible [42]. Phytic acid, the storage form of phosphorus in seeds, binds divalent cations, including Mg2, Zn2, Fe2 and Ca2, resulting in decreased absorption of these minerals. The inhibitory effect of phytate on calcium absorption is less than that of oxalate and is further decreased with fermentation [43]. Liberal consumption of whole grains and legumes is encouraged by the Dietary Guidelines for Americans [18], but this type of diet emphasizes the need for adequate intake of minerals. There have been numerous reports evaluating dietary constituents that might enhance mineral absorption, especially protein products or amino acids and non-digestible oligosaccharides. The most promising for growing bone has been a mixture of short- and long-chain inulin-like fructooligosaccharides [44]. A supplement of 8 g/d of the fructan product increased (P 0.03) total body BMC though enhancing calcium absorption efficiency by 8.5 1.6% (P 0.001) in pubertal adolescents. In growing rats,
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whey protein enhanced calcium absorption from a single meal, but the enhancing effect adapted away with chronic feeding [45].
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but not bone resorption (CTx), was also reduced. Similar studies in the growing skeleton need to be undertaken.
Nutrition and pediatric disorders Diet and exercise interactions Several studies provide evidence that there is a positive interaction between diet and physical activity. The most studied aspects of diet and milk and calcium intake. In one study, 28 boys were randomized to supplementing usual diet with three extra servings per day of fluid milk or non-calcium fortified juice, while engaged in a 12-week supervised resistance training program 3 hours/week [46]. Milk drinkers had higher calcium, vitamin D, vitamin A, magnesium, phosphorus and carbohydrate intakes. The milk group had higher total body (BMD) at the end of the training period. Another trial randomized 88 pre- and early pubertal boys to one of four groups: moderate exercise with and without calcium and low impact exercise with and without calcium (all exercise was 20 minutes three times per week and addition of calcium was through milk-mineral fortified foods versus non-fortified foods) [23]. After 8.5 months, femur BMD had increased more for the moderate exercise plus calcium group compared to each of the three other groups (moderate exercise plus placebo, low exercise plus calcium and low exercise plus placebo; approximately 2% increase, P 0.03). At the tibia-fibula, BMD was 3% greater (P 0.02) for the exercise plus calcium group compared to low exercise plus placebo. Although this small study was underpowered to see significant (only trends at P 0.05) effects of exercise and calcium alone, the combined intervention of calcium and exercise resulted in significant advantages to femur but not arms or spine. In contrast, a study in 9-year-old girls found main effects of exercise at the legs and calcium at the arms and an exercise-calcium interaction at the femur [47]. In the randomized trial of calcium supplementation in late adolescent boys previously discussed [24], there was a positive interaction with physical activity (4.4%, P 0.05) on BMC response at the intertrochanter, but not at other skeletal sites. The mechanism of the influence of exercise on calcium metabolism is not completely understood. Increased calcium absorption efficiency and reduced bone turnover have been reported. Fractional calcium absorption efficiency measured by a proxy, strontium, was higher in 31 exercisetrained compared to 26 age-matched sedentary young men (20.3 4.5 versus 16.3 3.1%, P 0.001) [48]. Using the same method for estimating calcium absorption efficiency in 18 male athletes, an acute bout of exercise significantly increased calcium absorption from 14.6 0.8% to 16.2 0.07% (P 0.05) and serum 1,25(OH)2D levels from 104 111 to 123 10 pmol/L (P 0.05) [49]. In this study, a biochemical marker of bone resorption (PICP),
Several pediatric disorders are associated with worsened bone health (Table 10.2), many as a result of their impact on nutritional status. Conditions affecting bone through nutritional pathways include: anorexia nervosa, celiac disease, inflammatory bowel disease and obesity. Other conditions may be primarily genetic (osteogenesis imperfect, cystic fibrosis) or idiopathic/acquired (seizure disorders); may have mechanisms that are based in alterations in bone turnover or in connective tissue; and may be associated with low bone density and BMC because of medications used to treat the condition, such as glucocorticoids, antiretrovirals and anticonvulsants.
Anorexia Nervosa Anorexia nervosa (AN) is a condition of undernutrition, low body weight and fear of gaining weight. While more common among females, 5–15% of AN patients are male [50]. Lifetime prevalence estimates for AN in US males are approximately one-third of that for females [51] and, in one study, 11% of adolescents hospitalized for eating disorders were male [52]. AN has been associated with high rates of bone resorption, bone loss and increased fracture risk among girls [53, 54]. Recently, Misra et al demonstrated that boys with AN (n 17, mean age 16.0 1.8)
Table 10.2 Conditions associated with low bone mass and/or fractures among children and adolescents Anorexia nervosa Celiac disease Craniospinal radiation Cystic fibrosis Diabetes mellitus Epilepsy (anti-convulsant medications) Gaucher disease Hemophilia HIV (antiretroviral therapy) Inflammatory bowel disease Obesity Organ transplantation (immunosuppressive medications) Osteogenesis imperfecta Osteoporosis-pseudoganglioma syndrome Nephrotic syndrome, glucocorticoid-sensitive Neurofibromatosis I Renal osteodystrophy Rheumatologic disease Turner syndrome Adapted from Gordon, 2005 [54].
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have lower BMD at lumbar spine, total hip and all subregions compared to normal, bone-age matched controls. Additionally, these boys had lower levels of PINP and CTX and lower testosterone levels compared to controls. Lower BMD was predicted by lower testosterone, body mass index (BMI) and lean mass [50, 55].
Celiac Disease Celiac disease (also referred to as celiac sprue) is an immunemediated small bowel enteropathy caused by gluten sensitivity. Celiac disease is increasingly diagnosed in children and adults, with a prevalence of 3–13 in 1000 for children and adolescents between the ages of 2.5 and 15 years [56]. Symptoms are often non-specific, including abdominal pain, diarrhea, abdominal distention and failure to thrive. Untreated, celiac disease results in malabsorption which can lead to vitamin D insufficiency, osteomalacia and fractures [57–60]. Bone disease can occur in patients without gastrointestinal symptoms [61–64]. Studies have demonstrated lower vitamin D levels, lower calcium and higher intact-parathyroid hormone levels [65, 66], as well as higher bone-specific alkaline phosphatase and n-telopeptide levels among children with untreated celiac disease compared to controls [59]. Among seropositive children with type I diabetes who also test positive for antibodies to gluten, the degree of villous atrophy seen on small bowel biopsy is associated with higher likelihood of growth failure and low bone mass [64]. When children are treated with a gluten-free diet, the absorptive problems are reversed and vitamin D levels and bone can be corrected. Among 54 children with previously untreated celiac disease, calcium, 25(OH) vitamin D and iPTH were normalized after 6 months of gluten-free diet [65]. Bone mineral content, bone area and BMD are all improved with treatment, as demonstrated by case control studies. The time it takes for treatment to improve BMD may be as little 6 months and gains have been documented at both 4.3 years and up to 10.7 years after starting treatment [59, 67]. Similar improvements in BMD have been shown in children with diabetes and celiac disease after 12 months of gluten restriction [64].
Inflammatory Bowel Disease Children with inflammatory bowel disease (IBD), either Crohn’s disease (CD) or ulcerative colitis (UC), are at risk for developing low bone mass because of the underlying inflammation, delayed maturation, concomitant malnutrition or medications (chronic use of glucocorticoids) [68]. Reduced BMD has been demonstrated in boys and girls with IBD [69–74]. This finding is at least partially explained by glucocorticoid treatment [70, 72–73]. Studies are conflicted as to gender differences, but some indicate that boys are less likely than girls to have reduced BMD [70, 71, 73, 75]. The prevalence of reduced BMD is higher among children
with CD compared to UC [70, 73]. Children with CD are also at increased risk for fracture [76]. There are several aspects of the relationship between IBD and skeletal health, including the question of whether 25-hydroxy vitamin D levels influence BMD and fracture in children/adolescents with BMD, that remain incompletely understood.
Obesity Although higher BMI is thought to be predictive of osteoporosis in adults, overweight children and adolescents may be at increased risk of fractures [77], possibly because of increased load on a developing skeleton [78]. A comparison of children who had broken a distal forearm on two separate occasions to those without prior fracture revealed low calcium intake, milk intolerance, early age at first fracture and high BMI (33% overweight versus 15.5% in control group) as risk factors, despite no difference between the groups in physical activity [77]. Several recent studies attempt to improve our understanding of the determinants of bone structure in obese versus normal weight children and adolescents. Compared with children of healthy weight, 202 overweight and obese boys had lower vertebral BMD for their bone area, body height and body weight and pubertal development. BMC and bone area relative to body weight was 2.5–10% lower than predicted (P 0.05) [79]. It may be that the obese pubertal skeleton is adapted for lean mass and muscle forces but not for fat mass [80]. However, this concept remains incompletely understood and there may be gender differences: a study of 444 girls and 482 boys aged 6–18 years showed that non-bone fat free mass was a determinant of BMD in all girls but only prepubertal boys [81]. As opposed to the effect of anorexia and low body weight on bone, the effect of weight loss in obese and overweight adolescents appears to be beneficial for bone health. Adolescents participating in medically supervised weight loss programs that included exercise and diet with or without weight-loss medication had improved BMC [82, 83].
Conclusions As with other aspects of our understanding of male osteoporosis, research on the role of nutrition in the growing male skeleton lags behind that in girls. Recently, the effect of calcium intake on calcium retention was reported for white adolescent boys as well as other predictors of calcium retention. Attention to bone health is warranted for children with conditions that may predispose to bone loss, reduced bone accrual and fractures. Studies of other age groups and racial and ethnic minorities are needed. Little systematic work has been done on nutrients other than calcium or importance of food patterns in the growing male skeleton.
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64. E. Artz, J. Warren-Ulanch, D. Becker, S. Greenspan, M. Freemark, Seropositivity to celiac antigens in asymptomatic children with type 1 diabetes mellitus: association with weight, height, and bone mineralization, Pediatr. Diabetes 9 (4) (2008) 277–284. 65. C. Zanchi, G. di Leo, L. Ronfani, S. Martelossi, T. Not, A. Ventura, Bone metabolism in celiac disease, J. Pediatr. 153 (2008) 262–265. 66. P.L. Selby, M. Davies, J.E. Adams, EB. Mawer, Bone loss in celiac disease is related to secondary hyperparathyroidism, J. Bone Miner. Res. 14 (4) (1999) 652–657. 67. S. Mora, G. Barera, S. Beccio, et al., Bone density and bone metabolism are normal after long-term gluten-free diet in young celiac patients, Am. J. Gastroenterol. 94 (2) (1999) 398–403. 68. F. Sylvester, IBD and skeletal health: children are not small adults!, Inflamm. Bowel Dis. 11 (2005) 1020–1023. 69. D. Herzog, N. Bishop, F. Glorieux, E.G. Seidman, Interpretation of bone mineral density values in pediatric Crohn’s disease, Inflamm. Bowel Dis. 4 (4) (1998) 261–267. 70. A.M. Boot, J. Bouquet, E.P. Krenning, SMPF. de Muinck Keizer-Schrama, Bone mineral density and nutritional status in children with inflammatory bowel disease, Gut 42 (1998) 188–194. 71. F. Walther, C. Fusch, M. Radke, S. Beckert, Osteoporosis in pediatric patients suffering from chronic inflammatory bowel disease with and without steroid treatment, J. Pediatr. Gastroenterol. Nutrit. 43 (1) (2006) 42–51. 72. E.J. Semeao, A.F. Jawad, N.O. Stouffer, B.S. Zemel, D.A. Piccoli, VA. Stallings, Risk factors for low bone mineral density in children and young adults with Crohn’s disease, J. Pediatr. 135 (1999) 593–600. 73. R. Gokhale, M.J. Favus, T. Karrison, M.M. Sutton, B. Rich, B.S. Kirschner, Bone mineral density assessment in children with inflammatory bowel disease, Gastroenterology 114 (1998) 902–911.
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74. F.J. Cowan, J.T. Warner, F.D.J. Dunstan, W.D. Evans, J.W. Gregory, H.R. Jenkins, Inflammatory bowel disease and predisposition to osteopenia, Arch. Dis. Child 76 (1997) 325–329. 75. E.J. Semeao, A.F. Jawad, B.S. Zemel, K.M. Neiswender, D.A. Piccoli, VA. Stallings, Bone mineral density in children and young adults with Crohn’s disease, Inflamm. Bowel Dis. 5 (3) (1999) 161–166. 76. E.J. Semeao, V.A. Stallings, S.N. Peck, D.A. Piccoli, Vertebral compression fractures in pediatric patients with Crohn’s disease., Gastroenterology 12 (1997) 1710–1713. 77. A. Goulding, A.M. Grant, S.M. Williams, Bone and body composition of children and adolescents with repeated forearm fractures, J. Bone Miner. Res. 20 (12) (2005) 2090–2096. 78. A. Goulding, R.W. Taylor, I.E. Jones, P.J. Manning, S.M. Williams, Spinal overload: a concern for obese children and adolescents? Osteoporos. Int. 13 (2002) 835–840. 79. A. Goulding, R.W. Taylor, I.E. Jones, K.A. McAuley, P.J. Manning, S.M. Williams, Overweight and obese children have low bone mass and area for their weight, Int. J. Obesity. 24 (2000) 627–632. 80. M.A. Petit, T.J. Beck, J. Shults, B.S. Zemel, B.J. Foster, M.B. Leonard, Proximal femur bone geometry is appropriately adapted to lean mass in overweight children and adolescents, Bone 36 (2005) 568–576. 81. A. Ackerman, J.C. Thornton, J. Wang, R.N. Pierson Jr., M. Horlick, Sex differences in the effect of puberty on the relationship between fat mass and bone mass in 926 healthy subjects, 6 to 18 years old, Obesity 14 (5) (2006) 819–825. 82. N. Stettler, R.I. Berkowtiz, J.L. Cronquist, et al., Observational study of bone accretion during successful weight loss in obese adolescents, Obesity 16 (1) (2008) 96–101. 83. C.C.W. Yu, R.Y.T. Sung, R.C.H. So, et al., Effects of strength training on body composition and bone mineral content in children who are obese, J. Strength Condit. Res. 19 (3) (2005) 667–672.
Chapter
11
Physical Activity and Skeletal Growth Heather M. Macdonald1, Melonie Burrows2,3 and Heather A. McKay2,3,4 1
Schulich School of Engineering, University of Calgary, Calgary, Canada Department of Orthopaedics, University of British Columbia, Vancouver, Canada 3 Centre for Hip Health and Mobility, Vancouver, canada 4 Department of Family Practice, University of British Columbia, Vancouver, Canada 2
few exercise intervention studies have been conducted in boys. That said, it seems ‘a little goes a long way’ and short bouts of high impact physical activity over a relatively short (8–20 months) timeframe may be all that is required to enhance children’s bone mass and strength. However, the specific exercise prescription for optimal bone strength has not been clearly defined for either sex. This knowledge gap may be related in part to our limited understanding in humans of how bone structure adapts to mechanical stimuli. Two-dimensional imaging technologies, such as dual energy x-ray absorptiometry (DXA) were designed for adults and these were then used to study pediatric bone. However, more sophisticated imaging techniques, such as peripheral quantitative computed tomography (pQCT) and high resolution pQCT (HR-pQCT) now permit us to evaluate bone’s complex nature. It is only very recently that investigators have begun to evaluate the material (e.g. volumetric bone mineral density), structural (e.g. bone cross-sectional area, second moment of area and cortical thickness) and microstructural (e.g. cortical porosity, trabecular number) adaptations that underpin bone’s response to physical activity. In this chapter we review:
Introduction When on board H.M.S. ‘Beagle’, as naturalist, I was much struck with certain facts in the distribution of the inhabitants of South America... These facts seemed to me to throw some light on the origin of species – that mystery of mysteries, as it has been called by one of our greatest philosophers. Charles Darwin. On the Origin of Species, 1859 On the Origin of Species was first published on 24 November 1859 and cost fifteen shillings (84 cents US). The 6th edition published in 1872, included a section called ‘Effects of habit and the use and disuse of parts’. In this section, Darwin provided an example of how large, ground feeding birds acquired stronger legs through exercise and weaker wings from not flying ‘until, like the ostrich, they could not fly at all’ [1]. Thus, the positive role of physical activity, and the negative consequences of disuse, on bone have been known for a long time. Although the skeletal adaptations that Darwin noted were manifest over generations, the effect of weight-bearing physical activity on bone has also been noted over much shorter timeframes. Indeed, there is now compelling evidence that physical activity is integral for developing and maintaining a strong and healthy skeleton. Further, the capacity for the skeleton of children and adolescents to adapt to exercise may be much greater than older adult bone [2, 3]. Therefore, optimizing bone accrual during the crucial years of growth may well be the best means to reduce fracture risk in later life [4, 5]. Despite the many advances in our understanding of the benefits of physical activity for growing bone, relatively Osteoporosis in Men
1. the mechanisms by which bone adapts to physical activity and 2. the imaging modalities that have been used to quantify these changes. From this foundation, we critically review the influence of physical activity on bone mass accrual in boys. We then discuss the emerging data describing material and structural properties that underpin the bone strength response to physical activity. We close with a discussion of whether benefits of physical activity undertaken during the growing years are sustained across the lifespan. 131
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How does bone adapt to physical activity? The primary mechanical function of the skeleton is to provide rigid levers for muscles to act against as they work to hold the body upright in the presence of gravitational forces [6]. Consequently, the skeleton is continually exposed to a loading environment where muscle forces produce the greatest loads during voluntary activities. The mechanical stimuli encountered throughout life serve to sculpt the skeleton’s genetic blueprint to match the loading requirements. Bone adaptation to such physical loads is determined by strain, or deformation of bone tissue, and is regulated by feedback loops that serve to maintain a customary strain level [7, 8]. An increase in bone strain (e.g. through an increase in physical activity) results in bone formation which, in turn, reduces bone strain to its original customary level. Conversely, a decrease in bone strain (e.g. through physical inactivity) results in bone resorption. The customary strain level, or setpoint, is likely genetically predetermined and is thought to vary by skeletal location. Further, the theoretical setpoint may be influenced by a variety of factors including age, nutrition and hormones (Figure 11.1) [8]. During growth, bone has the capacity to adapt to activityrelated increases in strain through several mechanisms:
bone cross-sectional area can increase through the addition of new bone to the periosteal surface (periosteal apposition); cortical thickness can increase through a combination of periosteal apposition and reduced endocortical resorption (or endosteal apposition); and tissue density can increase through modifications in trabecular microarchitecture (e.g. increased trabecular thickness [9, 10]). Ultimately, these adaptations adjust bone structure and strength to match the requirements of the mechanical environment [6]. For example, at long bone shafts where bending and torsion forces predominate, small increases in bone diameter contribute exponentially to bone section modulus, an indicator of bone bending strength [11]. Evidence from animal studies suggests that the potential for such adaptations is much greater in the growing than in the non-growing skeleton [2, 3]. In this chapter, we focus on bone adaptations to physical activity in boys. However, we acknowledge the welldocumented sex differences in the tempo, timing and magnitude of the pubertal growth spurt. In addition, the associated differences in hormonal milieu result in significant differences in bone material and structural properties between boys and girls that lead to varying skeletal responses between sexes to activity [12–14]. We encourage the reader to consult the many excellent reviews [10, 13, 15–17] that highlight physical activity and bone health in girls.
BONE STRENGTH Material properties & bone geometry
Tissue Strain
Regulatory Feedback Loop Signalling Pathway
Osteocytes (sensor cells)
Setpoints Signalling Pathway
CHALLENGES Growth: Increases in bone length and muscle force
Osteoblasts
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MODULATORS Genetics, nutrition, behavioural and environmental factors
Figure 11.1 A functional model of bone development based on the mechanostat theory [7] and related approaches [8]. The central component of the regulation of bone development and adaptation is the feed-back loop between bone deformation (tissue strain) and bone strength. During growth, this homeostatic system must continually adapt to external challenges (increases in bone length and muscle force) to keep tissue strain close to a preset level (setpoint). Various modulating factors influence aspects of the regulatory system as indicated by the dashed arrows. Adapted from Rauch and Schoenau [8] with permission from Lippincott Williams & Wilkins.
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How to measure bone adaptation to physical activity The common tool used to quantify skeletal adaptations to physical activity in children is dual energy x-ray absorptiometry (DXA). DXA measures bone mineral content (BMC, g) or areal bone mineral density (aBMD, g/cm2) and is the modality of choice for many investigators due to its widespread availability, relatively short scan time, low effective radiation dose and ability to scan clinically relevant sites such as the proximal femur and lumbar spine. While DXA studies have significantly furthered our knowledge of pediatric bone and its response to exercise and other interventions, its limitations have been clearly articulated [18]. Briefly, due to the two-dimensional planar technology and low resolution, DXA is unable to capture the underlying modifications to bone geometry such as adaptations specific to the periosteal or endosteal surface that directly influence overall bone strength [18]. This has been illustrated in both animal [19] and human [20] studies where exercise-induced changes in BMC or aBMD were minimal or non-existent, yet adaptations in bone geometry and mechanical characteristics were significantly greater in the exercise group. Despite its limitations, DXA remains a valuable clinical tool for the assessment of pediatric bone. Recent guidelines published by the International Society for Clinical Densitometry provide a means to help researchers use DXA technology and report their findings in an appropriate manner [21]. Finally, the well-recognized limitations of DXA have led to a paradigm shift where the focus of pediatric bone research has broadened beyond bone mass, to encompass the key concept of bone strength – and the bone properties that underpin it. In order more accurately to capture bone structural adaptations, the use of non-invasive imaging technologies such as peripheral quantitative computed tomography (pQCT) and magnetic resonance imaging (MRI) for the assessment of bone geometry, volumetric BMD and strength has become more widespread. Further, software is available to estimate bone geometry and strength from DXA scans (hip structural analysis (HSA)) and to derive additional geometrical outcomes from pQCT images (ImageJ). With these innovative tools we can determine surface- and regionspecific responses to loading that are not possible to assess with standard DXA imaging. The most recent evolution, high-resolution pQCT (HR-pQCT, XtremeCT), evaluates bone microstructure in the adolescent skeleton [22, 23]. The higher image resolution (82 m) permits investigation of trabecular microarchitecture including direct measures of trabecular volume and derived values for trabecular number, thickness and separation at peripheral sites (distal radius and tibia). In addition, finite element analysis can be applied to HR-pQCT scans in order to estimate bone strength. Together, these tools allow us to address more complex questions and help to further our understanding of bone adaptations to physical activity during growth.
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What types of physical activity promote bone strength? Despite the many observational and intervention studies that investigated the role of physical activity for bone health during growth, we remain uncertain about the specific type of physical activity that best promotes bone strength in the growing skeleton. In the next section, we discuss intervention studies that evaluated a variety of exercise protocols, however, to date, no study has performed a head-to-head comparison of two types of interventions (jumping versus running, for example) using a randomized controlled design. Many of the exercise protocols are informed by well-designed animal studies. Dr Charles Turner eloquently summarized the findings of these studies as ‘three rules for bone adaptation’ [24]: 1. adaptation is driven by dynamic, rather than static, loading 2. short duration of loading is more osteogenic 3. adaptation is ‘error-driven’, meaning abnormal strains drive structural change. In addition, inserting rest periods between loading bouts further optimizes the bone response to loading [19]. These principles were incorporated into an ‘osteogenic index (OI)’ that predicts the effect of an exercise protocol on bone mass and strength [25]. Three parameters are required to determine the OI: intensity (load frequency), number of loads per session and time between sessions. Importantly, these rules are based on loading-related changes in bone cross-sectional geometry and cortical bone properties. It is not entirely clear whether these rules also apply to loading-related adaptations at trabecular bone sites such as the lumbar spine or distal tibia. However, a newer innovation in animal models is to apply controlled loads at trabecular bone sites [26] and, using high resolution microCT quantify changes in microarchitecture. This approach can be used to determine the optimal loading characteristics for trabecular bone that, in turn, will inform the design of physical activity interventions.
How does physical activity influence the normal pattern of bone accrual in boys? It should come as no surprise that physical activity during growth is an essential element if bones are to achieve superior mechanics and architecture. Natural experiments, where limbs were amputated or congenitally absent, illustrate the tremendous capacity for adaptation of the remaining load-bearing limb [27]. A recent editorial in the Journal of Bone and Mineral Research contends that there is substantial quality evidence to support a key role for physical activity in children’s bone health [28]. This contention is
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well supported by numerous excellent reviews published over the past decade [10, 13, 15–17, 29] as all concluded that appropriate physical activity positively influences the normal pattern of bone mass and strength accrual. However, the debate continues as to whether these adaptations during the early formative years diminish the risk of fracture later in life [5].
What have we learned from cross-sectional studies? A number of cross-sectional studies of physical activity and bone health during growth have focused on comparisons between athlete and non-athlete populations. In general, young athletes participating in weight-bearing sports had augmented bone mass, geometry and strength compared with their less active peers. Importantly, these relationships are evident in boys as early as prepuberty [30, 31]. For example, at the shaft of the radius and tibia, school-aged male gymnasts had greater pQCT-derived cortical bone area and cortical thickness than same age non-gymnasts. Differences in bone geometry translated into a 5% and 14% greater polar SSI (an estimate of bone strength in torsion) at the tibia and radius, respectively. At the distal radius and tibia, boys’ gymnastics participation was associated with significantly greater total and trabecular vBMD which would confer greater resistance to compressive loads at these sites [32]. These findings illustrate the difference in adaptive mechanisms between cortical and trabecular bone that together lead to exerciseinduced gains in whole bone strength. During adolescence, boys who participate in weightbearing sports, such as running, gymnastics, soccer and badminton, consistently demonstrate greater bone mass than their peers who are either untrained or participate in non-impact sports such as swimming [33–35]. Among male badminton players, hockey players and non-athlete controls (17 years old, on average), badminton players had greater aBMD at the trochanter of the proximal femur and the distal femur than hockey players, despite significantly lower weekly average training [34]. It is likely that the training associated with badminton confers more diverse strain patterns than ice hockey and thus, has greater osteogenic potential. Of note, the average starting age of training for both badminton and hockey players was 7 and 9 years of age. Pre- and early puberty provides a ‘window of opportunity’ when bone is most responsive to physical activity [13, 15]. The strongest evidence in support of this theory comes from unilateral loading studies of female racquet sport athletes [36, 37]. However, recent pQCT findings provide further support for the presence of this ‘window’ in boys as well. In a large cohort (n 1068) of young Swedish men (aged 18 and 19 years), cortical bone area at the tibia diaphysis and trabecular vBMD of the metaphysis as well as femoral neck (FN) aBMD were greater if training for their
current sport began before age 13 [38]. In the average boy, age 13 corresponds to the approximate age at peak height velocity (13.4 years) and occurs approximately 1 year prior to peak bone mineral accrual velocity [12]. Thus, physical activity around this period of peak growth may enhance the normal pattern of bone accrual in boys. Cross-sectional athlete studies offer insight into the relationship between physical activity and bone health during growth, however, the high levels of physical activity associated with sport training and self-selection bias hamper external validity. To overcome these limitations, one can compare bone mass and structural differences between the playing and non-playing arms of racquet sport athletes. This unilateral loading model reduces the influence of confounding factors such as genetics, hormones and nutrition. Former competitive tennis players (aged 25–30 years) who began training during childhood had significantly greater side-to-side differences in estimates of bone strength at radius and humerus than non-playing controls (23–67% versus 5–16%, respectively) [39]. Importantly, greater bone strength at the humeral shaft was due to enlarged bone area (total and cortical CSA), not greater vBMD, indicating activity-related periosteal apposition. Studies of habitual or leisure-time physical activity are more generalizeable to all children – many of whom do not engage in organized or competitive sport. Unfortunately, habitual physical activity as a behavior is multidimensional and difficult to assess, particularly in young children. To date, habitual activity is assessed most often with subjective methods such as self-report questionnaires. In a large cohort of pre- and early pubertal boys, physical activity was measured with a valid and reliable self-report questionnaire and predicted boys’ total vBMD and bone strength index (BSI, an estimate of bone strength in compression) at the distal tibia (8% site) [32, 40]. The influence of physical activity on distal tibia bone strength persisted even after accounting for muscle cross-sectional area, a surrogate of muscle force. Similar to the results reported at the tibial diaphysis in gymnasts [31] and tennis players [39], physical activity was associated with boys’ cortical area and polar SSI at the tibial midshaft (50% site). Thus, at shaft sites where bending loads predominate, the optimal structural adaptation is to increase periosteal apposition, placing bone further from the neutral axis, so as to reduce resistance to bending. Despite best efforts, accurate assessment of children’s physical activity is an ongoing challenge. Questionnaires are a cost- and time-effective tool in large studies, however, young children have limited memory and recall [41]. Further, these relatively insensitive tools are unable to differentiate weight-bearing or intense activity, which often leads to reports of weak associations between leisure-time activity and bone outcomes. More recently, accelerometery has been employed as an objective assessment of children’s leisuretime physical activity. Accelerometers are valid and reliable tools that monitor frequency, intensity and duration of
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self-report questionnaire) and boys in the upper quartile. The more active boys demonstrated a greater bone mineral accrual rate at peak and acquired more bone in the 2 years around peak growth, compared with boys in the lower quartile of physical activity (Figure 11.2). Specifically, boys in the upper quartile of physical activity gained 7–18% more BMC at the femoral neck, lumbar spine and total body than boys in the lower quartile. As a follow up, Forwood et al [49] used PBMAS data and HSA to investigate the influence of physical activity on femoral neck bone strength during adolescence. As before, maturational differences were controlled using age at PHV but within a more sophisticated statistical approach – multilevel random-effects models. In boys, everyday physical activity was a significant independent predictor of both FN CSA and Z after controlling for biological age, height and weight (Figure 11.3(A). These findings suggest that the difference in estimated bone strength between low and high active boys would be approximately 4.5%. Importantly, when leg length and leg lean mass were included in the random-effects model, physical activity was no longer a significant predictor of FN CSA or Z. In keeping with the mechanostat theory [7, 8], lean mass, a surrogate of muscle force, likely mediated the relationship between physical activity and bone strength. 16 Peak LS BMC Accrual (g/yr)
physical activity [42] and are also used to estimate the ground reaction forces (GRF) associated with weight-bearing activities [43]. Although the utility of accelerometers demands more research, they are potentially valuable instruments for estimating the force on weight-bearing bones. Recently, several cross-sectional studies used accelerometers to explore the relationship between activity intensity and bone mass and strength in boys [44–48]. Across these reports, the consistent finding was that boys engaged in vigorous physical activity had significantly greater bone mass and estimated strength at clinically relevant sites such as the femoral neck. For example, 9-year old boys in the upper quartile of physical activity (40 min/day) demonstrated 6% higher FN BMC than boys in the lower quartile (12 min/day) [47]. Boys in the third and fourth physical activity quartiles had 10–14% higher FN strength indices (estimated from DXA measurement of FN width and hip axis length) than boys in the first quartile. Therefore, there may be a weak relationship between bone outcomes and physical activity below a certain threshold [47]. As the field of objective measurement of physical activity merges with pediatric bone research, it will be crucial to define clear thresholds for physical activity and sedentary behavior, relative to their known effects on bone. In summary, results from cross-sectional studies provide valuable evidence that, in boys, sport training and leisuretime physical activity are associated with enhanced bone mass and geometric adaptations that lead to optimized bone strength. However, given the inherent bias in these studies (e.g. self-selection), it seems prudent both to temper the interpretation of findings and encourage more randomized controlled studies that address the more specific question of optimal exercise prescription for children’s bone strength.
Prospective observational studies
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Long-term, prospective observational studies capture growth velocity and, by identifying the age at peak height velocity (PHV), are able to align children on a common maturational landmark. This overcomes the limitations of cross-sectional studies that attempt to compare bone outcomes between children of the same chronological age or at a similar Tanner stage. In a landmark study, the University of Saskatchewan Pediatric Bone Mineral Accrual Study (PBMAS) [12] highlighted the importance of accounting for differences in maturation when comparing children’s bone mass. Bailey and colleagues followed 113 normally active children (60 boys) for a period of 7 years to evaluate the relationship between everyday physical activity and peak bone mass accrual during adolescence. One innovative aspect of this trial was that the age of PHV and age at peak bone mass accrual were identified for every child. Boys were aligned on PHV and bone mass accrual was compared between boys in the lower quartile of physical activity (by
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1.2 1 0.8 0.6 0.4 0.2 Inactive
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Figure 11.2 Lumbar spine (LS) and femoral neck (FN) peak bone mineral content (BMC) accrual velocity (g/year) by inactive and active physical activity groups for boys. Bars are standard deviations. *Significantly greater than inactive P 0.005; **significantly greater than inactive P 0.001. Adapted from Bailey et al [12] with permission from the American Society for Bone and Mineral Research.
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Figure 11.3 (A) Growth curve for hip structural analysis (HSA) of the femoral neck in 17 active boys (solid line, squares) and 17 inactive boys (dashed line, circles), shown according to activity category. Adjusted mean values for section modulus (Z, adjusted for height and weight) are plotted according to years from age at peak height velocity (APHV, where 0 APHV). Adapted from Forwood et al [49] with permission from Elsevier. (B) Difference in femoral neck Z between low active boys (circles; 10 min/day moderate to vigorous physical activity, MVPA) and high active boys (squares; 40 min/day MVPA) at age 5, 8 and 11 years in the Iowa Bone Development Study [50]. Figure courtesy of Kathy Janz.
The relationship between physical activity and bone strength has also been demonstrated in prepubertal children [45]. The Iowa Bone Development Study followed 468 children across six years (ages ranged from 4 to 12 years). On average, boys who participated in 40 minutes/day of MVPA had 4% greater FN CSA (by HSA) and 5% greater FN Z than boys who participated in only 10 minutes of MVPA. The influence of MVPA on bone geometry strengthened as the boys aged (Figure 11.3B). This result further supports the notion of a ‘window of opportunity’ in boys just prior to adolescence, when the skeleton readily adapts to physical activity [50]. Although fewer studies have been undertaken in adolescent boys, it is most likely that weight-bearing activity continues to promote positive skeletal adaptations. As a follow up to their cross-sectional athlete studies, Gustavsson et al [51] showed that, in boys aged 16–19 years, being a badminton or hockey player was an independent and positive predictor of 3-year change in non-dominant humerus aBMD and FN aBMD. Unfortunately, baseline differences in aBMD between athletes and controls were not controlled in the analysis of change in aBMD. Thus, well-designed prospective studies provide valuable evidence that regular physical activity enhances bone mass and strength at the clinically relevant femoral neck. However, as imaging technology advances, it is important to look beyond the limitations of two-dimensional DXA technology and evaluate three-dimensional measures of bone geometry, microarchitecture and strength.
What have we learned from exercise intervention studies? Several well-designed randomized controlled trials (RCTs) provide the highest level of evidence to support the osteogenic effects of weight-bearing physical activity on the growing skeleton. Children assigned to physical activity
intervention groups gained significantly more bone mass and enhanced their bone strength compared with children in control groups [13, 17]. However, only two of these studies in boys used technologies other than DXA to evaluate the bone structure and strength response to physical activity. Further, it is often not possible to compare results across intervention studies (summarized in Table 11.1) as exercise protocol, study design and maturational status of the participants varies considerably. Of the DXA-based studies, gains in bone mass (BMC or aBMD) in intervention boys compared with control boys ranged from 1 to 6% depending on the anatomical site measured, the length of the trial and the intensity of the intervention. The longest randomized controlled intervention trial conducted in boys was 20 months [52]. A high-impact circuit training program enhanced BMC at the weight-bearing FN by nearly 5% more in exercising boys than in controls (Figure 11.4) [52]. As a positive response at the FN was not significant after only 7 months of participation in the Healthy Bones Study, the site-specific adaptation may have be related to boys’ advanced stage of maturity and/or the intensity and duration of the intervention [53]. Further support for the site-specific nature of the response in prepubertal boys is evidenced by the lack of a response at the femoral neck in an 8-month study of prepubertal Australian boys [54] and, more recently, in the 16-month Action Schools! BC (AS! BC) study in which the majority (60%) of boys were prepubertal [55]. In contrast, an earlier study of younger boys (and girls, aged 6–10 years) reported significantly greater increases (4.5%) in FN BMC in exercising children than in controls [56]. The very high-impact jumping program was associated with ground reaction forces nine times body weight (BW) – compared with forces 2–5 BW across other studies. Thus, more intense exercise interventions may be the key to achieving positive adaptations at the clinically relevant femoral neck during prepuberty.
Table 11.1 Intervention studies of the effects of weight-bearing physical activity on bone mass and strength in boys Reference
Subjects and study design
Intervention
Statistical approach
Results (INT vs. CON)
DXA only Unpaired t-tests: 8-month change in bone Program: activities included aerobics, football, dance, gymnastics, volleyball, basketball, weight parameters (INT vs CON). training in addition to regular school physical education Frequency and duration: 30 minutes, 3 times/ week, 8 months Progression: none stated
Femoral midshaft: BMC: 5.6% (P 0.01) vBMD: NS Peri diam: NS Endo diam: 11% (P 0.01) C.Th: 6.4% (P 0.05) CSMI: NS TB aBMD: 1.2% (P 0.01) LS aBMD: 2.8% (P 0.01)
Sundberg et al [57]
Subjects: Caucasian. INT: n 40 (12–13 years at baseline, mixed maturity) CON: n 82 (12–13 years at baseline, mixed maturity) Randomization: no randomization reported Study compliance: 93%
Program: increased time spent in regular physical education. Activities included running, jumping, gymnastics and/or ball activities. One class per week was swimming Frequency and duration: 40 minutes/week, 4 times/week, 36–48 months Progression: progressed from 100 minutes/week to 160 minutes/week (4 40 minutes)
TB BMC: NS LS BMC: 9% (P 0.05) FN BMC: 8% (P 0.05) Distal radius BMC: NS TB aBMD: NS LS aBMD: NS FN aBMD: 9% (P 0.01) Distal radius aBMD: NS
ANCOVA: 36–48 month change on bone outcomes between groups (INT vs CON). Covariates were weight, height, milk intake, physical activity, smoking, socioeconomic factors and housing. The authors did not control for maturity status
DXA: Lunar DPX-L (GE Medical) MacKelvie et al [53]
FN vBMD: 9% (P 0.01) ANCOVA: 7 month change in bone outcomes TB BMC: 1.6% Subjects: 44% Asian and 56% Caucasian Program: school-based, high-impact jumping (P 0.01) program integrated in school physical education between groups (INT vs CON). Covariates classes. Ground reaction forces 3.5–5 times body were baseline weight, change in height, LS BMC: NS physical activity and age weight
l
Subjects: Caucasian INT: n 19 (10.4 years at baseline, all prepubertal) CON: n 19 (age, height and baseline aBMD matched to INT group) Randomization: 2 schools randomly allocated to INT or CON Study compliance: 96% DXA: Lunar DPX-L (GE Medical)
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Bradney et al [54]
(Continued) 137
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Table 11.1 Continued Reference
Intervention
Statistical approach
INT: n 61 (10.2 years at baseline, all prepubertal) CON: n 60 (10.3 years at baseline, all prepubertal; age, height and baseline aBMD matched to INT group) Randomization: randomized by school (stratified by number of subjects and ethnicity) Study compliance: 80% DXA: Hologic QDR 4500 W
Frequency and duration: 10–12 minutes, 3 times/ week, 7 months Progression: # of jumps and height of jump advanced every 8–10 weeks; 50 (baseline) to 100 (final) jumps
Results (INT vs. CON) PF BMC: NS FN BMC: NS TR BMC: NS LS aBMD: NS PF aBMD: 1% (P 0.05) FN aBMD: NS TR aBMD: NS FN vBMD: NS
Linden et al Subjects: Caucasian [58] INT: n 76 (7.8 years at baseline, all prepubertal) CON: n 51 (8.0 years at baseline, all prepubertal; sex and age-matched to INT group) Randomization: no randomization Study compliance: not reported DXA: Lunar DPX-L (GE Medical)
Program: increased curricular time for physical education; indoor and outdoor activities, including ball games, running, jumping and climbing Frequency and duration: 40 minutes, 5 times/ week, 12 months Progression: none stated
Student t-tests: 12-month change in bone parameters between groups (INT vs CON)
TB BMC: NS LS3 BMC: 5.9% (P 0.001) FN BMC: NS TB aBMD: NS LS3 aBMD: 2.1% (P 0.05) FN aBMD: NS FN vBMD: NS LS3 width: 2.3% (P 0.05) FN width: NS
Hasselstrom Subjects: Caucasian et al [59] INT: n 135 (6.8 years at baseline, all prepubertal) CON: n 62 (6.8 years at baseline, all prepubertal) Randomization: no randomization reported Study compliance: not reported DXA: Lunar Pixi (GE Medical)
Program: increased curricular time for physical education Frequency and duration: 90 minutes, 2 times/ week, 3 years Progression: none stated
ANCOVA: 3-year change in bone outcomes between groups (INT vs CON). Covariates were baseline height, weight, bone mass and change in height Bonferroni corrections were applied
Distal forearm BMC: NS Calcaneus BMC: NS Distal forearm aBMD: NS Calcaneus aBMD: NS
ANCOVA: 20-month change in bone outcomes between groups (INT vs CON). Covariates were baseline bone, change in height and final Tanner stage
TB BMC: NS LS BMC: NS PF BMC: NS FN BMC: 4.3% (P 0.01)
DXA and HSA MacKelvie et al [52]
Subjects: Caucasian (42%), Asian (44%), other (14%) INT: n 31 (10.2 years at baseline, all prepubertal)
Program: school-based, high-impact jumping program integrated in school physical education classes. Ground reaction forces 3.5–5 times body weight Frequency and duration: 10–12 minutes, 3 times/ week, 2 school years (20 months)
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Subjects and study design
Table 11.1 Continued Reference
CON: n 33 (10.1 years at baseline, all prepubertal) Randomization: randomized by school (stratified by number of subjects and ethnicity) Study compliance: 61% DXA: Hologic QDR 4500 W
Progression: # of jumps and height of jump advanced every 8–10 weeks Yr 1: 50 (baseline) to 100 (final) jumps Yr 2: 55 (baseline) to 132 (final) jumps
Alwis et al [60]
Subjects: Caucasian INT: n 76 (7.8 years at baseline, all prepubertal) CON: n 51 (8.0 years at baseline, all prepubertal) Randomization: no randomization reported Study compliance: 95% DXA: Lunar DPX-L (GE Medical)
Program: increased curricular time for physical education; indoor and outdoor activities, including ball games, running, jumping and climbing Frequency and duration: 40 minutes, 5 times/ week, 24 months Progression: none stated
Macdonald et al [55]
Subjects: Caucasian (35%), Asian (53%) Program: Action Schools! BC program and mixed (12%) (Classroom Action) and Bounce at the Bell; 5–12 countermovement or side-to-side jumps/session INT: n 151 (10.2 years at baseline, performed in the classroom. Ground reaction mixed maturity) force 3.5–5 times body weight Frequency and duration: Classroom Action, 15 CON: n 62 (10.3 years at baseline, minutes, 5 times/week, 16 months; Bounce at the mixed maturity) Bell, 3 minutes, 3 times/day, 4 times/week, 16 Randomization: randomized by school months (stratified by school size) Progression: # of jumps increased every month up to a maximum of 36 jumps/day Study compliance: 74% (with Bounce at the Bell) DXA: Hologic QDR 4500 W
Statistical approach
Results (INT vs. CON) TR BMC: NS NN CSA: 2.5%, NS NN SPW: 2.6%, NS NN CSMI: 12.4% (P 0.05) NN Z: 7.5% (P 0.05) NN Endo diam: 2.9%, NS NN C.Th: NS
Student t-tests: 2-year change in bone outcomes between groups (INT vs CON)
TB BMC: NS LS3 BMC: 6% (P 0.01) FN BMC: NS LS3 width: 2.6% (P 0.01) FN width: NS FN CSA: NS FN Z: NS FN CSMI: NS
Intent-to-treat approach Linear regression model with change in bone outcome as dependent variable and group (INT vs CON) as independent variable. Covariates were baseline weight, change in height and change in TB lean mass. Random effect of school accounted for with variance inflation factor
TB BMC: 1.7% (P 0.05) LS BMC: 2.7% (P 0.05) PF BMC: NS FN BMC: NS FN CSA: NS FN SPW: NS FN Z: NS
(Continued)
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Subjects and study design
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Reference
Subjects and study design
Intervention
Statistical approach
Results (INT vs. CON)
Linear mixed-effects model to compare change in bone outcomes between groups (INT vs CON) and account for random effect of school Analysis 1: Group x maturity interaction term included in mixed-effects model along with baseline bone value, change in tibial length and change in muscle CSA as covariates Analysis 2: Group x maturity interaction not included in mixed-effects model. Covariates were baseline bone value, baseline body weight, change in tibial length, maturity offset (Mirwald equation)
Analysis 1 [61] P-value for group * maturity interaction Distal tibia ToA: NS ToD: 2.3% (P 0.07) BSI: 5% (P 0.03) (prepubertal boys only) Midshaft tibia CoA: NS CoD: NS SSIp: 2.3%, NS (prepubertal boys) Analysis 2 [62] Imax: 3% (P 0.05) Imin: 2%, NS CoA & C.Th by quadrant: 1–1.4%, NS
pQCT Macdonald Subjects: Caucasian (35%), Asian (53%) et al [61, 62] and mixed (12%) INT: n 145 (10.2 years at baseline, mixed maturity) CON: n 64 (10.3 yreas at baseline, mixed maturity) Randomized by school (stratified by school size) Compliance: 74% (with Bounce at the Bell) pQCT: Stratec XCT2000 with ImageJ and MomentMacro analysis
Program: Action Schools! BC program (Classroom Action) and Bounce at the Bell; 5–12 countermovement or side-to-side jumps/session performed in the classroom. Ground reaction force 3.5–5 times body weight Frequency and duration: Classroom Action, 15 minutes, 5 times/week, 16 months; Bounce at the Bell, 3 minutes, 3 times/day, 4 times/week, 16 months Progression: # of jumps increased every month up to a maximum of 36 jumps/day
INT: Intervention; CON: Control; DXA: dual energy x-ray absorptiometry; BMC: bone mineral content; vBMD: volumetric bone mineral density; NS: not significant; Peri diam: periosteal diameter; Endo diam: endosteal diameter; C.Th: cortical thickness; CSMI: cross-sectional moment of inertia; TB: total body; aBMD: areal bone mineral density; LS: lumbar spine; ANCOVA: analysis of covariance; HAS: hip structural analysis; PF: proximal femur; FN: femoral neck; TR: trochanter; LS3: third lumbar vertebra; NN: narrow neck; CSA: cross-sectional area; SPW: sub-periosteal width; Z: section modulus; pQCT: peripheral quantitative computed tomography; ToA: total bone cross-sectional area; ToD: total bone density; BSI: bone strength index; CoA: cortical bone area; CoD: cortical bone density; SSIp: polar strength strain index; Imax: maximum second moment of area; Imin: minimum second moment of area.
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Table 11.1 Continued
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% Change FN BMC
l
20 +4.4% p < 0.01
15 10 5 0 0
5
10 Months
15
20
Figure 11.4 Percent (%) change in femoral neck bone mineral content (FN BMC) over 20 months for intervention (squares) and control (circles) boys in the Healthy Bones Study [52, 53]. After 20-months, intervention boys gained 4.4% more FN BMC than control boys.
There are a number of fundamental considerations when designing intervention trials for children. First, programs must reflect what is known about bone’s response to specific types of loading. Thus, all interventions were comprised of high-impact activities designed to impose a ‘physiologic load’ [7] on the weight-bearing skeleton. The HBS and AS! BC interventions were also based in part on Turner’s three rules [24] discussed previously and on results from animal studies that suggested short bouts of dynamic activity followed by rest periods were more effective than longer bouts of activity [19]. Second, to influence large numbers of children and to be sustained, it is important that interventions be simple so as to be delivered by trained or untrained people (often generalist teachers) within the school or community setting. The Bounce at the Bell component of AS! BC provides one example as the jumps took only a few minutes, could easily be incorporated into the daily classroom routine, did not require additional equipment or space and were associated with low teacher burden. An alternative approach within the school setting was to increase the time devoted to physical education [57–59]. The Malmo Pediatric Osteoporosis Prevention Study (POP) compared four schools where, in the one intervention school, the weekly duration of physical education was increased from 80 min/week to 200 min/week (a 40 min/day increase) [58, 60]. Children were provided an otherwise unaltered physical education curriculum and, after 2 years, prepubertal boys in the intervention school demonstrated a 6% greater gain in BMC of the third lumbar vertebra and a 2.6% greater gain in vertebra width compared with control boys. Interestingly, as in most other studies of boys who were prepubertal, the POP program did not positively affect the load-bearing femoral neck. The Copenhagen School Child Interventions Study [59] used a similar design but did not elicit a benefit as a result of increased duration of standard physical education at any skeletal site. Given the results from these trials (and others [57]) and the demands placed on teachers and schools to adapt and deliver a modified school curriculum, these studies may not be justified, feasible or sustainable in many countries.
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Together, the aforementioned studies provide convincing evidence that physical activity can positively influence the normal trajectory of bone mass accrual in young boys, although the bone response appears to be both site- and maturity-specific. Importantly, we must advance beyond DXA technology if we are better to understand changes in bone geometry or structure that underpin growing bone’s response to weight-bearing exercise. To date, only three of the studies we discussed quantified adaptations in bone geometry, volumetric BMD or bone strength [52, 54, 55, 61]. Of these, only the HBS and AS! BC trials reported significant intervention effects for HSA-derived estimates of femoral neck geometry [52] or pQCT measures of tibial bone geometry, vBMD and strength [61, 62]. In addition to the intervention-related gain in FN BMC, boys who participated in the HBS demonstrated a significantly greater increase in FN cross-sectional area after 20 months compared with boys in control schools. This apparent increase in periosteal apposition was associated with a greater gain in FN section modulus, an indicator of bone bending strength. Although exercise-related periosteal apposition is thought to occur during prepuberty, when bones undergo rapid expansion due to normal growth [10, 63], the HBS results further support the hypothesis that structural adaptations at the femoral neck may occur primarily during early puberty. Thus, a longer intervention or follow-up period that traverses early puberty may yield more significant changes in boys’ bone structure and strength at this clinically relevant site. Hip structure analysis supplements standard DXA measures of bone mass. However, estimating three-dimensional properties from two-dimensional images has known limitations and HSA results must be interpreted with these in mind. In contrast, pQCT technology is able to capture accurately adaptations in bone cross-sectional geometry with exercise. However, it is unable to evaluate the clinically relevant femoral neck, thus, weight-bearing intervention studies that used this technology focused on assessing the tibia. AS! BC used pQCT technology and was the first RCT to demonstrate that short bouts of classroom-based activity significantly impacted bone strength. At the distal tibia (8% site), the greater gain in bone strength index (BSI) in prepubertal intervention boys compared with maturity-matched controls was mainly due to greater gains in vBMD, as opposed to an increase in cross-sectional area [61]. This finding is consistent with resistance to the primarily compressive loads at this site being a function, in large part, of trabecular density [32]. In contrast, the trend for a greater increase in polar SSI in prepubertal boys at the tibial midshaft was more likely due to increased periosteal apposition. We further explored this finding using a novel analysis for pQCT scans that allowed us to evaluate the biomechanically relevant second moments of area, Imax and Imin. These indices of bone bending strength provided an estimate of how bone was distributed about the anterior-posterior and
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A
B
CAmin
C
CAmax
Anterior D
Intervention Control
1.2 mm 0.8 mm 0.4 mm Lateral
Medial
Posterior
Figure 11.5 (A) Representative baseline (top) and (B) follow-up (bottom) pQCT images of an intervention group boy’s left tibia with the principal centroidal axes (CAmax, CAmin) superimposed. (C) Superimposition of the baseline (solid) and follow-up (dashed) bone surfaces. Alignment based upon minimization of pixel gray scale differences. (D) Radial plot of bone surface changes (follow-up-baseline) for the periosteal (outer lines) and endosteal (inner lines) surfaces for intervention (solid line) and control (dashed line) boys. Lines smoothed by a three-point running average. The apparent trend for greater periosteal apposition on the anterior and posterior surfaces lead to a significantly greater gain in Imax in intervention boys compared with controls. Adapted from Macdonald et al [62] with permission from Springer.
medial-lateral axes, respectively. The trend for greater gains in torsional bone strength (SSIp) in intervention boys was associated with an approximately 3% greater gain in Imax. Patterns of bone formation also reflected the predominantly anterior-posterior bending loads at the tibial shaft [64]. That is, changes in cortical area and thickness in the anterior, medial and posterior quadrants of the bone cross-section tended to be greater in intervention boys (Figure 11.5). These region-specific adaptations were consistent with those reported in animal studies [19] and highlight how three-dimensional imaging techniques advance our understanding of bone structural adaptations to physical activity beyond what we have learned from DXA studies.
Do the benefits of physical activity persist? Taken together, observational and intervention studies provide strong support for the positive influence of physical activity on skeletal development in boys during childhood and adolescence. However, there are no (and may never be) long-term prospective trials with fracture as the outcome that demonstrate a definitive link between childhood and adolescent bone mass and strength and decreased fracture risk. That said, we present a number of ‘detraining’, epidemiological and retrospective studies that lend credence to the notion that
skeletal adaptations to loading are maintained over the longer term and that there is indeed a relationship between childhood physical activity and reduced fracture risk in older age. Detraining or deconditioning studies aim to determine if gains in bone mass and/or strength are maintained following withdrawal of the exercise stimulus. The elegant animal studies undertaken by Warden and colleagues [65] provide a benchmark that human studies can aspire to. Using pQCT, they found that exercise-related gains in bone structure and strength in growing rats following a 7-week intervention period were still evident after 92 weeks of non-training follow up. In turn, the exercised ulna’s structural advantage increased its resistance to fracture. As alluded to previously, a similar lifelong follow-up study in humans that addresses the question of whether exercise-induced bone adaptations in childhood result in reduced fracture risk may not be feasible. However, the longest human detraining study to date found that gains in proximal femur BMC evident after 7 months of a high-impact jumping program were maintained in boys 8 years later [66]. The differences between exercise and control groups were, however, of a smaller magnitude (Figure 11.6). This study spanned pubertal growth and a powerful multilevel modeling approach, similar to that used in earlier longitudinal studies [49], controlled for the repeated measures within individuals and individual growth trajectories. Other observational studies investigated the relationship between reduced training or cessation of training and
C h a p t e r 1 1 Physical Activity and Skeletal Growth l
4
*
% D Total HIP BMC over controls
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2.5
*
2
*
*
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*
1 0.5
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7
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Figure 11.6 Different in percent (%) change in total hip bone mineral content (BMC) between jumpers and controls after 7 months of exercise training, one year of detraining (19 months) and 4 through 8 years of detraining (43–91 months). The intervention participants (boys and girls) had 3.6% greater BMC than controls at the end of the intervention and 1.4% greater total hip BMC than controls after 8 years. *Results are adjusted for baseline age, height change, weight change, maturity and sports participation and results are significant at each of the seven measurement intervals (P 0.05). From Gunter et al [66] with permission from the American Society for Bone and Mineral Research.
changes in bone outcomes in young adult athletes who began their sport training during childhood. In Swedish male hockey players (aged 17 years at baseline), physical activity-related gains at the FN and humerus (dominant and non-dominant aBMD) diminished 3 years after cessation of hockey training [67, 68]. In contrast, boys who continued ice hockey training over the same 3 years, gained significantly more aBMD at the FN, PF and arms than non-playing controls [68]. Conversely, it has been consistently demonstrated that athletes who retire from their sport sustain a greater bone mass than non-athlete controls [68–70]. Only one retrospective study linked the bone mass or strength advantage from a sport career during childhood and adolescence to reduced fracture risk later in life [69]. The field has not yet undertaken enough well designed intervention studies to determine whether gains in bone geometry or strength in the appendicular skeleton are maintained with age. However, in a recent pQCT study, young men’s (mean age 19 years) previous participation in sport was associated with a larger cortical bone area and periosteal circumference at the tibial diaphysis and with increased trabecular vBMD at the metaphysis [71]. Further, cortical bone geometry was significantly enhanced in men who had ceased their training up to 6.5 years earlier compared with men who were never active. Although the authors did not report tibial bone strength, the greater cortical area in the previously active men would increase resistance to bending or torsional forces due to the exponential relationship between bone diameter and bone strength [11]. These athlete studies suggest involvement in competitive sport during childhood is linked with bone strength benefits later in life. Similarly, bone gains from leisure-time physical activity during adolescence are maintained into young adulthood [72]. The University of Saskatchewan bone mineral
accrual study was the first to follow children prospectively into young adulthood [72]. During adolescence (1 year post PHV), active boys (by self-report questionnaire) had 8–13% greater BMC at the total body, lumbar spine and proximal femur than inactive boys. In young adulthood, the bone benefit was maintained in the active group (total body, proximal femur and femoral neck BMC were 8–10% greater than inactive group). The moderate, but significant correlation between adolescent and adult physical activity scores lends support to the notion that physical activity tracks (at least moderately) from childhood to adulthood [73, 74]. Finally, continued participation in weight-bearing activities throughout adolescence and into adulthood also confers a bone strength advantage. A recent cross-sectional study of older men used Turner and Robling’s osteogenic index (OI) [25] to categorize adolescent, mid-adulthood and lifetime exposure to weight-bearing activity [75]. A greater lifetime (13–50 years) and mid-adulthood (19–50 years) OI were positive predictors of mid-femur total and cortical area, cortical BMC and polar moment of inertia (by QCT). Further, men who continued consistently to participate in weight-bearing physical activities through adolescence and into adulthood had 6–15% greater indices of bone structure and strength compared with men who did not. Together, these results highlight the importance of adopting and sustaining an active lifestyle through the growing years and into later adult life.
Summary and conclusion In summary, effective weight-bearing physical activity can be attained through a wide range of extra-curricular sports and activities and through targeted school-based programs. It is more difficult to pinpoint the ‘window of opportunity’
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when the growing skeleton is most responsive to exerciseinduced loads. Although pre- and early puberty may well be the most opportune times to maximize the positive impact of physical activity on the growing skeleton, the timing may vary by site. For example, boys’ bone strength was enhanced through exercise at the clinically relevant femoral neck (through periosteal apposition) during early puberty, whereas structural adaptations at the tibia were evident in prepuberty. While we did not address sex differences in bone’s adaptation to physical activity, the timing of the ‘window’ likely varies between boys and girls. This may be due in part to the known sex differences in the timing of the pubertal growth spurt. Further study in well-defined maturity groups would serve to elucidate the precise time during growth when exercise has its most potent effect on bone strength accrual in boys and girls. We also do not know the optimal exercise prescription to enhance bone strength accrual in boys (and girls). In schools, short bouts of high-impact activity separated by rest periods may offer an effective, feasible and sustainable model to promote children’s bone health. However, there remains a need for rigorous randomized controlled intervention trials that control for potential confounds (sex, race, maturity and anthropometry) and where the influence of mediating factors such as nutrition and hormones are considered. Exciting new advances in imaging technology that include (p)QCT, HR-pQCT and MRI allow us to drill a little deeper into bone’s hierarchical nature to enhance our understanding of how bone structure and microarchitecture adapt to physical activity in both sexes. Although the answers to these questions are fascinating to scientists, they should not distract from the clear public implications of engaging boys and girls in physical activity. That is, children should be encouraged to adopt an active lifestyle (regardless of the timing, the site or the nature of the bone response), given the known benefits of physical activity across a range of body systems.
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Chapter
12
The Genetics of Peak Bone Mass Luigi Gennari1, Robert Klein2 and Serge Ferrari3 1
Deparment of Internal Medicine Endocrine Metabolic Sciences and Biochemistry, University of Siena, Italy Bone and Mineral Unit, Oregon Health & Science University and Portland VA Medical Center, Portland, Oregon, USA 3 Service of Bone Diseases, Department of Rehabilitation and Geriatrics, WHO Collaborating Center for Osteoporosis Prevention, Geneva University Hospital, Geneva, Switzerland 2
Introduction
history of fracture has been consistently associated with fracture risk, much less information exists about the heritability of fracture, with reported estimates of 25–35% or less, depending on the skeletal site and population studied [1].
Heritable Influences on the Osteoporosis Phenotype Genetic factors play a key role in the pathogenesis of skeletal fragility and osteoporosis in both genders. Several studies using twin pairs or parent–offspring models have shown high levels of heritability of bone mineral density (BMD), the most commonly used skeletal trait to evaluate the genetic basis of bone strength and, ultimately, osteoporotic fractures. In particular, twin studies have provided an efficient tool for detecting the influence of genetic factors on quantitative traits, including BMD. This model involves a comparison of intrapair differences between monozygtic and dizygotic twins. Since monozygotic twins are genetically identical, their intrapair differences in any given trait are assumed to arise exclusively from environmental factors. Conversely, intrapair differences in dizygotic twins can arise because of both genetic and environmental differences. If a significantly larger variation of intrapair differences can be demonstrated in dizygotic than monozygotic twins, it may be inferred that genetic factors exert a consistent contribution to the observed variation. By this approach, it has been estimated that 50% and 80% of the variance in BMD is genetically determined [1]. Other twin studies have shown similarly high degrees of heritability for other skeletal (i.e. quantitative ultrasound properties of bone, femoral neck geometry, bone loss and bone turnover markers) or extraskeletal (i.e. body mass index, muscle strength) determinants of osteoporotic fracture risk [1, 2]. Some concerns have been raised that the classic twin model overestimates heritability because of shared environmental covariates. This hypothesis is also supported by most of the family studies generally showing lower heritability estimates for BMD than twin studies. Moreover, even though a family Osteoporosis in Men
Heritability of Peak Bone Mass Theoretically, inheritance could affect bone strength and fracture risk in at least two ways. Genetic factors could influence skeletal growth and the amount of bone mass attained in early adulthood (peak bone mass) and subjects with genetically determined low bone mass might be more susceptible to develop osteoporosis with subsequent aging. Alternatively, or in conjunction with the above, genetic factors could influence the rate of age-related bone loss. To date, twin and family studies have shown a predominant genetic effect on peak bone mineral mass acquisition rather than on age-related bone loss. In fact, both male and female offspring of subjects with osteoporosis have reduced bone mass well before age-related or postmenopausal bone loss [3, 4], suggesting the expression of inherited determinants of osteoporotic risk from an early age. Moreover, a threegeneration study in males demonstrated that sons of men with osteoporosis have reduced bone size and reduced volumetric BMD, despite normal markers of bone remodeling, further reinforcing the view that the effect of genetics on bone is mainly growth-related rather than age-related [5]. Consistent with this postulate, a study on male twins of different ages revealed that intrapair differences in radial bone mass and width were highest in young subjects but increased with age both in monozygotic and dizygotic pairs [6] (Figure 12.1). Conventional heritability estimates suggested a low degree of genetic determination of bone mass in the adult twins. Thus, the genetic component appears primarily to affect peak bone mass, while its role progressively declines 149
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Intrapair variance in bone mass
0.02 P < 0.025 0.015
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Figure 12.1 Intrapair variance in bone mass between monozygotic (MZ) and dizygotic (DZ) pairs in juvenile and adult twins. (Adapted from Smith et al J Clin Invest 1973;52:2800–8).
with aging as a result of the accumulation of non-inherited (environmental) factors. Indeed, in a longitudinal study on premenopausal women and their prepubertal daughters, a familial resemblance in several different bone traits (areal and volumetric BMD, bone mineral content, bone area) was already present before puberty and remained unchanged during pubertal growth, indicating that genetic susceptibility to osteoporosis may already be detectable in early childhood [7]. Even though similar studies have not been performed in men, these results might also be applicable to the male, since before puberty, there is no consistent gender-related difference in bone mass or size. A separate, cross-sectional study in premenopausal women and their prepubertal male and female children confirmed a significant heritability of BMD in both genders before puberty [8]. In this study, heritability was generally higher for mother–daughter pairs (57% and 79% for lumbar and femoral BMD, respectively) than for mother–son pairs (24% and 51% for lumbar and femoral BMD, respectively). There was also some evidence of site specificity with poorer correlation coefficients if skeletal sites other than the corresponding maternal anatomical site were used for prediction. Taken together, these data indicate genetic factors play a major role in determining inherent bone structural characteristics and skeletal size. Most of these heritable effects appear to be programmed before attainment of peak bone mass or, for that matter, even before puberty. Importantly, these studies also suggest that the best population to investigate the genetic component of osteoporosis may not be older subjects but rather younger subjects with low bone mass.
Gender-Specific Heritability of Bone Mass Sexual dimorphism in the structural components of bone strength (i.e. skeletal dimensions, cortical thickness and
trabecular microstructure) is marked in both skeletal development and aging [9]. This has raised the hypothesis of different genetic effects on the male or female skeleton or, more likely, of gender-specific interactions modulating the expression or penetrance of common genetic factors (i.e. due to different exposure to gonadal steroids, differences in muscle strength, exercise or other risk factors for bone fragility) [10]. Several studies identified significant differences in the heritability between the sexes, including genotype-by-sex and environment-by-sex interactions on BMD. For example, in a study of dizygotic twins, the correlations between BMD of the opposite-sex twin pairs were lower than those of same-sex twin pairs [11], suggesting such differences arise at least in part from genetic imprinting and different environments in males and females. Moreover, genderrelated differences in the percentage of variance explained by additive genetic effects suggest that, at least in part, different genes may regulate bone mass in men as compared to women [10].
Identification of Osteoporosis Susceptibility Genes Segregation analysis in families has shown regulation of BMD and other osteoporosis-related phenotypes is polygenic and determined by the effects of several genes, each with relatively small effects rather than by a small number of genes with large effects [1]. Some genes with relatively larger effects may be also involved in at least some populations and particularly in men [12, 13], even though substantial residual polygenic effects were also in evidence in most of these studies. Irrespective of the contribution made by individual genetic variants, it is clear that osteoporosis is a complex, multifactorial disorder in which genetic determinants regulating bone remodeling, BMD, bone geometry and susceptibility to fracture are modulated by hormonal, environmental and nutritional factors. The genetic control of bone strength may also vary across skeletal sites, period of life (with different genes regulating bone growth and bone loss), gender and ethnicity [10, 14]. Moreover, the possibility that a significant part of the heritability of bone mass is related to shared genetic contributions to skeletal size and body composition cannot be excluded. Over the last 20 years, researchers seeking to find genes that influence osteoporosis and fracture risk have taken separate but complementary approaches: family studies of rare monogenic skeletal fragility disorders, linkage analysis in pedigrees, association studies in population samples and experimental crosses in animal models. In most of the studies, BMD (with the 2.5 SD diagnostic threshold for osteoporosis) was studied as a major surrogate phenotype, because it is highly heritable and represents an important and measurable clinical predictor of fracture risk. Most human studies have been performed in postmenopausal women or in mixed male and female population-based samples, while
C h a p t e r 1 2 The Genetics of Peak Bone Mass l
few studies were specifically designed to investigate the genetic determinants of peak bone mass in men.
Linkage studies Classic, parametric linkage analysis has been particularly successful in identifying the genes that are responsible for rare, monogenic disorders such as osteogenesis imperfecta and sclerosing bone dysplasias. In these studies, a genomewide set of a few hundred or a few thousand markers spaced millions of bases apart was typed in families with multiple affected or unaffected relatives. Genotype data were then analyzed to look for evidence of segregation of alleles with the phenotype according to the specified disease model (i.e. dominant or recessive). A slightly different approach (nonparametric linkage analysis) has been generally used for complex disorders, where no disease model is specified and the evidence of allele sharing in relation to sharing of the disease phenotype (i.e. low BMD) is investigated. Results are typically expressed as lod scores (LOD) that are defined as the logarithm of the odds that the disease locus and marker locus are linked. In parametric analysis, linkage is considered to be ‘suggestive’ when the LOD is greater than 1.9 and ‘significant’ when the LOD is greater than 3.3. For non-parametric analysis, higher thresholds are used and a suggestive or significant linkage is defined by a LOD greater than 2.2 and 3.6, respectively [1]. Overall, linkage studies have the advantage of being an unbiased, comprehensive search across the genome for susceptibility alleles and has been successfully applied to find the genes for many single gene disorders. However, linkage analysis has been less successful for polygenic diseases and quantitative traits, perhaps in part because of a limited power to detect the effect of common alleles with modest effects on disease.
Rare Monogenic Disorders Associated With Low Bone Mass In rare instances, low bone mass and multiple fractures in young males are found to be inherited in a simple Mendelian manner. Examples of this include osteogenesis imperfecta and other familial osteoporotic syndromes due to inactivating mutations in the aromatase (CYP19A1), estrogen receptor alfa (ESR1), lipoprotein receptor-related protein 5 (LRP5) and 6 (LRP6) genes. Mutations affecting the collagen type 1, 1 (COL1A1) or 2 (COL1A2) genes were the first to be associated with bone fragility and increased fracture risk in humans. These mutations are in fact responsible for the vast majority of cases of osteogenesis imperfecta, a hereditary disorder of connective tissue [15]. A heterogeneous nature of this disorder has been described, spanning from extremely severe, early onset and often lethal conditions to milder forms.
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The presence of osteoporosis was also described in a single case of a disruptive mutation in the ESR1 gene in a 28-year-old man with unfused epiphyses and continued linear growth [16]. The gene defect was inherited as an autosomal recessive from his consanguineous parents who were heterozygotes for the mutation. A cytosine to thymidine transition at exon 2, codon 157 resulted in a stop codon and a severely truncated alpha estrogen receptor that cannot bind estrogen. He had no detectable response to administration of large doses of exogenous estrogen despite achieving serum concentrations of estradiol 10-fold higher than the typical male. A similar skeletal phenotype has been observed in nine different cases of inactivating mutations at the aromatase CYP19A1 gene in young males [17]. The disorder occurs in an autosomal recessive pattern and, in at least six of the nine described subjects, parental consanguinity was evident. All known mutations exhibit no or minimal enzyme activity in transient expression systems. Accordingly, circulating estrogen levels are markedly low or undetectable while androgens are normal or elevated. Common skeletal characteristics of these men include tall stature, continued longitudinal growth, unfused epiphyses, delayed bone age, lack of pubertal growth spurt, eunuchoid skeletal proportions, genu valgum, elevated bone resorption markers and reduced bone mass. Estrogen treatment in all these cases of aromatase deficiency was associated with an increase in BMD and epiphyseal closure. Taken together these rare cases of mutations in ESR1 and CYP19A1 genes emphasized the dominant effect of estrogen in the attainment of peak bone mass. Major disruption of the LRP5 gene due to homozygous nonsense or frame-shift mutations, resulting in loss-offunction, is responsible for the osteoporosis pseudoglioma syndrome (OPPG), a rare disorder characterized by juvenile onset osteoporosis and blindness [18]. LRP5 encodes for a transmembrane co-receptor that is involved in the Wnt signaling pathway, a major regulator of osteoblast proliferation and activity. To date, more than 50 cases of OPPG have been reported, most with onset of fractures after age 2 years. Heterozygous carriers of LRP5 mutations have also been shown to have reduced BMD and osteoporotic fractures, without eye pathology. Moreover, LRP5 mutations have been reported in some cases of idiopathic juvenile osteoporosis [19, 20]. In one of these studies, functional in vitro analyses clearly showed an inhibitory effect of mutations on Wnt signal transduction [20]. A recent report identified an inherited mutation in lipoprotein receptor-related protein 6 (LRP6) linked to coronary heart disease as well as low BMD and fragility fractures [21]. Conversely, a number of dominantly inherited gain-offunction mutations in the LRP5 gene result in high bone mass (HBM) phenotypes [22] and autosomal dominant osteopetrosis type 1 [23]. Other syndromes have been described in which affected individuals have high bone mass and are protected against osteoporotic fractures.
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Examples are the recessive syndromes of sclerosteosis and Van Buchem disease that are caused by inactivating mutations in the sclerostin (SOST) gene [24, 25]. Interestingly, individuals who are heterozygous for disease-causing mutations in SOST also have high bone mass [26]. Even though such cases of single gene mutations in men with low or high bone mass represent extreme conditions, they indicate the possibility that more subtle functional differences in those genes (i.e. due to less functional polymorphisms) could predispose some men to osteoporosis.
Linkage Studies on Osteoporosis in Men To date, several linkage studies (some covering the entire genome, others just focusing on smaller intervals) have been conducted in a variety of populations. A number of chromosome regions have demonstrated at least suggestive evidence for linkage, but only a few regions have shown significant evidence for linkage and been replicated in multiple studies [1, 2]. Moreover, a recent collaborative metaanalysis including nine major genome-wide linkage studies and involving 11 842 subjects failed to detect evidence of genome-wide significance for any tested quantitative trait locus (QTL), even though many loci with suggestive linkage with lumbar or femoral BMD were identified [27]. Even though a consensus on QTLs associated with osteoporosis has not been reached, these studies (as well as linkage studies in inbred strains of mice) clearly indicate genes that regulate bone mass act in a gender-specific and site-specific manner. An additional potential explanation for the lack of consistency between major linkage results in different studies may be related to the wide age range of the included subjects, with few studies specifically restricted to younger individuals who had attained peak bone mass. Thus, the inclusion of older subjects could have impaired the ability to detect loci that regulate peak BMD. Indeed, some of these linkage studies confirmed that genetic effects on BMD can differ across age groups and that these differences cannot adequately be captured by simply entering age into the model [28, 29]. In the largest of these studies (performed in a European sample of 3691 individuals from 715 families), gender specific analyses were also conducted for subjects under or over the age threshold of 50 years to distinguish QTLs for peak bone mass from those that influence bone mass (and presumably bone loss) in older people. Interestingly, the suggestive or significant loci for BMD only became apparent when gender and age were taken into account [29]. In men below the age of 50 years, four major QTLs were detected, on chromosome 3q25 for lumbar BMD and on chromosomes 4q25, 10q21 and 16p13 for femoral neck BMD. An additional locus on chromosome 7p14 was associated with femoral neck BMD in elderly men. However, only one of these QTLs, 4q25, was associated with BMD in women. Weak evidence of linkage (LOD 1.31) was also indicated for a QTL on
chromosome 14q31, previously associated with lumbar BMD in a genome-wide scan performed in participants from the Framingham Osteoporosis Study [28], particularly when younger individuals (below 60 years) were considered. In this latter study, chromosomal regions on 4q34.1 and 8q24 were also associated with BMD in the male-only subsample. Recently, one linkage study was specifically designed to discover QTLs for low bone mass in pedigrees of males with idiopathic osteoporosis [30] and a single study was performed to identify QTLs for peak BMD in both sexes [31]. The first of these studies was performed in 103 pedigrees from the NEMO Family Study, ascertained through a male relative with low lumbar or femoral BMD values (Z score 2) [30]. Eight chromosomal regions with LOD score 1.5 were identified on 1q42-43, 11q12-13, 12q23-24, 17q21-23, 21q22 and 22q11 for lumbar BMD and on 5q3133 and 13q12-14 for femoral neck BMD. Four of these QTLs reached the genome-wide criteria for significant (17q21-23) or suggestive (11q12-13, 22q11 and 13q12-14) linkage. Interestingly, apart from 22q11, which is a novel QTL, all other loci provided replication for previously reported QTLs for BMD and other bone-related traits. Moreover, several of these areas encompassed prominent candidate genes for osteoporosis such as COL1A1 and the SOST genes on 17q21-23, the LRP5 gene on 11q12-13 and the RANKL gene on 13q12-14. In the second study, a sample of 2200 Caucasian men and premenopausal women aged 20–50 (supposed to reflect the genetic effects on peak BMD) from 207 pedigrees was tested [31]. In the overall analysis, two QTLs showed suggestive linkage with hip BMD (12p12 and 22q13) and four with wrist BMD (2p13, 10p14, 14q23 and Xq27). However, few of these regions identified in the overall sample overlapped with those from the gender-specific analysis. In fact, when sex-specific tests were performed, two major regions showed suggestive linkage with hip (15q26) or lumbar (7p21) BMD in men, while four regions were linked to wrist BMD in females (2p13, 6q24, 11q13 and 18q21). Additional information has been derived from a linkage analysis performed in a genetically closed sample from the Amish Osteoporosis Study, with large sibships and a relatively homogeneous lifestyle [32]. Even though no strong evidence for linkage was detected in the overall study population, secondary analyses indicated sex- and agespecific effects. For men, strong evidence for linkage was observed on chromosome 7q31 for hip BMD (LOD 4.15) and on chromosome 21q22 (LOD 3.36) for spine BMD. Different and more modest associations were detected in women (1p36 and 1q21). Moreover, suggestive QTLs on chromosomes 11q22 (LOD 2.11) for radial BMD and 14q23 (LOD 2.16) for hip BMD were evidenced when analysis was restricted in men and women below age 50. Overall, these data from different linkage studies underline the necessity to design specific and sufficiently powered
C h a p t e r 1 2 The Genetics of Peak Bone Mass l
studies in selected male or female cohorts of subjects within restricted age ranges, which may increase the ability to identify true susceptibility loci for peak bone mass or bone loss at different skeletal sites. So far, only one gene for osteoporosis susceptibility has been identified by linkage studies and subsequent positional cloning in a study in two isolated populations of Iceland, the bone morphogenetic protein 2 (BMP2) gene in chromosome 20p12.3 [33]. Three polymorphic variants in this gene were then associated with osteoporosis and fractures in the two populations from Iceland as well as in a replication study in an independent cohort of Danish postmenopausal women. A major influence of the BMP2 gene on the attainment of peak bone mass, rather than increased bone loss was also observed.
Association studies Association studies, in which polymorphic variants were correlated with BMD (or less commonly other traits) across a population rather than within families, have been widely used in the field of osteoporosis genetics. By this approach, a large number of polymorphisms in different genes have been related to the regulation of bone mass and the pathogenesis of osteoporotic fractures, even though no convincing conclusions have emerged [1, 2]. Large population based studies, retrospective meta-analyses and genomewide association studies recently confirmed some but not all of these associations [1, 2, 34, 35]. Again, most of these studies have been performed in women and less commonly in men. Moreover, despite the evidence of an increased genetic effect on the attainment of peak bone mass, a consistent number of studies was performed in postmenopausal women or elderly men.
Sex Hormones, Sex Hormone Receptors and Aromatase The role of sex hormones on male skeletal homeostasis has recently been revised and it is now clear that estrogen deficiency is a major cause of osteoporosis in males [17]. Thus, genes involved in sex steroid hormone metabolism, such as aromatase, or in mediating the estrogenic and/or androgenic response, such as estrogen and androgen receptors, are all possible contributors to the reduction of bone strength and fractures in the male. Indeed, consistent with observation of clinical syndromes in which disruptive mutations in these gene have been described, it is likely that more subtle differences in sex steroid action on bone (i.e. due to polymorphic variants) could predispose some men to osteoporosis. Importantly, despite normal estrogen levels, evidence of decreased ESR1 expression has been described in osteoblasts and osteocytes derived from young and middle-aged men with idiopathic osteoporosis [36].
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ESR1 gene polymorphisms have been analyzed extensively for associations with BMD, bone loss, turnover markers and/or fractures in women and less in men, with contrasting results [37]. Nevertheless, a large meta-analysis from 22 eligible studies (n 11 in Caucasians and n 11 in Asians), as well as a large study of 19 917 individuals from eight European centers concluded that homozygotes for the XbaI (rs9340799) XX genotype may have increased bone strength compared to xx genotype [38, 39]. While in the first of these studies a modest but significantly higher BMD (1–2%) was observed in subjects with XX genotype, a significant association with fracture risk but not BMD was observed in the second study. These data therefore suggest that ESR1 genetic variation may influence the age-related changes in bone structure that underlie bone strength/fragility, whereas the ESR1 association with bone mass may be more easily discernible in particular age ranges or above a certain estradiol threshold [10]. To date, few studies of modest size investigated the effects of ESR1 polymorphisms on bone in young or middle-aged men. In the only study specifically performed in healthy adolescent boys (mean age 16.9 years), a significant association of XbaI and PvuII polymorphisms with BMD was demonstrated cross-sectionally and longitudinally, indicating a possible role of ESR1 gene in the attainment of peak bone mass [40]. Interestingly, in a different study, the association between ESR1 polymorphisms and BMD was stronger for prepubertal than for postpubertal subjects [41]. A similar effect was observed in a preliminary study in 139 prepubertal girls and 232 prepubertal boys [42]. In this study, ESR1 genotypes were associated with BMD at most skeletal sites, but with a borderline interaction involving sex and calcium intake. A significant gene-bygene interaction between the ESR1 and VDR genes on BMD and bone mineral content (BMC) was also observed in very young children from both genders [43]. Moreover, Khosla et al [44] noted significant interactions between bioavailable estradiol and the XbaI and PvuII genotypes on rates of bone loss in men aged 22–90 years, indicating that positive or negative associations may be dependent on circulating estrogen levels. While the pp or xx genotype may be relatively estrogen-insensitive, subjects with the P or X allele appeared to benefit more from the protective effects of estrogen on bone than subjects with the p or x allele. Interpretation of all the above findings is limited by the lack of biological evidence that ESR1 intron 1 alleles affect estrogen receptor levels and/or activity. However, there is evidence that these polymorphisms may affect gene transcription [37]. Few studies have examined the polymorphisms in the estrogen receptor gene (ESR2) for association with BMD and fracture risk in young individuals. A recent analysis of ESR2 polymorphisms in 723 men and 795 women (mean age 60 years) from the Offspring Cohort of the Framingham Study found significant associations between CA repeat polymorphisms and measures of femoral BMD in both genders [45]. Consistent with other studies, the higher BMD
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Figure 12.2 Variation in circulating estradiol level in men in relation to CYP19A1 TTTAn repeat genotype. Subjects were grouped according to short (S, TTTA 9) and long (L, TTTA 9) repeats number. (Adapted from Gennari et al J Clin Endocrinol Metab 2004;89:2803–10).
values were observed in subjects who were homozygous for a lower number of repeats (CA 23) [13]. Furthermore, two common single nucleotide polymorphisms (rs1256031 and rs1256059) in strong linkage disequilibrium with one another but not with the CA repeat, showed an association with femoral BMD in men but not in women, suggesting that genetic variation in the ESR2 might play a prominent role in men. Since other ESR2 studies were mostly performed in small samples of either pre- or postmenopausal women [37], there is a need for additional studies of ESR2 alleles in males along with further meta-analysis of the results of these studies. Only a small fraction of circulating estradiol is derived directly from the testes, while up to 85% is due to peripheral aromatization of testicular and adrenal androgen precursors into estrogen. Thus, a functional aromatase enzyme is crucial for the normal development of the male skeleton. Several polymorphic regions have been detected in the human CYP19A1 aromatase gene that could be responsible for qualitative and/or quantitative differences in gene expression of aromatase activity [46]. CYP19A1 polymorphisms have been found to be associated with estrogen levels, BMD and fracture risk in postmenopausal women and elderly men in a number of studies (Figure 12.2). Subjects homozygous for short TTTA repeat number in intron 4 of the CYP19A1 gene generally exhibit lower BMD and increased rates of bone loss in comparison to subjects with longer TTTA repeat sequences [46]. Interestingly, these associations appear to be dependent on fat mass. Differences between CYP19A1 genotypes were greater in subjects with a normal body mass index (BMI), while the association progressively decreased in magnitude when overweight and obese men were analysed [46]. This
point suggests that fat mass may be a mitigating factor in the expression of CYP19A1 genotypes on bone. It is possible that, with more adipose tissue, the associated overall increase in adipose aromatase activity dominates any effect of the polymorphisms on intrinsic aromatase activity. Consistent with these clinical observations, higher in vitro aromatase efficiency and greater estrogen production were observed in fibroblasts from a high TTTA repeat sequence genotype in comparison to fibroblasts from a low TTTA repeat sequence genotype [46]. Given the importance of estrogen in bone accrual, it is likely that deleterious CYP19A1 polymorphisms exert even a greater role in young individuals. Despite an early study in 140 middleaged Finnish men that revealed an association between the number of TTTA repeat sequences and height and BMI but not with BMD [47], a more recent analysis confirmed that CYP19A1 polymorphisms significantly affect the attainment of peak bone mass [48]. In a large and well-characterized cohort of 1068 men at the age of peak bone mass (18.9 0.6 years), both the TTTA repeat variation and a silent G/A polymorphism at Val80 of the CYP19A1 gene were predictors of areal BMD of the radius, lumbar spine, total body and cortical bone size (cortical cross-sectional area and thickness) of both the radius and tibia (Figure 12.3). Although these studies, in the aggregate, provide data to argue for the importance of polymorphisms in CYP19A1 and ESRs as determinants of estrogen production or sensitivity and bone strength in men, larger and more definitive studies are needed before any firm conclusions can be drawn. Notably, a (CAG)n repeat polymorphism in the androgen receptor gene may be also important, as mRNA expression serves to be dependent on CAG repeat variations, with an inverse correlation between the length of the repeats and the extent of mRNA expression and AR protein levels. Even though some studies suggested that the number of CAG repeats may be an independent negative predictor of bone density, these studies were not well powered and the role of AR gene polymorphism in the attainment of peak bone mass remains unknown [49].
Vitamin D and Parathyroid Hormone (PTH) Receptor A common allelic variation in the VDR gene was the first to be implicated in the genetic determination of bone phenotypes [1, 2]. Several polymorphisms have been identified in the human VDR gene locus (more than 180 single nucleotide polymorphisms (SNPs) according to Celera and NCBI databases). Both exon 2 and 3-end polymorphisms of the VDR gene have been extensively investigated in women, but with conflicting results [1, 2]. These polymorphisms exert a weaker effect than that originally reported and there is now evidence to suggest that their role may be mediated by effects on body size and modulated by calcium intake [1, 50]. Some positive associations also have been described
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Figure 12.3 Differences in lumbar or femoral BMD (A) and cortical thickness (B) at the radius and ulna according to the CYP19A1 TTTAn repeat genotype in young Swedish men. Subjects were grouped according to short (S, TTTA 9) and long (L, TTTA 9) repeats number. (Adapted from Lorentzon et al J Bone Miner Res 2006;21:332–39).
in men, with 3-end VDR genotypes correlated with peak bone mass, bone size, fracture risk and intestinal calcium absorption efficiency [49]. However, most of these studies have been performed on limited samples. Although these VDR SNPs have shown a modest effect on BMD and fracture risk in recent large population surveys and no effects at all in two different genome-wide association studies [1, 34, 35], it is likely that more relevant effects may occur in response to treatments with calcium, vitamin D or its active metabolites. Direct evidence for an interaction between Bsm I VDR polymorphism and calcium intake first came from an analysis of BMD changes in elderly patients receiving calcium and vitamin D supplements, showing higher lumbar spine BMD losses in BB than in Bb or bb genotypes [51]. Different reports indicated that similar interactions also occur in younger subjects. In addition, VDR polymorphisms have been reported directly to affect parathyroid gland regulation in subjects with primary hyperparathyroidism or endstage renal disease and in normal premenopausal women [50]. Interestingly, in a study on healthy Caucasian males assigned to a high or a low calcium and phosphate diet, subjects with BB genotype displayed lower renal tubular reabsorption of phosphate and higher PTH levels, particularly during calcium and phosphate restriction (Figure 12.4), despite similar 1,25(OH)2D concentrations [52]. Taken together, these observations suggest that VDR allelic variants may assume an increased role during conditions requiring a higher calcium and vitamin D intake, such as pubertal growth and senescence. However, this hypothesis remains to be confirmed in longitudinal, large-scale studies as well as in high-risk populations (i.e. young subjects before the attainment of peak bone mass, subjects with low sunlight exposure, low vitamin D status or reduced calcium intake). In addition, combinations of haplotype blocks rather than single polymorphisms should be required to analyze systematically the possible influence of genetic variants at the VDR gene on the response to calcium supplementation and/
or treatment with vitamin D. Indeed, recent observational studies in larger samples showed that different and more complex combinations of genotypes (rather than 3-end polymorphisms) may be associated with low bone strength and increased fracture risk [53]. Recently, polymorphisms in the gene encoding for parathyroid hormone receptor type 1 (PTHR1) gene have been associated with BMD in a large study on 634 families (1236 men and 1926 women) ascertained with probands with low BMD and the Children in Focus subset of the Avon Longitudinal Study of Parents and Children [54]. Interestingly, this association was restricted to the youngest tertile of the population, suggesting a major role of this gene in determining peak BMD.
LRP5 Gene and the Wnt pathway The importance of LRP5 gene for bone homeostasis and particularly for osteoblast function was discovered following linkage studies in the OPPG and the HBM syndromes [18, 19]. Subsequent studies also provided some experimental evidence that Wnt-LRP5 signaling may be implicated in the sexual dimorphism of the skeleton [10]. Not only do rare mutations in the LRP5 gene play a major role in regulating bone mass, but more subtle polymorphisms seem also to regulate BMD in the normal population. In a casecontrol study in middle-aged men (mean age 50 years), LRP5 exon 9 V667M (rs4988321) and exon 18 A1330V (rs3736228) missense polymorphisms have been associated with an up to threefold increase risk of idiopathic osteoporosis (Figure 12.5) [55]. Moreover, vertebral bone mass and size in adult males, as well as changes over one year in lumbar spine BMD and size in prepubertal boys, were also significantly associated with these LRP5 variants [56], whereas no significant association was found in females, suggesting that LRP5 polymorphisms could mainly contribute to the risk of spine osteoporosis in men by influencing
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Figure 12.4 Influence of dietary modifications (calcium and phosphate restriction versus supplementation) on (A) serum phsosphate, (B) ionized calcium, (C) serum PTH and (D) renal tubular readsorption of phosphate (TmP/GFR) in young men with VDR BB or bb genotype (rs1544410, IVS8 284A G). (Adapted from Ferrari et al J Clin Endocrinol Metab 1999;84:2043–48). 10 9 8 7 6 5 4 3 2 1 0
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Figure 12.5 Odds ratio for LRP5 polymorphisms and idiopathic male osteoporosis. The reference group was GG for exon 9 SNP (rs4988321, G2047A) and CC for exon 18 SNP (rs3736228, C4037T). (Adapted from Ferrari et al Bone 2005;37:770–75).
vertebral bone growth during childhood. These findings were replicated in the Rotterdam Study cohort, where a significant association of LRP5 1330-valine and decreased lumbar spine area and a higher risk of fragility fractures (hip, proximal humerus and pelvis fractures) was observed in men (OR 1.6, 95% CI 1.0–2.4), but not in women [57]. Evidence of an interaction between the LRP5 A1330V variant and a coding polymorphism of LRP6 (1062V) was also suggested in this study. However, no association with bone loss was observed in this cohort, suggesting that these polymorphic variants exert most of their effects on bone growth and the attainment of peak bone mass. A more
recent study analyzed ten SNPs spanning the LRP5 gene in a large and well characterized sample of 1797 unrelated individuals from the Framingham Study [58]. Three SNPs (rs4988321, rs2306862 and rs3736228) were significantly associated with BMD in men 60 years of age, after adjustment for covariates. Even though a significant association was observed also in women (but with different SNPs than in men), an interaction of LRP5 polymorphisms with physical activity was observed only in men. In both rs2306862 and rs3736228 SNPs, the TT genotype was associated with lower spine BMD in men with higher physical activity scores, conversely with preserved BMD in men with lower physical activity scores [58]. In keeping with this observation, a study in 783 Caucasian men aged 20–30 years confirmed a significant inverse association between the number of the T alleles leading to 1330-valine in rs3736228 and BMD in the spine and whole body only in physically active men [59]. Moreover, a 6-month longitudinal study investigating exercise-induced changes in bone mass during military service in 185 Finnish men identified a slight decrease in bone mineral content of the spine in those with Ala-Val rs3736228 genotype but no change in those with Ala-Ala genotype [60]. Taken together, the gene–environment interaction observed in these studies provides support for LRP5 as a mediator of load-induced bone formation. Findings of sex-specific associations of LRP5 SNPs with BMD were further confirmed in Chinese and Caucasian populations [1, 13]. However, a more recent prospective meta-analysis of participant-level data on 37 760 individuals [61], which was focused on the A1330V (rs3736228) and V667M
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(rs4988321) polymorphisms, could not replicate the gender difference suggested in most of the above individual studies. These two polymorphisms were strongly associated with BMD and were predictive of osteoporotic fractures in Caucasians of both sexes. The BMD effects tended to be larger for Val667Met than for Ala1330Val. The interaction of LRP5 variants with physical activity in men and women, however, was not tested in this meta-analysis. Interestingly, in vitro promoter–reporter assays have indicated that different haplotypes for the V667M and A1330V polymorphisms differ in their ability to activate reporter gene transcription, indicating that they are also functional [1, 58]. A recent study in a moderate-sized cohort selected with extreme BMD (n 344), found significant associations between several members of the Wnt signaling pathway and bone densitometry measures [62]. In addition to LRP5, polymorphisms of LRP1, LRP6 and Wnt3a genes, as well as of different Wnt/LRP5 antagonists (SFRP1, SOST and DKK2), also showed association with BMD in women. Polymorphisms in the SOST gene, encoding sclerostin (a LRP5 antagonist) have been shown to be associated with BMD in male and female subjects from the Rotterdam Study [63]. In contrast to LRP5, the effect of SOST polymorphism seems to be more evident in the oldest age group.
COL1A1 Gene Type 1 collagen is the major structural protein of bone and thus the genes encoding this protein are important candidates for genetic regulation of bone mass in both males and females. An osteoporotic phenotype, without typical signs of osteogenesis imperfecta, could be the result of genetics defects in the COL1A1 and COL1A2 genes. An intronic polymorphism in the COL1A1 gene has been identified and associated with BMD and osteoporotic fracture risk in several studies on elderly women [1, 2]. This polymorphism involves a consensus binding site for the transcriptional regulator Sp-1 and there is now evidence of allelic specific differences in gene transcription, collagen protein production, bone mineralization and, most importantly, bone strength in samples derived from subjects with opposite genotypes [1]. To date, there are few studies that specifically analyzed the role of this polymorphism in males [1, 2, 49]. In larger studies or meta-analysis in mixed male and female populations, the association between COL1A1 alleles and fracture persisted even after correction for BMD and appeared stronger than would be expected on the basis of allelespecific differences in bone mass [1]. This has led to speculation that the polymorphism may principally act as a marker of bone fragility rather than of reduced BMD. The COL1A1 Sp1 polymorphism has been specifically studied in relation to BMD in children and adolescents, but the results have been contradictory. In the only study performed in a mixed male and female population (mean age 12–15 years) from Northern Ireland, no significant association was
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observed, indicating that this polymorphism may be associated with osteoporotic fractures by affecting age-related bone loss and bone fragility, rather than peak bone mass [64].
Insulin-like Growth Factor I In the past years, several lines of evidence indicated that the insulin-like growth factor I (IGF-I) gene may be a strong candidate for peak bone mass and osteoporosis in men. Low IGF-I levels have been implicated in the etiopathogenesis of idiopathic osteoporosis in young males and may account for the reduced osteoblast activity frequently observed in these subjects [49]. Moreover, heritable determinants of circulating IGF-I levels have been demonstrated [49]. This has led to the hypothesis that a particular allelic configuration of the IGF-I gene due to a (CA)n dinucleotide repeat polymorphism next to the promoter region could be associated with the observed variation in circulating IGF-I levels. In an early study by Rosen et al [65], a particular allele, defined by the presence of 19 CA repeats, was more prevalent in male patients with idiopathic osteoporosis than in controls. Interestingly, homozygosity for the same allele was also associated with low serum IGF-I levels and a trend for a lower BMD was also observed. Some preliminary observations in a larger sample of men seemed to confirm this association [49]. However, the molecular mechanism remains unknown and a large sib-pair study on premenopausal females did not confirm a significant role of this polymorphism, at least in women [66]. Thus, the effect of the (CA)n repeat polymorphism on bone mass and circulating IGF-I levels may be gender-specific, with a significant impact only in male subjects. Further large-scale studies are needed to confirm this hypothesis.
Other Polymorphic Variants A large number of other candidate genes have been studied in relation to BMD and susceptibility to osteoporotic fracture. Some polymorphisms in these genes have been also specifically associated with peak bone mass in men. These include methylene tetrahydrofolate reductase (MTHFR) [67], catechol-O-methyltransferase (COMT) [68], interleukin 6 (IL-6) [69], arachidonate 12-lipoxygenase (ALOX12) [70], receptor activator of NF-kappaB ligand (RANKL), receptor activator of NF-kappaB (RANK) and osteoprotegerin (OPG) [71] genes. In particular, the association between ALOX12 polymorphisms and BMD has been further supported by linkage studies and experimental observations in mice. The 17p13 region of the human genome containing the ALOX12 gene has been identified as a QTL for BMD of the hip, spine [72] and wrist [73]. Moreover, the murine arachidonate 15-lipoxygenase gene (Alox15) has been identified as a negative regulator of peak BMD [74]. Even though the human ALOX15 gene shares significant sequence homology with the murine Alox15 gene, the human ALOX12 gene is
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functionally more similar to the mouse Alox15 gene in terms of reaction products. Similarly, the importance of polymorphisms in RANK, RANKL and OPG genes, affecting a major pathway for the regulation of osteoclast activity and bone resorption, has been recently underlined in two large-scale, genome-wide, association studies [34, 35, 75]. The specific role of these polymorphisms in the regulation of peak BMD in men, however, needs to be further investigated. Finally, an interaction between polymorphisms in peroxisome proliferator activated receptor (PPARG) gene and dietary fat on BMD has been also described in both middle-aged men and women from the Framingham Offspring Cohort [76].
Animal studies Experimental animal models have provided a means largely to circumvent the complex effects of environmental (at least extrinsic) variations which are present in human studies [77]. Different animal models (and particularly mice, rats and non-human primates) have been the subject of experimental osteoporosis research [78]. Of the currently available options, the mouse is arguably the model of choice because: 1. mice are much cheaper to house and easier to handle 2. mouse genetic resources are quite extensive 3. once candidate genes are identified, the ability to manipulate them in mice and to deduce unambiguously their role in disease is unparalleled. Moreover, gene targeting has reached new heights in mice, but is barely on the horizon in other animals. With gene targeting perhaps as the ultimate arbiter for establishing causeand-effect relationships between candidate genes and osteoporosis susceptibility, the mouse is apt to remain the primary experimental model system for the foreseeable future [79]. Current murine research in the field of skeletal genetics is heavily dependent upon comparing inbred mice of different strains that exhibit marked differences in parameters of skeletal integrity. A strain of a species is inbred when virtually every genetic locus is homozygous. This means that all individuals within an inbred strain share a set of characteristics that uniquely define them compared to other strains. Typically, inbred strains are derived from 20 or more consecutive generations that have been brother sister mated; the strain can then be maintained with this same pattern of propagation. Individual animals within an inbred strain are virtually as identical as monozygotic twins. There are several qualities of inbred strains that make them especially valuable for research. The first is their long-term relative genetic stability. This is important because it allows researchers to build on previous investigations. Genetic change can occur only as a result of mutation within an inbred strain. A second important quality of inbred animals
is their homozygosity because inbred strains will breed true. Once the characteristics of a strain are known they can be reproduced repeatedly allowing for replicate experimentation as well as for studies by other investigators. The influence of genotype upon a particular characteristic can be investigated by placing mice from several inbred strains in a common environment. Observed differences must then be, within limits, the consequence of genetic factors. By reversing this strategy and placing mice from a single inbred strain in a variety of environments, it is possible to estimate the importance of environmental influences upon a parameter of interest. Thus, inbred animals can be used to determine whether genetic variation in the expression of a characteristic exists and the environmental malleability of the characteristic [80].
Sex-Specific Skeletal Traits and Genetics Experiments with inbred strains do have some limitations. While strain differences are easily demonstrated, it is often very difficult to attach much meaning to these differences, because the genes and gene products involved are usually unknown. Because comparisons of mice from two or more strains do not usually provide any information about the nature of the genetic differences, crosses between genotypes must be used to analyze patterns of genetic influence. Additionally, when using an inbred strain to investigate any type of phenomenon, it is important to be aware that the observations may be relevant only to that strain. Because an inbred strain differs from all others, there will be characteristics unique to it. It is therefore important to use more than one strain to confirm that any observation obtained pertains to the species and not just to the strain studied. Osteoporosis researchers have performed genotype– phenotype linkage (or quantitative trait or QTL) analyses in large populations of genetically heterogeneous mice derived from various combinations of inbred strains in the hopes of obtaining a more complete picture of the polygenic control of bone mass and an improved understanding of the complex interactions and physiological mechanisms involved. Results from these complementary studies are beginning to define the landscape of the genetic regulation of bone fragility and partition this quantitative trait into separate genetic components amenable for more detailed evaluation [81, 82]. A number of experiments on inbred mice have demonstrated evidence of sex-specific effects on skeletally-relevant traits. Using C57BL/6 J mice, Glatt and colleagues [83] found age-related changes in trabecular bone architecture occur earlier and are more dramatic in female than male mice, particularly in the secondary spongiosa of the femoral metaphysis. As described above, the study of an inbred strain usually provides very little information about specific mechanisms of gene action. The analysis of single mutant versus normal genes is often a more effective approach. Comparisons between homozygous mutant mice and their
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‘normal’ homozygous wild-type and heterozygous litter mates may provide considerable information on cellular mechanisms critical for discrete aspects of bone biology. For example, steroid receptor coactivator (SRC)-1 is critical for the maintenance of bone mass in both female and male mice. However, Mödder et al [84] recently demonstrated preserved responses to estrogen in trabecular bone in male gonadectomized SRC-1 knockout (KO) mice, in stark contrast to the deficient skeletal response to similar estrogen treatment in female gonadectomized SRC-1 KO mice. These investigators hypothesize the gender-specificity in the consequences of loss of SRC-1 for estrogen action may have to do with preferred interactions of SRC-1 with the two different ESR isoforms ( and ). Future studies with this model will likely provide insights into differential ESR and expression, utilization or interactions with SRC-1 in male versus female bones. The insulin-like growth factor (IGF) system is an important regulator of bone development. Recent studies of the skeletal phenotype of IGF binding protein 2 (IGFBP2) KO mice revealed gender- and compartment-specific effects [85]. Female IGFBP2-KO mice exhibited increased femoral cortical thickness and greater periosteal circumference compared to wild-type controls, whereas male IGFBP2-KO mice had reduced femoral cortical bone area and a 20% reduction in the trabecular bone volume fraction due to thinner trabeculae than their corresponding controls. Studies of transgenic mice bearing a mutation in LRP5 associated with an HBM phenotype in humans also indicate the presence of gender-specific effects on trabecular structural parameters [86]. The above examples demonstrate the utility of animal models in uncovering aspects of bone biology contributing to skeletal dimorphism that are currently not feasible to explore in human subjects. Just as is the case in humans, sex-specific differences in the amount of bone and the architectural arrangement of bone tissue are obvious in animals. Studies on controlled model systems are now beginning to provide some insight into putative sex-specific determinants of heritable skeletal traits. Orwoll et al [87] examined peak whole body BMD (measured by dual energy x-ray absorptiometry (DXA)) in male and female mice from a panel of recombinant inbred strains derived from C57BL/6 J (B6) and DBA/2 J (D2) progenitor mice. A significant gender by strain interaction was observed, with males having higher BMD than females in some strains but lower in others. In a follow-up linkage analysis experiment employing a genetically heterogeneous F2 (second generation offspring) population of mice (B6D2F2) derived from the same B6 and D2 progenitor strains, strong associations between peak bone mass and three chromosomal locations (chromosomes 1, 4 and 11) were identified in both male and female mice [82]. However, there was no relationship with bone mass in males at a fourth locus strongly associated with bone mass in females (chromosome 2) and the reverse situation (no relationship
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with bone mass in females at a fifth locus strongly associated with bone mass in males) was found at chromosome 7. It is informative to contrast the results obtained in these analyses to those obtained when gender is not considered in the study design [88]. When male and female animals were studied together, the association on chromosome 7 was not detected using standard criteria. Unless specifically sought, gender effects can lead to a lessened ability to detect potentially important genetic determinants. Size and shape are critical determinants of the mechanical properties of skeletal elements and can be anticipated, like BMD, to be highly heritable. Moreover, the genes responsible may be independent of those that regulate BMD. For a long bone, one of the most important geometric properties influencing its ability to resist fracture is its cross-sectional area (CSA). Companion experiments employing the same panel of recombinant inbred strains and B6D2F2 population described above [89] revealed regions on four different chromosomes that were very strongly linked to femoral mid-shaft CSA (chromosomes 6, 8, 10 and X) in both genders. Evidence of gender-specific genetic influences on femoral geometry was also identified at three other chromosomal sites (chromosomes 2, 7 and 12). Interestingly, none of these chromosomal associations with femoral CSA were identified in the previous analysis of whole body BMD in the same B6D2F2 population. Thus, the genetic determinants of bone size appear to be largely, if not entirely, distinct from those regulating BMD attainment. Furthermore, these studies strongly support the existence of sex-specific pathways engaged in the genetic regulation of peak bone mass and size – critical determinants of fracture resistance. Classical transmission genetics can also be used to transfer distinct chromosomal regions containing putative risk or protective genes onto appropriate background strains. Such congenic strains are produced by repeated backcrossing to the background inbred strain and genotypic selection of the desired allele at flanking markers at each backcross generation. The primary advantage of the congenic is that the influence of an individual chromosomal region on a given trait can be tested using the congenic versus background strain comparison at any level from the molecular to the physiological. Ultimately, congenic strains can greatly facilitate positional cloning of a causative gene. Knowing which genetic markers define a specific chromosomal region will automatically indicate which candidate genes reside within the region. In addition, congenic strains provide an invaluable resource for further defining specific genes of interest and for in depth studies of the mechanisms by which they affect skeletal phenotype. Using this experimental strategy, Turner and colleagues [90] discovered that regions of murine chromosome 1 and 18 impart sex-specific effects on femoral structure (as reflected by mid-diaphyseal polar moment of inertia) and a region of chromosome 6 imparts a sex-specific effect on femoral cortical volumetric
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BMD and femoral strength. Of particular interest, the introgressed region on chromosome 1 influenced the moment of inertia (an index of resistance to fracture) of male bones in an opposite direction from female bones. Extending these observations, subsequent studies with these chromosome 1 congenic mice found that the female congenic mice were more responsive while the male congenic mice were less responsive to mechanical loading events than their respective background littermates [91]. These findings may explain sex-specific differences in peak bone mass accrual despite similar physical activity. Edderkaoui et al [92] have explored this same region of murine chromosome 1 with congenic mice created from other inbred mouse strains and have identified three separate genetic loci influencing femoral volumetric BMD – the effects of two loci were only evident in female mice. Clearly, more studies are called for better to define the implications of these preliminary observations, but the fact that mice and humans share genetic homology between this region of mouse chromosome 1 and a region of human chromosome (1q20-24) that is associated with BMD [1] suggests the imperative to partition human data by sex to improve accuracy of mapping and genetic loci identification. In summary, data in mice suggest the presence of sexspecific genes governing bone mass, size and microstructure, which may, in part, occur via differences in skeletal responses to environment (e.g. mechanical loading, sex steroids, etc.) between males and females. Certainly, the chromosomal loci that reveal gender divergence may be related to the control of, or responsiveness to, sex steroid action. On the other hand, results thus far cannot support or refute the hypothesis that gender differences are sex steroid-independent. In fact, the presence of a clear gender divergence in the genetic basis of peak bone mass raises the intriguing possibility that there may also be other mechanisms by which gender influences gene activation. Other mechanisms that may be involved are uncertain, but include genes on X or Y chromosomes with complementary activities at autosomal sites. Since the male phenotype is associated with considerable fracture risk reduction, an elucidation of the nature of sex-specific effects on bone development could provide the basis for novel diagnostic, preventative or therapeutic approaches.
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Chapter
13
Age-related Changes in Bone Remodeling and Microarchitecture Roger Zebaze1 and Ego Seeman2 1
Department of Endocrinology and Medicine, Austin Health University of Melbourne, Melbourne, Victoria, Australia Endocrine Centre, Heidelberg Repatriation Hospital/Austin Health, Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
2
Introduction
(HSA), section modulus and cross-sectional moment of inertia, are used but these also fail to improve sensitivity and specificity in identifying individuals at high or low risk for fracture respectively, perhaps because these surrogates fail to quantify the age-related deterioration in the material composition and structure of bone in either sex [5, 6]. This chapter reviews age-related changes in bone remodeling in women and men. We focus on the sex differences in bone remodeling that are likely to produce sex differences in macro- and microarchitectural deterioration.
Fewer men sustain fractures than women during advancing age [1]. However, fragility fractures are also a public health problem in men because they are common, have a high morbidity, mortality and confer a high cost on the individual and the community [2]. Structural failure – fracture – reflects age-related changes in the material composition and structural design of bone. However, the pathogenesis and structural basis of bone fragility are not well understood in either sex and so the reasons underlying the lower incidence of fragility fractures in men than women are also not well understood. Most fractures occur in women and men without osteoporosis as defined by bone mineral density (T-score 2.5 SD) [3]. This partly reflects the occurrence of most events in the larger numbers of individuals at moderate risk for fracture occupying the ‘bell’ of the Gaussian distribution of areal bone mineral density (aBMD) rather than the smaller numbers of individuals at high fracture risk occupying the tail of the distribution (aBMD T score 2.5 SD designated as ‘osteoporosis’). In addition, individuals with normal aBMD may be at high risk for fracture due to structural abnormalities not captured by the aBMD measurement [4], while not all individuals with aBMD in the osteoporosis range have fragile bones. These limitations have consequences. Many men and women in need of treatment are not identified using conventional dual energy x-ray absorptiometry (DXA) and many who are treated on the basis of low BMD may not necessarily need to be treated with pharmacological agents. To overcome this problem, surrogates of structural strength derived from quantitative computed tomography (QCT) or densitometry-based methods, such as hip structure analysis
Osteoporosis in Men
The process and purpose of bone modeling and remodeling Bone modeling (construction) is the process by which bone is formed by osteoblasts without prior bone resorption. This process is vigorous during growth and changes bone size and shape. Bone remodeling (reconstruction) occurs throughout life. During remodeling, bone is first resorbed by osteoclasts and then formed in the same location by osteoblasts without a change in bone size or shape. These cells form the basic multicellular unit (BMU) that reconstructs bone in distinct locations on the three (endocortical, intracortical and trabecular) components of its inner (endosteal) envelope and, to a much lesser extent, on the outer (periosteal) envelope [7]. Bone modeling and remodeling during growth achieve strength for loading and lightness for mobility by strategically depositing bone in locations where it is needed, modifying bone size and shape and removing bone from where it is not needed to avoid bulk. The enormous capacity of this cellular machinery to modify structure during growth, primary a modeling period, is apparent
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in the morphological differences in the playing and nonplaying arms of tennis players [8–10]. Bone remodeling during adulthood maintains bone strength by removing damaged bone. Bone develops fatigue damage during repeated loading but contains a cellular machinery that can detect the location and magnitude of the damage, remove it, replace it with new bone and thus restore bone’s material composition, micro- and macroarchitecture [11, 12]. Bone resorption is not bad for bone unless it becomes excessive. The resorptive phase of remodeling removes damaged bone and is essential to bone health. The formation phase of the remodeling cycle restores bone’s structure provided that the volume of damaged bone removed is replaced by the same volume of normal bone. This process depends on the normal production, work and lifespan of osteoclasts and osteoblasts. A cell increasingly recognized as a major component of this cellular machinery is the osteocyte. The osteocyte plays a pivotal role in initiating and perhaps regulating bone modeling and remodeling. Osteocytes are the most numerous, longest-lived and least studied cells of bone. There are about 10 000 cells per cubic millimetre and 50 neuronal-like processes per cell [13]. These processes connect osteocytes with each other and with flattened lining cells on the endosteal surface. The dense lace-like network of osteocytes with their processes ensures that no part of bone is more than several microns from a lacuna containing its osteocyte suggesting that these cells are part of the machinery guarding the integrity of the composition and structure of bone [12]. Microcracks sever osteocyte processes in their canaliculi leading to osteocyte apoptosis [14]. Apoptotic osteocytes may also be a form of damage, perhaps reducing the energy absorbing/dissipating capacity of bone when lacunae mineralize. Estrogen deficiency and corticosteroid therapy result in apoptosis [15]. The increased remodeling rate in midlife in women may be partly the result of osteocyte death. Alternatively, or in addition, osteocyte apoptosis can produce damage to surrounding mineralized matrix producing bone fragility independent of bone loss. Whether apoptotic osteocytes are a consequence of damage, are the damage itself or produce matrix damage, the number of dead osteocytes provides the topographical information needed to identify the location and size of damage [16–18]. Osteocyte apoptosis is likely to be one of the first events signaling the need for remodeling. It precedes osteoclastogenesis [19]. The apoptotic osteocyte may stimulate the sequence of cellular events of bone remodeling. In vivo, osteocyte apoptosis occurs within 3 days of immobilization and is followed within 2 weeks by osteoclastogenesis [20]. Bone remodeling is initiated on the endocortical, trabecular and intra-cortical components of the endosteal envelope (Figure 13.1). The endocortical and trabecular surfaces are adjacent to marrow. The intracortical surface forms the wall of haversian canals. Damage may occur deep to these
surfaces within the matrix of osteons or the interstitial bone between osteons. Information concerning the location and size of matrix damage must reach these surfaces and cells involved in remodeling, originating as precursors in the marrow or in stem cell niches, must reach the site of damage beneath the endosteal surface. This anatomical arrangement makes the flattened lining cells conduits transmitting the health status of the bone matrix to the bone marrow environment. Apoptotic osteocytes signal the location and size of the damage burden to the flattened lining cells of the endosteal surface leading to the formation of a bone remodeling compartment (BRC) which confines and targets remodeling to the damage [21]. The regulatory steps between osteocyte apoptotic death and creation of the BRC are not known. Bone lining cells express collagenase mRNA [22]. An early event creating the BRC may be collagenase digestion of unmineralized osteoid to expose mineralized bone, a requirement for osteoclastic bone resorption to proceed. The flattened bone lining cells are probably osteoblasts or of the osteoblast lineage and those forming the canopy over the BRC express markers characteristic of osteoblast lineage cells [21]. These canopy cells also express markers for a range of growth factors and regulators of osteoclastogenesis, such as receptor activator of nuclear factor kappa B ligand (RANKL). Bone resorption by osteoclasts and bone formation by osteoblasts occur sequentially [23]. However, the cellular and molecular events leading to these two differentiated functions are likely to be contemporaneous and multidirectional; osteoblastogenesis and its regulators determine osteoclastogenesis and the volume of bone resorbed, while osteoclastogenesis and the products of the resorbed matrix regulate osteoblastogenesis. To some extent, and in ways not yet understood, both cells may be regulated by osteocytes and their products. Signaling from apoptotic osteocytes to cells in the canopy expressing the osteoblast phenotype may influence further differentiation towards osteoblast precursors expressing RANKL and fully differentiated osteoid-producing osteoblasts. Even at this stage, regulation of osteoclastogenesis and osteoblastogenesis is occurring simultaneously through osteoblast precursors. In the MLO-Y4 cell line, damaged osteocyte-like cells have been reported to secrete macrophage colony-stimulating factor (M-CSF) and RANKL [24]. Whether this also occurs in human subjects in vivo is not known but raises the possibility that osteocytes participate in the differentiation of monocyte–macrophage precursor cells towards the osteoclast lineage. Both osteoblast and osteoclast precursors circulate and so may arrive at the BRC via the circulation and via capillaries penetrating the canopy [25–27]. Osteoprogenitor cells are associated with vascular structures in the marrow with several studies suggesting that there may be common progenitors giving rise to cells forming the blood vessel and the perivascular cells that can differentiate towards cells of multiple lineages [28–34].
C h a p t e r 1 3 Age-related Changes in Bone Remodeling and Microarchitecture l
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Periosteal surface
6.
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Intracortical surface 2.
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Figure 13.1 (1) Osteocytes are connected to each other and to lining cells on the endosteal surface adjacent to the marrow. (2) Damage to osteocytic processes by a microcrack produces osteocyte apoptosis. (3) The distribution of apoptotic osteocytes provides the topographical information needed to target osteoclasts to the damage. Osteoclasts resorb bone and remove damage. (4) The reversal phase and formation of a cement line. (5, 6) Osteoblasts deposit osteoid and some become entombed in the osteoid to form osteocytes. (From E Seeman, with permission).
The factors regulating the cessation of resorption by teams of osteoclasts and the onset of bone formation after the reversal phase are not well defined. Products from osteoclasts independent of their resorption activity and products from the resorbed matrix are likely to contribute to the regulation of osteoblastogenesis and bone formation [35–37]. In addition, products from the osteocyte are also likely to contribute to regulation of bone formation. For example, sclerostin is secreted by osteocytes and perhaps other cells as well. It is a product of the SOST gene and inhibits bone formation. Osteoblast precursors generated before resorption may form pre-emptive teams of cells ready to deposit bone, die, become lining cells or osteocytes depend on later signals from osteoclasts, the resorbed matrix or products of the osteocyte such as sclerostin or cell–cell contact. After the reversal phase, osteoblasts deposit osteoid partly or completely filling the BMU and forming the lamellae that then undergo primary and secondary mineralization. Most osteoblasts die, others become lining cells while others are
entombed in the osteoid where they develop into the osteocyte with its osteocytic canalicular network [38].
Abnormalities in bone remodeling during aging While bone can accommodate loading circumstances by adaptive modeling and remodeling during growth, this capacity diminishes because of four age-related changes in the cellular machinery of bone modeling and remodeling that compromise bone’s material properties and structural design [39]. As growth nears completion, rapid remodeling rate slows. With the completion of longitudinal growth, the only requirement for bone formation is the repair of microand macrodamage so there is a decline in bone formation, a mechanism proposed to be responsible for bone fragility over 65 years ago (Figure 13.2).
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Figure 13.2 Endosteal bone loss is the result of: (A) a reduction in the volume of bone formed in each basic metabolic unit (BMU) reflected in a reduction in mean wall thickness with age (adapted from Lips et al 1978 [40]). (B, C) A fall or little change in the volume of bone resorbed in each BMU. This is reflected in (B) as little change in erosion depth defined by preosteoblasts, mononuclear cells or osteoclast surfaces (adapted from Ericksen et al, 1985, [43] and (C) and no change in interstitial wall thickness (females black symbols) (adapted from Vedi et al 1984 [41]). (D) Increased remodeling rate (activation frequency) (courtesy J Compston).
The first age-related change in this machinery is a reduction in bone formation at the cellular level by each BMU [40, 41]. The second abnormality is also a reduction in bone formation but at the tissue level – bone modeling on the periosteal envelope slows precipitously after completion of longitudinal growth but continues slowly so that bone diameters enlarge, but no more than a few millimeters during the next 60 years [42]. The third abnormality in remodeling is believed to be an increase in the volume of bone resorbed by the BMU, but this may be confined to a brief period following sex hormone deficiency [43, 44]. The opposite may occur across the whole of life – the volume of bone resorbed by each BMU appears to decrease as reflected in a lower resorption cavity depth and an age-related increase, rather than decrease in interstitial thickness [45]. The fourth age-related abnormality in the cellular machinery contributing to structural deterioration is an increase in the rate of bone remodeling after menopause. This is accompanied by worsening of the negative bone balance in each BMU as the volume of bone resorbed increases and the volume of bone formed decreases in
the many more BMUs now remodeling bone on the three (endocortical, intra-cortical and trabecular) components of its endosteal envelope. Variance in the negative BMU balance during aging is small compared with the variance in remodeling rate so differences in rates of bone loss between individuals are driven more by corresponding differences in remodeling rate than differences in the extent of negative BMU balance. Whatever the purpose of remodeling, whether it is initiated by damage removal, by death of osteocytes or adaptive change in response to loading, remodeling is initiated upon a surface – remodeling is a surface dependent event. A bone fashioned with a higher surface, such as thinner trabeculae in Caucasians than African Americans, or in females than males at some sites, will be ‘turned over’ more rapidly. The surface area is an independent determinant of remodeling intensity; more BMUs can be generated on a larger surface to remodel the matrix beneath and the negative BMU balance in each erodes the skeleton. In addition, the amount of bone lost is also determined by the volume available to be lost. So, trabecular bone loss may be
C h a p t e r 1 3 Age-related Changes in Bone Remodeling and Microarchitecture l
more rapid than cortical bone loss because trabeculae have a higher surface to volume ratio but, as only 20% of the skeleton is trabecular and 80% is cortical, cortical bone loss over time is greater than trabecular bone loss. Thus, between individuals within a sex, between sexes and between races, differences in the amount of bone lost with age is determined by each of these four factors. However, the structural and biomechanical consequences of bone loss depend on the underlying structure from which bone is lost and how that bone is removed. For example, thicker trabeculae and cortices can tolerate a greater amount of bone loss. Thinner trabeculae are more likely to perforate with a given loss of bone. Moreover, if bone is lost by reduced formation, the structural consequences are likely to be less than the same volume of bone lost by increased resorption depth.
Bone loss during young adulthood, menopause and advanced age At some stage in midlife or earlier, a net negative bone balance emerges as the volume of bone resorbed exceeds the volume of bone formed. The negative balance probably arises initially from a reduction in bone formation [40]. Trabecular volumetric density decreases prior to menopause. In a three-year prospective study of 553 women and men, Riggs et al reported that, before age 50 years, women lose 37% and men 42% of lifetime total trabecular bone and 6% and 15% of lifetime cortical bone [46]. The structural and biomechanical consequences are likely to be less than bone loss later in life because: 1. remodeling rate is slow 2. trabecular bone loss probably proceeds by reduced bone formation rather than increased bone resorption in the BMU 3. bone loss proceeds by trabecular thinning rather than loss of connectivity so a given decrement in trabecular BMD produces less loss of strength than produced by loss of connectivity 4. continued periosteal apposition partly offsets cortical thinning shifting the cortices radially, maintaining cortical area and resistance to bending [47]. While trabecular bone loss is more rapid than cortical bone loss in the initial postmenopausal years, trabecular bone is only 20% of the skeleton while 80% of the skeleton is cortical bone. So the slower loss of cortical bone contributes more to the net amount of bone lost across life than the loss of trabecular bone [48]. Cortical bone is regarded as being ‘compact’. However, it is traversed by myriads of haversian and Volkmann canals, the surface of which is similar to that of trabecular bone surface. It is for this reason
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that, in the first 15 years after menopause, the actual amount of bone lost is similar in absolute terms. Moreover, as remodeling on trabeculae removes them with their surfaces and endocortical and intracortical remodeling increase, the surface available for remodeling decreases in the trabecular compartment and increases in the cortical compartment, so the contribution to total bone loss from the trabecular compartment decreases while the larger volume of cortical bone becomes increasingly accessible to being remodeled and accounts for most of the bone loss with aging. The high remodeling rate itself is a most important determinant of bone loss. In the early menopause, estrogen deficiency leads to accelerated bone remodeling and so accelerated bone loss. All women become postmenopausal, not all lose bone. Women with low rates of bone remodeling lose little and are at a low risk for fracture [47]. The reasons why some women remodel their skeleton slowly while others remodel it rapidly are not understood but, in part, may be due to individual differences in the amount of surface available for remodeling. Women with slow remodeling rates may assemble a bone with a smaller cross-section and higher vBMD and, therefore, less surface, while women constructing a larger skeletal cross-section avoid bulk by assembling this with more surface and a lower vBMD. The rate of remodeling slows at completion of growth and then increases after menopause when estrogen deficiency occurs. Perhaps those women who remodel bone at a slow rate and assemble a bone with a high vBMD (with a low surface to volume ratio) may also have slow remodeling after menopause and so are protected against bone loss and bone fragility after menopause. There are two reasons for the lower fragility. First, the slow remodeling rate occurs because they have a low surface to volume ratio and second, whatever the loss, the resulting fragility is less because the thicker cortices and trabeculae are more resistant to structural decay by remodeling. Those women with high remodeling, who build a larger skeleton, excavate a correspondingly larger medullary cavity with relatively thinner cortices and perhaps thinner trabeculae, have a low vBMD. The high remodeling needed to ‘empty’ the larger skeleton during growth to avoid bulk may become a liability after menopause when high remodeling reappears. This may be double jeopardy; the high remodeling and the thinner cortices and trabeculae predispose these individuals to both more rapid bone loss and greater structural decay. Menopause is also associated with increases in the volume of bone resorbed by each BMU due to the prolonged the life span of osteoclasts and reductions in the volume of bone formed by each BMU due to shortening of the life span of osteoblasts. Whether the changes in the life span of the cells is permanent or temporary is not known but, together, these changes aggravate the negative BMU balance which, in turn, produces a greater loss of bone each time bone is remodeled and the deeper resorption cavities
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remove complete trabeculae accounting for loss of trabecular numbers in women with advancing age [15]. The rapid decline in BMD associated with menopause is the result of the above changes in the rate of remodeling and BMU imbalance. In addition, there is perturbation of the steady state and expansion of the remodeling space transient [12] (Figure 13.3). Remodeling is slow before menopause; the birth rate of new BMUs creating resorption cavities is matched by slow completion of previously created BMUs in their formation phase. At menopause, this steady state is perturbed by an increase in the birth rate of new BMUs on bone’s endosteal envelope. The now many more BMUs remove bone while the fewer BMUs created before menopause complete remodeling by depositing bone. This perturbation produces a net acceleration in bone loss and a rapid decline in BMD. This is the remodeling transient, a reversible loss of bone mass and bone mineral that is a consequence of the normal delay in onset and slower progression of the formation phase of the remodeling cycle in the many remodeling foci created after menopause. The temporary deficit in bone mass and mineral has three components: the excavation site that lacks osteoid and mineral; the osteoid that lacks mineral; and bone that has undergone primary but not secondary mineralization. Primary mineralization occurs rapidly, secondary mineralization, the slow enlargement of crystals of calcium hydroxyapatite-like mineral takes many months to years to go to completion [49]. At any time, there are
osteons created in the immediate postmenopausal period and fewer, earlier created, osteons at various stages of completing secondary mineralization. Bone fragility is also the result of stress concentrators. Excavated resorption sites are vulnerable to microdamage because these sites concentrate biomechanical stress. An example of stress risers is the etched cut in a test tube that makes it easy to snap [50]. The high remodeling rate and negative BMU balance produces trabecular thinning and complete loss of trabeculae. Increased resorption depth is more likely to produce perforation and complete loss of trabeculae than either greater numbers of resorption cavities or reduced formation in the BMU in women [51]. A 10% loss of trabecular density by perforation reduces strength more than the same loss by trabecular thinning [52]. As remodeling continues, trabeculae are lost so the trabecular surface available for resorption decreases but remodeling on endocortical and intracortical surfaces continues increasing cortical porosity [48]. Remodeling on the intracortical surface (haversian canals) increases intracortical porosity [53–56]. Increased porosity, due to increased numbers of pores and/or increased size of pores by coalescence of adjacent remodeling cavities, increases the surface available for remodeling in the cortex. As age advances and remodeling continues at the same intensity due to estrogen deficiency and perhaps secondary hyperparathyroidism, the extent of coalescence of pores
(i) Bone loss before menopause (ii) Bone loss during menopause (iii) Bone loss after menopause BMD
Time
Figure 13.3 (i) Bone loss is slow before menopause because remodeling is slow, only a few sites on the trabecular surface remove bone (open arrows). (ii) Bone loss accelerates because steady state is perturbed at menopause as remodeling rate increases. Now many basic multicellular units (BMUs) remove bone (black arrows) while the three BMUs initiated before menopause deposit bone. (iii) Bone loss after menopause slows relative to the immediate postmenopausal period because steady state is restored. The many BMUs removing bone at menopause are now in their formation phase but, as many new BMUs are created and resorb bone, bone is lost because each remodeling event removes bone from bone. (From E Seeman, with permission).
C h a p t e r 1 3 Age-related Changes in Bone Remodeling and Microarchitecture
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l
increases so the number of pores in cortical bone decreases but the total area of porosity increases, and perhaps more so in patients with hip fractures [55]. Cortical porosity reduces the ability of bone to limit crack propagation so that bone cannot absorb the energy imparted by a fall and this may result in a fracture [54]. The continued remodeling at a similar intensity with its negative BMU balance, on the same amount or more surface, removes the same amount of bone from an ever decreasing amount of bone accelerating the loss of bone and structural decay (Figure 13.4). Rapid remodeling also modifies the material properties of bone, increasing fracture risk. More densely mineralized bone is removed and replaced with younger, less densely mineralized bone, reducing stiffness [57]. Increased remodeling impairs isomerization of collagen [58]. Interstitial bone deep to surface remodeling becomes more densely mineralized and more highly cross-linked with advanced glycation products (AGEs) like pentosidine [59, 60], both processes reducing bone toughness; it is easier for microcracks to travel through homogeneously mineralized bone and lengthen. Interstitial bone (between osteons) has reduced osteocyte numbers, accumulating microdamage [61].
15
Reduced periosteal bone formation in adulthood The challenges regarding and identifying the existence of periosteal apposition during adulthood, its site specificity, magnitude and sex differences are considerable. In crosssectional studies, secular changes in bone size may obscure or exaggerate periosteal apposition. Secular increases in stature occur in one or both sexes, in some races but not others and may occur in the skeleton of the upper or lower body [62]. These secular trends can produce misleading inferences when increments or lack of increments in bone diameters are used as surrogates of periosteal apposition. For example, in cross-sectional studies, absence of an increment in periosteal diameter across age may not mean periosteal apposition was absent. Earlier born individuals (the elderly in a cross-sectional sample) may have been shorter and had more slender bones than later born individuals (young normals in a cross-sectional sample). When periosteal apposition occurs, earlier born persons with more slender bones have an increase in bone diameter that comes to equal that in later born persons (who have not yet had
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Figure 13.4 Porosity increases with age (left upper panel, Brockstedt et al 1993 [56]). This is associated with a decline in ultimate stress (adapted from Martin 1984 [53]) and reduction in toughness (adapted from Yeni et al 1997 [54]). Porosity is the result of enlargement and coalescence of intracortical pores (micrographs, Zebaze and Seeman, unpublished image).
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age-related periosteal apposition) leading to the flawed inference that there was no periosteal apposition in the cross-sectional sample. When comparisons are made between sexes (or races) in cross-sectional studies, if the truth is that periosteal apposition is greater in men than women but men have a secular increase in bone size and women do not, then the secular increase in size in men will blunt the increment in bone width across age in men and make it appear that the agerelated increase in vertebral and femoral neck diameters (and so periosteal apposition) is similar in women and men. Longitudinal studies are also problematic because changes in periosteal apposition during aging are small [42]. The precision of methods to determine bone diameter, usually bone densitometry, and problems with edge detection when bone mineral density is changing, limit the credibility of these measurements. Periosteal apposition is believed to increase as an adaptive response to compensate for the loss of strength produced by endocortical bone loss, so there will be no net loss of bone, no cortical thinning and no loss of bone strength [63]. In a seven-year prospective study of over 600 women, Szulc et al report that endocortical bone loss occurred in premenopausal women with concurrent periosteal apposition [47]. As periosteal apposition was less than endocortical resorption, the cortices thinned but there was no net bone loss because the thinner cortex was now distributed around a larger perimeter conserving total bone mass. Moreover, resistance to bending increased despite bone loss and cortical thinning because this same amount of bone was now distributed further from the neutral axis. So bone mass alone is a poor predictor of strength because resistance to bending is determined by the spatial distribution of the bone. Endocortical resorption increased during the perimenopausal period, yet periosteal apposition decreased – it did not increase as predicted if the notion that periosteal apposition is a compensatory mechanism is correct. The cortices thinned as periosteal apposition declined further. Nevertheless, bending strength remained unchanged – despite bone loss and cortical thinning because periosteal apposition was still sufficient to shift the thinning cortex outwards. Bone fragility emerged only after menopause when acceleration in endocortical bone resorption and deceleration in periosteal apposition produce further cortical thinning. As periosteal apposition was now minimal, there was little outward displacement of the thinning cortex so cortical area now declined as did resistance to bending. Endocortical resorption was reduced but not abolished in women receiving hormone replacement therapy while periosteal apposition was no different to untreated women; cortical thinning was reduced and the resistance to bending occurred but less than in untreated women. The periosteal envelope is regarded exclusively as a bone-forming surface. This is incorrect [7]. During
growth, bone resorption is critical for the in-wasting that produces the fan-shaped metaphyses [64]. Blizoites et al report that bone resorption occurs in adult non-human primates [7]. Femur specimens from 16 intact adult male and female non-human primates showed that periosteal remodeling of the femoral neck in intact animals was slower than in cancellous bone but more rapid than at the femoral shaft. Gonadectomized females showed an increase in osteoclast number on the periosteal surface compared with intact controls. If this information is correct, adult skeletal dimensions may decrease in size as age advances.
Sex differences in trabecular and cortical bone loss and fracture rates A greater proportion of women than men sustain fragility fractures during their lifetime. The reasons for this sexual dimorphism are not clear. Men have a larger skeleton than women and this is often held to be responsible for sex differences in fracture rates. The larger cross-sectional area of the vertebral body or a long bone in men does confer greater resistance to bending and torsional loads. Men and women have similar cortical thickness conferring a greater cortical area in men (because the cortex is fashioned around a larger perimeter). However, men also have larger muscle mass and greater weight so compressive stress (load/area) is similar in young adult men and women. The role of larger bone size as a cause of sex differences in fracture risk is also difficult to reconcile with finding that Asians have a smaller skeleton yet lower fracture rates than Caucasians and women with hip fractures and their premenopausal daughters have larger femoral neck diameter than controls [65]. Peak trabecular density (number and thickness) is similar in men and women. Thus, sex differences in bone size, cortical thickness or trabecular architecture do not appear to be obvious contributors to sex differences in fracture rates. The most tenable explanation for sex differences in fracture risk in old age is the sex difference in bone remodeling. BMU balance becomes negative due to a decline in the volume of bone formed by each BMU during aging in both sexes but, in women, at midlife, the volume of bone resorbed by each BMU increases. This probably does not occur in men unless they become estrogen deficient. In midlife, the intensity of remodeling increases in women due to menopause and remains elevated but not in men. Secondary hyperparathyroidism occurs in both sexes but this is superimposed on the high remodeling already present in women. Periosteal apposition is reduced in both sexes and may continue slowly but may be greater in men than in women, although this is still uncertain.
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The net structural consequences of the above changes in remodeling are as follows. For trabecular bone, the reduction in formation by the BMU without increased resorption by the BMU results in trabecular thinning in men while both reduced formation and increased resorption in women by each BMU causes loss of connectivity in women [66]. However, the same deficit in trabecular density produced by thinning (as occurs in men) produces less reduction in strength than produced by loss of connectivity (as occurs in women) [52]. The high bone remodeling with deeper excavation cavities in women produces greater numbers of stress concentrators in women than in men. If trabeculae are thicker in men, this will further protect from loss of connectivity and stress concentrating effects in men. While still unproven, a most important structural feature that is likely to account for sex differences in fracture risk is the greater structural deterioration of cortical bone in women than in men. The greater negative BMU balance and higher rater of remodeling in women on the intracortical surface is likely to produce more intracortical excavation, greater cortical thinning ‘within’ as coalescent excavated pores in cortex adjacent to the marrow produce cortical remnants and a remaining thin cortex adjacent to the periosteum has greater porosity but not to the point of producing cortical remnants. Direct evidence is still lacking because sex differences in cortical porosity have not been rigorously assessed in vivo at this time. Intracortical porosity has been reported to be lower in cortical bone in men than in women in in vitro studies [67]. As secondary hyperparathyroidism compounds the high remodeling due to sex hormone deficiency, it is also plausible that the exponential increase in intracortical surfaces is greater in women than in men so that there are more pores, more pores of irregular size and shape in women than in men and so, more stress concentrators, greater reduction in resistance to crack initiation and propagation through the cortex in women than in men. The increase in porosity has a profound negative effect on bone strength [53, 54]. Endocortical resorption is also likely to be less in men than in women for the same reasons; the number of remodeling sites on the endocortical surface will be less and each site will remove less bone in men than in women because the volume of bone resorbed is less. Marrow cavity expansion occurs in both sexes but whether it is greater in women than men is uncertain. Periosteal apposition is reported to be greater in men than in women in some [68], but not all [69], studies and it is unclear if any difference in periosteal apposition accounted for the sexual dimorphism in fragility fractures. Thus, methodological issues temper inferences possible regarding sexual dimorphism in bone strength [1]. The absolute risk for fracture in women and men of the same age and BMD is similar [70]. The lower fracture incidence in men than in women is likely to be the result of a lower proportion of elderly men than elderly women having
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material and structural properties (cortical thinning, porosity, trabecular thinning. loss of connectivity, microdamage) below the critical level at which the loads on the bone are greater than the bone’s net ability to tolerate them. Furthermore, structural failure occurs less in men because the relationship between load and bone strength is better maintained in men than in women [68].
Summary and Conclusion Modeling and remodeling are successful during growth, not aging. After completion of growth, there is a profound reduction in periosteal bone formation in both sexes. In midlife or earlier, a negative balance in the volumes of bone resorbed and formed by each basic BMU appears so remodeling on the endocortical, intracortical and trabecular components of bone’s endosteal surface produces structural decay but modestly because remodeling is slow. In midlife, remodeling rate increases and a transitory worsening of the negative BMU balance occurs as each BMU increases the volume of bone resorbed and reduces the volume of bone formed due to sex hormone deficiency in women so that structural decay accelerates, more rapidly from trabecular than cortical bone because its higher surface/volume ratio. Unlike trabecular bone where remodeling removes trabeculae and their surfaces, remodeling on intracortical and endocortical surfaces increases their surface so cortical bone becomes accessible to remodeling. Trabecular bone loss is more rapid than cortical bone loss during the first 15 years after menopause but the rapid loss of 20% of the skeleton (trabecular) and slower loss of 80% of the skeleton (cortical) results in a similar loss of each type of bone in absolute terms during the first 15 years of postmenopausal life. Men have no midlife acceleration in remodeling and the negative BMU balance is primarily due to reduced bone formation by the BMU so trabecular thinning (rather than perforation) dominates. Late in life in women, bone loss diminishes from the trabecular compartment as trabeculae and their surfaces are lost. Intracortical remodeling on haversian and Volkmann canal surfaces increases the number and area of pores, particularly in cortex adjacent to the marrow resulting in coalescence, trabecularization of the inner cortex so cortical thinning occurs from ‘within’. Thus, most bone loss during aging occurs after 60 years, is predominately cortical and originates from the intracortical (not endocortical) surface, particularly in cortex adjacent to the marrow cavity. Men have no midlife acceleration of remodeling so bone loss and structural decay proceed slowly until after 65–70 years when some men develop hypogonadism and/or secondary hyperparathyroidism. Whether the negative BMU balance is less in men than in women is unknown. The slower remodeling
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rate in men than women is probably the most important reason for the slower decay of the skeleton in men. The sex difference in fragility fractures is best explained by the earlier onset and longer duration of high remodeling in women than men. The combination of sex hormone deficiency and secondary hyperparathyroidism in women produce an additive or multiplicative effect and is the driving force behind structural decay in women. Our understanding of why or how bones fail at the material and structural level remains incomplete. This is an essential direction of inquiry if we are to identify women and men at risk for fracture, those not at risk and provide approaches to drug therapy based on the underlying structural basis of bone fragility.
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Chapter
14
Markers of Bone Remodeling and the Aging Skeleton Serge Cremers1, Christian Meier2 and Markus J. Seibel3 1
Division of Endocrinology, Department of Medicine, Columbia University, New York, USA Division of Endocrinology, Diabetes and Clinical Nutrition, University Hospital Basel, Basel, Switzerland 3 Bone Research Program, ANZAC Research Institute, The University of Sydney, Sydney, NSW, Australia 2
Introduction
variability that introduces substantial ‘background noise’. This latter fact is of particular relevance when it comes to the assessment of bone turnover in individual patients as opposed to the study of larger groups, e.g. in clinical trials. For an appropriate interpretation of any bone marker measurement, it is therefore important to identify pre-analytical (biological) and analytical (technical) factors that may affect variability. These factors often differ from marker to marker and, while some can be controlled by appropriate study design and sample handling, there always remain a number of factors that either require mathematical modeling or cannot be controlled at all [3–5, 13] (see also Chapter 3). This chapter will focus on age-related changes in markers of bone turnover in men, including their response to pharmacological interventions.
Osteoporosis has long been considered a disease which affects almost exclusively older women. However, over the past decade, we have learned to recognize bone loss and osteoporotic fractures as a growing health problem in older men [1, 2]. Given the morbidity, mortality and the cost associated with osteoporotic fractures in both genders, it is critical to identify at an early stage those individuals who may have, or soon will develop the disease. Measurement of bone mineral density (BMD) is widely used to identify men and women at risk of osteoporotic fracture. However, individual fracture risk is not determined by BMD alone but by the complex interaction of clinical risk factors, bone mineral density, bone geometry and microarchitecture, as well as bone turnover. Biochemical markers of bone turnover, i.e markers of bone formation and bone resorption, can be measured easily and non-invasively in serum and urine [3–5]. In postmenopausal women [6–10] and men [11], accelerated bone turnover (as measured by markers of bone formation and/or resorption) has been shown to be associated with increased fracture risk independent of BMD or clinical risk factors. Furthermore, as changes in bone turnover markers in response to therapeutic interventions occur much more rapidly than changes in BMD, bone markers may be useful in the monitoring of treatment, e.g. to evaluate treatment efficacy or patient compliance. One of the reasons why bone turnover markers are useful in assessing fracture risk and therapeutic efficacy is their ability quantitatively to reflect the actual rate of, and changes in, skeletal remodeling [12]. However, the simplicity, convenience and clinical sensitivity of these markers need to be balanced against a rather high degree of
Osteoporosis in Men
Age-related changes in bone marker levels Levels of most bone turnover markers are highest in the first three years of life [14], decrease during prepubertal childhood only rapidly to increase again to 4–10 times the adult levels during the pubertal growth spurt [15, 16]. In growing children and adolescents, serum and urine levels of bone turnover markers correlate well with somatic growth, thus, highest bone turnover markers are usually seen in children with the greatest growth velocity [17, 18]. Once somatic growth subsides, levels of most bone markers return to a low-level steady state. In women, bone marker levels reach a stable nadir during the age of 30–45 years. During and after menopause, bone marker levels rapidly increase to approximately 50–100%
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above premenopausal levels and, in many women, bone turnover remains elevated into the eighth and ninth decades [19–21]. This increase in bone turnover has been shown to be a major determinant of bone mass in older women [22–24]. In men, the pattern of age-related changes in bone markers is quite different from that observed in women. Markers of bone formation and resorption are high in men aged 20–30 years, which corresponds to the late phase of peak bone mass development. Thereafter, bone marker levels decrease, reaching their lowest levels between 50 and 60 years [25–29] (Figures 14.1 and 14.2). The relationship between bone remodeling and bone turnover markers becomes somewhat blurred during later stages of life, i.e. after the age of 50–60 years. Direct assessments of changes in bone mass and remodeling reveal that the pattern of age-related bone loss is remarkably different for the trabecular compartment when compared with the cortical compartment. Cross-sectional and longitudinal studies have established that, in both sexes,
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Figure 14.2 Age-related changes of 24-h urinary excretion of deoxypyridinoline (Dpyr) and its fractions; (A) tDpyr, (B) fDpyr 0 15 peptide-bound 25 35 [28]. 45 55 65 75 and (C) Dpyr 85
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trabecular bone loss begins early during adult life, whereas cortical bone loss seems to become evident later (e.g. after mid-life), with overall decreases in volumetric BMD being smaller in men compared to women. In men, there appears to be ongoing periosteal apposition with age, which leads to an increase in bone cross-sectional area. However, the pronounced increase in endocortical area results in a net decrease in cortical area [30]. Histomorphometric analyses of bone biopsies have also shown that physiological bone loss with age in males is characterized by a decrease in the cancellous bone volume as well as cortical width [31]. Trabecular separation is increased but, in contrast to postmenopausal women, trabecular connectivity seems to be preserved. Age-related bone loss in males appears to be the result of low bone formation, although a trend toward an increase in activation frequency has also been described by some authors [31]. In 43 healthy men, static histomorphometric parameters, such as cancellous bone volume and osteoblast–osteoid interface, decreased by 40% and 19%,
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C h a p t e r 1 4 Markers of Bone Remodeling and the Aging Skeleton l
respectively, between 20 and 80 years of age [32]. Dynamic bone histomorphometric parameters, such as double and single labeled osteoid surface, decreased by 18% over the same period and serum osteocalcin levels were significantly correlated with dynamic parameters of bone formation [32]. In contrast, neither static nor dynamic histomorphometric parameters of bone resorption (e.g. osteoclast surface, eroded surface) changed with age in this population sample of healthy men. Interestingly, however, these histological and histomorphometric changes were not reflected by corresponding changes in the levels of bone turnover markers. While there is general agreement on the pattern of agerelated changes of bone turnover markers in adult men between 20 and 60 years of age, data on markers in men over the age of 60 years are largely discordant. Based on recent cross-sectional studies, concentrations of bone formation markers remained either unchanged [27, 28], decreased [26, 33] or increased [25, 34, 35] with age in men 60 years or older. Most studies evaluating age-related changes in bone resorption markers observed an increase in serum and urinary indices [25–28, 35, 36] (see Figure 14.2). However, this was not confirmed in other population-based studies which reported no age-related change in resorption indices [29, 37]. Clarke et al [32] studied a cohort of healthy men by both bone histomorphometry and biochemical markers. In this study, bone resorption, as measured by urinary deoxypyridinoline (DPD), did not change with age, confirming the histomorphometric finding of unaltered osteoclast function with increasing age in these men [32]. These results are in contrast to some of the previously mentioned cross-sectional studies reporting an age-dependent increase in serum and urinary indices of bone resorption [25–28, 35, 36]. A careful analysis of the published data provides clues that may help to explain some of these discrepancies. Differences in results may be related to diverse population characteristics and sample sizes, to the use of marker assays with different specificities, to age-related changes in renal and hepatic function and, lastly, to the inclusion of men with osteoporosis [11]. Men with idiopathic osteoporosis are histomorphometrically characterized by increased bone resorption with an increase in eroded surfaces of up to 90% when compared with age-matched controls [31]. Hence, the observed increase in biochemical markers of bone resorption in population-based studies may also be caused by the heterogeneity of men investigated, including men with osteoporosis. Bone formation markers, such as serum osteocalcin, N-terminal propeptide of type I procollagen (PINP) and bone alkaline phosphatase (ALP) have been found to be negatively associated with estimates of endosteal bone loss in elderly men while being unrelated to parameters of periosteal apposition (calculated from dual energy x-ray absorptiometry (DXA)). Thus, these markers seem to reflect endosteal bone remodeling but not periosteal bone formation in elderly men [38].
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Renal function deserves special attention as certain biochemical markers of bone turnover are cleared via the kidney (e.g. collagen cross-links and cross-linked telopeptides such as C-terminal telopeptide of collagen I (ICTP), serum collagen type I cross-linked C-telopeptide (CTX) or collagen type I cross-linked N-telopeptide (NTX)). Consequently, age-associated changes in glomerular filtration rate are bound to affect the urinary and serum concentrations of such markers. Thus, a decrease in renal function will result in an artificially low urinary excretion of a marker when it is expressed as 24-hour output. Conversely, when corrected by urinary creatinine, marker levels can be falsely increased due to a decrease in both creatinine filtration and muscle mass [39]. Furthermore, serum concentrations of any marker cleared by renal mechanisms may be hard to interpret, as both changes in clearance and disease-related alterations in bone turnover can affect the actual marker level. Taken together, it remains controversial to what extent biochemical markers of bone resorption and formation change as a function of age in men over 60 years. Observational studies investigating age-dependent changes in bone marker levels indicate that there seems to be an imbalance in bone turnover in elderly men with increased bone resorption and stable bone formation after the age of 60 years. As biochemical markers have been shown to be negatively correlated with BMD [25, 28], this imbalance in bone turnover may, at least in part, be responsible for the age-related bone loss in men. However, confounding factors, such as population characteristics, specificity of bone marker assays, as well as estimates of renal and liver function, have to be taken into account when evaluating agedependent changes in bone turnover.
Bone markers, bone loss and fracture risk in aging men Prospective data generally show poor correlations between bone turnover markers and bone loss in men [40–44]. The situation is similar to that in women, where bone turnover markers have been shown to be poor predictors of bone loss [45]. Recently, however, accelerated bone turnover (assessed by biochemical markers) has been shown to be associated with greater endosteal bone mineral loss (but not with fracture risk) [46]. There are limited data on bone turnover markers and their relation to fracture risk in elderly men [11, 46–48]. Some studies have shown that the bone resorption marker ICTP in serum [11] or the ratio of carboxylated to total serum osteocalcin [46] are associated with the risk of osteoporotic fracture independent of BMD. In contrast, another study found that high bone turnover was associated with bone loss but not with the risk of incident fractures [46]. Hence, the role of bone turnover markers in the prediction of accelerated bone loss or fractures currently remains unclear.
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Figure 14.3 Mean percent change from baseline for serum osteocalcin (OC), N-terminal propeptide of type I procollagen (PINP) and collagen type I cross-linked N-telopeptide (NTX) in men receiving alendronate alone (square), human parathyroid hormone (PTH)(1–34) alone (diamond) or both (circle). PTH was commenced at month 6. Data are shown as mean and SE. Error bars that are not visible are contained within the symbols [52].
The response of bone turnover markers to pharmacological interventions in aging men Pharmacological options for therapeutic interventions in male osteoporosis include oral and intravenous bisphosphonates, teriparatide, calcitonin, thiazide diuretics, androgens and supplementation with calcium and/or vitamin D [30]. However, most of the published randomized controlled trials specifically addressing male populations are relatively small, rely on BMD endpoints and usually lack in power confidently to address drug effects on fracture risk in men. It seems, though, that for the most common osteoporosis therapies (i.e. the bisphosphonates and teriparatide), the effects in men are similar to those in women, including the effects on bone turnover markers (Figure 14.3) [28–30, 49, 50–52]. Interestingly, the response of bone turnover markers to these drugs seems independent of any of the known age-related factors in osteoporotic men, such as serum insulin-like growth factor I (IGF-I), IGF binding protein 3 (IGFBP-3), estradiol and free testosterone levels [50, 53]. Part of the changes in bone turnover markers as observed during treatment with either of these drugs is related to calcium and vitamin D supplementation. As described earlier, age-related changes in bone turnover markers show inconsistencies among studies, but they are also relatively small compared with treatment-induced changes. In men with a mean age of 63 years, daily alendronate 10 mg decreased uNTX/Cr by 59%, relative to baseline, as opposed to a reduction of only 9% in the placebo group receiving calcium and vitamin D [49]. In men aged 46–85 years, daily subcutaneous injections of teriparatide increased serum PINP concentrations by more than 1000% by month 12 (see Figure 14.3), illustrating the even more pronounced changes in BTM during anabolic treatment with parathyroid hormone (PTH) [52]. Age-related changes are thus marginal
relative to drug-induced changes and bone turnover markers can therefore be used for monitoring of treatment in men. Treatment with sex steroids or therapies that alter sex steroid levels clearly affect bone turnover markers in aging men. These changes are complex and depend, among other factors, on pre-treatment sex steroid levels and the dose administered [54–57]. (The effects of steroid treatment in aging men are discussed in Section 6).
Conclusion Aging in men affects bone turnover and its corresponding markers in a number of ways, not all of which are related to changes in skeletal metabolism. As a consequence, distinct changes are found in bone turnover and morphology in aging men, but changes in bone turnover marker data show inconsistencies among studies. At the moment, the role of bone turnover markers in predicting accelerated bone loss and fracture risk remains unclear. In contrast, bone turnover markers faithfully reflect treatment-induced changes in bone turnover and may therefore be used to monitor treatment. Additional prospective studies in larger cohorts of men are warranted further to investigate the relationship between bone turnover markers, bone loss and fracture risk. Furthermore, the clinical usefulness of bone turnover markers to assess and perhaps even predict treatment efficacy in men with osteoporosis requires further study.
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Chapter
15
Alterations in Mineral Metabolism in the Aging Male Bismruta Misra and Shonni J. Silverberg College of Physicians and Surgeons, Columbia University, New York, USA
Introduction
at a slower rate than do osteoblasts (2–5%) and apoptosis reflects a cumulative view of osteocyte death, because the cellular debris cannot be removed by phagocytes. Osteocyte apoptosis precedes the recruitment of osteoclasts to regions where osteocytes have died after unloading or application of excessive strain [3]. Finally, the osteoblast–osteoclast interaction also changes with aging. Changes in physical activity and mechanical loading, as well as lower levels of sex steroids, result in diminished effects upon osteoblasts. This, in turn, results in decreased secretion of osteoprotogerin. In addition, there is increased expression and secretion of receptor activator of nuclear factor-kappa B ligand (RANKL), important interleukins such as IL-1, IL-6, IL-11, and tumor necrosis factor-alpha. In aggregate, these changes directly stimulate greater osteoclast formation and activity. The imbalance of decreased osteoprotogerin and increased RANKL permits binding of RANKL to RANK, leading to increased osteoclastogenesis and bone resorption [2]. The cumulative effect of these cellular changes in aging bone leads to an imbalance of of osteoblasts and osteoclasts, ultimately favoring increased osteoclastic activity and bone resorption.
Although osteoporosis is more common in women than in men, an increasing prevalence in men has been recognized over the past several decades. After peak bone mass is achieved, there is a decline in bone mass of approximately 0.5%/year [1]. Alterations in the synthesis, metabolism and responsiveness of vitamin D and parathyroid hormone (PTH) are intrinsic to the aging process. While such changes in vitamin D and PTH could be causally related to the age-associated changes in bone mass, some hormonal changes may be adaptive, serving to protect the aging skeleton from further weakening. This chapter will review how age-related changes in mineral metabolism, from the cellular to the hormonal level, are involved in the pathogenesis of osteoporosis in men.
Cellular changes An exhaustive review of cellular changes in bone associated with advancing age is beyond the scope of this chapter. Briefly, aging is associated with changes in the mobility and differentiation of mesenchymal stem cells. In the bone marrow, osteoblasts and adipocytes share the same precursors. With aging, adipogenesis increases at the expense of osteoblastogenesis. The reduction in osteoblastogenesis results in the formation of fewer active osteoblasts. Increasing adipogenic differentiation also leads to fewer differentiated osteoblasts. Finally, aging brings about increased osteoblast apoptosis [2]. Osteocyte apoptosis also appears to play a role in the cellular changes involved in osteoporosis. Osteocytes die
Osteoporosis in Men
Age-related hormonal changes in mineral metabolism Vitamin D Alterations in vitamin D play a key role in the development of age-related bone loss. Most, but not all, studies report a fall in the circulating concentration of vitamin D with advancing age. Although 25-hydroxyvitamin D levels
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(25(OH)D) have been reported to be significantly higher in males than females at all ages, levels decline with increasing age in both sexes [4]. The pivotal role of vitamin D in the development of osteoporosis could result from abnormalities in vitamin D availability, synthesis or metabolism, or from alterations in responsiveness to vitamin D. Possible abnormalities include deficient vitamin D intake; abnormal production of 25(OH)D or 1,25-dihydroxyvitamin D (1,25(OH)2D), the active form of the vitamin; altered intestinal vitamin D receptor number or sensitivity; and acquired resistance to vitamin D. Individuals deficient in calcium as a result of such an abnormality will be at greater risk for an imbalance in the dynamic interplay between bone formation and bone resorption. Aging is associated with reduced availability of vitamin D from its two natural sources: diet and sunlight. Although current recommendations of the National Academy of Science for those 65 years of age include a minimal daily requirement for 600 IU of vitamin D [5], many feel that significantly higher intakes are appropriate in older individuals. Despite this, many older Americans choose diets with low vitamin D content, with reports suggesting a mean intake of approximately 75–100 IU of vitamin D per day [6]. Furthermore, vitamin D absorption from the gastrointestinal tract may be impaired in the elderly. Some studies show that intestinal absorption of vitamin D does not change with age [7], while others show it to be decreased [8]. In women, a decline of up to 40% in absorption of vitamin D in the distal ileum has been reported to occur with advancing age [9]. An age-related reduction in intestinal vitamin D receptor concentration has been observed in intestinal biopsies obtained from women spanning the wide age range of 20–87 years [8]. If vitamin D receptor concentration were limiting, lower receptor abundance would lead to impaired calcium absorption. Pattanaungkul et al studied the association of 1,25(OH)2D concentrations with fractional fasting calcium absorption [10]. Interestingly, the strong relationship between the two seen in young subjects did not persist in an elderly population. Moreover, the slope of the relationship between these two indices was significantly greater in the young than in the elderly. While these observations have not been fully reproduced in men, they do support the hypothesis that the elderly may be relatively resistant to the physiological actions of 1,25(OH)2D on intestinal calcium absorption. Furthermore, aging may be associated with altered responses to vitamin D supplementation. Harris et al compared plasma 25(OH)D responses to vitamin D2 supplementation (45 g/day for three weeks) in older (age 65–73 years) and younger men (age 22–28 years). The younger men had a 90% greater increase in 25(OH)D levels than did the older men in response to the same dose of vitamin D [11]. The other important source of vitamin D is the skin, where UVB rays convert 7-dehydrocholesterol to previtamin D. Cutaneous production of vitamin D decreases
with advancing age [12]. Production of 7-dehydrocholesterol levels in the epidermis fall by 50% between 20 and 80 years of age and the response in serum vitamin D after one minimal erythemal dose of UVB radiation is reduced nearly four-fold in elderly male and female subjects [13]. In addition, the prevalent use of sunscreen and the avoidance of sun exposure compound the problem of producing vitamin D in the skin. There is no evidence that the liver loses its capacity to convert vitamin D to 25(OH)D with aging, unless there is severe, advanced liver disease [14, 15]. On the other hand, a decline in the ability of the kidney to form 1,25(OH)2D, the active metabolite of vitamin D, does occur with age and has long been implicated as a possible mechanism for agerelated osteoporosis [16]. In men, the serum 1,25(OH)2D concentration has been variously reported to decrease with age or remain unchanged [17–19]. This discrepancy may be explained by the inclusion of different proportions of sick and healthy elderly subjects in different studies. Those in poor health, who may be living in nursing homes, have both lower sun exposure and lower vitamin D levels. In healthy elderly men, the production rate and metabolic clearance were noted to be normal [19]. Even though the levels of 1,25(OH)2D may be normal in healthy elderly subjects, the sensitivity of the renal 1-alpha hydroxylase to trophic factors may be reduced [20]. Older individuals respond to the stimulatory effects of PTH on 1,25(OH)2D production less well than young subjects did (discussed in further detail below). Studies in women and osteoporotic subjects found that serum PTH and creatinine increased with age, but that 1,25(OH)2D levels did not rise as expected with parathyroid hormone increases [21, 22]. Responsiveness to PTH decreased with age, but significant reductions were not noted until after age 70 [23–25]. Halloran et al studied the response to PTH infusion in healthy elderly men. They reported that the time course of the increase in 1,25(OH)2D was delayed in older men, but that the final magnitude of the increase was similar to that seen in young men (Table 15.1) [26]. In summary, the explanation for the role of age-related alterations in vitamin D metabolism in the pathogenesis of osteoporosis is clearly multifactorial. Aging is associated with reduced availability of vitamin D from its two natural sources,
Table 15.1 Response of serum 1,25(OH)2D to exogenous infusion of hPTH(1–34) for 24 hours in healthy young and elderly men Young (n 9) Elderly (n 8) Age (year)
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Serum concentration (pg/ml) Basal 31 3 After 24-hour infusion of PTH 47 3
32 4 44 5
Values are mean SE. From Halloran et al [26]
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diet and sunlight, a reduction in intestinal vitamin D receptor concentration, possible altered responses to vitamin D supplementation and incompletely characterized alterations in renal responsiveness in the production of 1,25-dihydroxyvitamin D. Those who develop osteoporosis may have further abnormalities superimposed upon these sequelae of the aging process.
Parathyroid Hormone Parathyroid hormone levels increase with advancing age [19, 27, 28]. Secondary hyperparathyroidism is expected as a result of the age-associated decreases in vitamin D levels and declining renal function. Decreasing 1,25(OH)2D concentration as a function of impaired renal 1-alpha hydroxylation of 25(OH)D would relieve the inhibitory effects of this metabolite on the parathyroid hormone gene. Although a component of the increase in circulating levels of parathyroid hormone with aging clearly reflects declining renal
function, elevated values also occur in older individuals whose renal function remains entirely normal. Halloran et al studied young and elderly men with normal renal function in this regard. Despite normal serum ionized calcium activity, serum 1,25(OH)2D and urinary calcium excretion, basal serum parathyroid hormone was 1.5-fold higher in the elderly as compared with the younger men [19]. Most studies have demonstrated the increases in serum parathyroid hormone concentration as a continuous relationship with age (Figure 15.1) [27, 28]. PTH levels were elevated in 65% of male and female centenarians, with the average PTH concentration twice the upper limit of normal [29]. Despite the increase in PTH levels with aging, the parathyroid gland has a near constant glandular weight between the ages of 30 and 90 [30]. The rise in PTH is associated with a threefold increase in the minimum and maximum secretory rates [31, 32]. There are two hypotheses to explain the increase in parathyroid hormone concentrations with age. The first links, in a causal way, the increase in parathyroid
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Figure 15.1 The relationship of PTH and age and creatinine clearance. (Reproduced from Sherman SS, Hollis BW, Tobin JD. Vitamin D status and related parameters in a healthy population: the effects of age, sex and season. J Clin Endocrinol Metab 1990;71:405-13 [27] with permission).
Osteoporosis in Men
hormone with age-related bone loss. An alternative hypothesis suggests that the increase in hormone concentration is protective against age-related bone loss. The work of Silverberg et al provides additional evidence for altered PTH responsiveness with aging [21]. Oral phosphate was used to induce a mild hypocalcemic challenge to assess the ensuing increase in PTH concentration. The study was first conducted in younger and older subjects who had no evidence of osteoporosis. While the serum phosphorus concentration rose and the serum calcium level fell to the same extent, young subjects showed a 43% increase in PTH concentration over baseline values, whereas older women showed a much more exuberant parathyroid response, with a 2.5-fold increase over baseline levels. This protocol set up two opposing stimuli with respect to 1,25(OH)2D; increased phosphorus, which would tend to inhibit its production, and increased PTH, which stimulates the conversion of 25(OH)D to the active moiety. In both younger and older subjects, the 1,25(OH)2D concentration did not change. These data were interpreted to suggest that older, normal subjects require more PTH for a given hypocalcemic challenge to maintain 1,25(OH)2D status. Such a formulation is consistent with the reduced renal capacity to form this metabolite with age. It is also possible that the aging skeleton requires a greater amount of PTH to achieve effects that are seen at lower levels in younger subjects. When the protocol was repeated in a group of postmenopausal women with osteoporosis, the same increase in serum phosphorus concentration and reduction in serum calcium concentration was observed [22]. However, in contrast to the marked increase in PTH seen in their agematched normal counterparts, the osteoporotic women demonstrated only a modest 43% increase (Figure 15.2). Although this increase in PTH was sufficient in younger individuals to prevent the inhibitory effects of phosphorus on 1,25(OH)2D production, it did not suffice in these osteoporotic women, in whom 1,25(OH)2D concentrations fell by 50%. These observations are consistent with the presence of an abnormality in PTH secretory function in osteoporosis. Osteoporotic women thus have both agerelated reductions in their ability to form 1,25(OH)2D and a superimposed deficiency in parathyroid responsiveness. Unfortunately, similar data are not available in older men. An alternative explanation for the age-related increase in PTH could be that there is an alteration in the calcium setpoint. Ledger et al investigated this question using a provocation challenge in women and were unable to demonstrate any age-related increase in the calcium setpoint for PTH secretion [31]. When postmenopausal women with osteoporosis were studied, however, differences did emerge. Using infusions of the synthetic peptide, human parathyroid hormone (1-34) to assess suppressibility of endogenous human PTH, the data of Cosman et al were consistent with a higher calcium set point in osteoporotic women [33]. The data are somewhat different in men.
Osteoporotic Control Young normal
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Figure 15.2 The effect of a hypocalcemic stimulus on the parathyroid hormone response in osteoporotic and non-osteoporotic postmenopausal women and in young normal subjects. (Reproduced from Silverberg SJ, Shane E, de la Cruz L, Segre GV, Clemens TL, Bilezikian JP. Abnormalities in PTH secretion and 1,25-dihydroxyvitamin D3 formation in women with osteoporosis. N Engl J Med 1989;320:277-81 [22] with permission).
Portale et al demonstrated that fasting and mean 24-hour whole blood calcium concentrations were not different in healthy young and elderly men, suggesting that hypocalcemia is not required to sustain the age-related elevation in serum PTH in men. However, the age-related increase in serum PTH was associated with an increase in the concentration of calcium required to suppress half-maximally PTH release [32]. Essentially, the setpoint for PTH responsiveness to calcium was shifted to the right. These results are consistent with a protective effect of PTH in the pathogenesis of osteoporosis in men. In summary, although secondary hyperparathyroidism is expected as a result of the age associated decline in both vitamin D levels and renal function, increased parathyroid hormone concentration is seen in the elderly regardless of renal function. The increase in parathyroid hormone concentrations with age could contribute to age-related bone loss or it could be protective against age-related bone loss. The latter hypothesis is supported by data showing that non-osteoporotic elderly individuals secrete excess PTH in order to compensate for reduced renal capacity to form 1,25OHD, while osteoporotic women are unable to mount a compensatory increase in PTH. Other data, however, demonstrate that the setpoint for PTH responsiveness to calcium is shifted to the right in aging men, which suggests that PTH may play a protective role in the pathogenesis of osteoporosis in men. Efforts are ongoing to characterize more fully the role of parathyroid hormone aging males.
Sex steroids Sex steroids are important for skeletal growth and for the maintenance of both the female and the male skeleton [34, 35]. This topic is covered in detail elsewhere and discussion
C h a p t e r 1 5 Alterations in Mineral Metabolism in the Aging Male l
here is limited to interaction of sex steroids with hormones of mineral metabolism with aging. It appears that declining estrogen levels play a significant role in mediating age-related bone loss and fracture risk in men. Although serum total and free testosterone decrease with advancing age [36], because most men do not develop overt hypogonadism with aging, the prevailing opinion had been that sex steroid deficiency was not a major cause of age-related bone loss in men. It is now clear that the failure of earlier studies to document decreased serum levels of total sex steroids was caused by the failure to account for the greater than twofold rise in serum sex hormone binding globulin (SHBG) with advancing age [37]. That serum levels of free or bioavailable sex steroid do substantially decrease with aging [37, 38] was confirmed by data from the Mr Os study, demonstrating that serum free testosterone and free estradiol declined significantly with age, in association with increased serum SHBG [39]. Data have not supported the traditional assumption that bone loss in men is related to the decrease in bioavailable testosterone. Instead, bone density (BMD) in men is most closely associated with estradiol levels [37–39]. In a study of the relative contributions of testosterone and estrogen on bone in elderly men, subjects (mean age 68 years) were placed on a long-acting gonadotrophin-releasing hormone (GnRH) agonist (leuprolide) and an aromatase inhibitor (letrozole) in addition to replacement testosterone and estradiol. Then, both sex steroids, testosterone only or estrogen only were discontinued and bone turnover was evaluated in all groups. Bone resorption markers were unchanged in men receiving both hormones and increased significantly in the absence of both hormones. Estrogen prevented the increase in bone resorption markers, whereas testosterone alone had no significant effect. In contrast, while bone formation markers decreased in the absence of both hormones, either estrogen or testosterone alone maintained these levels. It appears that, in aging men, estrogen is the dominant sex steroid regulating bone resorption, whereas both estrogen and testosterone are important in maintaining bone formation [40]. There are links between the decline in sex steroids with aging and alterations in hormones of mineral metabolism. The age-related increase in serum PTH is eliminated in postmenopausal women receiving long-term estrogen therapy. In a comparison of premenopausal and estrogendeficient postmenopausal women, serum PTH increased as a function of age [41]. However, this age-related increase in PTH was not seen in the postmenopausal women receiving long-term estrogen therapy. Additionally, estrogen treatment led to a similar suppression of markers of bone formation and resorption in both the early (20 years) and late (20 years) postmenopausal women. Estrogen deficiency could therefore be responsible not only for the increase in bone turnover in early postmenopausal women, but also indirectly for the secondary hyperparathyroidism and increase in bone turnover found in late postmenopausal
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women. Residual serum estrogen levels are thus important determinants of bone resorption in postmenopausal women. Recently, Leder et al evaluated the effects of male hypogonadism on PTH sensitivity and response [42]. They studied men (age 50–82) with locally advanced prostate cancer but no bone metastases. Subjects received PTH infusions both prior to initiation of GnRH agonist therapy and again after confirmation of GnRH agonist-induced hypogonadism. Bone formation markers and serum 1,25(OH)2D showed similar increases in response to PTH before and after leuprolide therapy. However, the bone resoprtion marker, urinary N-telopeptide (NTX), increased to a greater extent in the hypogonadal state. The authors conclude that, in elderly men, suppressed sex steroids increase responsiveness to the bone resorbing effects of PTH. A follow-up study by the same group assessed both testosterone and estrogen withdrawal on PTH sensitivity in younger men [43]. Healthy men (age 20–45) were treated with GnRH agonist, an aromatase inhibitor and subsequent hormone replacement, creating four study groups: testosterone and estradiol sufficient subjects, testosterone and estradiol deficient subjects, testosterone sufficient but estradiol deficient subjects and testosterone deficient but estradiol sufficient subjects. The groups received 24-hour PTH infusions at baseline and after 6 weeks of therapy. In all but the eugonadal group, serum NTX measured before PTH infusion was significantly higher after 6 weeks of therapy. Pre-infusion concentrations of osteocalcin and procollagen I N-terminal propeptide (PINP) fell significantly in the group that was testosterone sufficient but estrogen deficient. All groups demonstrated increases in NTX and C-terminal collagen cross-links (CTX) during PTH infusion. In the group that was both testosterone and estrogen sufficient, bone resorption increased to similar extents at week 0 and week 6. However, in all of the other groups, the increases in NTX were significantly greater at week 6 than baseline. This study suggests that deficiencies in either or both sex steroids increase the skeletal sensitivity to PTH, a finding that may play a role in the pathogenesis of osteoporosis in men. There are limited data on parathyroid hormone levels or glandular function in hypogonadal men treated with testosterone. Early studies of testosterone replacement in elderly hypogonadal men found no effect on serum PTH, but did show significant increases in osteocalcin levels [44]. A meta-analysis of randomized clinical trials of men treated with testosterone concluded that testosterone had a modest effect in reducing bone resorption markers and no significant effects on bone formation markers [45]. Alterations in sex steroids with aging could also affect vitamin D status in the elderly. A recent cross-sectional study found that vitamin D binding protein levels were higher in women than in men, although women had lower 25(OH)D levels. Most other cross-sectional studies have demonstrated no differences in vitamin D binding protein levels with aging in either men or women [46]. Estrogen
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increases serum vitamin D binding protein, thereby reducing the fraction of free 1,25(OH)2D [47]. Whether testosterone has similar effects and whether the fall in estrogen and testosterone with age influences the circulating levels of vitamin D binding protein and free 1,25(OH)2D is unknown. In summary, serum free testosterone and free estradiol decrease significantly with age and declining estrogen levels in particular play a significant role in mediating agerelated bone loss and fracture risk in men. The decline in sex steroids with aging is also associated with the increased skeletal sensitivity to PTH, which may be important in the pathogenesis of osteoporosis in men.
Growth Hormone, Insulin-like Growth Factor system Aging is associated with alterations in other hormones that could impact upon skeletal integrity. Growth hormone (GH), insulin-like growth factor (IGF-I) and insulin-like growth factor binding protein-II (IGFBP-II) decrease with advancing age in men and women [48–50]. The amplitude and frequency of GH secretory pulses also diminish with aging, leading to decreased hepatic IGF-I production [51]. While serum IGF-I decreases markedly with age, there are less dramatic declines in serum IGF-II [52]. Moreover, in men between the ages of 20 and 40 years, changes in trabecular microstructure, particularly the conversion of thick trabeculae into more numerous, thinner trabeculae, are closely associated with declining IGF-I levels [53]. Although agerelated decreases in circulating IGF-I levels and/or the activity of the IGF system may contribute to impaired bone formation with aging, these changes may also explain, at least in part, the age-related increase in circulating sex hormone binding globulin (SHBG) levels [37]. IGF-I inhibits in vitro SHBG production by hepatocytes [54]. In men, serum SHBG levels are inversely correlated with IGF-I levels [55]. It is therefore possible that age-related changes in the GH/IGF system could influence the activity of sex steroids through its effect on circulating SHBG levels. It has been hypothesized that the reduced bone density in both male and female patients with adult growth hormone deficiency (AGHD) is mediated by reduced parathyroid gland sensitivity. White et al compared AGHD patients with low and normal bone mineral density. Those with low bone density had significantly lower mean PTH and 1,25(OH)2D levels, consistent with reduced renal PTH effect [56]. Postmenopausal osteoporotic women had lower than expected IGF-I levels, which increased significantly with growth hormone administration. In addition, with treatment, PTH levels declined and PINP concentration increased, consistent with the hypothesis that GH may influence PTH sensitivity [57]. The effect of the growth hormone-IGF system on the skeleton could also, in part, be mediated by its effect on vitamin D production. GH and IGF-I treatment in vivo stimulate
1,25(OH)2D production. This action of GH appears to be mediated through IGF-I. IGF-I administration in vitro enhances 1,25(OH)2D synthesis, while administration of GH does not [58]. Serum calcitriol levels increase in both male and female elderly subjects treated with GH [59].
Calcitonin Serum calcitonin levels are higher in men than in women and have been reported either to decrease [60, 61] or remain unchanged with advancing age [62]. There is a greater increase in serum calcitonin in young compared to elderly women in response to a calcium challenge, but there are no studies evaluating this in men [61]. Gennari et al evaluated the relationship between estrogen and calcitonin in postmenopausal osteoporosis in a double-blind placebo-controlled study [63]. They evaluated the effects of l-year estrogen–progesterone treatment on calcitonin secretory reserve, as evaluated by calcium infusion test. Blood levels of calcitonin showed a progressive increase during the study period in the hormone-treated group, with a significant increase in the response to the calcium stimulation test. This was taken to suggest that estrogen may modulate calcitonin secretion, but more data are obviously needed in this regard. No similar data are available in men.
Summary Mineral metabolism changes in important ways in the aging male and some of these changes are implicated in the pathogenesis of osteoporosis. Age-associated alterations in vitamin D status are caused by decreased formation in the skin, decreased gastrointestinal absorption and decreased conversion to the active moiety in the aging kidney. Aging is also associated with increased and altered sensitivity to PTH. Some of these changes are adaptive and loss or absence of these adaptations may be associated with accelerated bone loss. The decline in sex steroids with aging has direct skeletal consequences. In addition, these declines may mediate an exaggerated response to parathyroid hormone, leading to enhanced bone resorptive activity. Age-related reductions in growth hormone/IGF-I may also have skeletal consequences, via effects on sex hormone binding globulin as well as through other mechanisms that are yet to be elucidated. Many questions remain with regard to the nature and consequences of hormonal changes on mineral metabolism in the aging male. First, it is not clear whether the data on hormonal changes in aging collected in women are applicable to the aging male. Clarification is also needed as to what constitutes the ‘normal’ physiologic responses of aging and what further changes are associated with the development of accelerated bone loss, or osteoporosis. In this regard, the aging male remains a fertile ground for further research.
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Chapter
16
Changes in Bone Size and Geometry with Aging Pawel Szulc INSERM 831 Unit, University of Lyon, Hôpital Edouard Heriot, Lyon, France
Radial bone growth in children and adolescents
femoral shaft widens faster than humerus probably due to a greater stimulation during bipedal walking. In most studies, bone width and radial growth velocity at a given skeletal site are similar in prepubertal boys and girls [4]. However, in some studies, late prepubertal boys have a larger radius than age-matched girls [5], which may result from higher physical activity in boys than in girls. Bone widening accelerates again at the beginning of the pubertal spurt [6] (Figure 16.1). In boys, this acceleration starts later, thus, boys may enter the pubertal spurt with slightly longer and larger bones. Then, pubertal radial growth in boys is faster and lasts longer than in girls [7]. Consequently, mid- and late-pubertal boys have wider bones and, despite longer bones, higher width/length index.
In children and adolescents, radial growth is linked to longitudinal growth and follows a similar age-related pattern [1]. Radial growth is crucial for bone to maintain bending strength and an ability to withstand mechanical loads. In newborns and infants, average width of different bones is similar in both sexes [2, 3]. In infants, radial growth is rapid and similar in both sexes, but varies according to the skeletal site, e.g. widening of the humerus (in mm/year) is faster than that of the femoral shaft, probably due to a greater stimulation during walking on all fours [3] At the age of 3, radial growth slows by about 50%. At this age,
Girls
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0 5
10 11.27
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Figure 16.1 Age-dependency of the total cross-sectional area (CSA) of the radius of 177 boys and 185 girls aged 6–18 years. Results in adults aged 29–40 years are presented as vertical bars (mean SD). The age 11.27 years – age of the maximal velocity of the increase in total CSA in girls. In boys, the age-related increase in total CSA was linear. (Reproduced from Neu et al Osteoporos Int 2001;12:538-47 [6] with permission of the Springer Verlag). Osteoporosis in Men
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Radial bone growth during aging After completion of growth, young men have larger bones than women after adjustment for body height and weight [8]. Although men have proportionally longer lower limbs and shorter trunk (for the same height) than women, men also have wider long bones after adjustment for bone length (e.g. femoral shaft) and wider vertebral bodies (adjusted for body height or for the vertebral height). That men have larger (wider) bones means that men’s bones have greater external diameter, greater external perimeter and greater cross-sectional area (CSA) is obvious, but it is important to understand seemingly discordant data concerning the difference in age-related periosteal expansion in men and women. As men have larger bones, an increase in the external diameter by the same absolute value may correspond to a slightly higher increase in CSA in men (because bone is distributed around a larger perimeter) but to a slightly greater relative increase in external diameter and in CSA in women (because initial values used for calculation of the percentage are lower in women). Periosteal apposition continues during adult life at various skeletal sites, regardless of the age, ethnic group, study design and measurement method [9, 10]. Age-related changes in bone size assessed cross-sectionally were compared at various skeletal sites in the same cohort [11]. For most of the skeletal sites (except tibia shaft), the increase is higher in men than women both in the absolute (cm2) and relative terms (percentage of the young adult values), also when adjusted for body height [11]. It supports the idea of the higher periosteal expansion in men. However, the extent of periosteal expansion and sex difference varies according to the skeletal site and, partly, to the way of expression of the results, i.e. absolute or relative values [11].
4.5
(cm)
Women
Chinese r = 0.20p =3
2
>=3
1
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2
Total Points 0
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60
80
100
120
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0.2
0.3
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0.9
10-year risk 0.01
0.05
0.1
0.2
0.3
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Figure 29.3 Nomogram for predicting the 5-year and 10-year probability of any fracture for a man based on age, BMD, prior fracture, and falls.
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Figure 29.4 Nomogram for predicting the 5-year and 10-year probability of any fracture for a man based on age, body weight, prior fracture, and falls.
validated in external population and the area under receiver operating characteristic curve varied between 0.76 to 0.82, indicating a very good to excellent predictive accuracy (data are not yet published). We present the following hypothetical, but typical examples to illustrate the clinical application of the nomograms. Clinical case 1: A 60-year-old man with a prior history of fracture at the spine, current BMD T-score 1.5, did not fall in the past 12 months. In Figure 29.3, 60 year old is equivalent to 12 points and T-score 1.5 scores 43 points and prior fracture scores 21 points. Because the man did not fall during the past 12 months, therefore, the points for fall were 0. The total points are thus 75. Marking the score on the ‘Total Points’ axis and drawing a vertical line from the ‘Total Points’ to obtain the 5-year and 10-year risks of fracture gives a 10-year risk of fracture for the man of 10%. Clinical case 2: A 70-year-old man with BMD T-score 2.5 (osteoporosis) without a history of fracture or a fall. Using Figure 29.3, the man’s 10-year risk of fracture is 14.3%, which is even higher than case 1. The idea of using nomograms in clinical medicine is not new. Since their introduction in 1928 [106], the literature of medicine has recorded more than 1700 nomograms in use [107]. Nomograms developed and used in oncology have clearly exhibited a better performance than risk-grouping categorization [108,109], in large part, this is because a nomogram estimates a continuous probability of an event, which yields more accurate predictions than models based
on categorical risk grouping. The use of a nomogram-based prognostic model obviates the need for grouping individuals by rather artificial thresholds and, as a result, increases the uniqueness of the risk estimate for an individual. Nomogram-based prognostic models have been shown to out-perform clinical judgment [110], because they can more objectively incorporate multiple risk factors and thus reduce the variability in risk estimates. The predicted risk of fracture is a continuous probabilistic variable ranging from 0 to 1. This raises the issue of selecting an optimal cut-off of predicted probability to classify an individual with respect to intervention. This is not an easy task, because the cut-off value – if it exists at all – depends on the complex risk-benefit consideration and, perhaps more importantly, on an individual’s perception of the importance of that risk. However, the predicted probability of fracture from the present prognostic models can be viewed as a measure of severity of osteoporosis for an individual. It is logical that individuals with high risk of fracture, regardless of their BMD levels, should be considered for treatment given evidence that treating these individuals could yield clinical benefit. However, what level (or levels) of risk should be regarded as ‘high risk’, so that an intervention can be considered cost-effective? The individualization of fracture risk can help select patients suitable for intervention. In a recent analysis, it was suggested that treatment is costeffective (based on the criteria of £30 000 per qualityadjusted life year gained) if an individual’s 10-year risk
C h a p t e r 2 9 Individualized Prognosis of Fracture in Men l
of hip fracture is between 1.2 and 9.0%, dependent on age [111]. It has been estimated that, for a 50-year-old Australian, treatment would be considered cost-effective if his 10-year risk of hip fracture is at least 1.93% [111]. However, for a 90-year-old man, the treatment would only be cost-effective if his 10-year risk is 10.8% or higher. The present nomograms can help identify such individuals for intervention. The National Osteoporosis Foundation (NOF) guidelines recommend treatment in the following clinical situations in postmenopausal women and men aged 50 years or older [112]: 1. with a hip or clinical vertebral fracture or a morphometric vertebral fracture 2. with femoral neck or lumbar spine BMD T-scores being equal to or less than 2.5 after excluding secondary cause of osteoporosis 3. with femoral neck or lumbar spine BMD T-scores between 1 and 2.5 and a 10-year risk of hip fracture 3% or a 10-year risk of major osteoporotic fracture 20%. The nomogram presented here and the FRAX model [104] in conjunction with the NOF guidelines can help select suitable individuals for intervention. The individualization of fracture prognosis may also be used to optimize the number needed to treat (NNT). In several randomized clinical trials [113], the number of patients needed to be treated to reduce one vertebral fracture compared to the untreated group ranged between 8 and 83. For hip fracture, the NNT ranged between 91 and 250 [114]. The NNT varies inversely with the background risk, such that treatment of high risk individuals inherently yields lower NNT. The large variability in the NNTs among trials is assumed to be due to the variability in fracture rates among the study samples, despite the fact that patients were selected on the basis of having osteoporosis and/or a prevalent vertebral fracture. However, the variability is expected given the multiple risk factors that affect the incidence of fractures. In the presence of such variability, selecting patients based on their absolute risk of fracture (rather than based on a BMD threshold value) may improve the consistency of therapeutic efficacy and efficiency of trials. Trials specifically testing the efficacy of multivariable risk based therapy have not been done. However, such approaches could be expected prove more cost effective and yield a more consistent NNT. An important question is whether treatment of individuals selected on the basis of absolute risk of fracture still result in reduced fracture risk. One clinical trial [115] randomized 5212 women aged 75 years and older into two groups, the placebo group receiving calcium and vitamin D and the clodronate group also receiving clodronate (800 mg daily po). Ten-year probability of fracture was computed for each woman using baseline clinical risk factors including body mass index (BMI), prior fracture, glucocorticoid use, parental hip fracture, smoking, alcohol and secondary osteoporosis. In women in the top 25th percentile of fracture probability
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(average probability of 24%), treatment reduced the risk of fracture by 23% over 3 years (hazards ratio (HR) 0.77, 95% CI 0.63–0.95). Importantly, among those in the top 10% percentile (average fracture probability of 30%), treatment reduced the fracture risk by 31% (HR 0.69, 0.53–0.90) [115]. Thus, treatment of individuals at high risk or moderate risk could reasonably be expected to reduce fractures.
Conclusion During the past three decades, several risk factors, including low bone mineral density, advancing age and a history of fracture, have been shown to be associated with fracture risk [61, 66, 69, 116–119]. Moreover, the risk of fracture increases with the cumulative presence of the number of risk factors [68]. The issue at hand is how to translate this knowledge of risk factors into prognostic models for individualizing fracture risk in clinical practice. Some prognostic models have recently been developed [64, 65, 104]. However, these models have not been externally validated and their validity and accuracy in Asian populations is not clear. Therefore, external validation should be a priority of research in the application of risk assessment models. Individualized prognosis – or the prediction of risk for an individual given a risk profile – is a fundamental to practicing medicine. Since fracture risk is determined by multiple factors, any unidimensional risk assessment is unlikely to be helpful. A multivariable-based nomogram can be an effective tool for individualizing short-term and long-term absolute risks of fracture, which can help patient counseling and selecting appropriate patients for intervention to maximize the benefit of fracture reduction in the general population.
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98. L. Gennari, D. Merlotti, G. Martini, et al., Longitudinal association between sex hormone levels, bone loss, and bone turnover in elderly men, J. Clin. Endocrinol. Metab. 88 (2003) 5327. 99. S. Khosla, L.J. Melton 3rd, E.J. Atkinson, W.M. O’Fallon, Relationship of serum sex steroid levels to longitudinal changes in bone density in young versus elderly men, J. Clin. Endocrinol. Metab. 86 (2001) 3555–3561. 100. W.D. Leslie, L.M. Lix, J.F. Tsang, P.A. Caetano, Single-site vs multisite bone density measurement for fracture prediction, Arch. Intern. Med. 167 (2007) 1641–1647. 101. P. Dargent-Molina, M.N. Douchin, C. Cormier, P.J. Meunier, G. Breart, Use of clinical risk factors in elderly women with low bone mineral density to identify women at higher risk of hip fracture: The EPIDOS prospective study, Osteoporos. Int. 13 (2002) 593–599. 102. N.D. Nguyen, J.A. Eisman, J.R. Center, T.V. Nguyen, Risk factors for fracture in nonosteoporotic men and women, J. Clin. Endocrinol. Metab. 92 (2007) 955–962. 103. M.W. Kattan, V. Reuter, R.J. Motzer, J. Katz, P. Russo, A postoperative prognostic nomogram for renal cell carcinoma, J. Urol. 166 (2001) 63–67. 104. J.A. Kanis, O. Johnell, A. Oden, H. Johansson, E. McCloskey, FRAX and the assessment of fracture probability in men and women from the UK, Osteoporos. Int. 19 (2008) 385–397. 105. B. Ettinger, T.A. Hillier, A. Pressman, M. Che, D.A. Hanley, Simple computer model for calculating and reporting 5year osteoporotic fracture risk in postmenopausal women, J. Womens Hlth. (Larchmt) 4 (2005) 159–171. 106. L.J. Henderson, Blood; a Study in General Physiology, Yale University Press, New Haven, 1928 London, H. Milford, Oxford University Press. 107. F.J. Bianco Jr, Nomograms and Medicine, Eur Urol, 2006 50:884-86. 108. M.W. Kattan, Nomograms are superior to staging and risk grouping systems for identifying high-risk patients: preoperative application in prostate cancer, Curr. Opin. Urol. 13 (2003) 111–116. 109. S.L. Wong, M.W. Kattan, K.M. McMasters, D.G. Coit, A nomogram that predicts the presence of sentinel node metastasis in melanoma with better discrimination than the American Joint Committee on Cancer staging system., Ann. Surg. Oncol. 12 (2005) 282–288. 110. P.L. Ross, C. Gerigk, M. Gonen, et al., Comparisons of nomograms and urologists’ predictions in prostate cancer., Semin. Urol. Oncol. 20 (2002) 82–88. 111. F. Borgstrom, O. Johnell, J.A. Kanis, B. Jonsson, C. Rehnberg, At what hip fracture risk is it cost-effective to treat? International intervention thresholds for the treatment of osteoporosis, Osteoporos. Int. 17 (2006) 1459–1471. 112. NOF Clinician’s guide to prevention and treatment of osteoporosis. (2008). National Osteoporosis Foundation, Washington DC. 113. D.M. Black, S.R. Cummings, D.B. Karpf, et al., Randomised trial of effect of alendronate on risk of fracture in women with existing vertebral fractures. Fracture Intervention Trial Research Group, Lancet 348 (1996) 1535–1541. 114. P.D. Delmas, R. Rizzoli, C. Cooper, J.Y. Reginster, Treatment of patients with postmenopausal osteoporosis is worthwhile. The position of the International Osteoporosis Foundation, Osteoporos. Int. 16 (2005) 1–5.
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115. E. McCloskey, H. Johansson, A. Oden, A. Aropuu, T. Jalava, J. Kanis, Efficacy of clodronate on fracture risk in women selected by 10-year fracture probability, J. Bone Miner. Res. 22 (2007) S131. 116. T.V. Nguyen, J.R. Center, J.A. Eisman, Femoral neck bone loss predicts fracture risk independent of baseline BMD, J. Bone. Miner Res. 20 (2005) 1195–1201. 117. H. Burger, C.E. de Laet, A.E. Weel, A. Hofman, H.A. Pols, Added value of bone mineral density in hip fracture risk scores, Bone 25 (1999) 369–374.
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Chapter
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Physical Activity, Physical Function and Fall and Fracture Risk in Older Men Peggy Mannen Cawthon1 and Lynn Marshall2 1
San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA Department of Medicine, Bone and Mineral Unit, Department of Public Health and Preventive Medicine, Oregon Health & Science University, Portland, OR, USA 2
Introduction
r ecommendations for the type and amount of physical activity that older adults should undertake (Table 30.1) [1]. The extensive recommendations are designed to be the minimum level of activity for older adults and pertain to both aerobic exercise as well as strength training. Because of the putative contribution of physical activity to the most important factors in the fracture pathway–skeletal integrity and fall propensity– these recommendations, if met, could result in reduced fracture incidence among the US elderly. Thus, research on the impact of these recommendations will be informative.
This chapter will describe the relation between both physical activity and physical performance with fall and fracture risk in older adults. First, an assessment of physical activity levels in both clinical and research settings will be discussed. Then, the evidence for the association between activity level and fall and fracture risk in older men will be reviewed. In the second half of the chapter, methods to assess physical performance (including muscle strength, walking speed and ability to rise from a chair) will be described. Next, changes in physical performance that occur with age in older men will be outlined. Finally, the association between physical performance and fall and fracture risk will be described.
Physical Activity Assessment Assessment of physical activity can be divided into two domains: subjective measures of activity, such as questionnaire based data; and objective measures of activity levels, such as use of accelerometers to measure movement. There are many validated instruments to measure subjectively reported
Physical activity Table 30.1 Recommendations for the type and amount of physical activity for older adults
Physical activity refers to the volitional and necessary levels of movement that an individual undertakes in his daily life, including exercise. In this section, we will describe recommendations for exercise for older adults; objective and subjective assessment of physical activity in research and clinical settings; the association between physical activity and fall risk; and the relation between physical activity and fracture risk in older men.
Do moderately intense aerobic exercise 30 minutes a day, 5 days a week or Do vigorously intense aerobic exercise 20 minutes a day, 3 days a week and Do 8 to 10 strength-training exercises, 10–15 repetitions of each exercise twice to three times per week and If you are at risk of falling, perform balance exercises and Have a physical activity plan
Recommended Levels of Activity in Older Adults The American College of Sports Medicine (ACSM) and the American Heart Association have developed specific Osteoporosis in Men
Adapted from Nelson, 2007 [1]
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physical activity in epidemiologic studies. Several instruments have been developed for the general population, including the Minnesota Leisure Time Physical Activity Questionnaire [2], the Seven Day Recall [3] and the Stanford Usual Activity Questionnaire [4]. Since older adults may engage in physical activity that is less intense, of shorter duration and less frequent than younger adults, specialized questionnaires to assess activity level in older adults have been developed [5, 6]. These include the Community Healthy Activities Model Program for Seniors (CHAMPS) Questionnaire [7], the Yale Physical Activity Survey (YPAS) [8] and the Physical Activity Scale for the Elderly (PASE) [9] among others. Many cross-sectional studies of self-reported physical activity have noted that activity levels decline across age groups, even among the oldest old [10–13]. Men consistently report more physical activity in older age (65 years) than women and this sex difference increases with advancing age [11]. Few longitudinal studies have assessed change in activity level over time; one study in the Netherlands found that total time spent on physical activity decreased 33% over a decade in elderly men [10]. The activities in which older individuals were participating changed with age as well: time spent gardening and bicycling declined, but time spent walking remained stable. Even though activity levels may decline with age, older adults may be exercising more now than ever before. For example, data from the Behavioral Risk Factor Surveillance System, a large, population-based survey, indicates that the percentage of people aged 75 and older who reported an inactive lifestyle declined from 48.5% in 1990 to 39.5% in 2000 [13]. Also during this time, the number of adults aged 75 years and older who reported regular, intense exercise almost doubled from 11.7% to 19.1%. Thus, the current cohort of older Americans may have more active lifestyles than previous generations. While self-reported physical activity questionnaires allow for report of volitional activities and are easy to field in a research setting, self-report is potentially prone to substantial measurement error [14]. In fact, a validation study conducted by Bonnefoy et al simultaneously evaluated 10 surveys of activity level used in elderly adults against the gold standard of doubly labeled water as a measure of total energy expenditure [6]. In general, agreement between the questionnaires and the gold standard was poor with correlations ranging between 0.11 and 0.63; only the Seven Day Recall and the YPAS were considered to measure accurately total energy expenditure. Such error would make it difficult to demonstrate an association between physical activity and health outcomes. Additionally, in a clinical setting, formal questionnaires regarding physical activity level may be difficult to administer and score given time constraints on patient–physician interaction. Objective measures of physical activity and function have recently been used in research studies and may have application in the clinical setting. Physical activity and energy
expenditure can be monitored by several objective methods, including pedometers to measure number of steps and accelerometers to measure counts of movement. The first large, population-based assessment of movement by accelerometers was completed in the Third National Health and Nutrition Examination Survey (NANES III) and demonstrated a sharp decline in activity across increasing age group [15]. Participants in the NHANES examination were asked to wear an accelerometer over the right hip for seven days; the accelerometer stored counts of each vertical movement over one minute epochs for up to 1 week. These count data were then translated into summary measures of physical activity. This study found that only 2.5% of older men and 2.3% of older women achieved 30 minutes of moderate or greater activity level on at least five days a week. Men were generally more active than women. However, after age 60 there was essentially no daily vigorous activity in older adults and an average of only 6–10 minutes of moderate activity daily. Thus, while subjective data suggest many adults meet recommended activity guidelines, the objective assessment of activity from accelerometers indicates that it is very rare that older adults engage in significant amounts of moderate physical activity.
Physical Activity and Fall Risk Among Older Men: Observational Studies The relation between physical activity and fall risk is somewhat paradoxical: older adults with low activity levels have been shown to have increased fall risk [16–18] and exercise interventions tend to reduce the risk of falling [19–21]. However, increased physical activity level may also increase the time at risk for falls, due to increased movement, ambulation, challenges to balance demands and changes in a person’s center of gravity [20, 22]. A systematic review published by Gregg and colleagues in 2000 noted studies that observed significant reductions in fall risk usually compared older adults who had any activity to those who were sedentary [16, 18] and no dose-response relationship was observed. Additionally, the association between low activity and fall risk was attenuated after adjustment for mobility limitations [23]. This implies that the associations between low physical activity and increased fall risk may be due to physical limitations rather than low activity per se. More recent observational studies that analyzed the influence of physical activity level on fall risk yielded mixed results. For example, in the US cohort of Osteoporotic Fractures in Men (MrOS) Study, a study of nearly 6000 men aged 65 years and older, physical activity was assessed using the PASE questionnaire [24]. Activity was analyzed as total activity level and as separate components: leisure activity, occupational activity and household activity. Falls were assessed prospectively. Overall, men in the highest quartile of total activity level were about 14% more likely (odds ratio, 1.14; 95% CI: 1.03, 1.25) to fall during follow
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up than men in the lowest total activity quartile. However, there was no association between leisure activity or occupational activity and fall risk. Only household activity (which includes light/heavy housework, home repair, lawn care/gardening and caregiver responsibilities) was associated with fall risk. Men in the highest quartile of household activity level had the highest risk of falls. The authors speculated that household activity, and not leisure activity, was associated with increased fall risk because some household activities, such as cleaning rain gutters or shoveling snow, are in some sense ‘mandatory’ and cannot be avoided in the same manner as voluntary exercise. Leisure activity, on the other hand, can be avoided if an older man is concerned about his fall risk. Another report from the Swedish MrOS cohort, a study of about 3000 men age 65 and older, showed that sedentary men (as assessed by a simple questionnaire) were more likely to have reported a history of falling compared to men with an active lifestyle [17]. Due to the cross-sectional nature of this report, it is not clear if men had first fallen and then reduced their activity levels, or if lower activity levels subsequently lead to increased falls. The cross-sectional nature of this report may be the reason for the apparently discrepant findings between the US and Swedish studies. Finally, a study of well-functioning older adults aged 70–80 years participating in the Health, Aging and Body Composition Study (Health ABC) found no cross-sectional association between history of falling and physical activity level [25]. As with previous findings reported in the Gregg review [20], these newer studies with discrepant results have used different methods to quantify physical activity and different methods for assessing falls. When falls have been analyzed prospectively and the compartments of activity consider separately, only increased household activity level (rather than leisure activity or occupational activity) has been associated with increased fall risk.
Physical Activity and Fall Risk in Older Men: Randomized Trials Given the discrepancies found in the observational studies and the limitations of self-reported information, data from randomized trials are needed to determine the causal association between physical activity and fall risk. As summarized by Gregg et al, a meta-analysis of randomized controlled trials in the Frailty and Injuries: Cooperative Studies of Intervention Techniques (FICSIT) program demonstrated that the general exercise resulted in a 10% reduction in the risk of falls, while balance training resulted in a 17% reduction in falls risk [20, 21]. Two more recent meta-analyses on fall interventions have been published. Both Gillespie and colleagues [26] and Chang and colleagues [27] agree that multifactorial falls intervention programs are effective at reducing the risk of falling. However, these reports have differing results for exercise interventions [28]: Chang et al report that exercise interventions (both individually
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targeted programs and group programs) reduce overall fall risk by about 20% (OR: 0.80, 95% CI: 0.66, 0.98). On the other hand, Gillespie et al suggest that only individualized, home-based exercise interventions are effective in reducing fall risk (OR: 0.86, 95% CI: 0.75, 0.99). In the Gillespie analysis, group-based programs were not deemed effective. Overall, these meta-analyses support the idea that individualized exercise interventions effectively reduce fall risk in older adults by about 15%. At the individual level, this is a relatively small risk reduction. However, given the large number of older individuals who fall, a small reduction in fall risk may have important public health implications. Other more recent trials that were not included in either the Gillepsie or Chang meta-analyses continue to provide equivocal results: a study that compared a pragmatic intervention program (which included home exercise, group exercise, walking exercise or self-care exercise) versus routine care found that the intervention had no effect on fall rates [29]. Another study that compared moderate intensity group exercise programs to a control program found that the exercise intervention was effective at reducing fall risk in pre-frail, but not frail, individuals [30]. In yet another intervention study, group exercise programs were shown to reduce fall risk by about 20% [31]. Given the evidence, it appears that exercise interventions generally reduce fall risk and that targeted, multifactorial programs may be the most effective. However, some randomized trials and meta-analyses have indicated that certain types of exercise interventions (e.g. group exercise) may not be useful in reducing fall risk. It is possible that exercise interventions are most effective in certain subpopulations, such as the pre-frail or inactive. Further research in this area is needed to refine recommendations for the types of activity programs that are effective at reducing fall risk.
Physical Activity and Fracture Risk Exercise interventions have been demonstrated to increase bone mineral density (BMD) in older adults. A meta-analysis of exercise interventions in men conducted by Kelly and colleagues examined the BMD of skeletal sites that were loaded during the exercise intervention [32]. The exercise inventions resulted in increased BMD at the specific skeletal sites by about 2.1% in the intervention groups, compared to a loss of 0.5% in the control groups. However, the difference in BMD between the intervention and control groups is fairly small (2.6%) and it is unclear if such differences in BMD would translate into clinically significant differences in fracture risk. However, in another randomized trial not included in the meta-analysis, a 6 month exercise regimen did not alter BMD in older men but did increase BMD in older women [33]. There was a small number of participants in this study (51 men) and a small difference in BMD may not have been detected. Thus, while exercise appears to improve BMD in older men at skeletal sites that
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are loaded during exercise, the resulting increase in BMD is small and may not result in reduced fracture risk. There are several prospective observational studies that have examined the association between physical activity and risk of hip fracture. As summarized in a meta-analysis by Moayyeri, men who engage in moderate to vigorous activity are about 50% less likely to have a hip fracture than those with lower activity levels (relative risk: 0.52, 95% CI: 0.44, 0.69) [34]. The definitions of activity level varied widely by study, however, so it remains unclear which specific subtype of activity (e.g. vigorous activity versus moderate activity; weight bearing versus not weight bearing) is most strongly associated with hip fracture risk. Additionally, these results have not been confirmed by a randomized controlled trial. However, it is unlikely that such a trial would be completed, as the sample size to detect a 20–30% reduction in hip fracture risk over 5 years in European men was estimated to range between 14 696 and 34 998 individuals per treatment group [34]. There have been very few observational analyses of physical activity and risk of non-spine fracture in older men. A large study of British men and women aged 20–89 years had two important findings [35]. First, bicycling in particular increased fracture risk for men and women of all ages: men who reported bicycling more than 5 hours per week had about a twofold increased risk of fracture compared to men who did not report any bicycling. Thus, the increased risk of injury from bicycling appeared to outweigh any benefit to bone density that may be associated with this exercise. This is not surprising given that bicycling is not a weight bearing exercise and that bicycling does not appear to improve bone mineral density as compared to other load bearing exercise [36]. The second finding from the British study was that increased physical activity was associated with increased fracture risk, but only in those fractures not caused by a fall (such as those from trauma). The association between greater activity and fracture risk was generally not present when fractures due to a fall were analyzed separately. Although the analyses in this report were not stratified by age, the results suggest that the association between physical activity and fracture risk may differ by age and frailty status. Results from the US cohort of the MrOS study suggest that among men aged 65 years and older, low physical activity level as measured by the PASE questionnaire is associated with an increased risk of non-spine fractures after accounting for age [37]. Men in the lowest quartile of activity level had a 42% increased risk of non-spine fracture compared to men in the third quartile; no association was seen for quartiles 2 and 4. However, the association was no longer significant after adjustment for confounding factors such as falling history, age, bone mineral density, depression and balance; the types of activity (leisure, household, occupational) were not analyzed separately. Additionally, among 1500 older men participating in the Dubbo Osteoporosis study, higher physical activity levels were protective against
osteoporotic fracture, but this association was not independent of quadriceps strength, sway and bone mineral density [38]. Finally, in a study of middle-aged Norwegian men, those most physically active had a reduced risk of a ‘lowenergetic fracture in the weight bearing skeleton’ compared to men who were sedentary. No association was seen for fractures in the areas of the skeleton that were deemed nonweight bearing [39]. In summary, higher levels of physical activity appear to be modestly protective against non-spine fracture risk, but this association tended to be attenuated or explained by confounding or mediating factors. There are only a handful of analyses of the association between physical activity and risk of vertebral fractures in older men. A report from the European Vertebral Osteoporosis Study (EVOS) examined the relationship between lifetime and current activity levels with prevalent vertebral fractures in a cohort of more than 14 000 men and women aged 50–79 years [40]. This study found that very heavy activity levels during young adulthood (15–25 years), adulthood (25–50 years) and mid-life (age 50 years) were associated with a 50–70% increased risk of vertebral fracture in men, but not in women. Regular walking reduced vertebral fracture risk in men, but not in women. In another report, physical activity was not associated increased long-term risk of vertebral fractures in men participating in the Framingham study [41]. This study was small in size (704 men and women participated) and would not have been able to detect modest associations. Thus, the associations between physical activity and vertebral fracture risk have not been extensively studied.
Physical function and performance Physical activity requires voluntarily engaging in movement of the limbs. Forces generated by muscles during movement are integral to physical functioning and therefore to the successful conduct of physical activities. Physical function and performance as defined for this chapter includes both subjective and objective assessment of physical ability. Subjective assessments of ability to complete common daily tasks, such as ability to walk 1–2 blocks or climb stairs, are commonly assessed in research studies. Additionally, objective measurement of performance in standardized tasks is increasingly assessed in clinical settings; these measurements include muscle strength, walking pace over a set distance or the ability to rise from a chair. In this section, we will describe the assessment of physical function; the changes in physical function with age; and the association between physical function and falls and fractures in older men.
Assessment of Physical Function Many tools are available to assess physical function in both epidemiological and clinical settings. Subjective assessment
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of performance is commonly evaluated by querying individuals about activities of daily living (ADLs) and instrumental activities of daily living (IADLs). ADLs generally refer to tasks related to daily care. The most common ADLs included in surveys are bathing, dressing, transferring (moving from a bed to a chair), mobility (walking a short distance or climbing stairs), using the toilet and eating. IADLs are more complex tasks. Commonly assessed IADLs include managing money, preparing meals, housework, using the telephone, managing medications and shopping for groceries or personal items. Numerous questionnaires have been used to assess limitations in the ability to complete ADLs and IADLs. Generally, the survey instruments differentiate inability to complete a task due to health reasons from not completing a task for other reasons not related to a person’s health. Some of the most commonly used instruments to assess IADL and ADLS are the Katz [42], Rosow-Breslau Functional Health Scale [43] and ADL/IADL items developed by Nagi [44]. However, there are few reports that study the association between fracture risk and ADL/IADL status. One of the more widely used instruments to assess physical function is the Short Physical Performance Battery (SPPB) developed by Guralink and colleagues [45, 46]. The SPPB includes three performance tests: walking pace (over 4 meters); repeated chair stands; and a balance test (tandem and semi-tandem stand). A score for each test is assigned and then summed; scores for the SPPB range from 0 (unable to complete any of the tests) to 12 (best performance on all three tests). The SPBB is predictive of mortality, disability and hospitalization in older adults [45, 47]. Other exams that measure physical function include: the timed up and go test [48]; the narrow walk test [49]; and the long distance corridor walk [50]. The timed up and go test measures the time needed to arise from a chair, walk 3 meters and return and sit in the chair. The narrow walk test is a measure of dynamic balance and assesses the ability to walk within a 20 cm path over 6 meters. The long distance corridor walk (LDCW) measures the ability and time to complete a 400 m walk; poor performance on the LDCW is associated with increased risk of mortality in older adults [50]. Objective measurement of physical function is very common in research studies but less common in clinical settings. The SPPB has also been developed to be used in a clinical setting; a score sheet and wall chart for administering the SPPB are available from the National Institute on Aging website (http://www.grc.nia.nih. gov/branches/ledb/sppb/index.htm). Upper and lower extremity strength and power are also commonly measured in research settings. Upper extremity strength is usually quantified as isometric grip strength (where the arm is static as the muscle is contracting) as measured on a hand-held dynamometer. Isometric leg strength can be measured with portable dynamometers or more complex equipment, such as specialized chairs. Isokinetic leg strength (where the leg is moving at constant speed as the muscle is contracting) is also measured with specialized equipment. Leg power (the amount of work done per unit of time) has
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also been assessed in research settings, using devices such as the Nottingham Power Rig [51, 52]. The use of a hand-held dynamometer may be practical in a general clinical setting, provided age-specific cut-points that define ‘weakness’ are available. However, most measures of lower extremity power or strength are cannot be used practically in the general clinical environment. Clinically, more global measures of function, such as the ability to rise from a chair, may be more useful than direct measures of strength.
Changes in Muscle Strength and Power in Older Age A hallmark of the aging process is a decline in physical ability and muscle strength. This section will describe changes in upper and lower extremity strength and power and the relation of these changes to changes in muscle mass. Given the limited availability of data on the changes in objective measures of physical performance, such as walking speed and chair stands, changes in these factors will not be reviewed in this chapter.
Upper Extremity Strength Knowledge about variation in muscle strength throughout the adult lifespan comes primarily from measurements of hand grip strength obtained in large cohort studies. Crosssectional data demonstrate consistently that grip strength is, on average, lower among older compared with younger men [53, 54]. Two cohorts that included community dwelling men aged 20 to 100 years, the Baltimore Longitudinal Study of Aging (BLSA) and the InCHIANTI study, demonstrated that average grip strength is greatest among the youngest men, which was at ages 20–29 in InCHIANTI and at ages 30–39 in the BLSA. From age 40 onward in InCHIANTI and age 50 onward in the BLSA, mean grip strength was successively lower for each decade of age, such that strength among men in their 80s was about 40% that of men in their 30s. In the BLSA cohort, upper extremity muscle power followed the same age-specific patterns as grip strength [55]. Others have demonstrated the same pattern, successively lower average grip according to age decade or 5-year age groups regardless of the age ranges studied [56–59]. Prospective studies with repeat grip strength assessments provide information about change in grip strength with aging [53, 56, 57, 59–61]. Three important observations emerge from these data. First, grip strength declines on average with aging and the decline begins at a relatively young age. In the BLSA, during follow up that averaged 9 years, men initially in their 20s or 30s gained strength. In contrast, men initially age 40 or older, on average, lost grip strength during follow up [53, 59]. The annualized rate of decline has been estimated to be about 1 kg/year [56, 59]. Loss of strength occurred in both extensor and flexor muscle groups [60, 61]. Second, the rate of grip strength loss increases with
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increasing age. In the BLSA, for men ages 40–49, 50–59, 60–69 and 70–79 annualized absolute changes in kg/year were, respectively, 0.31, 0.65, 0.78 and 1.27 [53]. Upper extremity muscle power in this cohort also declined by similar magnitudes [55]. In a cohort of men from Hawaii who were aged 45–68 at baseline, annualized percentage grip strength change ranged from 0.9% per year among men initially aged 45–49 to 1.5% among those aged 65–69 during follow-up visits that spanned 27 years [59]. Among older men, annualized percentage changes of 3% per year have been reported in cohorts with baseline age ranging from 50 to 84 years (average: 66 7) [57] and 65 years (average 74 6 years) [56]. Third, there is considerable variability in grip strength change. Although grip strength on average declines with aging, substantial proportions of men experience no change or gain strength. Rantanen et al reported that 13% of men aged 45–68 had declines of 0.5% per year [59] and Kallman et al reported that, in the BLSA, 29% of men aged 40–59 years and 15% of those age 60 years did not lose grip strength [53].
Lower Extremity Strength and Power Few studies have evaluated strength or power of lower extremity muscles. Like hand grip strength, isokinetic knee strength (Newtons per meter [N m]) is, on average, lower among older compared with younger men [62, 63]. From age 40 onward in the BLSA, mean knee strength was successively lower for each decade of age, such that strength among men in their 80s was about 50% that of men in their 30s [62, 63]. Longitudinally, knee extensor strength declined by 3% to 4% annually during follow up of about 3 years among white and black men aged 70–79 years at initial
examination in the Health Aging and Body Composition (HABC) cohort [64].
Relation of Decline in Muscle Strength to Decline in Muscle Mass Like muscle strength, lean muscle mass declines with age. Among older men, estimates of annualized percentage change in whole body lean mass are somewhat discrepant. Among men aged 45–78 years, the decline was estimated at 1.3% per year based on urinary creatine excretion [61]. Among men in their 70s, estimated declines in total body lean mass from dual energy x-ray absorptiometry (DXA) have been smaller, ranging from 0.7% per year [65, 66] to 0.3% per year [67]. Declines in leg lean mass measured with DXA, which reflect changes occurring primarily in skeletal muscle, were observed to be about 1% per year, a rate slightly greater than that for whole body lean mass [64]. Thus, rates of change in muscle strength as described above are about three times greater than rates of change in muscle mass (Figure 30.1). Early cross-sectional studies indicated a strong association between lean body mass and muscle strength [63, 68]. However, available data from large prospective cohort studies indicate that the relation between actual change in muscle mass with aging and loss of muscle strength is weak. Estimates of change in total body lean mass based on urinary creatine excretion were unrelated with change in hand grip strength ( 0.002, P 5 0.05) [53] and were only weakly related to change in knee extensor strength ( 0.01, P 0.06) or knee flexor strength ( 0.40, P 0.05) [61]. Additionally, change in leg lean mass assessed with DXA was significantly associated change in knee extensor strength
2 Lean mass
Annual % change (%/year)
1
Knee strength
0
–1 –2 –3 Men
Women
–4 –5 (a)
(b)
(c)
White (d,e) Black (d,e)
(a)
(b)
(c)
White (d,e) Black (d,e)
Figure 30.1 Changes in lean mass and knee extension strength in older men and women. Data sources [61, 64–67]. Data Sources: (a) Gallagher et al, 200066; (b) Fantin et al, 200765; (c) Hughes et al, 200261; (d) Visser et al, 200367; (e) Goodpaster et al, 200664.
C h a p t e r 3 0 Physical activity, physical function and fall and fracture risk in older men l
( 8.31, P 0.01). Although both Hughes et al [61] and Goodpaster et al [64] reported statistically significant associations of change in lean mass and change in muscle strength, change in lean mass accounted for less than 5% of the variance in strength change. Moreover, although physical activity contributes to muscle mass and strength, accounting for either baseline or change in physical activity did not affect the associations between muscle mass and strength. Finally, as illustrated in Figure 30.1, aging men appear to lose a greater percent of knee strength per year compared to women. Thus, we may speculate that declines in physical performance or strength may be a more important risk factor for fracture in men than in women. However, this hypothesis has yet to be formally tested.
Physical Performance and Fall Risk in Older Men There are many reports that describe the association between poor physical performance and increased risk of falling and physical function measures are commonly included in fall risk prediction models [69, 70]. Weakness is commonly reported as a risk factor for falling. A meta-analysis by Moreland et al has shown that lower extremity weakness is associated with a 1.8-fold increased likelihood of any fall (95% CI: 1.3, 2.4) and a 3.1-fold increased likelihood of recurrent falls (95% CI: 1.9, 5.0) [71]. Upper extremity weakness was more modestly associated with falls: upper extremity weakness was associated with a 1.5-fold (95% CI: 1.0, 2.3) increased likelihood of any fall and a 1.4-fold (1.3, 1.6) increased likelihood of recurrent falls. The relationship between more complex performance traits, such as walking speed and ability to rise from a chair, and fall risk has also been assessed. Many studies have found no association between preferred walking speed and fall risk [24, 72–74]. One report indicated that faster walking speed was associated with increased risk of outdoor falls, while slower walking speed was associated with increased risk of indoor falls [75]. The discrepancy may be due to the types of activity undertaken at the time of the fall. Outdoor falls may be more likely to be associated with higher activity or exercise levels that increase time at risk of falling, while falling during indoor activity may be a marker for worse frailty status. Finally, Tinetti et al demonstrated that abnormalities in balance, such as increased sway and path deviation, rather than simple walking speed alone, are important in determining fall risk [76].
Physical Performance and Fracture Risk in Older Men Despite the association between fall risk and poor physical performance, there are relatively few reports of the association between fracture risk and poor physical performance. The association between poor physical performance and risk of hip fracture has been examined in the US cohort of
381
the MrOS study [49]. Physical performance was assessed in 5902 men; 77 hip fractures occurred over an average of 5.3 years of follow up. Performance tests included grip strength, leg power (from the Nottingham Power Rig), narrow walk test, walking speed (over 6 m) and a repeat chair stands test. Poor performance was associated with increased hip fracture risk. In particular, men who were unable to stand from a chair without the use of the arms were much more likely to have a hip fracture compared to men who were able to complete the repeat chair stands in the fastest quartile (multivariate hazard ratio, 8.2; 95% CI: 2.7, 25.0). Additionally, those men with the worst performance (weakest/ slowest quartile or unable) on three or more exams had an increased risk of hip fracture and the majority of the hip fractures (n 49, 64% of fractures) occurred in men with poor performance on at least three exams. These associations were independent of potential confounding factors including physical activity level and age. Therefore, poor physical performance appears to increase the risk of hip fracture and this association is independent of BMD. The inability to rise from a chair without the use of the arms is particularly predictive of fracture risk and such a measure could be easily completed in a clinical setting. Poor physical performance, specifically weak muscle strength, has been examined in a few studies as a risk factor for non-spine fractures. Ngyuen and colleagues found that weak quadriceps strength and increased body sway were independent predictors of non-spine fracture for men participating in the Dubbo Osteoporosis study [38]. Low grip strength was associated with increased risk of fragility fractures (vertebrae, proximal femur, proximal humerus, distal forearm, ramii of the pelvis and the tibia condyle) among 654 older Swedish men [77]. A report from the Longitudinal Aging Study Amsterdam (LASA) found that among older men and women, self-reported functional limitations, low physical performance test score and low grip strength were associated with an increased risk of selfreported fractures and the association was similar among both genders. Another report from the MrOS study found that inability to complete the narrow walk test was associated with a 70% increased risk of non-spine fracture in multivariate models (hazard ratio: 1.7, 95% CI: 1.2, 2.3) [37]. Other performance measures were not independently associated with non-spine fracture in this analysis. Overall, poor physical performance, including weak quadriceps or grip strength and poor balance, tends to be independently associated with non-spine fracture risk. There are very few analyses of the association between physical performance and vertebral fracture. A crosssectional analysis of 158 men found that lower grip strength was associated with prevalence of vertebral fracture; only weak muscle strength, marital status and body weight were associated with vertebral fracture in this study [78]. However, it is unclear if the lower muscle strength occurred first and then predisposed the individual to a vertebral fracture or if the
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vertebral fracture led to reduced function that then resulted in poor muscle strength. More research on the association between physical performance and vertebral fracture risk in men is needed.
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Chapter
31
Economic Impact of Osteoporotic Fractures (versus Women) Terence W. O’Neill arc Epidemiology Unit, University of Manchester, Manchester, UK
Background
osteoporosis [1, 2]. Furthermore, osteoporosis in men contributes substantially to overall health care costs, accounting for more hospitalizations and hospital bed days than other chronic diseases (Figure 31.1) [3, 4]. Study of the economic impact of osteoporosis in men is important. Knowledge of costs is important in helping policy makers plan health care and prioritizing areas for prevention. Cost studies may also help identify aspects of fracture management and care that may be a focus for service developments. A knowledge of the costs related to fracture is also key in helping evaluate the impact of interventions aimed at reducing fracture occurrence.
Osteoporosis is an important and increasing health problem. The clinical and public health impact is due to the associated fractures which result in substantial morbidity, mortality and health care costs. Health costs of osteoporosis have been more widely studied in women, however, there is an increasing literature that confirms osteoporosis in men poses a substantial economic impact. Current estimates of the costs of osteoporotic fractures in men aged 50 and over are $4.1 billion in the USA and €8.7 billion in Europe, which represents about 24% of the total costs of 160 000
151 152
140 000
Hospital days (n)
120 000 100 000
88 579
84 608
80 000 61 142
60 000
57 122
56 779
Diabetes
Heart failure
40 000 20 000 0
COPD
Osteoporosis
Stroke
Myocardial
Infarction
Figure 31.1 Hospital days for osteoporosis and other frequent diseases in Swiss men in the year 2000. (Reproduced from Lippuner et al. Epidemiology and direct medical costs of osteoporotic fractures in men and women in Switzerland. Osteoporos Int 2005;16:S8-S17 [3]). Osteoporosis in Men
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This chapter focuses on the economic impact of osteoporotic fractures in men and compares this, where data are available, with the impact in women. In the first part, the nature of the costs related to osteoporotic fractures incurred (including both medical and societal costs) are considered, methodological approaches to characterizing these costs are reviewed and the reasons why costs differ in men and women are discussed. The second part includes a review of cost studies that have been published from different regions and populations worldwide.
Cost of illness studies Cost of illness studies estimate the overall economic burden of disease in a defined population.
Definition of Costs Health costs related to osteoporotic fractures can be considered as direct and indirect. Direct Costs These are costs that can be considered to be related to the fracture event. They include costs related to medical and nonmedical goods and services. Direct medical costs are those which relate to inpatient, outpatient and primary care, including, for example, the cost of the hospital bed, the type of surgery/intervention, postoperative care, medications during care, the length of stay in the hospital, follow-up visits both to hospital and to primary care and the costs for investigations undertaken during or after admission. In addition, fractures are linked with personal suffering and impairment in quality of life, though these are difficult to quantify in monetary terms. Non-medical costs are those which relate primarily to social and nursing home care. Typically, costs can be disaggregated into discrete units and an average price assigned to each – the direct costs are then estimated by multiplying the average price per unit by the number of units consumed. These can then be aggregated across care to provide an estimate of the total direct cost. Indirect Costs These include the loss of productivity arising from being unable to work due to illness/death. These costs can be assessed by looking at losses in projected earnings – typically based on the amount of time away from work, though this does not account for loss of productivity of others who may be affected, including loss of earnings by informal carers. Because of higher employment levels, loss of productivity is likely to be greater in men than in women though, because most fractures occur in the elderly who are retired, those costs are generally not high.
Gender differences in economic impact The economic impact of osteoporosis and osteoporotic fractures in most developed countries is substantially greater in women than men largely because fractures are more frequent in women [5]. This is partly because the age-specific incidence of fracture is greater but also because women live longer. For example, while the age-adjusted incidence of hip fracture is approximately twice that in women as in men, because of their greater lifespan about 80% of fractures occur in women [6, 7]. In low risk populations, there is no female excess and the economic impact is likely similar in men and women [8]. Apart from a difference in the number of fractures, other reasons why costs may differ in men and women include differences in outcome (morbidity/mortality) and healthcare utilization. Most, though not all, studies suggest an increase in mortality following the major osteoporotic fractures [9, 10]. While mortality following hip fracture is greater in men than women, it is also greater in men without fracture and the extent to which hip fracture is linked with any excess mortality in men (compared to women) is uncertain [11]. In large studies, after adjustment for age, the difference in mortality following vertebral fracture in men and women is not marked [12]. Hospitalization represents a substantial component of health-care costs. However, the proportion of men and women with hip (100%), wrist (20%) and spine fracture (10%) who are admitted to hospital is broadly similar and unlikely to contribute significantly to cost differentials [13, 14]. Length of stay among those admitted to hospital varies by age and type of fracture, though is generally shorter in men than women [5, 14]. Long-term nursing home care represents a large burden of hip fracture costs, but male sex has not been identified as a significant predictor of prolonged nursing home residence following hip fracture [15]. Differences in direct costs may also contribute to differences in the economic impact of fracture. Again these vary by age and fracture type and in different settings. Unit costs of fractures of different types calculated in a recent US study are shown in Table 31.1 [2]. Indirect costs of fracture might be anticipated to be greater in men than women, however, in an elderly group, employment levels generally are low.
Methodologic approaches to defining cost of illness Total Cost Economic costs of osteoporotic fracture can be estimated using either a ‘bottom up’ or ‘top down’ approach. In the ‘bottom up’ approach, cost data are obtained from cohort studies of patients with osteoporotic fracture – typically considered to be representative of a larger target
C h a p t e r 3 1 Economic Impact of Osteoporotic Fractures (versus Women)
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l
Table 31.1 Unit costs of fracture (US dollars) for white race, by sex and age group, total USA 2005 Women
Men
50–64 years old
65–74 years 75–84 years 85 years old old old
50–64 years 65–74 years old old
75–84 years 85 years old old
Inpatient LTC* Outpatient Total first year Total, years 2–5
31 548 10 810 4947 47 304 3367
25 935 12 246 4581 42 762 3672
24 536 12 171 4524 41 232 3915
23 147 14 391 4467 42 004 4106
24 339 9798 4268 38 405 3110
20 017 11 842 3977 35 836 3579
19 836 12 325 3974 36 135 3682
19 014 12 899 3959 35 872 3804
Vertebral Inpatient LTC* Outpatient Total first year Total, years 2–5
687 126 722 1535 344
658 116 720 1494 218
872 150 744 1766 368
779 143 743 1665 361
2515 459 894 3868 677
2441 438 891 3770 656
1042 183 755 1979 401
962 167 752 1,881 385
Wrist Inpatient LTC* Outpatient Total
413 92 448 953
359 80 401 840
745 167 739 1651
651 146 656 1453
1296 290 1220 2806
1172 263 1,112 2547
772 173 762 1706
916 205 888 2008
Pelvic Inpatient LTC* Outpatient Total first year Total, years 2–5
6809 5533 3291 15 633 840
6889 9151 3330 19 370 1560
6039 9249 2919 18 208 2076
6074 12 366 2936 21 376 2220
10 072 5303 4869 20 244 732
8139 7690 3935 19 764 1272
7831 10 729 3786 22 346 1864
7032 12 811 3399 23 243 2282
Other Inpatient LTC* Outpatient Total
2071 824 397 3292
2078 827 731 3636
2466 981 868 4315
3244 1291 1142 5676
1129 449 397 1975
1107 441 390 1937
2227 886 784 3896
2657 1057 935 4649
Hip
*
LTC Long-term care. Inpatient care includes inpatient facility, inpatient physician services and short-stay inpatient rehabilitation hospital care. Outpatient care includes home care, outpatient physician services, non-medical home care, outpatient hospital, and other outpatient care. LTC includes nursing home care (skilled nursing facilities, intermediate care facilities) and disability and dependency care. Reproduced from Burge et al. Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025. J Bone Miner Res 2007;22:465-75 [2]
population – and based on the actual costs incurred by these patients. The costs are then applied to the number of fractures which occur in a given time period (typically one year) estimated from national statistics or epidemiologic studies relevant to the country/region of interest to provide an overall cost. In the ‘top down’ approach, health care costs are based on cost data aggregated over groups of individuals and obtained from health-care providers or previous cross-sectional surveys. These are then applied to the number of fractures which occur with the costs adjusted to take account of the fact that not all fractures are related to osteoporosis. This is done by applying weights or attribution probabilities, typically derived by consensus among expert clinicians asked to estimate the likelihood that a given fracture by age, sex and site is due to osteoporosis. There are advantages and disadvantages with each approach. Studies which use a top down approach are easier
to perform though do not take account of all the costs incurred, including those related to complications, and are reliant on the validity of the osteoporotic attribution probabilities. The bottom up approach allows more accurate assessment of the economic cost, though the analyses are time consuming and, depending on the local population studied, there may be difficulties in generalizing the data to a larger population.
Attributable Cost Individuals with osteoporosis are older and have higher comorbidity levels – factors which contribute to increased costs even in the absence of fracture. For example, health costs incurred by individuals in the year prior to their sustaining a fracture are greater than in control subjects who do not [16]. To determine costs specifically related to a
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fracture event, these additional costs should be taken into consideration. Such costs are important for health care evaluation studies of interventions to reduce fracture where typically the costs of the intervention are compared with those that are potentially averted by avoiding the fracture. There are several study designs that can be used to estimate these costs. One approach is to use patients as their own control group and to compare the costs following fracture with those incurred during a comparative period of time prior to the fracture. The difference can be considered to be the excess cost which is related to the fracture – and thus the potential costs which could be saved had the fracture not occurred. Information about costs can be obtained prospectively or retrospectively. Accrual of data prospectively is costly and requires large numbers of subjects at risk of fracture, in whom there is information about health care utilization, to be followed. Accrual of data retrospectively (after the fracture has occurred) is cheaper though may be subject to errors of recording/recall. For both approaches, patients will be older in the year following fracture and costs slightly greater as a consequence, however, it is possible to make allowance or adjustment for this in the analysis. An alternative approach is to compare costs in those who sustain a fracture with the costs in a control group without fracture over a comparative time frame. The difference can be considered to be the incremental cost due to fracture. An important methodological consideration is that the morbidity experience of the fracture group should be similar (other than the fracture event) to that of the control group. Those with fracture typically have underlying osteoporosis which is associated per se with an excess morbidity and mortality: unless this is adjusted for, either in the study design (choice of control group) or the analysis, the costs related to the fracture may be overestimated. A third approach which has been used to assess the costs attributable to fracture is to follow patients from the time they sustain a fracture and to identify only the fracture related resource use. With this approach, it is possible to include all relevant costs incurred, information about costs prior to the fracture is not required and because no control group is needed the sample size does not need to be large. The main limitation, however, is determining whether or not a particular resource is related to the fracture or not.
Economic impact of osteoporotic fractures Over the past decade, and since publication of the first edition [17], there has been a significant increase in the number of studies which have considered the economic impact of osteoporotic fractures separately in men and women. Most, though not all, have focused on costs of the major
osteoporotic fractures, with hip fracture (which accounts for the greatest costs) being the most widely studied. Com parison of health-care costs in men and women is possible within individual studies, but direct comparison between studies is difficult because of differences in health care systems, patterns of treatment, unit costs, fracture occurrence and differences in study design and type of cost information obtained. In the following section, data from some of the major published studies are reviewed.
Total Costs North America One of the first reports of the costs related to fractures in North America was based on a large study of selected musculoskeletal conditions in men and women [18]. The report, based on 1977 data, estimated that the number of hospital discharges in the USA with a first diagnosis of osteoporosis was 26 000, with men comprising 20% of cases. The cost of all fractures (direct and indirect costs) was estimated at $18.1 billion. All hip fractures, not just those occurring in the elderly, were estimated to cost $7.3 billion; 40% of all fracture related costs. The study highlighted the significant contribution of nursing home costs to the overall direct medical costs of hip fracture (56%). The data were updated in 1988 when the projected total cost of all fractures in the USA was estimated at $20.1 billion, with hip fractures comprising 43% of the overall fracture costs [19]. Neither study, however, separately considered men and women in detail. In the first cost of illness survey to consider costs separately in men and women, Ray et al [20] estimated the direct medical expenditure associated with osteoporotic fracture for all persons aged 45 years and older in the USA in 1995. The study was notable in that expenditures for many types of fracture were included, though detailed information was presented for hip, spine and forearm fracture only. National health-care survey data (from the National Center for Health Statistics and the Agency for Health Care Policy and Research) were used to estimate the health resource utilization and expenditures. Indirect costs were not estimated. Osteoporosis attribution probabilities, based on expert clinician review, were used to estimate the proportion of health service utilization and expenditures of fractures that resulted from osteoporosis [21]. Overall, the cost of health care expenditure attributable to osteoporotic fractures in 1995 was $13.8 billion, of which approximately 20% ($2.7 billion) was spent on men. By site of service, 62% was spent on inpatient care, 28% nursing home care and 9% in outpatient care. Hospital costs accounted for a greater proportion of the total costs in men than women (66% versus 62%), while nursing home costs were less (23% versus 29%). Costs for hip fracture comprised a larger proportion of the total economic burden of fracture in men than women (73% versus 61% respectively). Of the total expenditure on hip fractures, 22.6% was in men.
C h a p t e r 3 1 Economic Impact of Osteoporotic Fractures (versus Women) l
In a later study, Max et al reported on costs related to osteoporosis by considering hospital discharges with a primary diagnosis of osteoporosis/fracture in men and women in California in 1988 [22]. The study also looked at indirect costs. Most subjects studied had sustained a fracture; almost one half had a hip fracture. The mean cost for an osteoporosis related hospitalization was greater in women than in men ($6025 versus $4991). Total direct costs were $634 million in men and $1.8 billion in women – with nursing home care the largest component (64% and 57% in men and women respectively). As in earlier studies, hip fractures were the most costly osteoporotic fracture, though the proportion of total expenditure devoted to hip fracture in this study was similar (64%) in men and women. Indirect costs were relatively small, less than 1% of the total, reflecting the fact that most sufferers had retired and thus had no loss of productivity, and were greater in men than women ($2.6 million and $1.7 million respectively). The most recent data from North America evaluated health costs related to osteoporotic fractures in 2005 by age gender and fracture type, including hip, wrist and spine fracture [2]. Indirect costs were not assessed in the study, though these comprise a relatively small proportion of the total costs [22]. Key data sources were fracture incidence rates based on published epidemiological data and national discharge databases, mortality rates, US population estimates and unit costs for each fracture types. Unit costs were estimated by age and sex based on inpatient, outpatient and long-term care components; these varied by age, sex and fracture type and, for hip fracture, were greater in women than men, with the converse true for fractures of the wrist and spine (see Table 31.1). A Markov model was used to estimate both the incidence of fracture and related costs in the US population aged
50–99 years. In 2005, the model predicted more than 2 million incident fractures at a cost of $16.9 billion (Table 31.2). Men accounted for 29% of the fractures and 24% of the costs ($4.1 billion). The distribution of costs by fracture differed for men compared with women with a lower proportion of the total spent on hip fracture in men (67% versus 73%) and a higher proportion spent on vertebral (10% versus 5.2%) and other fractures (15% versus 13.7%) (see Table 31.2). Costs increased with age in both men and women with the bulk of the costs spent on those aged 65 years and older (81% and 89% in men and women, respectively). Using data from a population cohort study, Witkorowicz et al analyzed the one year cost of hip fracture in men and women aged 50 years and over in Canada [23]. Health-care resources assessed included initial hospitalization, rehospitalization, rehabilitation and chronic care, long-term care, home care and informal care. Costs were determined using a bottom up approach including the cost of the individual hip fracture procedure and the patient’s length of stay. Overall costs for women were, as in the recent US study [2], higher than men ($27 793 versus $22 700). However, after adjustment for age, residence status, survival (did or did not die within 12 months) and duration of follow up, the gender difference in the fracture cost disappeared, suggesting that the effect of gender, at least on the cost of hip fracture in this study, was due to these factors. Europe Hip Fracture There are data from a number of European countries which include cost estimates for fracture in men and women. Using a ‘top down’ approach, the total direct costs of hip
Table 31.2 Fracture costs by fracture type, age and gender, USA 2005 Costs per fracture type ($ millions) Stratum
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Hip
Vertebral
Wrist
Pelvic
Other
Total
Age (years) 50–64 65–74 75–84 85 Total
263 360 991 1127 2741
109 133 101 71 414
115 22 10 10 158
34 27 61 66 188
269 125 129 95 619
790 667 1292 1370 4119
Women Age (years) 50–64 65–74 75–84 85 Total
614 1045 3521 4138 9319
91 126 253 193 663
130 76 113 58 377
34 67 253 331 686
564 318 461 410 1752
1433 1633 4601 5129 12 797
Men
Adapted from Burge et al. Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025. J Bone Miner Res 2007;22:465-75 [2]
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fracture in Germany in 2002 was estimated at €2200 million in women and €536 million in men. Indirect costs were relatively small, amounting to €152 million in women and €110 million Euros in men [24]. Using a bottom up approach, Reginster et al looked at the direct costs (excluding nursing home costs) of hip fractures in a cohort of 2374 patients over 60 years of age in Belgium [25]. Most data were presented in men and women combined, though data on the distribution of mean acute (hospital) costs of hip fracture by age and gender were presented. Costs were broadly similar in men and women. In a Swedish study of 180 hip fracture patients, however, the total short-term costs (within 4 months) were greater in women than men [26]. Factors significantly linked with higher costs included increasing age, type of fracture (troch anteric cervical) and poorer prefracture functional status. Vertebral Fracture There are few studies that have focused exclusively on costs related to vertebral fracture. Estimating costs is more difficult than for other fracture types as many patients do not come to clinical attention. In a recent European study, the costs of hospitalization in men and women 50 years and over was estimated using data collected at a national level [14]. The average cost of hospitalization for those with an uncomplicated vertebral fracture (without neurologic deficit) was higher for women than men (EU mean cost €3457 versus €3305) in part because length of stay was longer (13.1 versus 11.8 days) [14]. These costs were, on average, 67% of the average cost of a hip fracture for men (compared with 58% in women). It was thought the longer stay in hospital for women might be because osteoporosis is expected in women and only the more serious cases are admitted, while men may be more likely to be admitted for shorter periods for investigation to exclude secondary cause of fracture. Given the higher cost and greater number of women affected, the total cost of vertebral fracture in the EU was greater in women than men (€227 million versus €149 million) [14]. The overall cost of vertebral fracture, however, is likely to be higher as non-acute costs were not included in the analysis and may be significant [16, 27]. All Fractures Using a top down approach, Lippuner et al [28] looked at the direct costs of acute hospitalization for osteoporotic fractures in Switzerland in men and women in 1992. The mean length of hospitalization for osteoporotic fractures was greater in women than men. Fractures of the proximal lower limb contributed most to the burden of hospitalization; for women, this comprised just under a half of the total hospital bed days and, for men, one third. Using a similar daily cost of hospitalization in men and women (845 Swiss Francs), the total cost amounted to 464 million Swiss francs in women and 130 million Swiss francs for men. Inclusion
of nursing home, other non-hospital costs and indirect costs would obviously further increase these costs. In one of the few published studies to focus exclusively on men, and using a top down approach, Levy et al [29] looked at the cost of osteoporosis and related fractures in those aged 50 and over in France. Attribution probabilities were adapted from Melton [21]. A total of 23 260 acute hospitalizations in men were considered to be related to osteoporosis – 52% of which were for hip fracture. Mean cost per stay varied from €1300 for wrist fracture to €5900 for hip fracture. The total cost of acute hospitalization was €97.6 million, with hip fractures accounting for 73.2% of the total expenditure. Rehabilitation and convalescence costs were €90.8 million and outpatient costs were €9.1 million, resulting in total direct medical costs of €197.5 million. After adjusting for differences in demographics and exchange rates, these costs were about one quarter of the costs observed in the Swiss study [28] and one half of a US study [20]. Differences in unit costs may in part explain these differences. Costs in women based on an earlier survey (and inflated to 1999 prices) were about one third those in French women [30]. Using data from a range or sources, Kanis and Johnell estimated the direct cost of osteoporotic fractures in Europe (EU) at €27 billion in women and €8.7 billion in men [1]. Overall costs increased with age though there was variation in the rate of change with age by fracture type (Table 31.3). Other Regions Australia Randell et al studied the direct costs associated with 151 osteoporotic fractures occurring between 1989 and 1992 in a large cohort of elderly men (DUBBO) [31]. The median cost of hospital treated fractures was $A10 511 per fracture and non-hospitalized fractures $A455 per fracture in 1992
Table 31.3 Estimated costs of osteoporotic fractures in Europe (€000) by fracture site, age and gender Age (years)
Hip
Spine
Other
Total
Men 50–64 65–74 75–84 85 50
544 1111 1637 1264 4556
69 63 45 21 198
473 389 360 2781 4003
1086 1563 2042 4067 8757
Women 50–64 65–74 75–84 85 50
813 2751 9120 7112 19 796
101 165 152 102 521
1253 1376 2553 1992 7173
2168 4293 11 824 9206 27 491
Adapted from Kanis et al. Requirements for DXA for the management of osteoporosis in Europe. Osteoporos Int 2005;16:229-38 [1]
C h a p t e r 3 1 Economic Impact of Osteoporotic Fractures (versus Women) l
Australian dollars. There was little difference in the overall hospital costs between men and women, though for hip fracture, direct costs were significantly greater in women than men ($A18 890 versus $A12 815). Extrapolating from the sample to the Australian population, the total cost of osteoporotic fracture was estimated to be $A779 million with 21.9% of the total fracture costs in men; 53.5% of the total costs were attributable to hip fracture. Middle East Hospital costs of all patients (50 years) admitted to an orthopedic unit in an eastern Saudi Arabian province following a low trauma fractured femur were calculated. The direct costs per fracture were greater in women than in men (US$14 288 versus US$12 388), related in part to a longer hospital stay in women (20.7 versus 15.8 days) [32]. Overall costs (all fractures), however, were similar since despite the lower cost there were a greater number of men with hip fracture. This is consistent with epidemiological data from the area that suggest fracture incidence is broadly similar in men and women [33].
Attributable Costs In contrast to the data concerning total costs, less is known about the excess costs attributable to fracture in men. Excess Costs In one of the first studies to consider excess costs related to fracture in men, Zethraeus et al estimated costs for hip fracture in 1709 hip fracture patients admitted during 1992 in Stockholm, Sweden [34]. Direct costs arising in the healthcare sector and social welfare system were available during the year before and the year after the fracture event. Data regarding days in orthopedic departments and other acute hospital care costs were extracted from the inpatient database of the Stockholm county council, while data regarding days in a nursing home were extracted from the municipality database. Direct costs during the year after and the year before fracture were higher for women than men, due in part to a higher mean age in women and longer survival. The difference in costs (year after – year before) was also greater in women (US$18 985 versus US$13 373). This was true at all ages except 65–74 years where the difference was greater in men (US$16 306 versus US$12 657). Brainsky et al looked at costs before and after fracture in a group of men and women with hip fracture but did not consider costs separately in men and women [35]. Incremental Costs Using data from Olmstead County, Minnesota, Gabriel et al characterized the incremental direct medical costs (excluding nursing home costs) following osteoporotic fractures by
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comparing the costs among those who sustained a fracture with a control group who had not [36]. Cases included all county residents aged 50 years of age and older with an incident fracture due to minimal or moderate trauma during 1989–1992. Unit costs were obtained through the Mayo cost data warehouse which provides standardized estimates reflecting the national average cost of providing the service. Overall, there were 1263 case control pairs with an average age of 73.8 years and 78% were female. In a subset of 985, there were no significant differences in the excess costs for specific fractures in men and women and there were no statistically significant trends with increasing age in either sex [37]. Incremental costs in the year following fracture were US$11 241 for hip, US$1628 for wrist and US$1955 for spine fracture. Based on the age and sex specific incremental costs and using reference age, sex-specific incidence for each fracture type, it was possible to look at overall incremental costs in the year following fracture (case–control). In this analysis, the cost of all osteoporotic fractures combined was 46% greater than that for hip fractures alone in women and 47% greater in men. The results highlight the importance of considering all categories of fractures when determining the cost effectiveness of treatment or of prevention measures. In addition to looking at the difference in cases and controls (incremental costs), the authors also looked at costs in the year prior to and the year following fracture (excess costs) and were able to compare these costs with the data from the case–control analysis. Differences in costs using the two approaches were not large, though broadly, the excess cost approach resulted in a modest underestimate of the incremental costs. The latter were considered a better approximation of the true attributable cost. In the Swedish KOFOR study, the additional costs of fracture (direct and indirect) were determined by considering the costs specifically due to the fracture event within a large cohort of fracture patients. Overall costs of hip fracture were €14 920 in men and €14 033 in women. Costs increased with age in women from €11 082 at age 50 – 64 years to €18 743 age 85 , though not in men [38]. The cost increase with increasing age in women is mostly because of a rise in resource use in community care, in particular home help and accommodation. Additional costs due to wrist fracture did not vary by age or gender, while costs due to vertebral fracture did not vary by gender.
Projected Costs Life expectancy is increasing in most developed countries and, as a consequence, the number of elderly men and women will rise. The projected increase is greater for men than women: across Europe, for example, the proportion of men aged 50 years and over is set to increase by 36% between 2000 and 2050 and 26% in women [1, 39]. The increase will be most marked in the very elderly (80 years) with a 239% increase
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Table 31.4 Projected costs of osteoporotic fractures in Europe (€000 000) Calendar year
Men
Women
Men and women
2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
8.7 9.2 10.5 12.2 13.2 14.7 15.8 17.7 19.7 21.3 22.8
27.5 29.6 32.0 35.1 36.3 39.3 42.2 46.1 49.7 52.2 53.9
36.3 38.7 42.6 47.3 49.7 54.0 57.9 63.8 69.3 73.5 76.8
Reproduced from Kanis et al. Requirements for DXA for the management of osteoporosis in Europe. Osteoporos Int 2005;16:229– 38 [1]
in the number of men and a 160% increase in the number of women. More marked increases are projected in other regions worldwide, particularly in Asia, with a 7.6-fold increase in expected numbers of elderly men [7]. Because the rate of fractures and, in particular, hip fractures, increases exponentially with age, the number of fractures and, consequently, the economic impact of osteoporosis, is set to rise substantially. The projected increase in the cost of osteoporotic fractures between the years 2000 and 2050 (based on UK costings) across Europe are summarized in Table 31.4 [1]. For men, costs are set to increase from €8.7 billion to €22.8 billion, a 2.6-fold rise. Indeed, by 2050, the costs of fracture in men will begin to approach current costs in women. These data compare with an approximate doubling in costs in women during the same time period. The estimates may be conservative in that they do not take account of any changes in the secular trend for fracture incidence that may occur. Also, they assume no changes in health-care costs that, given ongoing improvements in health care, seem likely to rise. In the USA, the burden of osteoporotic fractures is projected to increase from a current level of $17 billion to $25.3 billion by 2025 with a quarter of the total cost being borne by men [2].
Summary Osteoporosis is an important and increasing health burden. The economic impact of osteoporosis and osteoporotic fractures in most developed countries is greater in women than men, primarily because fractures are more frequent in women. The economic impact in men is, however, substantial. Current estimates of the costs of osteoporotic fractures in men aged 50 and over are $4.1 billion in the USA and €8.7 billion in Europe, which represents about 24% of the total costs of osteoporosis. Costs are greatest for hip fracture, due to a combination of acute hospital costs and long-term
care. Direct costs tend to be lower in men than women – in part related to differences in age and length of hospital stay. Nevertheless, consideration of hip fractures alone substantially underestimates the economic burden of osteoporosis in men. The health costs related to osteoporotic fractures in men is projected to increase by 2.6-fold across Europe over the next 50 years, primarily due to increasing number of fractures as a consequence of increasing life expectancy. The projected increase will be greater in other regions, particularly Asia. There is an urgent need therefore to develop targeted, cost effective intervention and treatment programs to reduce the occurrence and associated health costs related to osteoporosis in men.
References 1. J.A. Kanis, O. Johnell, Requirements for DXA for the management of osteoporosis in Europe, Osteoporos Int. 16 (2005) 229–238. 2. R. Burge, B. Dawson-Hughes, D.H. Solomon, J.B. Wong, A. King, A. Tosteson, Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025, J. Bone Miner Res. 22 (2007) 465–475. 3. K. Lippuner, M. Golder, R. Greiner, Epidemiology and direct medical costs of osteoporotic fractures in men and women in Switzerland, Osteoporos Int. 16 (2005) S8–S17. 4. O. Johnell, J.A. Kanis, B. Jonsson, A. Oden, H. Johansson, C. De Laet, The burden of hospitalised fractures in Sweden, Osteoporos Int. 16 (2005) 222–228. 5. C. Cooper, G. Campion, L.J. Melton III, Hip fractures in the elderly: a world-wide projection, Osteoporos Int. 2 (1992) 285–289. 6. L.J. Melton III, Epidemiology of fractures, in: B.L. Riggs, L.J. Melton III (Eds.), Osteoporosis: etiology, diagnosis and management, second ed., Lippincott-Raven, Philadelphia, 1995, pp. 225–247. 7. J.A. Kanis, on behalf of the World Health Organisation Scientific Group. Assessment of osteoporosis at the primary health care level. Technical Report, 2007. WHO Centre for Metabolic Bone Diseases, University of Sheffield. 8. S.R. Cummings, L.J. Melton III, Epidemiology and outcomes of osteoporotic fractures, Lancet 359 (2002) 1761–1767. 9. C. Cooper, E.J. Atkinson, S.J. Jacobsen, W.M. O’Fallon, L.J. Melton III, Population based study of survival after osteoporotic fractures, Am. J. Epidemiol. 137 (1993) 1001–1005. 10. J.R. Center, T.V. Nguyen, D. Schneider, P.N. Sambrook, J.A. Eisman, Mortality after all major types of osteoporotic fracture in men and women: an observational study, Lancet 353 (1999) 878–882. 11. J.A. Kanis, A. Oden, O. Johnell, C. De Laet, B. Jonsson, A.K. Oglesby, The components of excess mortality after hip fracture., Bone 32 (2003) 468–473. 12. J.A. Kanis, A. Oden, O. Johnell, C. De Laet, B. Jonsson, Excess mortality after hospitalisation for vertebral fracture, Osteoporos Int. 15 (2004) 108–112. 13. T.W. O’Neill, C. Cooper, J.D. Finn, et al., Incidence of distal forearm fracture in British men and women, Osteoporos Int. 12 (2001) 555–558.
C h a p t e r 3 1 Economic Impact of Osteoporotic Fractures (versus Women) l
14. H.W. Finnern, D.P. Sykes, The hospital cost of vertebral fractures in the EU: estimates using national datasets, Osteoporos Int. 14 (2003) 429–436. 15. J. Steiner, A. Kramer, T. Eilertsen, J. Kowalsky, Development and validation of a clinical prediction rule for prolonged nursing home residence after hip fracture, J. Am. Geriatr. Soc. 45 (1997) 1510–1514. 16. S. Puffer, D.J. Torgerson, D. Sykes, P. Brown, C. Cooper, Health care costs of women with symptomatic vertebral fractures, Bone 35 (2004) 383–386. 17. A.N.A. Tosteson, Economic impact of fractures, in: E.S. Orwoll (Ed.), Osteoporosis in Men, Academic Press, San Diego, 1999, pp. 15–27. 18. T.L. Holbrook, K. Grazier, J.L. Kelsey, R.N. Stauffer, Frequency of occurrence, impact and cost of selected musculoskeletal conditions in the United States, American Academy of Orthopedic Surgeons, Chicago, 1984. 19. A. Praemer, S. Furner, D.P. Rice, Musculoskeletal conditions in the United States, American Academy of Orthopedic Surgeons, Chicago, 1992. 20. N.F. Ray, J.K. Chan, M. Thamer, L.J. Melton III, Medical expenditures for the treatment of osteoporotic fractures in the United States in 1995: report from the National Osteoporosis Foundation, J. Bone Miner Res. 12 (1997) 24–35. 21. L.J. Melton III, M. Thamer, N.F. Ray, et al., Fractures attributable to osteoporosis: report from the National Osteoporosis Foundation, J. Bone Miner Res. 12 (1997) 16–23. 22. W. Max, P. Sinnot, C. Kao, H.Y. Sung, D.P. Rice, The burden of osteoporosis in California, 1998, Osteoporos Int. 13 (2002) 493–500. 23. M.E. Wiktorowicz, R. Goeree, A. Papaioannou, J.D. Adachi, E. Papadimitropoulos, Economic implications of hip fracture: health service use, institutional care and cost in Canada, Osteoporos Int. 12 (2001) 271–278. 24. A. Konnopka, N. Jerusel, H.H. Konig, The health and economic consequences of osteopenia- and osteoporosisattributable hip fractures in Germany: estimation for 2002 and projection until 2050. Osteoporos Int 2008 [Epub ahead of print] Dec 2nd. 25. J.Y. Reginster, P. Gillet, W.B. Sedrine, et al., Direct costs of hip fractures in patients over 60 years of age in Belgium, Pharmacoeconomics 15 (1999) 507–514. 26. L. Borgquist, G. Lindelow, K.G. Thorngren, Costs of hip fracture. Rehabilitation of 180 patients in primary health care, Acta Orthop. Scand. 62 (1991) 39–48.
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27. P. Dolan, D.J. Torgerson, The cost of treating osteoporotic fractures in the United Kingdom female population, Osteoporos Int. 8 (1998) 611–617. 28. K. Lippuner, J. Overbeck, R. Perrelet, H. Bosshard, P.H. Jaeger, Incidence and direct medical costs of hospitalizations due to osteoporotic fractures in Switzerland, Osteoporos Int. 7 (1997) 414–425. 29. P. Levy, E. Levy, M. Audran, M. Cohen-Solal, P. Fardellone, J.M. Le Parc, The cost of osteoporosis in men: the French situation, Bone 30 (2002) 631–636. 30. E. Levy, Cost analysis of osteoporosis related to untreated menopause, Clin. Rheumatol. 8 (Suppl. 2) (1989) 76–82. 31. A. Randell, P.N. Sambrook, T.V. Nguyen, et al., Direct clinical and welfare costs of osteoporotic fractures in elderly men and women, Osteoporos Int. 5 (1995) 427–432. 32. D. Bubshait, M. Sadat-Ali, Economic implications of osteoporosis-related femoral fractures in Saudi Arabian society, Calcif Tissue Int. 81 (2007) 455–458. 33. A. Memon, W.M. Pospula, A.Y. Tantawy, S. Abdul-Ghafar, A. Suresh, A. Al-Rowaih, Incidence of hip fracture in Kuwait, Int. J. Epidemiol. 27 (1998) 860–865. 34. N. Zethraeus, L. Stromberg, B. Jonsson, O. Svensson, G. Ohlen, The cost of a hip fracture: estimates for 1709 patients in Sweden, Acta Orthop. Scand. 68 (1997) 13–17. 35. A. Brainsky, H. Glick, E. Lydick, et al., The economic cost of hip fractures in community-dwelling older adults: a prospective study, J. Am. Geriatr. Soc. 45 (1997) 281–287. 36. S.E. Gabriel, A.N.A. Tosteson, C.L. Leibson, et al., Direct medical costs attributable to osteoporotic fractures, Osteoporos Int. 13 (2002) 323–330. 37. L.J. Melton III, S.E. Gabriel, C.S. Crowson, A.N.A. Tosteson, O. Johnell, J.A. Kanis, Cost equivalence of different osteoporotic fractures, Osteoporos Int. 14 (2003) 383–388. 38. F. Borgstrom, N. Zethraeus, O. Johnell, et al., Costs and quality of life associated with osteoporosis-related fractures in Sweden, Osteoporos Int. 17 (2006) 637–650. 39. United Nations Population Division, World population prospects: the 2002 revision and world urban prospects, Population Division of the Department of Economic and Social Affairs of the UN Secretariat, 2003.
Chapter
32
Adverse Health Outcomes in Men with Osteoporosis Deborah T. Gold1 and Stuart L. Silverman2 1
Duke University Medical Center, Durham, North Carolina, USA Cedars-Sinai/UCLA and the OMC Clinical Research Center, Los Angeles, CA, USA
2
Introduction
Morbidity in men after osteoporotic fractures
In 2004, the Surgeon General of the USA issued the first report on osteoporosis and bone health [1]. That document reported that over 10 million American women and men had osteoporosis and another 34 million had low bone mass. Had the Surgeon General written this report 30 years earlier, in 1974, the report on osteoporosis would almost certainly have discussed only postmenopausal osteoporosis. Few lay people believed that men could have osteoporosis; few physicians and other health professionals were examining men’s bones to determine if skeletal loss had occurred. The evidence about men and osteoporosis has changed over the last 30 years [2]. Recent data suggest that at least 20% of people with osteoporosis are men. That means that 2 million men or more already have osteoporosis and another 12 million are at risk of the disease [1]. As life expectancy in the USA continues to rise, osteoporosis prevalence in men will increase. In light of these changing demographics, we need a better understanding of the incidence and gender-specific consequences of osteoporosis in men. In this chapter, we review research findings from the last decade that specifically illuminate the adverse outcomes of osteoporosis and consequent fractures in men. These outcomes include, but are not limited to, physical morbidity, psychosocial outcomes (including health-related quality of life) and mortality. Although the empirical evidence about men and their osteoporosis outcomes is somewhat limited, some recent studies have begun to help us understand what happens when men with osteoporosis experience fractures.
Osteoporosis in Men
The three most common atraumatic fractures that occur because of osteoporosis are those of the wrist or forearm, the vertebrae and the hip. We examine the incidence and/or prevalence of these three fractures in men as well as the morbidity they cause.
Wrist Fractures The pattern of wrist fractures in men is different from that in women. Women’s risk of wrist fracture begins after the menopause and continues to be substantial; however, the incidence of wrist fractures in men with osteoporosis peaks in the years between 50 and 64, then drops somewhat dramatically during the remaining years of adulthood [3]. According to findings in Dubbo, Australia, the incidence of forearm and wrist fractures in men was 33.8 per 10 000 person-years while the incidence for women was 124.6 per 10 000 personyears [4]. Symptoms following wrist fracture in both men and women include complaints of hand pain, weakness and, rarely, reflex sympathetic dystrophy (RSD), also known as complex regional pain syndrome [5]. Impairments in activities of daily living (ADL) and instrumental activities of daily living (IADL) have been reported in women post fracture but have not been studied in men [6].
Radiographic Vertebral Fractures In both men and women in The European Vertebral Osteoporosis Study (EVOS), a community-based cohort of men and women from 19 European countries, individuals
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with radiographic vertebral deformity (RVD) reported limitations in back-related activities of daily living, back pain and poorer self-rated health [7]. Multiple severe deformities were significantly associated with worse function, greater pain and poorer health status. These findings were stronger in men than in women. In a second study using EVOS data, investigators studied 756 men and 885 women who had radiographic evidence of vertebral deformities [8]. Although women with a single RVD were more likely to report back pain in association with lumbar than thoracic deformities, no such association was seen in men. Among men, nonadjacent deformities were associated with greater impaired functional disability than were adjacent deformities. Finally, the location of RVDs did not differ between men and women; some clustering occurred at the mid-thoracic region and the thoraco-lumbar junction in those with two deformities, suggesting that biomechanical factors might be the reason [9]. One of the few studies to examine racial differences in the prevalence of morphometric vertebral fractures in men used data from the Baltimore Men’s Osteoporosis Study [10]. Participants included 415 white men and 127 black men with a mean age of 74.0 5.7 years. The prevalence of these radiographic fractures was significantly higher in white men (7.3%) than in black men (7.3% versus 0.9%, P 0.01). The authors suggest that this difference may result from different bone mineral density between the two groups of men [11].
Clinical Vertebral Fractures Leidig and colleagues studied a cross-sectional clinical sample of 19 men (mean age: 52 12 years) and 51 women (mean age: 61 11 years) admitted to hospital for clinical vertebral fracture. They found a correlation between spinal deformity index and physical limitations of 0.44 (P 0.001) [12]. Of those with physical limitations, pain occurred with activity (64%), limited bending (71%) and limited rising (70%). Forty-one percent of this sample needed help with self-care. Unfortunately, data from men and women were not analyzed separately in this study. In the Canadian Multicentre Osteoporosis Study (CaMos), both men and women with clinical vertebral fractures reported lower health-related quality of life as measured by the Health Utility Index (HUI) as compared to participants without such fractures [13]. Interestingly, there were no gender differences with statistically significant deficits in pain experienced by both genders (P 0.05). Women experienced a greater impact in self-care, mobility and ambulation (P 0.05 for all) while men did not. However, it is important to note that the small sample of men may strongly influence these findings. The number of men with spine (n 9), hip (n 14) and pelvis (n 1) fractures was minuscule. It would be interesting to replicate these findings with a larger male sample.
Finally, in EVOS, investigators studied the long-term impact of fractures on long-term morbidity. They revisited participants 12 years after they experienced clinical vertebral fractures and found gender differences in long-term morbidity. While women had significantly greater current back pain than controls (42% versus 19%, P 0.006) and impaired health status (44% versus 17%, P 0.001), men reported only marginally significant current back pain (P 0.09) and had no significant reduction in health status [14].
Hip Fracture Of all osteoporotic fractures, hip fractures result in the greatest morbidity and mortality of any fractures in men. In 2005, there were 281 256 non-traumatic hip fracture hospitalizations in the USA in 67.1 million individuals aged 55 and older. Of these, 73 267 or 26% occurred in men; an incidence of 243.9/100 000. Comparable 2005 numbers for women are 207 989 non-traumatic hip fracture hospitalizations or 74% in women with an incidence of 560.5/100 000 [15]. As in women, men’s hip fracture rates increase exponentially with aging. For example, at age 55, the incidence of hip fracture in men was 23.7/100 000 which tripled by age 65 to 70.5, quadrupled again by age 75 to 319.1/100 000 and increased fivefold for ages 85 and older (1573.9/100 000). This exponential increase is essentially parallel for men and women with an average 3.5 year ‘lag’. At any age, prevalence rates for men are equivalent to those of women 3–4 years younger [15]. In both men and women, hip fracture results in marked impairment of function and physical performance [16–19]. In a study by Jette and colleagues [18], only 33% of those with intertrochanteric fractures returned to reported levels of prefracture functioning in ADLs, while 21% with subcapital hip fractures regained ADL function at one year. At 6 months after a hip fracture, approximately one fourth of patients regain prefracture levels of IADLs, with no further recovery by one year [18]. Magaziner and colleagues [17] showed that a significant proportion of older adults did not recover prefracture functional status after hip fracture. In addition, physical performance by patients who experienced hip fractures declined significantly. At 6 months, only 15% of hip fracture patients could walk independently compared to 75% at baseline; at 6 months, only 8% of these patients could climb stairs compared to 63% prefracture [20]. Further, Silverman and Zingmond [21] found that men in California were more likely to be discharged from the hospital to home after a hip fracture than were women (17.0% versus 9.5%). Men were also less likely to be sent to skilled nursing facilities than women (61.2% versus 72.4%). A similar proportion of men and women went to rehabilitation facilities (8.2% versus 7.9%). This finding is not surprising given that most men have younger wives who are able to care for them at home, while most women married older men who are either deceased or unable to provide care once a hip fracture occurs [22].
C h a p t e r 3 2 Adverse Health Outcomes in Men with Osteoporosis l
Psychosocial consequences of osteoporotic fractures in men Women with osteoporosis suffer multiple intrusions on their psychosocial functioning as a result of their fractures [23–25]. Fewer data are available about men [26].
Social Role Loss Studies examining the impact of fragility fracture on social role loss are limited. However, Greendale and colleagues [27] note that hip fracture results in significant losses in social/role function in women with only 26% returning to prefracture levels after recovery from the hip fracture. In CaMos, investigators found that those participants with fractures had substantially worse health-related quality of life (HRQOL) than those without fractures [28]. In terms of gender, men were most affected by hip fracture in the role physical domain while women were most affected in the physical functioning domain. This difference would be an interesting concept to pursue, given that many men define themselves by what they are able to do in the way of traditional role responsibilities (e.g. yard work, carrying garbage out, etc.).
Depression For almost two decades, researchers have been examining the relationship between depression and osteoporosis. Some studies used case-control designs to examine the relationship between depression or depressive symptoms and bone mineral density (BMD) in men and women and found that the relationship between low BMD and depression was stronger in men than in women [29,30]. Others used community or clinical samples to determine the cross-sectional correlation of the same variables and found that a statistically significant relationship between depressive symptoms and BMD existed only in white women [31]. Whooley and colleagues [32], in one of the few studies looking only at community-dwelling men to determine whether depressive symptoms and BMD were correlated cross-sectionally, provided support for the finding by Robbins and colleagues [31] that a significant relationship was not evident in men. However, few studies of men or women have examined depressive symptoms as an outcome of osteoporotic fracture rather than as a risk factor or predictor of osteoporosis. Even in studies of large, nationally representative samples, such as NHANES I which had a sample size of 6195 black and white adults (age range: 25–74), the relationship examined is the association between depression and subsequent hip fracture [33]. In determining the incidence of hip fractures in three categories of depressive symptoms, the investigators found that those classified in the ‘high’ depressive symptoms category had a greater incidence of hip fracture per 10 000 person-years (20.27) than did those in the intermediate (12.03) or low (10.83) categories.
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However, there is a growing literature which takes the opposite perspective and suggests that depression can result from hip fracture and its surgical repair. Researchers have well documented the fact that post-hip fracture depression and/or cognitive impairment has deleterious effects on rehabilitation [34]. Lenze and colleagues [35] examined the onset of major depressive disorder (MDD) after hip fracture, as well as possible risk factors for onset of MDD at that time. In 126 hip fracture patients age 60 years consecutively admitted to an acute care hospital who had surgical repair of the fracture, 14.2% developed MDD after hip fracture and the greatest risk period for MDD was immediately after the hip fracture. These findings, it would appear, suggest that a psychiatric intervention after hip fracture might prevent depression from developing or might minimize the impact of depressive symptoms. However, a study in England examined the impact of prevention and treatment interventions for posthip fracture depression [36]. This study did confirm previous findings that showed that approximately 42% of hip fracture patients – women and men – experienced depression after hip fracture and surgery. Of the 121 men and women who experienced surgical repair of hip fractures and became depressed immediately after the fracture, those receiving the treatment intervention did not differ from the usual care group in terms of depressive symptoms. Further, of the 172 men and women with hip fracture who were not depressed at baseline (i.e. directly after the fracture), those who received a preventive depression intervention did not differ in the development of depression from those in usual care [36]. Although we have made progress in understanding the relationship between depression and osteoporosis, much additional work remains. If we are to prevent or treat effectively post-fracture depression, we must utilize longitudinal research designs in both men and women to better understand the causal direction of the relationship.
Health-Related Quality Of Life Although an increasing number of studies of postmenopausal osteoporosis now include health-related quality of life (HRQOL) as an important outcome after fracture, few studies have examined HRQOL in men with osteoporosis and fractures. The Hertfordshire Cohort Study [37] included 737 men (mean age 64.3 2.6 years) and 675 women (mean age 65.7 2.5 years) and examined the relationship between HRQOL, measured with the SF-36 [38] and BMD. For the first time, its results showed a robust and significant correlation between quality of life and bone mineral density in men. The odds ratios between femoral neck BMD and SF-36 domains for men were as follows: physical functioning (0.72 (0.53, 0.97); P 0.03), social functioning (0.70 (0.53, 0.94); P 0.02) and general health (0.74 (0.56, 0.99); P 0.05). Relationships for
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the same domains in the women are much weaker: physical functioning (0.71 (0.50, 1.00); P 0.05), social functioning (1.16 (0.89, 1.52); P 0.27) and general health (0.97 (0.72, 1.31); P 0.83). Only 16% of the men and women in this study had experienced a fracture after age 45 [37]. In another study in England, Pande and colleagues recruited 100 consecutive men over age 50 who had a fragility fracture of the hip and were admitted to the Royal Cornwall Hospital, UK in the mid-1990s; they also recruited 100 controls who had not experienced a hip fracture [39]. The patients completed the SF-36 [38] and other scales soon after fracture and changes were analyzed at 6, 12 and 24 months post baseline. Perhaps not surprisingly, at baseline, the cases rated their HRQOL lower than did the controls. Further, the immediate impact of the fracture led to a deterioration in physical health scores but not the mental health scores. Physical health scores continuously declined until, at 2 years post fracture, they were 1.7SD below the US mean for that dimension. Two years later, there was also a significant decline in mental health scores (P 0.04). Additional declines were seen in the men with fractures as well. One year after hip fracture, only 36% of patients (17/47) walked unassisted; at 24 months, that proportion decreased to only 34% of the remaining patients (12/35). A population-based case control study was done by Ekstrom and colleagues [40] in Sweden to determine whether elderly men and women with fracture and pain (n 87) or with fracture and no pain (n 82) differed in HRQOL, life satisfaction and social activities from no fracture controls (n 239). They used the SF-12 [41] and the Life Satisfaction scale [42] to measure HRQOL and life satisfaction. Overall, this study showed that individuals with fractures had lower HRQOL (as measured by the Physical Component Summary (PCS) and the Mental Component Summary (MCS)) and life satisfaction than did controls (P 0.001). Additionally, people with fractures and pain had significantly lower scores on the PCS than did those who were fractured but had no pain and than controls (P 0.001). Unfortunately, gender specific analyses were not reported. The combination of a fracture and pain appeared to have the most profound negative outcomes in both men and women.
Mortality in men after osteoporotic fracture Excess mortality in older women from both hip and vertebral fractures has been well established [43, 44]. However, this adverse outcome of osteoporosis in men has been less well investigated, perhaps because there are no parallels with men to the large databases such as the Study of
Osteoporotic Fractures (SOF) or the Fracture Intervention Trial (FIT).
Mortality After Hip Fracture Mortality varies by fracture type, with hip fractures being the most likely to lead to death. Ioannidis and colleagues [45] studied 5-year mortality by fracture type in CaMos, a population-based Canadian cohort including both men and women. The highest death rates were seen after hip, pelvic and vertebral fractures in both men and women. Death rates following hip fracture were similar between men and women; however, men showed slightly greater long-term mortality with vertebral fractures and pelvic fractures. This was not seen with forearm fractures. Table 32.1 reflects the findings of this study. Excess deaths following hip fracture occur mainly in the first 6 months and diminish with time, although mortality may remain elevated for up to 10 years [46]. Bliuc and colleagues found an age adjusted standardized mortality ratio of 3.51 (95% CI 2.65–4.66) in men [46]. Hip fracture mortality depends on age and sex with greater survival for those under 75 years with a relative survival of 92% and a survival of only 83% for those over 75 years [47]. In virtually every study, hip fracture survival is more likely in women than in men. Poor and colleagues studied 131 men who experienced a hip fracture between 1978 and 1989 and an equal number of community-dwelling controls [48]. Of patients with fractures, 109 died during 373 personyears of follow-up observation. Only 75 of the controls died during the 742 person-years of observation. Increased comorbidity and increased age increased the risk of dying; so did mental confusion during hospitalization. It may be that the greater frequency of chronic diseases in men with hip fractures makes them more likely to die. Van Staa and colleagues used the General Practice Research Database in the UK to derive age- and genderspecific fractures rates in England and Wales between 1988 and 1998 [49]. Out of 5 million adults, about 119 317 women and 103 052 men were studied over follow up of
Table 32.1 Absolute post-fracture death rates (%) among Canadian men and women by fracture type
No fracture Hip fracture Vertebral fracture Rib Forearm Pelvis Other fracture
Men
Women
11.0 23.5 18.2 6.7 11.5 33.3 12.7
6.9 23.5 15.75 9.8 8.1 15.0 5.8
From Ioannidis G, Papaioannou A, Hopman WM et al. Absolute death rates by fracture type in Canadians. Arthritis Rheum 2008;58:S747 [45]
C h a p t e r 3 2 Adverse Health Outcomes in Men with Osteoporosis l
11.2 million and 10.4 million person-years. Both men and women age 65 had statistically significant (P 0.05) excess mortality from hip and vertebral fractures. They also found that the 12-month survival after hip fractures is lower in men than in women: 63% versus 90% expected as compared to women [49]. Finally, in California, approximately 6% of men with hip fracture die within the first 30 days and 10% within the first 60 days post fracture [21].
Mortality After Clinical Vertebral Fractures There are gender differences in excess mortality from clinical vertebral fractures. Bliuc and colleagues found a Standardized Mortality Ratio (SMR) of 2.12 (95% CI 1.66– 2.72) in men as opposed to an SMR of 1.82 in women [46]. In the Malmo University Hospital in Sweden, investigators followed 70 men (mean age 70 years; range 50–91 years) and 187 women (mean age 72 years; range 50–96 years), all of whom had experienced a clinical vertebral fracture [14]. A mortality analysis was done over 22 years after the baseline fracture. Investigators found that the excess mortality rate was higher in men with clinical vertebral fractures than in women with the same fractures. The male mortality rate was 111.7 per 1000 patient years (versus a rate of 73.4 per 1000 patient years in control men); in women, the mortality rate was 95.1 per 1000 patient years (versus control women’s rate of 62 per 1000 patient years) [14].
Mortality After Prevalent Vertebral Fracture Prevalent vertebral fractures are associated with well-documented loss of height, kyphosis and increased mortality risk [50, 51]. When male participants in EVOS from Malmo, Sweden were studied, there was an association between prevalent vertebral fracture as defined by a reduction in vertebral height of 3SD and increased mortality risk with an age adjusted HR of 2.4 (95% CI 1.6–3.9) as compared to female participants HR 2.3 (95% CI 1.3–4.3). However, reasons for mortality differ between genders as men have greater risk of mortality due to cardiovascular and pulmonary causes while, in women, there is greater risk of cancer mortality [52]. Finally, vertebral deformity due to prevalent vertebral fracture may result in hyperkyphosis, which is a cause of increased mortality. Hyperkyphosis is associated with a 40% increase in mortality in older men and women [53].
Mortality After Subsequent Fracture Bliuc et al found that, in men, mortality after a second fracture was greater (SMR 3.53, 95% CI, 2.62–4.74) than in those with only one fracture (SMR 1.82, 95% CI 1.51– 2.18). Mortality following a second fracture declined with time but, beyond 5 years, was still higher than in the general population (SMR 1.78, 95% CI 0.96–3.31) [46].
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Conclusions Both men and women have adverse outcomes following osteoporotic fracture. Whereas men and women have loss of HRQOL with osteoporotic fracture, gender differences exist in terms of HRQOL domains affected by lower BMD and by fracture [39]. Furthermore, there are gender differences in terms of long-term morbidity and mortality [14, 28]. Morbidity post fracture is complicated by the morbidity of subsequent fractures. In men older than 50 years, clinical vertebral and non-vertebral fractures cluster in time. Yearly absolute risk of another fracture after a clinical vertebral or non-vertebral fracture is 6.1% during the first year, 2.1% yearly for the next three years and 1.6% in fifth year [54]. There are also gender differences in mortality following osteoporotic hip fracture. Men may have greater earlier mortality following hip fracture, possibly due to comorbidities. This earlier mortality following hip fracture is coupled with findings of significant loss of quality of life. Excess mortality and morbidity is of particular relevance as we now appreciate that men, like women, experience an exponential increase in the rate of hip fracture [54]. Osteoporotic fractures in men are also associated with a disease burden that is higher (in terms of disability and mortality) than common cancers (excluding lung cancer) [55]. The cost burden of men hospitalized with osteoporotic fracture is higher than the cost burden of men hospitalized with prostate cancer [56]. Despite the absence of substantial empirical data on all outcomes from osteoporotic fractures in men, the data reviewed here strongly suggest that, in men, osteoporotic fractures and their adverse outcomes have become a major public health problem that will continue to increase in size and cost as our population ages. They also remind us of the importance of osteoporosis screening in men over age 70 and men over 50 with risk factors, as currently recommended in the National Osteoporosis Foundation Clinicians’ Guide [57]. Finally, as noted by the investigators of CaMos, in men, there is a substantial gap between what we do and what we could do to detect, prevent and treat this disease [58].
References 1. US Department of Health and Human Services, Bone Health and Osteoporosis. A Report of the Surgeon General, US Department of Health and Human Services, Rockville, 2004. 2. S. Khosla, S. Amin, E. Orwoll, Osteoporosis in men, Endocr. Rev. 29 (2008) 441–464. 3. R. Burge, B. Dawson-Hughes, D.H. Solomon, J.B. Wong, A. King, A. Tosteson, Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025, J. Bone Miner Res. 22 (2007) 465–475. 4. T.V. Nguyen, J.R. Center, P.N. Sambrook, J.A. Eisman, Risk factors for proximal humerus, forearm, and wrist fractures in elderly men and women: the Dubbo Osteoporosis Epidemiology Study, Am. J. Epidemiol. 153 (2001) 587–595.
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5. A.T. Marshall, A.J. Crisp, Reflex sympathetic dystrophy, Rheumatology 39 (2000) 692–695. 6. G.A. Greendale, E. Barrett-Connor, S. Ingles, R. Haile, Late physical and functional effects of osteoporotic fracture in women: the Rancho Bernardo Study, J. Am. Geriatr. Soc. 43 (1995) 955–961. 7. C. Mathis, U. Weber, T.W. O’Neill, H. Raspe, Health impact associated with vertebral deformities: results from the European Vertebral Osteoporosis Study (EVOS), Osteoporos. Int. 8 (1998) 364–372. 8. W. Cockerill, A.A. Ismail, C. Cooper, et al., Does location of vertebral deformity within the spine influence back pain and disability? European Vertebral Osteoporosis Study (EVOS) Group, Ann. Rheum. Dis. 59 (2000) 368–371. 9. A.A. Ismail, C. Cooper, D. Felsenberg, et al., Number and type of vertebral deformities: epidemiological characteristics and relation to back pain and height loss. European Vertebral Osteoporosis Study Group, Osteoporos. Int. 9 (1999) 206–213. 10. J.K. Tracy, W.A. Meyer, M. Grigoryan, et al., Racial differences in the prevalence of vertebral fractures in older men: the Baltimore Men’s Osteoporosis Study, Osteoporos. Int. 17 (2006) 99–104. 11. J.K. Tracy, W.A. Meyer, R.H. Flores, P.D. Wilson, M.C. Hochberg, Racial differences in rate of decline in bone mass in older men: the Baltimore Men’s Osteoporosis study, J. Bone Miner Res. 20 (2005) 1228–1234. 12. G. Leidig, H.W. Minne, P. Sauer, et al., A study of complaints and their relation to vertebral destruction in patients with osteoporosis, Bone Miner 8 (1990) 217–229. 13. A. Papaioannou, C.C. Kennedy, G. Ioannidis, et al; for the CaMos Study Group. The impact of incident fractures on health related quality of life; five years of data from CaMos. Osteoporos Int 2008; DOI 10.1007/s00198-008-0743-7. Accessed 12.10.08. 14. R. Hasserius, M.K. Karlsson, B. Jonsson, I. Redlund-Johnell, O. Johnell, Long-term morbidity and mortality after a clinically diagnosed vertebral fracture in the elderly – a 12- and 22-year follow-up of 257 patients, Calcif. Tissue Int. 76 (2005) 235–242. 15. A. Mithal, S. Vadhavkar, A. Mannalithara, G. Singh, G. Triadafilopoulos, An unrecognized hazard: exponential increase in prevalence rates of osteoporotic fractures in aging men parallels that of aging women, Arthritis Rheum. 58 (2008) S742. 16. S. Katz, K.G. Heiple, T.D. Downs, A.B. Ford, C.P. Scott, Long term course of 147 patients with fracture of the hip, Surg. Gynecol. Obstet. 124 (1967) 1219–1230. 17. J. Magaziner, E.M. Simonsick, T.M. Kashner, J.R. Hebel, J.E. Kenzora, Predictors of functional recovery one year following hospital discharge for hip fracture: a prospective study, J. Gerontol. 45 (1990) M101–M107. 18. A.M. Jette, B.A. Harris, P.D. Cleary, E.W. Campion, Functional recovery after hip fracture, Arch. Phys. Med. Rehabil. 68 (1987) 735–740. 19. S.R. Cummings, S.L. Phillips, M.E. Wheat, et al., Recovery of function after hip fracture. The role of social supports, J. Am. Geriatr. Soc. 36 (1988) 801–806. 20. R.A. Marotolli, L.F. Berkman, L.M. Cooney, Decline in physical function with hip fracture, J. Am. Geriatr. Soc. 40 (1992) 861–866.
21. S.L. Silverman, D. Zingmond, Increased mortality following acute hip fractures: secular trends in California. 1990–2001, J. Bone Miner Res. 19 (2004) S49. 22. R.G. Morris, R.T. Woods, K.S. Davies, L.W. Morris, Gender differences in carers of dementia sufferers, Br. J. Psychiatr. Suppl. 10 (1991) 69–74. 23. D.T. Gold, S.D. Smith, C.W. Bales, K.W. Lyles, R.E. Westlund, M.K. Drezner, Osteoporosis in late life: does health locus of control affect psychosocial adaptation?, J. Am. Geriatr. Soc. 39 (1991) 670–675. 24. D.T. Gold, Osteoporosis and quality of life psychosocial outcomes and interventions for individual patients, Clin. Geriatr. Med. 19 (2003) 271–280. 25. K.A. Roberto, J. Bartmann, Factors related to older women’s recovery from hip fractures: physical ability, locus of control, and social support, Health Care Women Int. 14 (1993) 457–468. 26. S. Solimeo, T.J. Weber, D.T. Gold, A women’s disease? Report on men’s experiences of osteoporosis, Gerontologist 47 (2007) 606. 27. G. Greendale, E. Barrett-Connor, Outcomes of osteoporotic fracture, in: R. Marcus, D. Feldman, J. Kelsey (Eds.) Osteoporosis, Academic Press, San Diego, 2001, pp. 819–829. 28. J.D. Adachi, G. Loannidis, C. Berger, et al., Canadian Multicentre Osteoporosis Study (CaMos) Research Group. The influence of osteoporotic fractures on health-related quality of life in community-dwelling men and women across Canada, Osteoporos. Int. 12 (2001) 903–908. 29. U. Schweiger, M. Deuschle, A. Körner, et al., Low lumbar bone mineral density in patients with major depression, Am. J. Psychiatr. 151 (1994) 1691–1693. 30. U. Halbreich, N. Rojansky, S. Palter, et al., Decreased bone mineral density in medicated psychiatric patients, Psychosom. Med. 57 (1995) 485–491. 31. J. Robbins, C. Hirsch, R. Whitmer, J. Cauley, T. Harris, The association of bone mineral density and depression in an older population, J. Am. Geriatr. Soc. 49 (2001) 732–736. 32. M.A. Whooley, J.A. Cauley, J.M. Zmuda, E.M. Haney, N.W. Glynn, Depressive symptoms and bone mineral density in older men, J. Geriatr. Psychiatr. Neurol. 17 (2004) 88–92. 33. M.E. Mussolino, Depression and hip fracture risk: the NHANES I epidemiologic follow-up study, Public Health Rep. 120 (2005) 71–75. 34. E.J. Lenze, M.C. Munin, M.A. Dew, et al., Adverse effects of depression and cognitive impairment on rehabilitation participation and recovery from hip fracture, Int J Geriatr Psychiatr 19 (2004) 472–478. 35. E.J. Lenze, M.C. Munin, E.R. Skidmore, et al., Onset of depression in elderly persons after hip fracture: implications for prevention and early intervention of late-life depression, J. Am. Geriatr. Soc. 55 (2007) 81–86. 36. A. Burns, S. Banerjee, J. Morris, et al., Treatment and prevention of depression after surgery for hip fracture in older people: randomized, controlled trials, J. Am. Geriatr. Soc. 55 (2007) 75–80. 37. E.M. Dennison, H.E. Syddall, C. Statham, A. Aihie Sayer, C. Cooper, Relationships between SF-36 health profile and bone mineral density: the Hertfordshire Cohort Study, Osteoporos. Int. 17 (2006) 1435–1442. 38. J.E. Ware Jr, C.D. Sherbourne, The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection, Med. Care 30 (1992) 473–483.
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39. I. Pande, D.L. Scott, T.W. O’Neill, C. Pritchard, A.D. Woolf, M.J. Davis, Quality of life, morbidity, and mortality after low trauma hip fracture in men, Ann. Rheum. Dis. 65 (2006) 87–92. 40. H. Ekstrom, S.D. Ivanoff, S. Elmstahl, Restriction in social participation and lower life satisfaction among fractured in pain: results from the population study ‘Good Aging in Skane’, Arch Gerontol Geriatr. 46 (2008) 409–424. 41. J. Ware Jr, M. Kosinski, S.D. Keller, A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity, Med. Care 34 (1996) 220–233. 42. B.L. Neugarten, R.J. Havinghurst, R.S. Weiner, The measurement of life satisfaction, J. Gerontol. 16 (1961) 134–143. 43. K.E. Ensrud, S.K. Ewing, B.C. Taylor for the Study of Osteoporotic Fractures Research Group, et al., Frailty and risk of falls, fracture, and mortality in older women: the study of osteoporotic fractures., J. Gerontol. A Biol. Sci. Med. Sci. 62 (2007) 744–751. 44. K.E. Ensrud, D.E. Thompson, J.A. Cauley, et al., Prevalent vertebral deformities predict mortality and hospitalization in older women with low bone mass. Fracture Intervention Trial Research Group, J. Am. Geriatr. Soc. 48 (2000) 241–249. 45. G. Ioannidis, A. Papaioannou, W.M. Hopman, et al., Absolute death rates by fracture type in Canadians, Arthritis Rheum. 58 (2008) S747. 46. D. Bliuc, D.N. Nguyen, V.E. Milch, T.V. Nguyen, J.A. Eisman, J.R. Center, Mortality risk associated with low trauma osteoporotic fracture and subsequent fracture in men and women, J. Am. Med. Assoc. 301 (2009) 513–521. 47. L.J. Melton III, Epidemiology of fractures, in: BL. Riggs, L.J Melton III (Eds.) Osteoporosis: etiology, Diagnosis and Management, Raven Press, New York, 1988, pp. 133–154. 48. G. Poor, E.J. Atkinson, W.M. O’Fallon, L.J. Melton III, Determinants of reduced survival following hip fracture in men, Clin. Orthop. 319 (1995) 260–265. 49. T.P. Van Staa, E.M. Dennison, H.G. Leufkens, C. Cooper, Epidemiology of fractures in England and Wales, Bone 29 (2001) 517–522.
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50. A.C. Scane, R.M. Francis, A.M. Sutcliffe, M.J. Francis, D.J. Rawlings, C.L. Chapple, Case-control study of the pathogenesis and sequelae of symptomatic vertebral fractures in men, Osteoporos. Int. 9 (1999) 91–97. 51. A.A. Ismail, T.W. O’Neill, C. Cooper on behalf of the EPOS study group, et al., Mortality associated with vertebral deformity in men and women: results from the European Prospective Osteoporosis study (EPOS), Osteoporos. Int. 8 (1998) 291–297. 52. R. Hasserius, M.K. Karlsson, B.E. Nilsson, I. Redlund-Johnell, O. Johnell, European Vertebral Osteoporosis Study. Prevalent vertebral deformities predict increased mortality and increased fracture rate in both men and women: a 10-year populationbased study of 598 individuals from the Swedish cohort in the European Vertebral Osteoporosis Study, Osteoporos. Int. 14 (2003) 61–68. 53. D.M. Kado, M.H. Huang, A.S. Karlamangla, E. Barrett-Connor, GA. Greendale, Hyperkyphotic posture predicts mortality in older community-dwelling men and women: a prospective study, J. Am. Geriatr. Soc. 52 (2004) 1662–1667. 54. K. Huntjens, T. van Geel, S. van Helden, P. Geusens, In men older than 50 years clinical vertebral and nonvertebral fractures cluster in time, Arthritis Rheum. 58 (2008) S941. 55. O. Johnell, J.A. Kanis, An estimate of the worldwide prevalence and disability associated with osteoporotic fractures, Osteoporos. Int. 17 (2006) 1726–1733. 56. O. Johnell, J.A. Kanis, B. Jonsson, A. Oden, H. Johansson, C. De Laet, The burden of hospitalised fractures in Sweden, Osteoporos. Int. 16 (2005) 222–228. 57. National Osteoporosis Foundation, The clinician’s guide to prevention and treatment of osteoporosis, National Osteoporosis Foundation, Washington, DC, 2008. 58. A. Papaioannou, C.C. Kennedy, G. Ioannidis, et al., CaMos Research Group (CaMos). The osteoporosis care gap in men with fragility fractures: the Canadian Multicentre Osteoporosis Study, Osteoporos. Int. 19 (2008) 581–587.
Chapter
33
Idiopathic Osteoporosis Jean-Marc Kaufman, Bruno Lapauw, Youri Taes and Stefan Goemaere Ghent University Hospital, Department of Endocrinology and Unit for Osteoporosis and Metabolic Bone Diseases, Gent, Belgium
Introduction
not distinguishable from senile osteoporosis? What about the diagnosis of idiopathic osteoporosis in men with low bone mass in the absence of prevalent fracture? In view of the lack of a generally accepted densitometry-based opera tional definition of osteoporosis in men, should the latter men without a history of fracture be labeled as having ‘idi opathic low bone mass’ rather than ‘idiopathic osteoporo sis’? Obviously, these areas of uncertainty, to name but a few, demand a pragmatic approach to the diagnosis of idiopathic osteoporosis of men. The epidemiology of idiopathic osteoporosis in men is presently largely unknown and, in any case, figures for prevalence and incidence would be expected to vary sub stantially, depending on the applied diagnostic criteria. In several series of osteoporosis in men, more than half of the subjects were found to have secondary osteoporosis. It is commonly stated that the cause of osteoporosis in men is more often secondary compared to osteoporosis in women. However, this has not been properly established. Indeed, reports on presentation and differential diagnosis of oste oporosis in men are mostly based on series collected in clinical practices and thus biased by the type of clinical practice (e.g. over-representation of rheumatoid arthritis and glucocorticoid-induced osteoporosis in a rheumatologybased practice). Furthermore, the relative prevalence of primary osteoporosis in men compared to women is likely to be underestimated in view of the much lower rate of screening and active case-finding in men, especially outside the context of major clinical fractures or presence of very well established and manifest secondary causes of oste oporosis [1–4].
Osteoporosis in men, with its clinical expression of bone fragility, may be either ‘secondary’ or ‘primary’. In sec ondary osteoporosis, the generalized quantitative and qualitative skeletal defects are an epiphenomenon and the consequence of an identifiable disease or its treatment (e.g. osteoporosis resulting from hypogonadism, gastrointesti nal malabsorption, primary hyperparathyroidism or gluco corticoid treatment) whereas, in primary osteoporosis, they are characteristics or changes inherent in the affected indi vidual. Presentations of osteoporosis considered as primary include osteoporosis linked to a specific monogenic disease (e.g. osteoporosis pseudoglioma syndrome), senile oste oporosis resulting from skeletal deterioration in aging and idiopathic osteoporosis in younger men [1–3]. It is this lat ter presentation of primary osteoporosis that is discussed in this chapter. Idiopathic osteoporosis is a diagnosis by exclusion, which implies that all established causes of osteoporosis are absent and thus also implies ignorance of the true under lying cause. In this context, one cannot assume a unique pathophysiological mechanism and idiopathic osteoporosis is undoubtedly a heterogeneous syndrome. Diagnostic cri teria are largely arbitrary and they are not carried by some general consensus or broadly endorsed guideline. Moreover, there inevitably are gray zones of overlap with other forms of osteoporosis. Potential areas of controversy are numerous. How exten sive a clinical and technical work-up to exclude secondary causes should one perform before labeling osteoporosis in a man as ‘idiopathic’? When should a risk factor identi fied in the patient’s history (e.g. high alcohol consumption, low calcium intake or high urinary calcium) no longer be regarded as a potentially contributing risk factor but rather as a secondary cause of osteoporosis in its own right? From what age in older subjects should the diagnosis of idiopathic osteoporosis no longer be made, because it is Osteoporosis in Men
Diagnosis As indicated in the introduction, idiopathic osteoporo sis is a diagnosis by exclusion and there is no generally 405
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endorsed consensus on diagnostic criteria. Main issues to be considered include bone mineral density (BMD) criteria, age, fracture prevalence and the exclusion of secondary causes.
How to Define Osteoporosis Bone mineral density criteria for osteoporosis in men are a matter of debate and there is no consensus BMD-based operational definition of osteoporosis in men [4–6]. This issue is addressed in other chapters. Briefly, when apply ing the 2.5 T-score cut-off limit for (areal) BMD by dual energy x-ray absorptiometry (DXA), similar to the com monly applied diagnostic threshold in postmenopausal women, with the T-score derived from a gender-specific ref erence population, this identifies men with a lower fracture risk than their female counterparts [6]. In epidemiological studies, fracture risk was found to be rather similar between men and women for a same absolute BMD value, which suggests that calculation of the T-score for men based on a female reference range will identify male subjects with a similar fracture risk as their female counterparts [7–9]. However, the latter findings from epidemiological studies have not been confirmed in all studies and, moreover, these observations pertain to an older age group than the men presenting with idiopathic osteoporosis [2, 6]. Finally, the use of the BMD Z-score, whereas less explicitly referring to a level of fracture risk, allows for straightforward identification of men with low bone mass relative to the expected BMD values in healthy men. The limitations of DXA, a projection technique, are well known. In this regard, techniques such as quantitative com puted tomography (QCT), which provide information on volumetric BMD, bone size and geometry, are particularly relevant to the study of the pathophysiology of idiopathic osteoporosis [2], but problems of standardization and lim ited access to dedicated software and/or hardware make them less suited for routine clinical diagnosis. A prevalent ‘major osteoporotic fracture’ is a strong independent indicator of bone fragility [10] and thus, besides and on top of a low bone mass, a valuable element for the diagnosis of osteoporosis and the identification of men at high risk of fracture. Further, whether the patient does or does not have a prevalent fracture is an element that one might have to consider when differentiating among phenotypes of idiopathic osteoporosis. Putting the focus on the clinically relevant consequences of osteoporosis, the present trend in clinical practice is to shift emphasis from ‘diagnosis of osteoporosis’ to ‘fracture risk evaluation’. In proposed algorithms, such as FRAX, also applicable to men, estimations of the 10-year abso lute fracture risk are based on combinations of clinical risk factors with or without BMD and prevalent fracture [11]. Such algorithms might be the preferable clinical approach to identify men at high fracture risk most likely to benefit
from treatment. However, they are obviously not suited to define idiopathic osteoporosis as a clinical syndrome when trying to understand its pathophysiology.
Age Developmental anomalies with deficient acquisition of peak bone mass might be a major pathophysiological mechanism in many men with idiopathic osteoporosis. Nevertheless, the diagnosis of idiopathic osteoporosis as discussed here refers to a clinical syndrome in adult men with a mature skeleton. How to justify a proposed arbitrary upper age limit for the diagnosis of idiopathic osteoporosis is an issue of potential debate related to the difficulty of distinguishing between idiopathic and senile osteoporosis in older sub jects. In men, age-specific incidence of most types of major fractures increases exponentially in the elderly, reflect ing the age-related increase of bone fragility besides an increased incidence of falls. As to date, no unique alteration of bone metabolism characteristic of senile osteoporosis has been described. Moreover, possible features of senile osteoporosis, such as tendency towards decreased bone formation and increased bone resorption, might also be encountered in idiopathic osteoporosis. Many men with idi opathic osteoporosis might present a fracture only at a later age as the consequence of (senile) bone loss superimposed on an initially low peak bone mass. In view of the inability to distinguish between older men with senile osteoporosis and men with idiopathic osteoporo sis who grew older, the diagnosis of idiopathic osteoporosis is commonly limited to men younger than 65 or 70 years [1–4], which roughly corresponds to the age when the inci dence of fractures in the male population tends to increase more steeply [7, 12–14].
Fragility Fractures The importance of a prevalent fragility fracture as a diag nostic element has been discussed earlier. In general, it is often difficult to decide whether a fracture in a patient’s history is a ‘fragility’ fracture, or rather a ‘traumatic’ frac ture [11]. For postmenopausal and senile osteoporosis, it is common practice to consider only fractures after age 50 years, but the diagnosis of idiopathic osteoporosis is often made at a younger age. On the other hand, the epidemiol ogy of fractures in men, with higher fracture incidence in males than in females from adolescence up to age 50 years, is highly suggestive for substantial contribution of trau matic fractures. This might in turn be explained by higher risk in the context of sports, on the workplace and linked to risk-taking behavior. In particular, fractures of the limbs, hands and feet are often related to trauma. Similarly, verte bral deformities as diagnosed on x-ray are more prevalent in men up to age 65 years [2, 12–14].
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The often made distinction between traumatic fractures and those resulting from so-called low-energy trauma, has the limitation to be a subjective one except for the more obvious cases [11]. Moreover, even fractures at younger age, although possibly not in childhood [15], and fractures associated with moderately severe trauma might be associ ated with some degree of bone fragility and increased risk of subsequent fracture, but there are few data available. Pragmatically, one can propose to consider as poten tially relevant to the diagnosis of idiopathic osteoporo sis in men any major fracture occurring in adult men that cannot be linked to a moderately severe to severe trauma. Noteworthy, distal forearm fractures in men, with an inci dence that is considerably lower than in women and shows atypically little variation during adult life, appear to be a sensitive marker of skeletal fragility in white men and pre dict a higher risk for both vertebral and hip fracture [16].
Exclusion of Secondary Causes Secondary causes of osteoporosis in men are numerous [1–4] and summarized in Table 33.1, but discussion in depth of secondary osteoporosis falls beyond the scope of this chapter. A reasonable strategy for excluding second ary causes can consist in the combination of a relatively straightforward standard set of (mostly clinical biochemis try and hormonal) screening investigations, complemented as needed by additional, more focused tests based on indi cations obtained from a careful history taking and clinical examination, or from the results of the initial biochemical screening. A thorough clinical assessment is needed for differen tial diagnosis between osteoporosis and other diseases and to detect possible underlying disease as cause of secondary osteoporosis. The medical history should address the family and fracture history, past diseases and present symptoms with special attention for common and less frequent sec ondary causes of osteoporosis, for differential diagnos tic pitfalls (e.g. osteomalacia and multiple myeloma), use of medication, lifestyle-related factors including calcium intake, exercise, use of alcohol and tobacco. In the clinical examination, attention should be paid to the anthropomet rics (body height and proportions, body mass index (BMI)), to possible signs of inherited syndromes, to signs sugges tive for causes of secondary osteoporosis, to possible con sequences of osteoporosis (e.g. thoracal spine kyphosis). The basic set of tests applied to ‘screen’ for secondary osteoporosis tends to vary according to clinician’s own biases and the characteristics of their medical practice, but the general principles are to include the tests needed to reveal major health problems (i.e. routine clinical chemis try), tests that will allow exclusion of relatively common specific causes of osteoporosis (e.g. serum calcium, testo sterone and thyroid stimulating hormone (TSH)) and tests that can be used as a common marker for a broader range
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Table 33.1 Some secondary causes of osteoporosis in men: the diagnosis of idiopathic osteoporosis is a diagnosis by exclusion Immobilization Alcoholism Endocrine disorders Hypogonadism Cushing’s syndrome Hyperparathyroidism Hyperthyroidism Diabetes mellitus (type 1) Gastrointestinal diseases Post-gastrectomy Coeliac disease Post-bariatric surgery Malabsorption syndromes (others) Inflammatory bowel disease Primary biliary cirrhosis Chronic obstructive pulmonary disease Post-transplantation Rheumatoid arthritis Hyperhomocysteinemia Neoplastic diseases Systemic mastocytosis Cystic fibrosis Homocystinuria Hypercalciuria Hemochromatosis Renal insufficiency Medication-related Glucocorticoids Anticonvulsants Chemotherapy Glitazones GnRH-analogues Anti-androgens
of possible secondary causes (e.g. low serum 25-hydroxyvitamin D and/or elevated parathyroid hormone (PTH) indi cating possible gastrointestinal malabsorption). However, no study is available that allows a proposal for a validated guideline for cost-effective investigation for secondary osteoporosis in men. In accordance with the foregoing general principles, it can be proposed that initial laboratory evaluation should include a complete blood count, a marker for inflammatory diseases (e.g. C-reactive protein), blood glucose, serum protein electrophoresis, serum ferritin and renal and liver function tests. Tests of the calciotropic axis should include serum calcium (corrected for serum albumin), phosphate, (total or bone specific) alkaline phosphatase, 25-hydroxy vitamin D and PTH. Assessment of 24 h urinary calcium excretion can reveal hypercalciuria (300 mg/24 h) or rather low calcium excretion (100 mg/24 h) as indication for low calcium intake or absorption (if no use of calcium sparing
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diuretics). Additional tests should include serum total testosterone (before 10 a.m.; if borderline, to be repeated on a separate occasion together with sex hormone binding globulin (SHBG) to calculate free/bioavailable testoster one), serum thyrotropin, serum cortisol (additional testing such as 24 h urinary free cortisol or evening salivary cor tisol if high serum value or clinical suspicion of Cushing’s syndrome). Biochemical markers of bone turnover (morn ing fasting blood sample and/or second void morning urine sample) may help differentiate between a low and a high bone turnover state, if assayed under sufficiently standard ized conditions. In many instances, spine x-ray is a needed complement to clinical evaluation, for objective documen tation of a history of clinical vertebral fracture, for differ ential diagnosis of back pain, which often is the reason for consultation, and for detection of ‘silent’ vertebral deformi ties or for confirmation and differentiation of vertebral deformities detected by DXA-based vertebral morphometry assessment. It is important to differentiate vertebral frac tures from other deformities not related to osteoporosis such as in vertebral epiphysitis (Sheuermann’s disease). Chest x-ray and abdominal ultrasound examination may be useful additional investigations in selected cases. A bone biopsy is very rarely indicated in men with severe osteoporosis and no evident cause, e.g. for exclusion of suspected systemic mastocytosis or associated osteoma lacia [1–4].
Conclusions In conclusion, idiopathic osteoporosis is a syndrome diag nosed by exclusion in adult men no older than 65 to 70 years with established low bone mass according to one of the several proposed DXA-based BMD criteria, when a reasonably comprehensive set of investigations has not revealed a secondary cause of osteoporosis. A prevalent fragility fracture is an important indicator of bone fra gility, which considerably strengthen the diagnosis of (severe) osteoporosis and helps to identify those men likely to benefit the most from treatment, but it is not generally considered a necessary condition for diagnosis.
Clinical presentation and phenotype Most commonly, the initial presentation of men with idi opathic osteoporosis may be with complaints of back pain, with a clinical fracture or on the occasion of the fortuitous finding of a vertebral fracture or diffuse osteopenia on x-ray examination performed for unrelated health problems. In reported clinical studies on idiopathic osteoporosis, all or only part of included men have a vertebral fracture, depend ing whether a prevalent vertebral fracture was an inclusion
criterion. In how far presence versus absence of a vertebral fracture contributes importantly to phenotype heterogeneity is an issue in need of further clarification.
Clinical Findings Men with idiopathic osteoporosis may be asymptomatic or present signs and symptoms of a clinical fracture. There are no clinical findings specific to men with idiopathic oste oporosis. Nevertheless, observational studies in men with idiopathic osteoporosis suggest that these men tend to have a somewhat smaller than average body size. In particular, a lower mean body weight appears to be a consistent find ing in these subjects, whether or not they have a prevalent vertebral fracture, and this appears to involve both a lower fat and lean mass [17–23]. A trend towards slightly shorter stature is reported in some [18–20,22], but not all stud ies [17, 23]. We have observed that the tendency towards slightly shorter stature results from a shorter trunk height, also in the absence of vertebral fracture, with normal length of the limbs and thus normal pubis-ground height compared to age-matched healthy controls (unpublished data).
Skeletal Phenotype In men with idiopathic osteoporosis, areal BMD, as meas ured by DXA, is usually markedly low, below the expected distribution for age, i.e. with a Z-score usually well below 2 (often a T-score below 3 using a male reference range). Although the patients have generalized low bone mass, the deficit tends to be more prominent at the axial skeleton [17, 18, 22]. The lower areal BMD results from both lower volumetric BMD and smaller bone size as indi cated by data derived from DXA at the lumbar spine and femoral neck [18, 22]. Data obtained by peripheral QCT revealed a decreased volumetric BMD for both trabecular and cortical bone at the radius and tibia and, furthermore, a decreased cortical thickness due to increased endosteal cir cumference with larger bone marrow cavity with unchanged periosteal circumference [24]. Bone histomorphometry per formed on transiliacal biopsies indicated reduced trabecu lar bone volume [25–27], trabecular thickness [25], mean wall thickness [25, 28] and cortical thickness [26, 27] with unchanged porosity [26]. Osteoid and osteoblast surfaces were reported to be reduced [26, 27], with no consistent findings on osteoid width [25, 26]. Activation frequency, erosion surfaces and mineral apposition rate were found to be unchanged [25–27], the formation rate unchanged [25] or decreased [27] and the mean resorption depth unchanged [25] or slightly increased [28]. Taken together these find ings show reduced cancellous and cortical bone volumes with indications for remodeling imbalance resulting pri marily from relatively low bone formation, without indi cation for increased bone turnover. Interestingly, Ostertag et al [29], in a cross-sectional study, reported differences
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in histomorphometric findings among men with idiopathic osteoporosis depending on whether they presented with out or with prevalent vertebral fractures. The latter men had lower trabecular bone volumes with lower trabecular connectivity and similar cortical width but greater cortical porosity compared to the men without vertebral fracture. The greater porosity resulted from higher mean area rather than density of the Haversian canals, thus suggesting greater remodeling imbalance due to greater bone resorption rather than increased turnover compared to the men without frac ture [30]. These findings suggest the existence of differ ences in phenotype between men with idiopathic low bone mass compared to men with severe osteoporosis and preva lent vertebral fracture. The question whether this represents a fundamental difference between the presentation of idi opathic osteoporosis with and without prevalent fracture or rather a different stage and severity of the disease with pos sibly additional pathophysiological mechanisms contribut ing to the fracture risk deserves further study. Moreover, taken the cross-sectional design of this study, it is not possible definitely to exclude that some of the observed differences might be a consequence of the fractures.
Physiopathology and genetics Maturational Defect or Accelerated Bone Loss? There is a convergence of clinical evidence, summarized in Table 33.2, that indicates that idiopathic low bone mass in men with or without prevalent fracture is most commonly the result of a maturational defect with deficient acquisition of bone mass, rather than being the consequence of prema ture bone loss. First, there is ample evidence that idiopathic osteoporosis in men is a ‘low bone turnover’ osteoporosis, in sharp con trast to the increased bone turnover that invariably underlies
Table 33.2 Indirect evidence for a maturational defect with deficient acquisition of bone mass as a major pathophysiological mechanism in idiopathic osteoporosis in men No indication of increased bone turnover on histomorphometry Biochemical markers do not show increased bone turnover Magnitude of bone mass deficit compared to age-matched controls is independent of age Follow up of affected men does usually not reveal rapid bone loss Besides low (volumetric) BMD subjects also have smaller bones Affected men also tend to have a smaller body size A bone mass deficit is also observed in first-degree relatives Similar phenotype with low bone mass and body weight, without increased bone turnover in up to 50% of young adult sons
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other forms of osteoporosis characterized by accelerated bone loss. Indeed, findings for histomorphometry [25–27] appear to indicate that a majority of men with idiopathic osteoporosis, including a substantial proportion of men with low bone mass and prevalent vertebral fracture, do not present with increased bone turnover [25–28]. This is corroborated by the findings for biochemical markers of bone turnover which, in most studies, were not significantly increased compared to healthy controls [18, 23, 27, 30]. An isolated increase of urinary markers of bone collagen degradation expressed in function of creatinine excretion, without changes in serum bone formation markers, in some studies [20, 31] appears to reflect low creatinine excre tion, in line with the lower lean body mass in men with idi opathic osteoporosis, rather than increased bone resorption [20]. Pietschmann et al [32] reported increased values for markers of bone resorption, without increased values for markers of bone formation, but the study was rather mod estly sized and included also older patients. Moreover, the bone mass deficit in the patients compared to age-matched controls appears largely independent of age [18, 22] and, finally, in longitudinal follow up of untreated men with idiopathic osteoporosis, we did not observe accelerated bone loss (unpublished results). Secondly, there is strong evidence pointing towards a familial, likely genetically determined, maturational defect. Indeed, there is a strong familial component with decreased BMD in first-degree relatives [17, 18, 22]. In a family study of male probands with idiopathic osteoporosis, as many as 50% of young adult sons were also affected (Z-score 2), presenting a similar phenotype with a more pro nounced deficit at the spine with low volumetric BMD and smaller bone size, with a deficit in body weight and without increased biochemical markers of bone turnover [18]. In families of male probands, a strong resemblance persisted after adjusting for environment [33]. In a complex segrega tion analysis accounting for gene-covariate interaction in 100 European pedigrees selected through a male proband, i.e. a combined analysis of two already mentioned similar family studies [17, 18], the best fitting models suggested a codominant major gene accounting for about 45% of spine and femoral neck BMDs adjusted for gender, age and BMI. However, substantial residual correlations were also found and these remained highly significant after accounting for the major gene [34]. A genome-wide linkage screen in these European pedigrees provided evidence for signifi cant or suggestive trait loci for lumbar spine (loci 17q2123, 11q12-13, and 22q11) and femoral neck BMD (locus 13q12-14) [35]. Ferrari et al [19] reported that a haplotype based on two polymorphisms in exon 9 and 18 of the LRP5 gene, respectively, was significantly associated with idiopathic osteoporosis in males. In 66 male probands with idi opathic osteoporosis, Crabbe et al [36] performed a muta tion analysis of the 23 exons and intron-exon boundaries
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and found in two men a mutation of the LRP5 gene with proven functionality. It was concluded that carrying a muta tion in the LRP5 gene is a risk factor for idiopathic oste oporosis but that, overall, idiopathic osteoporosis in men is infrequently underlied by such a mutation. Rosen et al [37] reported association of idiopathic osteoporosis in men with a polymorphic CA repeat in the insulin-like growth factor I (IGF-I) gene. Delany et al [38] described an association between polymorphisms in the 3UTR regulatory region of the osteonectin gene with BMD in Caucasian men with idiopathic osteoporosis.
Role of Hormonal Factors? Etiological considerations are per definition only specula tive, but there are interesting clues that offer directions for further research. The relative skeletal site and gender spe cificity observed in family studies suggest the possibility of alteration in bone acquisition during specific phases of pubertal development. In this regard, the observations of more pronounced bone mass and size deficits at the spine in men with idiopathic osteoporosis and of a shorter trunk height, might point towards some alterations in a late phase of pubertal development, when growth of long bones has ceased while growth of the axial skeleton is still ongoing [39]. However, this is a yet to be validated working hypoth esis and whether a defect might in fact already be apparent before puberty in affected children is presently not known. As to the hormonal factors possibly involved, it should be noted that, whereas the data point towards a develop mental defect underlying the pathogenesis of idiopathic osteoporosis in men, presently no information is available on hormonal status during the growth and pubertal develop ment in these patients. Evidence obtained in adult patients can thus only be circumstantial as observed hormonal alter ations in adults might not reliably reflect the situation dur ing development. There have been several reports of lower circulating IGF-I levels in men with idiopathic osteoporosis [27, 40, 41]. The serum levels of IGF-I in men with idiopathic oste oporosis have been reported to be positively correlated with BMD [40] and with osteoblastic surface [41] and inversely with percent eroded surfaces [27]. Lower circulating IGF-I in these patients does not result from a decreased growth hormone secretory reserve [31, 42]. Johansson et al [28] found no differences between patients and controls for growth hormone and IGF-I, but lower levels of IGF-binding protein 3 in men with idiopathic osteoporosis. Pernow et al [25] described a positive association of the IGF-I over IGFbinding proteinI levels with osteoid thickness. Low serum total and/or free estradiol in men with idi opathic osteoporosis has been found by several authors [23, 24, 32, 43, 44], but not by others [20, 30] although, in the latter reports, the authors did observe weak correlations between serum estradiol and BMD in osteoporotic men.
Albeit these data allow only for speculation on the existence of some deficit in skeletal estrogenic action during pubertal development, interestingly, we observed also lower levels of estradiol, compared to age-matched controls, in the affected young adult sons of men with idiopathic osteoporosis, but not in the sons with normal BMD [44]. Since estrogens are known to be important for skeletal maturation and miner alization during growth [45, 46], with serum (free and total) estradiol being positively correlated with areal and volumet ric BMD and negatively with endosteal circumference at age of peak bone mass in young adult men [47], a role of altered estrogen action in the deficient acquisition of bone mass and size in men with idiopathic osteoporosis can be suspected. In this regard, the bone phenotype in the men with idio pathic osteoporosis, with deficits in trabecular and cortical volumetric BMD and thinner cortices due to larger endo steal cavities [18, 24], seems to be in line with the findings of lower (free) estradiol levels. In our patients, we observed that the lower body weight, which is part of the pheno type of men with idiopathic osteoporosis, reflects in part a smaller fat mass as assessed by whole body DXA, which might in turn play a role in the lower estrogen levels, since fat tissue is a major site for aromatization of androgens. Although there have been occasional reports of lower free androgen index, a less reliable parameter of free or bioavailable testosterone serum concentrations, in men with idiopathic osteoporosis [23, 32], no consistent altera tions in serum (free or bioavailable) testosterone have been observed. A relatively consistent finding in men with idi opathic osteoporosis has been elevated serum levels of SHBG [20, 23, 30–32, 44, 48]. The lower BMI and possibly lower IGF-I levels might play a role in the higher SHBG levels which, in turn, may modulate tissue exposure to sex steroids [49].
Treatment Few prospective, randomized trials of osteoporosis thera pies have been performed in men and even less so spe cifically in men with idiopathic osteoporosis. Anderson et al [50] reported decreased bone turnover assessed by biochemical markers during testosterone treatment in an uncontrolled study of 6 months’ duration in 21 eugo nadal men with osteoporosis. Gillberg et al [51] reported an increase in BMD in men with idiopathic osteoporosis treated for 2 years with daily or intermittent subcutaneous growth hormone (GH) injections, in an uncontrolled study involving 29 patients. Kurland et al [52] conducted a rand omized, placebo-controlled double-blind trial of 18 months duration in 23 men with idiopathic osteoporosis, showing that daily subcutaneous injections of PTH (1–34) markedly increase global turnover as indicated by a marked increase of bone formation and resorption markers and resulting in a
C h a p t e r 3 3 Idiopathic Osteoporosis l
marked BMD increase at the spine with a less pronounced increase at the femoral neck. Larger randomized trials that have demonstrated increased BMD under treatment with bisphosphonates [53, 54] or teriparatide [PTH(1–34)] [55, 56] in men with osteoporosis did not include specifically patients with idi opathic osteoporosis but, in these studies, treatment effects appeared to be largely independent of baseline character istics such as age, bone turnover or prevalent sex steroid levels. Although in view of the absence of increased bone turnover or accelerated bone loss in most men with idi opathic osteoporosis, treatment with anabolic agents, such as daily injections of PTH, would seem the most logical treatment option on theoretical basis, available information seems to indicate that the patients will respond also to antiresorptive treatment with bisphosphonates [53, 54]. Primary endpoint in all randomized trials of osteoporosis therapies in men was changes in BMD and presently data on the effect of treatment on fracture risk reduction in men are very limited [53, 56]. In this context, pharmacological treatment other than calcium and vitamin D supplementa tion should be considered a priority for men with severe idiopathic osteoporosis with prevalent fractures. In younger men without prevalent fracture or indications for rapid bone loss, and thus with rather moderate absolute fracture risk, a more conservative approach seems advisable with mainly observation and advice on healthy lifestyle with calcium and vitamin D supplementation as appropriate.
Areas for further research Although some progress has been made in our understand ing of the processes underlying idiopathic osteoporosis in men, our knowledge base remains rather limited. Further progress is first of all dependent on pursued efforts for a detailed description of phenotypes with attention to anthro pometrics, bone geometry and microarchitecture, as well as histomorphometry and further hormonal and biochemical profiling. The manifestly substantial genetic component in the pathogenesis of idiopathic osteoporosis warrants pur sued genetic studies to evaluate further the impact of com mon gene variants, but also looking for major gene effects. In these studies, it is important to consider common genetic factors explaining related phenotypic characteristics. In par ticular, the common genetic determinants of skeletal status and other aspects of body composition is undoubtedly an important area for further research. Albeit available data on hormonal factors in the patho genesis of idiopathic osteoporosis in men do not yet allow for any firm conclusion, they do offer intriguing clues and warrant further research in this area. Considering the evidence for a developmental defect in the pathogenesis of idiopathic osteoporosis in a substantial proportion of affected men, the search for etiological
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clues should not be limited to adults or even to the puber tal period since individual determination of bone mass is already evident in prepubertal children. In this context, lon gitudinal follow-up study of children from affected families should provide useful information.
Acknowledgments Part of this work was supported by grant G.O662.07 from the Research Foundation Flanders (FWO; Fonds voor Wetenschappelijk Onderzoek Vlaanderen).
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30. C. Lormeau, B. Soudan, M. d’Herbomez, P. Pigny, B. Duquesnoy, B. Cortet, Sex hormone-binding globulin, estradiol, and bone turnover markers in male osteoporosis, Bone 34 (2004) 933–939. 31. P. Gillberg, A.G. Johansson, W.F. Blum, T. Groth, S. Ljunghall, Growth hormone secretion and sensitivity in men with idiopathic osteoporosis, Calcif. Tissue Int. 68 (2001) 67–73. 32. P. Pietschmann, S. Kudlacek, J. Grisar, et al., Bone turnover markers and sex hormones in men with idiopathic osteoporo sis, Eur. J. Clin. Invest. 31 (2001) 444–451. 33. C. Baudoin, M.E. Cohen-Solal, J. Beaudreuil, M.C. De Vernejoul, Genetic and environmental factors affect bone density variances of families of men and women with oste oporosis, J. Clin. Endocrinol. Metab. 87 (2002) 2053–2059. 34. C. Pelat, I. Van Pottelbergh, M. Cohen-Solal, et al., Complex segregation analysis accounting for GxE of bone mineral den sity in European pedigrees selected through a male proband with low BMD, Ann. Hum. Genet. 71 (2007) 29–42. 35. J.M. Kaufman, A. Ostertag, A. Saint-Pierre, et al., Genomewide linkage screen of bone mineral density (BMD) in European pedigrees ascertained through a male relative with low BMD values: evidence for quantitative trait loci on 17q21-23, 11q12-13, 13q12-14, and 22q11, J. Clin. Endocrinol. Metab. 93 (2008) 3755–3762. 36. P. Crabbe, W. Balemans, A. Willaert, et al., Missense mutations in LRP5 are not a common cause of idiopathic osteoporosis in adult men, J. Bone Miner. Res. 20 (2005) 1951–1959. 37. C.J. Rosen, E.S. Kurland, D. Vereault, et al., An association between serum IGF-1 and a simple sequence repeat in the IGF-1 gene: implications for genetic studies of bone mineral density, J. Clin. Endocrinol. Metab. 83 (1998) 2286–2290. 38. A.M. Delany, D.J. McMahon, J.S. Powel, D.A. Greenberg, E.S. Kurland, Osteonectin/SPARC polymorphisms in Caucasian men with idiopathic osteoporosis, Osteoporosis Int. 19 (2008) 969–978. 39. E. Seeman, Pathogenesis of bone fragility in women and men, Lancet 359 (2002) 1841–1850. 40. S. Ljunghall, A.G. Johansson, P. Burnan, O. Kampe, E. Lindh, F.A. Karlsson, Low plasma levels of insulin-like growth fac tor 1 (IGF1) in male patients with idiopathic osteoporosis, J. Intern. Med. 232 (1992) 59–64. 41. B.Y. Reed, J.E. Zerwekh, K. Sakhaee, N.A. Breslau, F. Gottschalk, C.Y.C. Pak, Serum IGF 1 is low and correlated with osteoblastic surface in idiopathic osteoporosis, J. Bone Miner. Res. 10 (1995) 1218–1224. 42. E.S. Kurland, F.K.W. Chan, C.J. Rosen, J.P. Bilezikian, Normal growth hormone secretory reserve in men with idiopathic oste oporosis and reduced circulating levels of insulin-like growth factor-1, J. Clin. Endocrinol. Metab. 83 (1998) 1–4. 43. C.G. Carlsen, T.H. Soerensen, E.F. Eriksen, Prevalence of low serum estrogen levels in male osteoporosis, Osteoporosis Int. 11 (2000) 697–701. 44. I. Van Pottelbergh, S. Goemaere, H. Zmierczac, J.M. Kaufman, Perturbed sex steroid status in men with idiopathic osteoporosis and their sons, J. Clin. Endocrinol. Metab. 89 (2004) 4949–4953. 45. J.P. Bilezikian, A. Morishima, J. Bell, M.M. Grumbach, Increased bone mass as a result of estrogen therapy in a man with aromatase deficiency, N. Engl. J. Med. 339 (1998) 599–603.
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46. D. Vanderschueren, K. Venken, J. Ophoff, R. Bouillon, S. Boonen, Sex steroids and the periosteum – reconsidering the roles of androgens and estrogens in periosteal expansion, J. Clin. Endocrinol. Metab. 91 (2006) 378–382. 47. B. Lapauw, Y. Taes, V. Bogaert, et al., Serum estradiol is associated with volumetric bone mineral density and modu lates the impact of physical activity on bone size at the age of peak bone mass: a study in healthy male siblings, J. Bone Miner. Res. 24 (2009) 1075–1085. 48. E. Legrand, C. Hedde, Y. Gallois, et al., Osteoporosis in men: a potential role for the sex hormone binding globulin, Bone 29 (2001) 90–95. 49. A. Vermeulen, J.M. Kaufman, V.A. Giagulli, Influence of some biological indexes on sex hormone-binding globulin and androgen levels in aging or obese males, J. Clin. Endocrinol. Metab. 81 (1996) 1821–1826. 50. S.H. Anderson, R.M. Francis, R.T. Peaston, H.J. Wastell, Androgen supplementation in eugonadal men with osteoporo sis: effect of six months’ treatment on markers of bone forma tion and resorption, J. Bone Miner. Res. 12 (1997) 472–478. 51. P. Gillberg, H. Mallmin, M. Petrén-Mallmin, S. Ljunghall, A.G. Nilsson, Two years of treatment with human recombinant
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growth hormone increases bone mineral density in men with idiopathic osteoporosis, J. Clin. Endocrinol. Metab. 87 (2002) 4900–4906. E.S. Kurland, F. Cosman, D.J. McMahon, C.J. Rosen, R. Lindsay, J.P. Bilezikian, Parathormone as a therapy for idiopathic osteoporosis in men: effects on bone mineral den sity and bone markers, J. Clin. Endocrinol. Metab. 85 (2000) 3069–3076. E. Orwoll, M. Ettinger, S. Weiss, et al., Alendronate for the treatment of osteoporosis in men, N. Engl. J. Med. 343 (2000) 604–610. S. Boonen, E.S. Orwoll, D. Wenderoth, K.J. Stoner, R. Eusebio, P.D. Delmas, Once-weekly residronate in men with osteoporo sis: results of a 2-year, placebo-controlled, double-blind, multi center study, J. Bone Miner. Res. 24 (2009) 719–725. E.S. Orwoll, W.H. Scheele, S. Paul, et al., The effect of teri paratide [human parathyroid hormone (1-34)] on bone density in men with osteoporosis, J. Bone Miner. Res. 18 (2003) 9–17. J.M. Kaufman, E. Orwoll, S. Goemaere, et al., Teriparatide effects on vertebral fractures and bone mineral density in men with osteoporosis: treatment and discontinuation of therapy, Osteoporosis Int. 16 (2005) 510–516.
Chapter
34
Glucocorticoid-induced Osteoporosis Gherardo Mazziotti and Andrea Giustina Department of Medical and Surgical Sciences, University of Brescia, Italy
Epidemiology
both associated with bone loss, independently of glucocorticoid treatment [12, 13]. The systemic release of inflammatory cytokines, which affect bone formation and bone resorption, may have a pathophysiological role in bone loss in these settings. Chronic obstructive pulmonary disease is usually reported as the most frequent cause of chronic glucocorticoid treatment in men [14, 15]. Endogenous hypercortisolism is less frequently a cause of GIO, although a recent paper showed that up to 10% of males attending an outpatient clinic of osteoporosis may have a subclinical Cushing’s syndrome [16]. Fragility fractures can be the presenting manifestation of Cushing’s syndrome, either clinical or subclinical [17, 18]. Limited data from cross-sectional studies show that at least 30–50% of patients with overt Cushing’s syndrome experience fractures, particularly at the vertebral level [17, 18]. The prevalence of osteoporosis in adults with Cushing’s syndrome has been suggested to be greater in males as compared to females [19]. Although remission of Cushing’s syndrome may lead to improvement in the attendant osteoporosis, recovery of bone loss is gradual and often incomplete [20].
Glucocorticoid-induced osteoporosis (GIO) is the most frequent form of secondary osteoporosis in males as well as in females [1, 2]. GIO is almost always caused by exogenous glucocorticoids which are widely used in the treatment of autoimmune, pulmonary and gastrointestinal disorders, as well as in patients after organ transplantation and with neoplastic diseases [3–5]. Approximately 1% of the population is under oral glucocorticoid treatment and, in the elderly, this prevalence rises to 2.5% [6]. Unfortunately, glucocorticoids also have several potential side effects, one of the most common being GIO with increased risk of vertebral and nonvertebral fractures [6]. In men, the fracture risk is low during midlife and increases after 65 years of age remaining lower compared with women [3]. It was calculated that the median risk score for a clinical osteoporotic fracture in men starting glucocorticoid treatment was 13, 22 and 31 for the ages 40–49, 60–69 and 80–89 years, respectively [7]. Likewise, the 10year probability to develop any osteoporotic fractures in men taking glucocorticoids is 7.5% regardless of bone mineral density (BMD), increasing to 15% in presence of a low BMD [8]. Fracture risk increases rapidly after starting oral corticosteroid treatment and is also related to the dose and duration of glucocorticoid exposure. Doses as low as 2.5– 7.5 mg of prednisolone equivalents per day can be associated with a 2.5-fold increase in vertebral fractures, but the risk is greater with higher doses used for prolonged periods [6, 9]. It is noteworthy that fracture risk returns toward baseline levels after discontinuation of oral corticosteroids, although the reversal time seems to be variable [3, 10]. The risk of osteoporotic fractures remains slightly increased in patients undergoing cyclic corticosteroid treatment at high doses [11]. Many disorders for which glucocorticoids are prescribed are themselves cause of osteoporosis. Rheumatoid arthritis and chronic obstructive pulmonary disease, for example, are Osteoporosis in Men
Pathophysiology Glucocorticoids have both direct and indirect effects on bone. The central pathophysiological mechanism of bone loss during long-term use of glucocorticoids is reduced bone formation, due to actions that affect osteoblast differentiation and function. However, during the first phases of glucocorticoid excess, significant increase in bone resorption (ultimately leading to the observed early increase of risk of fractures) may occur. Glucocorticoids may impair the differentiation of bone marrow stromal cells into cells of the osteoblastic lineage; 415
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precursor cells in the presence of glucocorticoids preferentially differentiate in to adipocytes [21]. Mechanisms involved include the induction of peroxisome proliferator activated receptor 2, the regulation of nuclear factors of the CAAT enhancer-binding protein family and the inhibition of Wnt/beta-catenin signaling [21]. Wnt signaling has emerged as a novel, key pathway for promoting osteo blastogenesis [22]. In skeletal cells in which the canonical Wnt/-catenin signaling pathway is active [23], when Wnt is absent, -catenin is phosphorylated by glycogen-synthase kinase-3 (GSK-3) and then degraded by ubiquitination. When Wnt is present, it binds to specific receptors leading to inhibition of GSK-3 activity and translocation of stabilized -catenin to the nucleus, where it associates with transcription factors to regulate gene expression [22]. Deletions of either Wnt or -catenin result in the absence of osteo blastogenesis and increased osteoclastogenesis [22]. The Wnt pathway can be inactivated by Dickkopf, an antagonist that prevents Wnt binding to its receptor complex, the expression of which is enhanced by glucocorticoids, that maintaining GSK 3- in an active state ultimately leads to the inactivation of -catenin [22, 24]. Glucocorticoids also inhibit osteoblast cell differentiation and inhibit osteoblast-driven synthesis of type I collagen, the major component of bone extracellular matrix [1]. The result is a decrease in bone matrix available for mineralization. Glucocorticoids have pro-apoptotic effects on osteo blasts and osteocytes [25]. Glucocorticoids may also affect the metabolism and function of osteocytes, modifying the elastic modulus surrounding osteocyte lacunae and causing reduced mineral to matrix ratios in the same areas with an increase in lacunar size [26]. These effects of glucocorticoids on osteocytes might account for a disproportionate loss of bone strength in relation to bone mass. The initial bone loss occurring in patients exposed to glucocorticoids may be secondary to increased bone resorption [4, 27]. In fact, glucocorticoids may increase the expression of receptor activator of NF-B ligand (RANKL) and decrease the expression of its soluble decoy receptor, osteoprotegerin (OPG) in stromal and osteoblastic cells [1, 28]. The combination of an increase in RANKL, a potent activator of osteoclasts, and a reduction in OPG, an inhibitor of RANKL action, leads to the initial phase of rapid bone loss. Glucocorticoids also enhance the expression of macrophage colony-stimulating factor (MCSF) which, in the presence of RANKL induces osteoclastogenesis [1]. Moreover, glucocorticoids have been demonstrated to upregulate receptor subunits for osteoclastogenic cytokines of the gp130 family [29]. Furthermore, glucocorticoids may decrease apoptosis of mature osteoclasts [30]. Consequently, there is increased formation of osteoclasts with a prolonged life span explaining, at the cellular level, the enhanced and prolonged bone resorption observed at least in the initial phases of GIO. The direct effects of glucocorticoids on osteoclasts also
Table 34.1 Behaviour of different parameters of spontaneous parathyroid hormone (PTH) secretion in glucocorticoid-treated versus control males Increased
Unchanged
Decreased
Pulse secretory rate* Fractional pulsatile secretion*
Total number of bursts Mean PTH concentration Mean integrated area
Tonic secretory rate*
Based on data from [32]. * P 0.05 versus controls
may contribute to a reduction of osteoblast function during glucocorticoid exposure [31]. Glucocorticoids may have also indirect effects on bone [1]. In fact, glucocorticoids may decrease calcium absorption from the gastrointestinal tract by opposing vitamin D action. Renal tubular calcium reabsorption is also inhibited by glucocorticoids. As a consequence of these effects, secondary hyperparathyroidism has been postulated to develop. However, other studies did not confirm that glucocorticoids are associated with increased baseline levels of parathyroid hormone (PTH). As a matter of fact, these two sets of evidence may be reconciled by recent data showing that glucocorticoids may significantly affect spontaneous PTH secretory dynamic in males, with a decrease in the tonic release of PTH and an increase in pulsatile bursts of the hormone (Table 34.1) [32]. Glucocorticoids may also enhance the sensitivity to PTH by changing the number of PTH receptors and their affinity for PTH [1]. Glucocorticoids may also influence the production and action of hormones that regulate bone and calcium metabolism. Although hypogonadism seems to be not contributing to GIO in experimental animals [33], in clinical conditions, decreased serum testosterone levels are frequently demonstrated in males during glucocorticoid treatment [34]. Reduced gonadotropin production and a direct effect on testosterone production from the testes may play a pathophysiological role in this regard (Figure 34.1). A direct interaction between glucocorticoids and testosterone is supported by molecular studies showing heterodimer formation between androgen and glucocorticoid receptors and mutual inhibition of transcriptional activity [35]. Hypogonadism may contribute to bone loss and fractures in GIO not only via negative effects on bone mass but also on muscle function (see Figure 34.1). In particular, hypogonadism may enhance the glucocorticoid-induced sarcopenia, thereby increasing the likelihood of falls and consequent fractures in male patients. Glucocorticoids also regulate the growth hormone/insulinlike growth factor-I (GH/IGF-I) axis [36] (Figure 34.2). GH secretion is blunted by glucocorticoids mainly via an increased hypothalamic somostatin tone and glucocorticoids also decrease IGF-I transcription in osteoblasts [37–39] (see Figure 34.2). It is interesting that blunted GH secretion
C h a p t e r 3 4 Glucocorticoid-induced Osteoporosis l
glucocorticoid molecules [42]. An increase of 11-hydroxy steroid dehydrogenase type 1 activity may possibly provide an explanation for the enhanced glucocorticoid effects in the skeleton of elderly subjects [43]. Furthermore, glucocorticoid receptor gene polymorphism may play a role in determining gender differences in bone effects of glucocorticoids [44]. In fact, there is recent evidence that glucocorticoid receptor gene polymorphism is correlated with BMD in males but not in females [45].
PITUITARY FSH LH GCs + +
TESTIS –
GCs
417
GCs TESTOSTERONE –+
+ –
BONE
MUSCLE
Figure 34.1 Systemic effects of glucocorticoids (GCs) on testosterone secretion and action in men. Solid lines indicate major effects of GCs. FSH: follicle stimulating hormone; LH: luteinizing hormone.
SS
GHRH
+ –
+
GCs
PITUITARY GH –
+ LIVER
IGF-I – +
GCs
BONE
Figure 34.2 Systemic effects of glucocorticoids (GCs) on GH/IGF-I-bone axis. Solid lines indicate major effects of GCs. GHRH: growth hormone releasing hormone; IGF-I: insulin-like growth hormone; SS: somatotropin.
in male asthmatic patients receiving inhaled corticosteroids is observed in association with reduced ultrasonometric bone density [40], suggesting that inhaled steroid-mediated inhibition of synthesis or release of GH may be involved in bone loss [40, 41]. Variable individual susceptibility to glucocorticoids may be due to differential absorption, distribution or metabolism of the steroid molecule or to the number and affinity of glucocorticoid receptors or their nuclear co-factors [42]. An attractive explanation to account for inter-individual variability among those exposed to glucocorticoids is related to a peripheral enzyme system that converts active and inactive
Diagnosis Despite the fact that glucocorticoids can cause osteoporosis and fractures, many patients receiving or initiating longterm glucocorticoid therapy are not evaluated for their bone status. The awareness of GIO seems to be much lower when males are concerned [14, 46]. In a retrospective chart review, BMD measurement was performed or prescribed only to less than 50% of men taking glucocorticoids and this was crucial for a subsequent initiation of antiosteoporotic treatment in these subjects [14]. Indeed, a consensus is still lacking on if or when to perform and how to interpret BMD measurement in males with GIO. In fact, while authoritative intervention guidelines recommend that a BMD measurement should be made in individuals starting glucocorticoid therapy and before administering bisphosphonates in all subjects taking glucocorticoids [47], other guidelines recommend BMD measurement only in subjects younger than 65 years [48]. Moreover, although BMD is highly predictive of fracture risk in men, this relationship is not as well established as in women [2]. Therefore, if, in general, the best cut-off to identify men at high risk of fracture is still not well defined, in patients with GIO, in particular, this issue is open since fractures tend to occur at lower BMD threshold than in the other forms of osteoporosis [49, 50]. This point has to be taken into account when treatment recommendations are made on the basis of BMD measurements. The intervention threshold of the Royal College of Physicians is a T-score of 1.5 and that of the American College of Rheumatology (ACR) a T-score of 1, both cut-offs that are much higher than the T-score treatment threshold of 2.5 in postmenopausal women [51]. It remains to be clarified whether these cut-offs may be of clinical utility in men taking glucocorticoids, especially when they are drawn from reference ranges obtained in women. The identification of vertebral osteoporotic fractures in patients under chronic glucocorticoid treatment may be important for the therapeutical decision-making process [48]. In fact, as in other forms of secondary osteoporosis [52–54], in GIO, vertebral fractures may be asymptomatic [55]. Therefore, since the clinical history may not be reliable, a radiological approach with morphometric analysis is often necessary for the identification of vertebral deformities.
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Osteoporosis in Men
The Royal College of Physicians guidelines recommend evaluation of calcium metabolism in all subjects in order to select those for whom vitamin D and/or calcium supplementation are indicated [48]. In contrast, according to ACR guidelines, this metabolic assessment may not be necessary since calcium and vitamin D supplementation is recommended in all patients with GIO independently of their baseline vitamin D status [47]. The role of biochemical markers of bone turnover in the diagnostic work-up in GIO has not yet been established with their levels also varying in the different stages of the disease [56]. In fact, following the initial exposure to glucocorticoids, there is an increase in biochemical markers of bone resorption, which is followed by a long-standing suppression of markers of bone formation and bone resorption [56]. Finally, the assessment of gonadal function may be useful for the subsequent treatment of GIO. In men taking glucocorticoids, low total and free-testosterone are frequently found. This status may be combined with low or normal serum gonadotropin levels as expression of a secondary hypogonadism [34].
Therapy Guidelines published by ACR and the Royal College of Physicians advocate the following measures for the prevention and treatment of GIO: general health awareness; administration of sufficient calcium and vitamin D; reduction of the dose of corticosteroids to a minimum; and, when indicated, therapeutic intervention with bisphosphonates and other agents [51]. The ultimate goal of all these measures is to prevent fractures. Vitamin D and its analogs prevent bone loss during glucocorticoid therapy without significant differences between males and females [57, 58]. A practical point of vitamin D therapy in subjects receiving glucocorticoids relates to vitamin D resistance that is often seen in this setting. In fact, rather than maintaining 25-hydroxyvitamin D levels at a minimally adequate level, i.e. 30 ng/ml, many experts recommend the goal to be set at 40–60 ng/ml. In order to maintain these levels, patients often require amounts of 1000–2000 IU of vitamin D3 daily [58]. The early effect of glucocorticoids on bone resorption represents the rationale for the use of antiresorptive therapy [59]. Pathophysiological considerations suggest that antiresorptive treatment should be started early in patients undergoing glucocorticoid therapy [59]. Guidelines from the UK suggest that treatment in GIO is indicated in: 1. patients who are at high risk of osteoporosis, such as those taking prednisone equivalent doses higher than 7.5 mg daily, or those with personal history of fractures or those with lifestyle risk factors for osteoporosis
2. patients with low risk of osteoporosis but with T-scores below 1.5 SD, as assessed by vertebral dual energy x-ray absorptiometry (DXA) 3. patients with low risk of osteoporosis and T-score above 1.5 SD, but with a decline in vertebral BMD of at least 4.0% after one year of glucocorticoid treatment [48]. Conversely, ACR guidelines recommend bisphosphonates to be started in patients who are receiving 5 mg of prednisone equivalents daily for more than 3 months and with T-scores below 1.0 SD [47]. Indeed, there is evidence that there is still suboptimal application of these guidelines. In clinical practice, treatment with bisphosphonates seems to be prevalently based on low BMD, whereas these drugs are rarely prescribed for the prevention of GIO [14, 60]. A recent retrospective chart review showed that more than 60% of men with available BMD measurement and only 8% of subjects who did not undergo BMD evaluation were prescribed bisphosphonates for GIO [14]. Alendronate and risedronate are the only antiresorptive drugs approved for the treatment of GIO in men [61]. These drugs were shown to improve BMD in all studies in which males and females were analyzed separately, whereas the data on fractures were scanty and not always statistically conclusive, likely due to the low number of enrolled males and the short period of treatment. Alendronate administered daily was shown to increase BMD by 3.4% after one year of treatment with a slight decrease of incidence in morphometric vertebral fractures [62]. The effects of alendronate on BMD were shown to be greater after 2 years of treatment, whereas the effects on vertebral fractures in males was not demonstrated due to the low number of events during the study period [63]. One-year treatment with risedronate was shown to increase BMD by 2.1–4.8% from baseline across different skeletal sites in men with GIO [64]. Risedronate was also shown to decrease slightly vertebral fractures in those studies in which the analysis was performed separately in men and women [65, 66]. In men with GIO, testosterone administered intramuscularly induced a significant increase in lumbar BMD, without any significant effects on BMD at femoral neck [67]. The studies had BMD as primary end-point, whereas no information on bone fractures is available [68–70]. Testosterone was also shown to improve muscular performance and quality of life in men with GIO [70]. Interestingly, the beneficial effects of testosterone on bone, muscle and quality of life were shown to be independent of the prior androgen status: this observation suggests a direct anti-glucocorticoid effect of androgens, presumably via steroid receptor interactions in addition to the reversal of the systemic catabolic effect of glucocorticoids [35]. Another drug approved for the treatment of GIO in men is teriparatide. PTH is an attractive candidate for the therapy of GIO because it protects against osteoblast apoptosis and increases osteoblast cell number [22]. PTH administration
C h a p t e r 3 4 Glucocorticoid-induced Osteoporosis l
induces an initial uncoupling of bone remodeling with an early increase in bone formation followed by a more gradual increase of bone resorption [22]. According to the concept of the ‘anabolic window’, PTH rapidly stimulates osteoblast function, inducing an upregulation of osteoblastderived cytokines which eventually leads to osteoclast activation and gradual rebalancing of bone formation and resorption [22]. The efficacy of teriparatide was initially assessed in eugonadic and hypogonadic men with idiopathic osteoporosis [71]. Recently, data in GIO have also been published. In a multicenter, randomized, controlled study, the effects of teriparatide were compared with those of alendronate on lumbar spine BMD as primary end-point in 82 males and 346 females undergoing long-term glucocorticoid therapy at high risk for osteoporotic fractures, i.e. with mean baseline lumbar T-score of 2.5 and with high prevalence of fragility fractures [72]. In this clinical setting, teriparatide was significantly more effective than alendronate in increasing BMD at both the lumbar spine and total hip during an 18-month period [72]. As a secondary end-point, the incidence of new vertebral fractures was determined to be 6.1% and 0.6% in patients receiving alendronate and teriparatide, respectively [72]. Teriparatide treatment was associated with a higher frequency of undesired side effects, such as injection-site reactions, headache and dizziness [72]. In a recently performed separate analysis, teriparatide has been shown to be as effective in men as compared to women with GIO [73]. GH and IGF-I administration have been proposed to revert some of the negative effects of chronic glucocorticoid treatment on bone [39, 50]. Increases in serum osteocalcin, carboxy-terminal propeptide of type I procollagen and carboxy-terminal telopeptide of type I collagen were observed following short-term use of recombinant human GH treatment in a selected population of male and female patients receiving chronic corticosteroid treatment for non-endocrine diseases [38]. Moreover, combined therapy of GH and IGF-I counteracted selected negative effects of glucocorticoids on bone in healthy volunteers who received short-term glucocorticoid therapy [74]. Observational and controlled studies in children receiving glucocorticoid therapy for juvenile idiopathic arthritis showed that GH restored normal height velocity with a concomitant improvement in bone mineralization [75, 76]. However, the efficacy on BMD and fractures and safety of GH and IGF-I treatment in GIO needs still to be documented by prospective controlled studies.
Conclusions GIO is one of the most frequent forms of osteoporosis in men, for which the awareness is still suboptimal. Peculiar epidemiological (underlying diseases) and pathophysiological (hypogonadism) aspects characterize GIO in men. With
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regard to diagnostic as well as therapeutic measures there are no specific recommendations in males with GIO with the exception of testosterone replacement. Moreover, data concerning BMD cut-offs and treatment efficacy are often translated from the experiences in females more than based on sex-specific evidences.
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Chapter
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Testicular Dysfunction Christian Meier1, Markus J. Seibel2 and David J. Handelsman3 1
Division of Endocrinology, Diabetes and Clinical Nutrition, University Hospital Basel, Switzerland Bone Research Program, ANZAC Research Institute, University of Sydney, Sydney NSW, Australia 3 Department of Andrology, ANZAC Research Institute, Concord Hospital, University of Sydney, Sydney NSW, Australia 2
[1]. In men, the secretion of testosterone from testicular Leydig cells is responsible for virtually all (95%) of the body’s androgen secretion with minor amount or proandrogens, such as dehydroepiandrosterone (DHEA), emanating from the adrenal glands which serve mainly as substrates for extragonadal conversion to estradiol. At puberty, testosterone secretion increases 20–30-fold to circulate for the remainder of adult life at levels 10–15 times that of children, women and castrate men. Testosterone, the principal mammalian androgen, has a complex mode of action as it can bind directly to the androgen receptor (AR) or undergo pre-receptor activation via the amplification (to dihydrotestosterone) or diversification (to estradiol) pathways [1] (Figure 35.1). The amplification pathway converts testosterone via the 5- reductase enzymes to dihydrotestosterone (DHT), a 3–10-fold more potent, pure, non-aromatizable androgen that acts solely on the AR. The diversification pathway converts testosterone to
Introduction The gonads have two distinct canonical functions – the production of functional gametes for fertilization and the secretion of gonadal steroids for sexual differentiation, maturation and near ubiquitous functional effects on organs and tissues. Consequently, gonadal dysfunction may be manifest as failure in either or both of its twin functions, such as infertility and/or steroid hormone deficiency. In men, testicular failure may become evident as isolated defects in spermatogenesis or steroidogenesis or both because the two axes operate in largely independent fashion with their inter-dependence only evident in extremes such as after orchidectomy or with complete gonadotropin deficiency. Most disorders of spermatogenesis – such as cytotoxic chemo- or radiotherapy effects on the testis or most causes of male infertility – however have essentially no, or at most, minimal clinical effects on androgen secretion or action. Conversely, acquired luteinizing hormone deficiency (LH) deficiency, such as with under-nutrition or other catabolic states that commence after completion of normal puberty and sperm production, may spare spermatogenesis. All known effects of the testis on bone are solely attributable to its gonadal steroid secretions and are unrelated to the testis’s other function of spermatogenesis. Consequently, this chapter will consider the effects of androgen (and/or estrogen) deficiency and avoid using the ambiguous term ‘hypogonadism’ which is functionally non-specific and inaccurate.
Pathways of testosterone action IE
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Androgens are synthesized from cholesterol through a multistep enzymatic pathway which shortens the side chain of cholesterol via oxidation from 27 to a 19 carbon skeleton Osteoporosis in Men
DHT
Figure 35.1 Pathways of testosterone action. 423
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estradiol (E2) via the CYP19 (aromatase) enzyme, a widely distributed microsomal cytochrome P450 enzyme, which acts on the estrogen receptor (ER), thereby broadening the scope of testosterone action. The adrenal cortex secretes relatively large amounts of 19 carbon androgens including DHEA, DHEA sulfate and androstenedione. These androgens can be converted to biologically active estrogens, such as estradiol, or to biologically active androgens, such as testosterone and DHT, via a succession of enzymatic steps involving steroid sulfatase, 17-hydroxysteroid dehydrogenase (17-HSD) and/or 3-HSD [2]. Thus, testosterone functions not only as a potent and amplifiable androgen acting on the AR but also as a precursor for conversion to the biologically active estrogen, estradiol, which acts on the ERs. This has significance for bone in that E2 plays a major role in bone metabolism of not only women but also of men. In men, the extra-testicular aromatization of circulating testosterone to estradiol is important. Only a small proportion (15–20%) of estradiol is directly secreted by the testes, although this proportion increases with circulating blood LH levels [3]. Nevertheless, overall, only a tiny fraction (0.1%) of testosterone undergoes aromatization, whereas a larger proportion (5–10%) is 5 reduced to DHT, while the remainder is inactivated mainly by the liver. A consequence is that, except under the rare circumstances of inactivating mutations in estradiol synthesis (aromatase) or action (ER), men never become severely estrogen deficient. Conversely, administration of exogenous estrogens, such as estradiol, at sufficient doses produces androgen deficiency via negative hypothalamic feedback. Consequently, studying isolated estrogen effects in men is difficult for both practical and ethical/safety reasons. In general, depending on the relative expression and pre-receptor enzymatic activation by aromatase, 5-reductase and dehydrogenases together with the relative distribution of AR and ERs in peripheral target tissues, testosterone and its bioactive metabolites may predominantly activate either the AR and/or the ER. For bone, the pattern of expression in osteoblasts, osteoclasts and osteocytes of aromatase, 5-reductase, 17-HSD, 3-HSD enzymes and of the AR and ERs (ER and ER) supports the concept of tissue-specific pre-receptor activation and local action of gonadal steroid hormones within the skeleton. While the gender dimorphism in bone size, density and strength is attributable to androgen action, the relative effects of the direct action of testosterone relative to the contributions of pre-receptor testosterone activation to DHT and aromatization to E2, both within bone and in extra-osseous tissues, remain to be accurately apportioned. Clinical studies suggest that aromatization of testosterone to E2 plays a significant role in the regulation of bone mass, notably in relation to age-related bone loss in older men [4]. However, the relative importance of blood testosterone for accrual and maintenance of bone in men relative to pre-receptor activation remains contentious and difficult to study in decisive fashion due to ethical and practical
constraints. A recent elegant study in mice, however, provides definitive evidence on the differential roles of AR and ER for bone and body composition. Using AR, ER and double knockout mice, direct AR activation was shown to be solely responsible for the development and maintenance of male trabecular bone mass, whereas both AR and ER activation are required to optimize the acquisition of cortical bone [5]. Androgen deficiency is a clinical diagnosis based on: 1. an appropriate clinical context (presentation) 2. identification of an underlying pathological disorder of the hypothalamo-pituitary-testicular axis responsible for a sustained decreased in testicular testosterone secretion 3. biochemical confirmation of consistently low serum testosterone [6]. No single element alone is sufficient for the clinical diagnosis of chronic androgen deficiency. In particular, reduced circulating testosterone is a characteristic, non-specific hypothalamo-pituitary response to a variety of acute or chronic pathological states or diseases, including fractures, chronic pain or opiate analgesic medication [6]. Hence, a single blood testosterone measurement by any assay does not constitute a diagnosis of chronic androgen deficiency. The inaccuracy and method-dependence of commercial semi-automated platform immunoassays for testosterone [7, 8] and of so-called ‘free testosterone’ [9] is now well established. The superseding of these assays by mass spectrometry-based measurements is underway in research and larger routine clinical pathology laboratories and likely to become universal in the near future.
Age-Related Changes in Gonadal Hormones Male aging is associated with a gradual, progressive decrease in circulating testosterone [10, 11]. Longitudinal populationbased studies show that serum total testosterone concentrations decline by 1% per year in men [12], but the biological or clinical importance of such a decline remains unclear [13]. A variety of derived testosterone measures (‘free’, ‘bioavailable’), which putatively better reflect androgen action of testosterone on tissues, have been postulated as variants of the ‘free hormone’ hypothesis. This hypothesis remains unproven and lacks both adequate theoretical basis or empirical verification [9]. For example, while ‘free’ testosterone (i.e. the fraction of total testosterone not bound to sex hormone binding globulin (SHBG) or albumin) falls as SHBG (and its binding capacity) rises with age [14–16], it is unclear whether this represents more or less net androgen action at a tissue level. The ‘free’ hormone is not only more accessible to sites of hormone action but also to the, quantitatively more important, site of testosterone inactivation [17]. It remains implausible that a single static derived testosterone measure would adequately reflect androgenic action in all
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androgen-responsive tissues, including bone, given the complexity of blood-to-tissue transfer of testosterone as well as local tissue- and organ-specific androgen amplification systems which are likely to be crucial in modulating the net biological androgen action within cells. The widely used calculational formulae to estimate ‘free testosterone’ from concurrent testosterone and SHBG measurements do not correspond well to laboratory direct measurement of ‘free testosterone’, are erroneous and poorly validated [18]. Similar limitations are likely to be present for so-called ‘free estradiol’, although this variable lacks even basic validation. Despite the firmly established decline in total, free or SHBGbound testosterone with male aging, such a gradual and modest decline may not warrant replacement because older tissues may not remain as androgen responsive and the magnitude of the deficit may not be sufficient. Whether testosterone replacement is effective or safe remains to be established by appropriate interventional studies [13, 19]. Although the decline in testosterone levels with male aging is observed in virtually all studies, evidence remains conflicting whether there is any change in blood E2 with male aging [10, 11, 20]. This may be due to a combination of factors, such as the low overall proportion of testosterone converted to E2 (0.1%) so that substrate (testosterone) for aromatization is not limiting and the age-related increased aromatase activity due to the concomitant increase in fat mass [21]. Although non-SHBG bound E2 levels decrease with age (by about 50% over six decades) as a consequence of increasing SHBG concentrations [22], the biological meaning of this unvalidated, derived estradiol measure remains to be established. The single steroid binding on SHBG displays competitive binding of steroids so that the biological meaning of unbound E2 relative to the 100-fold higher molar concentrations of testosterone remains unclear. Furthermore, non-extraction direct (automated) immuno assays are especially unreliable for the very low serum estradiol concentrations present in men, children and postmenopausal women [23]. For these reasons, the biological significance for bone of ‘free’ or SHBG-bound E2 is even less well defined than for comparable derived testosterone measures. While the available evidence indicates that estradiol has significance for the male skeleton [4], the circulating blood estradiol concentrations in men are comparable with estrogen-deficient postmenopausal women raising the paradoxical issue of why bone of healthy men does not acquire the osteoporotic state of postmenopausal women. In fact, male bone actually becomes and remains larger, with higher peri- and endosteal diameters than women, which makes it even stronger than premenopausal female bone. This may be explained, at least in part, by AR-mediated effects and/or greater importance of local bone aromatase expression in male bone so that estrogen action is more dependent on local production than on systemic exposure. However, other factors, such as larger body and muscle mass in men, are also likely to be important.
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Skeletal health in androgen deficiency at various ages Bone undergoes two major changes during postnatal life of men, the accrual of bone mass during adolescence to achieve peak bone mass in early manhood and the age-related bone loss in older men. Both are multifactorial with important hormonal, environmental and genetic factors. At puberty, a dramatic increase in bone size, mass and mineral content as well as muscle mass occurs following the dramatic 20–30-fold increase in circulating testosterone levels. This leads to development of peak bone mass early in the third decade of life after which there begins a gradual decline with age in bone mineral density (BMD), although the rate of decline is less in men than in premenopausal women and especially postmenopausal women. At all ages, gonadal steroid hormones are important determinants of skeletal integrity. To appreciate the effect of gonadal steroid hormones on bone turnover, BMD and fracture risk in men, the effects of androgens are discussed separately in prepubertal and post-pubertal (adult) onset of androgen deficiency. Whether this age-related bone loss in men contributes to or is coincidental with the concomitant slow decrease in blood testosterone levels will be considered but remains unclear.
Prepubertal Onset of Androgen Deficiency Adolescence is associated with profound increases in bone mass in both sexes with significant increase in axial and appendicular bone mass [24, 25]. Maximal increases in bone mass accrual occur between 11 and 14 years of age in girls and 13 and 17 years in boys [26], with more than 90% of peak bone mass being achieved by the end of the second decade [27]. The pattern of skeletal growth in puberty differs in boys being about 2 years later, allowing for 2 more years of prepubertal statutural growth prior to epiphyseal fusion. Furthermore, the pubertal growth spurt lasts 4 years in boys, longer than the 3 years in girls [28, 29]. In concert, these differences account for the 10% greater statural height and the 25% greater peak bone mass acquired by boys during puberty. The greater bone mass of boys is largely due to their greater bone size, whereas peak volumetric bone density does not differ between young men and women. In boys, the increase in indices of bone formation and skeletal mass during pubertal development is closely linked to pubertal stage [30] and to testicular [31] and adrenal [32] androgen levels. Many chronic childhood illnesses are associated with delayed puberty and low body weight. Importantly, failure to enter puberty or pubertal arrest can occur as a consequence of primary gonadal failure (e.g. chemotherapy) or secondary to gonadotropin deficiency due to pituitary damage (e.g. as a consequence of iron overload in thalassemia major treated with regular blood
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transfusions) [33]. Anorexia nervosa, a condition of severe undernutrition associated with sex hormone deficiency is known to result in decreased bone turnover and low bone mass. The condition, which also occurs in adolescent boys, is characterized by hypothalamic-pituitary androgen deficiency, undernutrition with decreased lean body mass and impaired growth hormone action [27]. Further evidence of the importance of androgens in male bone development comes from reports showing that men with complete androgen resistance appear to have low bone density [34] and men with androgen insufficiency due to isolated gonadotropin deficiency have been shown to have abnormally low bone mass even when corrected for bone age [35]. Androgen replacement therapy in these men before epiphyseal closure resulted in rapid increase in bone mass [36–38]. It has been known for decades that neuroendocrine effects of testosterone mainly, but not exclusively, negative feedback on the hypothalamus, were mediated by local tissue aromatization of testosterone to E2 with effects manifest via both AR and ER mechanisms [39]. Recent observations suggest similar aromatization-dependent mechanisms apply to bone. The first evidence supporting this concept emerged from a report of a 28-year-old man with estrogen resistance caused by a homozygous and inactivating mutation in the estrogen receptor gene. Despite normal serum testosterone levels and elevated circulating levels of E2, he had accelerated bone turnover with increased rates of bone formation and bone resorption resulting in a bone mass in the osteopenic range [40]. Subsequently, clinical findings in men with aromatase deficiency caused by inactivating mutations in the aromatase gene and undetectable circulating E2 confirmed similar findings due to functional estrogen deficiency [41–43]. Again, bone turnover and BMD in these estrogen deficient men were markedly altered with undetectable circulating E2 levels but normal serum testosterone levels. Furthermore, estrogen treatment in men with aromatase deficiency suppressed bone resorption [43] and markedly increased bone mass [42, 43]. Although showing a striking requirement for estrogen effects in bone of men, these individual cases reflect developmentally disordered bone formed under conditions of congenital severe estrogen deficiency and it is not clear how these findings relate to the maintenance of normal mature bone developed under eugonadal conditions. Some corroboration of a role for E2 is provided by two studies suggesting an important role for E2 in maintaining mature bone in men [44, 45]. These short-term studies induced isolated estrogen deficiency by treatment with a combination of gonadotropin releasing hormone (GnRH) analog plus an aromatase inhibitor in older men and demonstrated that E2 has distinct effects in maintaining biochemical markers of bone turnover. These experimental studies were not long enough, however, to determine the net effects of induced isolated E2 deficiency on bone mass.
Post-Pubertal (Adult) Onset of Androgen Deficiency A low blood testosterone level, usually based only on a single blood sample, is present in 15–36% of men with documented osteoporosis [46, 47]. Even with better standardization of testosterone assays, this is likely to overestimate the rate of underlying chronic androgen deficiency because the impact of transient non-specific effects of acute or chronic illness, notably fractures, pain and opiate analgesics, on blood testosterone concentrations, is not accounted for. Nevertheless, it is clear that normal testicular function is crucial to maintain optimal bone integrity for men while substantial, sustained androgen deficiency has detrimental effects on bone, lowering bone density and increases fracture risk. Severe androgen deprivation by either surgical orchidectomy or medical (drug-induced) castration, such as required for palliative care of older men with incurable prostate cancer, eliminated the testicular contribution to circulating testosterone levels leading to a profound, near complete decline in circulating testosterone. The rapid decline in gonadal steroids after castration causes an accelerated bone loss and turnover with a marked increase in bone resorption unmatched by a sufficient increase in the coupled bone formation. Bone turnover, as assessed by biochemical markers of bone resorption and formation, are both increased [48– 54] and the net effect is a rapid and sustained bone loss in androgen deficient men. In older men with prostate cancer subjected to therapeutic castration, BMD is predominately reduced at the lumbar spine which decreases by 5–10% within the first year after castration [48–53, 55]. Bone loss is also observed at peripheral skeletal sites, including the hip, although to a lesser extent [50–52, 56–58]. Ultimately, bone loss after castration results in an increased risk of osteoporotic fractures [57, 59–64]. For example, Daniell et al reported that the cumulative incidence of a first osteoporotic fracture is increased more than fivefold in castrated men [57]. Of men surviving at least 5 years after prostate cancer diagnosis, 19.4% of those who underwent castration had a fracture, as compared with 12.6% of those not castrate (P 0.001). Importantly, a recent populationbased database study revealed that there is a significant relation between the number of doses of gonadotropinreleasing hormone analogs (used to induce medical castration) received during the first 12 months after diagnosis and the subsequent risk of fracture [65] (Figure 35.2). For men with prostate cancer who are at high risk for osteoporosis and fractures, clinical management should be based on radiographic and densitometric assessment. Bisphosphonates have emerged as an integral part of the management of bone loss related to castration in men with advanced, incurable prostate cancer [66]. There is, however, no established role for bisphosphonates in men with localized prostate cancer treated with curable intent using short-term medical castration as part of adjuvant, stage-reducing therapy.
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Figure 35.2 Unadjusted fracture-free survival among patients with prostate cancer, according to androgen-deprivation therapy. GnRH denotes gonadotropin-releasing hormone. The number of doses is the number administered within 12 months after diagnosis. (Adapted from Shahinian et al N Engl J Med 2005;352: 154164 [65] with permission).
Men with overt androgen deficiency due to testicular or hypothalamic-pituitary dysfunction have less severe and more variable deficits in testosterone secretion and, consequently, have less marked changes in BMD and bone turnover. Most men with established chronic androgen deficiency have significantly lower bone density than age-matched controls [67–71]. Luisetto et al, however, observed that bone mass was comparable to healthy controls in 32 men with Klinefelter’s syndrome [72], a discrepancy most likely reflecting the wide phenotypic spectrum including variability in testicular function in Klinefelter’s syndrome [73, 74]. Recent European population-based record linkage studies of men with Klinefelter’s syndrome showed not only striking underdiagnosis of Klinefelter’s syndrome, with fewer than 20% diagnosed during life, but also the first evidence that chronic androgen deficiency is associated with an excess of deaths from bone fractures [75, 76]. In contrast to these mostly uniform alterations in BMD, changes in bone turnover, specifically in bone formation, are less consistent. While bone resorption is accelerated in androgen deficient men compared with eugonadal controls [70, 77, 78], bone formation may be either decreased [70, 79, 80] or increased [2, 77, 78] when assessed either by biochemical indices of bone formation or histomorphometric studies. Testosterone replacement therapy for androgen deficiency conversely decreases bone resorption [78, 81–84] and exerts an anabolic effect with increased bone formation [81, 82, 85], although some studies failed to show an increase in bone formation [78, 83, 84]. These inconsistencies are probably due to the inadequate testosterone replacement regimens widely used [86] and heterogeneity of the populations studied and tests used.
CAGn length
Figure 35.3 Body height in relation to CAGn length of the AR genes of Klinefelter patients. Inset: height distribution according to tertiles of X-weighted biallelic CAGn length (short: CAGn, 20.0 (n 27); medium: 20.0 CAGn 23.0 (n 27); long: CAGn, 23.0 (n 23)). Significant differences according to Kruskal-Wallis and post hoc tests. Levels of statistical significance are given as asterisks (* P 0.05; ** P 0.01; ***, P 0.001). (Adapted from Zitzmann et al J Clin Endocrinol Metab 2004;89: 6208-17 [91] with permission from The Endocrine Society).
Effects of Androgen Replacement in Male Hypogonadism Most studies of androgen replacement therapy in androgen deficient men report beneficial effects of increased BMD, although the gain in bone density varies between studies [38, 82–84, 87–90]. This variability is likely to be due, in part, to differences in the adequacy of testosterone replacement regimens [86], especially in the more salient longitudinal studies of the same men before and after treatment using the same dual energy x-ray absorptiometry (DXA) equipment. By contrast, cross-sectional studies introduce additional sources of variability, such as the wide variability in magnitude of testosterone deficiency according to the underlying disorders of gonadal function, as well as to different methods to quantify bone density (DXA, quantitative computed tomography (QCT)). Pharmacogenetic differences between men in the CAG triplet repeat in exon 1 of the AR, the length of which is inversely related to androgen sensitivity, also contributes to the effectiveness of testosterone treatment on bone [91] (Figure 35.3), although the magnitude of these effects appears relatively modest. The most striking increase in BMD is seen during the first year of testosterone replacement therapy and is greatest in those with the lowest initial BMD. Thereafter, bone density is maintained during longterm testosterone administration [88] (Figure 35.4), so long as adequate testosterone dosage is continued [86]. Data from prospective and retrospective studies on the effect of androgen replacement on bone density in androgen deficient men have recently been summarized [2, 92]. These studies provide mostly consistent evidence that sites with
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[78, 81–84] and increases levels of bone formation markers [81, 82, 85] resulting in increased bone mass [83, 97]. However, beneficial effects on body composition, specifically on muscle mass, most likely make some indirect contribution to the increase in BMD based on increased physical activity and/or biophysical shear force stress. Many studies now confirm that testosterone administration increases lean (i.e. muscle) mass [78, 81, 84, 94] and/or muscle strength [81, 85, 98, 99] in a dose-dependent fashion in androgen deficient men, in men with andropause as well as in eugonadal young and older men.
Duration of testosterone therapy (years)
Figure 35.4 Increase in BMD during long-term testosterone substitution therapy up to 16 years in 72 hypogonadal men. Circles indicate hypogonadal patients with first QCT measurement before initiation of testosterone replacement therapy, squares show those patients already receiving testosterone therapy at the first QCT. The dark shaded area indicates the range of high fracture risk, the unshaded area shows the range without significant fracture risk and the light shaded area indicates the intermediate range where fractures may occur. (Adapted from Behre et al J Clin Endocrinol Metab 1997;82:2386–90 [88] with permission from The Endocrine Society).
mostly cancellous bone (e.g. the spine) are more responsive to androgen deficiency and replacement than sites of predominantly cortical bone (e.g. the radius or proximal femur). Furthermore, measurements based on QCT show much greater responsiveness than studies using single or dual photon absorptiometry due to its unique measurement of trabecular bone mass. On the other hand, subcortical bone apposition appears particularly important in men and is responsible for their larger and stronger bone structure [93]. These differences may be in part due to androgen-induced changes in body composition (i.e. reduced fat and increased lean mass) which remain uncorrected in QCT measures of BMD response. Furthermore, the adequacy of testosterone regimen is an important determinant of the efficacy of testosterone replacement therapy [86]. Intramuscular testosterone ester administration, with its supraphysiological peak blood testosterone levels and maintenance of relatively high blood testosterone levels for at least 10 days after injection has more beneficial effects on bone than transdermal [94, 95] or buccal [96] testosterone administration which have difficulty maintaining physiological blood testosterone levels. However, no well-controlled prospective studies comparing the effects of different forms of testosterone on skeletal health are reported. Nor are there any adequately powered randomized controlled trials of testosterone therapy for men with either idiopathic or androgen deficiency related osteoporosis with fractures as a clinical endpoint. The effect of androgen replacement therapy on BMD is largely accounted for by androgen effects on bone turnover. In androgen deficient men, testosterone administration decreases biochemical markers of bone resorption
Partial Androgen Deficiency in Older Men In recent years, the increased life expectancy in developed countries has led to interest in reproductive health of aging men. Among the issue of greatest interest is the possibility that age-related androgen deficiency in older men may be a potentially correctable aspect of healthy aging. As an issue of growing interest to physicians as well as the wider society with interests in healthy aging and burgeoning health care costs [19], the putative somatic consequences of gradually falling testosterone concentrations include changes in bone mass. This has become one rationale for wider use of testosterone treatment of middle-aged and older men with apparent age-related, but no other pathological basis for, androgen deficiency. This has led to a massive increase, nearly 20-fold worldwide over the last decade, in testosterone prescribing. Although there is evidence that chronic androgen deficiency is associated with premature deaths due to fractures [48, 73–76], there remain no well-controlled, prospective studies evaluating whether testosterone administration for agerelated bone loss is safe and effective. Several cross-sectional and longitudinal studies have investigated the association between gonadal steroids, biochemical markers of bone turnover and bone mass in older men [22, 100–103]. One cross-sectional study including men between 23 and 90 years of age, reported inverse correlations between urinary collagen type I cross-linked N-telopeptide (NTX) levels and both ‘bioavailable’ E2 and ‘bioavailable’ testosterone [22]. However, no correlation with total estradiol or testosterone was identified and the biological meaning of such derived steroid measures, which largely reflect age-related changes in SHBG, remains dubious. In contrast, in another study of men over 51 years of age, only ‘bioavailable’ E2 levels correlated negatively with bone turnover but, again, no relationships were observed with total E2 or testosterone or various derived testosterone measures [100]. A third study found a relationship between E2 and bone resorption markers (serum and urinary NTX) but not with indices of bone formation (osteocalcin (OC), bone alkaline phosphatase (BAP)) [102]. Any conclusion about the significance of low levels of blood E2 in men is constrained by the unreliability of direct serum E2 immunoassays on which many are based [23]. Whether the low levels of circulating
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E2 in men are associated with increased bone resorption or this is an artefact of age-related increases in SHBG remains to be clarified. If such increases in bone resorption are associated with bone loss, this indicates that the usual concomitant increase in bone formation is at least partly uncoupled and under-compensated. Older men, especially after the age of 70 years, usually have substantial bone loss and are at increasing risk of osteoporotic fractures. However, the extent to which low levels of testosterone contribute to age-related bone loss in men remains unclear [2]. In analogy to markers of bone turnover, several cross-sectional and longitudinal studies have documented significant correlations between serum levels of ‘bioavailable’ or total E2 and bone density [4, 104] or change in bone mass during follow up [101–103]. In contrast, other studies fail to show consistent associations between ‘bioavailable’ testosterone and BMD or bone loss [22, 105, 106]. A recently published cross-sectional study among men in NHANES III, however, showed that men with lower ‘free’ estradiol and lower ‘free’ testosterone concentrations (calculated, not measured) were more likely to have low BMD [107]. It is unclear whether the main mechanism of estrogen action on bone is via local aromatization of testosterone to estradiol within bone or to systemic estradiol exposure. One possible explanation is that there is a threshold for estrogen action, possibly based on some critical level of blood or local estradiol. All the above-mentioned studies focus on the association between sex hormone levels and bone turnover markers and
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BMD as surrogate markers of bone integrity. However, data on the more direct relationship between blood testosterone and E2 and rates of osteoporotic fractures are limited. A recent study from Sweden reported that ‘free’ testosterone within the normal range was independently associated with prevalent osteoporotic fractures in elderly men [108]. However, this weak relationship explained only 1% of variance and the direction of causality remained unclear. In contrast, a subset analysis from the Rotterdam Study failed to confirm an association between testosterone and fracture risk [109]. Data from the Framingham Study recently indicated a synergistic effect of sex hormones on fracture risk in that men with low serum testosterone and low E2 levels were at increased risk for incident hip fractures. Analyses restricted to either gonadal steroid alone, however, revealed that in older men, serum E2 but not testosterone was associated with hip fracture risk [110]. In these studies [109,110], however, serum testosterone levels were measured using immunoassay-based methods that are unreliable, particularly in the lower concentration range [8]. Based on the prospective Dubbo Osteoporosis Epidemiology Study and using tandem mass spectrometry for gonadal steroid measurement, we recently observed that community-dwelling elderly men with lower serum testosterone levels had increased risk of osteoporotic fracture (Figure 35.5). This effect was independent of established risk factors, such as age and BMD. In contrast there was no significant association between serum E2 levels and fracture in the presence of BMD and age [111].
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Figure 35.5 Proportion of study participants with low-trauma fractures during follow up (time-to-event analysis) according to baseline sex hormone levels, grouped by adjusted baseline serum testosterone levels (low testosterone, 294 ng/dL; intermediate testosterone, 294–559 ng/dL; and high testosterone, 559 ng/dL), P 5 0.01 for the low versus high testosterone group. (Adapted from Meier et al Arch Intern Med 2008;168:47–54 [111], with permission from The American Medical Association).
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TESTOSTERONE TREATMENT EFFECT ON % CHANGE IN L2-L4 BMD
The effects of testosterone treatment on bone in older men remain inconclusive in the absence of adequately powered, sufficiently long-term, randomized placebo-controlled studies to indicate whether testosterone treatment reduces bone fractures in older men [19]. So far, few randomized placebo-controlled studies in healthy men over 50 years have examined the impact of androgen supplementation on bone represented either by bone turnover markers [112–115] and/or bone density [113–116]. All studies treated otherwise healthy, non-osteoporotic men with transdermal testosterone [113, 115], oral testosterone [116] or intramuscular (IM) testosterone injections [112, 114]. Irrespective of baseline entry criterion blood testosterone concentrations (range 10.1–13.7 nmol/L), no study showed consistent changes in bone turnover markers after 3–36 months of treatment. Only in an early small cross-over study by Tenover [112] was urinary excretion of hydroxyproline decreased in testosterone treated men while remaining unchanged in the placebo treated group. The relevance of this isolated finding using a non-specific marker of collagen turnover remains unclear. Three placebo-controlled studies investigating the effect on BMD have differed in outcome: whereas the studies by Snyder et al and Emmelot-Vonk et al showed no benefit of treatment [113, 116], the study by Kenny et al showed that testosterone prevented ongoing age-related bone loss in
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PRETREATMENT TESTOSTERONE CONCENTRATION (ng/dl)
Figure 35.6 The testosterone treatment effect on percent change in BMD during 36 months of testosterone treatment in men over 65 years of age as a function of the pretreatment serum testosterone concentration. The lower the pretreatment serum testosterone concentration the greater the effect of testosterone treatment on BMD. The treatment effect was statistically significant (P 0.01) for pretreatment serum testosterone concentrations of 10–300 ng/dL. The values shown are the mean (SE) changes in BMD during the 36 months of treatment in the testosterone-treated subjects minus those in the placebo-treated subjects (Adapted from Snyder et al J Clin Endocrinol Metab 1999;84:1966–1972 [113], with permission The Endocrine Society).
one of five bone sites [115]. Post-hoc analysis of the larger study by Snyder et al suggested that bone density gains were inversely related to pre-study baseline levels of blood testosterone [113], consistent with the idea that the benefits depend on the degree of underlying androgen deficiency (Figure 35.6). A recent study in which testosterone enantate was administered at a higher dose reported significant increases in BMD at the lumbar spine and the hip after 36 months of treatment [114], however, a reduction in dose for polycythemia was required in 25% of the participating men. In summary, from available well controlled evidence, there appears to be no consistent effect of exogenous testosterone treatment on bone turnover and limited, dose-dependent effect on BMD in older men with low-normal circulating testosterone. Results from placebo-controlled trials including elderly men with consistently lower baseline testosterone levels (i.e. below 8 nmol/L) are needed to unravel the effects of testosterone replacement on bone surrogate markers, such as BMD and bone turnover markers and, ultimately, fracture risk, morbidity and mortality [117]. In the interim, there is no basis for empirical testosterone treatment for men with idiopathic or age-related osteoporosis unless there is concomitant evidence of overt androgen deficiency.
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114. J.K. Amory, N.B. Watts, K.A. Easley, et al., Exogenous testosterone or testosterone with finasteride increases bone mineral density in older men with low serum testosterone, J. Clin. Endocrinol. Metab. 89 (2) (2004) 503–510. 115. A.M. Kenny, K.M. Prestwood, C.A. Gruman, K.M. Marcello, L.G. Raisz, Effects of transdermal testosterone on bone and muscle in older men with low bioavailable testosterone levels., J. Gerontol A. Biol. Sci. Med. Sci. 56 (5) (2001) M266–M272. 116. M.H. Emmelot-Vonk, H.J. Verhaar, H.R. Nakhai Pour, et al., Effect of testosterone supplementation on functional mobility, cognition, and other parameters in older men: a randomized controlled trial, J. Am. Med. Assoc. 299 (1) (2008) 39–52. 117. S. Bhasin, G.R. Cunningham, F.J. Hayes, et al., Testosterone therapy in adult men with androgen deficiency syndromes: an endocrine society clinical practice guideline, J. Clin. Endocrinol. Metab. 91 (6) (2006) 1995–2010.
Chapter
36
Alcohol Use and Bone Health in Men Neil Binkley and Diane Krueger University of Wisconsin, Madison, Wisconsin, USA
Introduction
With the increasing number of older adults worldwide and well-known increase in fragility fracture risk with advancing age, the potential toxic effect(s) of alcohol on bone is of substantial concern. It should be appreciated that cultural and/or personal habits related to drinking alcohol may impact its metabolism in that food in the stomach slows absorption [7]. Thus, it is possible that the weekly consumption of seven units of alcohol could have markedly different physiologic effects if this intake consists of seven glasses of beer on an empty stomach in a relatively small period of time (i.e. at one setting) or of one glass of wine with supper daily. While ‘binge drinking’ is noted in some published works as a special kind of risk, this is not uniformly the case of published reports considering alcohol intake and its long-term outcomes.
Alcohol is consumed by approximately two-thirds of men across the lifespan in the USA and alcohol abuse is widely appreciated as a risk factor for fragility fracture. However, moderate alcohol consumption is associated with higher bone mineral density (BMD) and lower fracture risk. The mechanism(s) of these apparently contradictory observations are not well defined and the issues surrounding alcohol use and bone health are exceedingly complex. This chapter will review the epidemiology of alcohol use/abuse among men, explore the effects of alcohol on musculoskeletal metabolism, bone mineral density, falls and fracture risk.
Alcohol physiology Epidemiology
Ethanol is a non-essential molecule produced by fermentation of grains or fruits [1] and is consumed as a beverage (usually beer, wine or distilled spirits) or added during cooking. Small amounts of ingested ethanol are degraded by alcohol dehydrogenase in the stomach [2] and excreted via the lungs, however, the liver is the primary site of ethanol metabolism. Ethanol is metabolized by alcohol dehydrogenase and the cytochrome P450 enzyme, CYP2E1 [3, 4]. The first metabolic product, acetaldehyde, is a known carcinogen due to its mutagenic effects on DNA [5]. Thus, ethanol has obvious potential toxicity. Individual variability in response to alcohol exists in that genetic predisposition may increase the risk of alcohol abuse. Moreover, with advancing age, older adults appear to be more sensitive to alcohol toxicity [3]. Based on this age-related increase in sensitivity, the US National Institute on Alcohol Abuse and Alcoholism recommends that adults age 65 and over limit their intake to one drink per day. However, the definition of ‘safe’ intake is controversial [6]. Osteoporosis in Men
It is clear that excessive alcohol use leads to addiction and to damage of virtually all body organs [5]. In fact, the World Health Organization reports that alcohol is responsible for over 3% of all deaths worldwide. This is not surprising as is the case with most drugs, dose-dependent toxicity is seen with alcohol. Alcohol is particularly of concern for men in that more males than females consume alcohol and men, on average, consume a greater quantity [8]. Additionally, the type of alcohol ingested differs by sex, with women drinking primarily wine and men consuming primarily beer. These differences may influence outcomes due to variation in alcohol and nutrient content [9]. While alcohol consumption, in general, declines with advancing age [8, 10], alcohol use remains common among older adults. Over 50% of those greater than age 60 currently consume alcohol and approximately 25% of men over age 60 consume one or more drinks daily [11]. 435
Copyright 2009, 2010 Elsevier, Inc. All rights of reproduction in any form reserved.
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In attempting to summarize a diverse literature, a few generalizations seem appropriate. First, there is substantial cultural variation in alcohol consumption among men. Second, men are more likely to be regular drinkers at all ages than are women. Third, alcohol consumption remains high in men until approximately age 75 but declines thereafter [7]. Given this high prevalence of alcohol consumption across the lifespan among men, any potential effects on bone, either positive or negative, could be of substantial importance. High alcohol intakes have widespread adverse physiologic consequences and formal Diagnostic and Statistical Manual (DSM-IV) and International Classification of Diseases (ICD10) criteria exist for the diagnosis of alcohol dependence and alcohol abuse [12]. However, these formal definitions have not been uniformly applied in the published literature and/or in clinical practice. A useful clinical definition of alcohol abuse has been suggested as ‘sufficient alcohol intake to cause physical, psychiatric, or social harm’ [7]. Much of the published work relevant to bone health in men has evaluated alcoholics with very high alcohol intakes, sometimes for many years [13]. However, a substantial body of published data focuses on men with ‘moderate’ intake. Unfortunately, a consensus definition of ‘moderate’ alcohol consumption has not been applied uniformly either in studies or by governmental agencies [1]. For example, moderate daily alcohol intake is defined by the US Department of Agriculture (USDA) as 14 g/day (one drink) in women and 28 g/day (two drinks) in men [1]. However, a recent review defines moderate alcohol consumption as intake of 15–45 grams of ethanol per day (one to three standard drinks) with ‘immoderate’ intake being greater than this [1]. Others suggest that a toxicity threshold exists at 50–60 grams of ethanol daily with daily intakes greater than this being associated with adverse health consequences [1]. To confound further the definition of ‘moderate’ alcohol intake, guidelines differ for various nations [14]. For example, the acceptable daily alcohol intake for men is 20 grams in Sweden, 28 grams in the USA and 39 grams in the Netherlands [14]. Thus, what is ‘moderate’ to one, may be ‘immoderate’ to another. Additionally, it must be appreciated that all studies of alcohol intake are confounded by self-report and by identification of what constitutes one ‘unit’ of alcohol. Though a standard unit of alcohol has been defined as 8 grams of 10 ml of ethyl alcohol [9], it is reasonable that virtually no one actually measures the amount of alcohol they consume and moreover that what constitutes a ‘serving size’ may vary substantially [14]. For perspective, one unit of alcohol is the amount in a 125 ml (4 oz) glass of wine that contains 8% ethanol. However, this may not simply be ‘one glass’ as wine glasses often are capable of containing 250 ml or more. Additionally, the strength of wine has increased over time such that white and red wine often contain 12% and
15% alcohol respectively. As such, a ‘glass’ of red wine with 15% alcohol could easily contain over three units of alcohol [9]. Thus, what is reported as ‘moderate’ alcohol intake could easily differ between individuals and between published reports. Finally, self-report of alcohol intake seems likely to be confounded by individuals reporting less than they actually consumed.
Moderation; is less more? Consumption of alcohol in ‘moderate’ amounts may possibly have beneficial effects. In fact, the lowest all cause and coronary artery disease mortality is seen in those who consume one to two drinks daily. It is not surprising, therefore, that the US Department of Health & Human Services dietary guidelines for Americans states that those who consume alcohol should ‘drink alcoholic beverages in moderation’ [15]. The potential mechanism(s) by which a beneficial effect of moderate alcohol intake could occur are not well understood. One potential mechanism may be via reduction of proinflammatory cytokines in that moderate alcohol intake is associated with lower markers of inflammation [16, 17]. Additionally, the possibility that consumption of alcoholic beverages serves as a source of various nutrients, rather than simply adding ethanol to the diet, must be considered. Moreover, it is possible and, in fact likely, that moderate drinking may have beneficial effects on psychosocial function [18, 19], potentially leading to improved appetite and enhanced dietary intake [20]. Finally, moderate alcohol intake is associated with better reported quality of life and improved survival [21]. Therefore, it is possible that the reported health benefits of moderate alcohol consumption (e.g. bone density, heart disease, etc.) reflect associated, but unmeasured, healthy behaviors and is not directly the result of ethanol consumption [22, 23].
Alcohol impacts on bone and calcium homeostasis Given the complexities of evaluating alcohol use/abuse in humans, it is reasonable to turn to animal studies that have evaluated the effects of alcohol, models that are independent of the various confounding effects inherent in human studies. The rat model has generally been used most widely in evaluating the effects of alcohol on bone. In these studies (as could be expected), the alcohol dose, rat strain and age and duration of alcohol administration all influence the study outcomes. In addition to impairing overall growth, alcohol ingestion inhibits bone formation and thereby bone growth, density and strength in growing male and female rats [24–26]. These reductions persist throughout life [27].
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Moreover, reduced weight bearing further reduces bone formation in adult male rats [28], perhaps implying that inactivity might contribute to osteoporosis development in male alcoholics. Finally, alcohol abuse may impair fracture healing due to impairment of osteoinduction [24]. To summarize, in animals, alcohol inhibits bone formation and reduces bone strength [29]. In humans, the effects of alcohol on bone are complex, multifactorial and dose dependent. Overall, as detailed below, it appears that the primary effect of high-dose alcohol on bone is suppression of osteoblastic activity. However, some studies suggest a component of increased osteoclastic resorption [29]. The inconsistencies reported in the literature likely reflect the complexities associated with human alcohol intake including dose, duration and type of alcohol consumed, concomitant nutritional deficiencies, associated toxins, e.g. smoking, presence or absence of liver disease, age, body weight and other factors. As is the case in rats, human alcohol abuse is associated with reduced osteoblast function both histologically [30] and as measured by circulating markers of bone turnover [31]. For example, circulating osteocalcin concentration is lowered by both acute and chronic alcohol intake [31–35]. The effect of alcohol abuse on bone resorption is variable; some reports finding no effect, while others suggest increased resorption [36]. Effects of alcohol on sex steroids in men is important. Acute and chronic alcohol use reduces testosterone levels in males [37]. Additionally, estrone and estradiol concentrations may be elevated in alcoholic men. Moreover, alcohol may increase estrogen receptor activity and may reduce the rate of estradiol catabolism [14]. To summarize a substantial literature in this regard, alcohol use/abuse is associated with reduced androgen levels and potentially frank hypogonadism in men along with increased levels and sensitivity to estrogens [14]. These varying effects of alcohol on sex steroids may have relevance to skeletal metabolism because of the relationship between hypogonadism in men and osteoporosis. On the other hand, the positive effects of alcohol on estrogen levels and metabolism could be beneficial to the male skeleton [38]. Clearly, overall nutritional deficits may exist in alcoholics with resulting deleterious skeletal results [35]. The nutritional deficits among alcoholics may be due to dietary neglect and/or reduced appetite due to gastritis or ulcer disease. Moreover, chronic pancreatitis and/or liver impairment may be associated with malabsorption of a multitude of nutrients, importantly including calcium and vitamin D. Consistent with this, alcohol use may cause hypocalcemia and hypomagnesemia [13]. Additionally, low vitamin D status is common among those who habitually consume alcohol [13, 35], a not surprising finding given the high prevalence of low vitamin D status worldwide. Moreover, low 1,25 dihydroxyvitamin D concentrations have been reported, potentially reflecting impaired 1-hydroxylase activity
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or alternatively increased degradation via alcohol-induced induction of the cytochrome P450 system. One would expect reduced 1,25 dihydroxyvitamin D status to be associated with calcium malabsorption and parathyroid hormone (PTH) elevation. However, alcohol intake has been reported to increase, decrease or to have no effect on serum PTH concentration. Calcium absorption has not been exhaustively studied in alcoholic men but one report identifies substantially increased calcium absorption in such individuals [32]. This unexpected finding could potentially reflect direct alcohol-induced damage to the intestinal mucosa thereby facilitating enhanced passive, i.e. paracellular, calcium absorption [35]. It is clear from the discussion above, that alcohol could potentially have varied, complex and not well-defined mechanistic impacts upon bone health that likely differs between individuals.
Bone mineral density (BMD) Alcohol abuse has been correlated with low bone mass in multiple studies [25, 33, 34]. Specifically, low bone mass has been demonstrated by both dual energy x-ray absorptiometry (DXA) and bone histomorphometry in male alcoholics [36]. In such individuals, bone histomorphometry finds reduced trabecular thickness, consistent with reduced bone formation. As a note of caution, as is the case for ‘moderation’, it is possible that these associations of low bone mass with alcohol abuse could also reflect confounding factors. In this regard, up to 80% of alcohol-dependent individuals are regular smokers [12]; a habit associated with low BMD and increased fracture risk [39]. Be that as it may, many reports confirm that alcohol abuse adversely affects bone mass. In contrast, recent data find greater alcohol consumption to be associated with higher BMD [40, 41]. For example, in the MrOS study involving almost 6000 men aged 65 and older, greater alcohol intake was associated with higher BMD [42]. In this study, even men with a history of binge drinking or problem drinking had higher BMD than those who did not. Similarly, NHANES data find higher total hip BMD among men who consume alcohol as compared to those who do not [43]. This positive association of greater alcohol intake with higher hip BMD has been quite consistently reported (Figure 36.1) in contrast to low BMD among alcoholic men. Taken together, it seems possible that the reports of low BMD among alcoholic men reflects poor nutritional status, overall poor health and/or other confounders, perhaps with a direct toxic effect of alcohol on bone formation superimposed. Consistent with this concept, some work suggests that the beneficial effects of alcohol on BMD in men may be J- or U-shaped with lower BMD at the highest intakes [45]. Though intermittent consumption of
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Bone mineral density (grams/cm2)
0.850
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7 to 13 14 or more 0.750
0.700
0.650 Total hip
Femoral neck
Figure 36.1 Association of alcohol consumption and bone mineral density. In this study of 1482 adults, total hip and femur neck BMD were progressively higher with greater alcohol consumption. Data adapted from Mukamal et al [44].
large amounts of alcohol (binge drinking) appears to have adverse skeletal consequence in rats, binge drinking did not appear to adversely affect BMD according to the NHANES data. At this time, it has not been determined conclusively whether binge drinking, at least if confined to approximately twice per month, adversely affects BMD [43]. The possibility that specific alcoholic beverages and their composition might have differential effects upon bone requires further evaluation. For example, dietary silicon intake is positively associated with BMD [46] and beer is the major source of dietary silicon intake in men [47]. Thus, it is possible that the silicon in beer could potentially mediate the reported positive effects of high alcohol (beer) intake on BMD in men in the Framingham Offspring study [45]. Similarly, resveratrol, a phytochemical compound that is a constituent of red wine, reduces ovariectomy-induced bone loss in rats [48]. Thus, estrogenic effects of resveratrol have been suggested as a mechanism to prevent bone loss in humans [49]. If true, this component may in part explain the higher BMD observed with increasing wine consumption [14]. In this regard, and confounding the effect of ‘wine’ on bone health, it should be noted that not all wine is the same in that white wine contains fewer potentially bioactive compounds than does red [9]. It is possible, and perhaps likely, that other types of alcoholic beverage would have differing effects due to the presence of nutrients such as silicon or resveratrol. Moreover, this suggests that the contribution of alcoholic beverages to overall nutrition, rather than simply as ethanol sources, must be considered. In essence, the
effects of ‘alcoholic beverages’ on bone health may be due to their contribution as ‘food’. In conclusion, though the association of moderate alcohol intake with higher BMD is becoming increasingly well established, the mechanism(s) underlying this observation remains to be determined [14].
Alcohol, falls and fractures in men Falls are a major problem for older adults [50] causing substantial morbidity and mortality. In fact, falls are the leading cause of injury-related hospitalizations and injury-related mortality for older adults [51], leading to almost 16 000 deaths annually. As chronic, heavy alcohol consumption can cause peripheral neuropathy and skeletal myopathy [52, 53], it is intuitively obvious that alcohol intake and intoxication would be associated with increased falls risk due not only to adverse neurological and muscular function but also to adverse effects on balance and judgment [54, 55]. However, the association between alcohol use and fall risk is surprisingly inconsistent. For example, in the MrOS study, intake of 14 or more drinks per week was not associated with an increased risk for falls [42]. Existing data regarding the relationship between alcohol intake and fracture risk in men are similarly controversial with some reports finding moderate alcohol intake to be protective against fractures, with others finding no association
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l
Enter yes if the patient takes 3 or more units of alcohol daily. A unit of alcohol varies slightly in different countries from 8–10 g of alcohol. This is equivalent to a standard glass of beer (285 ml), a single measure of spirits (30 ml), a medium-sized glass of wine (120 ml). The impact of checking alcohol ‘yes’ or ‘no’ as a clinical risk factor for an osteopenic man at various ages modestly alters the FRAX-calculated 10-year fracture probability as noted in Figure 36.2. In addition to the increased fracture risk noted above, fracture healing is impaired in alcoholics. A higher incidence
7 f
6 10 year hip fracture probability
between alcohol intake and fracture risk and still other studies reporting a higher fracture risk for heavy alcohol users [56]. For example, in the MrOS study, all fractures (not just osteoporosis-related fragility fractures) were reported over a prospective follow up of 3.6 years. Despite the occurrence of approximately 250 non-vertebral fractures, no difference in overall fracture rate based on alcohol intake was found [42]. However, a trend towards lower hip fracture rates among those with higher alcohol intake was observed. Moreover, episodic heavy drinking (binge drinking) was unrelated to non-vertebral fracture risk. Similarly, in the Dubbo study, moderate alcohol intake was associated with lower fracture risk but, after adjustment for BMD, this effect was no longer statistically significant [57]. This suggests that the effect of alcohol to reduce fracture risk might be mediated via effects on BMD as noted above. A recent meta-analysis of existing data, which combined fracture risk for men and women, concluded that individuals who consume 0.5 to 1.0 drinks per day had an estimated 20% lower hip fracture risk than those who abstained, whereas those consuming more than two drinks daily had an approximately 40% increased hip fracture risk [22]. The authors note that studies evaluating hip fracture risk included those with higher alcohol intakes, which may explain the U-shaped relationship of fracture. Increasing hip fracture risk at high alcohol intake was clearly observed in longitudinal Danish studies in which consuming up to 27 drinks weekly was not associated with increased hip fracture risk, whereas men consuming 28–41 drinks were at substantially increased risk and those consuming 10 or more drinks daily were at an over fivefold increased hip fracture risk [58]. Similarly, in the MEDOS study of men from southern Europe, modest alcohol intake was not associated with increased hip fracture risk, whereas alcoholism substantially increased this risk [59]. Overall, the literature confirms that high alcohol intakes are associated with increased fracture risk in men. While the definition of ‘high intake’ is obviously a ‘moving target’ vis à vis definition, a recent report of data from multiple countries concluded that fracture risk is increased when more than two drinks daily are consumed [60]. As such, intake of three or more drinks daily is included in the WHO FRAX calculator, with the clinician being advised to:
Alcohol
5
No alcohol
4 3 2 1 0
55
65 Age
75
Figure 36.2 Effect of alcohol consumption on FRAX-estimated 10-year hip fracture risk. The 10-year hip fracture risks for a hypothetical 190 pound (86.2 kg), 73.5 inch (186.7 cm) white male in the USA with a femur neck T-score of 2.0 are presented for ages 55, 65 and 75 years. Addition of alcohol intake greater than 3 units per day substantially alters the estimated fracture probability as shown such that if a clinician were using the 3% hip fracture risk cutpoint (dashed line) for therapeutic recommendations as recommended by the NOF Guide [61], a different treatment recommendation would likely ensue. Data from www.shef. ac.uk/FRAX.
of delayed union or non-union may be the result of alcohol inhibiting new bone formation at the fracture site [29].
Issues confounding studies of alcohol use From the above, it is clear that the effect of alcohol consumption on skeletal health in men is complex. Many studies have demonstrated diverse beneficial health effects of moderate alcohol consumption to include lower risk of cardiovascular disease, stroke and even overall mortality. It must be emphasized that these studies demonstrate association, which does not necessarily indicate causality. Importantly, the presence of various medical conditions, medication use and acute health events predict a higher likelihood of abstaining from alcohol [62]. Thus, ‘unhealthy’ people appear to be less likely to drink. Given the association of ‘illness’ with increased abstinence from alcohol, it seems almost certain that studies will demonstrate a greater likelihood of alcohol consumption in ‘healthier’ individuals [10]. It is possible that this explains, or at least contributes to, the ‘J-shaped’ or ‘U-shaped’ effect of alcohol consumption observed for various diseases (Figure 36.3) including fracture.
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Relative risk
Conclusion
1
0
None
Low
Moderate
High
Figure 36.3 Conceptualization of the ‘J-shaped’ curve associated with alcohol consumption. Similar ‘J’ or ‘U-shaped’ associations with moderate alcohol intake being associated with lower risk for a variety of diseases [63, 64] (including fractures) [55] and with overall mortality [65]. Whether moderate alcohol intake is causally related to these reduced risks or is somehow indicative of better health or health behaviors remains to be determined.
Thus, it is essential to appreciate that associations noted in observational studies can in fact indicate causality, but also might be the result of chance, bias or unappreciated confounders [66]. Importantly, physiologically reasonable associations observed in observational studies may not be the result of the factor being studied (in this case alcohol consumption) but rather be due to unappreciated behavioral and/ or social factors [67]. This point has previously been demonstrated with antioxidant vitamins which were associated with reduced risk of cardiovascular disease and cancer in observational studies [68–70] but not when randomized controlled trials (RCTs) were conducted [71, 72]. While recognizing that RCTs evaluating the long-term effects of alcohol consumption will be difficult, if not impossible to conduct, it seems prudent to have healthy skepticism about the observations of health benefits from alcohol consumption. Moreover, additional confounders in the study of alcohol include the fact that people do not always drink a single type of alcoholic beverage, that alcohol metabolism is affected by when it is consumed with or without food, how rapidly it is consumed and whether there is daily or intermittent consumption. Additionally, an individual’s genetic background influences alcohol metabolism [4]. Finally, as noted earlier, the definition of what constitutes ‘one drink’, the variable methodology for data collection and the reliance on self-reported intake confounds existing studies. Given this, the advice of Balsa et al seems wise: A number of potential biases inherent in retrospective, self-reported observational studies temper any definitive statements that we can make about alcohol use and its potential health benefits [10].
In conclusion, a plethora of observational studies report a positive association between alcohol intake and BMD in men (and women) at various skeletal sites. Biologically plausible mechanisms exist to account for these findings. Thus, drinking alcohol in ‘moderation’ may well be beneficial to bone health in men, although the mechanism(s) underlying this statement remain to be defined, are likely to be complex and multifactorial and potentially do not reflect consumption of ethanol per se. Moreover, it is possible that different alcoholic beverages, notably beer and wine, may have different effects than other forms. Despite the reported beneficial effect on BMD, excessive intake of alcoholic beverages is clearly detrimental and increases fracture risk. As such, despite the difficulties of defining ‘high’ alcohol intake, including this as a clinical fracture risk factor is appropriate. Perhaps it is reasonable to consider alcohol as a drug with potential toxicities when utilized in high doses, but as a ‘nutrient’ at low doses in association with a well-balanced diet. However, despite the multiple studies relating ‘moderate’ alcohol intake with higher BMD, it is not appropriate to recommend consumption of alcoholic beverages as a way to enhance bone health. It must be appreciated that the relationship between alcohol intake and skeletal health is extraordinarily complex being influenced by a variety of physiologic, nutritional and psychosocial factors. It is therefore not surprising that these relationships remain poorly defined.
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49. R.E. King, J.A. Bomser, D.B. Min, Bioactivity of resveratrol, Comp. Rev. Food Sci. Food Safety 5 (2006) 65–70. 50. M.E. Tinetti, M. Speechley, S.F. Giner, Risk factors for falls among elderly persons living in the community, N. Engl. J. Med. 319 (1988) 1701–1707. 51. Anonymous. Centers for Disease Control and Prevention, National Center for Injury Prevention and Control. Web-based Injury Statistics Query and Reporting System (WISQARS). 2006. 52. J. Fernandez-Sola, J.M. Nicolas, F. Fatjo, et al., Evidence of apoptosis in chronic alcoholic skeletal myopathy, Hum. Pathol. 34 (2003) 1247–1252. 53. V.R. Preedy, J.D. Adachi, Y. Ueno, et al., Alcoholic skeletal muscle myopathy: Definitions, features, contribution of neuropathy, impact and diagnosis, Eur. J. Neurol. 8 (2001) 677–687. 54. B. Resnick, P. Junlapeeya, Falls in a community of older adults: findings and implications for practice, Appl. Nurs. Res. 17 (2004) 81–91. 55. K.J. Mukamal, M.A. Mittleman, W.T. Longstreth, et al., Selfreported alcohol consumption and falls in older adults: crosssectional and longitudinal analyses of the cardiovascular health study, J. Am. Geriatr. Soc. 52 (2004) 1174–1179. 56. D.T. Felson, D.P. Kiel, J.J. Anderson, et al., Alcohol consumption and hip fractures: the Framingham study, Am. J. Epidemiol. 128 (1988) 102–110. 57. T.V. Nguyen, J.A. Eisman, P.J. Kelly, et al., Risk factors for osteoporotic fractures in elderly men, Am. J. Epidemiol. 144 (1996) 255–263. 58. S. Hoidrup, M. Gronbaek, A. Gottschau, et al., Alcohol intake, beverage preference and risk of hip fracture in men and women, Am. J. Epidemiol. 149 (1999) 993–1001. 59. J. Kanis, O. Johnell, B. Gullberg, et al., Risk factors for hip fracture in men from southern Europe: the MEDOS study, Osteoporos. Int. 9 (1999) 45–54. 60. J. Kanis, H. Johansson, O. Johnell, et al., Alcohol intake as a risk factor for fracture, Osteoporos. Int. 16 (2005) 737–742.
61. Anonymous, Clinician’s guide to prevention and treatment of osteoporosis, National Osteoporosis Foundation, Washington, DC, 2008. 62. R.H. Moos, P.L. Brennan, K.K. Schutte, et al., Older adults’ health and changes in late-life drinking patterns, Aging Mental Hlth. 9 (2005) 49–59. 63. A.A. de Lorimier, Alcohol, wine and health, Am. J. Surg. 180 (2000) 357–361. 64. D.M. Goldberg, G.J. Soleas, M. Levesque, Moderate alcohol consumption: the gentle face of Janus, Clin. Biochem. 32 (1999) 505–518. 65. R. Doll, R. Peto, J. Boreham, et al., Mortality in relation to alcohol consumption: a prospective study among male British doctors, Int. J. Epidemiol. 34 (2005) 199–204. 66. P. Jepsen, S.P. Johnsen, M.W. Gillman, et al., Interpretation of observational studies, Heart 90 (2009) 956–960. 67. D.A. Lawlor, G.D. Smith, K.R. Bruckdorfer, et al., Those confounded vitamins: what can we learn from the differences between observational versus randomised trial evidence?, Lancet 363 (2004) 1724–1727. 68. L.H. Kushi, A.R. Folsom, R.J. Prineas, et al., Dietary antioxidant vitamins and death from coronary heart disease in postmenopausal women, N. Engl. J. Med. 334 (1996) 1156–1162. 69. M.J. Stampfer, C.H. Hennekens, J.E. Manson, et al., Vitamin E consumption and the risk of coronary disease in women, N. Engl. J. Med. 328 (1993) 1444–1449. 70. E.B. Rimm, M.J. Stampfer, A. Ascherio, et al., Vitamin E consumption and the risk of coronary heart disease in men, N. Engl. J. Med. 328 (1993) 1450–1456. 71. G.S. Omenn, G.E. Goodman, M.D. Thornquist, et al., Effects of a combination of beta carotene and vitamin A on lung cancer and cardiovascular disease, N. Engl. J. Med. 334 (1996) 1150–1155. 72. C.H. Hennekens, J.E. Buring, J.E. Manson, et al., Lack of effect of long-term supplementation with beta carotene on the incidence of malignant neoplasms and cardiovascular disease, N. Engl. J. Med. 334 (1996) 1145–1149.
Chapter
37
Transplantation Osteoporosis Emily M. Stein1, Juliet Compston2 and Elizabeth Shane1 1
Columbia University College of Physicians & Surgeons, New York, NY, USA University of Cambridge School of Clinical Medicine, Cambridge, UK
2
Introduction
Skeletal effects of immunosuppressive drugs
The introduction of cyclosporine to transplantation immunology in the early 1980s resulted in marked improvement in short-term graft and patient survival and ushered in a new era for patients with end-stage renal, hepatic, cardiac, pulmonary and hematopoietic disease. However, with increasing survival of patients after transplantation, adverse skeletal effects, particularly reduced bone mass and fragility fractures, have been documented. The pathogenesis of osteoporosis following transplantation is multifactorial and includes pre-transplantation bone disease, immunosuppressive therapy, vitamin D insufficiency, hypogonadism, reduced physical activity and malnutrition (Figure 37.1) [1–4]. This review, adapted from our recent publication [5], summarizes current knowledge of post-transplantation osteoporosis. Most of the available studies have included both men and women and few data specific to men have been reported.
Glucocorticoids
Pre-transplant bone disease Hypogonadism Malnutrition
Glucocorticoids Glucocorticoids, an integral component of most transplant immunosuppression regimens, have well documented adverse effects on bone. Prednisone or methylprednisolone may be prescribed in high doses (50–100 mg of prednisone or its equivalent daily) immediately after transplantation and during episodes of severe rejection, with gradual reduction over weeks to months. Total exposure varies with the organ transplanted, the number and management of rejection episodes and the practice of individual transplantation programs. The mechanisms by which glucocorticoids increase bone loss and fracture risk are discussed in several recent reviews [6–8]. In recent years, there has been a trend toward more rapid lowering of glucocorticoid doses after transplantation or
Cyclosporine A or Tacrolimus Vitamin D deficiency
Bone formation and bone resorption
Renal Insufficiency 2° hyperparathyroidism Reduced physical activity
Bone loss and fracture
Figure 37.1 Pathogenesis of transplantation osteoporosis. (Adapted from Compston JE. Osteoporosis after liver transplantation. Liver Transpl 2003;9:321–30). Osteoporosis in Men
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rejection episodes and an increase in the use of alternative drugs to treat rejection. In more recently transplanted patients who have received lower doses of steroids, significant bone loss has been reported in some, but not all, studies and, where present, may be less rapid than previously documented [9–12]. Furthermore, early withdrawal of glucocorticoids after transplantation is associated with significantly less bone loss than more prolonged regimens [13, 14]. Whether the recent trends towards reduction in glucocorticoid dose and duration have had a specific impact on fracture risk is difficult to determine because of the other changes that have occurred concurrently in the management of patients undergoing organ transplantation.
Cyclosporines Cyclosporine (CsA) is a small fungal cyclic peptide. Its activity depends upon the formation of a heterodimer consisting of cyclosporine and its cytoplasmic receptor, cyclophilin. This cyclosporine–cyclophilin heterodimer then binds to calcineurin [15]. CsA and, similarly, tacrolimus, inhibits the phosphatase activity of calcineurin through interaction with distinct domains on the calcineurin subunit. Animal studies suggest that CsA has effects on bone and mineral metabolism that may contribute to bone loss after organ transplantation [16]. Studies examining the effects of CsA on the human skeleton have yielded conflicting results. Several have shown that kidney transplant patients receiving cyclosporine in a steroid-free regimen did not lose bone [17–19]. In contrast, in a small study of kidney transplant recipients, no difference in bone loss was detected between those who received CsA monotherapy and those who received azathioprine and prednisolone [20] and, in a recent prospective study, cumulative CsA dose was associated with bone loss in the 2 years following transplant, independent of the effect of steroids [21].
Tacrolimus (FK506) FK506 is a macrolide that binds to an immunophilin FK binding protein and blocks T-cell activation in a manner similar to CsA. FK506 has been shown to cause bone loss in the rat model comparable to that observed with CsA [22] and accompanied by similar biochemical and histomorphometric alterations. In humans, rapid bone loss has been documented after both cardiac [23] and liver transplantation [24], when FK506 is used for immunosuppression. However, other studies suggest that FK506 may cause less bone loss than CsA in humans [25, 26], likely because lower doses of glucocorticoids are required for immunosuppression.
Sirolimus (Rapamycin) Rapamycin is a macrocyclic lactone. Although it is structurally similar to FK506 and binds to the same binding
protein, the mechanism by which rapamycin induces immunosuppression is distinct from both FK506 and CsA. There is some evidence that rapamycin may have bone sparing effects in rats but its skeletal effects in humans have not been defined.
Azathioprine, Mycophenolate Mofetil and Other Drugs In the past, azathioprine was frequently used in combination with prednisone and CsA or FK506 to prevent organ rejection. However, it has largely been supplanted by myco phenolate mofetil, which does not have deleterious effects on bone in the rat [27]. The skeletal effects of other immunosuppressant agents, such as mizoribine, deoxyspergualin, brequinar sodium, liflunomide and azaspirane, are unclear.
Effect of transplantation on bone and mineral metabolism Kidney and Kidney – Pancreas Transplantation Skeletal status before transplantation In patients with severe chronic kidney disease (CKD) or end-stage kidney disease (ESKD), disturbances in calcium and phosphate metabolism, decreased calcitriol synthesis, increased synthesis and secretion of parathyroid hormone (PTH), metabolic acidosis and defective bone mineralization result in the complex form of bone disease known as renal osteodystrophy [28]. Renal osteodystrophy is almost universal in patients who undergo kidney transplantation and may be manifest as high bone turnover, due to hyperparathyroidism with or without osteitis fibrosa, low turnover or adynamic bone disease, osteomalacia or ‘mixed’ renal osteodystrophy, a combination of one or more of the aforementioned lesions. Low bone mineral density, assessed by dual energy x-ray absorptiometry (DXA), is often present and the risk of fragility fracture is increased [29, 30]. Risk factors for low bone mineral density and fractures include female gender, Caucasian race, hyperparathyroidism, adynamic bone disease, secondary amenorrhea, type I diabetes, older age, duration of dialysis, peripheral vascular disease, prior kidney transplant and diabetic nephropathy [31]. Bone loss and fracture rate after kidney transplantation (Table 37.1) Low bone mineral density (BMD) has been reported in several cross-sectional studies of patients who have undergone kidney transplantation [2, 3] and prospective studies have documented high rates of bone loss posttransplantation, particularly in the first 6–18 months [32, 33]. In a recent study of male renal transplant recipients, only 17% had normal BMD, 30% having osteoporosis at the hip or
C h a p t e r 3 7 Transplantation Osteoporosis l
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Table 37.1 Osteoporosis, fractures and bone loss after solid organ and bone marrow transplantation Type of transplant
Bone loss: first post-transplant year
Prevalence after transplantation Osteoporosis*
Fractures
Kidney
11–56%
Heart
25–50%
Vertebral: 3–29% Peripheral: 11–22% Vertebral: 22–35%
Liver
30–46%
Vertebral: 29–47%
Lung
57–73%
42%
Bone marrow
4–15%
5%
**
Spine: 4–9% Hip: 8% Spine: 2.5–8% Hip: 6–11% Spine: 0–24% Hip: 2–4% Spine: 1–5% Hip: 2–5% Spine: 2–9% Hip: 6–11%
Fracture incidence
Vertebral: 3–10% Peripheral: 10–50% 10–36% Vertebral: 24–65% 18–37% 1–16%
*
Accepted definitions included BMD (by dual x-ray absorptiometry) of the spine and/or hip with Z-score 2 or T-score 2.5. Definition of osteoporosis also included BMD of predominantly cortical sites such as the femoral shaft or proximal radius that are adversely affected by excessive PTH secretion. Adapted from Cohen and Shane [2]
**
lumbar spine and 41% if the distal radius site was included. Bone resorption markers were elevated in 48% [34]. Fractures are common after renal transplantation and affect appendicular sites (feet, ankles, long bones, hips) more commonly than axial sites (spine, ribs) [34]. Non-vertebral fractures are fivefold more common in males aged 25–64, and 18-fold and 34-fold more common in females aged 25–44 and 45–64, respectively, who have had a renal transplant than in the normal population [35]. Vertebral fractures have been reported in 3–10% of non-diabetic patients after renal transplantation and, in one study, the risk of hip fracture was increased by 34% in patients who underwent kidney transplant compared to those who remained on dialysis [36]. Fractures are particularly common in patients who receive kidney or kidney–pancreas transplants for diabetic nephropathy [37]. Before transplantation, hyperparathyroidism is the most common lesion on bone biopsy. However, by 6 months after transplantation, glucocorticoid effects predominate, with osteoblast dysfunction and decreased mineral apposition rate [32]. In long-term kidney transplant recipients, bone biopsy results are more heterogeneous and include osteoporosis, osteomalacia and osteitis fibrosa. Mineralization defects are common [38]. Mineral metabolism and bone turnover after kidney transplantation
PTH levels, usually elevated before transplantation, frequently remain high for some time after transplantation and may never completely normalize. Hypercalcemia and hypophosphatemia, related to persistent parathyroid hyperplasia and elevated PTH levels, occur commonly during the first few months. Persistent elevations in fibroblast growth factor-23 (FGF-23) after transplant may be related to
post-transplant hypophosphatemia. In most patients, these biochemical abnormalities are mild and resolve within the first year although, in long-term transplant recipients, persistent elevations in PTH may be associated with reduced hip BMD [39].
Cardiac Transplantation Skeletal status before transplantation Risk factors common in patients with end-stage cardiac failure that may predispose to bone loss before transplantation include exposure to tobacco, alcohol and loop diuretics, physical inactivity, hypogonadism and anorexia, which may contribute to dietary calcium deficiency. Hepatic congestion and prerenal azotemia may also affect mineral metabolism, causing mild secondary hyperparathyroidism. An increased prevalence of osteoporosis has been reported in some studies [40]. Bone loss and fracture rate after heart transplantation (see Table 37.1) Osteoporosis and fractures constitute a major cause of morbidity after cardiac transplantation. In cross-sectional studies, the prevalence of vertebral fractures in cardiac transplant recipients ranges between 18 and 50% and moderate to severe bone loss is present in a substantial proportion of subjects at both lumbar spine and femoral neck [40]. Prospective longitudinal studies have documented rates of bone loss ranging from 2.5 to 11%, predominantly during the first 3–12 months after transplantation [40–42]. While bone loss at the lumbar spine slows or stops after the first 6 months, femoral neck bone loss continues during the second half of the first year after transplantation [11, 42]; thereafter, the rate of bone loss slows or stops in the majority
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of patients with some recovery at the lumbar spine noted during the third year of observation [42]. Bone loss also slows at the hip after the first year, however, in contrast to the spine, there has been no significant recovery by the fourth post-transplant year. The results of a recent study suggest that there may be less bone loss than suggested in literature from the 1980s and early 1990s [11]. Fragility fractures are most common during the phase of rapid bone loss that characterizes the first post-transplant year. In a prospective observational longitudinal study, 36% of patients (54% of the women and 29% of the men) suffered one or more fractures of the vertebrae, ribs and hip in the first year despite daily supplementation with calcium (1000 mg) and vitamin D (400 IU) [43]. It was not possible to predict who would fracture either on the basis of pretransplant BMD or any other demographic or biochemical parameter [43]. Two European studies of cardiac transplant recipients reported similar fracture incidence with approximately 30–33% sustaining vertebral fractures during the first 3 years [44]. The risk of a vertebral fracture was higher in those patients who had lumbar spine T-scores below 1.0 (hazard ratio 3.1) [44]. However, in a more recent interventional study, the incidence of vertebral fractures during the first post-transplant year in patients who received only calcium and vitamin D was only 14% [11]. Similarly, in a prospective study of untreated patients only 12% had fractures [45], suggesting fracture rates may be lower than in the past. Mineral metabolism and bone turnover after cardiac transplantation
Biochemical changes after cardiac transplantation include sustained increases in serum creatinine [42] and decreases in 1,25 dihydroxyvitamin D concentrations. Serum testosterone concentrations decrease in men and may recover by the sixth post-transplant month [42, 46]. In a recent study, testosterone levels were lowest in the first month following transplant and reflected suppression of the hypothalamic pituitary gonadal axis by prednisone [47]. Serum osteocalcin falls precipitously and there is a sharp increase in markers of bone resorption [42, 46]. This biochemical pattern coincides with the period of most rapid bone loss and highest fracture incidence and suggests that the early post-transplant period is associated with uncoupling of formation from resorption with restitution of coupling when glucocorticoid doses are lowered. High bone turnover may also occur later in the post-transplant course, possibly due to cyclosporine-induced renal impairment.
Liver Transplantation Skeletal status before transplantation Patients with liver failure have multiple risk factors that may predispose to low bone mineral density before
transplantation and fracture after transplantation. Many patients with end-stage liver disease who are listed for liver transplantation have prevalent osteoporosis, as evidenced by low BMD and fragility fractures [48–50]. In a recent study of 360 liver transplant candidates, 38% had osteoporosis and 39% had osteopenia [51]. Bone loss and fracture after liver transplantation (see Table 37.1) Osteoporosis is also common after liver transplantation [50]. Reported rates of bone loss and fracture vary considerably after liver transplantation, but were often extremely high, particularly in earlier studies [52]. Bone loss appears to stop after 3–6 months with gradual improvement by the second and third post-transplant years. Although some investigators have reported improvement in BMD in longterm liver transplant recipients, this finding has not been uniform. More recent studies have found smaller rates of bone loss, or even absence of bone loss. Ninkovic et al found only a 2.3% loss at the femoral neck, with preservation of lumbar spine BMD one year after liver transplant [10] while Floreani et al found increases in BMD at one year [53]. Guichelaar reported higher rates of spinal bone loss after transplantation in patients with primary sclerosing cholangitis, current smokers, younger age, higher baseline BMD, shorter duration of liver disease and ongoing cholestasis [51]. Fracture incidence is highest in the first year and ranges from 24 to 65%, although fracture rates appear to be considerably lower in more recent studies [10, 50]. Glucocorticoid exposure and markers of bone turnover do not reliably predict bone loss or fracture risk. Older age and pre-transplant BMD at the femoral neck and lumbar spine were predictive of post-transplant fractures in recent prospective studies [10, 54]. Vertebral fractures prior to transplant have been shown to predict post-transplant vertebral fractures [44, 55]. In a recent study of patients who survived more than 15 years after liver transplantation, 49% had osteoporosis and 30% had sustained vertebral fractures [56]. Mineral metabolism and bone turnover after liver transplantation
Studies of calciotropic hormone levels and bone turnover markers after liver transplantation are limited. Increases in serum PTH levels during the first 3–6 months after transplantation have been reported in some, but not all, studies [50]. Measurement of markers of bone turnover has also produced conflicting results. Histomorphometric data demonstrate a low turnover state pre-transplantation, with a significant increase in remodeling rate 3 months posttransplantation, indicating that increased bone turnover is the predominant mechanism of bone loss in the early posttransplantation period [57].
C h a p t e r 3 7 Transplantation Osteoporosis l
Lung Transplantation Skeletal status before lung transplantation Hypoxemia, tobacco use and glucocorticoid therapy are frequent characteristics of candidates for lung transplantation and may contribute to the pre-transplant bone loss and fractures that are particularly common in these patients [58]. Cystic fibrosis (CF) is also associated with osteoporosis and fractures due to pancreatic insufficiency, inflammation, vitamin D deficiency and calcium malabsorption and hypogonadism [59, 60]. Bone loss and fracture rate after lung transplantation (see Table 37.1) Few studies have prospectively evaluated patients after lung transplantation. However, existing data indicate increased rates of bone loss and a high prevalence of fractures, particularly at the spine [61, 62]. Risk factors for fracture and bone loss include female gender, low pre-transplant lumbar spine BMD, pre-transplant glucocorticoid therapy and higher bone turnover after transplantation. Bone turnover markers are elevated following lung transplant.
Bone Marrow Transplantation (BMT) BMT is performed with increasing frequency and is preceded by myeloablative therapy (alkylating agents and/or total body irradiation), commonly leading to profound and often permanent hypogonadism. The pathogenesis of osteoporosis after allogeneic BMT is complex and includes the effects of treatment and effects on the stromal cell compartment of the bone marrow. Low BMD has been reported in cross-sectional studies of BMT recipients and prospective studies also indicate increased rates of bone loss, particularly after allogeneic BMT [63]. There appears to be little bone loss after the first year, although the significant bone loss that occurs in the femoral neck does not appear to be regained [64]. Bone turnover markers are consistent with the pattern of decreased formation and increased resorption observed in other forms of transplantation during the first 3 months.
Evaluation and management of candidates for transplantation Evaluation (Table 37.2) All patients undergoing transplantation should have a full assessment of bone health prior to transplantation so that potentially treatable abnormalities of bone and mineral metabolism may be addressed and the skeletal condition of the patient optimized before transplantation. Risk factors for osteoporosis should be assessed and, where possible,
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Table 37.2 Skeletal evaluation of the candidate for organ transplantation In all candidates: Assess risk factors for osteoporosis, including menstrual history, history of low-trauma fractures Measure bone density (BMD) of spine and hip by DXA Obtain thoracic and lumbar spine radiographs or lateral DXA images If BMD testing reveals osteoporosis or if there are prevalent vertebral or non-vertebral fractures: Serum electrolytes, blood urea nitrogen (BUN), creatinine, calcium, phosphate, alkaline phosphatase, parathyroid hormone, 25-hydyroxyvitamin D, thyroid function tests, liver function tests (see text) In men, serum total and/or testosterone, FSH and LH Urine for calcium and creatinine
modified. Risk factors for falling (poor vision, hearing, balance and muscle strength, use of psychotropic drugs) should also be evaluated. BMD of the spine and hip should be measured in all patients before transplantation, using dual X-ray absorptiometry (DXA). Radiographs of the thoracic and lumbar spine are also important since the risk of future fracture is greater in patients with prevalent vertebral fractures; alternatively vertebral morphometry can be examined on lateral images obtained by DXA. If the pre-transplant BMD is low, a thorough biochemical evaluation should include a chemistry panel (serum electrolytes, creatinine, calcium, phosphorus, alkaline phosphatase), thyroid function tests, liver function tests, intact PTH and serum 25-OHD. In men, total and free testosterone, follicle stimulating hormone (FSH) and luteinizing hormone (LH) concentrations should be measured. Markers of bone turnover can also be measured, although their value in aiding management is debatable. Where indicated, rehabilitation therapy should be prescribed as tolerated to maximize conditioning and physical fitness. All transplant candidates should receive the recommended daily allowance (RDA) of vitamin D (400–800 IU), or as necessary, to maintain the serum 25-OHD level above 30 ng/ml (80 nmol/mL) and elemental calcium (1000– 1500 mg, depending on dietary intake and menopausal status). Calcium citrate is preferred as many of these patients take proton pump inhibitors before or after transplantation, which can reduce intestinal calcium absorption. Clinically hypogonadal men should be offered testosterone replacement. Generally accepted guidelines for gonadal hormone replacement should apply to these patients. Patients with low BMD and/or fracture before cardiac, liver, lung or bone marrow transplantation should be treated according to established clinical guidelines for women and men at high risk of osteoporotic fracture. In most
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cases, the first line option will be bisphosphonate therapy. Patients with renal osteodystrophy should be managed in accordance with the accepted clinical guidelines for this condition. After transplantation, routine monitoring of serum and urine indices of mineral metabolism is generally not indicated, except in patients with renal bone disease. Measurement of BMD should be performed at 6–12-month intervals for the first 2 years and at appropriate intervals thereafter depending on the individual clinical circumstances. Bone biopsy may be necessary in kidney transplant recipients to exclude adynamic bone disease before commencing bisphosphonate therapy.
Table 37.3 Primary prevention of bone loss in transplant recipients Measure BMD before or immediately after transplantation Consider pharmacologic therapy in all patients with low bone mass (T score between 1.0 and 2.5) or osteoporosis (T score 2.5) Use the lowest dose of glucocorticoids possible Consider alternative therapies for rejection Calcium intake of 1500 mg/d both before and after transplantation Vitamin D intake of 400–1000 IU, or as needed to maintain serum 25-OHD concentrations above 30 ng/ml (80 nmol/ml) Physical rehabilitation program both before and after transplantation Replace gonadal steroids (in clinically hypogonadal men and amenorrhoeic, premenopausal women) Begin antiresorptive therapy, preferably a bisphosphonate, before transplantation in patients with antecedent osteoporosis or low bone mass Begin antiresorptive therapy, preferably a bisphosphonate, immediately after transplantation in patients with normal or low bone mass and continue for at least the first year
l l
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Prevention of transplantation osteoporosis (Table 37.3)
l
The major principles, which have been demonstrated consistently after kidney, liver, heart, lung, and bone marrow transplantation, and that should guide therapy of transplantation osteoporosis are as follows: rates of bone loss are most rapid immediately after transplantation fractures also occur very early after transplantation, sometimes within only a few weeks of grafting fragility fractures develop both in patients with low and those with normal pre-transplant BMD therefore, preventive strategies should be instituted immediately after transplantation both in patients with normal pre-transplant BMD and those with low BMD who have not been treated previously the long-term transplant recipient with established osteoporosis and/or fractures should not be neglected.
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There are several prospective controlled randomized studies for prevention and treatment of transplantation osteoporosis in the literature, although the quality of these studies varies. The recommendations provided herein are also based upon experience with glucocorticoid-induced osteoporosis. Available therapies of transplantation osteoporosis include antiresorptive drugs (bisphosphonates and calcitonin), as well as analogs of vitamin D and gonadal hormone replacement. Since resorption markers increase after transplantation and there is an increase in remodeling rate, attempts to prevent post-transplantation bone loss and, hopefully, fractures by inhibition of bone resorption provide a logical approach.
Bisphosphonates Bisphosphonates act by inhibiting osteoclastic bone resorption. They are approved for the treatment of osteoporosis in postmenopausal women and, in the case of alendronate
and risedronate, in men. Alendronate, risedronate and, in Europe, etidronate, are also approved for the management of glucocorticoid-induced bone loss in women and men. Several studies suggest that intravenous bisphosphonates can prevent bone loss after transplantation. Intravenous pamidronate administered in repeated doses has been shown to prevent bone loss at the lumbar spine and femoral neck in kidney [65, 66], heart [67, 68], liver [69] and lung [70, 71] transplant recipients. In two large prospective studies of patients after allogeneic BMT, intravenous pamidronate prevented lumbar spine bone loss and reduced proximal femoral bone loss [72, 73]. Some bone loss at the proximal femur still occurred, however, despite doses of up to 90 mg one study [73]. Recent randomized trials with the more potent intravenous bisphosphonates, zoledronic acid and ibandronate, have also shown significant protective effects on BMD at 6 and 12 months in recipients of liver [74, 75] and kidney [76, 77] transplants. Intravenous zoledronic acid (4 mg), given 12 months after BMT, has been shown to prevent spinal and femoral bone loss [78]. Clinical trials with oral bisphosphonates, including alendronate, risedronate and clodronate, have also shown beneficial effects on BMD. In terms of primary prevention of bone loss immediately after transplantation, several studies have compared alendronate with calcitriol. A randomized trial comparing alendronate (10 mg daily) with calcitriol (0.25 g twice daily) treatment starting immediately after cardiac transplant found that both regimens prevented bone loss at the lumbar spine and hip one year after transplant, compared with a reference group receiving only calcium and vitamin D [11]. Although alendronate and calcitriol were discontinued during the second year after cardiac transplant,
C h a p t e r 3 7 Transplantation Osteoporosis l
BMD remained stable. Several recent trials found improvements in lumbar spine BMD in patients treated with alendronate or risedronate following kidney transplant [79–81] or liver transplant [82]. At present, bisphosphonates constitute the most promising approach to the prevention of transplantation osteoporosis. As with other forms of therapy, many issues remain to be resolved. These include whether or not they actually prevent fractures, since most studies have been under-powered to address this important issue, the optimal drug and route of administration, whether continuous or intermittent (cyclical) therapy should be used, at what level of renal impairment these drugs should be avoided, whether they are safe in renal transplant recipients with adynamic bone disease and whether they are beneficial in the setting of pediatric transplantation.
Vitamin D and Analogs Since most of the observational studies of bone loss after organ transplantation have included at least 400 IU of parent vitamin D in the post-transplant regimen, it is clear that the RDA for vitamin D is not sufficient to prevent transplantation osteoporosis. In two recent studies, parent vitamin D, in doses of 800 IU daily [83] or 25 000 IU monthly [12] also did not prevent bone loss after kidney transplantation. Active forms of vitamin D may be more effective. Calcidiol (25-OHD) prevented bone loss and increased lumbar spine BMD after cardiac transplantation [84] and alfacalcidiol (1--OHD) prevented or attenuated bone loss at the lumbar spine and femoral neck when given immediately after kidney transplantation [85]. Sambrook et al reported that calcitriol (0.5–0.75 mg/d) prevented spine and hip bone loss during the first 6 months after heart or lung transplantation and was as effective as cyclic etidronate [86]. Calcitriol given during the first year after kidney transplantation was associated with an increase in lumbar spine, femoral neck and forearm BMD [21]. In a stratified, placebo-controlled, randomized study, heart and lung transplant recipients received calcitriol or placebo for 12 or 24 months after transplantation [87]. While lumbar spine bone loss was similar between groups, femoral neck bone loss at 24 months was reduced only in the group that received calcitriol for the entire period. In contrast, studies of long-term kidney [88] and heart transplant patients [89] have failed to demonstrate any benefit of calcitriol. Hypercalcemia and hypercalciuria are the major side effects of therapy of these agents and regular urinary and serum monitoring is required. If hypercalcemia occurs, it must be recognized and reversed promptly because of the adverse effects on renal function and the life-threatening potential of a severely elevated serum calcium concentration. Supplemental calcium and any vitamin D preparations should be discontinued until the calcium normalizes. Treatment may subsequently be recommenced at a lower
449
dose. Vitamin D analogs are generally regarded as a second line option in the management of transplantation osteoporosis, although calcium and vitamin D supplements should be used as an adjunct to bisphosphonate therapy.
Calcitonin Although both injectable and inhaled calcitonin have been used successfully to treat glucocorticoid-induced bone loss, calcitonin has not consistently been shown to have beneficial skeletal effects after transplantation, with most studies showing no benefit. In summary, calcitonin is relatively ineffective in preventing bone loss after transplantation and we would not recommend its use.
Testosterone Approximately 25% of men evaluated 1–2 years after transplantation have biochemical evidence of hypogonadism and men with low serum testosterone concentrations have been shown to lose bone more rapidly after cardiac transplantation [42, 46]. Fahrleitner et al reported that hypogonadal men treated with intravenous ibandronate had improved BMD at one year if they were treated with testosterone compared with those who were not replaced [90]. However, testosterone replacement should be reserved for men with clinical as well as biochemical evidence of hypogonadism.
Summary and conclusions In recent years, there has been significant progress in elucidating the natural history and pathogenesis of transplantation osteoporosis. It is now clear that a substantial proportion of candidates for solid organ and bone marrow transplantation already have osteoporosis. Prospective longitudinal studies have provided definitive evidence of rapid bone loss and a high incidence of fragility fractures, particularly during the first post-transplant year. Vertebral fractures occur both in patients with low and those with normal pre-transplant BMD, so that it is difficult to predict fracture risk in the individual patient. Early post-transplantation bone loss (before 6 months) is associated with biochemical evidence of uncoupled bone turnover, with increases in markers of resorption and decreases in markers of formation. Later in the post-transplantation course (after 6 months), concomitant with tapering of glucocorticoid doses, bone formation recovers and the biochemical pattern is more typical of a high turnover osteoporosis. More recent studies suggest that rates of bone loss and fracture are lower than they were before 1995. However, the rates of bone loss and fracture following transplantation remain unacceptably high. Bisphosphonates are the most consistently effective agents for the prevention and treatment of bone loss
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in organ transplant recipients. Patients should be assessed before transplantation and receive treatment for prevalent osteoporosis, if present. Primary prevention therapy should be initiated immediately after transplantation, as the majority of bone loss occurs in the first few months after grafting. Long-term transplant recipients should be monitored and treated for bone disease as well. With proper vigilance, early diagnosis and treatment, transplant osteoporosis is a preventable disease.
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79.
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Chapter
38
Management of Fractures in Men with Impaired Renal Function Paul D. Miller University of Colorado Health Sciences Center, Colorado Center for Bone Research, Lakewood, Colorado, USA
Introduction
any or all of which can impact bone strength [13, 15–19]. In addition, the pharmacokinetics (PK) of bisphosphonates are affected by altered renal function. Bisphosphonates are both filtered by the glomerulus as well as secreted by the proximal renal tubule so that their clearance exceeds that of any measurements of true GFR [20, 21]. Reduction in renal function could also alter the pharmacodynamics of bisphosphonates and bone metabolism – an unexplored area; and the clearance of bisphosphonates by hemodialysis has limited data [21–26]. There also may be clear distinctions between renal–bone biology when the reduction in GFR is due to a systemic disease that also affects the kidneys as opposed to reductions in GFR when the reduced GFR is purely an age-related phenomenon [15, 19]. This suggestion is also based on observations in the postmenopausal and male osteoporosis clinical trials where neither hyperphosphatemia nor secondary hyperparathyroidism are seen in the randomized populations even at eGFR 30 ml/min when the decline in renal function is due to age-related reductions in renal function [27–30] in contrast to hyperphosphatemia and/or secondary hyperparathyroidism, which are common in chronic kidney disease (CKD), when due to known intrinsic renal disease [16, 30–32]. These potential differences in the bone–renal–systemic biology will require prospective investigation to define differences in disease progression and/or response to therapeutic intervention [33]. This chapter explores these aspects of bone biology in men with reduced GFR. While many of the data have been acquired in women, the fundamental principles of diagnosis and management should be applicable to men as well.
In population studies of both females and males (National Health and Nutritional Examination Survey), men and women of all studied ethnicities and genders have a decline in renal function as age increases [1, 2]. Age-related reduction in kidney function defined by measurements of glomerular filtration rate (GFR) measured either directly by 24-hour urine for creatinine clearances (CrCl) or by equations which estimate the GFR (either Cockcroft-Gault or Modification in Diet for Renal Diseases (MDRD)) occur universally in most populations as age increases [3–6]. There are increasing data, however, to suggest that serum creatinine concentration alone or eGFR underestimates or overestimates the prevalence of reduced renal function in many individuals, depending on the population and methodology employed to define renal function [7–14]. These controversies demand more investigation because of their implications in screening populations for kidney failure. Until we have better data, current estimates suggest that, on average, otherwise healthy populations have 50% of a normal GFR adjusted for body mass index by age 70 years [4–6, 10]. While the first renal functional adaptive capabilities lost as age increases are maintenance of renal blood flow in dehydrated states, renal acidification and renal concentrating ability, filtration of all solutes and, therefore, excretion of these solutes becomes reduced as well. The mechanism for the decline in GFR with aging in otherwise healthy populations is unclear but it may be related to non-specific effects of vascular changes on renal blood flow [6, 13]. In the field of osteoporosis, these effects of age on renal function become important because, as renal function declines, there may be associated abnormalities in calcium– phosphorus balance, parathyroid hormone (PTH) levels and/or end-organ resistance to PTH, abnormalities in renal production of 1,25 dihydroxyvitamin D3 and/or metabolic acidosis – Osteoporosis in Men
Diagnosis of osteoporosis in stage 1–3 chronic kidney disease Osteoporosis is the most prevalent metabolic bone disease leading to fragility fractures in human beings [34–36]. While 453
Copyright 2009, 2010 Elsevier, Inc. All rights of reproduction in any form reserved.
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Table 38.1 More common metabolic bone diseases that may be associated with fragility fractures Osteoporosis (including all secondary causes of osteoporosis, including steroid-induced osteoporosis, post-solid organ transplantation) Osteogenesis imperfecta Osteomalacia Osteitis fibrosa cystica (severe) Pathological fractures (malignancies) Severe renal failure (CKD–MBD) Osteopetrosis Paget’s disease of bone
the most common condition leading to osteoporosis is estrogen deficiency, there are other metabolic bone diseases that may be associated with fragility fractures [37] (Table 38.1). Since many medical conditions can lead to osteoporosis, a simple diagnostic criterion for this metabolic bone disease has been difficult to achieve. Prior to the 1994 World Health Organization (WHO) classification of ‘normal’ versus ‘osteopenia’ versus ‘osteoporosis’ based on bone mineral density (BMD) values (‘T-scores’) [38], the diagnosis of osteoporosisis was made on the basis of low-trauma fractures [39]. Lowtrauma fractures can also be due to metabolic bone diseases that are not osteoporosis, including renal bone diseases [40, 41]. While the T-score or fractures provide a working diagnosis for osteoporosis, they are neither specific nor sensitive for separating among osteoporosis and non-osteoporotic metabolic bone diseases. For example, in most patients with low-trauma fractures, osteoporosis is the disease most often associated with skeletal fragility, but other metabolic bone diseases not characterized by any diagnostic criteria for osteoporosis may independently cause fragility fractures, such as osteomalacia and osteogenesis imperfecta, to name two. This utilization of WHO criteria or fragility fractures to define osteoporosis becomes even more problematic, as mentioned, in the heterogeneous metabolic bone diseases that may accompany chronic kidney disease (CKD). All forms of renal severe (stage 5–5D) osteodystrophy, as defined by quantitative bone histomorphometry [42] or by chronic kidney disease–metabolic bone disease (CKD–MBD) may be associated with low-trauma fractures (Table 38.2) [17, 40]. In addition, the recent development from the Kidney Disease: Improving Global Outcomes (KDIGO) classification of renal metabolic bone disease based on dynamics of mineralization, turnover and volume (abbreviated TMV) also does not provide a working diagnosis of osteoporosis [31] (Table 38.3). In an attempt to define osteoporosis by a pathophysiological mechanism, the National Institutes of Health (NIH) have held two consensus conferences on osteoporosis and have stated that osteoporosis is: ‘a systemic skeletal disease characterized by impairment in bone strength. Bone strength is a composite of bone mineral density and microarchitecture’ [43]. As accurate as the NIH consensus definition is, it still does not provide a working diagnosis of osteoporosis – one that
Table 38.2 Renal bone diseases that may be associated with fragility fractures Osteoporosis Severe osteitis fibrosa cystica Osteomalacia Mixed osteodystrophy Adynamic bone disease, including aluminum bone disease Amyloid bone disease
Table 38.3 Kidney Disease: Improving Global Outcomes (KDIGO) classification of chronic kidney disease-metabolic bone disease based on dynamic parameters of turnover-mineralization-volume KDIGO: kidney disease improving global outcomes Classification of ROD
Turnover Turnover High High Normal Normal Low
Low
Mineralization Mineralization Normal Abnormal Normal
Abnormal Moe S et al Kid Internat 2006
Volume Volume High Normal High Low Normal
Low
Reference [31]
allows clinicians to apply in patient management decisions and one that is also accepted by the United States International Classification of Disease (ICD-9) codes for reimbursement purposes. The 1994 WHO criteria offer the most pragmatic operational definition for osteoporosis, can be applied in both men and women alike and in younger patients who have secondary medical conditions associated with increased risk for low-trauma fracture [44]. While the main purpose of the WHO classification of normal, osteopenia (T score: 1.0 – 2.5) and osteoporosis was to advise international health economies of the potential future economic impact of osteoporosis, the T-score also became the pragmatic diagnostic threshold for defining these three categories in clinical practice. The T-score has also been useful to underscore an important population-based observation: more people who fracture who have osteopenia than osteoporosis by T-score because: 1 there are more people with osteopenia than osteoporosis [45, 46] 2 many other factors independent of low BMD contribute to bone strength [47, 48]. Hence, in patients with CKD who develop low-trauma fractures, the reasonable question is: is the cause of the
C h a p t e r 3 8 Management of Fractures in Men with Impaired Renal Function l
low-trauma fracture osteoporosis? In stage 1–3 CKD, there is emerging agreement that, in the absence of any other biochemical abnormality suggesting CKD–MBD, the WHO criteria or low-trauma fractures can be used to diagnose osteoporosis. In patients with stage 5–5D CKD, the answer to this question is neither straightforward nor clearly defined. In stage 5–5D CKD, the derangements in bone and mineral metabolism become so profound that they may lead to specific forms CKD–MBD of sufficient magnitude to lead to impairment in bone strength and increase risk for low-trauma fractures. There may be a fourfold increased risk of hip fracture in men and women in stage 5–5D CKD that may be seen as compared to age-matched controls [49–52]. Adynamic, severe hyperparathyroid bone disease as well as osteomalacia can be associated with a higher risk for fragility fractures than is seen in age-matched population studies of postmenopausal women or elderly men. These are bone fragility conditions that are not osteoporosis but can mimic osteoporosis by WHO criteria or the presence of fragility fractures. Thus, when the patient with severe stage 5 or 5D CKD has severe low-trauma fractures that, by themselves are life threatening, it is a reasonable question to ask if the pharmacological agents that have been shown to reduce the risk of global fractures in many other osteoporotic conditions (postmenopausal, steroid osteoporosis, elderly male osteoporosis, post-solid organ transplantation) may also be useful in severe CKD patients who may have osteoporosis.
Diagnosis of osteoporosis in stage 5–5D CKD There are no universally accepted criteria for making the diagnosis of osteoporosis in more advanced CKD patients. The diagnosis is best suggested by excluding the other forms of renal osteodystrophy (ROD) by quantitative histomorphometry or to attempt to classify the form of CKD–MBD by non-invasive means of assessing bone turnover, mineralization and volume (TMV). However, we currently lack clinical tools to accomplish TMV distinctions in individual patients. While many promising radiological techniques currently in research are examining bone microarchitecture and offer hope to be capable of defining TMV non-invasively in severe CKD, they are still in development such that, at this time, they cannot yet be used to discriminate between CKD–MBD and osteoporosis in clinical practice [53–55]. As we better refine the relationships between TMV parameters and bone strength, these non-invasive imaging technologies may, in time, become the means to correlate TMV parameters to bone strength and open up an entirely new way to classify skeletal strength and manage patients with severe CKD. In the meantime, the clinician is left with quantitative bone histomorphometry and/or biochemical markers of bone turnover to characterize the bone disease that may be
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identified for low-trauma fractures in stage 5–5D CKD. The clinician should first use biochemical markers before bone biopsy to discriminate among the forms of renal osteodystrophy since, if they can make this distinction, a biopsy may be obviated.
Biochemical markers of bone metabolism In CKD, the bone biochemical tests that are usually assessed by nephrologists during the course of declining renal function are serum phosphorus, parathyroid hormone (PTH), calcium, total alkaline phosphatase, 1,25 dihydroxyvitamin D level and serum electrolytes. For the management of postmenopausal osteoporosis, the biochemical markers of bone turnover that are measured to reflect baseline levels of bone turnover or change in bone turnover by pharmacological agents are serum or urine collagen cross-links (bone resorption markers: N-telopepetide (NTX) or C-telopeptide (CTX)), bone-specific alkaline phosphatase (BSAP), serum osteocalcin and/or propeptide type 1 collagen (bone formation markers) and 25 hydroxyvitamin D levels. Biochemical markers of bone turnover cannot be used to make a diagnosis of osteoporosis. They can, however, be used to provide data regarding the level of bone turnover and, in that manner, provide clinical guidance as to whether a patient might have high or low bone turnover and whether or not there may be bone biological effects from therapy to reduce or increase bone turnover [56–63]. While these markers have value in making these distinctions in groups of patients, they become less sensitive and specific for classifying an individual patient’s bone turnover status. In the renal field, the PTH and alkaline phosphatase are generally considered to be the most useful markers for characterizing a patient’s bone turnover and their application for group classification are outlined in Tables 38.4 and 38.5 [64, 65]. There are a few generalizable clinical points that may be useful from these tables: If a patient has an elevated (above the upper limit of the normal reference range) BSAP, adynamic bone disease is highly unlikely. Elevated BSAP could be osteomalacia, or hyperparathyroid bone disease, assuming that other secondary causes of elevated BSAP have already been excluded (Paget’s disease, metastatic cancer, for example) A ‘normal’ BSAP does not exclude adynamic bone disease, while a low BSAP is more often associated with low bone turnover An elevated PTH does not exclude adynamic renal bone disease but a low (150 pg/ml) PTH is suggestive of a low bone turnover state. A PTH six times or higher above the upper limit of normal of the reference range is far more likely to be associated with high bone turnover.
l
l
l
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Table 38.4 Ranges of parathyroid hormone as they relate to a specific form of CKD–MBD Disorder
Serum intact PTH levels (pg/mL)
Hyperparathyroidism Mild Moderate Severe hsp:1 Aluminum bone Adynamic bone Osteomalacia
200–400 350–800 700 10–500 (mostly 100) 100–150 Normal or mildly elevated
In groups of patients the PTH level can distinguish among the histological forms of renal osteodystrophy. Overlap in values are often seen between PTH and bone histology in individual patients [64]
Table 38.5 Ranges of bone-specific alkaline phosphatase as they relate to a specific form of CKD-MBD Disorder
Serum bone specific alkaline phosphatase
Hyperparathyroidism Mild Moderate Severe hsp:1 Aluminum bone Adynamic bone Osteomalacia
Normal Normal to elevated Elevated Normal Normal to low Mildly elevated
In groups of patients the BSAP can distinguish among the various histological forms of renal osteodystrophy. In individual patients there is often overlap in the BSAP and the histology [64]
Thus, in clinical practice, a patient with stage 4–5D CKD who has an elevated BSAP or very high PTH values does not have adynamic bone disease and, once other etiologies for these aberrant biochemical abnormalities have been defined, then high bone turnover from ‘high bone turnover osteoporosis’ may be a consideration. Certainly, in my opinion, if bone turnover markers suggest low bone turnover, a biopsy is necessary before initiating an antiresorptive agent [66].
Quantitative bone histomorphometry The science of double tetracycline-labeled quantitative histomorphometry was and continues to be the only clinical means to define turnover, mineralization and volume in accepted quantitative ways [67, 68]. The American Society for Bone and Mineral Research (ASBMR) committee on standardization of histomorphometric criteria developed the criteria for distinguishing among the heterogeneous forms of metabolic bone diseases (osteomalacia, adynamic bone disease, hyperparathyroid bone disease) [42]. These criteria can be used to distinguish among the various metabolic bone diseases that accompany stage 5–5D CKD including adynamic bone disease [69–71] (Figure 38.1). For patients with stage 5–5D CKD and who are suffering fragility fractures, adynamic bone disease should be excluded before initiating, off-label, an osteoporosis pharmacological agent that reduces bone turnover (bisphosphonates, calcitonin, estrogen, selective estrogen
Figure 38.1 Renal adynamic bone disease. (A) Scant trabeculae seen (black); (B) scant osteoid seen (yellow); (C) no osteoclasts seen; (D) no tetracycline labels seen [66]. (See color plate section).
C h a p t e r 3 8 Management of Fractures in Men with Impaired Renal Function l
receptor modulators or denosumab). While there is no evidence, for example, that adding a bisphosphonate to a preexisting adynamic bone is detrimental to either bone strength or systemic vascular calcification that may be linked to low bone turnover [72], it seems unreasonable to take such an approach until solid prospective data describe the harm or benefit. Hence, quantitative bone histomorphometry can discriminate among the various forms of renal osteodystrophy and, if not present in a fracturing patient with stage 4–5D CKD who also, on biopsy, has a low trabecular bone volume, probably has, by exclusion, osteoporosis.
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agents that reduce the risk for fractures in postmenopausal, male or glucocorticoid-induced osteoporosis [73, 74]. Evidence from registration clinical trials shows efficacy of these agents down to levels of renal function calculated either by serum creatinine concentrations (2.0 mg/dl) or estimated glomerular filtration rates by Cockcroft-Gault equations (eGFR) or creatinine clearance 30 ml/min. While all of the registered agents have evidence of risk reduction for vertebral fractures, patients at higher fracture risk or who have already suffered a non-vertebral fracture are more often considered candidates for bisphosphonate or teriparatide, which have evidence for global fracture risk reduction. There is prospective evidence that patients with agerelated reduction in GFR down to 30 ml/min gain a benefit from oral and intravenous bisphosphonates or teriparatide [75–80]. In addition, theses agents seem to have an excellent safety profile as measured by effects on renal adverse events. In the intravenous bisphosphonate studies of postmenopausal women, it appears that both ibandronate, even at doses of 3 mg IV every 3 months (the registered dose for postmenopausal osteoporosis) as well as zoledronic acid (5 mg/year) are safe in patients with GFR 30–35 ml/min when given as an injection (ibandronate) or 15-minute infusion (zoledronic acid). A non-inferiority study in men also has recently shown that intravenous zoledronic acid is as effective (using surrogate markers as end-points) as weekly alendronate (Figure 38.2) [81]. It is important, however, to point out that, even though there was no adverse effects of these intravenous bisphosphonates on renal function in the
Treatment of osteoporosis in CKD As previously mentioned, patients who are suffering lowtrauma fragility fractures with stage 1–3 CKD are more likely to have osteoporosis than CKD–MBD as the cause of their impaired bone strength. Though several articles have described a higher fragility fracture risk associated with age-related reduction in renal function compared with agedmatched patients with normal renal function, the specific metabolic bone disease other than osteoporosis accounting for this bone fragility has not been defined [13, 17, 19, 31]. Hence, in patients with osteoporosis and who are in stage 1–3 CKD ranges of glomerular filtration rate that do not have a known biochemical abnormality that might suggest some form of CKD–MBD, they can and should be considered for treatment with FDA-registered pharmacological
Zoledronic acid is not inferior to alendronate in increasing lumbar spine BMD (LOCF) at Month 24 relative to baseline ZOL
10
ALN
Percentage change from baseline in LS BMD
9
[p -value = 0.7935]*
8 7 6 5 4 3
3.7%
3.1% n=138
n=143 n=143
5.0% 4.3% n=136 n=136 n=142 n=142
6.5% 6.7% n=135 n=123 n=135 n=123
2 1 0
6
12
24
Months value obtained from ANCOVA on % change from baseline of BMD with treatment and center as factors and baseline LS *P-BMD as a covariate. LS Mean diff (95% CI) = -0.131 (-1.116, 0.854). Data on file, Novartis. 7| Presentation Title | Presenter Name | Date | Subject | Business Use Only
Figure 38.2 The effect of zoledronic acid (5 mg IV over 15 minutes) on lumbar spine bone mineral density change from baseline as compared to alendronate (70 mg/week) in men [81].
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Osteoporosis in Men Reclast renal safety
Short term: 9–11 day postdose monitoring in > 5000 patients1
Overall, no cumulative impact on renal function over 3 years
Changes in Calculated Creatinine Clearance* From Baseline Over Time3
1
Mean (±SE) Change From Baseline in Calculated Creatinine Clearance (mL/min)
Transient rises in serum creatinine in 1.8% of patients (vs 0.8% placebo) (P < 0.01) with resolution and all patients redosed2 The percentage of patients who had a decrease in creatinine clearance < 30 mL/min prior to the second or third infusion or at month 36 was similar between treatment groups3
Placebo (n = 3852)
0
Reclast (n = 3862)
–5
–10
–15 0
12
24
36
Months
*Cockcroft-Gault equation 1. Black DM, et al. N Engl J Med. 2007;356:1809-1822. 2. Reclast® (zoledronic acid) Injection [prescribing information]. East Hanover, NJ: Novartis Pharmaceuticals Corp; August 2007. 3. Miller P, et al. Poster presented at: 7th European Congress on Clinical and Economic Aspects of Osteoporosis and Osteoarthritis; March 28-31, 2007; Porto, Portugal. Poster P308.
Figure 38.3 Results of the effects of 3 years of IV zoledronic acid (5 mg/year) on GFR as compared with placebo In the pivotal IV (5 mg/year) zoledronic acid postmenopausal clinical trial there were equal numbers of patients that received active treatment as well as placebo that had a decline in creatinine clearance over the 3-year trial period [77].
randomized populations used for registration, safety might not be the same in patients with pre-existing renal disease from intrinsic parenchymal disease (e.g. diabetics) or in patients using other agents that could affect renal function (e.g. non-steroidal anti-inflammatory drugs), so caution should still be exercised in decisions to use intravenous bisphosphonates in specific higher-risk subpopulations. In the zoledronic acid clinical trials, a substantial proportion of the population had diabetes; no different adverse renal effects were seen between diabetic and non-diabetic patients. Also, in the zoledronic acid trials, GFR declined equally between the treated and placebo groups over time and were no different at the end of the 3-year study (Figure 38.3) [77]. However, in a short-term subset of patients where serum creatinine was measured during days 9–11 after the 15-minute infusion of zoledronic acid, there was a small but statistically significant number of patients who had a transient increase in serum creatinine concentration (0.5 to 2.0 mg/dl above baseline) during the second annual infusion (Figure 38.4) [79]. However, all of these patients had a return of their serum creatinine concentration before the next annual infusion. It is important to stress that infusions of zoledronic acid be given no faster than 15 minutes since more rapid infusion rates have been associated with acute renal failure, suggesting that the tubular damage that mimics acute tubular necrosis (ATN) is related to the Cmax and not the AUC (area under the curve). This author administers zoledronic acid over a 30-minute infusion time in patients with normal renal function or in those with stages 1–3 CKD.
In the registration trial for teriparatide, baseline measurements of GFR were not required for randomization, but patients were enrolled if their baseline serum creatinine concentration was 2.0 mg/dl [80]. In a post-hoc analysis, there was a small subset of patients who had eGFR down to 30 ml/ min (by Cockgroft-Gault) and, in this subset, teriparatide both at 20 g/day as well as 40 g/day had an anabolic effect as measured by increases in osteoblast activity markers (Figure 38.5) [27] and BMD and pooled reduction in vertebral as well as non-vertebral fracture risk (Figure 38.6) [27] similar to those with higher eGFR and without any adverse renal effects [27]. There are no teriparatide data in stage 4–5D CKD and it is important to emphasize that, in all of the teriparatide clinical trials, all patients, even those with eGFR down to 30 ml/min, had normal baseline serum intact PTH levels. It is possible that the bone biological response could differ between patients with CKD who have an elevated as compared with a normal serum PTH. This query should be investigated. Treatment decisions become more difficult to make in fracturing patients with stage 5 and 5D CKD. This is even the case when the clinician has determined to the best of his/her ability that the patient with stage 5–5D CKD has suffered a fragility fracture and has osteoporosis rather than CKD–MBD. There are no prospective data showing efficacy of any of the approved pharmacological agents to treat osteoporosis at these levels of GFR. There are data from two separate post-hoc analyses that both risedronate, using the 5 mg/day formulation (from pooled data of 9 clinical trials)
C h a p t e r 3 8 Management of Fractures in Men with Impaired Renal Function l
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Short Term Renal Safety Sub-Group Data (n= 5,038) Placebo
Mean serum creatinine (mg/dL)
3.5
Zoledronic acid 5 mg
3 2.5 2 1.5 1 0.5 0 Baseline
Zoledronic acid n = 31 Placebo n =
10
9–11 days 2nd infusion 9–11 days 3rd infusion 9–11 days after 1st (mth 12) after 2nd (mth 24) after 3rd infusion infusion infusion 29 29 21 26 19 8
8
7
8
8
Month 36
24 7
Boonen S et al Kid Internat 2008
Figure 38.4 The short-term (9–11 days post-infusion) effect of zoledronic acid (5 mg/year) on serum creatinine concentration. After the second infusion of 5 mg zoledronic acid there was a small but significant number of patients (n 27) who had at least a doubling of their serum creatinine concentration 9–11 days post infusion as compared to placebo (n 7) (P 0.004). All serum creatinine concentrations returned to baseline before the next annual infusion of zoledronic acid [79]. Effect of Renal Function on Changes in PINP Concentrations with Teriparatide
Median change from baseline [ng/ml] (25th, 75th percentiles)
PINP (3 months)
*
200
*
150
Placebo TPTD20 TPTD40 * P 80 ml/min)
Moderate Mild Impairment Impairment (50–79 ml/min) (30–49 ml/min)
Miller P, et al. Osteopor Int 2007
Figure 38.5 The effect of teriparatide (rh 1-34 PTH: 20 g or 40 g/day) on osteoblastic activity marker (P1NP) change at 3 months from baseline in patients as a function of the baseline renal function (tertiles) [27].
(Figure 38.7) as well as alendronate (from the Fracture Intervention Trial where 5 mg/day was given for the first 2 years and 10 mg/day for the third year) reduced incident vertebral fractures (risedronate) or vertebral as well as all
clinical fractures (alendronate) without changing serum creatinine concentration when given at these daily registration doses for a period of 2–3 years in patients with eGFR (by Cockgroft-Gault equation) [28, 29]. Hence, these are
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Osteoporosis in Men Vertebral fracture 30 25 Fracture incidence (%)
Non-vertebral fracture 10
RR = 0.22 (0.13,0.39)
20 RR = 0.43 (0.25,0.73)
15
37/199
Placebo
8
RR = 0.53 (0.26, 1.05)
6
RR = 0.37 (0.17, 0.80)
TPTD20+40
15/246 15/292
10
4
27/244
16/593
2
5
23/483
0
Normal (> 80 ml/min)
11/485
16/383
Abnormal (< 80 ml/min)
0
Normal (> 80 ml/min)
Renal function
Abnormal (< 80 ml/min)
Renal function
Miller P, et al. Osteopor Int 2007
Figure 38.6 The effect of teriparatide (1-34 rhPTH 20 40 g/day) on vertebral fracture incidence and non-vertebral fracture risk reduction in pooled analysis of postmenopausal women and men as a function of renal function [27].
Control
30
5 mg RIS
Percent of patients
25 20 15
56% (11,78%) p = 0.021
45% (31,57%) p < 0.001
32% (14,46%) p = 0.001
10 5 0 Baseline renal impairment* Mild N = 3000
Moderate N = 2423
Severe N = 232
*Creatinine clearance estimated using the Cockcroft and Gault method [9] N Number of patients with evaluable paired spinal radiographs Miller PD et al JBMR 2005
Figure 38.7 Effect of risedronate (5 mg/day) on incident morphometric vertebral fracture risk in patients with baseline eGFR (Cockgroft Gault) divided into tertiles. Equal reduction in incident vertebral fractures in pooled risedronate clinical trials (5 mg/day) even in patients with eGFR less than 30 ml/min (none below 15 ml/min) [52].
the only data that suggest that these formulations are safe and effective for 2–3 years in patients in the postmenopausal clinical trials with eGFR reductions by Cockkroft-Gault down to 15 ml/min from age-related bone loss. Similar post-hoc data have been published on raloxifene [30]. There are no data on the efficacy or safety of bisphosphonates of any formulation on fracture risk reduction in patients with GFR 15 ml/min (stage 5 or 5D CKD). Nevertheless,
the question often arises on opinions on management of fragility fractures in this population. Here only opinion exists and is controversial and leads us to appeal for good science and randomized prospective data in these groups. In this author’s opinion, patients without fractures with stage 5 or 5D CKD should not be given bisphosphonates or teriparatide off-label. That is, treating only on the basis of low BMD and other risk factors would seem possibly to
C h a p t e r 3 8 Management of Fractures in Men with Impaired Renal Function l
be associated with greater risk than benefit. In those 5–5D CKD patients suffering fragility fractures, a bisphosphonate may be considered but only after a thorough elimination of CKD–MBD, which most often requires a bone biopsy [66, 73]. A transiliac bone biopsy is a safe procedure with little morbidity when performed in skilled hands. Once a diagnosis of osteoporosis appears to be the cause of fractures then, if one chooses to use a bisphosphonate after open informed consent of the patient, then this author halves the usual dose formulation and restricts the use to no more than 3 years. This approach is based on the known pharmaco kinetics of bisphosphonates in human beings with normal renal function: 50% of an administered dose goes to bone and 50% gets excreted by the kidney. Thus, with severe impairment of renal function, and where the dialyzability of bisphosphonates has not been well studied, it seems reasonable to give one-half the usual dose. The limitation of administration to no more than 3 years is based on the unknown, but probable, greater bone retention of bisphosphonates when excretion is impaired. It should be stressed that these approaches are based on no evidence for efficacy but are considered in extreme cases of often recurrent fragility fractures where the fractures per se pose a great risk for morbidity and mortality. These approaches should be clearly discussed with the patient, be undertaken by specialists knowledgeable in complex metabolic bone disease management and be initiated only after the disease leading to fractures is well characterized.
Conclusions No consensus exists regarding the criteria for the diagnosis of osteoporosis in stage 4 or 5–5D CKD. In higher-risk patients with stage 1–3 CKD and osteoporosis, it appears that any agent registered for osteoporosis can be used with efficacy and safety data, including the bisphosphonates and/ or teriparatide. The considerations for management become far more complex in stage 4, 5–5D CKD where the prevalence of other metabolic bone diseases and CKD–MBD increase and the WHO criteria for fragility fractures cannot be used for the diagnosis of osteoporosis. In these more severe cases of CKD (5–5D), the differential diagnosis requires careful analysis of a broad range of biochemical markers of bone turnover and, at times, quantitative bone histomorphometry, especially if management considerations include the use of bisphosphonates. It is unknown if bisphosphonates, by reducing bone turnover in a pre-existing low bone turnover state, would help or harm bone or lead to more or less cardiovascular disease. These questions must be addressed by better science and prospective data. The future application of newer non-invasive radiological tools to measure microstructure and mineralization of bone promises to help us better understand osteoporosis and CKD–MBD in a
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non-invasive manner. In clinical practice, at the current time and with current limited knowledge, treatment of osteoporosis in stage 4–5, 5D CKD is opinion based. Nevertheless, in very specific clinical cases of severe fragility fractures that, by themselves, may cause a high morbidity and mortality, bisphosphonates should be considered by experts in bone metabolism and, as with the use of any off-label application, after careful informed discussions with the patient.
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32. G. Elder, Pathophysiology and recent advances in the management of renal osteodystrophy, Osteoporos. Int. 17 (12) (2002) 2094–2105. 33. K.A. Hruska, G. Saab, S. Mathew, R. Lund, Renal osteodystrophy, phosphate homeostasis, and vascular calcification, Semin. Dial. 20 (4) (2007) 309–315. 34. L.J. Melton III, Epidemiology worldwide, Endocrinol. Metab. Clin. N. Am. 32 (2003) 1–13. 35. R. Burge, B. Dawson-Hughes, D.H. Solomon, et al., Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025, J. Bone Miner. Res. 22 (2007) 465–475. 36. E. Barrett-Connor, E.S. Siris, L.E. Wehren, et al., Osteoporosis and fracture risk in women of different ethnic groups, J. Bone Miner. Res. 20 (2005) 185–194. 37. P. Camacho, M. Kleerekoper, Secondary osteoporosis, Endocr. Pract. (2007). 38. WHO Study Group, Assessment of fracture risk and its application to screening for postmenopausal osteoporosis, World Health Organ. Tech. Rep. Ser. Geneva 843 (1994) 1–129. 39. P.D. Miller, S.L. Bonnick, Clinical utilization of bone mass measurements for the assessment and management of osteoporosis in the adult population, in: M. Favus (Ed.), Primer of Metabolic Bone Diseases, American Society for Bone and Mineral Research, 1999. 40. T.L. Nickolas, M.B. Leonard, E. Shane, Chronic kidney disease and bone fracture: a growing concern, Kidney Int. 2 (2008) 1–11. 41. A. Gal-Moscovici, S.M. Sprague, Osteoporosis and chronic kidney disease, Semin. Dial. 20 (5) (2007) 423–430. 42. A.M. Parfitt, M. Drezner, F. Glorieux, et al., Bone histomorphometry: standardization of nomenclature, symbols, and units. Report of the ASBMR Histomorphometry Nomenclature Committee, J. Bone Miner. Res. 2 (6) (1987) 595–610. 43. NIH Consensus Development Panel Osteoporosis Prevention Diagnosis and Therapy. J. Am. Med. Assoc. 285 (2001) . 44. S. Baim, N. Binkley, J.P. Bilezikian, et al., Official Positions of the International Society for Clinical Densitometry and executive summary of the 2007 ISCD Position Development Conference, J. Clin. Densitom. 11 (1) (2008) 75–91. 45. E. Siris, P. Miller, E. Barrett-Connor, et al., Identification and fracture outcomes of undiagnosed low bone mineral density in postmenopausal women: results from the National Osteoporosis Risk Assessment (NORA), J. Am. Med. Assoc. 286 (2001) 2815–2822. 46. S.C.E. Schuit, H.H. Oei, J.C. Witteman, et al., Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam Study, Bone 34 (1) (2004) 195–202. 47. M.L. Bouxsein, Non-invasive measurements of bone strength: promise and peril, J. Musculoskelet. Neuron. Interact. 4 (4) (2004) 404–405. 48. E. Seeman, Bone quality: the material and structural basis of bone strength, J. Bone Miner. Metab. 26 (1) (2008) 1–8. 49. A.M. Alem, D.J. Sherrard, D.L. Gillen, et al., Increased risk of hip fracture among patients with end-stage renal disease, Kidney Int. 58 (2000) 396–399. 50. A.M. Ball, D.L. Gillen, D. Sherrard, et al., Risk of hip fracture among dialysis and renal transplant recipients, J. Am. Med. Assoc. 288 (2002) 3014–3018.
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Chapter
39
Primary Hyperparathyroidism in Men Claudio Marcocci1, Luisella Cianferotti1, Shonni J. Silverberg2 and John P. Bilezikian2 1
Department of Endocrinology and Metabolism, University of Pisa, Pisa, Italy Division of Endocrinology, Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, USA
2
Introduction
stones, overt bone disease and specific neuromuscular dysfunction, to one that is primarily asymptomatic at the time of diagnosis [1] (Figure 39.1). In this chapter, the modern profile of PHPT will be described with specific reference to possible gender differences among men and women.
Primary hyperparathyroidism (PHPT) is one of the most frequently diagnosed endocrine disorders. Together with malignancy, PHPT is the most common cause of hypercalcemia and therefore should be considered in any subject with elevated serum calcium concentration. Following the introduction and widespread use of the multichannel autoanalyzer in the early 1970s, a four- to fivefold increase in the prevalence and incidence of the disease was appreciated. Along with the increase in incidence, the most common clinical presentation of PHPT changed from a disease that was primarily symptomatic, with hypercalcemia, kidney
Epidemiology PHPT was not a common disease when serum calcium determinations were not routinely obtained. Incidence figures
80
Percentage of patients
70 60 50 40 30 20 10 0 Cope et al.a (1930–1965)
Heath et al.(2) (1965–1974)
Mallette et al.c (1965–1972)
Silverberg et al.(54) (1984–2000)
Figure 39.1 Changes in clinical manifestations of PHPT at diagnosis in subsequent epidemiological studies: increase in asymptomatic disease (filled bars) versus osteitis fibrosa cystica (gray bars) and nephrolithiasis (open bars). Osteoporosis in Men
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rose dramatically when serum calcium determinations became routine in the context of the multichannel biochemistry autoanalyzer. Comparing figures before and after the introduction of the autoanalyzer at the Mayo Clinic, there was a four- to fivefold increase in the incidence of PHPT to approximately 27.7 cases per 100 000 persons per year [3]. More recent reports from USA and Europe have suggested that the incidence of PHPT may be declining, even though, in the experience of most endocrinologists, this does not appear to be the case [6, 7]. The estimated prevalence of PHPT is 3/1000 in the general population, but may be as high as 2.1% in postmenopausal women. PHPT occurs at all ages, but the incidence increases with age and peaks in the sixth decade of life. It is generally reported that men are affected much less often than women by a ratio of approximately 1:3. A Mayo Clinic update on the incidence of PHPT between 1993 and 2001 showed that the mean age at diagnosis has remained stable (52 years and 56 years, respectively) and that the majority
Incidence (per 100 000 person-years)
350
