Exploring correlation between bone metabolism markers and densitometric traits in extended families from Spain |
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| Affiliation: | 1. Unit of Genomics of Complex Diseases, Institute of Biomedical Research, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain;2. Laboratory of Angiology, Vascular Biology and Inflammation, Institute of Biomedical Research, Universitat Autònoma de Barcelona, Barcelona, Spain;3. Departament of Internal Medicine, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain;1. Università Campus Bio-Medico di Roma, Italy;2. Division of Bone and Mineral Diseases, Washington University in St Louis;3. University of California, San Francisco, CA, USA;4. San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA;5. California Pacific Medical Center, San Francisco, CA, USA;6. Department of Epidemiology, Center for Aging and Population Health, Graduate School of Public Health, USA;7. Center for Health Research NW, Kaiser Permanente, USA;8. Stanford University, USA;9. Veterans Affairs Health Care System, Portland, OR, USA;1. Division of Human Genetics, Children''s Hospital of Philadelphia, Philadelphia, USA;2. Department of Genetics, University of Pennsylvania, Philadelphia, USA;3. Division of Orthopedic Surgery, Children''s Hospital of Philadelphia, Perelman School of Medicine at University of Pennsylvania, USA;4. Department of Systems Pharmacology and Translation Therapeutics, University of Pennsylvania, Philadelphia, USA;5. Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, USA;6. Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA;7. Division of Endocrinology and Diabetes, Children''s Hospital of Philadelphia, Philadelphia, USA;1. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Box 281, 171 77 Stockholm, Sweden;2. Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA;3. Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Room: E8527, Baltimore, MD 21205, USA;4. Functional Food and Metabolic Stress Prevention Laboratory, Center of Nutrition, Council for Agricultural Research and Economics, Via Ardeatina 546, 00100 Rome, Italy;5. Department of Surgical Sciences, Section of Orthopedics, Uppsala Clinical Research Center, Akademiska sjukhuset ing. 61 6 tr, 751 85 Uppsala, Sweden;6. Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Edificio U7, Via Bicocca degli Arcimboldi 8, 20126 Milan, Italy;7. Clinical Epidemiology Unit, T2, Department of Medicine, Karolinska Institutet, SE-171 76 Stockholm, Sweden;8. Department of Medicine, Karolinska University Hospital, Huddinge, C2:84, SE-141 86 Stockholm, Sweden;1. Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, United States;2. Beck Radiological Innovations, Inc., United States;3. Center for Medicare and Medicaid Innovation, Centers for Medicare and Medicaid Services, Baltimore, MD, United States;4. Novartis Institute for Biomedical Research, United States;5. Department of Epidemiology and Public Health, University of Maryland, School of Medicine, United States;6. National Institute on Aging, Longitudinal Study Section, United States;7. Department of Sociology and Anthropology, University of Maryland Baltimore County, United States;8. University of Maryland, School of Medicine, United States;9. Research Institute, California Pacific Medical Center, San Francisco, CA, United States;10. Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, United States;11. National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control, United States;12. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, United States;13. Laboratory of Epidemiology and Population Sciences Intramural Research Program, National Institute on Aging, United States |
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| Abstract: | Osteoporosis is a common multifactorial disorder characterized by low bone mass and reduced bone strength that may cause fragility fractures. In recent years, there have been substantial advancements in the biochemical monitoring of bone metabolism through the measurement of bone turnover markers. Currently, good knowledge of the genetics of such markers has become an indispensable part of osteoporosis research. In this study, we used the Genetic Analysis of Osteoporosis Project to study the genetics of the plasma levels of 12 markers related to bone metabolism and osteoporosis. Plasma phenotypes were determined through biochemical assays and log-transformed values were used together with a set of covariates to model genetic and environmental contributions to phenotypic variation, thus estimating the heritability of each trait. In addition, we studied correlations between the 12 markers and a wide variety of previously described densitometric traits. All of the 12 bone metabolism markers showed significant heritability, ranging from 0.194 for osteocalcin to 0.516 for sclerostin after correcting for covariate effects. Strong genetic correlations were observed between osteocalcin and several bone mineral densitometric traits, a finding with potentially useful diagnostic applications. In addition, suggestive genetic correlations with densitometric traits were observed for leptin and sclerostin. Overall, the few strong and several suggestive genetic correlations point out the existence of a complex underlying genetic architecture for bone metabolism plasma phenotypes and provide a strong motivation for pursuing novel whole-genome gene-mapping strategies. |
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