Genetic studies of body mass index yield new insights for obesity biology

Genetic studies of body mass index yield new insights for obesity biology · SciRah

^aDepartment of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, 48109, Michigan, USA
^bCenter for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
^cDepartment of Internal Medicine, Division of Gastroenterology, and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, 48109, Michigan, USA
^dDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, 20892, Maryland, USA
^eDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA.
^fBroad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, 02142, Massachusetts, USA
^gDepartment of Genetics, Harvard Medical School, Boston, 02115, Massachusetts, USA
^hDepartment of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby 2800, Denmark.
ⁱDivisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, 02115, Massachusetts, USA
^jMRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.
^kDepartment of Internal Medicine, Division of Gastroenterology, and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
^lDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
^mDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
ⁿDepartment of Genetics, University of North Carolina, Chapel Hill, 27599, North Carolina, USA
^oBroad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 02142, USA
^pCenter for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark
^qDepartment of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
^rDivisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts 02115, USA
^sQueensland Brain Institute, The University of Queensland, Brisbane 4072, Australia.
^tMRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
^uDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden.
^vDepartment of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala 75185, Sweden.
^wScience for Life Laboratory, Uppsala University, Uppsala 75185, Sweden.
^xDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
^yWellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.
^zQueensland Brain Institute, The University of Queensland, Brisbane 4072, Australia
^aaThe University of Queensland Diamantina Institute, The Translation Research Institute, Brisbane 4012, Australia
^abChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
^acInstitute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne 1010, Switzerland.
^adEstonian Genome Center, University of Tartu, Tartu 51010, Estonia
^aeDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden
^afDepartment of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala 75185, Sweden
^agScience for Life Laboratory, Uppsala University, Uppsala 75185, Sweden
^ahEstonian Genome Center, University of Tartu, Tartu 51010, Estonia.
^aiWellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
^ajDepartment of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, D-93053 Regensburg, Germany.
^akDepartment of Medical Genetics, University of Lausanne, Lausanne 1005, Switzerland
^alInstitute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne 1010, Switzerland
^amSwiss Institute of Bioinformatics, Lausanne 1015, Switzerland
^anGenetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK.
^aoDepartment of Nutrition, Harvard School of Public Health, Boston, 02115, Massachusetts, USA
^apSurvey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, 48104, Michigan, USA
^aqWellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
^arDepartment of Epidemiology, University of Michigan, Ann Arbor, 48109, Michigan, USA
^asDepartment of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, D-93053 Regensburg, Germany
^atGenetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
^auDepartment of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
^avDepartment of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, 48109, Michigan, USA
^awSurvey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan 48104, USA
^axDepartment of Genetics, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands.
^ayDepartment of Epidemiology, University of Michigan, Ann Arbor, Michigan 48109, USA

Abstract

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10−8), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis. A genome-wide association study and Metabochip meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis. In the second of two Articles in this issue from the GIANT Consortium, Elizabeth Speliotes and collegues conducted a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), commonly used to define obesity and assess adiposity, to find 97 BMI-associated loci, of which 56 were novel. Many of these loci have significant effects on other metabolic phenotypes. The 97 loci account for about 2.7% of BMI variation, and genome-wide estimates suggest common variation accounts for more than 20% of BMI variation. Pathway analyses implicate the central nervous system in obesity susceptibility including synaptic function, glutamate signaling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

TL;DRA genome-wide association study and meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis. (Semantic Scholar)

Genetic studies of body mass index yield new insights for obesity biology

Abstract

Plain-language summary

Discussion