Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry

Author:

Pulit Sara L123ORCID,Stoneman Charli4ORCID,Morris Andrew P56,Wood Andrew R4,Glastonbury Craig A1,Tyrrell Jessica4,Yengo Loïc7,Ferreira Teresa1,Marouli Eirini8,Ji Yingjie4,Yang Jian79,Jones Samuel4ORCID,Beaumont Robin4,Croteau-Chonka Damien C10ORCID,Winkler Thomas W11,Hattersley Andrew T4,Loos Ruth J F12,Hirschhorn Joel N13141516,Visscher Peter M79,Frayling Timothy M4,Yaghootkar Hanieh4,Lindgren Cecilia M136,

Affiliation:

1. Big Data Institute, Li Ka Shing Center for Health Information and Discovery, Oxford University, Oxford, UK

2. Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands

3. Program in Medical and Population Genetics, Broad Institute, Boston, MA, USA

4. University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter, UK

5. Biostatistics Department, University of Liverpool, Liverpool, UK

6. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK

7. Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia

8. William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK

9. Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia

10. Channing Division of Network Medicine, Department of MedicineBrigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

11. Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany

12. The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, the Icahn School of Medicine at Mount Sinai, New York, NY, USA

13. Broad Institute of MIT and Harvard, Cambridge, MA, USA

14. Department of Genetics, Harvard Medical School, Boston, MA, USA

15. Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA

16. Department of Pediatrics, Harvard Medical School, Boston, MA, USA

Abstract

Abstract More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.

Funder

Li Ka Shing Foundation

The National Institute for Health Research Biomedical Research Centre

National Institutes of Health

ZonMw

Dutch Organization for Scientific Research

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Diabetes UK RD Lawrence fellowship

European Research Council

Wellcome Trust

Royal Society

European Regional Development Fund

Diabetes Research andWellness Foundation Fellowship

Medical Research Council

Australian National Health and Medical Research Council

Sylvia and Charles Viertel Charitable Foundation

U.S. National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Genetics(clinical),Genetics,Molecular Biology,General Medicine

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