Genetic risk factors for BMI and obesity in an ethnically diverse population: Results from the population architecture using genomics and epidemiology (PAGE) study |
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| Authors: | Megan D Fesinmeyer Kari E North Marylyn D Ritchie Unhee Lim Nora Franceschini Lynne R Wilkens Myron D Gross Petra B??ková Kimberly Glenn P Miguel Quibrera Lindsay Fernández‐Rhodes Qiong Li Jay H Fowke Rongling Li Christopher S Carlson Ross L Prentice Lewis H Kuller JoAnn E Manson Tara C Matise Shelley A Cole Christina TL Chen Barbara V Howard Laurence N Kolonel Brian E Henderson Kristine R Monroe Dana C Crawford Lucia A Hindorff Steven Buyske Christopher A Haiman Loic Le Marchand Ulrike Peters |
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| Institution: | 1. Department of Biostatistics and Biomathematics, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA;2. Carolina Center for Genome Sciences, School of Public Health, University of North Carolina, Chapel Hill, North Carolina, USA;3. Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA;4. Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA;5. Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, USA;6. Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, Minnesota, USA;7. Department of Biostatistics, University of Washington, Seattle, Washington, USA;8. University of North Carolina, School of Medicine, Department of Medicine, Chapel Hill, North Carolina, USA;9. Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA;10. Office of Population Genomics, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA;11. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA;12. Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA;13. Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA;14. Department of Epidemiology, Harvard School of Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA;15. Department of Statistics and Biostatistics, Rutgers University, Piscataway, New Jersey, USA;16. Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas, USA;17. MedStar Health Research Institute, Hyattsville, Maryland, USA;18. Division of Endocrinology and Metabolism, Department of Medicine, Georgetown University, Washington, DC, USA;19. Department of Preventive Medicine, Keck School of Medicine/Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA;20. Department of Genetics, Rutgers University, Piscataway, New Jersey, USA |
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| Abstract: | Objective: Several genome–wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups. Design and Methods: As part of the “Population Architecture using Genomics and Epidemiology (PAGE)” Consortium, we investigated the association between 13 GWAS‐identified single‐nucleotide polymorphisms (SNPs) and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African‐Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI‐increasing allele of each SNP, we calculated β coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI ≥ 30) followed by fixed‐effects meta‐analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and were adjusted for age, sex, and current smoking. We defined “replicating SNPs” (in European Americans) and “generalizing SNPs” (in other racial/ethnic groups) as those associated with an allele frequency‐specific increase in BMI. Results: By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians. Conclusion: Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine‐mapping in large samples is needed to comprehensively explore these loci in diverse populations. |
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