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Hum Genet. 2017 Jun;136(6):771-800. doi: 10.1007/s00439-017-1787-6. Epub 2017 Apr 8.

Trans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci.

Author information

1
Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. fernandez-rhodes@unc.edu.
2
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
3
Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
4
Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
5
Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA.
6
Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA.
7
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
8
Center for Human Genetics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
9
Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA.
10
Department of Biostatistics, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
11
Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
12
National Heart Lung, and Blood Institute, Bethesda, MA, USA.
13
Insitute of Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA.
14
Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
15
Geriatrics and Gerontology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
16
Division of Biostatistics, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
17
Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA.
18
Division of Cardiology, Geneva University Hospital, Geneva, OH, Switzerland.
19
Department of Medicine, University of Alabama, Birmingham, AL, USA.
20
Department of Human Genetics, University of Utah, Salt Lake City, UT, USA.
21
Department of Biostatistics, University of Alabama, Birmingham, AL, USA.
22
Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
23
Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
24
Charles R. Bronfman Instituted for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
25
Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
26
School of Medicine, National Defense Medical Center, National Yang-Ming University, Taipei, Taiwan.
27
Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA.
28
Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan.
29
Division of Endocrinology and Metabolism, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
30
HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
31
Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan Town, Taiwan.
32
Division of Cardiology, Department of Internal Medicine, Cardiovascular Center, National Taiwan University Hospital, Taipei, Taiwan.
33
Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
34
Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
35
Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA.
36
School of Social Welfare, The University of Kansas, Lawrence, KS, USA.
37
Department of Nutrition, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
38
Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
39
Department of Statistics and Biostatistics, Rutgers University, Piscataway, NJ, USA.
40
Department of Genetics, Rutgers University, Piscataway, NJ, USA.

Abstract

Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70 kg/m2) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants.

PMID:
28391526
PMCID:
PMC5485655
DOI:
10.1007/s00439-017-1787-6
[Indexed for MEDLINE]
Free PMC Article

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