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.

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Fernández-Rhodes, L; Gong, J; Haessler, J; Franceschini, N; Graff, M; Nishimura, KK; Wang, Y; Highland, HM; Yoneyama, S; Bush, WS; Goodloe, R; Ritchie, MD; Crawford, D; Gross, M; Fornage, M; Buzkova, P; Tao, R; Isasi, C; Avilés-Santa, L; Daviglus, M; Mackey, RH; Houston, D; Gu, CC; Ehret, G; Nguyen, K-DH; Lewis, CE; Leppert, M; Irvin, MR; Lim, U; Haiman, CA; Le Marchand, L; Schumacher, F; Wilkens, L; Lu, Y; Bottinger, EP; Loos, RJL; Sheu, WH-H; Guo, X; Lee, W-J; Hai, Y; Hung, Y-J; Absher, D; Wu, I-C; Taylor, KD; Lee, I-T; Liu, Y; Wang, T-D; Quertermous, T; Juang, J-MJ; Rotter, JI; Assimes, T; Hsiung, CA; Chen, Y-DI; Prentice, R; Kuller, LH; Manson, JE; Kooperberg, C; Smokowski, P; Robinson, WR; Gordon-Larsen, P; Li, R; Hindorff, L; Buyske, S; Matise, TC; Peters, U; North, KE

Published Date

  • June 2017

Published In

Volume / Issue

  • 136 / 6

Start / End Page

  • 771 - 800

PubMed ID

  • 28391526

Pubmed Central ID

  • PMC5485655

Electronic International Standard Serial Number (EISSN)

  • 1432-1203

Digital Object Identifier (DOI)

  • 10.1007/s00439-017-1787-6


  • eng

Conference Location

  • Germany