Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI

Int J Obes (Lond). 2018 Mar;42(3):384-390. doi: 10.1038/ijo.2017.304. Epub 2017 Dec 21.

Abstract

Objective: Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population.

Subjects: Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models.

Results: We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10-7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue.

Conclusion: Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Body Mass Index*
  • Genome-Wide Association Study
  • Genomics
  • Humans
  • Polymorphism, Single Nucleotide / genetics
  • Racial Groups / genetics*
  • Racial Groups / statistics & numerical data*

Grants and funding