Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity.

Hum Mol Genet
Authors
Keywords
Abstract

To date, genome-wide association studies (GWASs) have identified >100 loci with single variants associated with body mass index (BMI). This approach may miss loci with high allelic heterogeneity; therefore, the aim of the present study was to use gene-based meta-analysis to identify regions with high allelic heterogeneity to discover additional obesity susceptibility loci. We included GWAS data from 123 865 individuals of European descent from 46 cohorts in Stage 1 and Metabochip data from additional 103 046 individuals from 43 cohorts in Stage 2, all within the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Each cohort was tested for association between ∼2.4 million (Stage 1) or ∼200 000 (Stage 2) imputed or genotyped single variants and BMI, and summary statistics were subsequently meta-analyzed in 17 941 genes. We used the 'VErsatile Gene-based Association Study' (VEGAS) approach to assign variants to genes and to calculate gene-based P-values based on simulations. The VEGAS method was applied to each cohort separately before a gene-based meta-analysis was performed. In Stage 1, two known (FTO and TMEM18) and six novel (PEX2, MTFR2, SSFA2, IARS2, CEP295 and TXNDC12) loci were associated with BMI (P

Year of Publication
2015
Journal
Hum Mol Genet
Volume
24
Issue
23
Pages
6849-60
Date Published
2015 Dec 01
ISSN
1460-2083
URL
DOI
10.1093/hmg/ddv379
PubMed ID
26376864
PubMed Central ID
PMC4643645
Links
Grant list
G1001799 / Medical Research Council / United Kingdom
R01 DK075787 / DK / NIDDK NIH HHS / United States
MC_UU_12015/1 / Medical Research Council / United Kingdom
MC_U106179471 / Medical Research Council / United Kingdom
MR/N01104X/1 / Medical Research Council / United Kingdom
T32 HL007055 / HL / NHLBI NIH HHS / United States