Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits.

ABSTRACT: While large-scale, genome-wide association studies (GWAS) have identified hundreds of loci associated with brain-related traits, identification of the variants, genes and molecular mechanisms underlying these traits remains challenging. Integration of GWAS with expression quantitative trait loci (eQTLs) and identification of shared genetic architecture have been widely adopted to nominate genes and candidate causal variants. However, this approach is limited by sample size, statistical power and linkage disequilibrium. We developed the multivariate multiple QTL approach and performed a large-scale, multi-ancestry eQTL meta-analysis to increase power and fine-mapping resolution. Analysis of 3,983 RNA-sequenced samples from 2,119 donors, including 474 non-European individuals, yielded an eff

SUBMITTER: Zeng B 

PROVIDER: S-EPMC8852232 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature