Adipose tissue eQTL meta-analysis highlights the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. In the present study, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34,774 conditionally distinct expression quantitative trait locus (eQTL) signals at 18,476 genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared with primary eQTL signals, nonprimary eQTL signals had lower effect sizes, lower minor allele frequencies and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTLs with genome-wide association study (GWAS) signals for 28 cardiometabolic traits identified 1,835 genes. Inclusion of nonprimary eQTL signals increased discovery of colocalized GWAS–eQTL signals by 46%. Furthermore, 21 genes with ≥2 colocalized GWAS–eQTL signals showed a mediating gene dosage effect on the GWAS trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation. This study introduces AdipoExpress, an eQTL meta-analysis of 2,344 subcutaneous adipose tissue samples, which triples the size of previous studies and expands the discovery of eQTLs colocalized with GWAS signals for cardiometabolic traits.