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

Author:

Brotman Sarah M.ORCID,El-Sayed Moustafa Julia S.,Guan Li,Broadaway K. Alaine,Wang Dongmeng,Jackson Anne U.,Welch Ryan,Currin Kevin W.,Tomlinson Max,Vadlamudi Swarooparani,Stringham Heather M.,Roberts Amy L.,Lakka Timo A.,Oravilahti Anniina,Silva Lilian Fernandes,Narisu Narisu,Erdos Michael R.,Yan Tingfen,Bonnycastle Lori L.,Raulerson Chelsea K.,Raza Yasrab,Yan Xinyu,Parker Stephen C.J.,Kuusisto Johanna,Pajukanta Päivi,Tuomilehto Jaakko,Collins Francis S.,Boehnke Michael,Love Michael I.,Koistinen Heikki A.,Laakso Markku,Mohlke Karen L.ORCID,Small Kerrin S.ORCID,Scott Laura J.ORCID

Abstract

AbstractComplete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary 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 eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with ≥2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

Publisher

Cold Spring Harbor Laboratory

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