Adipose Tissue Gene Expression Associations Reveal Hundreds of Candidate Genes for Cardiometabolic Traits

Abstract

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with cardiometabolic traits including type 2 diabetes (T2D), lipid levels, body fat distribution, and adiposity, although most causal genes remain unknown. We used subcutaneous adipose tissue RNA-seq data from 434 Finnish men from the METSIM study to identify 9,687 primary and 2,785 secondary cisexpression quantitative trait loci (eQTL; <1 Mb from TSS, FDR < 1%). Compared to primary eQTL signals, secondary eQTL signals were located further from transcription start sites, had smaller effect sizes, and were less enriched in adipose tissue regulatory elements compared to primary signals. Among 2,843 cardiometabolic GWAS signals, 262 colocalized by LD and conditional analysis with 318 transcripts as primary and conditionally distinct secondary cis-eQTLs, including some across ancestries. Of cardiometabolic traits examined for adipose tissue eQTL colocalizations, waist-hip ratio (WHR) and circulating lipid traits had the highest percentage of colocalized eQTLs (15% and 14%, respectively). Among alleles associated with increased cardiometabolic GWAS risk, approximately half (53%) were associated with decreased gene expression level. Mediation analyses of colocalized genes and cardiometabolic traits within the 434 individuals provided further evidence that gene expression influences variant-trait associations. These results identify hundreds of candidate genes that may act in adipose tissue to influence cardiometabolic traits.

Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation

“…Mediation analysis has recently been used with genomic data, including in humans (e.g., [10,15]) and rodents (e.g., [51,81]), to identify and refine potential intermediates of causal paths underlying phenotypes. We use a similar genome-wide mediation analysis as used with the DO [22, 33] to detect mediators of eQTL effects on gene expression.…”

“…In human data, co-occurence of QTL across various multi-omic data has been used to assess potentially related and connected biological processes; examples include gene expression with chromatin accessibility [7] or regulatory elements [8], and ribosome occupancy with protein abundances [9]. More formal integration through statistical mediation analyses has also been used to investigate relationships between levels of human biological data, such as distal genetic regulation through local gene expression [10,11], and eQTL with regulatory elements [12][13][14] and physiological phenotypes, such as cardiometabolic traits [15].…”

Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation

“…Mediation analysis has recently been used with genomic data, including in humans 698 (e.g., [11,15]) and rodents (e.g., [54,58]), to identify and refine potential intermediates of 699 October 25, 2019 19/32 causal paths underlying phenotypes. We use a similar genome-wide mediation analysis 700 as used with the DO [22,59] to detect mediators of eQTL effects on gene expression.…”

Consistent RNA sequencing contamination in GTEx and other data sets

“…All 10 had cross-sample contamination of the type described herein (Supplementary Data 6). We also analyzed the METSIM study, containing bulk sequencing of adipose tissue in 434 subjects 25 . The data from that study demonstrates how, in the absence of sequencing at the same time as a contaminating tissue (ex.…”

“…Only sun exposed skin was used for GTEx analysis. TPM RNA-seq data from the METSIM study was downloaded through the GEO (GSE135134) 25 .…”