Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits.

Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis -eQTL (within 1 Mb of the transcription start site) than trans -eQTL. Here, we tested the cis component of gene expression for association with observed plasma protein levels to identify cis - and trans- acting genes that regulate protein levels. We used transcriptome prediction models from 49 Genotype-Tissue Expression (GTEx) Project tissues to predict the cis component of gene expression and tested the predicted expression of every gene in every tissue for association with the observed abundance of 3,622 plasma proteins measured in 3,301 individuals from the INTERVAL study. We tested significant results for replication in 971 individuals from the Trans -omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA). We found 1,168 and 1,210 cis - and trans- acting associations that replicated in TOPMed (FDR < 0.05) with a median expected true positive rate (π 1) across tissues of 0.806 and 0.390, respectively. The target proteins of trans- acting genes were enriched for transcription factor binding sites and autoimmune diseases in the GWAS catalog. Furthermore, we found a higher correlation between predicted expression and protein levels of the same underlying gene (R = 0.17) than observed expression (R = 0.10, p = 7.50 × 10−11). This indicates the cis -acting genetically regulated (heritable) component of gene expression is more consistent across tissues than total observed expression (genetics + environment) and is useful in uncovering the function of SNPs associated with complex traits. We performed TWAS for thousands of plasma proteins, comparing same-gene, cis, and trans effects across tissues. We show the heritable component of gene expression more strongly correlates with protein levels than with total observed expression and is therefore more useful in uncovering the functions of SNPs associated with complex traits. [ABSTRACT FROM AUTHOR]