Quantifying genetic effects on disease mediated by assayed gene expression levels

Abstract

Disease variants identified by genome-wide association studies (GWAS) tend to overlap with expression quantitative trait loci (eQTLs). However, it remains unclear whether this overlap is driven by mediation of genetic effects on disease by expression levels, or whether it primarily reflects pleiotropic relationships instead. Here we introduce a new method, mediated expression score regression (MESC), to estimate disease heritability mediated by the cis-genetic component of assayed steady-state gene expression levels, using summary association statistics from GWAS and eQTL studies. We show that MESC produces robust estimates of expression-mediated heritability across a wide range of simulations. We applied MESC to GWAS summary statistics for 42 diseases and complex traits (average N = 323K) and cis-eQTL data across 48 tissues from the GTEx consortium. We determined that a statistically significant but low proportion of disease heritability (mean estimate 11% with S.E. 2%) is mediated by the cis-genetic component of assayed gene expression levels, with substantial variation across diseases (point estimates from 0% to 38%). We further partitioned expression-mediated heritability across various gene sets. We observed an inverse relationship between cis-heritability of expression and disease heritability mediated by expression, suggesting that genes with weaker eQTLs have larger causal effects on disease. Moreover, we observed broad patterns of expression-mediated heritability enrichment across functional gene sets that implicate specific gene sets in disease, including loss-of-function intolerant genes and FDA-approved drug targets. Our results demonstrate that eQTLs estimated from steady-state expression levels in bulk tissues are informative of regulatory disease mechanisms, but that such eQTLs are insufficient to explain the majority of disease heritability. Instead, additional assays are necessary to more fully capture the regulatory effects of GWAS variants.

The role of gene expression on human sexual dimorphism: too early to call

“…Our results suggest that sex-specific eQTLs in whole blood do not translate to detectable sex-specific trait associations, and vice versa that the observed sex-specific trait associations cannot be explained by sex-specific eQTLs. While a recent work revealed that ~11% of trait heritability could be explained by cis-eQTL regulation [26], our findings show that the sex-specific heritability is not detectably mediated by sex-specific gene expression regulation. Our extensive power analyses, performed using a range of realistic effect sizes, confirmed these observations.…”

Transcriptomic Insight Into the Polygenic Mechanisms Underlying Psychiatric Disorders

“…Finally, these methods assume that genetic risk for disease is mediated through regulation of gene expression. Yet, recent evidence suggests that the overall proportion of disease heritability mediated by cis-eQTLs is much lower than previously thought, around w10% in SCZ at least with current bulk tissue reference panels (66). The missing signal may be explained by distal QTLs, by missing cis-eQTLs for lowly expressed genes (e.g., ncRNAs), by those not captured in bulk tissue (cell typespecific QTLs) (23,67), or in distinct biological contexts, such as the fetal brain (37).…”

eQTL Catalogue: a compendium of uniformly processed human gene expression and splicing QTLs

“…Systematic colocalisation efforts based on GTEx data have identified putative target genes for 47% of the GWAS loci (3). Still, these genetic effects mediate only 11% of disease heritability (4), suggesting that many regulatory effects cannot be detected in bulk tissues at a steady-state (5). In contrast, profiling specialised disease-relevant cell types such as induced pluripotent stem cells (6), peripheral immune cells (7), microglia (8,9) or dopaminergic neurons (10) often identifies additional colocalisations that are missing in GTEx.…”