Abstract
Disease variants identified by genome-wide association studies (GWAS) tend to overlap with expression quantitative trait loci (eQTLs), but it remains unclear whether this overlap is driven by gene expression levels mediating genetic effects on disease. Here we introduce a new method, mediated expression score regression (MESC), to estimate disease heritability mediated by the cis-genetic component of gene expression levels. We applied MESC to GWAS summary statistics for 42 traits (average N = 323K) and cis-eQTL summary statistics for 48 tissues from the Genotype-Tissue Expression (GTEx) consortium. Averaging across traits, only 11±2% of heritability was mediated by assayed gene expression levels. Expression-mediated heritability was enriched in genes with evidence of selective constraint and genes with disease-appropriate annotations. Our results demonstrate that assayed bulk-tissue eQTLs, though disease relevant, cannot explain the majority of disease heritability.
Highlights
In the past decade, genome-wide association studies (GWAS) have shown that most disease-associated variants lie in noncoding regions of the genome[1,2,3], leading to the hypothesis that regulation of gene expression levels is the primary biological mechanism through which genetic variants affect complex traits, and motivating large scale expression quantitative trait loci studies[4, 5]
In the above definition of h2med, which we call h2med;causal, we assume that cis-expression quantitative trait loci (eQTL) effect sizes are taken in the causal cell types/contexts for the disease, which is the natural setting in which we conceptualize a model of mediation via gene expression levels
We have developed a new method, mediated expression score regression (MESC), to estimate complex trait heritability mediated by the cis-genetic component of assayed expression levels (h2med) from GWAS summary statistics and eQTL effect sizes estimated from an external expression panel
Summary
Genome-wide association studies (GWAS) have shown that most disease-associated variants lie in noncoding regions of the genome[1,2,3], leading to the hypothesis that regulation of gene expression levels is the primary biological mechanism through which genetic variants affect complex traits, and motivating large scale expression quantitative trait loci (eQTL) studies[4, 5]. The copyright holder for this preprint It is made available under are eQTLs)[17,18,19,20] Application of these methods to eQTL and GWAS data has shown that many genes have eQTLs that colocalize with GWAS loci[6,7,8,9,10] and/or exhibit significant cis-genetic correlations between their expression and trait[11,12,13,14,15,16, 21,22,23,24,25,26,27,28], while showing that eQTLs as a whole are significantly enriched for disease heritability[17,18,19,20]
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