Co-expression analysis reveals interpretable gene modules controlled by <i>trans</i>-acting genetic variants.

Abstract

Understanding the causal processes that contribute to disease onset and progression is essential for developing novel therapies. Although <i>trans</i>-acting expression quantitative trait loci (<i>trans</i>-eQTLs) can directly reveal cellular processes modulated by disease variants, detecting <i>trans</i>-eQTLs remains challenging due to their small effect sizes. Here, we analysed gene expression and genotype data from six blood cell types from 226 to 710 individuals. We used co-expression modules inferred from gene expression data with five methods as traits in <i>trans</i>-eQTL analysis to limit multiple testing and improve interpretability. In addition to replicating three established associations, we discovered a novel <i>trans</i>-eQTL near <i>SLC39A8</i> regulating a module of metallothionein genes in LPS-stimulated monocytes. Interestingly, this effect was mediated by a transient <i>cis</i>-eQTL present only in early LPS response and lost before the <i>trans</i> effect appeared. Our analyses highlight how co-expression combined with functional enrichment analysis improves the identification and prioritisation of <i>trans</i>-eQTLs when applied to emerging cell-type-specific datasets.