While trans-eQTLs are useful for the identification of the distal effects of a single variant, a different approach is required to determine the combined consequences of all variants associated with a polygenic trait. Polygenic scores (PGSs) summarize genome-wide combined risk for a complex disease into a single metric that may be used to stratify individuals into groups11,12. The recently proposed omnigenic model13,14 postulates that the heritability of most complex traits is dominated by numerous weak trans-effects and hypothesizes that those effects converge on a smaller set of trait-relevant ‘core’ genes. This suggests that associations between PGSs and gene expression (expression quantitative trait scores, eQTS) could help to prioritize putative trait-relevant genes (Supplementary Note, Liu et al.14). While it remains unclear what fraction of the genome affects complex traits, we here systematically investigated trans-eQTLs and eQTS to determine how genetic effects regulate genes and pathways, and whether these effects could be informative about the biology of the respective traits.
