It remains unknown to what extent gene-gene interactions contribute to complex traits. Here, we introduce a new approach using predicted gene expression to perform exhaustive transcriptome-wide interaction studies (TWISs) for multiple traits across all pairs of genes expressed in several tissue types. Using imputed transcriptomes, we simultaneously reduce the computational challenge and improve interpretability and statistical power. We discover and replicate several interaction associations and find several hub genes with numerous interactions. We also demonstrate that TWIS can identify novel associated genes because genes with many or strong interactions have smaller single-locus model effect sizes. Finally, we develop a method to test gene set enrichment of TWIS associations (E-TWIS), finding numerous pathways and networks enriched in interaction associations. Epistasis is likely widespread, and our procedure represents a tractable framework for beginning to explore gene interactions and identify novel genomic targets.

We developed Transcriptome-Wide Interaction Study (TWIS), a new method that comprehensively tests associations of all pairwise gene-gene interactions with complex traits using imputed expression. We applied the method to 12 complex traits in humans across four tissues/cross-tissue expression measures. We applied the method to multiple datasets, then meta-analyzed the results using METAL.

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Transcriptome-wide interaction study (TWIS): code available at https://github.com/evanslm/TWIS.