An alternative framework for transcriptome-wide association studies to detect and decipher gene-trait associations

Abstract

Transcriptome-wide association studies (TWAS) are widely used to uncover transcriptomic mechanisms underlying disease. Here, we present VINTAGE, an alternative TWAS framework designed to identify and decipher gene-trait associations through two complementary tests: a genetic variance test that generalizes TWAS and unifies it with SKAT, offering a clearer understanding of TWAS false signals when expression is not relevant to SNP-trait associations; and a local genetic correlation test that distinguishes it from TWAS by explicitly quantifying and testing the proportion of genetic effects on trait mediated through gene expression. Applied to eQTLGen and eighteen traits from UK Biobank, VINTAGE improved gene-trait association power by an average of 5% and 87% over SKAT and TWAS, respectively. VINTAGE is also the only method effective in assessing potential gene mediation effects, revealing that most genes lack detectable mediation effects (median = 12%), which explains the power advantage of VINTAGE and SKAT over TWAS. Notably, VINTAGE identified 61 genes with significant mediation, highlighting the role of expression in genetic influences on traits.