Integrative Multi-Omics Approach for Improving Causal Gene Identification.

ABSTRACT: Transcriptome-wide association studies (TWAS) have been widely used to identify thousands of likely causal genes for diseases and complex traits using predicted expression models. However, most existing TWAS methods rely on gene expression alone and overlook other regulatory mechanisms of gene expression, including DNA methylation and splicing, that contribute to the genetic basis of these complex traits and diseases. Here we introduce a multi-omics method that integrates gene expression, DNA methylation, and splicing data to improve the identification of associated genes with our traits of interest. Through simulations and by analyzing genome-wide association study (GWAS) summary statistics for 24 complex traits, we show that our integrated method, which leverages these complementary omic

SUBMITTER: King A 

PROVIDER: S-EPMC11659073 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature