Integration of genetically regulated gene expression and pharmacological library provides therapeutic drug candidates

Abstract

Approaches toward new therapeutics using disease genomics, such as genome-wide association study (GWAS), are anticipated. Here, we developed Trans-Phar [integration of transcriptome-wide association study (TWAS) and pharmacological database], achieving in silico screening of compounds from a large-scale pharmacological database (L1000 Connectivity Map), which have inverse expression profiles compared with tissue-specific genetically regulated gene expression. Firstly we confirmed the statistical robustness by the application of the null GWAS data and enrichment in the true-positive drug-disease relationships by the application of UK-Biobank GWAS summary statistics in broad disease categories, then we applied the GWAS summary statistics of large-scale European meta-analysis (17 traits; naverage = 201 849) and the hospitalized COVID-19 (n = 900 687), which has urgent need for drug development. We detected potential therapeutic compounds as well as anisomycin in schizophrenia (false discovery rate (FDR)-q = 0.056) and verapamil in hospitalized COVID-19 (FDR-q = 0.068) as top-associated compounds. This approach could be effective in disease genomics-driven drug development.