Identifying therapeutic target genes for stroke through systematic druggable Mendelian randomization analysis.

Stroke remains a major cause of mortality and disability, highlighting the need for new therapeutic targets. This study aimed to systematically identify druggable genes causally associated with stroke risk using genetic and transcriptomic data. A total of 5883 druggable genes were compiled from the Drug-Gene Interaction Database and previous reviews. We integrated data from a large-scale stroke GWAS with blood and brain expression quantitative trait loci (eQTLs) for druggable genes and performed a two-sample Mendelian randomization analysis using eQTLs as genetic instruments for gene expression. Significant findings were validated using colocalization analysis. Expression of prioritized genes was further examined in external bulk (GSE140275) and single-cell (GSE174574) RNA-seq datasets. Finally, protein-protein interaction networks and the Drug Signature Database were employed for downstream functional and therapeutic prediction. The intersection of eQTL data identified 3453 genes in blood and 3150 genes in brain tissues. Mendelian randomization analysis identified ten gene-stroke associations (3 in blood, 7 in brain). Colocalization analysis supported a shared causal variant for 5 of these genes, indicated by high posterior probability of hypothesis 4 values, suggesting potential pathogenic roles. The protein-protein interaction network highlighted 5 core druggable genes (protein tyrosine kinase 2, cyclin-dependent kinase 6, ring finger protein 43, papilin proteoglycan-like sulfated glycoprotein, and coagulation factor II) interacting with 20 predicted genes. Myosin light chain kinase inhibitor 7 and staurosporine were the 2 most significant compounds interacting with these genes, followed by simvastatin and cortisol succinate. This study uncovered potential stroke mechanisms and therapeutic targets using integrated multi-omics data, providing a foundation for future clinical applications and drug development strategies. Five druggable genes were identified in stroke (protein tyrosine kinase 2, cyclin-dependent kinase 6, ring finger protein 43, papilin proteoglycan-like sulfated glycoprotein, and coagulation factor II). Myosin light chain kinase inhibitor 7, staurosporine, simvastatin, and cortisol succinate were identified as potential drug candidates for stroke. These results could add additional tools to manage stroke.