Integrative Multi-Omics and Mendelian Randomization Analysis Identify Core Genes and Potent Drug Targets for Insomnia

Insomnia is a prevalent sleep disorder with limited specific therapeutic targets. This study integrated druggable genes, multi-tissue QTL data (blood, brain, plasma), insomnia-related GWAS summary statistics, transcriptome data and bioinformatics methods including two-sample Mendelian randomization (MR), WGCNA, differential expression analysis, machine learning (LASSO regression, random forest), SMR, colocalization, immune infiltration analysis and molecular docking. We aimed to screen core causal genes and potential drug targets for insomnia, explore the mechanism linking key genes to immune infiltration and insomnia comorbidities (depression, anxiety, hypertension, type 2 diabetes), and validate gene expression via RT-qPCR. This study follows STROBE-MR guidelines for rigorous causal inference.