In recent decades, many genome-wide association studies on insomnia have reported numerous genes harboring multiple risk variants. Nevertheless, the molecular functions of these risk variants conveying risk to insomnia are still ill-studied. In this study, we integrated GWAS summary statistics (N = 386,533) with two independent brain expression quantitative trait loci (eQTL) datasets (N = 329) to determine whether expression-associated SNPs convey risk to insomnia. Furthermore, we applied numerous bioinformatics analyses to highlight promising genes associated with insomnia risk. By using Sherlock integrative analysis, we detected 449 significant insomnia-associated genes in the discovery stage. These identified genes were significantly overrepresented in 6 biological pathways including Huntington’s disease (P = 5.58×10-5), Alzheimer’s disease (P = 5.58×10-5), Parkinson’s disease (P = 6.34×10-5), spliceosome (P = 1.17×10-4), oxidative phosphorylation (P = 1.09×10-4), and wnt signaling pathways (P = 2.07×10-4). Further, 5 of these identified genes were replicated in an independent brain eQTL dataset. Through a PPI network analysis, we found that there existed highly functional interactions among these 5 identified genes. 3 genes of LDHA (P = 0.044), DALRD3 (P = 5.0×10-5) and HEBP2 (P = 0.032) showed significantly lower expression in brain tissues of insomnic patients than that in controls. In addition, the expression levels of these 5 genes showed prominently dynamic changes across different time points between behavioral states of sleep and sleep deprivation in mice brain cortex. Together, this study strongly suggested that these 5 identified genes may represent candidate genes and contributed risk to the etiology of insomnia.