In this study, bioinformatics methods were used to preliminarily screen ischemic stroke (IS)-related differentially expressed genes (DEGs) and hub genes, and then predict potential IS therapeutics. DEGs were screened after transcriptome sequencing (RNA-Seq) in the cortex of the normal group and the bilateral internal carotid artery occlusion (BICAO) group. GO and KEGG enrichment analysis of DEGs were performed and protein interaction networks of DEGs were constructed, and key genes were obtained. Finally, IS related drugs were predicted according to the key genes. A total of 197 significant DEGs were obtained in this study, and enrichment analysis showed that these genes were mainly involved in metabolism, neuroactive ligandreceptor interactions, complement/coagulation cascade and biosynthesis of steroid hormones. DEGs have a close interrelationship, and among the genes most closely related, ORM1, SERPINA1 and GC all participate in the process of inflammation, oxidative stress and apoptosis, which are the key genes in the pathogenesis of IS. Therefore, inflammation, oxidative stress and apoptosis may be closely related to the occurrence and development of IS. It has potential clinical significance for drug treatment targeting hub genes such as ORM1, SERPINA1, and GC.

ischemic stroke  /  RNA-sequencing  /  bioinformatics  /  differentially expressed genes  /  drugs prediction