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The incidence of ischemic stroke (IS) is escalating rapidly, and glycolysis significantly influences the pathogenesis and prognosis of these patients. However, current methods for assessing this are insufficient. This study aimed to identify molecular biomarkers of glycolysis in patients with IS. We retrieved relevant data from the Gene Expression Omnibus database and identified differentially expressed genes (DEGs). Gene set enrichment analysis was conducted on all genes within the integrated Gene Expression Omnibus dataset. Glycolysis-related differentially expressed genes (GRDEGs) were subjected to gene ontology and pathway analysis (Kyoto Encyclopedia of Genes and Genomes) to determine the functions of DEGs. The protein-protein interaction network of GRDEGs was established using the STRING database. The miRNAs of glycolysis-associated hub genes were acquired from the StarBase and miRDB databases, followed by an analysis of the relationship between glycolysis-related core genes and miRNAs. The mRNA-miRNA regulatory network was visualized. Lastly, a cross-comparison of immune-related genes and GRDEGs in IS was conducted to compare immune cell infiltration between the 2 groups. In the IS group, there were 42 up-regulated genes, 73 down-regulated genes, and 27 GRDEGs compared with the control group. These genes are involved in regulating various biological processes and signaling pathways. The protein-protein interaction network identified 7 hub genes related to glycolysis, including C-C motif chemokine receptor 7, ribosomal protein S3, and ribosomal protein SA, which also have immune correlations. Ribosomal protein SA, ribosomal protein S3, eukaryotic translation elongation factor 1 gamma, CD163, arginase 1, C-C motif chemokine receptor 7, and matrix metallopeptidase 9 are the hub genes related to glycolysis in IS. Our research will contribute to the discovery of potential biomarkers and fresh approaches to the clinical management of IS.