Identification of Potential Core Genes and Promising Compounds in STEMI Using Bioinformatics Analysis

Purpose: The objective of this research was to reveal the fundamental molecular processes and determine the critical pathways and genes for ST-segment elevation myocardial infarction by performing bioinformatics analysis. Methods: The Gene Expression Omnibus Gene (GEO) database was utilized to acquire the microarray data for GSE60993 and GSE61144. The R package limma was employed for the purpose of identifying differentially expressed genes (DEGs). The DAVID database was retrieved to conduct enrichment analyses for both gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. STRING was employed to construct a DEG-related protein-protein interaction (PPI) network, which was then visualized in Cytoscape. The modules belonging to the PPI network were analyzed using MCODE. With the aid of Connectivity Map (CMap), we determined potential medications according to the genes that had previously been identified. Results: A total of 201 downmodulated and 43 upmodulated genes were discovered. The findings from GO and KEGG pathway enrichment analyses demonstrated a significant correlation between the DEGs and immunological responses, inflammatory responses, and pathways such as cytokine-cytokine receptor interface and Hematopoietic cell lineage. MMP9, PGLYRP1, CAMP, FOLR3, ORM1, QPCT, LRG1, ARG1, CDA and S100A12 were determined as the hub genes in the PPI network according to their extent of connectivity. The hub genes that were identified together with their corresponding transcriptional factors included ELF-1, PAX, PEA3, Pu.1, ZF5, EGR-3, Dp-1, FOXP3, etc. Conclusions: The microarray data and bioinformatics analyses conducted in the present research offer a viable option for identifying critical pathways and genes correlated with STEMI.