Identification of Hypoxia-related Genes in Acute Myocardial Infarction using Bioinformatics Analysis.

Abstract

Acute myocardial infarction (AMI) remains one of the most fatal diseases worldwide. Persistent ischemia and hypoxia are implicated as significant mechanisms in the development of AMI. However, no hypoxia-related gene targets of AMI have been identified to date. This study aimed to identify potential genes and drugs for AMI using bioinformatics analysis. Two datasets both related to AMI (GSE76387 and GSE161427) were downloaded from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) between AMI and sham mice. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. A protein-protein interaction (PPI) network was constructed to identify hub genes using Cytoscape. Candidate genes were identified by the intersection of hub genes and hypoxia-related genes. Western blotting was used to validate the candidate genes in the AMI mouse model. Furthermore, the Drug-Gene Interaction Database was used to predict potential therapeutic drugs targeting all hub genes. Fifty-three upregulated and 16 downregulated genes closely related to AMI were identified. The DEGs were primarily enriched in protein, heparin, and integrin binding. KEGG analysis suggested that focal adhesion, PI3K-Akt signaling pathway, and extracellular matrix-receptor interaction are crucial pathways for AMI. The PPI network analysis identified 14 hub genes, two of which were hypoxia-related. Several agents were found to have therapeutic potential for AMI. This study suggests that connective tissue growth factors and the collagen family members may be candidate targets in treating AMI. Agents targeting these candidates may be potential treatments.