Exploration Of Potential Biomarkers Involved In Acute Myocardial Infarction

Objective: The aim of the current study was to screen potential novel biomarkers involved in AMI. Methods: Microarray data of AMI (GSE66360) was obtained from the Gene Expression Omnibus (GEO) database. Usingthe limma package, differentially-expressed genes (DEGs) between samples from AMI and healthy controls were screened. Based on the DAVID tool, functional analysis was carried out Protein-protein interaction (PPI) and transcription factor (TF)-miRNA-target gene regulatory networks were visualized using Cytoscape software. Finally, drug gene interactions were predicted using the DGIdb database. Results: A total of 339 DEGs between samples from AMI and healthy controls were identified. Upregulated DEGs were mainly enriched in 32 pathways, including osteoclast differentiation, TNF signaling pathways, and transcriptional mis regulation in cancer. Cytokine-cytokine receptor interaction was the main functional enrichment for downregulated DEGs. IL8, JUN, IL1B, TNF, and FOS were key nodes in the PPI network. In addition, three miRNAs, including has-miR-191, has-miR-101, and has-miR-20, nine TFs, including NFKAPPAB, SRF, IK3, and NFKAPPAB65, and 34 regulatory relationship pairs were integrated. Prediction results revealed that TNF, IL1B, and TLR4 might be potential druggable genes for AMI patients. Conclusion: IL8, JUN, IL1B might be novel markers for atherosclerotic plaque instability. MicroRNAs, including miR-191, miR-101, and miR-20, might provide a window for exploration of potential biomarkers for diagnosis and prognosis for AMI patients.