Prioritization of microRNA biomarkers for a prospective evaluation in a cohort of myocardial infarction patients based on their mechanistic role using public datasets

BACKGROUND: MicroRNAs (miR) have proven to be promising biomarkers for several diseases due to their diverse functions, stability and tissue/organ-specific nature. Identification of new markers with high sensitivity and specificity will help in risk reduction in acute myocardial infarction (AMI) patients with chest pain and also prevent future adverse outcomes. Hence the aim of this study was to perform a detailed in silico analysis for identifying the mechanistic role of miRs involved in the pathogenesis/prognosis of AMI for prospective evaluation in AMI patients. METHODS: miR profiling data was extracted from GSE148153 and GSE24591 datasets using the GEO2R gene expression omnibus repository and analyzed using limma algorithm. Differentially expressed miRs were obtained by comparing MI patients with corresponding controls after multiple testing corrections. Data mining for identifying candidate miRs from published literature was also performed. Target prediction and gene enrichment was done using standard bioinformatics tools. Disease specific analysis was performed to identify target genes specific for AMI using open targets platform. Protein-protein interaction and pathway analysis was done using STRING database and Cytoscape platform. RESULTS AND CONCLUSION: The analysis revealed significant miRs like let-7b-5p, let-7c-5p, miR-4505, and miR-342-3p in important functions/pathways including phosphatidylinositol-3-kinase/AKT and the mammalian target of rapamycin, advanced glycation end products and its receptor and renin–angiotensin–aldosterone system by directly targeting angiotensin II receptor type 1, forkhead box protein O1, etc. With this approach we were able to prioritize the miR candidates for a prospective clinical association study in AMI patients of south Indian origin.