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Myocardial infarction (MI) is the most prevalent coronary heart disease caused by the complex molecular interactions between multiple genes and environment. Here, we aim to identify potential biomarkers for the disease development and for prognosis of MI. We have used gene expression dataset (GSE66360) generated from 51 healthy controls and 49 patients experiencing acute MI and analyzed the differentially expressed genes (DEGs), protein-protein interactions (PPI), gene network-clusters to annotate the candidate pathways relevant to MI pathogenesis. Bioinformatic analysis revealed 810 DEGs. Their functional annotations have captured several MI targeting biological processes and pathways like immune response, inflammation and platelets degranulation. PPI network identify seventeen hub and bottleneck genes, whose involvement in MI was further confirmed by DisGeNET database. OpenTarget Platform reveal unique bottleneck genes as potential target for MI. Our findings identify several potential biomarkers associated with early stage MI providing a new insight into molecular mechanism underlying the disease. Unlabelled Image • Integrated bioinformatic analysis to identify potential biomarkers and/or novel drug targets for complex diseases. • Hubs, bottleneck genes can be useful biomarkers of inflammatory response in the early stage of myocardial infarction (MI). • Prioritized the MI candidate genes with DisGeNET and Open Target Platform. • Identified the key functional pathways for MI to unravel the biological basis of the disease development. • Carriers of variants in the identified MI genes may have increased risk of developing MI. [ABSTRACT FROM AUTHOR]