Targeting myocardial infarction-specific protein interaction network using computational analyses

Myocardial infarction (MI) is a leading cause of deaths in the United States. Currently, the high mortality rate in MI is partially due to the lacking of diagnostic and prognostic biomarkers. Therefore, the purpose of this study was to develop a framework to understand MI-specific protein interaction network and identify MI-specific biomarkers with public databases and literatures. We established an MI-specific protein interaction network, examined the statistical significance of the MI-specific network compared to random networks, and evaluated the importance of the MI-specified proteins with its network properties and research intensity. The established MI-specific protein interaction network had less sub-networks and more links in addition to higher measurements on closeness centrality, clustering coefficient and degree centrality, suggesting a strong connectivity of hub proteins, which confirmed the determination of key proteins based on structural evaluation. In summary, this study established a framework to integrate published data in literatures and provided a promising way to identify biomarkers post-myocardial infarction.