Background This study focuses on the identification of conserved genes involved in myocardial infarction (MI), and then analyzed the differentially expressed genes (DEGs) between the incident and recurrent events to identify MI-recurrent biomarkers. Methods Gene expression data of MI peripheral blood were downloaded from GSE97320 and GSE66360 datasets. We identified the common DEGs in these two datasets by functional enrichment analysis and protein–protein interaction (PPI) network analysis. GSE48060 was further analyzed to validate the conserved genes in MI and to compare the DEGs between the incident and recurrent MI. Results A total of 477 conserved genes were identified in the comparison between MI and control. Protein–protein interaction (PPI) network showed hub genes, such as MAPK14 , STAT3 , and MAPKAPK2 . Part of those conserved genes was validated in the analysis of GSE48060. The DEGs in the incident and recurrent MI showed significant differences, including RNASE2 and A2M - AS1 as the potential biomarkers of MI recurrence. Conclusions The conserved genes in the pathogenesis of MI were identified, benefit for target therapy. Meanwhile, some specific genes may be used as markers for the prediction of recurrent MI. Electronic supplementary material The online version of this article (10.1186/s40001-019-0381-x) contains supplementary material, which is available to authorized users.
ABSTRACT. Previous research has focused on revealing the functions of each individual gene and/or pathway in idiopathic dilated cardiomyopathy (DCM) or ischemic cardiomyopathy (IC). However, the common or specific pathways of the initiation and processes of DCM and IC are still unclear. Here, we attempted to uncover the critical genes and potential molecular networks that play important roles in DCM and IC progression commonly or specifically. The transcriptional profiles from normal and DCM or IC patient samples were analyzed and compared using bioinformatic methods. Initially, the normal and DCM or IC sample data were processed and the most notable differentially expressed genes (DEGs) from DCM or IC were identified. By comparing the DEGs from DCM with those from IC, the DCM-and IC-specific DEGs were identified. The gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses indicated the significance of multiple biological processes as well as signaling pathways that affect heart function and DCM or IC progression. Protein-protein interaction network analysis identified the relationships between different genes, and some important genes such as MYC and FN1 were found to be hubs, which master each individual module of DCM-specific and ICspecific DEGs, respectively. We discovered commonalities and differences of gene expression profiles and molecular pathways between different cardiomyopathies. The gene discovery and molecular signature analysis in this study could offer insights into disease mechanisms and also identify markers useful for diagnostic, prognostic, and therapeutic purposes.
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