Bioinformatics method identifies potential biomarkers of dilated cardiomyopathy in a human induced pluripotent stem cell-derived cardiomyocyte model.

Dilated cardiomyopathy (DCM) is the most common type of cardiomyopathy that account for the majority of heart failure cases. The present study aimed to reveal the underlying molecular mechanisms of DCM and provide potential biomarkers for detection of this condition. The public dataset of GSE35108 was downloaded, and 4 normal induced pluripotent stem cell (iPSC)-derived cardiomyocytes (N samples) and 4 DCM iPSC-derived cardiomyocytes (DCM samples) were utilized. Raw data were preprocessed, followed by identification of differentially expressed genes (DEGs) between N and DCM samples. Crucial functions and pathway enrichment analysis of DEGs were investigated, and protein-protein interaction (PPI) network analysis was conducted. Furthermore, a module network was extracted from the PPI network, followed by enrichment analysis. A set of 363 DEGs were identified, including 253 upregulated and 110 downregulated genes. Several biological processes (BPs), such as blood vessel development and vasculature development ( and ), cell adhesion (, , , and ) and extracellular matrix (ECM)-receptor interaction pathway (, , , and ), were significantly enriched by these DEGs. Among them, MMP2, CDH1 and FLT1 were hub nodes in the PPI network, while COL6A3, COL6A1, LAMC2 and ITGB6 were highlighted in module 3 network. In addition, PENK and APLNR were two crucial nodes in module 2, which were linked to each other. In conclusion, several potential biomarkers for DCM were identified, such as , , , , , , , and . These genes may serve significant roles in DCM via involvement of various BPs, such as blood vessel and vasculature development and cell adhesion, and the ECM-receptor interaction pathway.