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

ABSTRACT: 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 (FLT1 and MMP2), cell adhesion (CDH1, ITGB6, COL6A3, COL6A1 and LAMC2) and extracellular matrix (ECM)-receptor interaction pathway (CDH1, ITGB6, COL6A3, COL6A1 and LAMC2), 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 MMP2, FLT1, CDH1, ITGB6, COL6A3, COL6A1, LAMC2, PENK and APLNR. 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.

SUBMITTER: Zhuang Y

PROVIDER: S-EPMC5585721 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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

Zhuang Yu Y Gong Yu-Jia YJ Zhong Bei-Fen BF Zhou Yi Y Gong Li L

Experimental and therapeutic medicine 20170728 4

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, follo ...[more]

PMID: 28912841

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Project description:Objective: To explore immune-related feature genes in patients with dilated cardiomyopathy (DCM). Methods: Expression profiles from three datasets (GSE1145, GSE21610 and GSE21819) of human cardiac tissues of DCM and healthy controls were downloaded from the GEO database. After data preprocessing, differentially expressed genes (DEGs) were identified by the ‘limma’ package in R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were then performed to identify biological functions of the DEGs. The compositional patterns of stromal and immune cells were estimated using xCell. Hub genes and functional modules were identified based on protein-protein interaction (PPI) network analysis by STRING webtool and Cytoscape application. Correlation analysis was performed between immune cell subtypes and hub genes. Hub genes with |correlation coefficient| > 0.5 and p value <0.05 were selected as feature biomarkers. A logistic regression model was constructed based on the selected biomarkers and validated in datasets GSE5406 and GSE57338. Results: A total of 1,005 DEGs were identified. Functional enrichment analyses indicated that extracellular matrix remodeling and immune and inflammation disorder played important roles in the pathogenesis of DCM. Immune cells, including CD8+ T-cells, macrophages M1 and Th1 cells, were proved to be significantly changed in DCM patients by immune cell infiltration analysis. In the PPI network analysis, STAT3, IL6, CCL2, PIK3R1, ESR1, CCL5, IL17A, TLR2, BUB1B and MYC were identified as hub genes, among which CCL2, CCL5 and TLR2 were further screened as feature biomarkers by using hub genes and immune cells correlation analysis. A diagnosis model was successfully constructed by using the three biomarkers with area under the curve (AUC) scores 0.981, 0.867 and 0.946 in merged dataset, GSE5406 and GSE57338, respectively. Conclusion: The present study identified three immune-related genes as diagnostic biomarkers for DCM, providing a novel perspective of immune and inflammatory response for the exploration of DCM molecular mechanisms.

Dataset Information

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

Publications

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

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