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Identification of biomarkers for ischemic cardiomyopathy based on microarray data analysis.
Cardiology Journal 2017
BACKGROUND: The aim of this study was to explore the biomarkers and potential mechanism underlying ischemic cardiomyopathy (ICM).
METHODS: Using the GSE42955 Affymetrix microarray data accessible from the Gene Expression Omnibus database, the differentially expressed genes between 12 ICM tissue samples and 5 normal controls were identified. To investigate the function changes in the course of disease progression, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the differentially expressed genes, followed by analysis of the protein-protein interaction (PPI) network and modules.
RESULTS: A total of 50 up-regulated and 179 down-regulated genes were identified. The biological processes of immune response, response to virus, and cell adhesion molecules (CAMs) were significantly altered by the differentially expressed genes. The PPI network revealed certain hub nodes such as CXCL10, IRF1, STAT1, IFIT2, and IFIT3.
CONCLUSIONS: Candidate biomarker genes such as CXCL10, IRF1, STAT1, IFIT2, and IFIT3 may be suitable therapeutic targets for ICM. Further study of the CAMs pathway and immune response biological processes will be helpful in understanding the pathogenesis of ICM.
METHODS: Using the GSE42955 Affymetrix microarray data accessible from the Gene Expression Omnibus database, the differentially expressed genes between 12 ICM tissue samples and 5 normal controls were identified. To investigate the function changes in the course of disease progression, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the differentially expressed genes, followed by analysis of the protein-protein interaction (PPI) network and modules.
RESULTS: A total of 50 up-regulated and 179 down-regulated genes were identified. The biological processes of immune response, response to virus, and cell adhesion molecules (CAMs) were significantly altered by the differentially expressed genes. The PPI network revealed certain hub nodes such as CXCL10, IRF1, STAT1, IFIT2, and IFIT3.
CONCLUSIONS: Candidate biomarker genes such as CXCL10, IRF1, STAT1, IFIT2, and IFIT3 may be suitable therapeutic targets for ICM. Further study of the CAMs pathway and immune response biological processes will be helpful in understanding the pathogenesis of ICM.
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