open access

Vol 24, No 3 (2017)
Original articles — Basic science and experimental cardiology
Published online: 2017-01-11
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Identification of biomarkers for ischemic cardiomyopathy based on microarray data analysis

Yushuang Yang, Wei Yang, Wenxin Huo, Pengfei Huo, Hailing Yang
DOI: 10.5603/CJ.a2017.0005
·
Pubmed: 28150292
·
Cardiol J 2017;24(3):305-313.

open access

Vol 24, No 3 (2017)
Original articles — Basic science and experimental cardiology
Published online: 2017-01-11

Abstract

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

 

Abstract

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

 

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Keywords

ischemic cardiomyopathy, differentially expressed genes, pathways, protein–protein interactions

About this article
Title

Identification of biomarkers for ischemic cardiomyopathy based on microarray data analysis

Journal

Cardiology Journal

Issue

Vol 24, No 3 (2017)

Pages

305-313

Published online

2017-01-11

DOI

10.5603/CJ.a2017.0005

Pubmed

28150292

Bibliographic record

Cardiol J 2017;24(3):305-313.

Keywords

ischemic cardiomyopathy
differentially expressed genes
pathways
protein–protein interactions

Authors

Yushuang Yang
Wei Yang
Wenxin Huo
Pengfei Huo
Hailing Yang

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