Literature DB >> 28150292

Identification of biomarkers for ischemic cardiomyopathy based on microarray data analysis.

Yushuang Yang, Wei Yang, Wenxin Huo, Pengfei Huo1, Hailing Yang.   

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.

Entities:  

Keywords:  differentially expressed genes; ischemic cardiomyopathy; pathways; protein–protein interactions

Mesh:

Substances:

Year:  2017        PMID: 28150292     DOI: 10.5603/CJ.a2017.0005

Source DB:  PubMed          Journal:  Cardiol J        ISSN: 1898-018X            Impact factor:   2.737


  3 in total

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Authors:  Federica Raggi; Davide Cangelosi; Pamela Becherini; Fabiola Blengio; Martina Morini; Massimo Acquaviva; Maria Luisa Belli; Giuseppe Panizzon; Giuseppe Cervo; Luigi Varesio; Alessandra Eva; Maria Carla Bosco
Journal:  J Transl Med       Date:  2020-01-10       Impact factor: 5.531

3.  Identification of key molecular markers of acute coronary syndrome using peripheral blood transcriptome sequencing analysis and mRNA-lncRNA co-expression network construction.

Authors:  Ming Shen; Rui Gong; Haibin Li; Zhihui Yang; Yunpeng Wang; Dandan Li
Journal:  Bioengineered       Date:  2021-12       Impact factor: 3.269

  3 in total

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