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Bioinformatics Analysis and Identification of Genes and Pathways in Ischemic Cardiomyopathy

Authors :
Cao,Jing
Liu,Zhaoya
Liu,Jie
Li,Chan
Zhang,Guogang
Shi,Ruizheng
Cao,Jing
Liu,Zhaoya
Liu,Jie
Li,Chan
Zhang,Guogang
Shi,Ruizheng
Publication Year :
2021

Abstract

Jing Cao,1,* Zhaoya Liu,2,* Jie Liu,3 Chan Li,3 Guogang Zhang,1 Ruizheng Shi3 1Department of Cardiovascular Medicine, Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 2Department of Geriatrics, Third Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 3Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ruizheng ShiDepartment of Cardiovascular Medicine, Xiangya Hospital, Central South University, Xiangya Road, Changsha, 410008, Hunan, People’s Republic of ChinaEmail xyshiruizheng@csu.edu.cnPurpose: Ischemic cardiomyopathy (ICM) is considered to be the most common cause of heart failure, with high prevalence and mortality. This study aimed to investigate the different expressed genes (DEGs) and pathways in the pathogenesis of ICM using bioinformatics analysis.Methods: The control and ICM datasets GSE116250, GSE46224 and GSE5406 were collected from the gene expression omnibus (GEO) database. DEGs were identified using limma package of R software, and co-expressed genes were identified using Venn diagrams. Then, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to explore the biological functions and signaling pathways. Protein–protein interaction (PPI) networks were assembled with Cytoscape software to identify hub genes related to the pathogenesis of ICM. RT-PCR of Heart tissues (n=2 for non-failing controls and n=4 for ischemic cardiomyopathy patients) was used to validate the bioinformatic results.Results: A total of 844 DEGs were screened from GSE116250, of which 447 were up-regulated genes and 397 were down-regulated genes, respectively. A total of 99 DEGs were singled out from GSE46224, of which 58 were up-regulated genes and 41 were down-regulate

Details

Database :
OAIster
Notes :
text/html, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1286360017
Document Type :
Electronic Resource