International Journal of General Medicine (Sep 2021)

Bioinformatics Analysis and Identification of Genes and Pathways in Ischemic Cardiomyopathy

  • Cao J,
  • Liu Z,
  • Liu J,
  • Li C,
  • Zhang G,
  • Shi R

Journal volume & issue
Vol. Volume 14
pp. 5927 – 5937

Abstract

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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 [email protected]: 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-regulated genes, respectively. Thirty DEGs were screened from GSE5406, including 10 genes with up-regulated expression and 20 genes with down-regulated expression. Five up-regulated and 3 down-regulated co-expressed DEGs were intersected in three datasets. GO and KEGG pathway analyses revealed that DEGs are mainly enriched in collagen fibril organization, protein digestion and absorption, AGE-RAGE signaling pathway and other related pathways. Collagen alpha-1(III) chain (COL3A1), collagen alpha-2(I) chain (COL1A2) and lumican (LUM) are the three hub genes in all three datasets through PPI network analysis. The expression of 5 DEGs (SERPINA3, FCN3, COL3A1, HBB, MXRA5) in heart tissues by qRT-PCR results was consistent with our GEO analysis, while expression of 3 DEGs (ASPN, LUM, COL1A2) was opposite with GEO analysis.Conclusion: These findings from this bioinformatics network analysis investigated key hub genes, which contributed to better understanding the mechanism and new therapeutic targets of ICM.Keywords: ischemic cardiomyopathy, differential expressed genes, bioinformatics analysis

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