Rui Yan; Jiahui Song; Ming Guo; Minghui Hao

doi:10.14715/cmb/2022.69.1.17

Issue

Vol. 69 No. 1: Issue 1

Issue Published : May 9, 2023

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Bioinformatics Analysis of Differentially Expressed Genes in Ischemic Cardiomyopathy Using GEO Database

Genes expression in cardiomyopathy using the GEO database

https://doi.org/10.14715/cmb/2022.69.1.17

Rui Yan

Department of Cardiology, Beijing Luhe Hospital, Capital Medical University, Beijing, 101199, China

Jiahui Song

Department of Cardiology, Beijing Luhe Hospital, Capital Medical University, Beijing, 101199, China

Ming Guo

Department of Cardiology, Beijing Luhe Hospital, Capital Medical University, Beijing, 101199, China

Minghui Hao

Department of Cardiology, Beijing Luhe Hospital, Capital Medical University, Beijing, 101199, China

Corresponding Author(s) : Rui Yan

yanrui_med@ccmu.edu.cn

Cellular and Molecular Biology, Vol. 69 No. 1: Issue 1
Article Published : January 31, 2023

Abstract

It was to analyze differentially expressed genes and their expression characteristics in ischemic cardiomyopathy (ICM) by bioinformatics and provide targets for drug therapy of ICM. For this purpose, the gene expression data of ICM in the gene expression omnibus (GEO) database were used, the differentially expressed genes between healthy myocardium and ICM myocardium were screened by R language, and then the differentially expressed genes were analyzed by protein-protein interaction (PPI), gene ontology (GO), and KEGG to select the key genes. Results showed that the useful genes of ICM were successfully screened in the GEO database, and KEGG pathway analysis was performed for the differentially expressed genes in ICM tissues, including the main pathways: viral carcinogenesis, energy metabolism, viral response, oxidative phosphorylation, influenza A, extracellular matrix receptor interaction, Epstein-Barr virus infection, chemokine receptor pathway, phagosome, proteasome, and protein digestion and absorption. PPI network analysis showed that C3, F5, FCGR3A, APOB, PENK, LUM, CHRDL1, FCGR3A, CIQB, and FMOD were critical genes. In conclusion, bioinformatics can screen out the key genes in ICM, which is helpful to understand the treatment of drug targets in ICM patients.

Keywords

bioinformatics differential expression ischemic cardiomyopathy (ICM) database gene expression

Yan, R., Song, J., Guo, M., & Hao, M. (2023). Bioinformatics Analysis of Differentially Expressed Genes in Ischemic Cardiomyopathy Using GEO Database: Genes expression in cardiomyopathy using the GEO database. Cellular and Molecular Biology, 69(1), 98–103. https://doi.org/10.14715/cmb/2022.69.1.17