Potential biomarkers of acute myocardial infarction based on co‑expression network analysis

Hu,Zhaohui; Liu,Ruhui; Hu,Hairong; Ding,Xiangjun; Ji,Yuyao; Li,Guiyuan; Wang,Yiping; Xie,Shengquan; Liu,Xiaohong; Ding,Zhiwen

doi:10.3892/etm.2021.11085

Potential biomarkers of acute myocardial infarction based on co‑expression network analysis

Authors:
- Zhaohui Hu
- Ruhui Liu
- Hairong Hu
- Xiangjun Ding
- Yuyao Ji
- Guiyuan Li
- Yiping Wang
- Shengquan Xie
- Xiaohong Liu
- Zhiwen Ding
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Affiliations: Department of Cardiology, Tongji University Affiliated Tongji Hospital, Shanghai 200065, P.R. China, Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Wenzhou Medical University, Ruian, Zhejiang 325200, P.R. China, Department of Cardiology, The West Coast New Area of Qingdao Traditional Chinese Medicine Hospital, Qingdao, Shandong 266500, P.R. China, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China, Cardiovascular Department of Internal Medicine, Central Hospital of Karamay, Karamay, Xinjiang 834000, P.R. China
Published online on: December 21, 2021 https://doi.org/10.3892/etm.2021.11085
Article Number: 162
Copyright: © Hu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Acute myocardial infarction (AMI) is a common cause of death in numerous countries. Understanding the molecular mechanisms of the disease and analyzing potential biomarkers of AMI is crucial. However, specific diagnostic biomarkers have thus far not been fully established and candidate regulatory targets for AMI remain to be determined. In the present study, the AMI gene chip dataset GSE48060 comprising blood samples from control subjects with normal cardiac function (n=21) and patients with AMI (n=26) was downloaded from Gene Expression Omnibus. The differentially expressed genes (DEGs) between the AMI and control groups were identified with the online tool GEO2R. The co‑expression network of DEGs was analyzed by calculating the Pearson correlation coefficient of all gene pairs, mutual rank screening and cutoff threshold screening. Subsequently, the Gene Ontology (GO) database was used to analyze the genes' functions and pathway enrichment of genes in the most important modules was performed. Kyoto Encyclopedia of Genes and Genomes (KEGG) Disease and BioCyc were used to analyze the hub genes in the module to determine important sub‑pathways. In addition, the expression of hub genes was confirmed by reverse transcription‑quantitative PCR in AMI and control specimens. In the present study, 52 DEGs, including 26 upregulated and 26 downregulated genes, were identified. As key hub genes, three upregulated genes (AKR1C3, RPS24 and P2RY12) and three downregulated genes (ACSL1, B3GNT5 and MGAM) were identified from the co‑expression network. Furthermore, GO enrichment analysis of all AMI co‑expression network genes revealed functional enrichment mainly in ‘RAGE receptor binding’ and ‘negative regulation of T cell cytokine production’. In addition, KEGG Disease and BioCyc analysis indicated functional enrichment of the genes RPS24 and P2RY12 in ‘cardiovascular diseases’, of AKR1C3 in ‘cardenolide biosynthesis’, of MGAM in ‘glycogenolysis’, of B3GNT5 in ‘glycosphingolipid biosynthesis’ and of ACSL1 in ‘icosapentaenoate biosynthesis II’. In conclusion, the hub genes AKR1C3, RPS24, P2RY12, ACSL1, B3GNT5 and MGAM are potential markers of AMI, and have potential application value in the diagnosis of AMI.

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