Research Paper Volume 12, Issue 19 pp 19440—19454

Weighted gene coexpression network analysis identifies the key role associated with acute coronary syndrome

Yong Wang1, *, , Liu Miao1, *, , Lin Tao1, , Jian-Hong Chen1, , Chuan-Meng Zhu1, , Ye Li1, , Bin Qi1, , Fei Liao1, , Rong-Shan Li1, ,

  • 1 Departments of Cardiology, Liuzhou People’s Hospital, Liuzhou 545006, Guangxi, People’s Republic of China
* Equal contribution

Received: May 6, 2020       Accepted: July 21, 2020       Published: October 14, 2020
How to Cite

Copyright: © 2020 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


The present study sought to identify potential hub genes and pathways of acute coronary syndrome (ACS). We downloaded the dataset (GSE56045) from the Gene Expression Omnibus (GEO) database and analyzed weighted gene coexpression networks (WGCNA). Gene Ontology annotation, Disease Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R software. The protein-protein interaction (PPI) network was constructed using Cytoscape, and the Molecular Complex Detection app was employed to identify significant modules and hub genes. The hub genes were then validated in other microarrays and patients by RT–PCR. Two modules were identified and associated with coronary artery disease (CAD) and included 219 genes. After function and PPI analyses, 24 genes were identified to be potentially associated with CAD. Linear correlation was performed to calculate the relationship between the gene expression levels and coronary artery calcification score and found that CCR7 (R = -0.081, P = 0.0065), CD2 (R = -0.075, P = 0.0012), CXCR5 (R = -0.065, P = 0.029) and IL7R (R = -0.06, P = 0.043) should be validated in other dataset. By comparing the gene expression levels in different groups in GSE23561, GSE34822, GSE59867, GSE60993 and GSE129935, only two genes (CCR7 and CXCR5) showed significance. The nomogram showed that CXCR5 showed the risk of ACS. Further analysis in chest patients found CXCR5 played a key role resulting in ACS. Our WGCNA analysis identified CXCR5 as a risk factor for ACS, and the potential pathogenesis may be associated with immune inflammation.


Apo: apolipoprotein; BMI: body mass index; ACS: acute coronary syndrome; CAD: coronary artery disease; CAMs: Cell adhesion molecules; DO: disease ontology; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GEO: Gene Expression Omnibus; GO: gene ontology; HDL-C: high-density lipoprotein cholesterol; KEGG: Kyoto Encyclopedia of Genes and genomes; LDL-C: low-density lipoprotein cholesterol; MAPK: Mitogen activated protein kinase; MCODE: molecular complex detection; MI: myocardial infarction;; PPI: protein-protein interaction; PTPRC: protein tyrosine phosphatase receptor type C; qRT-PCR: quantitative real-time PCR; TC: total cholesterol; TG: triglyceride.