Identification of 5 hub genes for diagnosis of coronary artery disease

Pengyuan Zhu; Haitao Huang; Tian Xie; Huoqi Liang; Xing Li; Xingyi Li; Hao Dong; Xiaoqiang Yu; Chunqiu Xia; Chongjun Zhong; Zhibing Ming

doi:10.3389/fcvm.2023.1086127

Identification of 5 hub genes for diagnosis of coronary artery disease

Front Cardiovasc Med. 2023 Jul 5:10:1086127. doi: 10.3389/fcvm.2023.1086127. eCollection 2023.

Authors

Pengyuan Zhu^#^{1

2}, Haitao Huang^#³, Tian Xie³, Huoqi Liang³, Xing Li³, Xingyi Li³, Hao Dong³, Xiaoqiang Yu³, Chunqiu Xia³, Chongjun Zhong³, Zhibing Ming³

Affiliations

¹ Department of Thoracic and Cardiovascular Surgery, School of Medicine, The Second Affiliated Hospital of Nantong University, Nantong University, Nantong, China.
² Department of Thoracic and Cardiovascular Surgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
³ Department of Vascular Surgery, The Second Affiliated Hospital of Nantong University, Nantong, China.

^# Contributed equally.

Abstract

Background: Coronary artery disease (CAD) is a main cause leading to increasing mortality of cardiovascular disease (CVD) worldwide. We aimed to discover marker genes and develop a diagnostic model for CAD.

Methods: CAD-related target genes were searched from DisGeNET. Count expression data and clinical information were screened from the GSE202626 dataset. edgeR package identified differentially expressed genes (DEGs). Using online STRING tool and Cytoscape, protein-protein reactions (PPI) were predicted. WebGestaltR package was employed to functional enrichment analysis. We used Metascape to conduct module-based network analysis. VarElect algorithm provided genes-phenotype correlation analysis. Immune infiltration was assessed by ESTIMATE package and ssGSEA analysis. mRNAsi was determined by one class logistic regression (OCLR). A diagnostic model was constructed by SVM algorithm.

Results: 162 target genes were screened by intersection 1,714 DEGs and 1,708 CAD related target genes. 137 target genes of the 162 target genes were obtained using PPI analysis, in which those targets were enriched in inflammatory cytokine pathways, such as chemokine signaling pathway, and IL-17 signaling pathway. From the above 137 target genes, four functional modules (MCODE1-4) were extracted. From the 162 potential targets, CAD phenotype were directly and indirectly associated with 161 genes and 22 genes, respectively. Finally, 5 hub genes (CCL2, PTGS2, NLRP3, VEGFA, LTA) were screened by intersections with the top 20, directly and indirectly, and genes in MCODE1. PTGS2, NLRP3 and VEGFA were positively, while LTA was negatively correlated with immune cells scores. PTGS2, NLRP3 and VEGFA were negatively, while LTA was positively correlated with mRNAsi. A diagnostic model was successfully established, evidenced by 92.59% sensitivity and AUC was 0.9230 in the GSE202625 dataset and 94.11% sensitivity and AUC was 0.9706 in GSE120774 dataset.

Conclusion: In this work, we identified 5 hub genes, which may be associated with CAD development.

Keywords: CAD development; cardiovascular disease; coronary artery disease; diagnosis; gene.

Grants and funding

This subject was funded by Jiangsu Province “Six Talents Peak” High-Level Talent Project (WSN-269) and Nantong Medical Key Talent Project.