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

TITLE=Identification of 5 hub genes for diagnosis of coronary artery disease

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1086127

DOI=10.3389/fcvm.2023.1086127

ISSN=2297-055X

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 GSE202626 dataset. edgeR package identified differentially expressed genes (DEGs). Using online STRING tool and Cytoscape, protein-protein interactions (PPI) was 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 targets genes were screened by intersection 1714 DEGs and 1708 CAD related target genes. 137 targets genes in 162 targets genes were obtained using PPI analysis, which those targets were enriched in in inflammatory cytokine pathways, such as chemokine signaling pathway, IL-17 signaling pathway. From the above 137 targets 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 were, respectively. Finally, 5 hub genes (CCL2, PTGS2, NLRP3, VEGFA, LTA) were screened by intersection Top20 directly/indirectly genes 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 GSE202625 dataset and 94.11% sensitivity and AUC was 0.9706 in GSE120774 dataset.
Conclusion: In this work, we identified 5 hub gene, which may be associated with CAD development.