Integrated Weighted Gene Co-expression Network Analysis Identified That TLR2 and CD40 Are Related to Coronary Artery Disease.

Bin Qi,Chuan-Meng Zhu,Yong Wang,Lin Tao,Liu Miao,Guo-Xiong Deng,Jian-Hong Chen

doi:10.3389/fgene.2020.613744

Bin Qi, Chuan-Meng Zhu + Show 5 more

Open Access

https://doi.org/10.3389/fgene.2020.613744

Copy DOI

Abstract

The current research attempted to identify possible hub genes and pathways of coronary artery disease (CAD) and to detect the possible mechanisms. Array data from GSE90074 were downloaded from the Gene Expression Omnibus (GEO) database. Integrated weighted gene co-expression network analysis (WGCNA) was performed to analyze the gene module and clinical characteristics. Gene Ontology annotation (GO), Disease Ontology (DO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by clusterProfiler and the DOSE package in R. A protein-protein interaction (PPI) network was established using Cytoscape software, and significant modules were analyzed using Molecular Complex Detection (MCODE) to identify hub genes. Then, further functional validation of hub genes in other microarrays and population samples was performed, and survival analysis was performed to investigate the prognosis. A total of 660 genes were located in three modules and associated with CAD. GO functions identified 484 biological processes, 39 cellular components, and 22 molecular functions with an adjusted P < 0.05. In total, 38 pathways were enriched in KEGG pathway analysis, and 147 DO items were identified with an adjusted P < 0.05 (false discovery rate, FDR set at < 0.05). There was a total of four modules with a score > 10 after PPI network analysis using the MCODE app, and two hub genes (TLR2 and CD14) were identified. Then, we validated the information from the GSE60993 dataset using the GSE59867 dataset and population samples, and we found that these two genes were associated with plaque vulnerability. These two genes varied at different time points after myocardial infarction, and both of them had the lowest prognosis of heart failure when they were expressed at low levels. We performed an integrated WGCNA and validated that TLR2 and CD14 were closely associated with the severity of coronary artery disease, plaque instability and the prognosis of heart failure after myocardial infarction.

Highlights

With the continuous improvement of living standards, the incidence of coronary artery disease (CAD) is increasing
CAD remains one of the leading causes of death worldwide, and the high morbidity and mortality have become a burden in all countries worldwide, which has gradually attracted people’s attention (Benjamin et al, 2018)
We used integrated Weighted gene coexpression network analysis (WGCNA) methods to analyze the dataset and identify two hub genes (TLR2 and CD14) that were positively correlated with the severity of coronary atherosclerosis

Summary

Introduction

With the continuous improvement of living standards, the incidence of coronary artery disease (CAD) is increasing. Improvements in science and technology have provided us with a new understanding of CAD that abnormal gene expression plays an important role in the pathogenesis of CAD (Malakar et al, 2019). With the remarkable evolution of bioinformatics, numerous microarray data can be used to identify hub genes, interaction networks and pathways of CAD. We constructed an mRNA expression profile of CAD samples to screen gene modules that are closely related and highly coregulated with CAD to show the potential molecular mechanisms

Methods

Results

Conclusion