Bioinformatics approach to identify the influences of SARS-COV2 infections on atherosclerosis
Jiuchang Zhang, Liming Zhang
Abstract
Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a global pandemic since early 2020. Understanding the relationship between various systemic disease and COVID-19 through disease ontology (DO) analysis, an approach based on disease similarity studies, has found that COVID-19 is most strongly associated with atherosclerosis. The study provides new insights for the common pathogenesis of COVID-19 and atherosclerosis by looking for common transcriptional features. Two datasets (GSE152418 and GSE100927) were downloaded from GEO database to search for common differentially expressed genes (DEGs) and shared pathways. A total of 34 DEGs were identified. Among them, ten hub genes with high degrees of connectivity were picked out, namely C1QA, C1QB, C1QC, CD163, SIGLEC1, APOE, MS4A4A, VSIG4, CCR1 and STAB1. This study suggests the critical role played by Complement and coagulation cascades in COVID-19 and atherosclerosis. Our findings underscore the importance of C1q in the pathogenesis of COVID-19 and atherosclerosis. Activation of the complement system can lead to endothelial dysfunction. The DEGs identified in this study provide new biomarkers and potential therapeutic targets for the prevention of atherosclerosis.