Bioinformatics approach to identify the influences of SARS-COV2 infections on atherosclerosis - Zhang, Jiuchang; Zhang, Liming (Frontiers in Cardiovascular Medicine, 2022)
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. We analyzed two gene expression data sets (GSE152418 and GSE100927) downloaded from the GEO database. Comprehensive bioinformatics and enrichment analysis were used to determine the common differentially expressed genes (DEGs) and its functions of COVID-19 and atherosclerosis. In addition, protein protein interaction (PPI) networks were established to reveal hub genes. 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. The DEGs identified in this study provide new biomarkers and potential therapeutic targets for preventing atherosclerosis during the onset of COVID-19.