Identification of key genes in platelets associated with COVID-19 using a weighted gene co-expression network analysis

Abstract

Abstract There is growing evidence of a strong relationship between COVID-19 and thrombosis. However, few bioinformatics-based analyses of critical genes and the mechanisms related to COVID-19 thrombosis existed. This study aimed to identify critical genes related to COVID-19 thrombosis by bioinformatic methods and explore the biological mechanisms and gene regulatory networks. The gene expression data were obtained from the Gene Expression Omnibus (GEO). Significant modular genes in GSE176480 were identified by weighted gene correlation network analysis and overlapped with differentially expressed genes by R package ‘DESeq2’ to obtain common genes. Functional enrichment analyses indicated that common genes were mainly enriched in biological processes such as platelet activation, signaling and aggregation, neutrophil degranulation and immune system and VEGFA-VEGFR2 signaling pathway et al. Finally, 16 genes (RPLP0, RPS4X, RPL13A, RPL13, RPL10, TPT1, PSMA7, ATP5D, AKT1, HIST1H2AC, HIST1H2BH, H3F3B, KDM6A, GATA3, ITGAM and RBMX) were identified as potential hub genes. Our study provides a new perspective to explore the pathogenesis and gene regulatory networks of thrombosis in COVID-19. It is worth highlighting that critical genes may be potential biomarkers and treatment targets of COVID-19 thrombosis for future study.