Bioinformatics analysis based on high-throughput sequencing data to identify hub genes related to different clinical types of COVID-19

This article aims to explore hub genes related to different clinical types of cases with COVID-19 and predict the therapeutic drugs related to severe cases. The expression profile of GSE166424 was divided into four data sets according to different clinical types of COVID-19 and then calculated the differential expression genes (DEGs). The specific genes of four clinical types of COVID-19 were obtained by Venn diagram and conducted enrichment analysis, protein-protein interaction (PPI) networks analysis, screening hub genes, and ROC curve analysis. The hub genes related to severe cases were verified in GSE171110, their RNA-specific expression tissues were obtained from the HPA database, and potential therapeutic drugs were predicted through the DGIdb database. There were 536, 266, 944, and 506 specific genes related to asymptomatic infections, mild, moderate, and severe cases, respectively. The hub genes of severe specific genes were AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11, and also differentially expressed in GSE171110 (P < 0.05), and their AUC values were greater than 0.955. The RNA tissue specificity of AURKB, CDC6, KIF11, UBE2C, CCNB2, CDC20, TOP2A, BUB1, and CCNB1 specifically enhanced on lymphoid tissue; CCNB2, CDC20, TOP2A, and BUB1 specifically expressed on the testis. Finally, 55 drugs related to severe COVID-19 were obtained from the DGIdb database. Summary, AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11 may be potential diagnostic biomarkers for severe COVID-19, which may affect immune and male reproductive systems. 55 drugs may be potential therapeutic drugs for severe COVID-19.

Automated summary

This study aimed to explore hub genes related to different clinical types of COVID-19 cases and predict therapeutic drugs for severe cases. The expression profile of GSE166424 was divided into four data sets based on clinical types of COVID-19, and differential expression genes (DEGs) were calculated. Specific genes for each clinical type were identified and subjected to enrichment analysis, protein-protein interaction (PPI) network analysis, hub gene screening, and ROC curve analysis. Hub genes related to severe cases were verified in GSE171110, and their tissue specificity was obtained from the HPA database. Potential therapeutic drugs were predicted using the DGIdb database. The study identified specific genes for asymptomatic infections, mild, moderate, and severe cases, and discovered potential diagnostic biomarkers for severe COVID-19. Additionally, 55 drugs were found to have potential therapeutic value for severe COVID-19.