Aim: The present study aimed to introduce a possible biomarker to differentiate between severe and fatal conditions of COVID-19. Background: The COVID-19 pandemic, appearing as a complicated health problem, has changed the lifestyle of people in recent years. Clinical findings indicate mild, severe, and fatal conditions of this disease. Prediction of disease severity is a significant point in managing COVID-19 infection Methods: In this study, 195 differentially expressed genes (DEGs) that discriminate between fatal and severe conditions in patients were extracted from the literature and screened to determine the significant ones. The significant DEGs plus the 90 first neighbors added from the STRING database were included in the interactome using Cytoscape software v 3.7.2. The central nodes of the analyzed network were identified and assessed. Results: Ten significant DEGs were candidates for assessment, of which 9 were recognized by the STRING database. IL6, ALB, TNF, CRP, INS, MPO, C3, CXCL8, TTR, and TLR4 were determined as central nodes; IL6, CRP, and TTR were highlighted as the critical genes related to the severity of COVID-19 infection. Conclusion: CRP was identified as the best possible biomarker with levels related to the severity and fatality of COVID-19 infection.
【저자키워드】 COVID-19, severity, bioinformatics, C-reactive protein, network analysis, 【초록키워드】 Biomarker, TLR4, COVID-19 pandemic, disease severity, Infection, IL6, prediction, CRP, MPO, database, Health, COVID-19 infection, severity of COVID-19, Patient, Mild, disease, Critical, differentially expressed gene, CXCL8, fatality, TNF, Clinical finding, candidate, DEGs, Cytoscape software, central node, analyzed, screened, condition, added, determine, changed, ALB, INS, TTR, 【제목키워드】 Mortality, COVID-19 infection, marker,