Identification of genes and signaling pathways associated with severe COVID-19: high-throughput data analysis with a system virology approach

Abstract

Corona Virus Disease 2019 (COVID-19) has caused over six million deaths worldwide so far. COVID-19 has presented a variety of severities and outcomes which is able to damage many different organs. In this study, we aimed to identify factors responsible for severe illness and also alterations caused by the virus in various organs at the molecular level. First, after preprocessing steps, we chose one mRNA expression profile (GSE164805) for further analysis. Differentially Expressed Genes (DEGs) were screened with the Limma R package and considered for the PPI network construction. By maximizing co-expression value, we constructed subnetworks and subjected them to the Gene Sets Net Correlation Analysis (GSNCA). Successfully passed clusters were subjected to enrichment analysis. From 60k genes, 7106, 3151, and 1809 genes were considered as DEGs in normal vs. mild, normal vs. severe, and mild vs. severe comparisons, respectively, with p < 0.05 and |LogFC| > 2 as thresholds. PPI network analysis resulted in 17 modules, and 11 of them successfully passed GSNCA analysis with a P value < 0.05. Enrichment analysis culminated in identifying genes and signaling pathways with possible roles in the establishment of severe disease. We noticed considerable similarities between altered signaling pathways in COVID-19 and various malignancies. In addition, we detected alterations of pathways that can help to explain neurological involvement.