Analysis of multi-omics data revealed candidate drugs for COVID-19

Abstract

The infection with severe acute respiratory syndrome coronavirus 2is the cause of COVID-19, which has rapidly spread worldwide through person-to-person transmission. More than 6.5 million people died because of COVID-19. Significant data revealed COVID-19-related cardiovascular complications and endothelial dysfunction leading to increased inflammation in various organs. Novel approaches for the development of therapeutics are required given the lack of reliable prognostic biomarkers, multifactorial effects, and the morbidity and mortality risks in vulnerable groups associated with COVID-19. Therefore, the objective of this study is to identify new molecular signatures for drug development. A comparative analysis of genome-wide expression data obtained from lung tissue samples of COVID-19 patients and healthy controls was performed. Specifically, differentially expressed genes (DEGs) were identified, and functional enrichment analyzes of DEGs were carried out. In addition, hub proteins, reporter regulatory elements (i.e., TF and miRNAs), and reporter metabolites were identified by integrating transcriptome data with protein-protein interaction (PPI), regulatory, and genome-scale metabolic networks, respectively. Moreover, a transcriptionally active subnetwork was identified by mapping transcriptome data to PPI network through KeyPathwayMiner. A total of 884 up- and 608 down-regulated DEGs were identified. Functional enrichment analysis demonstrated alterations in immunity, inflammation, and infection disease-associated pathways in the presence of COVID-19. Furthermore, DEGs encoding hub proteins that were regulated by reporter molecules were considered as key genes, and key gene-based drug repositioning analysis revealed candidate drugs including cardiac glycosides, insulin sensitizers, and drugs with antifibrotic, anti-inflammatory, and antiproliferative effects, for consideration in future clinical drug development.