Network-based Multi-omics Disease–Drug Associations Reveal Drug Repurposing Candidates for Covid-19 Disease Phases

Abstract

Background The development and rollout of vaccines and the use of various drugs have contributed to controlling the coronavirus disease 2019 (Covid-19) pandemic. Nevertheless, challenges such as the inequitable distribution of vaccines, the influence of emerging viral lineages and immunoevasive variants on vaccine efficacy, and the inadequate immune defense in subgroups of the population continue to motivate the development of new drugs to combat the disease. Aim In this study, we sought to identify, prioritize, and characterize drug repurposing candidates appropriate for treating mild, moderate, or severe Covid-19 using a network-based integrative approach that systematically integrates drug-related data and multi-omics datasets. Methods We leveraged drug data and multi-omics data and used a random walk with restart algorithm to explore an integrated knowledge graph comprising three subgraphs: (i) a Covid-19 knowledge graph, (ii) a drug repurposing knowledge graph, and (iii) a Covid-19 disease state-specific omics graph. Results We prioritized 20 US Food and Drug Administration-approved agents as potential candidate drugs for mild, moderate, and severe Covid-19 disease phases. Specifically, drugs that could stimulate immune cell recruitment and activation including histamine, curcumin, and paclitaxel have potential utility in mild disease states to mitigate disease progression. Drugs like omacetaxine, crizotinib, and vorinostat that exhibit antiviral properties and have the potential to inhibit viral replication can be considered for mild to moderate Covid-19 disease states. Also, given the association between antioxidant deficiency and high inflammatory factors that trigger cytokine storms, antioxidants like glutathione can be considered for moderate disease states. Drugs that exhibit potent anti-inflammatory effects like (i) anti-inflammatory drugs (sarilumab and tocilizumab), (ii) corticosteroids (dexamethasone and hydrocortisone), and (iii) immunosuppressives (sirolimus and cyclosporine) are potential candidates for moderate to severe disease states that trigger a hyperinflammatory cascade of Covid-19. Conclusion Our study demonstrates that the multi-omics data-driven integrative analysis within the drug data enables prioritizing drug candidates for Covid-19 disease phases, offering a comprehensive basis for therapeutic strategies that can be brought to market quickly given their established safety profiles. Importantly, the multi-omics data-driven integrative analysis within the drug data approach implemented here can be used to prioritize drug repurposing candidates appropriate for other diseases.