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Media type:
E-Article
Title:
COVID-19: disease pathways and gene expression changes predict methylprednisolone can improve outcome in severe cases
Contributor:
Draghici, Sorin;
Nguyen, Tuan-Minh;
Sonna, Larry A.;
Ziraldo, Cordelia;
Vanciu, Radu;
Fadel, Raef;
Morrison, Austin;
Kenney, Rachel M.;
Alangaden, George;
Ramesh, Mayur;
Mor, Gil
Published:
Oxford University Press (OUP), 2021
Published in:
Bioinformatics, 37 (2021) 17, Seite 2691-2698
Language:
English
DOI:
10.1093/bioinformatics/btab163
ISSN:
1367-4803;
1367-4811
Origination:
Footnote:
Description:
Abstract Motivation COVID-19 has several distinct clinical phases: a viral replication phase, an inflammatory phase and in some patients, a hyper-inflammatory phase. High mortality is associated with patients developing cytokine storm syndrome. Treatment of hyper-inflammation in these patients using existing approved therapies with proven safety profiles could address the immediate need to reduce mortality. Results We analyzed the changes in the gene expression, pathways and putative mechanisms induced by SARS-CoV2 in NHBE, and A549 cells, as well as COVID-19 lung versus their respective controls. We used these changes to identify FDA approved drugs that could be repurposed to help COVID-19 patients with severe symptoms related to hyper-inflammation. We identified methylprednisolone (MP) as a potential leading therapy. The results were then confirmed in five independent validation datasets including Vero E6 cells, lung and intestinal organoids, as well as additional patient lung sample versus their respective controls. Finally, the efficacy of MP was validated in an independent clinical study. Thirty-day all-cause mortality occurred at a significantly lower rate in the MP-treated group compared to control group (29.6% versus 16.6%, P = 0.027). Clinical results confirmed the in silico prediction that MP could improve outcomes in severe cases of COVID-19. A low number needed to treat (NNT = 5) suggests MP may be more efficacious than dexamethasone or hydrocortisone. Availability and implementation iPathwayGuide is available at https://advaitabio.com/ipathwayguide/. Supplementary information Supplementary data are available at Bioinformatics online.