COVID-19: disease pathways and gene expression changes predict methylprednisolone can improve outcome in severe cases
Recommended Citation
Draghici S, Nguyen TM, Sonna LA, Ziraldo C, Vanciu R, Fadel R, Morrison A, Kenney RM, Alangaden G, Ramesh M, and Mor G. COVID-19: disease pathways and gene expression changes predict methylprednisolone can improve outcome in severe cases. Bioinformatics 2021.
Document Type
Article
Publication Date
3-9-2021
Publication Title
Bioinformatics (Oxford, England)
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 vs. 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 data sets including Vero E6 cells, lung and intestinal organoids, as well as additional patient lung sample vs. 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% vs. 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: iPathwayGuide is available at https://ipathwayguide.advaitabio.com/.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
PubMed ID
33693506
ePublication
ePub ahead of print