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Meta-analysis of orthogonal OMICs data from COVID-19 patients unveils prognostic markers and antiviral factors.
Preprint
in En
| PREPRINT-BIORXIV
| ID: ppbiorxiv-431825
ABSTRACT
While our battle with the COVID-19 pandemic continues, a multitude of Omics data has been generated from patient samples in various studies, which remains to be translated. We conducted a meta-analysis of published transcriptome and proteome profiles of nasal swab and bronchioalveolar lavage fluid (BALF) samples of COVID-19 patients, to shortlist high confidence upregulated host factors. Subsequently, mRNA overexpression of selected genes was validated in nasal swab/BALF samples from a cohort of COVID-19 positive/negative, symptomatic/asymptomatic individuals. Analysis of these data revealed S100 family genes (S100A6, S100A8, S100A9, and S100P) as prognostic markers of COVID-19 disease. Furthermore, Thioredoxin gene (TXN) was identified as a significant upregulated host factor in our overlap analysis. An FDA-approved drug Auranofin, which inhibits Thioredoxin reduction, was found to mitigate SARS-CoV-2 replication in vitro and in vivo in the hamster challenge model. Overall, this study translates COVID-19 host response Big Data into potential clinical interventions.
Full text:
1
Collection:
09-preprints
Database:
PREPRINT-BIORXIV
Type of study:
Cohort_studies
/
Observational_studies
/
Prognostic_studies
/
Review
Language:
En
Year:
2021
Document type:
Preprint