Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples

Biji, Abhijith; Khatun, Oyahida; Swaraj, Shachee; Narayan, Rohan; Rajmani, Raju; Sardar, Rahila; Satish, Deepshikha; Mehta, Simran; Bindhu, Hima; Jeevan, Madhumol; Saini, Deepak K; Singh, Amit; Gupta, Dinesh; Tripathi, Shashank

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.