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

Background: While our battle with the COVID-19 pandemic continues, a multitude of Omics data have been generated from patient samples in various studies. Translation of these data into clinical interventions against COVID-19 remains to be accomplished. Exploring host response to COVID-19 in the uppe...

Full description

Bibliographic Details
Main Authors: Abhijith Biji, Oyahida Khatun, Shachee Swaraj, Rohan Narayan, Raju S. Rajmani, Rahila Sardar, Deepshikha Satish, Simran Mehta, Hima Bindhu, Madhumol Jeevan, Deepak K. Saini, Amit Singh, Dinesh Gupta, Shashank Tripathi
Format: Article
Language:English
Published: Elsevier 2021-08-01
Series:EBioMedicine
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396421003182
id doaj-bfbd95263fcd418a8b64272ffc787c2e
record_format Article
collection DOAJ
language English
format Article
sources DOAJ
author Abhijith Biji
Oyahida Khatun
Shachee Swaraj
Rohan Narayan
Raju S. Rajmani
Rahila Sardar
Deepshikha Satish
Simran Mehta
Hima Bindhu
Madhumol Jeevan
Deepak K. Saini
Amit Singh
Dinesh Gupta
Shashank Tripathi
spellingShingle Abhijith Biji
Oyahida Khatun
Shachee Swaraj
Rohan Narayan
Raju S. Rajmani
Rahila Sardar
Deepshikha Satish
Simran Mehta
Hima Bindhu
Madhumol Jeevan
Deepak K. Saini
Amit Singh
Dinesh Gupta
Shashank Tripathi
Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples
EBioMedicine
COVID-19
Nasal swab/BALF
Transcriptome
Proteome
Meta-analysis
Prognostic marker
author_facet Abhijith Biji
Oyahida Khatun
Shachee Swaraj
Rohan Narayan
Raju S. Rajmani
Rahila Sardar
Deepshikha Satish
Simran Mehta
Hima Bindhu
Madhumol Jeevan
Deepak K. Saini
Amit Singh
Dinesh Gupta
Shashank Tripathi
author_sort Abhijith Biji
title Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples
title_short Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples
title_full Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples
title_fullStr Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples
title_full_unstemmed Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples
title_sort identification of covid-19 prognostic markers and therapeutic targets through meta-analysis and validation of omics data from nasopharyngeal samples
publisher Elsevier
series EBioMedicine
issn 2352-3964
publishDate 2021-08-01
description Background: While our battle with the COVID-19 pandemic continues, a multitude of Omics data have been generated from patient samples in various studies. Translation of these data into clinical interventions against COVID-19 remains to be accomplished. Exploring host response to COVID-19 in the upper respiratory tract can unveil prognostic markers and therapeutic targets. Methods: We conducted a meta-analysis of published transcriptome and proteome profiles of respiratory samples of COVID-19 patients to shortlist high confidence upregulated host factors. Subsequently, mRNA overexpression of selected genes was validated in nasal swabs from a cohort of COVID-19 positive/negative, symptomatic/asymptomatic individuals. Guided by this analysis, we sought to check for potential drug targets. An FDA-approved drug, Auranofin, was tested against SARS-CoV-2 replication in cell culture and Syrian hamster challenge model. Findings: The meta-analysis and validation in the COVID-19 cohort revealed S100 family genes (S100A6, S100A8, S100A9, and S100P) as prognostic markers of severe COVID-19. Furthermore, Thioredoxin (TXN) was found to be consistently upregulated. Auranofin, which targets Thioredoxin reductase, was found to mitigate SARS-CoV-2 replication in vitro. Furthermore, oral administration of Auranofin in Syrian hamsters in therapeutic as well as prophylactic regimen reduced viral replication, IL-6 production, and inflammation in the lungs. Interpretation: Elevated mRNA level of S100s in the nasal swabs indicate severe COVID-19 disease, and FDA-approved drug Auranofin mitigated SARS-CoV-2 replication in preclinical hamster model. Funding: This study was supported by the DBT-IISc partnership program (DBT (IED/4/2020-MED/DBT)), the Infosys Young Investigator award (YI/2019/1106), DBT-BIRAC grant (BT/CS0007/CS/02/20) and the DBT-Wellcome Trust India Alliance Intermediate Fellowship (IA/I/18/1/503613) to ST lab.
topic COVID-19
Nasal swab/BALF
Transcriptome
Proteome
Meta-analysis
Prognostic marker
url http://www.sciencedirect.com/science/article/pii/S2352396421003182
work_keys_str_mv AT abhijithbiji identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT oyahidakhatun identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT shacheeswaraj identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT rohannarayan identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT rajusrajmani identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT rahilasardar identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT deepshikhasatish identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT simranmehta identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT himabindhu identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT madhumoljeevan identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT deepakksaini identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT amitsingh identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT dineshgupta identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
AT shashanktripathi identificationofcovid19prognosticmarkersandtherapeutictargetsthroughmetaanalysisandvalidationofomicsdatafromnasopharyngealsamples
_version_ 1721207805570973696
spelling doaj-bfbd95263fcd418a8b64272ffc787c2e2021-08-14T04:31:04ZengElsevierEBioMedicine2352-39642021-08-0170103525Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samplesAbhijith Biji0Oyahida Khatun1Shachee Swaraj2Rohan Narayan3Raju S. Rajmani4Rahila Sardar5Deepshikha Satish6Simran Mehta7Hima Bindhu8Madhumol Jeevan9Deepak K. Saini10Amit Singh11Dinesh Gupta12Shashank Tripathi13Microbiology & Cell Biology Department, Indian Institute of Science, Bengaluru, India; Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, IndiaMicrobiology & Cell Biology Department, Indian Institute of Science, Bengaluru, India; Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, IndiaMicrobiology & Cell Biology Department, Indian Institute of Science, Bengaluru, India; Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, IndiaMicrobiology & Cell Biology Department, Indian Institute of Science, Bengaluru, India; Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, IndiaMolecular Biophysics Unit, Indian Institute of Science, Bengaluru, IndiaTranslational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, IndiaTranslational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, IndiaCOVID-19 Diagnostic Facility, Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, IndiaCOVID-19 Diagnostic Facility, Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, IndiaCOVID-19 Diagnostic Facility, Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, IndiaMolecular Reproduction & Developmental Genetics, Indian Institute of Science, Bengaluru, IndiaMicrobiology & Cell Biology Department, Indian Institute of Science, Bengaluru, India; Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, IndiaTranslational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, IndiaMicrobiology & Cell Biology Department, Indian Institute of Science, Bengaluru, India; Centre for Infectious Disease Research, Indian Institute of Science, Bengaluru, India; Corresponding author: Dr. Shashank Tripathi, Indian Institute of Science, Microbiology and Cell Biology, Centre For Infectious Disease Research, C.V.Raman Avenue, Indian Institute of Science, Bengaluru, Karnataka 560012, India.Background: While our battle with the COVID-19 pandemic continues, a multitude of Omics data have been generated from patient samples in various studies. Translation of these data into clinical interventions against COVID-19 remains to be accomplished. Exploring host response to COVID-19 in the upper respiratory tract can unveil prognostic markers and therapeutic targets. Methods: We conducted a meta-analysis of published transcriptome and proteome profiles of respiratory samples of COVID-19 patients to shortlist high confidence upregulated host factors. Subsequently, mRNA overexpression of selected genes was validated in nasal swabs from a cohort of COVID-19 positive/negative, symptomatic/asymptomatic individuals. Guided by this analysis, we sought to check for potential drug targets. An FDA-approved drug, Auranofin, was tested against SARS-CoV-2 replication in cell culture and Syrian hamster challenge model. Findings: The meta-analysis and validation in the COVID-19 cohort revealed S100 family genes (S100A6, S100A8, S100A9, and S100P) as prognostic markers of severe COVID-19. Furthermore, Thioredoxin (TXN) was found to be consistently upregulated. Auranofin, which targets Thioredoxin reductase, was found to mitigate SARS-CoV-2 replication in vitro. Furthermore, oral administration of Auranofin in Syrian hamsters in therapeutic as well as prophylactic regimen reduced viral replication, IL-6 production, and inflammation in the lungs. Interpretation: Elevated mRNA level of S100s in the nasal swabs indicate severe COVID-19 disease, and FDA-approved drug Auranofin mitigated SARS-CoV-2 replication in preclinical hamster model. Funding: This study was supported by the DBT-IISc partnership program (DBT (IED/4/2020-MED/DBT)), the Infosys Young Investigator award (YI/2019/1106), DBT-BIRAC grant (BT/CS0007/CS/02/20) and the DBT-Wellcome Trust India Alliance Intermediate Fellowship (IA/I/18/1/503613) to ST lab.http://www.sciencedirect.com/science/article/pii/S2352396421003182COVID-19Nasal swab/BALFTranscriptomeProteomeMeta-analysisPrognostic marker