Evidence map›Paper›PMID 34582497›Full record

ArticlePloS one2021

Drug repurposing for COVID-19 based on an integrative meta-analysis of SARS-CoV-2 induced gene signature in human airway epithelium.

Rajaneesh K Gupta, Enyinna L Nwachuku, Benjamin E Zusman, Ruchira M Jha, Ava M Puccio

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Integrative transcriptome-based drug repurposing in tuberculosis.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Fenofibrate for COVID-19 and related complications as an approach to improve treatment outcomes: the missed key for Holy Grail.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2022
    Review
  14. Article
  15. Review
  16. Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.International journal of molecular sciences · 2022
    Review
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Rajaneesh K GuptaDepartment of Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.ORCID 0000-0003-0212-6478
Enyinna L NwachukuDepartment of Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Benjamin E ZusmanDepartment of Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Ruchira M JhaDepartments of Neurology, Neurobiology, Neurosurgery, Barrow Neurological Institute, Phoenix, Arizona, United States of America.ORCID 0000-0002-3047-7649
Ava M PuccioDepartment of Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.ORCID 0000-0003-2569-9607

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug repurposing has the potential to bring existing de-risked drugs for effective intervention in an ongoing pandemic-COVID-19 that has infected over 131 million, with 2.8 million people succumbing to the illness globally (as of April 04, 2021). We have used a novel `gene signature'-based drug repositioning strategy by applying widely accepted gene ranking algorithms to prioritize the FDA approved or under trial drugs. We mined publically available RNA sequencing (RNA-Seq) data using CLC Genomics Workbench 20 (QIAGEN) and identified 283 differentially expressed genes (FDR<0.05, log2FC>1) after a meta-analysis of three independent studies which were based on severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infection in primary human airway epithelial cells. Ingenuity Pathway Analysis (IPA) revealed that SARS-CoV-2 activated key canonical pathways and gene networks that intricately regulate general anti-viral as well as specific inflammatory pathways. Drug database, extracted from the Metacore and IPA, identified 15 drug targets (with information on COVID-19 pathogenesis) with 46 existing drugs as potential-novel candidates for repurposing for COVID-19 treatment. We found 35 novel drugs that inhibit targets (ALPL, CXCL8, and IL6) already in clinical trials for COVID-19. Also, we found 6 existing drugs against 4 potential anti-COVID-19 targets (CCL20, CSF3, CXCL1, CXCL10) that might have novel anti-COVID-19 indications. Finally, these drug targets were computationally prioritized based on gene ranking algorithms, which revealed CXCL10 as the common and strongest candidate with 2 existing drugs. Furthermore, the list of 283 SARS-CoV-2-associated proteins could be valuable not only as anti-COVID-19 targets but also useful for COVID-19 biomarker development.

Indexed as

COVID-19 Drug TreatmentAntiviral AgentsDrug Evaluation, PreclinicalDrug RepositioningEpithelial CellsEpitheliumHumansRespiratory MucosaRespiratory SystemSARS-CoV-2Antiviral Agents

Identifiers

PMID34582497
PMCPMC8478222

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.