Evidence map›Paper›PMID 33037393›Full record

ReviewCell death and differentiation2020

An aberrant STAT pathway is central to COVID-19.

Toshifumi Matsuyama, Shawn P Kubli, Steven K Yoshinaga, Klaus Pfeffer, Tak W Mak

Open access · bronzeAbstract readReview
In one paragraph

Review in Cell death and differentiation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 189 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
189citing papers in PubMed, 3 pooled it
6.4field-weighted citation impact, top 3% of its field
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

189 citing papers in PubMed, 3 syntheses or guidelines pooled it, 305 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Immunomodulation as Treatment for Severe Coronavirus Disease 2019: A Systematic Review of Current Modalities and Future Directions.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
    Pooled it
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Observational
  12. Mucosal implications of oral Jak3-targeted drugs in COVID patients.Molecular medicine (Cambridge, Mass.) · 2025
    Review
  13. Article
  14. Article
  15. Article
  16. Identification ofMolecules (Basel, Switzerland) · 2025
    Article
  17. Article
  18. Classification and regulatory interactions of key transcription factors in COVID-19.Frontiers in cellular and infection microbiology · 2025
    Review
  19. Article
  20. Article

129 more citing papers are in PubMed but not listed here.

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 at 4 institutions in 4 countries.

Toshifumi MatsuyamaDepartment of Pathology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan.ORCID http://orcid.org/0000-0003-1831-4094
Shawn P KubliPrincess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, ON, M5G 2M9, Canada.
Steven K YoshinagaSKYBAY Education, Thousand Oaks, CA, 91360, USA.
Klaus PfefferInstitute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.ORCID http://orcid.org/0000-0002-5652-6330
Tak W MakPrincess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, ON, M5G 2M9, Canada. tmak@uhnres.utoronto.ca.
Heinrich Heine University Düsseldorf · DENagasaki University · JPUniversity Health Network · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 is caused by SARS-CoV-2 infection and characterized by diverse clinical symptoms. Type I interferon (IFN-I) production is impaired and severe cases lead to ARDS and widespread coagulopathy. We propose that COVID-19 pathophysiology is initiated by SARS-CoV-2 gene products, the NSP1 and ORF6 proteins, leading to a catastrophic cascade of failures. These viral components induce signal transducer and activator of transcription 1 (STAT1) dysfunction and compensatory hyperactivation of STAT3. In SARS-CoV-2-infected cells, a positive feedback loop established between STAT3 and plasminogen activator inhibitor-1 (PAI-1) may lead to an escalating cycle of activation in common with the interdependent signaling networks affected in COVID-19. Specifically, PAI-1 upregulation leads to coagulopathy characterized by intravascular thrombi. Overproduced PAI-1 binds to TLR4 on macrophages, inducing the secretion of proinflammatory cytokines and chemokines. The recruitment and subsequent activation of innate immune cells within an infected lung drives the destruction of lung architecture, which leads to the infection of regional endothelial cells and produces a hypoxic environment that further stimulates PAI-1 production. Acute lung injury also activates EGFR and leads to the phosphorylation of STAT3. COVID-19 patients' autopsies frequently exhibit diffuse alveolar damage (DAD) and increased hyaluronan (HA) production which also leads to higher levels of PAI-1. COVID-19 risk factors are consistent with this scenario, as PAI-1 levels are increased in hypertension, obesity, diabetes, cardiovascular diseases, and old age. We discuss the possibility of using various approved drugs, or drugs currently in clinical development, to treat COVID-19. This perspective suggests to enhance STAT1 activity and/or inhibit STAT3 functions for COVID-19 treatment. This might derail the escalating STAT3/PAI-1 cycle central to COVID-19.

Indexed as

ChemokinesCOVID-19CytokinesErbB ReceptorsHumansInterferon Type ISARS-CoV-2Signal TransductionSTAT Transcription FactorsViral Nonstructural ProteinsChemokinesCytokinesEGFR protein, humanErbB ReceptorsInterferon Type ISTAT Transcription FactorsViral Nonstructural Proteins

Identifiers

PMID33037393
PMCPMC7545020
OpenAlexW3092207907

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.