Evidence map›Paper›PMID 37350967›Full record

ArticleFrontiers in immunology2023

Central role of lung macrophages in SARS-CoV-2 physiopathology: a cross-model single-cell RNA-seq perspective.

Thibaut Olivier, Joël Blomet, Daniel Desmecht

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Antibody-dependent enhancement of coronaviruses.International journal of biological sciences · 2025
    Review
  5. Article
  6. Article
  7. Article
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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

3 authors at 1 institution in 1 country.

Thibaut OlivierGAS Department, Prevor Research Laboratories, Valmondois, France.
Joël BlometGAS Department, Prevor Research Laboratories, Valmondois, France.
Daniel DesmechtDepartment of Pathology, Fundamental and Applied Research for Animals & Health (FARAH), Faculty of Veterinary Medicine, University of Liege, Liège, Belgium.
University of Liège · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cytokine storms are considered a driving factor in coronavirus disease 2019 (COVID-19) severity. However, the triggering and resolution of this cytokine production, as well as the link between this phenomenon and infected cells, are still poorly understood. In this study, a cross-species scRNA-seq analysis showed that cytokine-producing macrophages together with pneumocytes were found to be the main contributors of viral transcripts in both Syrian hamsters and African green monkeys. Whatever the cell type, viral read-bearing cells show an apoptotic phenotype. A comparison of SARS-CoV-2 entry receptor candidates showed that Fc receptors are better correlated with infected cells than ACE2, NRP1, or AXL. Although both species show similar interferon responses, differences in adaptive immunity were highlighted. Lastly, Fc receptor and cytokine upregulation in M1 macrophages was found to correlate with a comprehensive interferon response. Based on these results, we propose a model in which lung macrophages play a central role in COVID-19 severity through antibody-dependent enhancement.

Indexed as

COVID-19SARS-CoV-2Alveolar Epithelial CellsAnimalsChlorocebus aethiopsCytokinesInterferonsMacrophagesSingle-Cell Gene Expression AnalysisCytokinesInterferonsantibody-dependent enhancementcytokine stormFcγRinterferonsM1 macrophagesSARS-CoV-2

Identifiers

PMID37350967
PMCPMC10282834
OpenAlexW4379797205

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.