Evidence map›Paper›PMID 37904132›Full record

ArticleCell communication and signaling : CCS2023

SARS-CoV-2 primed platelets-derived microRNAs enhance NETs formation by extracellular vesicle transmission and TLR7/8 activation.

Tsai-Ling Liao, Hung-Jen Liu, Der-Yuan Chen, Kuo-Tung Tang, Yi-Ming Chen, Po-Yu Liu

Open access · goldAbstract read
In one paragraph

Article in Cell communication and signaling : CCS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

16 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Neutrophil extracellular traps: a catalyst for atherosclerosis.Molecular and cellular biochemistry · 2024
    Review
  15. miR-574-5p in epigenetic regulation and Toll-like receptor signaling.Cell communication and signaling : CCS · 2024
    Review
  16. Review
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

6 authors at 3 institutions in 1 country.

Tsai-Ling LiaoDepartment of Medical Research, Taichung Veterans General Hospital, No.1650, Sec.4, Taiwan Boulevard, Xitun Dist, Taichung City, 407, Taiwan. tlliao@vghtc.gov.tw.
Hung-Jen LiuRong Hsing Translational Medicine Research Center, National Chung Hsing University, Taichung, 402, Taiwan.
Der-Yuan ChenRheumatology and Immunology Center, China Medical University Hospital, Taichung, 404, Taiwan.
Kuo-Tung TangDivision of Allergy, Immunology and Rheumatology, Taichung Veterans General Hospital, Taichung, 407, Taiwan.
Yi-Ming ChenDepartment of Medical Research, Taichung Veterans General Hospital, No.1650, Sec.4, Taiwan Boulevard, Xitun Dist, Taichung City, 407, Taiwan.
Po-Yu LiuRong Hsing Translational Medicine Research Center, National Chung Hsing University, Taichung, 402, Taiwan. pyliu@vghtc.gov.tw.
Taichung Veterans General Hospital · TWChung Shan Medical University Hospital · TWNational Chung Hsing University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperactive neutrophil extracellular traps (NETs) formation plays a key role in the pathogenesis of severe COVID-19. Extracellular vesicles (EVs) are vehicles which carry cellular components for intercellular communication. The association between COVID-19 patients-derived EVs and NETs formation remains elusive.

methodsWe explored the roles of EVs in NETs formation from 40 COVID-19 patients with different disease severities as well as 30 healthy subjects. The EVs-carried microRNAs profile was analyzed using next generation sequencing approach which was validated by quantitative reverse transcription PCR. The regulatory mechanism of EVs on NETs formation was investigated by using an in vitro cell-based assay, including immunofluorescence assay, flow cytometry, and immunoblotting.

resultsCOVID-19 patient-derived EVs induced NETs formation by endocytosis uptake. SARS-CoV-2 spike protein-triggered NETs formation was significantly enhanced in the presence of platelet-derived EVs (pEVs) and this effect was Toll-like receptor (TLR) 7/8- and NADPH oxidase-dependent. Increased levels of miR-21/let-7b were revealed in EVs from COVID-19 patients and were associated with disease severity. We demonstrated that the spike protein activated platelets directly, followed by the subsequent intracellular miR-21/let-7b upregulation and then were loaded into pEVs. The pEVs-carried miR-21 interacted with TLR7/8 to prime p47phox phosphorylation in neutrophils, resulting in NADPH oxidase activation to promote ROS production and NETs enhancement. In addition, miR-21 modulates NF-κB activation and IL-1β/TNFα/IL-8 upregulation in neutrophils upon TLR7/8 engagement. The miR-21 inhibitor and TLR8 antagonist could suppress efficiently spike protein-induced NETs formation and pEVs primed NETs enhancement.

conclusionsWe identified SARS-CoV-2 triggered platelets-derived GU-enriched miRNAs (e.g., miR-21/let-7b) as a TLR7/8 ligand that could activate neutrophils through EVs transmission. The miR-21-TLR8 axis could be used as a potential predisposing factor or therapeutic target for severe COVID-19.

Indexed as

COVID-19Extracellular TrapsExtracellular VesiclesMicroRNAsHumansNADPH OxidasesSARS-CoV-2Spike Glycoprotein, CoronavirusToll-Like Receptor 7Toll-Like Receptor 8MicroRNAsNADPH OxidasesSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2TLR7 protein, humanToll-Like Receptor 7Toll-Like Receptor 8COVID-19extracellular vesiclesmicroRNAsPlatelets, NETsTLR8

Identifiers

PMID37904132
PMCPMC10614402
OpenAlexW4388035373

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.