Evidence map›Paper›PMID 40500689›Full record

ArticleRespiratory research2025

Transcriptomic analysis reveals shared deregulated neutrophil responses in COVID-19 and idiopathic pulmonary fibrosis.

Georgios Divolis, Evgenia Synolaki, Rodoula Tringidou, Argyrios Tzouvelekis, Dimitrios T Boumpas, Panagiotis Skendros, Ioanna-Evdokia Galani

Abstract read
In one paragraph

Article in Respiratory research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Proceedings of the 2Mediterranean journal of rheumatology · 2026
    Article
  5. 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

7 authors.

Georgios Divolis *Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation Academy of Athens (BRFAA), 4 Soranou Ephessiou Street, Athens, 11527, Greece. gdivolis@bioacademy.gr.
Evgenia SynolakiCenter for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation Academy of Athens (BRFAA), 4 Soranou Ephessiou Street, Athens, 11527, Greece.
Rodoula TringidouDepartment of Pathology, 'Sotiria' General Hospital of Chest Diseases, Athens, Greece.
Argyrios TzouvelekisDivision of Respiratory Medicine, Medical School, University of Patras, Patras, Greece.
Dimitrios T BoumpasCenter for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation Academy of Athens (BRFAA), 4 Soranou Ephessiou Street, Athens, 11527, Greece.
Panagiotis SkendrosLaboratory of Molecular Hematology, Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece.
Ioanna-Evdokia Galani *Center for Basic Research, BRFAA, Athens, Greece.

Funding

European Social Fund, implemented by the State Scholarships Foundation (IKΥ). MIS-5000432Greek General Secretariat of Research and Innovation T1EDK-00617/MIS-5048548
6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) is a respiratory disease linked with deregulated immune responses, leading to hyperinflammation, acute respiratory distress syndrome, and pulmonary fibrosis, often with fatal outcomes. Neutrophils play a central role in COVID-19 pathogenesis, with elevated peripheral blood neutrophil counts correlating with disease severity. Despite extensive research, the molecular processes associated with neutrophil hyperactivation in COVID-19 remain elusive.

methodsTo investigate the molecular signatures underlying neutrophil-driven pathology, we conducted transcriptome analysis in neutrophils isolated from the peripheral blood of COVID-19 patients versus healthy individuals. To evaluate the specificity of identified neutrophil signatures in COVID-19, we extended our transcriptomic analysis to neutrophils from patients with idiopathic pulmonary fibrosis (IPF), a non-infectious fibrotic lung disease. Additionally, immunofluorescence staining was performed on lung biopsy specimens from IPF patients to validate transcriptomic findings at the tissue level.

resultsOur analysis revealed significant transcriptional changes in COVID-19 neutrophils, particularly in pathways involved in immune regulation, inflammation, and antiviral responses. Additionally, pathways associated with autophagy and chromatin remodeling were upregulated, while translation-related processes were suppressed, indicating an increased predisposition for neutrophil extracellular trap (NET) release. This neutrophil transcriptional signature in COVID-19 appears to be associated with the previously reported deregulation of the Activin/Follistatin system in the periphery. Notably, a comparative transcriptomic analysis with neutrophils isolated from IPF patients revealed the induction of substantially overlapping inflammatory processes, suggesting common deregulated responses in COVID-19 and IPF. Consistently, significant NET formation, a hallmark of COVID-19-related inflammation, was observed within lung biopsies from IPF patients.

conclusionBy delineating both shared and disease-specific molecular pathways, our findings validate the critical role of neutrophils in COVID-19 and IPF pathophysiology, highlighting their involvement in balancing the inflammatory response across diverse lung diseases.

Indexed as

COVID-19Gene Expression ProfilingIdiopathic Pulmonary FibrosisNeutrophilsTranscriptomeAgedExtracellular TrapsFemaleHumansLungMaleMiddle AgedSARS-CoV-2ActivinCOVID-19FollistatinIdiopathic pulmonary fibrosisLung inflammationNETosisNeutrophilsRNA SequencingTranscriptomicsViral infection

Identifiers

PMID40500689
PMCPMC12160113

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.