Evidence map›Paper›PMID 39073027›Full record

ArticleClinical and translational medicine2024

Endotypes of severe neutrophilic and eosinophilic asthma from multi-omics integration of U-BIOPRED sputum samples.

Nazanin Zounemat Kermani, Chuan-Xing Li, Ali Versi, Yusef Badi, Kai Sun, Mahmoud I Abdel-Aziz, Martina Bonatti, Anke-Hilse Maitland-van der Zee, Ratko Djukanovic, Åsa Wheelock and 6 more

Abstract read
In one paragraph

Article in Clinical and translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Beyond Type 2 Inflammation: Why Neutrophils Deserve a Central Role in Refractory Airway Disease.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2026
    Article
  4. Review
  5. Review
  6. Article
  7. Bridging Rare to Common Diseases: Precision Medicine and the Transforming Landscape of Pediatric Allergy and Immunology.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2026
    Review
  8. Asthma endotypes and theratypes.Chinese medical journal pulmonary and critical care medicine · 2026
    Review
  9. Article
  10. Review
  11. Immunotherapy for asthma.Cellular & molecular immunology · 2025
    Review
  12. Review
  13. Multi-omics identifies severe asthma endotypes linked toThe World Allergy Organization journal · 2025
    Article
  14. Review
  15. Article
  16. The immunology of asthma.Nature immunology · 2025
    Review
  17. Multiomic approaches for endotype discovery in allergy/immunology.The Journal of allergy and clinical immunology · 2025
    Article
  18. Article
  19. Review
  20. Microbial influencers: the airway microbiome's role in asthma.The Journal of clinical investigation · 2025
    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

16 authors.

Nazanin Zounemat KermaniNational Heart and Lung Institute, Imperial College London, London, UK.ORCID 0000-0003-2479-3861
Chuan-Xing LiRespiratory Medicine Unit, Department of Medicine & Centre for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Ali VersiNational Heart and Lung Institute, Imperial College London, London, UK.
Yusef BadiNational Heart and Lung Institute, Imperial College London, London, UK.
Kai SunData Science Institute, Imperial College London, London, UK.
Mahmoud I Abdel-AzizDepartment of Pulmonology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Martina BonattiRespiratory Medicine Unit, Department of Medicine & Centre for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Anke-Hilse Maitland-van der ZeeDepartment of Pulmonology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Ratko DjukanovicNIHR Southampton Respiratory Biomedical Research Unit and Clinical and Experimental Sciences, Southampton, UK.
Åsa WheelockRespiratory Medicine Unit, Department of Medicine & Centre for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Sven-Erik DahlenRespiratory Medicine Unit, Department of Medicine & Centre for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Peter HowarthNIHR Southampton Respiratory Biomedical Research Unit and Clinical and Experimental Sciences, Southampton, UK.
Yike GuoData Science Institute, Imperial College London, London, UK.
Kian Fan ChungNational Heart and Lung Institute, Imperial College London, London, UK.ORCID 0000-0001-7101-1426
Ian M AdcockNational Heart and Lung Institute, Imperial College London, London, UK.ORCID 0000-0003-2101-8843
U‐BIOPRED Project Team

Funding

AI-RESPIRE EP/Y018680/1European Federation of Pharmaceutical Industries and Associations (EFPIA)European Union's Seventh Framework Programme FP7/2007-2013Innovative Medicines Initiative 115010PRISM MR/T010371/1UK National Institute for Health Research (NIHR)UK Research and Innovation (UKRI)
6 · The paper itself

Abstract

backgroundClustering approaches using single omics platforms are increasingly used to characterise molecular phenotypes of eosinophilic and neutrophilic asthma. Effective integration of multi-omics platforms should lead towards greater refinement of asthma endotypes across molecular dimensions and indicate key targets for intervention or biomarker development.

objectivesTo determine whether multi-omics integration of sputum leads to improved granularity of the molecular classification of severe asthma.

methodsWe analyzed six -omics data blocks-microarray transcriptomics, gene set variation analysis of microarray transcriptomics, SomaSCAN proteomics assay, shotgun proteomics, 16S microbiome sequencing, and shotgun metagenomic sequencing-from induced sputum samples of 57 severe asthma patients, 15 mild-moderate asthma patients, and 13 healthy volunteers in the U-BIOPRED European cohort. We used Monti consensus clustering algorithm for aggregation of clustering results and Similarity Network Fusion to integrate the 6 multi-omics datasets of the 72 asthmatics.

resultsFive stable omics-associated clusters were identified (OACs). OAC1 had the best lung function with the least number of severe asthmatics with sputum paucigranulocytic inflammation. OAC5 also had fewer severe asthma patients but the highest incidence of atopy and allergic rhinitis, with paucigranulocytic inflammation. OAC3 comprised only severe asthmatics with the highest sputum eosinophilia. OAC2 had the highest sputum neutrophilia followed by OAC4 with both clusters consisting of mostly severe asthma but with more ex/current smokers in OAC4. Compared to OAC4, there was higher incidence of nasal polyps, allergic rhinitis, and eczema in OAC2. OAC2 had microbial dysbiosis with abundant Moraxella catarrhalis and Haemophilus influenzae. OAC4 was associated with pathways linked to IL-22 cytokine activation, with the prediction of therapeutic response to anti-IL22 antibody therapy.

conclusionMulti-omics analysis of sputum in asthma has defined with greater granularity the asthma endotypes linked to neutrophilic and eosinophilic inflammation. Modelling diverse types of high-dimensional interactions will contribute to a more comprehensive understanding of complex endotypes. KEY POINTS: Unsupervised clustering on sputum multi-omics of asthma subjects identified 3 out of 5 clusters with predominantly severe asthma. One severe asthma cluster was linked to type 2 inflammation and sputum eosinophilia while the other 2 clusters to sputum neutrophilia. One severe neutrophilic asthma cluster was linked to Moraxella catarrhalis and to a lesser extent Haemophilus influenzae while the second cluster to activation of IL-22.

Indexed as

AsthmaSputumAdultEosinophilsFemaleHumansMaleMiddle AgedMultiomicsNeutrophilsasthma endotypeconsensus clusteringeosinophilic inflammationgene set variation analysisneutrophilic inflammationpathogenic bacteriasevere asthmasimilarity network fusion

Identifiers

PMID39073027
PMCPMC11283589

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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.