4.7 Article

Sputum microbiome profiles identify severe asthma phenotypes of relative stability at 12 to 18 months

期刊

JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY
卷 147, 期 1, 页码 123-134

出版社

MOSBY-ELSEVIER
DOI: 10.1016/j.jaci.2020.04.018

关键词

Sputum microbiome; metagenomics; asthma phenotypes; unbiased clusters; follow-up; neutrophils; macrophages; lung function

资金

  1. Innovative Medicines Initiative Joint Undertaking [115010]
  2. European Union
  3. European Federation of Pharmaceutical Industries and Associations
  4. Egyptian Government PhD Research Scholarships

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Two distinct severe asthma phenotypes were identified based on sputum microbiome profiles, showing relative stability over 12 to 18 months. Further validation with an independent cohort of patients with mild-to-moderate asthma confirmed the robustness and consistency of the clustering assignments.
Background: Asthma is a heterogeneous disease characterized by distinct phenotypes with associated microbial dysbiosis. Objectives: Our aim was to identify severe asthma phenotypes based on sputum microbiome profiles and assess their stability after 12 to 18 months. A further aim was to evaluate clusters' robustness after inclusion of an independent cohort of patients with mild-to-moderate asthma. Methods: In this longitudinal multicenter cohort study, sputum samples were collected for microbiome profiling from a subset of the Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adult patient cohort at baseline and after 12 to 18 months of follow-up. Unsupervised hierarchical clustering was performed by using the Bray-Curtis b-diversity measure of microbial profiles. For internal validation, partitioning around medoids, consensus cluster distribution, bootstrapping, and topological data analysis were applied. Follow-up samples were studied to evaluate within-patient clustering stability in patients with severe asthma. Cluster robustness was evaluated by using an independent cohort of patients with mild-to-moderate asthma. Results: Data were available for 100 subjects with severe asthma (median age 55 years; 42% males). Two microbiome-driven clusters were identified; they were characterized by differences in asthma onset, smoking status, residential locations, percentage of blood and/or sputum neutrophils and macrophages, lung spirometry results, and concurrent asthma medications (all P values <.05). The cluster 2 patients displayed a commensal-deficient bacterial profile that was associated with worse asthma outcomes than those of the cluster 1 patients. Longitudinal clusters revealed high relative stability after 12 to 18 months in those with severe asthma. Further inclusion of an independent cohort of 24 patients with mild-to-moderate asthma was consistent with the clustering assignments. Conclusion: Unbiased microbiome-driven clustering revealed 2 distinct robust phenotypes of severe asthma that exhibited relative overtime stability. This suggests that the sputum microbiome may serve as a biomarker for better characterizing asthma phenotypes.

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