TY - JOUR
T1 - Sputum microbiome profiles identify severe asthma phenotypes of relative stability at 12 to 18 months
AU - Abdel-Aziz, M.I.
AU - Brinkman, P.
AU - Vijverberg, S.J.H.
AU - Neerincx, A.H.
AU - Riley, J.H.
AU - Bates, S.
AU - Hashimoto, S.
AU - Kermani, N.Z.
AU - Chung, K.F.
AU - Djukanovic, R.
AU - Dahlén, S.-E.
AU - Adcock, I.M.
AU - Howarth, P.H.
AU - Sterk, P.J.
AU - Kraneveld, A.D.
AU - Maitland-van der Zee, A.H.
AU - U-BIOPRED Study Group
PY - 2021/1/1
Y1 - 2021/1/1
N2 - © 2020 American Academy of Allergy, Asthma & ImmunologyBackground: 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 β-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.
AB - © 2020 American Academy of Allergy, Asthma & ImmunologyBackground: 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 β-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.
UR - https://www.scopus.com/pages/publications/85085769714
UR - https://www.scopus.com/pages/publications/85085769714#tab=citedBy
U2 - 10.1016/j.jaci.2020.04.018
DO - 10.1016/j.jaci.2020.04.018
M3 - Article
SN - 0091-6749
VL - 147
SP - 123
EP - 134
JO - Journal of Allergy and Clinical Immunology
JF - Journal of Allergy and Clinical Immunology
IS - 1
ER -