Imperial College London
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DrNazaninZounemat Kermani

Faculty of Engineering, Department of Computing

Research Associate
 
 
 
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n.kermani

 
 
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Location

 

William Penney LaboratorySouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Abdel-Aziz:2021:10.1016/j.jaci.2020.04.018,
author = {Abdel-Aziz, MI and Brinkman, P and Vijverberg, SJH and Neerincx, AH and Riley, JH and Bates, S and Hashimoto, S and Kermani, NZ and Chung, KF and Djukanovic, R and Dahlén, S-E and Adcock, IM and Howarth, PH and Sterk, PJ and Kraneveld, AD and Maitland-van, der Zee AH and U-BIOPRED, Study Group},
doi = {10.1016/j.jaci.2020.04.018},
journal = {Journal of Allergy and Clinical Immunology},
pages = {123--134},
title = {Sputum microbiome profiles identify severe asthma phenotypes of relative stability at 12-18 months},
url = {http://dx.doi.org/10.1016/j.jaci.2020.04.018},
volume = {147},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BACKGROUND: Asthma is a heterogeneous disease characterized by distinct phenotypes with associated microbial dysbiosis. OBJECTIVES: To identify severe asthma phenotypes based on sputum microbiome profiles and assess their stability after 12-18 months. Furthermore, to evaluate clusters' robustness after inclusion of an independent mild-to-moderate asthmatics. METHODS: In this longitudinal multicenter cohort study, sputum samples were collected for microbiome profiling from a subset of the U-BIOPRED adult patient cohort at baseline and after 12-18 months of follow-up. Unsupervised hierarchical clustering was performed 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 severe asthmatics. Cluster robustness was evaluated by an independent mild-moderate asthma cohort. RESULTS: Data were available for 100 severe asthma subjects (median age: 55 yrs, 42% males). Two microbiome-driven clusters were identified, characterized by differences in asthma onset, smoking status, residential locations, percentage of blood and/or sputum neutrophils and macrophages, lung spirometry, and concurrent asthma medications (all p-values <.05). Cluster 2 patients displayed a commensal-deficient bacterial profile which was associated with worse asthma outcomes compared to cluster 1. Longitudinal clusters revealed high relative stability after 12-18 months in the severe asthmatics. Further inclusion of 24 independent mild-to-moderate asthmatics was consistent with the clustering assignments. CONCLUSION: Unbiased microbiome-driven clustering revealed two distinct robust severe asthma phenotypes, which exhibited relative overtime stability. This suggests that the sputum microbiome may serve as a biomarker for better characterizing asthma phenotypes.
AU  - Abdel-Aziz,MI
AU  - Brinkman,P
AU  - Vijverberg,SJH
AU  - Neerincx,AH
AU  - Riley,JH
AU  - Bates,S
AU  - Hashimoto,S
AU  - Kermani,NZ
AU  - Chung,KF
AU  - Djukanovic,R
AU  - Dahlén,S-E
AU  - Adcock,IM
AU  - Howarth,PH
AU  - Sterk,PJ
AU  - Kraneveld,AD
AU  - Maitland-van,der Zee AH
AU  - U-BIOPRED,Study Group
DO  - 10.1016/j.jaci.2020.04.018
EP  - 134
PY  - 2021///
SN  - 0091-6749
SP  - 123
TI  - Sputum microbiome profiles identify severe asthma phenotypes of relative stability at 12-18 months
T2  - Journal of Allergy and Clinical Immunology
UR  - http://dx.doi.org/10.1016/j.jaci.2020.04.018
UR  - https://www.ncbi.nlm.nih.gov/pubmed/32353491
UR  - http://hdl.handle.net/10044/1/79185
VL  - 147
ER  -
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