U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics

Background: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. Objectives: We stratified patients with moderate-to-severe asthma based on clinicophysio...

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Main Authors: Lefaudeux, Diane, De Meulder, Bertrand, Loza, Matthew J., Peffer, Nancy, Rowe, Anthony, Baribaud, Frédéric, Bansal, Aruna T., Lutter, Rene, Sousa, Ana R., Corfield, Julie, Pandis, Ioannis, Bakke, Per S., Caruso, Massimo, Chanez, Pascal, Dahlén, Sven-Erik, Fleming, Louise J., Fowler, Stephen J., Horvath, Ildiko, Krug, Norbert, Montuschi, Paolo, Sanak, Marek, Sandstrom, Thomas, Shaw, Dominic E., Singer, Florian, Sterk, Peter J., Roberts, Graham, Adcock, Ian M., Djukanovic, Ratko, Auffray, Charles, Chung, Kian Fan
Format: Article
Published: Elsevier 2017
Online Access:https://eprints.nottingham.ac.uk/51856/
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author Lefaudeux, Diane
De Meulder, Bertrand
Loza, Matthew J.
Peffer, Nancy
Rowe, Anthony
Baribaud, Frédéric
Bansal, Aruna T.
Lutter, Rene
Sousa, Ana R.
Corfield, Julie
Pandis, Ioannis
Bakke, Per S.
Caruso, Massimo
Chanez, Pascal
Dahlén, Sven-Erik
Fleming, Louise J.
Fowler, Stephen J.
Horvath, Ildiko
Krug, Norbert
Montuschi, Paolo
Sanak, Marek
Sandstrom, Thomas
Shaw, Dominic E.
Singer, Florian
Sterk, Peter J.
Roberts, Graham
Adcock, Ian M.
Djukanovic, Ratko
Auffray, Charles
Chung, Kian Fan
author_facet Lefaudeux, Diane
De Meulder, Bertrand
Loza, Matthew J.
Peffer, Nancy
Rowe, Anthony
Baribaud, Frédéric
Bansal, Aruna T.
Lutter, Rene
Sousa, Ana R.
Corfield, Julie
Pandis, Ioannis
Bakke, Per S.
Caruso, Massimo
Chanez, Pascal
Dahlén, Sven-Erik
Fleming, Louise J.
Fowler, Stephen J.
Horvath, Ildiko
Krug, Norbert
Montuschi, Paolo
Sanak, Marek
Sandstrom, Thomas
Shaw, Dominic E.
Singer, Florian
Sterk, Peter J.
Roberts, Graham
Adcock, Ian M.
Djukanovic, Ratko
Auffray, Charles
Chung, Kian Fan
author_sort Lefaudeux, Diane
building Nottingham Research Data Repository
collection Online Access
description Background: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. Objectives: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. Methods: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. Results: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. Conclusion: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.
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spelling nottingham-518562020-05-04T18:53:19Z https://eprints.nottingham.ac.uk/51856/ U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics Lefaudeux, Diane De Meulder, Bertrand Loza, Matthew J. Peffer, Nancy Rowe, Anthony Baribaud, Frédéric Bansal, Aruna T. Lutter, Rene Sousa, Ana R. Corfield, Julie Pandis, Ioannis Bakke, Per S. Caruso, Massimo Chanez, Pascal Dahlén, Sven-Erik Fleming, Louise J. Fowler, Stephen J. Horvath, Ildiko Krug, Norbert Montuschi, Paolo Sanak, Marek Sandstrom, Thomas Shaw, Dominic E. Singer, Florian Sterk, Peter J. Roberts, Graham Adcock, Ian M. Djukanovic, Ratko Auffray, Charles Chung, Kian Fan Background: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. Objectives: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. Methods: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. Results: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. Conclusion: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways. Elsevier 2017-06-30 Article PeerReviewed Lefaudeux, Diane, De Meulder, Bertrand, Loza, Matthew J., Peffer, Nancy, Rowe, Anthony, Baribaud, Frédéric, Bansal, Aruna T., Lutter, Rene, Sousa, Ana R., Corfield, Julie, Pandis, Ioannis, Bakke, Per S., Caruso, Massimo, Chanez, Pascal, Dahlén, Sven-Erik, Fleming, Louise J., Fowler, Stephen J., Horvath, Ildiko, Krug, Norbert, Montuschi, Paolo, Sanak, Marek, Sandstrom, Thomas, Shaw, Dominic E., Singer, Florian, Sterk, Peter J., Roberts, Graham, Adcock, Ian M., Djukanovic, Ratko, Auffray, Charles and Chung, Kian Fan (2017) U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics. Journal of Allergy and Clinical Immunology, 139 (6). pp. 1797-1807. ISSN 0091-6749 https://www.sciencedirect.com/science/article/pii/S009167491631185X?via%3Dihub doi:10.1016/j.jaci.2016.08.048 doi:10.1016/j.jaci.2016.08.048
spellingShingle Lefaudeux, Diane
De Meulder, Bertrand
Loza, Matthew J.
Peffer, Nancy
Rowe, Anthony
Baribaud, Frédéric
Bansal, Aruna T.
Lutter, Rene
Sousa, Ana R.
Corfield, Julie
Pandis, Ioannis
Bakke, Per S.
Caruso, Massimo
Chanez, Pascal
Dahlén, Sven-Erik
Fleming, Louise J.
Fowler, Stephen J.
Horvath, Ildiko
Krug, Norbert
Montuschi, Paolo
Sanak, Marek
Sandstrom, Thomas
Shaw, Dominic E.
Singer, Florian
Sterk, Peter J.
Roberts, Graham
Adcock, Ian M.
Djukanovic, Ratko
Auffray, Charles
Chung, Kian Fan
U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
title U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
title_full U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
title_fullStr U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
title_full_unstemmed U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
title_short U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
title_sort u-biopred clinical adult asthma clusters linked to a subset of sputum omics
url https://eprints.nottingham.ac.uk/51856/
https://eprints.nottingham.ac.uk/51856/
https://eprints.nottingham.ac.uk/51856/