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 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

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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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/870519
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Medicine > Division of Respiratory Medicine
Identification Number: https://doi.org/10.1016/j.jaci.2016.08.048
Depositing User: Eprints, Support
Date Deposited: 17 May 2018 10:30
Last Modified: 04 May 2020 18:53
URI: https://eprints.nottingham.ac.uk/id/eprint/51856

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