Advanced search
1 file | 2.26 MB

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

Author
Organization
Abstract
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.
Keywords
EPITHELIAL-CELLS, CLASS DISCOVERY, PHENOTYPES, EXPRESSION, INFLAMMATION, IDENTIFICATION, LYN, Severe asthma, clustering, sputum eosinophilia, partition-around-medoids, algorithm

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 2.26 MB

Citation

Please use this url to cite or link to this publication:

Chicago
Lefaudeux, Diane, Bertrand De Meulder, Matthew J Loza, Nancy Peffer, Anthony Rowe, Frederic Baribaud, Aruna T Bansal, et al. 2017. “U-BIOPRED Clinical Adult Asthma Clusters Linked to a Subset of Sputum Omics.” Journal of Allergy and Clinical Immunology 139 (6): 1797–1807.
APA
Lefaudeux, D., De Meulder, B., Loza, M. J., Peffer, N., Rowe, A., Baribaud, F., Bansal, A. T., et al. (2017). U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics. JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, 139(6), 1797–1807.
Vancouver
1.
Lefaudeux D, De Meulder B, Loza MJ, Peffer N, Rowe A, Baribaud F, et al. U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics. JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY. 2017;139(6):1797–807.
MLA
Lefaudeux, Diane, Bertrand De Meulder, Matthew J Loza, et al. “U-BIOPRED Clinical Adult Asthma Clusters Linked to a Subset of Sputum Omics.” JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY 139.6 (2017): 1797–1807. Print.
@article{8556036,
  abstract     = {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.},
  author       = {Lefaudeux, Diane and De Meulder, Bertrand and Loza, Matthew J and Peffer, Nancy and Rowe, Anthony and Baribaud, Frederic and Bansal, Aruna T and Lutter, Rene and Sousa, Ana R and Corfield, Julie and Pandis, Ioannis and Bakke, Per S and Caruso, Massimo and Chanez, Pascal and Dahlen, Sven-Erik and Fleming, Louise J and Fowler, Stephen J and Horvath, Ildiko and Krug, Norbert and Montuschi, Paolo and Sanak, Marek and Sandstrom, Thomas and Shaw, Dominic E and Singer, Florian and Sterk, Peter J and Roberts, Graham and Adcock, Ian M and Djukanovic, Ratko and Auffray, Charles and Chung, Kian Fan and Study Group, U-BIOPRED and Lambrecht, Bart},
  issn         = {0091-6749},
  journal      = {JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY},
  language     = {eng},
  number       = {6},
  pages        = {1797--1807},
  title        = {U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics},
  url          = {http://dx.doi.org/10.1016/j.jaci.2016.08.048},
  volume       = {139},
  year         = {2017},
}

Altmetric
View in Altmetric
Web of Science
Times cited: