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; ... (2017). U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics. The Journal of allergy and clinical immunology, 139(6), pp. 1797-1807. Elsevier 10.1016/j.jaci.2016.08.048

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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:

 Journal Article (Original Article)

Division/Institute:

 04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > Forschungsbereich Mu50 > Forschungsgruppe Pneumologie (Erwachsene)
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04 Faculty of Medicine > Department of Gastro-intestinal, Liver and Lung Disorders (DMLL) > Clinic of Pneumology
04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > Unit Childrens Hospital > Forschungsgruppe Pneumologie (Pädiatrie)
04 Faculty of Medicine > Department of Gynaecology, Paediatrics and Endocrinology (DFKE) > Clinic of Paediatric Medicine

UniBE Contributor:

 Singer, Florian

Subjects:

 600 Technology > 610 Medicine & health

ISSN:

 1097-6825

Publisher:

 Elsevier

Language:

 English

Submitter:

 Anette van Dorland

Date Deposited:

 03 Mar 2017 08:56

Last Modified:

 05 Dec 2022 15:01

Publisher DOI:

 10.1016/j.jaci.2016.08.048

PubMed ID:

 27773852

Additional Information:

Prof. Dr. med. Thomas Geiser and Prof. Dr. med. Ch. von Garnier are both members of the U-BIOPRED Study Group and are mentioned as collaborators.

Uncontrolled Keywords:

 Severe asthma; clustering; partition-around-medoids algorithm; sputum eosinophilia

BORIS DOI:

 10.7892/boris.92918

URI:

 https://boris.unibe.ch/id/eprint/92918

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