Identification and prospective stability of eNose derived inflammatory phenotypes in severe asthma

Publication date: Available online 6 December 2018

Source: Journal of Allergy and Clinical Immunology

Author(s): P. Brinkman, A.H. Wagener, P.P. Hekking, A.T. Bansal, A.H. Maitland-van der Zee, Y. Wang, H. Weda, H.H. Knobel, T.J. Vink, N.J. Rattray, A. D'Amico, G. Pennazza, M. Santonico, D. Lefaudeux, B. De Meulder, C. Auffray, P.S. Bakke, M. Caruso, P. Chanez, K.F. Chung

Abstract

Background

Severe asthma is a heterogeneous condition as shown by independent cluster analyses based on demographic, clinical and inflammatory characteristics. A next step is to identify molecular driven phenotypes using 'omics'-technologies. Molecular fingerprints of exhaled breath are associated with inflammation and may qualify as non-invasive assessment of severe asthma phenotypes.

Objectives

We aimed: 1) to identify severe asthma phenotypes by exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses); 2) to assess stability of eNose derived phenotypes in relation to within-patient clinical and inflammatory changes.

Methods

In this longitudinal multicenter study exhaled breath samples were taken from an unselected subset of adult severe asthma subjects from the U-BIOPRED cohort. Exhaled metabolites were centrally analyzed by an assembly of eNoses. Unsupervised Ward clustering enhanced by Similarity Profile Analysis (SPA) together with K-Means clustering was performed. For internal validation Partitioning Around Medoids (PAM) and topological data analysis (TDA) were applied. Samples at 12-18 months of prospective follow-up were used to assess longitudinal within-patient stability.

Results

Data were available for 78 subjects (age 55 [IQR: 45-64] years, 41% male). Three eNose-driven clusters (n=26/33/19) were revealed, showing differences in circulating eosinophil- (p=0.045) and neutrophil percentages (p=0.017) and ratio of patients using oral corticosteroids (p=0.035). Longitudinal within-patient cluster stability was associated to changes in sputum eosinophils (p=0.045).

Conclusions

We have identified and followed-up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid usage. This suggests that breath analysis might contribute to the management of severe asthma.

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