Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma.

Brinkman, Paul; Wagener, Ariane H; Hekking, Pieter-Paul; Bansal, Aruna T; Maitland-van der Zee, Anke-Hilse; Wang, Yuanyue; Weda, Hans; Knobel, Hugo H; Vink, Teunis J; Rattray, Nicholas J; D'Amico, Arnaldo; Pennazza, Giorgio; Santonico, Marco; Lefaudeux, Diane; De Meulder, Bertrand; Auffray, Charles; Bakke, Per S; Caruso, Massimo; Chanez, Pascal; Chung, Kian F; ... (2019). Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma. The Journal of allergy and clinical immunology, 143(5), 1811-1820.e7. Elsevier 10.1016/j.jaci.2018.10.058

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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 molecularly driven phenotypes using "omics" technologies. Molecular fingerprints of exhaled breath are associated with inflammation and can qualify as noninvasive assessment of severe asthma phenotypes. OBJECTIVES We aimed (1) to identify severe asthma phenotypes using exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses) and (2) to assess the 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 adults with severe asthma from the U-BIOPRED cohort. Exhaled metabolites were analyzed centrally by using an assembly of eNoses. Unsupervised Ward clustering enhanced by similarity profile analysis together with K-means clustering was performed. For internal validation, partitioning around medoids and topological data analysis were applied. Samples at 12 to 18 months of prospective follow-up were used to assess longitudinal within-patient stability. RESULTS Data were available for 78 subjects (age, 55 years [interquartile range, 45-64 years]; 41% male). Three eNose-driven clusters (n = 26/33/19) were revealed, showing differences in circulating eosinophil (P = .045) and neutrophil (P = .017) percentages and ratios of patients using oral corticosteroids (P = .035). Longitudinal within-patient cluster stability was associated with changes in sputum eosinophil percentages (P = .045). CONCLUSIONS We have identified and followed up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid use. This suggests that breath analysis can contribute to the management of severe asthma.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Gastro-intestinal, Liver and Lung Disorders (DMLL) > Clinic of Pneumology

UniBE Contributor:

Geiser, Thomas

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1097-6825

Publisher:

Elsevier

Language:

English

Submitter:

Rahel Holderegger

Date Deposited:

07 Mar 2019 17:46

Last Modified:

24 Oct 2019 11:27

Publisher DOI:

10.1016/j.jaci.2018.10.058

PubMed ID:

30529449

Uncontrolled Keywords:

Electronic nose technology eosinophils exhaled breath follow-up neutrophils oral corticosteroids severe asthma unbiased clustering volatile organic compound

BORIS DOI:

10.7892/boris.123963

URI:

https://boris.unibe.ch/id/eprint/123963

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