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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.; Corfield, Julie; Dahlén, Sven-Erik; Djukanovic, Ratko; Geiser, Thomas; Horvath, Ildiko; Krug, Nobert; Musial, Jacek; Sun, Kai; Riley, John H.; Shaw, Dominic E.; Sandström, Thomas; Sousa, Ana R.; Montuschi, Paolo; Fowler, Stephen J.; Sterk, Peter J.; Study Group, U-BIOPRED


Paul Brinkman

Ariane H. Wagener

Pieter-Paul Hekking

Aruna T. Bansal

Anke-Hilse Maitland-van der Zee

Yuanyue Wang

Hans Weda

Hugo H. Knobel

Teunis J. Vink

Nicholas J. Rattray

Arnaldo D'Amico

Giorgio Pennazza

Marco Santonico

Diane Lefaudeux

Bertrand De Meulder

Charles Auffray

Per S. Bakke

Massimo Caruso

Pascal Chanez

Kian F. Chung

Julie Corfield

Sven-Erik Dahlén

Ratko Djukanovic

Thomas Geiser

Ildiko Horvath

Nobert Krug

Jacek Musial

Kai Sun

John H. Riley

Thomas Sandström

Ana R. Sousa

Paolo Montuschi

Stephen J. Fowler

Peter J. Sterk

U-BIOPRED Study Group


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.


Brinkman, P., Wagener, A. H., Hekking, P., Bansal, A. T., Maitland-van der Zee, A., Wang, Y., …Study Group, U. (2019). Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma. Journal of Allergy and Clinical Immunology, 143(5), 1811-1820.

Journal Article Type Article
Acceptance Date Oct 22, 2018
Online Publication Date Dec 7, 2018
Publication Date May 1, 2019
Deposit Date Jan 23, 2023
Journal Journal of Allergy and Clinical Immunology
Print ISSN 0091-6749
Electronic ISSN 1097-6825
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 143
Issue 5
Pages 1811-1820
Keywords Electronic nose technology, exhaled breath, volatile organic compound, follow-up, severe asthma, unbiased clustering, eosinophils, neutrophils, oral corticosteroids
Public URL
Publisher URL
PMID 30529449
Additional Information Authors on behalf of the U-BIOPRED Study Group