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

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; Dominic E. Shaw; Thomas Sandström; Ana R. Sousa; Paolo Montuschi; Stephen J. Fowler; Peter J. Sterk

doi:10.1016/j.jaci.2018.10.058

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

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

Research output: Contribution to journal › Article › peer-review

32 Citations (Scopus)

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 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

Original language	English
Pages (from-to)	1811-1820
Number of pages	10
Journal	Journal of Allergy and Clinical Immunology
Volume	143
DOIs	https://doi.org/10.1016/j.jaci.2018.10.058
Publication status	Published - 2019

Keywords

electronic nose
severe asthma
volatile organic compounds

Access to Document

10.1016/j.jaci.2018.10.058

Cite this

Brinkman, P., Wagener, A. H., Hekking, P.-P., Bansal, A. T., Maitland-Van Der Zee, A.-H., Wang, Y., Weda, H., Knobel, H. H., Vink, T. J., Rattray, N. J., D'Amico, A., Pennazza, G., Santonico, M., Lefaudeux, D., De Meulder, B., Auffray, C., Bakke, P. S., Caruso, M., Chanez, P., ... Sterk, P. J. (2019). Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma. Journal of Allergy and Clinical Immunology, 143, 1811-1820. https://doi.org/10.1016/j.jaci.2018.10.058

@article{f6e15430a12c41f3984b4a06d6b9d6d7,

title = "Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma",

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 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",

keywords = "electronic nose, severe asthma, volatile organic compounds, electronic nose, severe asthma, volatile organic compounds",

author = "Paul Brinkman and Wagener, {Ariane H.} and Pieter-Paul Hekking and Bansal, {Aruna T.} and {Maitland-Van Der Zee}, Anke-Hilse and Yuanyue Wang and Hans Weda and Knobel, {Hugo H.} and Vink, {Teunis J.} and Rattray, {Nicholas J.} and Arnaldo D'Amico and Giorgio Pennazza and Marco Santonico and Diane Lefaudeux and {De Meulder}, Bertrand and Charles Auffray and Bakke, {Per S.} and Massimo Caruso and Pascal Chanez and Chung, {Kian F.} and Julie Corfield and Sven-Erik Dahl{\'e}n and Ratko Djukanovic and Thomas Geiser and Ildiko Horvath and Nobert Krug and Jacek Musial and Kai Sun and Riley, {John H.} and Shaw, {Dominic E.} and Thomas Sandstr{\"o}m and Sousa, {Ana R.} and Paolo Montuschi and Fowler, {Stephen J.} and Sterk, {Peter J.}",

year = "2019",

doi = "10.1016/j.jaci.2018.10.058",

language = "English",

volume = "143",

pages = "1811--1820",

journal = "Journal of Allergy and Clinical Immunology",

issn = "0091-6749",

publisher = "Mosby Year Book Incorporated:6277 Sea Harbor Drive:Orlando, FL 32887:(800)654-2452, (407)345-4000, EMAIL: [email protected], INTERNET: http://www.mosby.com, Fax: (407)363-9661, (314)432-1380",

}

Brinkman, P, Wagener, AH, Hekking, P-P, Bansal, AT, Maitland-Van Der Zee, A-H, Wang, Y, Weda, H, Knobel, HH, Vink, TJ, Rattray, NJ, D'Amico, A, Pennazza, G, Santonico, M, Lefaudeux, D, De Meulder, B, Auffray, C, Bakke, PS, Caruso, M, Chanez, P, Chung, KF, Corfield, J, Dahlén, S-E, Djukanovic, R, Geiser, T, Horvath, I, Krug, N, Musial, J, Sun, K, Riley, JH, Shaw, DE, Sandström, T, Sousa, AR, Montuschi, P, Fowler, SJ & Sterk, PJ 2019, 'Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma', Journal of Allergy and Clinical Immunology, vol. 143, pp. 1811-1820. https://doi.org/10.1016/j.jaci.2018.10.058

TY - JOUR

T1 - Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma

AU - Brinkman, Paul

AU - Wagener, Ariane H.

AU - Hekking, Pieter-Paul

AU - Bansal, Aruna T.

AU - Maitland-Van Der Zee, Anke-Hilse

AU - Wang, Yuanyue

AU - Weda, Hans

AU - Knobel, Hugo H.

AU - Vink, Teunis J.

AU - Rattray, Nicholas J.

AU - D'Amico, Arnaldo

AU - Pennazza, Giorgio

AU - Santonico, Marco

AU - Lefaudeux, Diane

AU - De Meulder, Bertrand

AU - Auffray, Charles

AU - Bakke, Per S.

AU - Caruso, Massimo

AU - Chanez, Pascal

AU - Chung, Kian F.

AU - Corfield, Julie

AU - Dahlén, Sven-Erik

AU - Djukanovic, Ratko

AU - Geiser, Thomas

AU - Horvath, Ildiko

AU - Krug, Nobert

AU - Musial, Jacek

AU - Sun, Kai

AU - Riley, John H.

AU - Shaw, Dominic E.

AU - Sandström, Thomas

AU - Sousa, Ana R.

AU - Montuschi, Paolo

AU - Fowler, Stephen J.

AU - Sterk, Peter J.

PY - 2019

Y1 - 2019

N2 - 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

AB - 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

KW - electronic nose

KW - severe asthma

KW - volatile organic compounds

KW - electronic nose

KW - severe asthma

KW - volatile organic compounds

UR - http://hdl.handle.net/10807/132314

U2 - 10.1016/j.jaci.2018.10.058

DO - 10.1016/j.jaci.2018.10.058

M3 - Article

SN - 0091-6749

VL - 143

SP - 1811

EP - 1820

JO - Journal of Allergy and Clinical Immunology

JF - Journal of Allergy and Clinical Immunology

ER -

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

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this