P Brinkman1, M A van de Pol2, M G Gerritsen1, L D Bos3, T Dekker2, B S Smids2, A Sinha1, C J Majoor1, M M Sneeboer1, H H Knobel4, T J Vink4, F H de Jongh5, R Lutter2, P J Sterk1, N Fens1. 1. Department of Respiratory Medicine, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands. 2. Department of Experimental Immunology, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands. 3. Department of Intensive Care, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands. 4. Philips Research, Eindhoven, The Netherlands. 5. Department of Pulmonary Function, Medisch Spectrum Twente, Enschede, The Netherlands.
Abstract
BACKGROUND: Asthma is a chronic inflammatory airway disease, associated with episodes of exacerbations. Therapy with inhaled corticosteroids (ICS) targets airway inflammation, which aims to maintain and restore asthma control. Clinical features are only modestly associated with airways inflammation. Therefore, we hypothesized that exhaled volatile metabolites identify longitudinal changes between clinically stable episodes and loss of asthma control. OBJECTIVES: To determine whether exhaled volatile organic compounds (VOCs) as measured by gas-chromatography/mass-spectrometry (GC/MS) and electronic nose (eNose) technology discriminate between clinically stable and unstable episodes of asthma. METHODS: Twenty-three patients with (partly) controlled mild to moderate persistent asthma using ICS were included in this prospective steroid withdrawal study. Exhaled metabolites were measured at baseline, during loss of control and after recovery. Standardized sampling of exhaled air was performed, after which samples were analysed by GC/MS and eNose. Univariate analysis of covariance (ANCOVA), followed by multivariate principal component analysis (PCA) was used to reduce data dimensionality. Next paired t tests were utilized to analyse within-subject breath profile differences at the different time-points. Finally, associations between exhaled metabolites and sputum inflammation markers were examined. RESULTS: Breath profiles by eNose showed 95% (21/22) correct classification for baseline vs loss of control and 86% (19/22) for loss of control vs recovery. Breath profiles using GC/MS showed accuracies of 68% (14/22) and 77% (17/22) for baseline vs loss of control and loss of control vs recovery, respectively. Significant associations between exhaled metabolites captured by GC/MS and sputum eosinophils were found (Pearson r≥.46, P<.01). CONCLUSIONS & CLINICAL RELEVANCE: Loss of asthma control can be discriminated from clinically stable episodes by longitudinal monitoring of exhaled metabolites measured by GC/MS and particularly eNose. Part of the uncovered biomarkers was associated with sputum eosinophils. These findings provide proof of principle for monitoring and identification of loss of asthma control by breathomics.
BACKGROUND: Asthma is a chronic inflammatory airway disease, associated with episodes of exacerbations. Therapy with inhaled corticosteroids (ICS) targets airway inflammation, which aims to maintain and restore asthma control. Clinical features are only modestly associated with airways inflammation. Therefore, we hypothesized that exhaled volatile metabolites identify longitudinal changes between clinically stable episodes and loss of asthma control. OBJECTIVES: To determine whether exhaled volatile organic compounds (VOCs) as measured by gas-chromatography/mass-spectrometry (GC/MS) and electronic nose (eNose) technology discriminate between clinically stable and unstable episodes of asthma. METHODS: Twenty-three patients with (partly) controlled mild to moderate persistent asthma using ICS were included in this prospective steroid withdrawal study. Exhaled metabolites were measured at baseline, during loss of control and after recovery. Standardized sampling of exhaled air was performed, after which samples were analysed by GC/MS and eNose. Univariate analysis of covariance (ANCOVA), followed by multivariate principal component analysis (PCA) was used to reduce data dimensionality. Next paired t tests were utilized to analyse within-subject breath profile differences at the different time-points. Finally, associations between exhaled metabolites and sputum inflammation markers were examined. RESULTS: Breath profiles by eNose showed 95% (21/22) correct classification for baseline vs loss of control and 86% (19/22) for loss of control vs recovery. Breath profiles using GC/MS showed accuracies of 68% (14/22) and 77% (17/22) for baseline vs loss of control and loss of control vs recovery, respectively. Significant associations between exhaled metabolites captured by GC/MS and sputum eosinophils were found (Pearson r≥.46, P<.01). CONCLUSIONS & CLINICAL RELEVANCE: Loss of asthma control can be discriminated from clinically stable episodes by longitudinal monitoring of exhaled metabolites measured by GC/MS and particularly eNose. Part of the uncovered biomarkers was associated with sputum eosinophils. These findings provide proof of principle for monitoring and identification of loss of asthma control by breathomics.
Authors: Wadah Ibrahim; Liesl Carr; Rebecca Cordell; Michael J Wilde; Dahlia Salman; Paul S Monks; Paul Thomas; Chris E Brightling; Salman Siddiqui; Neil J Greening Journal: Thorax Date: 2021-01-07 Impact factor: 9.139
Authors: Xin Zhang; Ke Deng; Yulai Yuan; Lei Liu; Shuwen Zhang; Changyong Wang; Gang Wang; Hongping Zhang; Lei Wang; Gaiping Cheng; Lisa G Wood; Gang Wang Journal: Nutrients Date: 2022-06-17 Impact factor: 6.706
Authors: Linsey E S de Groot; Dingyu Liu; Barbara S Dierdorp; Niki Fens; Marianne A van de Pol; Peter J Sterk; Wim Kulik; Miriam E Gerlofs-Nijland; Flemming R Cassee; Elena Pinelli; René Lutter Journal: Environ Health Date: 2020-07-03 Impact factor: 5.984
Authors: Korneliusz Golebski; Michael Kabesch; Erik Melén; Uroš Potočnik; Cornelis M van Drunen; Susanne Reinarts; Anke H Maitland-van der Zee; Susanne J H Vijverberg Journal: Curr Opin Allergy Clin Immunol Date: 2020-04