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Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air

BACKGROUND: Several classifications of adult asthma patients using cluster analyses based on clinical and demographic information has resulted in clinical phenotypic clusters that do not address molecular mechanisms. Volatile organic compounds (VOC) in exhaled air are released during inflammation in...

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Autores principales: Meyer, Norbert, Dallinga, Jan W, Nuss, Sarah Janine, Moonen, Edwin JC, van Berkel, Joep JBN, Akdis, Cezmi, van Schooten, Frederik Jan, Menz, Günter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4264530/
https://www.ncbi.nlm.nih.gov/pubmed/25431084
http://dx.doi.org/10.1186/s12931-014-0136-8
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author Meyer, Norbert
Dallinga, Jan W
Nuss, Sarah Janine
Moonen, Edwin JC
van Berkel, Joep JBN
Akdis, Cezmi
van Schooten, Frederik Jan
Menz, Günter
author_facet Meyer, Norbert
Dallinga, Jan W
Nuss, Sarah Janine
Moonen, Edwin JC
van Berkel, Joep JBN
Akdis, Cezmi
van Schooten, Frederik Jan
Menz, Günter
author_sort Meyer, Norbert
collection PubMed
description BACKGROUND: Several classifications of adult asthma patients using cluster analyses based on clinical and demographic information has resulted in clinical phenotypic clusters that do not address molecular mechanisms. Volatile organic compounds (VOC) in exhaled air are released during inflammation in response to oxidative stress as a result of activated leukocytes. VOC profiles in exhaled air could distinguish between asthma patients and healthy subjects. In this study, we aimed to classify new asthma endotypes by combining inflammatory mechanisms investigated by VOC profiles in exhaled air and clinical information of asthma patients. METHODS: Breath samples were analyzed for VOC profiles by gas chromatography–mass spectrometry from asthma patients (n = 195) and healthy controls (n = 40). A total of 945 determined compounds were subjected to discriminant analysis to find those that could discriminate healthy from asthmatic subjects. 2-step cluster analysis based on clinical information and VOCs in exhaled air were used to form asthma endotypes. RESULTS: We identified 16 VOCs, which could distinguish between healthy and asthma subjects with a sensitivity of 100% and a specificity of 91.1%. Cluster analysis based on VOCs in exhaled air and the clinical parameters FEV1, FEV1 change after 3 weeks of hospitalization, allergic sensitization, Junipers symptoms score and asthma medications resulted in the formation of 7 different asthma endotype clusters. We identified asthma clusters with different VOC profiles but similar clinical characteristics and endotypes with similar VOC profiles, but distinct clinical characteristics. CONCLUSION: This study demonstrates that both, clinical presentation of asthma and inflammatory mechanisms in the airways should be considered for classification of asthma subtypes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12931-014-0136-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-42645302014-12-13 Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air Meyer, Norbert Dallinga, Jan W Nuss, Sarah Janine Moonen, Edwin JC van Berkel, Joep JBN Akdis, Cezmi van Schooten, Frederik Jan Menz, Günter Respir Res Research BACKGROUND: Several classifications of adult asthma patients using cluster analyses based on clinical and demographic information has resulted in clinical phenotypic clusters that do not address molecular mechanisms. Volatile organic compounds (VOC) in exhaled air are released during inflammation in response to oxidative stress as a result of activated leukocytes. VOC profiles in exhaled air could distinguish between asthma patients and healthy subjects. In this study, we aimed to classify new asthma endotypes by combining inflammatory mechanisms investigated by VOC profiles in exhaled air and clinical information of asthma patients. METHODS: Breath samples were analyzed for VOC profiles by gas chromatography–mass spectrometry from asthma patients (n = 195) and healthy controls (n = 40). A total of 945 determined compounds were subjected to discriminant analysis to find those that could discriminate healthy from asthmatic subjects. 2-step cluster analysis based on clinical information and VOCs in exhaled air were used to form asthma endotypes. RESULTS: We identified 16 VOCs, which could distinguish between healthy and asthma subjects with a sensitivity of 100% and a specificity of 91.1%. Cluster analysis based on VOCs in exhaled air and the clinical parameters FEV1, FEV1 change after 3 weeks of hospitalization, allergic sensitization, Junipers symptoms score and asthma medications resulted in the formation of 7 different asthma endotype clusters. We identified asthma clusters with different VOC profiles but similar clinical characteristics and endotypes with similar VOC profiles, but distinct clinical characteristics. CONCLUSION: This study demonstrates that both, clinical presentation of asthma and inflammatory mechanisms in the airways should be considered for classification of asthma subtypes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12931-014-0136-8) contains supplementary material, which is available to authorized users. BioMed Central 2014-11-28 2014 /pmc/articles/PMC4264530/ /pubmed/25431084 http://dx.doi.org/10.1186/s12931-014-0136-8 Text en © Meyer et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Meyer, Norbert
Dallinga, Jan W
Nuss, Sarah Janine
Moonen, Edwin JC
van Berkel, Joep JBN
Akdis, Cezmi
van Schooten, Frederik Jan
Menz, Günter
Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air
title Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air
title_full Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air
title_fullStr Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air
title_full_unstemmed Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air
title_short Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air
title_sort defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4264530/
https://www.ncbi.nlm.nih.gov/pubmed/25431084
http://dx.doi.org/10.1186/s12931-014-0136-8
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