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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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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. |
format | Online Article Text |
id | pubmed-4264530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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