Lamkaddam Houssni, Micic Srdjan, Bruderer Tobias, Baumann Yvette, Di Francesco Fabio, Koch Patricia, Lomonaco Tommaso, Prévôt André, Prince Tiwari, Reale Serena, Ripszam Matyas, Weber Ronja, Imad El Haddad, Alexander Moeller
{"title":"Breath profiles in paediatric allergic asthma by proton transfer reaction mass spectrometry.","authors":"Lamkaddam Houssni, Micic Srdjan, Bruderer Tobias, Baumann Yvette, Di Francesco Fabio, Koch Patricia, Lomonaco Tommaso, Prévôt André, Prince Tiwari, Reale Serena, Ripszam Matyas, Weber Ronja, Imad El Haddad, Alexander Moeller","doi":"10.1136/bmjresp-2025-003223","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Enhancing paediatric asthma diagnosis is crucial. Molecular analysis of exhaled breath is a rapidly evolving field aimed at harnessing established and innovative technologies for clinical applications. This study evaluates the feasibility of using online proton-transfer-reaction mass spectrometry (PTR-MS) to identify distinctive breath signatures in children with allergic asthma.</p><p><strong>Methods: </strong>Exhaled breath samples of 81 children (41 with allergic asthma and 40 healthy controls) were analysed using the Vocus CI-TOF mass spectrometer (Tofwerk AG, Switzerland), with mass spectra acquired in H<sub>3</sub>O<sup>+</sup> and NH<sub>4</sub> <sup>+</sup> ionisation modes. Significant mass-to-charge (m/z) features were extracted using the Wilcoxon rank-sum test. Molecular identification was conducted using two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC-Q-TOF).</p><p><strong>Results: </strong>Statistical analysis revealed 89 significant m/z features associated with paediatric allergic asthma, 66 in H<sub>3</sub>O<sup>+</sup> mode and 23 in NH<sub>4</sub> <sup>+</sup> mode. Supervised machine learning achieved an average accuracy of 74.7% in distinguishing between the groups. GCxGC-QTOF analysis identified a subset of significant features, including four previously reported asthma predictors in breath analysis studies. 16 novel asthma predictor candidates were additionally detected, including 7 likely endogenous, 4 unknowns and 3 exogenous. The main group of breath metabolites was structurally related fatty acids, methyl esters and aldehydes, including four known biomarkers of lipid peroxidation.</p><p><strong>Conclusion: </strong>Our findings demonstrate the suitability of PTR-MS for real-time breath analysis in paediatric populations. Moreover, the identification of distinct breath signatures exclusive to allergic asthma in children suggests the potential of leveraging such technology for non-invasive diagnostic applications.</p>","PeriodicalId":9048,"journal":{"name":"BMJ Open Respiratory Research","volume":"12 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Open Respiratory Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/bmjresp-2025-003223","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Enhancing paediatric asthma diagnosis is crucial. Molecular analysis of exhaled breath is a rapidly evolving field aimed at harnessing established and innovative technologies for clinical applications. This study evaluates the feasibility of using online proton-transfer-reaction mass spectrometry (PTR-MS) to identify distinctive breath signatures in children with allergic asthma.
Methods: Exhaled breath samples of 81 children (41 with allergic asthma and 40 healthy controls) were analysed using the Vocus CI-TOF mass spectrometer (Tofwerk AG, Switzerland), with mass spectra acquired in H3O+ and NH4+ ionisation modes. Significant mass-to-charge (m/z) features were extracted using the Wilcoxon rank-sum test. Molecular identification was conducted using two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC-Q-TOF).
Results: Statistical analysis revealed 89 significant m/z features associated with paediatric allergic asthma, 66 in H3O+ mode and 23 in NH4+ mode. Supervised machine learning achieved an average accuracy of 74.7% in distinguishing between the groups. GCxGC-QTOF analysis identified a subset of significant features, including four previously reported asthma predictors in breath analysis studies. 16 novel asthma predictor candidates were additionally detected, including 7 likely endogenous, 4 unknowns and 3 exogenous. The main group of breath metabolites was structurally related fatty acids, methyl esters and aldehydes, including four known biomarkers of lipid peroxidation.
Conclusion: Our findings demonstrate the suitability of PTR-MS for real-time breath analysis in paediatric populations. Moreover, the identification of distinct breath signatures exclusive to allergic asthma in children suggests the potential of leveraging such technology for non-invasive diagnostic applications.
期刊介绍:
BMJ Open Respiratory Research is a peer-reviewed, open access journal publishing respiratory and critical care medicine. It is the sister journal to Thorax and co-owned by the British Thoracic Society and BMJ. The journal focuses on robustness of methodology and scientific rigour with less emphasis on novelty or perceived impact. BMJ Open Respiratory Research operates a rapid review process, with continuous publication online, ensuring timely, up-to-date research is available worldwide. The journal publishes review articles and all research study types: Basic science including laboratory based experiments and animal models, Pilot studies or proof of concept, Observational studies, Study protocols, Registries, Clinical trials from phase I to multicentre randomised clinical trials, Systematic reviews and meta-analyses.