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 HO and NH 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 HO mode and 23 in NH 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.