Abstract
<b>Introduction:</b> The diagnostic accuracy of tests used in early diagnosis of childhood asthma is limited and could benefit from the application of noninvasive omics technologies, both in clinical and population-based setting. <b>Aims and objectives:</b> To identify metabolic content of exhaled breath in asthmatic children and to develop an automatic classification method to measure metabolome changes including molecular mapping. <b>Methods:</b> Group of 13 children (F/M: 6/7, mean age 8.8 ± 1.4 years) with diagnosed childhood asthma and 12 children (F/M: 6/6 mean age 9.5 ± 0.5 years) as control group were examined. The breath phase of all the subjects was collected using a highly porous aseptic material (patented device: holder PL230578, OHIM 002890789-0001). The specimens were analyzed using gas chromatography coupled with mass spectrometry (GC/MS). The algorithms of Spectral Clustering, KMeans, DBSCAN, and hierarchical clustering methods were applied in analysis. <b>Results:</b> In asthmatic and not in control subjects the results of GC/MS showed the cluster of compounds including VOCS (volatile organic compounds), SVOCS (semi volatile organic compounds) in the range of retention time from 12 to 30 min with the control peak of NO<sub>x</sub>, more apparent in asthmatic children. <b>Conclusions:</b> The use of GC/MS in analysis of metabolic content of exhaled air collected with novel porous polymeric material seems to offer a sensitive and differentiating method supporting screening for childhood asthma in clinical and population-based setting.
Published Version
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