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 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.

Exhaled volatile organic compounds predict exacerbations of childhood asthma in a 1-year prospective study.

The hypothesis was that prediction of asthma exacerbations in children is possible by profiles of exhaled volatile organic compounds (VOCs), a noninvasive measure of airway inflammation. The aims of the present study were to determine: 1) whether VOCs in exhaled breath are able to predict asthma exacerbations; and 2) the time course and chemical background of the most predictive VOCs. A prospective study was performed in 40 children with asthma over 1 year. At standard 2-month intervals, exhaled nitric oxide fraction (FeNO), VOC profiles in exhaled breath samples, lung function and symptoms were determined in a standardised way. VOC profiles were analysed by gas chromatography-time-of-flight mass spectrometry. 16 out of 40 children experienced an exacerbation. With support vector machine analysis, the most optimal model of baseline measurements versus exacerbation within patients was based on six VOCs (correct classification 96%, sensitivity 100% and specificity 93%). The model of baseline values of patients with compared to those without an exacerbation consisted of seven VOCs (correct classification 91%, sensitivity 79% and specificity 100%). FeNO and lung function were not predictive for exacerbations. This study indicates that a combination of different exhaled VOCs is able to predict exacerbations of childhood asthma.

Exhaled breath profiling in diagnosing wheezy preschool children.

Although wheeze is common in preschool children, the underlying pathophysiology has not yet been disentangled. Volatile organic compounds (VOCs) in exhaled breath may serve as noninvasive markers of early wheeze. We aimed to assess the feasibility of VOC collection in preschool children, and to study whether a VOC profile can differentiate between children with and without recurrent wheeze. We included children (mean (range) age 3.3 (1.9-4.5) yrs) with (n=202) and without (n=50) recurrent wheeze. Exhaled VOCs were analysed by gas chromatography-time-of-flight mass spectrometry. VOC profiles were generated by ANOVA simultaneous component analysis (ASCA) and sparse logistic regression (SLR). Exhaled breath collection was possible in 98% of the children. In total, 913 different VOCs were detected. The signal-to-noise ratio improved after correction for age, sex and season using ASCA pre-processing. An SLR model with 28 VOCs correctly classified 83% of the children (84% sensitivity, 80% specificity). After six-fold cross-validation, 73% were correctly classified (79% sensitivity, 50% specificity). Assessment of VOCs in exhaled breath is feasible in young children. VOC profiles are able to distinguish children with and without recurrent wheeze with a reasonable accuracy. This proof of principle paves the way for additional research on VOCs in preschool wheezing.

The versatile use of exhaled volatile organic compounds in human health and disease.

Exhaled breath contains thousands of volatile organic compounds (VOCs) of which the composition varies depending on health status. Various metabolic processes within the body produce volatile products that are released into the blood and will be passed on to the airway once the blood reaches the lungs. Moreover, the occurrence of chronic inflammation and/or oxidative stress can result in the excretion of volatile compounds that generate unique VOC patterns. Consequently, measuring the total amount of VOCs in exhaled air, a kind of metabolomics also referred to as breathomics, for clinical diagnosis and monitoring purposes gained increased interest over the last years. This paper describes the currently available methodologies regarding sampling, sample analysis and data processing as well as their advantages and potential drawbacks. Additionally, different application possibilities of VOC profiling are discussed. Until now, breathomics has merely been applied for diagnostic purposes. Exhaled air analysis can, however, also be applied as an analytical or monitoring tool. Within the analytic perspective, the use of VOCs as biomarkers of oxidative stress, inflammation or carcinogenesis is described. As monitoring tool, breathomics can be applied to elucidate the heterogeneity observed in chronic diseases, to study the pathogen(s) responsible for occurring infections and to monitor treatment efficacy.

Metabolomics of volatile organic compounds in cystic fibrosis patients and controls.

In cystic fibrosis (CF), airway inflammation causes an increased production of reactive oxygen species, responsible for degradation of cell membranes. During this process, volatile organic compounds (VOCs) are formed. Measurement of VOCs in exhaled breath of CF patients may be useful for the assessment of airway inflammation. This study investigates whether "metabolomics' of VOCs could discriminate between CF and controls, and between CF patients with and without Pseudomonas colonization. One hundred five children (48 with CF, 57 controls) were included in this study. After exhaled breath collection, samples were transferred onto tubes containing active carbon to adsorb and stabilize VOCs. Samples were analyzed by gas chromatography-time of flight-mass spectrometry to assess VOC profiles. Analysis showed that 1099 VOCs had a prevalence of at least 7%. By using 22 VOCs, a 100% correct identification of CF patients and controls was possible. With 10 VOCs, 92% of the subjects were correctly classified. The reproducibility of VOC measurements with a 1-h interval was very good (match factor 0.90 +/- 0.038). We conclude that metabolomics of VOCs in exhaled breath was possible in a reproducible way. This new technique was able to discriminate not only between CF patients and controls but also between CF patients with or without Pseudomonas colonization.