There is an increasing interest in the potential of exhaled biomarkers, such as volatile organic compounds (VOCs), to improve accurate diagnoses and management decisions in pulmonary diseases. The objective of this manuscript is to systematically review the current knowledge on exhaled VOCs with respect to their potential clinical use in asthma, lung cancer, chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF), and respiratory tract infections. A systematic literature search was performed in PubMed, EMBASE, Cochrane database, and reference lists of retrieved studies. Controlled, clinical, English-language studies exploring the diagnostic and monitoring value of VOCs in asthma, COPD, CF, lung cancer and respiratory tract infections were included. Data on study design, setting, participant characteristics, VOCs techniques, and outcome measures were extracted. Seventy-three studies were included, counting in total 3,952 patients and 2,973 healthy controls. The collection and analysis of exhaled VOCs is non-invasive and could be easily applied in the broad range of patients, including subjects with severe disease and children. Various research groups demonstrated that VOCs profiles could accurately distinguish patients with a pulmonary disease from healthy controls. Pulmonary diseases seem to be characterized by a disease specific breath-print, as distinct profiles were found in patients with dissimilar diseases. The heterogeneity of studies challenged the inter-laboratory comparability. In conclusion, profiles of VOCs are potentially able to accurately diagnose various pulmonary diseases. Despite these promising findings, multiple challenges such as further standardization and validation of the diverse techniques need to be mastered before VOCs can be applied into clinical practice.

Background. Asthma control does not yet meet the goals of asthma management guidelines. Non-invasive monitoring of airway inflammation may help to improve the level of asthma control in children. Objectives . (1) To identify a set of exhaled volatile organic compounds (VOCs) that is most predictive for an asthma exacerbation in children. (2) To elucidate the chemical identity of predictive biomarkers. Methods . In a one-year prospective observational study, 96 asthmatic children participated . During clinical visits at 2 month intervals, asthma control, fractional exhaled nitric oxide, lung function (FEV ₁ , FEV ₁ /VC) and VOCs in exhaled breath were determined by means of gas chromatography time-of-flight mass spectrometry. Random Forrest classification modeling was used to select predictive VOCs, followed by plotting of receiver operating characteristic-curves (ROC-curves). Results . An inverse relationship was found between the predictive power of a set of VOCs and the time between sampling of exhaled breath and the onset of exacerbation. The sensitivity and specificity of the model predicting exacerbations 14 days after sampling were 88% and 75%, respectively. The area under the ROC-curve was 90%. The sensitivity for prediction of asthma exacerbations within 21 days after sampling was 63%. In total, 7 VOCs were selected for the classification model: 3 aldehydes, 1 hydrocarbon, 1 ketone, 1 aromatic compound, and 1 unidentified VOC. Conclusion. VOCs in exhaled breath showed potential for predicting asthma exacerbations in children within 14 days after sampling. Before using this in clinical practice, the validity of predicting asthma exacerbations should be studied in a larger cohort.

There is increasing evidence that obesity is related to asthma development and severity. However, it is largely unknown whether weight reduction can influence asthma management, especially in children. To determine the effects of a multifactorial weight reduction intervention on asthma management in overweight/obese children with (a high risk of developing) asthma. An 18-month weight-reduction randomized controlled trial was conducted in 87 children with overweight/obesity and asthma. Every six months, measurements of anthropometry, lung function, lifestyle parameters and inflammatory markers were assessed. Analyses were performed with linear mixed models for longitudinal analyses. After 18 months, the body mass index-standard deviation score decreased by -0.14±0.29 points (p<0.01) in the intervention group and -0.12±0.34 points (p0.05). Asthma features (including asthma control and asthma-related quality of life) and lung function indices (static and dynamic) improved significantly over time in both groups. The FVC% predicted improved over time by 10.1 ± 8.7% in the intervention group (p<0.001), which was significantly greater than the 6.1 ± 8.4% in the control group (p<0.05). Clinically relevant improvements in body weight, lung function and asthma features were found in both the intervention and control group, although some effects were more pronounced in the intervention group (FVC, asthma control, and quality of life). This implies that a weight reduction intervention could be clinically beneficial for children with asthma. ClinicalTrials.gov NCT00998413

Asthma is the most common chronic disease in childhood, characterized by chronic airway inflammation. There are problems with the diagnosis of asthma in young children since the majority of the children with recurrent asthma-like symptoms is symptom free at 6 years, and does not have asthma. With the conventional diagnostic tools it is not possible to differentiate between preschool children with transient symptoms and children with asthma. The analysis of biomarkers of airway inflammation in exhaled breath is a non-invasive and promising technique to diagnose asthma and monitor inflammation in young children. Moreover, relatively new lung function tests (airway resistance using the interrupter technique) have become available for young children. The primary objective of the ADEM study (Asthma DEtection and Monitoring study), is to develop a non-invasive instrument for an early asthma diagnosis in young children, using exhaled inflammatory markers and early lung function measurements. In addition, aetiological factors, including gene polymorphisms and gene expression profiles, in relation to the development of asthma are studied.

In asthma management guidelines the primary goal of treatment is asthma control. To date, asthma control, guided by symptoms and lung function, is not optimal in many children and adults. Direct monitoring of airway inflammation in exhaled breath may improve asthma control and reduce the number of exacerbations. 1) To study the use of fractional exhaled nitric oxide (FeNO) and inflammatory markers in exhaled breath condensate (EBC), in the prediction of asthma exacerbations in a pediatric population. 2) To study the predictive power of these exhaled inflammatory markers combined with clinical parameters. 96 asthmatic children were included in this one-year prospective observational study, with clinical visits every 2 months. Between visits, daily symptom scores and lung function were recorded using a home monitor. During clinical visits, asthma control and FeNO were assessed. Furthermore, lung function measurements were performed and EBC was collected. Statistical analysis was performed using a test dataset and validation dataset for 1) conditionally specified models, receiver operating characteristic-curves (ROC-curves); 2) k-nearest neighbors algorithm. Three conditionally specified predictive models were constructed. Model 1 included inflammatory markers in EBC alone, model 2 included FeNO plus clinical characteristics and the ACQ score, and model 3 included all the predictors used in model 1 and 2. The area under the ROC-curves was estimated as 47%, 54% and 59% for models 1, 2 and 3 respectively. The k-nearest neighbors predictive algorithm, using the information of all the variables in model 3, produced correct predictions for 52% of the exacerbations in the validation dataset. The predictive power of FeNO and inflammatory markers in EBC for prediction of an asthma exacerbation was low, even when combined with clinical characteristics and symptoms. Qualitative improvement of the chemical analysis of EBC may lead to a better non-invasive prediction of asthma exacerbations.

The relationship between exhaled inflammatory markers and asthma control in children is unclear. (1) To explore the association between inflammatory markers in exhaled breath (fractional nitric oxide (FeNO), volatile organic compounds (VOCs), cytokines/chemokines) and asthma control. (2) To assess whether exhaled inflammatory markers are able to discriminate between children with persistently controlled/uncontrolled asthma. 96 asthmatic children were followed-up in a one-year observational study. Every 2 months, the following parameters were assessed: asthma control, FeNO, lung function (forced expiratory volume in 1 s (FEV ₁ ) and forced vital capacity (FVC), exhaled VOCs, and cytokines/chemokines in exhaled breath condensate (EBC). Random Forest was used to analyse the relationship between exhaled inflammatory markers and asthma control. For each model, patients were randomly selected for a training set and validation set. To assess the accuracy of the classification models, receiver operating characteristic-curves (ROC-curves) were generated. No significant association was found between the exhaled inflammatory markers (FeNO, markers in EBC, VOCs) and asthma control (area under the ROC-curve 49%). However, 15 exhaled VOCs could discriminate between subgroups of children with persistently controlled and uncontrolled asthma during all clinical visits (area under the ROC-curve 86%). Adding FeNO and markers in EBC to this model, did not lead to a more accurate classification (area under the ROC-curve 87%). There was no association between exhaled inflammatory markers and asthma control in children. However, children with persistently controlled or uncontrolled asthma during the 12 month study period could be discriminated by a set of VOCs.