Exhaled breath condensate (EBC) is a noninvasive method for the study of airway lining fluid. Nuclear magnetic resonance (NMR) spectroscopy can provide biochemical profiles of metabolites in biological samples. The aim of the present study was to validate the NMR metabonomic analysis of EBC in adults, assessing the role of pre-analytical variables (saliva and disinfectant contamination) and the potential clinical feasibility.In total, 36 paired EBC and saliva samples, obtained from healthy subjects, laryngectomised patients and chronic obstructive pulmonary disease patients, were analysed by means of 1 H-NMR spectroscopy followed by principal component analysis. The effect on EBC of disinfectant, used for reusable parts of the condenser, was assessed after different washing procedures. To evaluate intra-day repeatability, eight subjects were asked to collect EBC and saliva twice within the same day. All NMR saliva spectra were significantly different from corresponding EBC samples. EBC taken from condensers washed with recommended procedures invariably showed spectra perturbed by disinfectant. Each EBC sample clustered with corresponding samples of the same group, while presenting intergroup qualitative and quantitative signal differences (94% of the total variance within the data).In conclusion, the nuclear magnetic resonance metabonomic approach could identify the metabolic fingerprint of exhaled breath condensate in different clinical sets of data. Moreover, metabonomics of exhaled breath condensate in adults can discriminate potential perturbations induced by pre-analytical variables.

Nuclear magnetic resonance (NMR)-based metabolomics separates exhaled breath condensate (EBC) profiles of patients affected by pulmonary disease from those of healthy subjects. Here we show the discriminatory ability of NMR-based metabolomics in separating patients exposed to the same risk factor, namely, smoking habit in smoking-related diseases. Fifty duplicated EBC samples from a cohort of current smokers without chronic obstructive pulmonary disease (COPD, henceforth HS), COPD smokers, and subjects with established pulmonary Langerhans cell histiocytosis (PLCH) were analyzed by means of NMR spectroscopy followed by principal component analysis (PCA) and projection to latent structures discriminant analysis (PLS-DA). Clusterization of EBC spectra was disease-specific. COPD and PLCH samples present a profile different from that of HS, showing acetate increase and 1-methylimidazole reduction. An inverse behavior of 2-propanol and isobutyrate characterized COPD with respect to PLCH (high/low in COPD, low/high in PLCH). Both the 2-component and the 3-component PLS-DA models showed a 96% cross-validated accuracy, presenting R(2) and Q(2) values in the ranges of 0.97-0.87 and 0.91-0.78, respectively, and R(2) = 0.87 and Q(2) = 0.78, indicating that data variation is well explained by each model (R(2)), with a good predictivity (Q(2)). NMR spectra of EBC discriminate COPD and PLCH patients from HS and between them, with well-defined metabolic profiles for each class. The specificity of EBC profiles suggests that disease itself drives metabolic separation overwhelming the "common background" due to smoking habit. EBC-NMR investigation offers a powerful tool for assessing the evolution of airway diseases even in the presence of a strong common factor.

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Absence of a nasal NO peak during humming is associated with endoscopic findings suggestive of sinus ostial obstruction in subjects with allergic rhinitis. Measurement of nasal NO during humming may be a simple method to detect sinus abnormalities in these patients.