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Exhaled breath analysis is able to identify biomarkers of respiratory and systemic diseases. It was hypothesized that markers of pancreatic function would be identified in the breath of those with diabetes mellitus and cystic fibrosis. Children aged 6-18 years old with diabetes mellitus (DM), cystic fibrosis (CF), cystic fibrosis related diabetes (CFRD) and healthy controls (C) contributed exhaled breath condensate (EBC), with concurrent blood glucose measurements taken from a subset. EBC C-peptide, glucose, sodium concentrations and conductivity were subsequently measured.A total of 104 children were recruited (DM = 56, CF = 26, CFRD = 5, C = 17). C-peptide was detected in EBC: CF 19.6  ±  11.7 pmol L(-1); DM: 9.66  ±  8.27 pmol L(-1); CFRD: 11.9  ±  9.23 pmol L(-1) which was significantly higher than in the control group (0.987  ±  2.26 pmol L(-1)) (p < 0.0001). No statistically significant difference was seen between the three groups for glucose, conductivity or sodium concentration.Glucose was not reliably found in EBC, but C-peptide was found to be higher in CF EBC. This may represent inflammation and a change in airway integrity, rather than increased secretion of this peptide.

Exhaled breath condensate (EBC) is a non-invasive method of sampling airway lining fluids in respiratory diseases. This may be useful in identifying exhaled biomarkers of granulomatous inflammation and pulmonary fibrosis in patients with sarcoidosis. The aim of this pilot study was to identify markers of granulomatous airway inflammation and disease activity including neopterin, transforming growth factor-β1 (TGF-β1) and angiotensin converting enzyme (ACE) in EBC. EBC was collected from 16 patients with sarcoidosis and 22 healthy control subjects. EBC neopterin, and active-TGF-β1 were measured by ELISA. EBC-ACE activity was measured using a colorimetric assay. EBC neopterin was detectable in 3/20 controls and 7/16 patients with sarcoidosis. Patients with sarcoidosis had greater mean neopterin levels compared to control subjects (0.57 ± 0.45 nmol l(-1) versus 0.41 ± 0.22 nmol l(-1), p = 0.04). TGF-β1 was detectable in the EBC of all subjects and concentrations were higher in patients with sarcoidosis compared with controls (115.5 ± 79.6 pg mol(-1) versus 82.3 ± 16.2 pg mol(-1), p = 0.048). There was no difference in EBC ACE activity, which was only detectable in 3/20 healthy controls and 2/16 patients (p = 0.91). EBC markers of granulomatous inflammation are detectable at greater levels in patients with sarcoidosis compared to healthy controls subjects. Larger studies and development of sensitive assays are warranted to examine the disease correlates and predictive utility of these markers.

Exhaled breath condensate (EBC) collection is an innovative method of non-invasively sampling the lung, and can detect a variety of volatile and non-volatile biomarkers, but the disadvantage is the small volume of sample collected. It was hypothesized that a collection system at a lower temperature would increase the volume collected, but may alter the relative concentration of the biomarkers of interest. EBC was collected in a cross-over study using a custom-made collection system, cooled using either wet (4 °C) or dry ice (-20 °C) in randomized order in normal non-smoking volunteers. The volume of the EBC collected per unit time was determined as were conductivity, the concentrations and total amount of protein, hydrogen peroxide, and nitrite/nitrate concentrations. Dry ice was associated with a 79% greater volume of EBC than the wet ice (1387 ± 612 µL; 773 ± 448 µL respectively, p < 0.0001). Conductivity was influenced by the temperature of collection (18.78 ± 6.71 µS cm(-1) for wet ice and 15.32 ± 6.28 µS cm(-1) for dry ice, p = 0.02) as was hydrogen peroxide (1.34 ± 0.88 µg mL(-1) for wet ice and 0.68 ± 0.32 µg mL(-1) for dry ice, p = 0.009) while the concentrations and total values for protein and nitrate/nitrite were not significantly different (p > 0.05). This pilot study suggests that lower collection temperatures facilitate the collection of a larger sample volume. This larger volume is not simply more dilute, with increased water content, nor is there a simple correction factor that can be applied to the EBC biomarkers to correct for the different methods.

Over the last decade, several new agents have been developed for the treatment of pulmonary arterial hypertension (PAH), and blood biomarkers have been developed which aim to monitor such treatment, and which correlate well with physiological parameters, symptoms and mortality. However, little is known regarding biomarkers collected using non-invasive methods such as exhaled breath condensate (EBC). EBC biomarkers show potential as a rapid, repeatable and easy method of sampling the pulmonary vasculature in severely ill patients. The current study aimed to investigate EBC biomarkers in patients with PAH of different aetiologies. We studied 89 patients in four groups: pulmonary arterial hypertension (PAH, n = 30), PAH associated with COPD (COPD/PAH, n = 14), COPD but no PAH (n = 16) and healthy controls (n = 29). Levels of the following EBC markers were measured: amino-terminal pro-brain natriuretic peptide (NT-proBNP), endothelin-1 (ET-1), 6-keto prostaglandin (PG)F(1α), hydrogen peroxide (H(2)O(2)), total oxides of nitrogen (NO(x)), total protein and pH. ET-1 and NT-proBNP were measured in plasma concurrently. Data were analysed with ANOVA or Kruskal Wallis tests where appropriate. Correlations were performed using Pearson's correlation coefficient. NT-proBNP was detectable in EBC and was highest in the PAH group, significantly higher than the COPD/PAH group (194.1 ± 23.3 versus 80.8 ± 22.2 fmol ml(-1), p < 0.05). EBC ET-1 was significantly higher in subjects with PAH (1.53 ± 0.32 fmol ml(-1)) compared to those with COPD/PAH (0.25 ± 0.03 fmol ml(-1), p < 0.05) and controls (0.66 ± 0.18 fmol ml(-1), p < 0.05). 6-keto PGF(1α) was low in the PAH group, significantly lower than the COPD/PAH group (4027 ± 445 versus 8381 ± 1024 pg ml(-1), p < 0.01). EBC biomarkers are measurable in PAH. EBC ET-1 was raised in PAH compared with controls and patients with PAH secondary to COPD, whereas 6-keto PGF(1α) was low. EBC biomarkers may be useful in detection and monitoring of PAH.

The diffuse parenchymal lung diseases (DPLDs) are a group of clinicopathological entities which have recently undergone reclassification. The commonest type of idiopathic DPLD is interstitial pulmonary fibrosis (PF), which is histologically characterized by usual interstitial pneumonia (UIP), with inflammatory changes in the alveoli and subsequent collagen deposition. A similar type of inflammatory change can also be seen with connective tissue disorders. Many mediators are involved, but it is difficult to study these in a non-invasive manner in patients. The aim of the study detailed in this paper was to investigate inflammatory and oxidative stress biomarkers in PF and correlate these with lung function. 20 PF patients and 20 controls participated in the study. Exhaled breath condensate (EBC) was collected over 10 min using a refrigerated condenser, after fractional exhaled nitric oxide (FeNO) and carbon monoxide (eCO) measurement. EBC total nitrogen oxides (NOx), hydrogen peroxide (H(2)O(2)), 8-isoprostane (8-iso), 3-nitrotyrosine (3-NT), pH and total protein were measured. EBC biomarkers were significantly raised in PF compared with controls: EBC 3-NT (2.5 (0.7-8.9) versus 0.3 (0.1-1.1) ng ml(-1), p = 0.02); pH (7.6 ± 0.3 versus 7.4 ± 0.2, p = 0.004); 8-isoprostane (0.2 (0.1-0.4) versus 0.08 (0.04-0.2) ng ml(-1), p = 0.04) and total protein (24.7 ± 21.1 versus 10.7 ± 7.0 µg ml(-1), p = 0.008). FeNO and eCO were also increased (8.6 (7.1-10.4) versus 6.6 (5.6-7.8) ppb, p = 0.04, and 4.5 ± 1.7 versus 2.7 ± 0.7 ppm, p = 0.001, respectively), but no significant differences were found for NOx or H(2)O(2). In conclusion, inflammatory and oxidative stress biomarkers are raised in patients with PF compared with controls. EBC may be useful for detecting and monitoring lung inflammation in PF.

Gastro-oesophageal reflux disease (GORD) has been implicated in the worsening of several respiratory disorders. Current methods of diagnosis lack accuracy, are invasive and can be costly. Recently, novel methods of analysing lung pathophysiology have been developed including the use of an electronic nose and analysis of components of exhaled breath condensate (EBC). We hypothesised that these methods would distinguish patients with GORD from those without GORD in the common obstructive lung diseases and healthy controls. In a cross-sectional study, exhaled breath was analysed using the Cyranose 320 electronic nose, using principal components and canonical discriminant analyses. EBC pH and pepsin were quantified using a pH meter and an enzyme-linked immunosorbent assay, respectively. A standardized reflux disease questionnaire (RDQ) was used to assess reflux symptoms. The Cyranose 320 distinguished exhaled breath profiles of obstructive lung disease patients without GORD from obstructive lung disease patients with GORD (p = 0.023, accuracy 67.6%), asthmatic patients with reflux from asthmatics without GORD (85%, p = < 0.015, interclass M distance > 2.8), but did not produce as robust a profile for patients with COPD and COPD with GORD (p = 0.047, accuracy 64%). Patients with obstructive lung disease and GORD had significantly higher levels of EBC pepsin (9.81 ± interquartile range (IQR) 4.38 ng ml(-1)) than those without GORD (4.6 ± IQR 6.95 ng ml(-1)), as well as healthy controls (3.44 ± IQR 7.87 ng ml(-1); p = < 0.013). EBC pH was not significantly related to the presence of GORD in any group. The RDQ results correlated significantly with the presence of EBC pepsin. This pilot study has shown that exhaled breath profiling can be used for detecting GORD in obstructive lung diseases. While the electronic nose was useful in asthma, EBC pepsin was more helpful in COPD. In this study, several different confounders could potentially have affected results and larger prospective interventional studies are needed.

Biomarkers in exhaled breath condensate (EBC) and fractional exhaled nitric oxide (FeNO) have been widely evaluated in respiratory research as non-invasive methods of sampling the lungs. These methods are particularly attractive in lung transplantation (LTx) as they are simple, repeatable and sensitive. Chronic rejection, manifest by progressive airflow limitation and bronchiolitis obliterans syndrome (BOS), is currently the major limiting factor to long-term survival in LTx. Early detection of BOS and initiation of appropriate treatment could significantly improve survival. Exhaled breath biomarkers could allow early diagnosis of factors associated with chronic rejection. FeNO is elevated in LTx patients with infections and chronic rejection prior to clinical presentation, and several EBC biomarkers and volatile organic compound patterns also show promise in these areas. This review summarizes information on exhaled breath biomarkers in LTx and discusses their potential role in the management of LTx patients.

Exhaled breath condensate (EBC) analysis is a non-invasive method to repeatedly evaluate airway inflammation. Dissolved carbon dioxide contributes to lowering EBC pH which is reversed by degassing with argon. Hypothetically, argon may also improve biomarker stability by removing reactive gases, since many markers are pH sensitive or easily oxidized. In this study, the influence of two degassing methods was assessed on (i) the volume of EBC, (ii) the EBC pH, and (iii) the concentration of H₂O₂ in EBC. EBC was collected from 13 healthy subjects and 12 chronic obstructive pulmonary disease subjects over 20 min, then aliquoted and either left on ice or de-aerated with argon by bubbling or surface delivery at 400 ml min(-1) for 0 to 600 s, to quantify the EBC volume loss and the efficiency of pH equilibration. Biomarker stability was measured by H₂O₂ concentration. Both degassing methods reached a pH equilibrium by 300 s. Bubbling reached pH equilibrium faster (60 s versus 300 s), while having significantly less EBC volume loss (bubbling 3.32 ± 1.31% versus surface 10.74 ± 1.46%, p < 0.0001). The H₂O₂ concentration was higher in non-degassed samples (0.47 ± 0.18 µM, p = 0.017) but similar in the bubbling and surface degassed samples (0.30 ± 0.08 µM versus 0.31 ± 0.10 µM, p = 0.54). The optimal degassing methods were to bubble the aliquots with argon at 400 ml min(-1) for 60 s or surface degassing for 300 s. Both methods resulted in significantly less EBC volume loss than the commonly adopted method of bubbling for 10 min. There was a significant difference in the H₂O₂ concentration between the degassed and the non-degassed samples.

Asbestos usage was very common worldwide in the last century and continues in several countries today. Several diseases occur due to asbestos exposure, including malignant tumours such as malignant mesothelioma of the pleura and lung cancer, which have a very poor prognosis. Asbestos inhalation may also result in more benign conditions such as asbestosis (or pulmonary fibrosis due to asbestos), pleural plaques and pleural thickening. It is predicted that asbestos-associated mortality and morbidity will continue to increase, but methods for diagnosing asbestos-related disease are currently invasive and unsuitable for an increasingly elderly population. New non-invasive methods such as analysis of exhaled breath biomarkers e.g. exhaled nitric oxide (F(E)NO), exhaled breath condensate or of exhaled volatile organic compounds could potentially be extremely useful in these conditions. This article reviews the current literature on this topic and suggests areas for their application in the future.

Exhaled breath contains hundreds of volatile organic compounds (VOCs) that may be used as non-invasive markers of lung disease. Electronic noses (e-noses) can analyse VOCs by composite nanosensor arrays with learning algorithms. This study investigated the use of an e-nose (Cyranose C320) to distinguish the breath of smokers from that of non-smokers. Smoking and non-smoking subjects exhaled from total lung capacity into a 2 L Tedlar bag and these samples were introduced offline to the e-nose in a random order. Two classes of breath, 'smoker' and 'non-smoker', were established and this model was then cross-validated. Principal component analysis then identified the maximal point of difference between classes. Smellprints of breath from smokers were separated from those of non-smokers (cross-validation value, 95%; Mahalanobis distance, 3.96). Subsequently, 15 smokers (mean age 37.9 ± 4.78 years, FEV(1) 3.15 ± 0.21 L), and 24 non-smokers (add mean age and FEV1 as for smokers) were sampled to revalidate the model. The e-nose correctly identified the smoking status in 37 of the 39 subjects. This demonstrates that the e-nose is simple to use in clinical practice and can differentiate the breath of smokers from that of non-smokers. It may prove to be a useful, non-invasive tool for further breath assessment of exposure to other inhaled noxious substances as well as disease monitoring.