Volatile organic compounds in headspace characterize isolated bacterial strains independent of growth medium or antibiotic sensitivity.

INTRODUCTION: Early and reliable determination of bacterial strain specificity and antibiotic resistance is critical to improve sepsis treatment. Previous research demonstrated the potential of headspace analysis of volatile organic compounds (VOCs) to differentiate between various microorganisms associated with pulmonary infections in vitro. This study evaluates whether VOC analysis can also discriminate antibiotic sensitive from resistant bacterial strains when cultured on varying growth media. METHODS: Both antibiotic-sensitive and -resistant strains of Pseudomonas aeruginosa, Staphylococcus aureus and Klebsiella pneumonia were cultured on 4 different growth media, i.e. Brain Heart Infusion, Marine Broth, Müller-Hinton and Trypticase Soy Agar. After overnight incubation at 37°C, the headspace air of the cultures was collected on stainless steel desorption tubes and analyzed by gas chromatography time-of-flight mass spectrometry (GC-tof-MS). Statistical analysis was performed using regularized multivariate analysis of variance and cross validation. RESULTS: The three bacterial species could be correctly recognized based on the differential presence of 14 VOCs (p<0.001). This discrimination was not influenced by the different growth media. Interestingly, a clear discrimination could be made between the antibiotic-resistant and -sensitive variant of Pseudomonas aeruginosa (p<0.001) based on their species-specific VOC signature. CONCLUSION: This study demonstrates that isolated microorganisms, including antibiotic-sensitive and -resistant strains of Pseudomonas aeruginosa, could be identified based on their excreted VOCs independent of the applied growth media. These findings suggest that the discriminating volatiles are associated with the microorganisms themselves rather than with their growth medium. This study exemplifies the potential of VOC analysis as diagnostic tool in medical microbiology. However, validation of our results in appropriate in vivo models is critical to improve translation of breath analysis to clinical applications.

Detecting Colorectal Adenomas and Cancer Using Volatile Organic Compounds in Exhaled Breath: A Proof-of-Principle Study to Improve Screening.

INTRODUCTION: Early detection of colorectal cancer (CRC) by screening programs is crucial because survival rates worsen at advanced stages. However, the currently used screening method, the fecal immunochemical test (FIT), suffers from a high number of false-positives and is insensitive for detecting advanced adenomas (AAs), resulting in false-negatives for these premalignant lesions. Therefore, more accurate, noninvasive screening tools are needed. In this study, the utility of analyzing volatile organic compounds (VOCs) in exhaled breath in a FIT-positive population to detect the presence of colorectal neoplasia was studied. METHODS: In this multicenter prospective study, breath samples were collected from 382 FIT-positive patients with subsequent colonoscopy participating in the national Dutch bowel screening program (n = 84 negative controls, n = 130 non-AAs, n = 138 AAs, and n = 30 CRCs). Precolonoscopy exhaled VOCs were analyzed using thermal desorption-gas chromatography-mass spectrometry, and the data were preprocessed and analyzed using machine learning techniques. RESULTS: Using 10 discriminatory VOCs, AAs could be distinguished from negative controls with a sensitivity and specificity of 79% and 70%, respectively. Based on this biomarker profile, CRC and AA combined could be discriminated from controls with a sensitivity and specificity of 77% and 70%, respectively, and CRC alone could be discriminated from controls with a sensitivity and specificity of 80% and 70%, respectively. Moreover, the feasibility to discriminate non-AAs from controls and AAs was shown. DISCUSSION: VOCs in exhaled breath can detect the presence of AAs and CRC in a CRC screening population and may improve CRC screening in the future.

Implementation of quality controls is essential to prevent batch effects in breathomics data and allow for cross-study comparisons.

Exhaled breath analysis has become a promising monitoring tool for various ailments by identifying volatile organic compounds (VOCs) as indicative biomarkers excreted in the human body. Throughout the process of sampling, measuring, and data processing, non-biological variations are introduced in the data leading to batch effects. Algorithmic approaches have been developed to cope with within-study batch effects. Batch differences, however, may occur among different studies too, and up-to-date, ways to correct for cross-study batch effects are lacking; ultimately, cross-study comparisons to verify the uniqueness of found VOC profiles for a specific disease may be challenging. This study applies within-study batch-effect-correction approaches to correct for cross-study batch effects; suggestions are made that may help prevent the introduction of cross-study variations. Three batch-effect-correction algorithms were investigated: zero-centering, combat, and the analysis of covariance framework. The breath samples were collected from inflammatory bowel disease ([Formula: see text]), chronic liver disease ([Formula: see text]), and irritable bowel syndrome ([Formula: see text]) patients at different periods, and they were analysed via gas chromatography-mass spectrometry. Multivariate statistics were used to visualise and verify the results. The visualisation of the data before any batch-effect-correction technique was applied showed a clear distinction due to probable batch effects among the datasets of the three cohorts. The visualisation of the three datasets after implementing all three correction techniques showed that the batch effects were still present in the data. Predictions made using partial least squares discriminant analysis and random forest confirmed this observation. The within-study batch-effect-correction approaches fail to correct for cross-study batch effects present in the data. The present study proposes a framework for systematically standardising future breathomics data by using internal standards or quality control samples at regular analysis intervals. Further knowledge regarding the nature of the unsolicited variations among cross-study batches must be obtained to move the field further.

Exhaled Volatile Organic Compounds Are Able to Discriminate between Neutrophilic and Eosinophilic Asthma.

Rationale: Analysis of exhaled breath for asthma phenotyping using endogenously generated volatile organic compounds (VOCs) offers the possibility of noninvasive diagnosis and therapeutic monitoring. Induced sputum is indeed not widely available and markers of neutrophilic asthma are still lacking.Objectives: To determine whether analysis of exhaled breath using endogenously generated VOCs can be a surrogate marker for recognition of sputum inflammatory phenotypes.Methods: We conducted a prospective study on 521 patients with asthma recruited from the University Asthma Clinic of Liege. Patients underwent VOC measurement, fraction of exhaled nitric oxide (FeNO) spirometry, sputum induction, and gave a blood sample. Subjects with asthma were classified in three inflammatory phenotypes according to their sputum granulocytic cell count.Measurements and Main Results: In the discovery study, seven potential biomarkers were highlighted by gas chromatography-mass spectrometry in a training cohort of 276 patients with asthma. In the replication study (n = 245), we confirmed four VOCs of interest to discriminate among asthma inflammatory phenotypes using comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry. Hexane and 2-hexanone were identified as compounds with the highest classification performance in eosinophilic asthma with accuracy comparable to that of blood eosinophils and FeNO. Moreover, the combination of FeNO, blood eosinophils, and VOCs gave a very good prediction of eosinophilic asthma (area under the receiver operating characteristic curve, 0.9). For neutrophilic asthma, the combination of nonanal, 1-propanol, and hexane had a classification performance similar to FeNO or blood eosinophils in eosinophilic asthma. Those compounds were found in higher levels in neutrophilic asthma.Conclusions: Our study is the first attempt to characterize VOCs according to sputum granulocytic profile in a large population of patients with asthma and provide surrogate markers for neutrophilic asthma.

Limited clinical value of exhaled volatile organic compound measurements in childhood asthma.

Exhaled volatile organic compound measurements do not aid the clinician diagnosing asthma in children http://ow.ly/Z2d930lpZ60.

The necessity of external validation in exhaled breath research: a case study of sarcoidosis.

As in other disciplines of 'omics' research, reproducibility is a major problem in exhaled breath research. Many studies report discriminatory volatiles in the same disease, yet the similarity between lists of identified compounds is low. This can occur due to many factors including the lack of internal and, in particular, external validation. In an ideal situation, an external validation-sampled at, for example, a different location-is always included to ensure generalization of the observed findings to a general population. In this study, we hypothesized that sarcoidosis patients and healthy controls could be discriminated based on a group of volatile organic compounds (VOCs) in exhaled breath and that these discriminating VOCs could be validated in an external population. The first dataset consisted of 87 sarcoidosis patients and 27 healthy controls, whereas the validation dataset consisted of 25 patients and 29 controls. Using the first dataset, nine VOCs were found that could predict sarcoidosis with 79.4% accuracy. Different types of internal and external validation were tested to assess the validity of the nine VOCs. Of the internal validations, randomly setting aside part of the data achieved the most accurate predictions while external validation was only possible by building a new prediction model that yielded a promising yet not entirely convincing accuracy of 74% due to the indirect approach. In conclusion, the initial results of this study are very promising but, as the results of our validation set already indicated, may not be reproducible in other studies. In order to achieve a reliable diagnostic breath fingerprint for sarcoidosis, we encourage other scientists to validate the presented findings. TRIAL REGISTRATION: NCT00741572 & NCT02361281.

Volatile organic compounds discriminate between eosinophilic and neutrophilic inflammation in vitro.

Inflammation associated oxidative stress leads to peroxidation of polyunsaturated fatty acids thereby generating volatile organic compounds (VOCs). The integrative analysis of the total amount of VOCs released by eosinophils and neutrophils in vitro enables the search for those compounds that discriminates between various inflammatory conditions. The approach comprises isolating eosinophils and neutrophils from 30 ml of blood of healthy non-smoking volunteers by gradient centrifugation, using lymphoprep. Eosinophils are separated from neutrophils by immunomagnetic cell separation using anti-CD16. Cells are activated with phorbol 12-myristate 13-acetate and VOCs from the headspace are collected at time 0', 30', 60' and 90' by introduction of ultra-pure nitrogen in the closed flasks at a flow rate of 200 ml min(-1) during 10 min. The gases are trapped onto a sorption tube and analyzed by gas chromatography-time-of-flight-mass spectometry (GC-TOF-MS) in order to identify VOCs released in the headspace by activated neutrophils and eosinophils. Eosinophils and neutrophils were isolated from 26 healthy non-smoking volunteers. The average absolute number of eosinophils and neutrophils upon isolation was 3.5 × 10(6) and 19.4 × 10(6), respectively. The volatome in headspace consisted of 2116 compounds and those compounds present in at least 8% of the samples (1123 compounds) were used for further discriminant analysis. Discriminant analysis showed that two VOCs were able to distinguish between eosinophilic and neutrophilic cultures in the unactivated state with 100% correct classification of the entire data set and upon cross validation while five VOCs were able to discriminate between activated eosinophils and neutrophils with 96% correct classification in the original set and upon cross-validation. Analysis of VOCs seems to be a very promising approach in identifying eosinophilic and neutrophilic inflammation but it needs further development and in vivo confirmation.

A profile of volatile organic compounds in exhaled air as a potential non-invasive biomarker for liver cirrhosis.

Early diagnosis of liver cirrhosis may prevent progression and development of complications. Liver biopsy is the current standard, but is invasive and associated with morbidity. We aimed to identify exhaled volatiles within a heterogeneous group of chronic liver disease (CLD) patients that discriminates those with compensated cirrhosis (CIR) from those without cirrhosis, and compare this with serological markers. Breath samples were collected from 87 CLD and 34 CIR patients. Volatiles in exhaled air were measured by gas chromatography mass spectrometry. Discriminant Analysis was performed to identify the optimal panel of serological markers and VOCs for classifying our patients using a random training set of 27 CIR and 27 CLD patients. Two randomly selected independent internal validation sets and permutation test were used to validate the model. 5 serological markers were found to distinguish CIR and CLD patients with a sensitivity of 0.71 and specificity of 0.84. A set of 11 volatiles discriminated CIR from CLD patients with sensitivity of 0.83 and specificity of 0.87. Combining both did not further improve accuracy. A specific exhaled volatile profile can predict the presence of compensated cirrhosis among CLD patients with a higher accuracy than serological markers and can aid in reducing liver biopsies.

Volatile Organic Compounds in Exhaled Air as Novel Marker for Disease Activity in Crohn's Disease: A Metabolomic Approach.

BACKGROUND: Disappearance of macroscopic mucosal inflammation predicts long-term outcome in Crohn's disease (CD). It can be assessed by ileocolonoscopy, which is, however, an invasive and expensive procedure. Disease activity indices do not correlate well with endoscopic activity and noninvasive markers have a low sensitivity in subgroups of patients. Volatile organic compounds (VOCs) in breath are of increasing interest as noninvasive markers. The aim of this study was to investigate whether VOCs can accurately differentiate between active CD and remission. METHODS: Patients participated in a 1-year follow-up study and Harvey-Bradshaw index, blood, fecal, and breath samples were collected at regular intervals. Patients were stratified into 2 groups: active (fecal calprotectin >250 µg/g) or inactive (Harvey-Bradshaw index <4, C-reactive protein <5 mg/L, and fecal calprotectin <100 µg/g) disease. Breath samples were analyzed by gas chromatography-time-of-flight mass spectrometry. Random forest analyses were used to find the most discriminatory VOCs. RESULTS: Eight hundred thirty-five breath-o-grams were measured, 140 samples were assigned as active, 135 as inactive disease, and 110 samples of healthy controls. A set of 10 discriminatory VOCs correctly predicted active CD in 81.5% and remission in 86.4% (sensitivity 0.81, specificity 0.80, AUC 0.80). These VOCs were combined into a single disease activity score that classified disease activity in more than 60% of the previously undetermined individuals. CONCLUSIONS: We showed that VOCs can separate healthy controls and patients with active CD and CD in remission in a real-life cohort. Analysis of exhaled air is an interesting new noninvasive application for monitoring mucosal inflammation in inflammatory bowel disease.

Exhaled biomarkers and gene expression at preschool age improve asthma prediction at 6 years of age.

RATIONALE: A reliable asthma diagnosis is difficult in wheezing preschool children. OBJECTIVES: To assess whether exhaled biomarkers, expression of inflammation genes, and early lung function measurements can improve a reliable asthma prediction in preschool wheezing children. METHODS: Two hundred two preschool recurrent wheezers (aged 2-4 yr) were prospectively followed up until 6 years of age. At 6 years of age, a diagnosis (asthma or transient wheeze) was based on symptoms, lung function, and asthma medication use. The added predictive value (area under the receiver operating characteristic curve [AUC]) of biomarkers to clinical information (assessed with the Asthma Predictive Index [API]) assessed at preschool age in diagnosing asthma at 6 years of age was determined with a validation set. Biomarkers in exhaled breath condensate, exhaled volatile organic compounds (VOCs), gene expression, and airway resistance were measured. MEASUREMENTS AND MAIN RESULTS: At 6 years of age, 198 children were diagnosed (76 with asthma, 122 with transient wheeze). Information on exhaled VOCs significantly improved asthma prediction (AUC, 89% [increase of 28%]; positive predictive value [PPV]/negative predictive value [NPV], 82/83%), which persisted in the validation set. Information on gene expression of toll-like receptor 4, catalase, and tumor necrosis factor-α significantly improved asthma prediction (AUC, 75% [increase of 17%]; PPV/NPV, 76/73%). This could not be confirmed after validation. Biomarkers in exhaled breath condensate and airway resistance (pre- and post- bronchodilator) did not improve an asthma prediction. The combined model with VOCs, gene expression, and API had an AUC of 95% (PPV/NPV, 90/89%). CONCLUSIONS: Adding information on exhaled VOCs and possibly expression of inflammation genes to the API significantly improves an accurate asthma diagnosis in preschool children. Clinical trial registered with www.clinicaltrial.gov (NCT 00422747).

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.

Analysis of volatile organic compounds in exhaled breath by gas chromatography-mass spectrometry combined with chemometric analysis.

Analysis of exhaled breath samples reveals the presence of many volatile organic compounds (VOCs). The VOC composition of the breath, the so-called breath profile, contains a variety of information including the health status and condition of the organism that produced the sample. Therefore, breath profiling can be used in diagnosing and monitoring disease and other characteristics of the organism, such as phenotype, diet, and exercise. Among various techniques available for breath analysis, GC-MS provides the most extensive information with regard to the qualitative and quantitative presence of VOCs in breath.

Profiling of volatile organic compounds in exhaled breath as a strategy to find early predictive signatures of asthma in children.

Wheezing is one of the most common respiratory symptoms in preschool children under six years old. Currently, no tests are available that predict at early stage who will develop asthma and who will be a transient wheezer. Diagnostic tests of asthma are reliable in adults but the same tests are difficult to use in children, because they are invasive and require active cooperation of the patient. A non-invasive alternative is needed for children. Volatile Organic Compounds (VOCs) excreted in breath could yield such non-invasive and patient-friendly diagnostic. The aim of this study was to identify VOCs in the breath of preschool children (inclusion at age 2-4 years) that indicate preclinical asthma. For that purpose we analyzed the total array of exhaled VOCs with Gas Chromatography time of flight Mass Spectrometry of 252 children between 2 and 6 years of age. Breath samples were collected at multiple time points of each child. Each breath-o-gram contained between 300 and 500 VOCs; in total 3256 different compounds were identified across all samples. Using two multivariate methods, Random Forests and dissimilarity Partial Least Squares Discriminant Analysis, we were able to select a set of 17 VOCs which discriminated preschool asthmatic children from transient wheezing children. The correct prediction rate was equal to 80% in an independent test set. These VOCs are related to oxidative stress caused by inflammation in the lungs and consequently lipid peroxidation. In conclusion, we showed that VOCs in the exhaled breath predict the subsequent development of asthma which might guide early treatment.

Profile of volatile organic compounds in exhaled breath changes as a result of gluten-free diet.

In the present longitudinal study, we followed volatile organic compounds (VOCs) excreted in exhaled breath of 20 healthy individuals over time, while adhering to a gluten-free diet for 4 weeks prior to adherence to a normal diet. We used gas chromatography coupled with mass spectrometry (TD-GC-tof-MS) in combination with chemometric analysis to detect an array of VOCs in exhaled breath. Multivariate analysis was applied to extract the maximal information from the obtained data. Dietary intake was assessed to verify adherence to the diet and to get insight into macronutrient intake during the intervention period. A set of 12 volatile compounds distinguished the samples obtained during the gluten-free diet from those obtained during a normal diet. Seven compounds could be chemically identified (2-butanol, octane, 2-propyl-1pentanol, nonanal, dihydro-4-methyl-2(3H)-furanone, nonanoic acid and dodecanal) and speculated on a possible origin. Our findings suggest that a gluten-free dietary period had a reversible impact on participants' excreted metabolites visible in their breath. Several explanations are proposed of influencing metabolic status through dietary interventions. Although the exact origin of the discriminating compounds is not yet known, the main goal of this paper was to share a new potential use of exhaled air analysis and might become a useful tool in fields of nutrition and metabolism.

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.

Non-alcoholic steatohepatitis: a non-invasive diagnosis by analysis of exhaled breath.

BACKGROUND & AIMS: Histological evaluation of a liver biopsy is the current gold standard to diagnose non-alcoholic steatohepatitis (NASH), but the procedure to obtain biopsies is associated with morbidity and high costs. Hence, only subjects at high risk are biopsied, leading to underestimation of NASH prevalence, and undertreatment. Since analysis of volatile organic compounds in breath has been shown to accurately identify subjects with other chronic inflammatory diseases, we investigated its potential as a non-invasive tool to diagnose NASH. METHODS: Wedge-shaped liver biopsies from 65 subjects (BMI 24.8-64.3 kg/m(2)) were obtained during surgery and histologically evaluated. The profile of volatile organic compounds in pre-operative breath samples was analyzed by gas chromatography-mass spectrometry and related to liver histology scores and plasma parameters of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). RESULTS: Three exhaled compounds were sufficient to distinguish subjects with (n=39) and without NASH (n=26), with an area under the ROC curve of 0.77. The negative and positive predictive values were 82% and 81%. In contrast, elevated ALT levels or increased AST/ALT ratios both showed negative predictive values of 43%, and positive predictive values of 88% and 70%, respectively. The breath test reduced the hypothetical percentage of undiagnosed NASH patients from 67-79% to 10%, and of misdiagnosed subjects from 49-51% to 18%. CONCLUSIONS: Analysis of volatile organic compounds in exhaled air is a promising method to indicate NASH presence and absence. In comparison to plasma transaminase levels, the breath test significantly reduced the percentage of missed NASH patients and the number of unnecessarily biopsied subjects.

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.

Potential role of cytochrome P450-1B1 in the metabolic activation of 4-aminobiphenyl in humans.

Metabolites of the human carcinogen 4-aminobiphenyl (4-ABP) form hemoglobin (Hb) adducts, which represent a useful biomarker for exposure. However, not every individual responds to a similar degree to 4-ABP exposure, and variations in 4-ABP-Hb adduct formation might be explained by genetic polymorphisms in genes coding for enzymes involved in 4-ABP metabolism. 4-ABP-Hb adducts were measured in blood samples from 57 smoking and 10 non-smoking volunteers. An association was found between cigarette smoking and 4-ABP-Hb adduct levels in smokers (R(2) = 0.5, P < 0.001). Subsequently, subjects were genotyped for 12 polymorphisms in seven genes involved in biotransformation reactions. From this selection of polymorphisms, a significant impact was found for the CYP1B1 Leu(432)Val polymorphism (P = 0.021), which has been reported to lead to a decrease in enzyme activity. Indeed higher levels of 4-ABP-Hb adducts were observed in homo- and heterozygous carriers of the CYP1B1 (432)Leu as compared to the double CYP1B1 (432)Val genotype. A significant interaction between these CYP1B1 genotypes and the level of exposure was found (P = 0.003). Noteworthy, a saturation effect was observed for 4-ABP-Hb adduct formation at high smoking doses limited to carriers of the CYP1B1 (432)Leu allele. No effect of polymorphisms in other genes were found. This is the first study in humans suggesting a crucial role of the CYP1B1 enzyme in 4-ABP metabolism, indicating a protective effect of the CYP1B1 Leu(432)Val polymorphism against the formation of 4-ABP-Hb adduct levels, depending on the smoking dose.