Comparing patterns of volatile organic compounds exhaled in breath after consumption of two infant formulae with a different lipid structure: a randomized trial.

Infant formulae have been used since decades as an alternative to or a complement to human milk. Human milk, the "gold standard" of infant nutrition, has been studied for its properties in order to create infant formulae that bring similar benefits to the infant. One of the characteristics of milk is the size of the lipid droplets which is known to affect the digestion, gastric emptying and triglyceride metabolism. In the current study a concept infant milk formula with large, phospholipid coating of lipid droplets (mode diameter 3-5 µm; NUTURIS, further described as "active"), was compared to a commercially available formula milk characterised by smaller lipid droplets, further described as "control" (both products derived from Nutricia). We investigated whether we could find an effect of lipid droplet size on volatile compounds in exhaled air upon ingestion of either product. For that purpose, exhaled breath was collected from a group of 29 healthy, non-smoking adult males before ingestion of a study product (baseline measurements, T0) and at the following time points after the test meal: 30, 60, 120, 180 and 240 min. Volatile organic compounds (VOCs) in breath were detected by gas chromatography-time-of-flight-mass spectrometry. Any differences in the time course of VOCs patterns upon intake of active and control products were investigated by regularised multivariate analysis of variance (rMANOVA). The rMANOVA analysis revealed statistically significant differences in the exhaled breath composition 240 min after ingestion of the active formula compared to control product (p-value < 0.0001), but did not show significant changes between active and control product at any earlier time points. A set of eight VOCs in exhaled breath had the highest contribution to the difference found at 240 minutes between the two formulas. A set of ten VOCs was different between baseline and the two formulae at T240 with p-value < 0.0001. To our knowledge this is the first study that shows the ability of VOCs in exhaled breath to monitor metabolic effects after ingestion of infant formulae with different lipid structure. The statistically significant differences in compound abundance found between active and control formula milk may be related to: (i) specific differences in the digestion, (ii) absorption of lipids and proteins and (iii) assimilation of the products in the gut.

Exposure to genotoxic compounds alters in vitro cellular VOC excretion.

Genotoxic carcinogens significantly damage cells and tissues by targeting macromolecules such as proteins and DNA, but their mechanisms of action and effects on human health are diverse. Consequently, determining the amount of exposure to a carcinogen and its cellular effects is essential, yet difficult. The aim of this manuscript was to investigate the potential of detecting alterations in volatile organic compounds (VOCs) profiles in the in vitro headspace of pulmonary cells after exposure to the genotoxic carcinogens cisplatin and benzo[a]pyrene using two different sampling set-ups. A prototype set-up was used for the cisplatin exposure, whereas a modified set-up was utilized for the benzo[a]pyrene exposure. Both carcinogens were added to the cell medium for 24 h. The headspace in the culture flask was sampled to measure the VOC content using gas chromatography-time-of-flight-mass spectrometry. Eight cisplatin-specific VOCs and six benzo[a]pyrene-specific VOCs were discriminatory between treated and non-treated cells. Since the in vivo biological effects of both genotoxic compounds are well-defined, the origin of the identified VOCs could potentially be traced back to common cellular processes including cell cycle pathways, DNA damage and repair. These results indicate that exposing lung cells to genotoxins alters headspace VOC profiles, suggesting that it might be possible to monitor VOC changes in vivo to study drug efficacy or exposure to different pollutants. In conclusion, this study emphasizes the innovative potential of in vitro VOCs experiments to determine their in vivo applicability and discover their endogenous origin.

The potential of volatile organic compounds for the detection of active disease in patients with ulcerative colitis.

BACKGROUND: To optimise treatment of ulcerative colitis (UC), patients need repeated assessment of mucosal inflammation. Current non-invasive biomarkers and clinical activity indices do not accurately reflect disease activity in all patients and cannot discriminate UC from non-UC colitis. Volatile organic compounds (VOCs) in exhaled air could be predictive of active disease or remission in Crohn's disease. AIM: To investigate whether VOCs are able to differentiate between active UC, UC in remission and non-UC colitis. METHODS: UC patients participated in a 1-year study. Clinical activity index, blood, faecal and breath samples were collected at each out-patient visit. Patients with clear defined active faecal calprotectin >250 µg/g and inactive disease (Simple Clinical Colitis Activity Index <3, C-reactive protein <5 mg/L and faecal calprotectin <100 µg/g) were included for cross-sectional analysis. Non-UC colitis was confirmed by stool culture or radiological evaluation. Breath samples were analysed by gas chromatography time-of-flight mass spectrometry and kernel-based method to identify discriminating VOCs. RESULTS: In total, 72 UC (132 breath samples; 62 active; 70 remission) and 22 non-UC-colitis patients (22 samples) were included. Eleven VOCs predicted active vs. inactive UC in an independent internal validation set with 92% sensitivity and 77% specificity (AUC 0.94). Non-UC colitis patients could be clearly separated from active and inactive UC patients with principal component analysis. CONCLUSIONS: Volatile organic compounds can accurately distinguish active disease from remission in UC and profiles in UC are clearly different from profiles in non-UC colitis patients. VOCs have demonstrated potential as new non-invasive biomarker to monitor inflammation in UC.

Factors that influence the volatile organic compound content in human breath.

BACKGROUND: Thousands of endogenous and exogenous volatile organic compounds (VOCs) are excreted in each breath. Inflammatory and deviant metabolic processes affect the level of endogeneous VOCs, which can serve as specific biomarkers for clinical diagnosis and disease monitoring. Important issues that still need to be tackled are related to potential confounding factors like gender and age and endogenous and exogenous factors, like f.i. smoking. METHODS: The aim of this study was to systematically access the effect of endogenous and exogenous factors on VOC composition of exhaled breath. In the current study breath samples from 1417 adult participants from the LifeLines cohort, a general population cohort in the Netherlands, were collected and the total content of VOCs was measured using gas chromatography-time-of-flight-mass spectrometry. Breath samples were collected in Groningen and transferred to carbon tubes immediately. These samples were then shipped to Maastricht and measured in batches. VOCs profiles were correlated to 14 relevant characteristics of all participants including age, BMI, smoking and blood cell counts and metabolic parameters as well as to 16 classes of medications. RESULTS: VOCs profiles were shown to be significantly influenced by smoking behavior and to a lesser extent by age, BMI and gender. These factors need to be controlled for in breath analysis studies. We found no evidence whatsoever in this 1417 subjects' cohort that white blood cell counts, cholesterol or triglycerides levels have an influence on the VOC profile. Thus they may not have to be controlled for in exhaled breath studies. CONCLUSION: The large cohort of volunteers used here represents a unique opportunity to gauge the factors influencing VOCs profiles in a general population i.e. the most clinically relevant population. Classical clinical parameters and smoking habits clearly influence breath content and should therefore be accounted for in future clinical studies involving breath analysis.

Volatile organic compounds in breath as markers for irritable bowel syndrome: a metabolomic approach.

BACKGROUND: The diagnosis of irritable bowel syndrome (IBS) is challenging because of its heterogeneity and multifactorial pathophysiology. No reliable biomarkers of IBS have been identified so far. AIMS: In a case-control study, using a novel application of breath analysis to distinguish IBS patients from healthy controls based on the analysis of volatile organic compounds (VOCs). Subsequently, the diagnostic VOC-biomarker set was correlated with self-reported gastrointestinal (GI) symptoms of subjects of the Maastricht IBS clinical cohort and of a general population cohort, LifeLines DEEP. METHODS: Breath samples were collected from 170 IBS patients and 153 healthy controls in the clinical cohort and from 1307 participants in general population cohort. Multivariate statistics were used to identify the most discriminatory set of VOCs in the clinical cohort, and to find associations between VOCs and GI symptoms in both cohorts. RESULTS: A set of 16 VOCs correctly predicted 89.4% of the IBS patients and 73.3% of the healthy controls (AUC = 0.83). The VOC-biomarker set correlated moderately with a set of GI symptoms in the clinical (r = 0.55, P = 0.0003) and general population cohorts (r = 0.54, P = 0.0004). A Kruskal-Wallis test showed no influence from possible confounding factors in distinguishing IBS patients from healthy controls. CONCLUSIONS: A set of 16 breath-based biomarkers that distinguishes IBS patients from healthy controls was identified. The VOC-biomarker set correlated significantly with GI symptoms in two independent cohorts. We demonstrate the potential use of breath analysis in the diagnosis and monitoring of IBS, and a possible application of VOC analyses in a general population cohort.

Association between exhaled inflammatory markers and asthma control in children.

The relationship between exhaled inflammatory markers and asthma control in children is unclear. To explore the association between inflammatory markers in exhaled breath (fractional nitric oxide (FeNO), volatile organic compounds (VOCs), cytokines/chemokines) and asthma control. 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 (FEV1) 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.

Dynamic collection and analysis of volatile organic compounds from the headspace of cell cultures.

Exhaled breath has proven to be a valuable source of information about human bodies. Subtle differences between volatile organic compounds (VOCs) formed endogenously can be detected and become a base for a potential monitoring tool for health and disease. Until now, there has been a lack of biological and mechanistic knowledge of the processes involved in the production of relevant VOCs. Among the possible sources of health-related and disease-related VOCs are microorganisms found in the respiratory tract and in the gut. Other VOCs in the body are produced by cells that are influenced by the disease, for instance, due to metabolic disorders and/or inflammation. To gain insight into the in vivo production of VOCs by human cells and thus the exhaled breath composition, in vitro experiments involving relevant cells should be studied because they may provide valuable information on the production of VOCs by the affected cells. To this aim we developed and validated a system for dynamically (continuously) collecting headspace air in vitro using a Caco-2 cell line. The system allows the application of different cell lines as well as different experimental setups, including varying exposure times and treatment options while preserving cell viability. Significant correlation (p ⩽ 0.0001) between collection outputs within each studied group confirmed high reproducibility of the collection system. An example of such an application is presented here. We studied the influence of oxidative stress on the VOC composition of the headspace air of Caco-2 cells. By comparing the VOC composition of air flushed through empty culture flasks (n = 35), flasks with culture medium (n = 35), flasks with medium and cells (n = 20), flasks with medium and an oxidative stressor (H2O2) (n = 20), and flasks with medium, stressor, and cells (n = 20), we were able to separate the effects from the stressor on the cells from all other interactions. Measurements were performed with gas chromatography time-of-flight mass spectrometry. Multivariate data analysis allowed detection of significant altered compounds in the compared groups. We found a significant change (p ⩽ 0.001) of the composition of VOCs due to the stressing of the Caco-2 cells by H2O2. A total of ten VOCs showed either increased or decreased abundance in the headspace of the cell cultures due to the presence of the H2O2 stressor.

Current breathomics--a review on data pre-processing techniques and machine learning in metabolomics breath analysis.

We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics.

Identification of microorganisms based on headspace analysis of volatile organic compounds by gas chromatography-mass spectrometry.

The identification of specific volatile organic compounds (VOCs) produced by microorganisms may assist in developing a fast and accurate methodology for the determination of pulmonary bacterial infections in exhaled air. As a first step, pulmonary bacteria were cultured and their headspace analyzed for the total amount of excreted VOCs to select those compounds which are exclusively associated with specific microorganisms. Development of a rapid, noninvasive methodology for identification of bacterial species may improve diagnostics and antibiotic therapy, ultimately leading to controlling the antibiotic resistance problem. Two hundred bacterial headspace samples from four different microorganisms (Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Klebsiella pneumoniae) were analyzed by gas chromatography-mass spectrometry to detect a wide array of VOCs. Statistical analysis of these volatiles enabled the characterization of specific VOC profiles indicative for each microorganism. Differences in VOC abundance between the bacterial types were determined using ANalysis of VAriance-principal component analysis (ANOVA-PCA). These differences were visualized with PCA. Cross validation was applied to validate the results. We identified a large number of different compounds in the various headspaces, thus demonstrating a highly significant difference in VOC occurrence of bacterial cultures compared to the medium and between the cultures themselves. Additionally, a separation between a methicillin-resistant and a methicillin-sensitive isolate of S. aureus could be made due to significant differences between compounds. ANOVA-PCA analysis showed that 25 VOCs were differently profiled across the various microorganisms, whereas a PCA score plot enabled the visualization of these clear differences between the bacterial types. We demonstrated that identification of the studied microorganisms, including an antibiotic susceptible and resistant S. aureus substrain, is possible based on a selected number of compounds measured in the headspace of these cultures. These in vitro results may translate into a breath analysis approach that has the potential to be used as a diagnostic tool in medical microbiology.

Breath analysis as a potential diagnostic tool for tuberculosis.

SETTING: Cape Town, South Africa. OBJECTIVES: We investigated the potential of breath analysis by gas chromatography-mass spectrometry (GC-MS) to discriminate between samples collected prospectively from patients with suspected tuberculosis (TB). DESIGN: Samples were obtained in a TB-endemic setting in South Africa, where 28% of culture-proven TB patients had Ziehl-Neelsen (ZN) negative sputum smear. A training set of breath samples from 50 sputum culture-proven TB patients and 50 culture-negative non-TB patients was analysed using GC-MS. We used support vector machine analysis for classification of the patient samples into TB and non-TB. RESULTS: A classification model with seven compounds had a sensitivity of 72%, a specificity of 86% and an accuracy of 79% compared with culture. The classification model was validated with breath samples from a different set of 21 TB and 50 non-TB patients from the same area, giving a sensitivity of 62%, a specificity of 84% and an accuracy of 77%. CONCLUSION: This study shows that GC-MS breath analysis is able to differentiate between TB and non-TB breath samples even among patients with a negative ZN sputum smear but a positive culture for Mycobacterium tuberculosis. We conclude that breath analysis by GC-MS merits further research.

A profile of volatile organic compounds in breath discriminates COPD patients from controls.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an inflammatory condition characterized by oxidative stress and the formation of volatile organic compounds (VOCs) secreted via the lungs. We recently developed a methodological approach able to identify profiles of VOCs in breath unique for patient groups. Here we applied this recently developed methodology regarding diagnosis of COPD patients. METHODS: Fifty COPD patients and 29 controls provided their breath and VOCs were analyzed by gas chromatography-mass spectrometry to identify relevant VOCs. An additional 16 COPD patients and 16 controls were sampled in order to validate the model, and 15 steroid naïve COPD patients were sampled to determine whether steroid use affects performance. FINDINGS: 1179 different VOCs were detected, of which 13 were sufficient to correctly classify all 79 subjects. Six of these 13 VOCs classified 92% of the subjects correctly (sensitivity: 98%, specificity: 88%) and correctly classified 29 of 32 subjects (sensitivity: 100%, specificity: 81%) from the independent validation population. Fourteen out of 15 steroid naïve COPD patients were correctly classified thus excluding treatment influences. INTERPRETATION: This is the first study distinguishing COPD subjects from controls solely based on the presence of VOCs in breath. Analysis of VOCs might be highly relevant for diagnosis of COPD.

Volatile organic compounds in exhaled breath as a diagnostic tool for asthma in children.

BACKGROUND: The correct diagnosis of asthma in young children is often hard to achieve, resulting in undertreatment of asthmatic children and overtreatment in transient wheezers. OBJECTIVES: To develop a new diagnostic tool that better discriminates between asthma and transient wheezing and that leads to a more accurate diagnosis and hence less undertreatment and overtreatment. A first stage in the development of such a tool is the ability to discriminate between asthmatic children and healthy controls. The integrative analysis of large numbers of volatile organic compounds (VOC) in exhaled breath has the potential to discriminate between various inflammatory conditions of the respiratory tract. METHODS: Breath samples were obtained and analysed for VOC by gas chromatography-mass spectrometry from asthmatic children (n=63) and healthy controls (n=57). A total of 945 determined compounds were subjected to discriminant analysis to find those that could discriminate diseased from healthy children. A set of samples from both asthmatic and healthy children was selected to construct a model that was subsequently used to predict the asthma or the healthy status of a test group. In this way, the predictive value of the model could be tested. MEASUREMENTS AND MAIN RESULTS: The discriminant analyses demonstrated that asthma and healthy groups are distinct from one another. A total of eight components discriminated between asthmatic and healthy children with a 92% correct classification, achieving a sensitivity of 89% and a specificity of 95%. Conclusion The results show that a limited number of VOC in exhaled air can well be used to distinguish children with asthma from healthy children.

Development of accurate classification method based on the analysis of volatile organic compounds from human exhaled air.

Analysis of exhaled air leads to the development of fast accurate and non-invasive diagnostics. A comprehensive analysis of the entire range of volatile organic compounds (VOCs) in exhaled air samples will enable the identification of VOCs unique for certain patient groups. This study demonstrates proof of principle of our developed method tested on a smoking/non-smoking study population. Thermal desorption and gas chromatography coupled to time-of-flight mass spectrometry were used to analyse exhaled air samples. The VOC profiles obtained from each individual were combined into one final database based on similarity of mass spectra and retention indexes (RI), which offers the possibility for a reliable selection of compounds of interest. As proof of principle we correctly classified all subjects from population of smoking (N=11) and non-smoking (N=11) based on the VOC profiles available in their exhaled air. Support vector machine (SVM) analysis identified 4 VOCs as biomarkers of recent exposure to cigarette smoke: 2,5-dimethyl hexane, dodecane, 2,5-dimethylfuran and 2-methylfuran. This approach contributes to future development of fast, accurate and non-invasive diagnostics of inflammatory diseases including pulmonary diseases.

Helicobacter pylori does not mediate the formation of carcinogenic N-nitrosamines.

BACKGROUND: Both N-nitroso compounds and colonization with Helicobacter pylori represent known risk-factors for the development of gastric cancer. Endogenous formation of N-nitroso compounds is thought to occur predominantly in acidic environments such as the stomach. At neutral pH, bacteria can catalyze the formation of N-nitroso compounds. Based on experiments with a noncarcinogenic N-nitroso compound as end product, and using only a single H. pylori strain, it was recently reported that H. pylori only displays a low nitrosation capacity. As H. pylori is a highly diverse bacterial species, it is reasonable to question the generality of this finding. In this study, several genetically distinct H. pylori strains are tested for their capacity to form carcinogenic N-nitrosamines. MATERIALS AND METHODS: Bacteria were grown in the presence of 0-1000 microM morpholine and nitrite (in a 1 : 1 molar ratio), at pH 7, 5 and 3. RESULTS: Incubation of Neisseria cinerea (positive control) with 500 microM morpholine and 500 microM nitrite, resulted in a significant increase in formation of N-nitrosomorpholine, but there was no significant induction of N-nitrosomorpholine formation by any of the H. pylori strains, at any of the three pH conditions. CONCLUSION: H. pylori does not induce formation of the carcinogenic N-nitrosomorpholine in vitro. The previously reported weak nitrosation capacity of H. pylori is not sufficient to nitrosate the more difficulty nitrosatable morpholine. This probably also holds true for other secondary amines. These results imply that the increased incidence of gastric cancer formation that is associated with gastric colonization by H. pylori is unlikely to result from the direct induced formation of carcinogenic nitrosamines by H. pylori. However, this has to be further confirmed in in vivo studies.

Intragastric volatile N-nitrosamines, nitrite, pH, and Helicobacter pylori during long-term treatment with omeprazole.

BACKGROUND & AIMS: This study evaluated the effect of long-term gastric acid suppressive therapy with omeprazole on intragastric levels of carcinogenic N-nitrosamines and related parameters. METHODS: Forty-five patients on long-term omeprazole medication (mean, 35 months) and 13 healthy subjects without medication participated. Volatile N-nitrosamines were determined in gastric juice and urine. Intragastric pH, nitrite, nitrate, and H. pylori status were determined. DNA isolated from gastric biopsy specimens was analyzed for precarcinogenic alkyl-DNA adducts. RESULTS: The intragastric pH in patients was significantly higher compared with controls (P = 0.0001). Gastric nitrite levels in patients were nonsignificantly higher. There was no difference in total levels of intragastric volatile N-nitrosamines between patients and controls, however, urinary N-nitrosodimethylamine excretion was higher in patients (P = 0.001). On omeprazole, Helicobacter pylori-positive vs. -negative patients had a nonsignificantly higher intragastric nitrite level and higher urinary N-nitrosodimethylamine excretion. No alkyl-DNA adducts could be detected in gastric epithelium. CONCLUSIONS: Increased intragastric pH caused by long-term treatment with omeprazole does not result in increased intragastric levels of nitrite and volatile N-nitrosamines. The significantly higher urinary N-nitrosamine excretion implies the risk of increased endogenous formation of N-nitrosamines during long-term omeprazole treatment. This risk may be higher in H. pylori-positive patients.

Modulation of DNA and protein adducts in smokers by genetic polymorphisms in GSTM1,GSTT1, NAT1 and NAT2.

The formation of DNA and protein adducts by environmental pollutants is modulated by host polymorphisms in genes that encode metabolizing enzymes. In our study on 67 smokers, aromatic-DNA adduct levels were examined by nuclease P1 enriched 32P-postlabelling in mononuclear blood cells (MNC) and 4-aminobiphenyl-haemoglobin adducts (4-ABP-Hb) by gas chromatography-mass spectroscopy. Genetic polymorphisms in glutathione S-transferase M1 (GSTM1), T1 (GSTT1) and N-acetyl-transferase 1 (NAT1) and 2 (NAT2) were assessed by polymerase chain reaction-based methods. DNA adduct levels, adjusted for the amount of cigarettes smoked per day, were higher in GSTM1(-/-) individuals (1.30 +/- 0.57 adducts per 108 nucleotides) than in GSTM1(+) subjects (1.03 +/- 0.56, P = 0.05), higher in NAT1 slow acetylators (1.58 +/- 0.54) than in NAT1 fast acetylators (1.11 +/- 0.58, P = 0.05) and were also found to be associated with the NAT2 acetylator status (1.29 +/- 0.64 and 1.03 +/- 0.46, respectively, for slow and fast acetylators, P = 0.06). An effect of GSTT1 was only found in combination with the NAT2 genotype; individuals with the GSTT1(-/-) and NAT2-slow genotype contained higher adduct levels (1.80 +/- 0.68) compared to GSTT1(+)/NAT2 fast individuals (0.96 +/- 0.36). Highest DNA adduct levels were observed in slow acetylators for both NAT1 and NAT2 also lacking the GSTM1 gene (2.03 +/- 0.17), and lowest in GSTM1(+) subjects with the fast acetylator genotype for both NAT1 and NAT2 (0.91 +/- 0.45, P = 0.01). No overall effects of genotypes were observed on 4-ABP-Hb levels. However, in subjects smoking less than 25 cigarettes per day, 4-ABP-Hb levels were higher in NAT2 slow acetylators (0.23 +/- 0.10 ng/g Hb) compared to fast acetylators (0.15 +/- 0.07, P = 0.03). These results provide further evidence for the combined effects of genetic polymorphisms in GSTM1, GSTT1, NAT1 and NAT2 on DNA and protein adduct formation in smoking individuals and indicate that, due to the complex carcinogen exposure, simultaneous assessment of multiple genotypes may identify individuals at higher cancer risk.

Determination of N-nitrosodimethylamine in artificial gastric juice by gas chromatography-mass spectrometry and by gas chromatography-thermal energy analysis.

The thermal energy analyser (TEA) is considered to be the gold standard for the determination of nitrosamines. However, since many laboratories cannot justify the use of such a very specific detection system, alternative detection methods are useful. While standard gas chromatography (GC) detectors lack the selectivity of the TEA detector, mass spectrometry (MS) seems to be the method of choice to combine GC separation with mass selective detection. Moreover, the detection limits of the GC-MS assay in general use are about 4 times lower than those of the GC-TEA assay. A comparison of GC-MS and GC-TEA data on N-nitrosodimethylamine determinations showed a strong correlation between the two assays (R2 = 0.86), demonstrating the exchangeability of these methods.

Excretion of volatile nitrosamines in a rural population in relation to food and drinking water consumption.

Urinary excretion of volatile nitrosamines was assessed in 59 non-smokers living in a rural county of Québec, Canada. Water and food intakes were measured by means of a 24-hour recall. Nitrates were analyzed in the tap water of all participants (geometric mean=2.0 mg nitrate-N/L) and dietary intakes of nitrate and vitamins C and E were estimated via a validated Canadian food database. Urine was collected over the same 24-hour period and analyzed for nitrates by hydrazine reduction and for volatile nitrosamines by gas-chromatography/mass spectrometry. N-Nitrosopiperidine (NPIP) was found in urine samples from 52 of the 59 subjects. Geometric mean of NPIP urinary excretion was 67 ng/day and maximum value was 1045 ng/day. No other volatile nitrosamine was detected. There was a correlation between urinary nitrate excretion and total nitrate intake (r=0.71, P < 0.001). However, no relationship was found between urinary NPIP excretion and either nitrate excretion, dietary or water nitrate intakes. NPIP excretion was significantly correlated to coffee intake (r=0.40, P=0.002) and this relation was not modified by vitamin intake. We conclude that nitrate intake is not related to nitrosamine excretion in this rural population. The influence of coffee consumption on NPIP excretion deserves further attention.

Effect of ascorbic acid and green tea on endogenous formation of N-nitrosodimethylamine and N-nitrosopiperidine in humans.

Many constituents present in the human diet may inhibit endogenous formation of N-nitroso compounds (NOC). Studies with human volunteers showed inhibiting effects of intake of ascorbic acid and green tea consumption on nitrosation using the N-nitrosoproline test. The aim of the present study was to evaluate the effects of ascorbic acid and green tea on urinary excretion of carcinogenic N-nitrosodimethylamine (NDMA) and N-nitrosopiperidine (NPIP) in humans. Twenty-five healthy female volunteers consumed a fish meal rich in amines as nitrosatable precursors in combination with intake of nitrate-containing drinking water at the Acceptable Daily Intake level during 7 consecutive days. During 1 week before and after nitrate intake a diet low in nitrate was consumed. Using the same protocol, the effect of two different doses of ascorbic acid (250 mg and 1 g/day) and two different doses of green tea (2 g and 4 g/day) on formation of NDMA and NPIP was studied. Mean nitrate excretion in urine significantly increased from control (76+/-24) to 167+/-25 mg/24 h. Intake of nitrate and fish resulted in a significant increase in mean urinary excretion of NDMA compared with the control weeks: 871+/-430 and 640+/-277 ng/24 h during days 1-3 and 4-7, respectively, compared with 385+/-196 ng/24 h (p<0.0002). Excretion of NPIP in urine was not related to nitrate intake and composition of the diet. Intake of 250 mg and 1 g of ascorbic acid per day resulted in a significant decrease in urinary NDMA excretion during days 4-7 (p=0.0001), but not during days 1-3. Also, consumption of four cups of green tea per day (2 g) significantly decreased excretion of NDMA during days 4-7 (p=0.0035), but not during days 1-3. Surprisingly, consumption of eight cups of green tea per day (4 g) significantly increased NDMA excretion during days 4-7 (p=0.0001), again not during days 1-3. This increase is probably a result of catalytic effects of tea polyphenols on nitrosation, or of another, yet unknown, mechanism. These results suggest that intake of ascorbic acid and moderate consumption of green tea can reduce endogenous NDMA formation.

The use of 4-aminobiphenyl hemoglobin adducts and aromatic DNA adducts in lymphocytes of smokers as biomarkers of exposure.

Two biomarkers of exposure to cigarette smoke, 4-aminobiphenyl-hemoglobin (Hb) adducts and aromatic DNA adducts in lymphocytes, were determined from a population of 55 smokers and 4 nonsmokers. The levels of these adducts were related to daily cigarette consumption and also to (calculated) tar and nicotine intake. The Hb adduct levels seemed to correspond best to the number of cigarettes (cig) smoked, but at a cigarette consumption of >30 cig/day, a saturation effect was observed. Lymphocytic DNA adducts also correlated well with cigarette and tar consumption; for this type of adduct, a saturation level was reached at a dose of approximately 15-20 cig/day. From a subpopulation, a second sample was obtained after 2 months, and the adduct levels were compared with their initial adduct levels. Strong correlations were found between the first and second DNA adduct measurements (r = 0.84). In another subpopulation, resampling was performed after 6 months. No correlation between DNA adduct levels in the first and last samples was found, but 4-aminobiphenyl Hb adduct levels were strongly correlated (r = 0.78), the absolute quantities measured being comparable (paired t test: t = -1.27, P = 0.22, n = 15). We found no influence of GSTM1 and NAT2 polymorphisms on Hb adduct formation and of GSTM1 polymorphism on aromatic DNA adduct formation. A significantly lower aromatic DNA adduct level was observed for intermediate acetylators when compared to slow acetylators.