The use of exhaled air analysis in discriminating interstitial lung diseases: a pilot study.

BACKGROUND: Fibrotic Interstitial lung diseases (ILD) are a heterogeneous group of chronic lung diseases characterized by diverse degrees of lung inflammation and remodeling. They include idiopathic ILD such as idiopathic pulmonary fibrosis (IPF), and ILD secondary to chronic inflammatory diseases such as connective tissue disease (CTD). Precise differential diagnosis of ILD is critical since anti-inflammatory and immunosuppressive drugs, which are beneficial in inflammatory ILD, are detrimental in IPF. However, differential diagnosis of ILD is still difficult and often requires an invasive lung biopsy. The primary aim of this study is to identify volatile organic compounds (VOCs) patterns in exhaled air to non-invasively discriminate IPF and CTD-ILD. As secondary aim, the association between the IPF and CTD-ILD discriminating VOC patterns and functional impairment is investigated. METHODS: Fifty-three IPF patients, 53 CTD-ILD patients and 51 controls donated exhaled air, which was analyzed for its VOC content using gas chromatograph- time of flight- mass spectrometry. RESULTS: By applying multivariate analysis, a discriminative profile of 34 VOCs was observed to discriminate between IPF patients and healthy controls whereas 11 VOCs were able to distinguish between CTD-ILD patients and healthy controls. The separation between IPF and CTD-ILD could be made using 16 discriminating VOCs, that also displayed a significant correlation with total lung capacity and the 6 min' walk distance. CONCLUSIONS: This study reports for the first time that specific VOC profiles can be found to differentiate IPF and CTD-ILD from both healthy controls and each other. Moreover, an ILD-specific VOC profile was strongly correlated with functional parameters. Future research applying larger cohorts of patients suffering from a larger variety of ILDs should confirm the potential use of breathomics to facilitate fast, non-invasive and proper differential diagnosis of specific ILDs in the future as first step towards personalized medicine for these complex diseases.

Non-invasive breath collection in murine models using a newly developed sampling device.

Volatile organic compounds (VOCs) in exhaled breath have the potential to be used as biomarkers for screening and diagnosis of diseases. Clinical studies are often complicated by both modifiable and non-modifiable factors influencing the composition of VOCs in exhaled breath. Small laboratory animal studies contribute in obtaining fundamental insight in alterations in VOC composition in exhaled breath and thereby facilitate the design and analysis of clinical research. However, long term animal experiments are often limited by invasive breath collection methods and terminal experiments. To overcome this problem, a novel device was developed for non-invasive breath collection in mice using glass nose-only restrainers thereby omitting the need of anesthetics. C57Bl/6 J mice were used to test reproducibility and different air sampling settings for air-flow (ml min-1) and time (minutes). Exhaled air was collected on desorption tubes and analysed for VOCs by gas chromatography time-of-flight mass spectrometry (GC-tof-MS). In total 27 compounds were putatively identified and used to assess the variability of the VOC measurements in the breath collections. Best reproducibility is obtained when using an air flow of 185 ml min-1and a collection time of 20 min. Due to the non-invasive nature of breath collections in murine models, this device has the potential to facilitate VOC research in relation to disturbed metabolism and or disease pathways.

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.

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.

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.

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.

Electronic nose analysis of exhaled breath to diagnose ventilator-associated pneumonia.

BACKGROUND: Exhaled breath analysis is an emerging technology in respiratory disease and infection. Electronic nose devices (e-nose) are small and portable with a potential for point of care application. Ventilator-associated pneumonia (VAP) is a common nosocomial infection occurring in the intensive care unit (ICU). The current best diagnostic approach is based on clinical criteria combined with bronchoalveolar lavage (BAL) and subsequent bacterial culture analysis. BAL is invasive, laborious and time consuming. Exhaled breath analysis by e-nose is non-invasive, easy to perform and could reduce diagnostic time. Aim of this study was to explore whether an e-nose can be used as a non-invasive in vivo diagnostic tool for VAP. METHODS: Seventy-two patients met the clinical diagnostic criteria of VAP and underwent BAL. In thirty-three patients BAL analysis confirmed the diagnosis of VAP [BAL+(VAP+)], in thirty-nine patients the diagnosis was rejected [BAL-]. Before BAL was performed, exhaled breath was sampled from the expiratory limb of the ventilator into sterile Tedlar bags and subsequently analysed by an e-nose with metal oxide sensors (DiagNose, C-it, Zutphen, The Netherlands). From further fifty-three patients without clinical suspicion of VAP or signs of respiratory disease exhaled breath was collected to serve as a control group [control(VAP-]). The e-nose data from exhaled breath were analysed using logistic regression. RESULTS: The ROC curve comparing [BAL+(VAP+)] and [control(VAP-)] patients had an area under the curve (AUC) of 0.82 (95% CI 0.73-0.9). The sensitivity was 88% with a specificity of 66%. The comparison of [BAL+(VAP+)] and [BAL-] patients revealed an AUC of 0.69; 95% CI 0.57-0.81) with a sensitivity of 76% with a specificity of 56%. CONCLUSION: E-nose lacked sensitivity and specificity in the diagnosis of VAP in the present study for current clinical application. Further investigation into this field is warranted to explore the diagnostic possibilities of this promising new technique.

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.

Evaluation of methods for Mycobacterium avium ssp. paratuberculosis detection in milk samples from the cattle herd showing low seroprevalence of Johne's disease.

Mycobacterium avium ssp. paratuberculosis (MAP) is the cause of chronic gastroenteritis in cattle called the Johne's disease (JD). The disease causes significant economic losses in cattle production. MAP is also supposed to be involved in the Crohn's disease and inflammatory bowel disease (IBD) in people. The detection of the cattle infection based on investigations of milk samples and evaluation of the capacity of the methods used to detect the disease was the objective of the present study. Following methods were applied for milk samples testing: detection of MAP in bacterial culture, detection of the specific IS-900 fragment of MAP in the genetic material isolated directly and detection of MAP antibodies. The results obtained were compared with the "golden standard" results, i.e. the isolation of MAP from the faeces. PQStat-the program for diagnostic reliability estimation, was used for evaluation of the sensitivity, specificity and predictive value. The method based on detection of the specific IS-900 fragment of MAP in the genetic material isolated directly from milk samples was found to possess the highest sensitivity. Detection of anti-MAP antibodies on the other hand showed the lowest sensitivity. The method of detecting anti-MAP antibodies in milk was the most specific while detection of the IS-900 fragment in the genetic material was the least specific method. These results obtained may serve as a guide to choose the most appropriate method for diagnosis of MAP infections by milk sample testing.

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.

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.

Analysis of correlations between the occurrence of anti-MAP antibodies in blood serum and the presence of DNA-MAP in milk.

Paratuberculosis (Johne's disease) is a chronic, infectious enteritis of both domestic and wild ruminants. Unfortunately, the problem of MAP infections is not linked only with the health status of animals and potential direct and indirect economic losses in bovine herds (of dairy cattle in particular). MAP bacilli present in food of animal origin (milk in particular) are likely to lead to the development of the disease in humans. Fast and effective diagnosis of the disease in animals, especially of its subclinical form, may prevent the transmission of the germ to humans. The study was aimed at analyzing the correlations between the occurance of seropositive and serodoubtful reaction in the ELISA test and the presence of DNA-MAP in udder milk. The results suggest that half of the population of animals with positive and doubtful serological responces against John's disease are likely to be a potential source of germ transmission into humans. The fact of detecting DNA-MAP in 1/3 of all milk samples points to the likelihood of occurrence of MAP bacilli in milk of animals not displaying seropositive or serodoubtful responses.