A chemometric study on human breath mass spectra for biomarker identification in cystic fibrosis

Exhaled volatile organic compounds analysis in clinical pediatrics: a systematic review

BACKGROUND

Measured exhaled volatile organic compounds (VOCs) in breath also referred to as exhaled volatilome have been long claimed as a potential source of non-invasive and clinically applicable biomarkers. However, the feasibility of using exhaled volatilome in clinical practice remains to be demonstrated, particularly in pediatrics where the need for improved non-invasive diagnostic and monitoring methods is most urgent. This work presents the first formal evidence-based judgment of the clinical potential of breath volatilome in the pediatric population.

METHODS

A rigorous systematic review across Web of Science, SCOPUS, and PubMed databases following the PRISMA statement guidelines. A narrative synthesis of the evidence was conducted and QUADAS-2 was used to assess the quality of selected studies.

RESULTS

Two independent reviewers deemed 22 out of the 229 records initially found to satisfy inclusion criteria. A summary of breath VOCs found to be relevant for several respiratory, infectious, and metabolic pathologies was conducted. In addition, we assessed their associated metabolism coverage through a functional characterization analysis.

CONCLUSION

Our results indicate that current research remains stagnant in a preclinical exploratory setting. Designing exploratory experiments in compliance with metabolomics practice should drive forward the clinical translation of VOCs breath analysis.

IMPACT

What is the key message of your article? Metabolomics practice could help to achieve the clinical utility of exhaled volatilome analysis. What does it add to the existing literature? This work is the first systematic review focused on disease status discrimination using analysis of exhaled breath in the pediatric population. A summary of the reported exhaled volatile organic compounds is conducted together with a functional characterization analysis. What is the impact? Having noted challenges preventing the clinical translation, we summary metabolomics practices and the experimental designs that are closer to clinical practice to create a framework to guide future trials.

Breathomics: Review of Sample Collection and Analysis, Data Modeling and Clinical Applications

Metabolomics research is rapidly gaining momentum in disease diagnosis, on top of other Omics technologies. Breathomics, as a branch of metabolomics is developing in various frontiers, for early and noninvasive monitoring of disease. This review starts with a brief introduction to metabolomics and breathomics. A number of important technical issues in exhaled breath collection and factors affecting the sampling procedures are presented. We review the recent progress in metabolomics approaches and a summary of their applications on the respiratory and non-respiratory diseases investigated by breath analysis. Recent reports on breathomics studies retrieved from Scopus and Pubmed were reviewed in this work. We conclude that analyzing breath metabolites (both volatile and nonvolatile) is valuable in disease diagnoses, and therefore believe that breathomics will turn into a promising noninvasive discipline in biomarker discovery and early disease detection in personalized medicine. The problem of wide variations in the reported metabolite concentrations from breathomics studies should be tackled by developing more accurate analytical methods and sophisticated numerical analytical alogorithms.

Pancreatic ductal adenocarcinoma can be detected by analysis of volatile organic compounds (VOCs) in alveolar air

Background

In the last decade many studies showed that the exhaled breath of subjects suffering from several pathological conditions has a peculiar volatile organic compound (VOC) profile. The objective of the present work was to analyse the VOCs in alveolar air to build a diagnostic tool able to identify the presence of pancreatic ductal adenocarcinoma in patients with histologically confirmed disease.

Methods

The concentration of 92 compounds was measured in the end-tidal breath of 65 cases and 102 controls. VOCs were measured with an ion-molecule reaction mass spectrometry. To distinguish between subjects with pancreatic adenocarcinomas and controls, an iterated Least Absolute Shrinkage and Selection Operator multivariate Logistic Regression model was elaborated.

Results

The final predictive model, based on 10 VOCs, significantly and independently associated with the outcome had a sensitivity and specificity of 100 and 84% respectively, and an area under the ROC curve of 0.99. For further validation, the model was run on 50 other subjects: 24 cases and 26 controls; 23 patients with histological diagnosis of pancreatic adenocarcinomas and 25 controls were correctly identified by the model.

Conclusions

Pancreatic cancer is able to alter the concentration of some molecules in the blood and hence of VOCs in the alveolar air in equilibrium. The detection and statistical rendering of alveolar VOC composition can be useful for the clinical diagnostic approach of pancreatic neoplasms with excellent sensitivity and specificity.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4452-0) contains supplementary material, which is available to authorized users.

Inflammatory bowel disease and patterns of volatile organic compounds in the exhaled breath of children: A case-control study using Ion Molecule Reaction-Mass Spectrometry

Inflammatory bowel diseases (IBD) profoundly affect quality of life and have been gradually increasing in incidence, prevalence and severity in many areas of the world, and in children in particular. Patients with suspected IBD require careful history and clinical examination, while definitive diagnosis relies on endoscopic and histological findings. The aim of the present study was to investigate whether the alveolar air of pediatric patients with IBD presents a specific volatile organic compounds’ (VOCs) pattern when compared to controls. Patients 10–17 years of age, were divided into four groups: Crohn’s disease (CD), ulcerative colitis (UC), controls with gastrointestinal symptomatology, and surgical controls with no evidence of gastrointestinal problems. Alveolar breath was analyzed by ion molecule reaction mass spectrometry. Four models were built starting from 81 molecules plus the age of subjects as independent variables, adopting a penalizing LASSO logistic regression approach: 1) IBDs vs. controls, finally based on 18 VOCs plus age (sensitivity = 95%, specificity = 69%, AUC = 0.925); 2) CD vs. UC, finally based on 13 VOCs plus age (sensitivity = 94%, specificity = 76%, AUC = 0.934); 3) IBDs vs. gastroenterological controls, finally based on 15 VOCs plus age (sensitivity = 94%, specificity = 65%, AUC = 0.918); 4) IBDs vs. controls, built starting from the 21 directly or indirectly calibrated molecules only, and finally based on 12 VOCs plus age (sensitivity = 94%, specificity = 71%, AUC = 0.888). The molecules identified by the models were carefully studied in relation to the concerned outcomes. This study, with the creation of models based on VOCs profiles, precise instrumentation and advanced statistical methods, can contribute to the development of new non–invasive, fast and relatively inexpensive diagnostic tools, with high sensitivity and specificity. It also represents a crucial step towards gaining further insights on the etiology of IBD through the analysis of specific molecules which are the expression of the particular metabolism that characterizes these patients.

Electronic Nose Technology in Respiratory Diseases

Electronic noses (e-noses) are based on arrays of different sensor types that respond to specific features of an odorant molecule, mostly volatile organic compounds (VOCs). Differently from gas chromatography and mass spectrometry, e-noses can distinguish VOCs spectrum by pattern recognition. E-nose technology has successfully been used in commercial applications, including military, environmental, and food industry. Human-exhaled breath contains a mixture of over 3000 VOCs, which offers the postulate that e-nose technology can have medical applications. Based on the above hypothesis, an increasing number of studies have shown that breath profiling by e-nose could play a role in the diagnosis and/or screening of various respiratory and systemic diseases. The aim of the present study was to review the principal literature on the application of e-nose technology in respiratory diseases.

Gram-negative and -positive bacteria differentiation in blood culture samples by headspace volatile compound analysis

BACKGROUND

Identification of microorganisms in positive blood cultures still relies on standard techniques such as Gram staining followed by culturing with definite microorganism identification. Alternatively, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry or the analysis of headspace volatile compound (VC) composition produced by cultures can help to differentiate between microorganisms under experimental conditions. This study assessed the efficacy of volatile compound based microorganism differentiation into Gram-negatives and -positives in unselected positive blood culture samples from patients.

METHODS

Headspace gas samples of positive blood culture samples were transferred to sterilized, sealed, and evacuated 20 ml glass vials and stored at -30 °C until batch analysis. Headspace gas VC content analysis was carried out via an auto sampler connected to an ion-molecule reaction mass spectrometer (IMR-MS). Measurements covered a mass range from 16 to 135 u including CO2, H2, N2, and O2. Prediction rules for microorganism identification based on VC composition were derived using a training data set and evaluated using a validation data set within a random split validation procedure.

RESULTS

One-hundred-fifty-two aerobic samples growing 27 Gram-negatives, 106 Gram-positives, and 19 fungi and 130 anaerobic samples growing 37 Gram-negatives, 91 Gram-positives, and two fungi were analysed. In anaerobic samples, ten discriminators were identified by the random forest method allowing for bacteria differentiation into Gram-negative and -positive (error rate: 16.7 % in validation data set). For aerobic samples the error rate was not better than random.

CONCLUSIONS

In anaerobic blood culture samples of patients IMR-MS based headspace VC composition analysis facilitates bacteria differentiation into Gram-negative and -positive.

Cavity-Enhanced Near-Infrared Laser Absorption Spectrometer for the Measurement of Acetonitrile in Breath

Elevated concentrations of acetonitrile have been found in the exhaled breath of patients with cystic fibrosis1 and may indicate the severity of their condition or the presence of an accompanying bacterial infection of the airways. There is therefore interest in detecting acetonitrile in exhaled breath. For this purpose, a cavity-enhanced laser absorption spectrometer (λ = 1.65 μm) with a preconcentration stage was built and is described here. The spectrometer has a limit of detection of 72 ppbv and 114 ppbv of acetonitrile in nitrogen and breath, respectively, with a measurement duration of just under 5 min. The preconcentration stage, which employs a carbon molecular sieve and an adsorption/thermal desorption cycle, can increase the acetonitrile concentration by up to a factor 93, thus, lowering the overall limit of detection to approximately 1 ppbv. The suitability of the system for acetonitrile measurements in breath is demonstrated with breath samples taken from the authors, which yielded acetonitrile concentrations of 23 ± 3 ppbv and 29 ± 3 ppbv, respectively.

Application of Cavity Enhanced Absorption Spectroscopy to the Detection of Nitric Oxide, Carbonyl Sulphide, and Ethane--Breath Biomarkers of Serious Diseases

The paper presents one of the laser absorption spectroscopy techniques as an effective tool for sensitive analysis of trace gas species in human breath. Characterization of nitric oxide, carbonyl sulphide and ethane, and the selection of their absorption lines are described. Experiments with some biomarkers showed that detection of pathogenic changes at the molecular level is possible using this technique. Thanks to cavity enhanced spectroscopy application, detection limits at the ppb-level and short measurements time (<3 s) were achieved. Absorption lines of reference samples of the selected volatile biomarkers were probed using a distributed feedback quantum cascade laser and a tunable laser system consisting of an optical parametric oscillator and difference frequency generator. Setup using the first source provided a detection limit of 30 ppb for nitric oxide and 250 ppb for carbonyl sulphide. During experiments employing a second laser, detection limits of 0.9 ppb and 0.3 ppb were obtained for carbonyl sulphide and ethane, respectively. The conducted experiments show that this type of diagnosis would significantly increase chances for effective therapy of some diseases. Additionally, it offers non-invasive and real time measurements, high sensitivity and selectivity as well as minimizing discomfort for patients. For that reason, such sensors can be used in screening for early detection of serious diseases.

Comparison of breath gases, including acetone, with blood glucose and blood ketones in children and adolescents with type 1 diabetes

Previous studies have suggested that breath gases may be related to simultaneous blood glucose and blood ketone levels in adults with type 2 and type 1 diabetes. The aims of this study were to investigate these relationships in children and young people with type 1 diabetes in order to assess the efficacy of a simple breath test as a non-invasive means of diabetes management. Gases were collected in breath bags and measurements were compared with capillary blood glucose and ketone levels taken at the same time on a single visit to a routine hospital clinic in 113 subjects (59 male, age 7 years 11 months-18 years 3 months) with type 1 diabetes. The patients were well-controlled with relatively low concentrations of the blood ketone measured (β hydroxybutyrate, 0-0.4 mmol l(-1)). Breath acetone levels were found to increase with blood β hydroxybutyrate levels and a significant relationship was found between the two (Spearman's rank correlation ρ = 0.364, p < 10(-4)). A weak positive relationship was found between blood glucose and breath acetone (ρ = 0.16, p = 0.1), but led to the conclusion that single breath measurements of acetone do not provide a good measure of blood glucose levels in this cohort. This result suggests a potential to develop breath gas analysis to provide an alternative to blood testing for ketone measurement, for example to assist with the management of type 1 diabetes.

Exhaled breath analysis by electronic nose in airways disease. Established issues and key questions

Exhaled air contains many volatile organic compounds (VOCs) that are the result of normal and disease-associated metabolic processes anywhere in the body. Different omics techniques can assess the pattern of these VOCs. One such omics technique suitable for breath analysis is represented by electronic noses (eNoses), providing fingerprints of the exhaled VOCs, called breathprints. Breathprints have been shown to be altered in different disease states, including in asthma and COPD. This review describes the current status on clinical validation and application of breath analysis by electronic noses in the diagnosis and monitoring of chronic airways diseases. Furthermore, important methodological issues including breath sampling, modulating factors and incompatibility between eNoses are raised and discussed. Next steps towards clinical application of electronic noses are provided, including further validation in suspected disease, assessment of the influence of different comorbidities, the value in longitudinal monitoring of patients with asthma and COPD and the possibility to predict treatment responses. Eventually, a Breath Cloud may be constructed, a large database containing disease-specific breathprints. When collaborative efforts are put into optimization of this technique, it can provide a rapid and non-invasive first line diagnostic test.

Integration of biosensors and drug delivery technologies for early detection and chronic management of illness

Recent advances in biosensor design and sensing efficacy need to be amalgamated with research in responsive drug delivery systems for building superior health or illness regimes and ensuring good patient compliance. A variety of illnesses require continuous monitoring in order to have efficient illness intervention. Physicochemical changes in the body can signify the occurrence of an illness before it manifests. Even with the usage of sensors that allow diagnosis and prognosis of the illness, medical intervention still has its downfalls. Late detection of illness can reduce the efficacy of therapeutics. Furthermore, the conventional modes of treatment can cause side-effects such as tissue damage (chemotherapy and rhabdomyolysis) and induce other forms of illness (hepatotoxicity). The use of drug delivery systems enables the lowering of side-effects with subsequent improvement in patient compliance. Chronic illnesses require continuous monitoring and medical intervention for efficient treatment to be achieved. Therefore, designing a responsive system that will reciprocate to the physicochemical changes may offer superior therapeutic activity. In this respect, integration of biosensors and drug delivery is a proficient approach and requires designing an implantable system that has a closed loop system. This offers regulation of the changes by means of releasing a therapeutic agent whenever illness biomarkers prevail. Proper selection of biomarkers is vital as this is key for diagnosis and a stimulation factor for responsive drug delivery. By detecting an illness before it manifests by means of biomarkers levels, therapeutic dosing would relate to the severity of such changes. In this review various biosensors and drug delivery systems are discussed in order to assess the challenges and future perspectives of integrating biosensors and drug delivery systems for detection and management of chronic illness.

Determination of hazardous volatile organic compounds in the Hoffmann list by ion-molecule reaction mass spectrometry

RATIONALE

Off-line gas or liquid chromatographic mass spectrometry techniques are the most widely used method for analysis of hazardous, carcinogenic volatile organic compounds (VOCs) in mainstream cigarette smoke. However, these conventional techniques can lead to modification of VOCs during sample preparation due to the high reactivity of VOCs. Thus, the development of on-line mass spectrometric methods for analysis of VOCs is desirable to circumvent this problem.

METHODS

The accurate identification of VOCs is a critical step in the analysis of cigarette smoke. Here, we use ion-molecule reaction mass spectrometry (IMR-MS) to study the behavior of standard VOCs in the Hoffmann list during this analytical procedure, and then to profile the VOCs in mainstream cigarette smoke using this on-line mass spectrometric method.

RESULTS

We first discuss and summarize the charge transfer (CT) ionization and further fragmentation of 20 standard VOCs in the Hoffmann list with the ion reagents Hg(+), Xe(+), and Kr(+). The IMR-MS instrument was then connected to a Borgwaldt-RM20H rotary smoking machine in order to study VOCs in mainstream cigarette smoke on-line. Using this procedure, more than 20 VOCs were identified by IMR-MS by comparison with experimental results obtained on standard VOCs.

CONCLUSIONS

The IMR-MS technique can potentially result in reduced molecular fragmentation during analysis of VOCs. However, significant fragmentation still occurs during IMR-MS when the ionization energy (IE) of the ion reagent is much higher than the IE of the VOC, given that excess energy is stored in the newly formed ion during CT ionization. Given that IMR-MS cannot distinguish between isobaric compounds or isomers, we summarize the possible overlapping mass peaks from these isobaric species that may be present in analyses of VOCs. Selection of the ion reagent for IMR-MS should be based on the need to ensure CT ionization of the analytes, as well as avoiding their severe fragmentation.

Volatile compound profiling for the identification of Gram-negative bacteria by ion-molecule reaction-mass spectrometry

AIMS

Fast and reliable methods for the early detection and identification of micro-organism are of high interest. In addition to established methods, direct mass spectrometry-based analysis of volatile compounds (VCs) emitted by micro-organisms has recently been shown to allow species differentiation. Thus, a large number of pathogenic Gram-negative bacteria, which comprised Acinetobacter baumannii, Enterobacter cloacae, Escherichia coli, Klebsiella oxytoca, Pseudomonas aeruginosa, Proteus vulgaris and Serratia marcescens, were subjected to headspace VC composition analysis using direct mass spectrometry in a low sample volume that allows for automation.

METHODS AND RESULTS

Ion-molecule reaction-mass spectrometry (IMR-MS) was applied to headspace analysis of the above bacterial samples incubated at 37°C starting with 10(2) CFU ml(-1) . Measurements of sample VC composition were performed at 4, 8 and 24 h. Microbial growth was detected in all samples after 8 h. After 24 h, species-specific mass spectra were obtained allowing differentiation between bacterial species.

CONCLUSIONS

IMR-MS provided rapid growth detection and identification of micro-organisms using a cumulative end-point model with a short analysis time of 3 min per sample.

SIGNIFICANCE AND IMPACT OF THE STUDY

Following further validation, the presented method of bacterial sample headspace VC analysis has the potential to be used for bacteria differentiation.

Non-invasive diagnosis of liver diseases by breath analysis using an optimized ion-molecule reaction-mass spectrometry approach: a pilot study

Breath composition is altered in liver diseases. We tested if ion-molecule-reaction mass spectrometry (IMR-MS) combined with a new statistical modality improves the diagnostic accuracy of breath analysis in liver diseases. We analysed 114 molecules in the breath of 126 individuals (healthy controls, and patients with non-alcoholic and alcoholic fatty liver disease and liver cirrhosis) by IMR-MS. Characteristic exhalation patterns were identified for each group. Combining two to seven molecules in the new stacked feature ranking model reached a diagnostic accuracy (area under the curve) for individual liver diseases between 0.88 and 0.97. IMR-MS followed by sophisticated statistical analysis is a promising tool for liver diagnostics by breath analysis.