Comprehensive Two-Dimensional Gas Chromatography–Mass Spectrometry Analysis of Exhaled Breath Compounds after Whole Grain Diets

Exhaled breath is a potential noninvasive matrix to give new information about metabolic effects of diets. In this pilot study, non-targeted analysis of exhaled breath volatile organic compounds (VOCs) was made by comprehensive two-dimensional gas chromatography–mass spectrometry (GCxGC-MS) to explore compounds relating to whole grain (WG) diets. Nine healthy subjects participated in the dietary intervention with parallel crossover design, consisting of two high-fiber diets containing whole grain rye bread (WGR) or whole grain wheat bread (WGW) and 1-week control diets with refined wheat bread (WW) before both diet periods. Large interindividual differences were detected in the VOC composition. About 260 VOCs were detected from exhaled breath samples, in which 40 of the compounds were present in more than half of the samples. Various derivatives of benzoic acid and phenolic compounds, as well as some furanones existed in exhaled breath samples only after the WG diets, making them interesting compounds to study further.     

Noninvasive detection of colorectal cancer by analysis of exhaled breath

There has been growing interest in exhaled breath analysis for cancer screening and disease monitoring; however, limited breath biomarker information exists regarding colorectal cancer (CRC). The objective of this study was to screen for breath biomarkers of CRC. Exhaled breath was collected from 20 CRC patients and 20 healthy controls; subsequently, solid-phase microextraction–gas chromatography/mass spectrometry (SPME-GC/MS) was used to assess the exhaled volatile organic compounds (VOCs) of the study participants. The statistical methods of principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed to process the final data. The VOCs in the exhalations of CRC patients exhibited significant differences from the VOCs in the exhalations of healthy controls; in particular, relative to the latter exhalations, the former exhalations contain significantly higher levels of cyclohexanone, 2,2-dimethyldecane, dodecane, 4-ethyl-1-octyn-3-ol, ethylaniline, cyclooctylmethanol, trans-2-dodecen-1-ol, and 3-hydroxy-2,4,4-trimethylpentyl 2-methylpropanoate but significantly lower levels of 6-t-butyl-2,2,9,9-tetramethyl-3,5-decadien-7-yne (P?<?0.05). Analyses of breath VOCs provide a related model of CRC exhalation that could represent an effective and convenient screening method for this disease.

人体呼出气中挥发性有机化合物的检测方法

呼出气检测作为一种潜在的新型临床检测手段受到广泛关注。本文详细综述了人体呼出气中挥发性有机化合物(VOCs)的各类检测方法和技术,分别对色谱法、质谱法和光谱及传感器法的原理、特点和最新研究进展进行了介绍,对照总结了目前已确定的异戊二烯、丙酮等疾病生物标志物的各种分析方法和实测数据,并展望了未来的研究动向。     

Human exhaled air analytics: biomarkers of diseases

Over the last few years, breath analysis for the routine monitoring of metabolic disorders has attracted a considerable amount of scientific interest, especially since breath sampling is a non-invasive technique, totally painless and agreeable to patients. The investigation of human breath samples with various analytical methods has shown a correlation between the concentration patterns of volatile organic compounds (VOCs) and the occurrence of certain diseases. It has been demonstrated that modern analytical instruments allow the determination of many compounds found in human breath both in normal and anomalous concentrations. The composition of exhaled breath in patients with, for example, lung cancer, inflammatory lung disease, hepatic or renal dysfunction and diabetes contains valuable information. Furthermore, the detection and quantification of oxidative stress, and its monitoring during surgery based on composition of exhaled breath, have made considerable progress. This paper gives an overview of the analytical techniques used for sample collection, preconcentration and analysis of human breath composition. The diagnostic potential of different disease-marking substances in human breath for a selection of diseases and the clinical applications of breath analysis are discussed.     

Ultrafast gas chromatography coupled to electronic nose to identify volatile biomarkers in exhaled breath from chronic obstructive pulmonary disease patients: A pilot study

An analytical method to identify volatile organic compounds (VOCs) in the exhaled breath from patients with a diagnosis of chronic obstructive pulmonary disease (COPD) using a ultrafast gas chromatography system equipped with an electronic nose detector (FGC eNose) has been developed. A prospective study was performed in 23 COPD patients and 33 healthy volunteers; exhalation breathing tests were performed with Tedlar bags. Each sample was analyzed by FCG eNose and the identification of VOCs was based on the Kovats index. Raw data were reduced by principal component analysis (PCA) and canonical discriminant analysis [canonical analysis of principal coordinates (CAP)]. The FCG eNose technology was able to identify 17 VOCs that distinguish COPD patients from healthy volunteers. At all stages of PCA and CAP the discrimination between groups was obvious. Chemical prints were correctly classified up to 82.2%, and were matched with 78.9% of the VOCs detected in the exhaled breath samples. Receiver operating characteristic curve analysis indicated the sensitivity and specificity to be 96% and 91%, respectively. This pilot study demonstrates that FGC eNose is a useful tool to identify VOCs as biomarkers in exhaled breath from COPD patients. Further studies should be performed to enhance the clinical relevance of this quick and ease methodology for COPD diagnosis.     

Identification of volatile lung cancer markers by gas chromatography–mass spectrometry: comparison with discrimination by canines

In this work, a chromatographic method for identification of volatile organic compounds was compared with canine recognition. Gas chromatography and mass spectrometry (GC-TOF MS) were used for determination of concentrations of trace gases present in human breath. The technique enables rapid determination of compounds in human breath, at the parts per billion level. Linear correlations were from 0.83-234.05 ppb, the limit of detection was the range 0.31-0.75 ppb, and precision, expressed as relative standard deviation (RSD), was less than 10.00 %. Moreover, trained dogs are able to discriminate breath samples of patients with diagnosed cancer. We found a positive correlation between dog indications and the ethyl acetate and 2-pentanone content of breath (r = 0.85 and r = 0.97, respectively). The methods presented for detection of lung cancer markers in exhaled air could be used as a potential non-invasive tool for screening. In addition, the canine method is relatively simple and inexpensive in comparison with chromatography.     

Detection of infectious agents in the airways by ion mobility spectrometry of exhaled breath

Diseases of the lung, e. g. chronic obstructive pulmonary disease (COPD), interstitial lung diseases, bronchiectasis or cystic fibrosis, often lead to recurrent severe respiratory infections that cause exacerbations of the underlying disease. These acute or chronic inflammatory processes can result in a progressive destruction of the lung and in an ongoing decline in lung function. Therefore longer inpatient stays for intravenous antibiotic treatment are necessary and the quality of life in these patients is severely limited. A rapid detection of infectious agents in human lungs is often crucial, because the choice of the appropriate therapeutic regime depends at first on the identification of the infecting species. Standard methods for detection and identification are either time consuming, of low sensitivity or expensive. It is known that bacteria, and also mitosporic fungi, produce volatile organic compounds (VOCs) that can be detected in exhaled breath by ion mobility spectrometry (IMS), were a distinct detection of a specific VOC is related to a “peak”. We investigated, whether the detection and characterisation of VOCs by Multi-capillary column coupled to IMS in exhaled breath of patients whose airways are either infected or colonized by Pseudomonas aeruginosa compared to healthy non-smoker controls is capable of identifying those infectious agents. To realize a non invasive identification of pathogens, the exhaled breath of 53 persons (24 patients suffering chronic or infectious on Pseudomonas and 29 healthy controls) was investigated using an ion mobility spectrometer type BioScout. In total 224 different signals were found. Actually, 21 different signals are able to differentiate the two groups, Control and Pseudomonas, with rank sum values less than 0.2. For all 224 signals Box-and-Wisker plots were realized. The peaks with the lowest rank sum values F (0,107) and PS0 (0,112) show rather good separation of both groups. Our preliminary results demonstrate that distinct patterns of a small number of IMS-peaks are sufficient for the identification of these infectious agents. Therefore MCC-IMS seems to be a promising method for the non-invasive identification of patients which are colonized or infected with bacteria such as Pseudomonas aeruginosa.     

Detection of volatile organic compounds (VOCs) in exhaled breath of patients with chronic obstructive pulmonary disease (COPD) by ion mobility spectrometry

COPD is a disease characterised by a chronic inflammation of the airways and a not fully reversible airway obstruction. The spirometry is considered as gold-standard to diagnose the disease and to grade its severity. In this study we used the methodology of Ion Mobility Spectometry in order to detect Volatile Organic Compounds (VOCs) in exhaled breath of patients with COPD. The purpose of this study was to investigate if the VOCs detected in patients with COPD were different from the VOCs detected in exhaled breath of healthy controls. 13 COPD patients and 33 healthy controls were included in the study. Breath samples were collected via a side-steam Teflon tube and directly measured by an ion mobility spectrometer coupled to a multi capillary column (MCC/IMS). One peak was identified only in the patients group compared to the healthy control group. Consequently, the analysis of exhaled breath could be a useful tool to diagnose COPD.     

Pilot Study on Exhaled Breath Analysis for a Healthy Adult Population in Hawaii

Fast diagnostic results using breath analysis are an anticipated possibility for disease diagnosis or general health screenings. Tests that do not require sending specimens to medical laboratories possess capabilities to speed patient diagnosis and protect both patient and healthcare staff from unnecessary prolonged exposure. The objective of this work was to develop testing procedures on an initial healthy subject cohort in Hawaii to act as a range-finding pilot study for characterizing the baseline of exhaled breath prior to further research. Using comprehensive two-dimensional gas chromatography (GC×GC), this study analyzed exhaled breath from a healthy adult population in Hawaii to profile the range of different volatile organic compounds (VOCs) and survey Hawaii-specific differences. The most consistently reported compounds in the breath profile of individuals were acetic acid, dimethoxymethane, benzoic acid methyl ester, and n-hexane. In comparison to other breathprinting studies, the list of compounds discovered was representative of control cohorts. This must be considered when implementing proposed breath diagnostics in new locations with increased interpersonal variation due to diversity. Further studies on larger numbers of subjects over longer periods of time will provide additional foundational data on baseline breath VOC profiles of control populations for comparison to disease-positive cohorts.     

基于气相离子迁移谱研究肺隐球病患者呼出气中特征挥发性有机物

该文采用气相色谱离子迁移谱(GC-IMS)对81例受试者呼出气样品进行了检测,包括临床确诊的20例肺隐球菌病患者,以及28例临床确诊的肺曲霉病患者和33例健康个体的对照样品,单个样品分析仅需10 min。结果显示,所有呼气样品中共检出19种挥发性有机物(VOCs)。通过主成分(PCA)分析发现,肺隐球病患者呼气中VOCs与健康对照组差异显著,但与肺曲霉病患者呼气中VOCs差异不显著。正交偏最小二乘判别模型(OPLS-DA)分析显示,与健康人群相比,肺隐球菌病患者呼气中特征VOCs为2-甲基-1-丙醛、异丙苯、2-戊酮、4-甲基-2-戊酮、丁醛和己醛;肺曲霉病患者的呼气特征VOCs为2-丁酮、2-戊酮、异丙苯、2-甲基-1-丙醛、4-甲基-2-戊酮和3-戊酮。此外,2种肺部感染患者呼气中特征性VOCs均包括2-甲基-1-丙醛、异丙苯、4-甲基-2-戊酮和2-戊酮,这表明丁醛和己醛在肺隐球菌病患者呼气中特异性略强,而2-丁酮和3-戊酮在肺曲霉病患者呼气中特异性更好。综上,采用GC-IMS可快速检出肺隐球病患者呼气中的VOCs,可用于后续数百例甚至数千例大样本分析,为更客观地评价呼气用于肺部真菌感染诊断的可行性提供必要的基础数据。     

纳米材料在用于癌症诊断的呼出气挥发性有机物检测中的应用

细胞新陈代谢的变化会导致挥发性有机化合物（VOCs）类型及含量发生变化,因此可通过分析某些标志性VOCs简立起多种疾病早期诊断的模型. 人体呼出物中特征VOCs的检测作为一种非侵入性、无损的检测手段,近些年在疾病检测领域已成为世界范围内的研究热点. 其中,纳米材料可用于增强传感器性能,并使传感器便携式小型化,推进检测传感器进入临床. 在这篇综述中,作者将种类繁多的传感器中用到的纳米材料归纳总结为金属、金属氧化物、碳基、复合物和MOFs基纳米材料等几类,并讨论了不同类纳米材料在VOCs检测中的优劣势. 本文所建立起的分析方法及讨论有助于进一步了解检测技术的优越性与局限性. 最后,作者对利用VOCs的检测实现癌症早期筛选的研究及发展提出了个人观点.     

Determination of volatile organic compounds in human breath for Helicobacter pylori detection by SPME-GC/MS

Helicobacter pylori living in the human stomach release volatile organic compounds (VOCs) that can be detected in expired air. The aim of the study was the application of breath analysis for bacteria detection. It was accomplished by determination of VOCs characteristic for patients with H. pylori and the analysis of gases released by bacteria in suspension. Solid-phase microextraction was applied as a selective technique for preconcentration and isolation of analytes. Gas chromatography coupled with mass spectrometry was used for the separation and identification of volatile analytes in breath samples and bacterial headspace. For data calculation and processing, discriminant and factor analyses were used. Endogenous substances such as isobutane, 2-butanone and ethyl acetate were detected in the breath of persons with H. pylori in the stomach and in the gaseous mixture released by the bacteria strain but they were not identified in the breath of healthy volunteers. The canonical analysis of discrimination functions showed a strong difference between the three examined groups. Knowledge of substances emitted by H. pylori with the application of an optimized breath analysis method might become a very useful tool for noninvasive detection of this bacterium.     

二次纳流电喷雾电离耦合超高分辨质谱检测人体呼出气中相对高分子量化合物

二次电喷雾电离源耦合超高分辨质谱(SESI-UHRMS)有望检出人体呼出气中分子量大于300的相对高分子量化合物,这些化合物的发现将有助于更准确地理解呼出气中挥发性有机化合物(VOCs)的来源、产生机制以及SESI源电离机理,更好地实现SESI-UHRMS的转化应用.本研究自组装nanoSESI源(尚无商业产品)耦合四极杆-静电场轨道阱质谱(最高质量分辨率1.2×10~5),考察了该装置对健康人体呼出气中分子量为300~500化合物的检出情况.结果表明,所搭建的nanoSESI-UHRMS装置检测人体呼出气的重现性好、灵敏度高,可检出数十种分子量为300~500的化合物.根据这些化合物在单次呼气过程中信号强度随时间变化的趋势,推断其来源分别为内源性和外源性;各化合物的元素组成主要包括C,H,N和O,环-双键当量(RDB)的均值为(4.5±3.1),表明检出的化合物可能为醛酮或不饱和脂肪酸,容易在SESI源中被电离.本研究初步验证了自组建nanoSESI-UHRMS检测人体呼出气中相对高分子量化合物的可行性,为后续进一步开展方法应用奠定了基础.     

An adaptive breath sampler for use with human subjects with an impaired respiratory function

An adaptive sampler for collecting 2.5 dm(3) samples of exhaled air from human subjects with an impaired respiratory function is described. Pressure in the upper respiratory tract is continuously monitored and the data used to control an automated system to collect select portions of the expired breathing cycle onto a mixed bed Tenax(trade mark) and Carbotrap(trade mark) adsorbent trap for analysis by GC-MS. The sampling approach is intended for use in metabolomic profiling of volatiles in human breath at concentrations greater than microg m(-3). The importance of experimental reproducibility in metabolomic data is emphasised and consequently a high purity air supply is used to maintain a stable exogenous volatile organic compound profile at concentrations in the range 5 to 30 microg m(-3). The results of a 90 day stability study showed that exogenous VOCs were maintained at significantly lower levels (40 times lower for isopropyl alcohol) and with significantly higher reproducibility (80 times lower standard deviation for isopropyl alcohol) than would have been be the case if ambient air had been used. The sampling system was evaluated with healthy controls alongside subjects with chronic obstructive pulmonary disease. Subjects were able to breathe normally with control subjects observed to breathe at a rate of 9 to 17 breaths per minute, compared to 16 to 30 breaths per minute for subjects with COPD. This study presents, for the first time, observations and estimates of intra-subject breath sample reproducibility from human subjects. These reproducibility studies indicated that VOCs in exhaled breath exhibit a variety of dynamic behaviours, with some species recovered with a RSD <30%, while other species were observed to have significantly more variable concentrations, 30 to 130% RSD. The approach was also demonstrated to reliably differentiate the differences in the VOC profiles between alveolar and dead space air.     

Volatile organic compounds in head and neck squamous cell carcinoma—An in vitro pilot study

Owing to the lack of specific symptoms, diagnosis of head and neck squamous cell carcinoma (HNSCC) may be delayed. We evaluated volatile organic compounds in tumor samples from patients suffering from HNSCC and tested the hypothesis that there is a characteristic altered composition in the headspace of HNSCC compared with control samples from the same patient with normal squamous epithelium. These results provide the basis for future noninvasive breath analysis in HNSCC. Headspace air of suspected tumor and contralateral control samples in 20 patients were analyzed using ion-mobility spectrometry. Squamous cell carcinoma was diagnosed in 16 patients. In total, we observed 93 different signals in headspace measurements. Squamous cell carcinomas revealed significantly higher levels of volatile cyclohexanol (0.54 ppb_v, 25th to 75th percentiles 0.35–0.86) compared with healthy squamous epithelium (0.24 ppb_v, 25th to 75th percentiles 0.12–0.3; p < 0.001). In conclusion, head and neck squamous cell carcinoma emitted significantly higher levels of volatile cyclohexanol in headspace compared with normal squamous epithelium. These findings form the basis for future breath analysis for diagnosis, therapy control and the follow-up of HNSSC to improve therapy and aftercare.     

Selected ion flow tube mass spectrometry of exhaled breath condensate headspace

Collection of exhaled breath condensate (EBC) is a relatively simple noninvasive method of breath analysis; however, no data have been reported that would relate concentration of volatile compounds in EBC to their gaseous concentrations in exhaled air. The aim of the study was to investigate which volatile compounds are present in EBC and how their concentrations relate to results of direct breath analysis. Thus, samples of EBC were collected in a standard way from several subjects and absolute levels of several common volatile breath metabolites (ammonia, acetone, ethanol, methanol, propanol, isoprene, hydrogen cyanide, formaldehyde and acetaldehyde) were then determined in their headspace using selected ion flow tube mass spectrometry (SIFT-MS). Results are compared with those from on-line breath analyses carried out immediately before collecting the EBC samples. It has been demonstrated that SIFT-MS can be used to quantify the concentrations of volatiles in EBC samples and that, for methanol, ammonia, ethanol and acetone, the EBC concentrations correlate with the direct breath levels. However, the EBC concentrations of isoprene, formaldehyde, acetaldehyde, hydrogen cyanide and propanol do not correlate with direct breath measurements. Copyright (c) 2008 John Wiley & Sons, Ltd.     

Detection of Paratuberculosis in Dairy Herds by Analyzing the Scent of Feces,Alveolar Gas,and Stable Air

Paratuberculosis is an important disease of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). Early detection is crucial for successful infection control, but available diagnostic tests are still dissatisfying. Methods allowing a rapid, economic, and reliable identification of animals or herds affected by MAP are urgently required. This explorative study evaluated the potential of volatile organic compounds (VOCs) to discriminate between cattle with and without MAP infections. Headspaces above fecal samples and alveolar fractions of exhaled breath of 77 cows from eight farms with defined MAP status were analyzed in addition to stable air samples. VOCs were identified by GC–MS and quantified against reference substances. To discriminate MAP-positive from MAP-negative samples, VOC feature selection and random forest classification were performed. Classification models, generated for each biological specimen, were evaluated using repeated cross-validation. The robustness of the results was tested by predicting samples of two different sampling days. For MAP classification, the different biological matrices emitted diagnostically relevant VOCs of a unique but partly overlapping pattern (fecal headspace: 19, alveolar gas: 11, stable air: 4–5). Chemically, relevant compounds belonged to hydrocarbons, ketones, alcohols, furans, and aldehydes. Comparing the different biological specimens, VOC analysis in fecal headspace proved to be most reproducible, discriminatory, and highly predictive.     

Analysis of human breath with micro extraction techniques and continuous monitoring of carbon dioxide concentration

The detection of volatile organic compounds (VOCs) in human breath can be useful for the clinical routine diagnosis of several diseases in a non-invasive manner. Traditional methods of breath analysis have some major technical problems and limitations. Membrane extraction with a sorbent interface (MESI), however, has many advantages over current methods, including good selectivity and sensitivity, and is well suited for breath analysis. The aim of this project was to develop a simple and reproducible sampling device and method based on the MESI system for breath analysis. The feasibility and validity of the MESI system was tested with real human breath samples. Internal standard calibration methods were used for the quantitative analysis of various breath samples. Calibration curves for some main components (target analytes such as acetone and pentane) were determined in the research. The optimized stripping-side and feeding-side gas velocities were determined. The use of breath CO₂ as an internal standard for the analysis of breath VOCs is an effective method to solve the difficulties associated with variations in the target analyte concentrations in a sample, which are attributed to mass losses and different breathing patterns of different subjects. In this study, the concentration of breath acetone was successfully expressed normalized to CO₂ as in the alveolar air. Breath acetone of healthy males and females profiled at different times of the day was plotted using the MESI system, and results were consistent with the literature. This technique can be used for monitoring breath acetone concentrations of diabetic patients and for applications with other biomarker monitoring.     

Chemical characterization of exhaled breath to differentiate between patients with malignant plueral mesothelioma from subjects with similar professional asbestos exposure

Malignant pleural mesothelioma (MPM) is an aggressive tumour whose main aetiology is the long-term exposure to asbestos fibres. The diagnostic procedure of MPM is difficult and often requires invasive approaches; therefore, it is clinically important to find accurate markers for MPM by new noninvasive methods that may facilitate the diagnostic process and identify patients at an earlier stage. In the present study, the exhaled breath of 13 patients with histology-established diagnosis of MPM, 13 subjects with long-term certified professional exposure to asbestos (EXP) and 13 healthy subjects without exposure to asbestos (healthy controls, HC) were analysed. An analytical procedure to determine volatile organic compounds by sampling of air on a bed of solid sorbent and thermal desorption GC-MS analysis was developed in order to identify the compounds capable of discriminating among the three groups. The application of univariate (ANOVA) and multivariate statistical treatments (PCA, DFA and CP-ANN) showed that cyclopentane and cyclohexane were the dominant variables able to discriminate among the three groups. In particular, it was found that cyclohexane is the only compound able to differentiate the MPM group from the other two; therefore, it can be a possible marker of MPM. Cyclopentane is the dominant compound in the discrimination between EXP and the other groups (MPM and HC); then, it can be considered a good indicator for long-term asbestos exposure. This result suggests the need to perform frequent and thorough investigations on people exposed to asbestos in order to constantly monitor their state of health or possibly to study the evolution of disease over time.     

Chromatographic analysis of VOC patterns in exhaled breath from smokers and nonsmokers

Cigarette smoking harms nearly every organ of the body and causes many diseases. The analysis of exhaled breath for exogenous and endogenous volatile organic compounds (VOCs) can provide fundamental information on active smoking and insight into the health damage that smoke is creating. Various exhaled VOCs have been reported as typical of smoking habit and recent tobacco consumption, but to date, no eligible biomarkers have been identified. Aiming to identify such potential biomarkers, in this pilot study we analyzed the chemical patterns of exhaled breath from 26 volunteers divided into groups of nonsmokers and subgroups of smokers sampled at different periods of withdrawal from smoking. Solid‐phase microextraction technique and gas chromatography/mass spectrometry methods were applied. Many breath VOCs were identified and quantified in very low concentrations (ppbv range), but only a few (toluene, pyridine, pyrrole, benzene, 2‐butanone, 2‐pentanone and 1‐methyldecyclamine) were found to be statistically significant variables by Mann–Whitney test. In our analysis, we did not consider the predictive power of individual VOCs, as well as the criterion of uniqueness for biomarkers suggests, but we used the patterns of the only statistically significant compounds. Probit prediction model based on statistical relevant VOCs‐patterns showed that assessment of smoking status is heavily time dependent. In a two‐class classifier model, it is possible to predict with high specificity and sensitivity if a subject is a smoker who respected 1 hour of abstinence from smoking (short‐term exposure to tobacco) or a smoker (labelled "blank smoker") after a night out of smoking (long‐term exposure to tobacco). On the other side, in our study "blank smokers" are more like non‐smokers so that the two classes cannot be well distinguished and the corresponding prediction results showed a good sensitivity but low selectivity.