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.     

Volatile Organic Compounds Analysis in Breath Air in Healthy Volunteers and Patients Suffering Epidermoid Laryngeal Carcinomas

Exhaled breath contains thousands of gaseous volatile organic compounds (VOCs) that may be used as non-invasive markers of head and neck epidermoid cancer. We hypothesized that solid phase micro-extraction coupled to gas chromatography–mass spectrometry can discriminate patients with epidermoid head and neck cancer from healthy controls by analyzing the gaseous volatile organic compounds, VOC-profile, in exhaled breath, thus identifying some non-invasive biomarkers to be used in early detection. Twenty healthy subjects participated in a cross-sectional study plus 11 patients with epidermoid supraglottic laryngeal cancer. VOCs from T3 supraglottic cancer were clustered distinctly from those of T1 and healthy subjects. Up to seven VOCs were detected differently from healthy volunteers, mainly 2-butanone and ethanol. Thus VOC-patterns of exhaled breath may discriminate patients with epidermoid head and neck cancer from healthy controls.     

Statistical and bioinformatical methods to differentiate chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control by breath analysis using ion mobility spectrometry

Human breath analysis is a powerful and especially a non-invasive technique for the monitoring and hopefully also for the diagnosis of respiratory diseases, including chronic obstructive pulmonary disease (COPD). The exhaled breath of 95 patients suffering COPD and of 35 healthy controls was investigated using an Ion Mobility Spectrometer (IMS) coupled to a Multi-Capillary Column (MCC) without any pre-separation or pre-enrichment. Starting with the results from a Mann–Whitney-Wilcoxon rank sum test to find analytes with the highest potential with respect to differentiation, box and whisker plots, metabolic maps and probability charts were introduced and compared. In addition, the sensitivity, specificity, positive and negative predictive values and the accuracy of the relation were also summarized. The findings were compared to the results of a principal component analysis. Finally, decision trees were introduced to visualize the interdependencies between the analytes and the classifications. The application of these biostatistical methods with simultaneous inclusion of several VOCs for disease classification by ion mobility spectrometry of human breath will provide much more information than using single peaks and single concentration dependencies for disease classification and discrimination of various groups. Towards the future application of potential biomarkers for clinical diagnostic procedures, complex analytical methods, such as ion mobility spectrometry, need statistical and bioinformatical tools which are simple in application, visualize the results and support decisions on the basis of the data obtained from measurements of analytes in exhaled human breath.     

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.

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.     

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.     

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...     

Differentiation of chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control group by breath analysis using ion mobility spectrometry

Non-invasive methods with potential for diagnosis of lung diseases gain increasing interest. Within the present study the exhaled breath of 132 persons (97 Chronic obstructive pulmonary disease (COPD) patients [35 COPD without lung cancer, 62 COPD with lung cancer] and 35 healthy volunteers) was investigated using an Ion Mobility Spectrometer (IMS) coupled to a Multi-Capillary Column (MCC) without any pre-separation or pre-enrichment. One hundred four different peaks were considered within the IMS-Chromatograms of the 10 mL breath samples of both groups. A principal component analysis (PCA) of these 104 peaks identified a single analyte, that allowed a separation of the healthy persons and the COPD patients (with and without lung cancer). The sensitivity obtained was 60%, the specificity 91%, the positive predictive value 95%. The peak was characterized as cyclohexanone (CAS 108-94-1). Subsequent studies must validate the identity of the peak used for separation of the two groups with a greater population and external standards. Breath gas analysis using ion mobility spectrometry offers a chance of separating healthy persons and COPD patients using a single analyte at a defined concentration.     

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.     

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。     

The Influence of Smoking Status on Exhaled Breath Profiles in Asthma and COPD Patients

Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking <24 vs. >24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking <24 vs. >24 h. The area under the receiver–operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked <24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC: 0.74; 95% CI: 0.66–0.81), and no cigarette consumption <24h (AUC 0.54, 95% CI: 0.43–0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54; 95% CI: 0.49–0.60) and recent cigarette consumption (AUC 0.60; 95% CI: 0.50–0.69). The eNose could distinguish between ever and never-smokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles.     

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.     

柔性PDA薄膜阵列用于双模光学检测VOC标志物气体

本研究以亲油性的双面胶作为基底,利用滴涂二乙炔单体结合紫外光聚合来制备均匀的聚二乙炔(PDA)薄膜,通过荧光和颜色两种信号变化模式(即"双模光学检测")研究了PDA薄膜对VOC气体的响应性,发现制备的PDA薄膜在2 min内就可以实现明显的荧光和颜色变化,有效解决了目前PDA薄膜在VOC气体检测方面存在响应速度慢、薄膜均一性差等问题.此外,为解决单一PDA薄膜的交叉响应性问题,本研究制备了四种不同的基于双面胶基底的PDA薄膜,并将制备的4种PDA薄膜集成到一片PDMS薄膜基底上来构建柔性的传感阵列,利用阵列的颜色变化结合模式识别技术,实现了对8种VOC气体的快速、灵敏区分.进一步将制备的PDA薄膜阵列用于健康人、模拟糖尿病及肾病患者呼出气体中VOC标志物的辨别和分析研究,发现可以将三类人的呼出气体清晰地区分,说明了该阵列在呼气疾病诊断中的应用前景.与目前报道的PDA薄膜阵列相比,本研究中基于双面胶基底的PDA薄膜阵列具有气体响应速度快、灵敏性高、柔韧性好、制备工艺简单、成本低、易于大规模制备等优点,有望用于实VOC气体检测研究中.     

Role of differential scanning calorimetry (DSC) in the staging of COPD

Chronic obstructive pulmonary disease (COPD) is an imminent public health catastrophe. A proper severity marker is desperately needed to reflect the progress of the disease in a stage-specific manner (GOLD I–IV/A–D). The aim of the study was testing the applicability of thermodynamic analysis of blood, identifying different stages of COPD patients against each other and healthy controls. Sera from 63 COPD patients were investigated using differential scanning calorimetry (DSC). Patients formed four groups according to their GOLD severity stages, and smoking or ex-smoking subgroups were further analysed. In total, 18 GOLD A, 17 GOLD B, 16 GOLD C and 12 GOLD D patients’ DSC characteristics were investigated. Nine healthy sera (smoker and non-smoker controls) were evaluated using the same methodology. Enthalpy and melting parameters of severe COPD patients are significantly different from those in the early stages and from healthy subjects. There are clearly visible trends in both features in all stages as COPD progresses. The thermal denaturation parameters are significantly different between the smokers and non-smokers in advanced COPD stages (C&D). Healthy controls do not differ significantly according to their smoking status. The new thermophysical method described here has a potential to be applicable as a stage and/or symptom score of the individual COPD patients. Longitudinal studies are needed to monitor DSC changes of the same patients during progression and/or stagnation.     

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.     

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.     

Non-labeling multiplex surface enhanced Raman scattering (SERS) detection of volatile organic compounds (VOCs)

In this paper, we report multiplex SERS based VOCs detection with a leaning nano-pillar substrate. The VOCs analyte molecules adsorbed at the tips of the nano-pillars produced SERS signal due to the field enhancement occurring at the localized surface plasmon hot spots between adjacent leaning nano-pillars. In this experiment, detections of acetone and ethanol vapor at different concentrations were demonstrated. The detection limits were found to be 0.0017 ng and 0.0037 ng for ethanol and acetone vapor molecules respectively. Our approach is a non-labeling method such that it does not require the incorporation of any chemical sensing layer for the enrichment of gas molecules on sensor surface. The leaning nano-pillar substrate also showed highly reproducible SERS signal in cyclic VOCs detection, which can reduce the detection cost in practical applications. Further, multiplex SERS detection on different combination of acetone and ethanol vapor was also successfully demonstrated. The vibrational fingerprints of molecular structures provide specific Raman peaks for different VOCs contents. To the best of our knowledge, this is the first multiplex VOCs detection using SERS. We believe that this work may lead to a portable device for multiplex, specific and highly sensitive detection of complex VOCs samples that can find potential applications in exhaled breath analysis, hazardous gas analysis, homeland security and environmental monitoring.     

Ion trap liquid chromatography/tandem mass spectrometry analysis of leukotriene B4 in exhaled breath condensate

The objective of this study is the measurement of leukotriene B7 (LTB4), a potent inflammatory mediator, in exhaled breath condensate by using liquid chromatography/mass spectrometry (LC/MS and LC/MS/MS). Condensation of exhaled breath is a non-invasive method to collect airway secretions. Deuterated (d4)-LTB4 was used as internal standard. The MS and MS/MS behavior of LTB4 and LTB4-d4 was studied by electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) in both positive and negative ion polarity mode. Preliminary results show that monitoring negative ions in ESI mode has the best sensitivity for both LTB4 and LTB4-d4. Therefore, negative ESI was chosen, and the [M-H]- ions at m/z 335 and 339 were selected for quantification. The lower limit of quantification for LTB4, expressed as the lowest point of the calibration curve, was 100 pg/mL. Using this technique, we measured LTB4 in exhaled breath condensate in two healthy subjects, four asthmatic patients on anti-inflammatory treatment, and four asthmatic patients who were not on anti-inflammatory drugs. Exhaled LTB4 concentrations were detected only in asthmatic patients who were not on anti-inflammatory therapy. This method is potentially useful for non-invasive assessment of airway inflammation, but the sensitivity of the technique needs to be improved.     

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.     

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.