Breath analysis of smokers, non-smokers, and e-cigarette users

Serum-volatile organic compounds in the diagnostics of esophageal cancer

The early diagnosis of esophageal cancer (EC) is extremely challenging due to a lack of effective diagnostic methods. The study presented herein aims to assess whether serum volatile organic compounds (VOCs) could be utilised as emerging diagnostic biomarkers for EC. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in the serum samples of 55 patients with EC, with samples from 84 healthy controls (HCs) patients analysed as a comparison. All machine learning analyses were based on data from serum VOCs obtained by GC-IMS. A total of 33 substance peak heights were detected in all patient serum samples. The ROC analysis revealed that four machine learning models were effective in facilitating the diagnosis of EC. In addition, the random forests model for 5 VOCs had an AUC of 0.951, with sensitivities and specificities of 94.1 and 96.0%, respectively.

Chemical Analysis of Exhaled Vape Emissions: Unraveling the Complexities of Humectant Fragmentation in a Human Trial Study

Electronic cigarette smoking (or vaping) is on the rise, presenting questions about the effects of secondhand exposure. The chemical composition of vape emissions was examined in the exhaled breath of eight human volunteers with the high chemical specificity of complementary online and offline techniques. Our study is the first to take multiple exhaled puff measurements from human participants and compare volatile organic compound (VOC) concentrations between two commonly used methods, proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) and gas chromatography (GC). Five flavor profile groups were selected for this study, but flavor compounds were not observed as the main contributors to the PTR-ToF-MS signal. Instead, the PTR-ToF-MS mass spectra were overwhelmed by e-liquid thermal decomposition and fragmentation products, which masked other observations regarding flavorings and other potentially toxic species associated with secondhand vape exposure. Compared to the PTR-ToF-MS, GC measurements reported significantly different VOC concentrations, usually below those from PTR-ToF-MS. Consequently, PTR-ToF-MS mass spectra should be interpreted with caution when reporting quantitative results in vaping studies, such as doses of inhaled VOCs. Nevertheless, the online PTR-ToF-MS analysis can provide valuable qualitative information by comparing relative VOCs in back-to-back trials. For example, by comparing the mass spectra of exhaled air with those of direct puffs, we can conclude that harmful VOCs present in the vape emissions are largely absorbed by the participants, including large fractions of nicotine.

Dual Exposure to E-Cigarette Vapour and Cigarette Smoke Results in Poorer Airway Cell, Monocyte, and Macrophage Function Than Single Exposure

E-cigarette users predominantly also continue to smoke cigarettes. These Dual Users either consume e-cigarettes in locations where smoking is not allowed, but vaping is, or to reduce their consumption of cigarettes, believing it will lead to harm reduction. Whilst it is known that e-cigarette vapour is chemically less complex than cigarette smoke, it has a distinct chemical profile, and very little is known about the health impacts of exposure to both chemical profiles vs. either alone. We simultaneously exposed cells in vitro to non-toxic levels of e-cigarette vapour extract (EVE) and cigarette smoke extract (CSE) to determine their effects on 16HBE14o- airway epithelial cell metabolism and inflammatory response, as well as immune cell (THP-1 cells and monocyte-derived macrophages (MDM) from healthy volunteers) migration, phagocytosis, and inflammatory response. We observed increased toxicity, reduced metabolism (a marker of proliferation) in airway epithelial cells, and reduced monocyte migration, macrophage phagocytosis, and altered chemokine production after exposure to either CSE or EVE. These cellular responses were greater after dual exposure to CSE and EVE. The airway epithelial cells from smokers showed reduced metabolism after EVE (the Switcher model) and dual CSE and EVE exposure. When EVE and CSE were allowed to interact, the chemicals were found to be altered, and new chemicals were also found compared to the CSE and EVE profiles. Dual exposure to e-cigarette vapour and cigarette smoke led to worse functional outcomes in cells compared to either single exposure alone, adding to limited data that dual use may be more dangerous than smoking only.

Advancing accuracy in breath testing for lung cancer: strategies for improving diagnostic precision in imbalanced data

BACKGROUND

Breath testing using an electronic nose has been recognized as a promising new technique for the early detection of lung cancer. Imbalanced data are commonly observed in electronic nose studies, but methods to address them are rarely reported.

OBJECTIVE

The objectives of this study were to assess the accuracy of electronic nose screening for lung cancer with imbalanced learning and to select the best mechanical learning algorithm.

METHODS

We conducted a case‒control study that included patients with lung cancer and healthy controls and analyzed metabolites in exhaled breath using a carbon nanotube sensor array. The study used five machine learning algorithms to build predictive models and a synthetic minority oversampling technique to address imbalanced data. The diagnostic accuracy of lung cancer was assessed using pathology reports as the gold standard.

RESULTS

We enrolled 190 subjects between 2020 and 2023. A total of 155 subjects were used in the final analysis, which included 111 lung cancer patients and 44 healthy controls. We randomly divided samples into one training set, one internal validation set, and one external validation set. In the external validation set, the summary sensitivity was 0.88 (95% CI 0.84-0.91), the summary specificity was 1.00 (95% CI 0.85-1.00), the AUC was 0.96 (95% CI 0.94-0.98), the pAUC was 0.92 (95% CI 0.89-0.96), and the DOR was 207.62 (95% CI 24.62-924.64).

CONCLUSION

Electronic nose screening for lung cancer is highly accurate. The support vector machine algorithm is more suitable for analyzing chemical sensor data from electronic noses.

GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review

Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.

Exhaled volatile organic compounds associated with risk factors for obstructive pulmonary diseases: a systematic review

Background

Asthma and COPD are among the most common respiratory diseases. To improve the early detection of exacerbations and the clinical course of asthma and COPD new biomarkers are needed. The development of noninvasive metabolomics of exhaled air into a point-of-care tool is an appealing option. However, risk factors for obstructive pulmonary diseases can potentially introduce confounding markers due to altered volatile organic compound (VOC) patterns being linked to these risk factors instead of the disease. We conducted a systematic review and presented a comprehensive list of VOCs associated with these risk factors.

Methods

A PRISMA-oriented systematic search was conducted across PubMed, Embase and Cochrane Libraries between 2000 and 2022. Full-length studies evaluating VOCs in exhaled breath were included. A narrative synthesis of the data was conducted, and the Newcastle-Ottawa Scale was used to assess the quality of included studies.

Results

The search yielded 2209 records and, based on the inclusion/exclusion criteria, 24 articles were included in the qualitative synthesis. In total, 232 individual VOCs associated with risk factors for obstructive pulmonary diseases were found; 58 compounds were reported more than once and 12 were reported as potential markers of asthma and/or COPD in other studies. Critical appraisal found that the identified studies were methodologically heterogeneous and had a variable risk of bias.

Conclusion

We identified a series of exhaled VOCs associated with risk factors for asthma and/or COPD. Identification of these VOCs is necessary for the further development of exhaled metabolites-based point-of-care tests in these obstructive pulmonary diseases.

A review on characteristics and mitigation strategies of indoor air quality in underground subway stations

Due to the rapidly increasing ridership and the relatively enclosed underground space, the indoor air quality (IAQ) in underground subway stations (USSs) has attracted more public attention. The air pollutants in USSs, such as particulate matter (PM), CO₂ and volatile organic compounds (VOCs), are hazardous to the health of passengers and staves. Firstly, this paper presents a systematic review on the characteristics and sources of air pollutants in USSs. According to the review work, the concentrations of PM, CO₂, VOCs, bacteria and fungi in USSs are 1.1-13.2 times higher than the permissible concentration limits specified by WHO, ASHRAE and US EPA. The PM and VOCs are mainly derived from the internal and outdoor sources. CO₂ concentrations are highly correlated with the passenger density and the ventilation rate while the exposure levels of bacteria and fungi depend on the thermal conditions and the settled dust. Then, the online monitoring, fault detection and prediction methods of IAQ are summarized and the advantages and disadvantages of these methods are also discussed. In addition, the available control strategies for improving IAQ in USSs are reviewed, and these strategies are classified and compared from different viewpoints. Lastly, challenges of the IAQ management in the context of the COVID-19 epidemic and several suggestions for underground stations' IAQ management in the future are put forward. This paper is expected to provide a comprehensive guidance for further research and design of the effective prevention measures on air pollutants in USSs so as to achieve more sustainable and healthy underground environment.

High-resolution mass spectrometry exhalome profiling with a modified direct analysis in real time ion source

RATIONALE

Exhaled breath contains many substances that are closely related to human metabolism. Analysis of its composition is important for human health, but it is difficult. Since the volatile molecules in breath samples are exhaled instantaneously, easily diffused and modified, and at low level of presence, they are difficult to identify and quantify.

METHODS

A modified direct analysis in real time ion source was used for high-resolution mass spectrometry measurement of human metabolites in exhaled breath through online monitoring and offline analysis, in both positive and negative ion modes. The improved system enabled the breath volatiles as well as condensates to be directly sampled, rapidly transmitted and efficiently ionized in a confined region, and then detected using an Orbitrap mass analyzer.

RESULTS

The molecular features with online and offline analysis of exhaled breath were demonstrated with obvious differences. A total of about 65 metabolites in positive ion mode and about 55 metabolites in negative ion mode were identified based on accurate m/z values. Exhalome profile and the composition proportion of different classes of compounds were obtained. The relative contents of metabolites from breath varied during different time periods throughout a day.

CONCLUSIONS

A more complete picture of the human breath metabolome was provided combining the results obtained from both online and offline analysis. The developed method allows analysis of breath samples with different status rapidly and directly, and it features simple operation and metabolite identification, requiring little or no sample preparation.

Validating Discriminative Signatures for Obstructive Sleep Apnea in Exhaled Breath

Rapid and reliable tools for the diagnosis and monitoring of obstructive sleep apnea (OSA) are currently lacking. Prior studies using a chemical analysis of exhaled breath have suggested the existence of an OSA-specific metabolic signature. Here, we validated this diagnostic approach and the proposed marker compounds, as well as their potential to reliably diagnose OSA. In this cross-sectional observational study, exhaled breath was analyzed using secondary electrospray ionization high-resolution mass spectrometry. The study cohort included untreated OSA patients, OSA patients treated with continuous positive airway pressure and healthy subjects. The robustness of previously reported OSA markers was validated based on detectability, significant differences between groups (Mann–Whitney U test) and classification performance. The breath analysis of 118 participants resulted in 42 previously reported markers that could be confirmed in this independent validation cohort. Nine markers were significantly increased in untreated OSA compared to treated OSA, with a subset of them being consistent with a previous validation study. An OSA prediction based on the confirmed OSA signature performed with an AUC of 0.80 (accuracy 77%, sensitivity 73% and specificity 80%). As several breath markers were clearly found to be repeatable and robust in this independent validation study, these results underscore the clinical potential of breath analysis for OSA diagnostics and monitoring.

Short-Term Effect of Cigarette Smoke on Exhaled Volatile Organic Compounds Profile Analyzed by an Electronic Nose

Breath analysis using an electronic nose (e-nose) is an innovative tool for exhaled volatile organic compound (VOC) analysis, which has shown potential in several respiratory and systemic diseases. It is still unclear whether cigarette smoking can be considered a confounder when analyzing the VOC-profile. We aimed to assess whether an e-nose can discriminate exhaled breath before and after smoking at different time periods. We enrolled 24 healthy smokers and collected their exhaled breath as follows: (a) before smoking, (b) within 5 min after smoking, (c) within 30 min after smoking, and (d) within 60 min after smoking. Exhaled breath was collected by a previously validated method and analyzed by an e-nose (Cyranose 320). By principal component analysis, significant variations in the exhaled VOC profile were shown for principal component 1 and 2 before and after smoking. Significance was higher 30 and 60 min after smoking than 5 min after (p < 0.01 and <0.05, respectively). Canonical discriminant analysis confirmed the above findings (cross-validated values: baseline vs. 5 min = 64.6%, AUC = 0.833; baseline vs. 30 min = 83.6%, AUC = 0.927; baseline vs. 60 min = 89.6%, AUC = 0.933). Thus, the exhaled VOC profile is influenced by very recent smoking. Interestingly, the effect seems to be more closely linked to post-cigarette inflammation than the tobacco-related odorants.

Pilot study to determine differences in breath odour between cigarette and e-cigarette consumers

Cigarette smoke is known to influence breath odour, but the effect of e-cigarettes is unknown. In this pilot study, we aimed to determine differences in breath odour between cigarette smokers (CSs) and e-cigarette consumers (ECs) in 33 healthy subjects: 11 CSs, 11 ECs and 11 non-smokers (NSs). Breath was sampled at baseline and following product use (CSs and ECs) or a waiting period (NSs) by eight trained odour judges using a six-point smoke intensity scale and a nine-point hedonic scale. We observed a statistically significant difference between CSs and ECs. Smoke intensity values were significantly higher in CSs than ECs and NSs, which were comparable both at baseline and after product use. In addition, hedonic values for CSs were significantly lower than both NSs and ECs after product use. These acute results indicate that cigarette and e-cigarette use results in significantly different breath. ECs breath has a reduced smoke odour and more pleasant aroma than CSs, and is comparable to NSs. This suggests there may be cosmetic benefits for CSs who quit smoking or switch to exclusive use of ECs. Further studies are required to understand the long-term effects of e-cigarette use on breath odour.

A headspace collection chamber for whole body volatilomics

The human body secretes a complex blend of volatile organic compounds (VOCs) via the skin, breath and bodily fluids. In this study, we have developed a headspace collection chamber for whole body volatilome profiling.

Toxicology of flavoring- and cannabis-containing e-liquids used in electronic delivery systems

Electronic cigarettes (e-cigarettes) were introduced in the United States in 2007 and by 2014 they were the most popular tobacco product amongst youth and had overtaken use of regular tobacco cigarettes. E-cigarettes are used to aerosolize a liquid (e-liquid) that the user inhales. Flavorings in e-liquids is a primary reason for youth to initiate use of e-cigarettes. Evidence is growing in the scientific literature that inhalation of some flavorings is not without risk of harm. In this review, 67 original articles (primarily cellular in vitro) on the toxicity of flavored e-liquids were identified in the PubMed and Scopus databases and evaluated critically. At least 65 individual flavoring ingredients in e-liquids or aerosols from e-cigarettes induced toxicity in the respiratory tract, cardiovascular and circulatory systems, skeletal system, and skin. Cinnamaldehyde was most frequently reported to be cytotoxic, followed by vanillin, menthol, ethyl maltol, ethyl vanillin, benzaldehyde and linalool. Additionally, modern e-cigarettes can be modified to aerosolize cannabis as dried plant material or a concentrated extract. The U.S. experienced an outbreak of lung injuries, termed e-cigarette, or vaping, product use-associated lung injury (EVALI) that began in 2019; among 2,022 hospitalized patients who had data on substance use (as of January 14, 2020), 82% reported using a delta-9-tetrahydrocannabinol (main psychoactive component in cannabis) containing e-cigarette, or vaping, product. Our literature search identified 33 articles related to EVALI. Vitamin E acetate, a diluent and thickening agent in cannabis-based products, was strongly linked to the EVALI outbreak in epidemiologic and laboratory studies; however, e-liquid chemistry is highly complex, and more than one mechanism of lung injury, ingredient, or thermal breakdown product may be responsible for toxicity. More research is needed, particularly with regard to e-cigarettes (generation, power settings, etc.), e-liquids (composition, bulk or vaped form), modeled systems (cell type, culture type, and dosimetry metrics), biological monitoring, secondhand exposures and contact with residues that contain nicotine and flavorings, and causative agents and mechanisms of EVALI toxicity.

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.