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Journal of Breath Research

Purpose-led Publishing is a coalition of three not-for-profit publishers in the field of physical sciences: AIP Publishing, the American Physical Society and IOP Publishing.

Together, as publishers that will always put purpose above profit, we have defined a set of industry standards that underpin high-quality, ethical scholarly communications.

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This journal is dedicated to all aspects of breath science, with the major focus on analysis of exhaled breath in physiology and medicine, and the diagnosis and treatment of breath odours.

Official Journal of the International Association for Breath Research ( IABR ).

This journal is currently seeking an enthusiastic and experienced Editor-in-Chief. The deadline for applications is 15 April 2024. Find out more and apply.

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Veronika Ruzsányi and Miklós Péter Kalapos 2017 J. Breath Res. 11 024002

In recent decades, two facts have changed the opinion of researchers about the function of acetone in humans. Firstly, it has turned out that acetone cannot be regarded as simply a waste product of metabolism, because there are several pathways in which acetone is produced or broken down. Secondly, methods have emerged making possible its detection in exhaled breath, thereby offering an attractive alternative to investigation of blood and urine samples. From a clinical point of view the measurement of breath acetone levels is important, but there are limitations to its wide application. These limitations can be divided into two classes, technical and biological limits. The technical limits include the storage of samples, detection threshold, standardization of clinical settings, and the price of instruments. When considering the biological ranges of acetone, personal factors such as race, age, gender, weight, food consumption, medication, illicit drugs, and even profession/class have to be taken into account to use concentration information for disorders. In some diseases such as diabetes mellitus and lung cancer, as well as in nutrition-related behavior such as starvation and ketogenic diet, breath acetone has been extensively examined. At the same time, there is a lack of investigations in other cases in which ketosis is also evident, such as in alcoholism or an inborn error of metabolism. In summary, the detection of acetone in exhaled breath is a useful and promising tool for diagnosis and it can be used as a marker to follow the effectiveness of treatments in some disorders. However, further endeavors are needed for clarification of the exact distribution of acetone in different body compartments and evaluation of its complex role in humans, especially in those cases in which a ketotic state also occurs.

Theo Issitt et al 2022 J. Breath Res. 16 024001

Volatile compounds contained in human breath reflect the inner workings of the body. A large number of studies have been published that link individual components of breath to disease, but diagnostic applications remain limited, in part due to inconsistent and conflicting identification of breath biomarkers. New approaches are therefore required to identify effective biomarker targets. Here, volatile organic compounds have been identified in the literature from four metabolically and physiologically distinct diseases and grouped into chemical functional groups (e.g. methylated hydrocarbons or aldehydes; based on known metabolic and enzymatic pathways) to support biomarker discovery and provide new insight on existing data. Using this functional grouping approach, principal component analysis doubled explanatory capacity from 19.1% to 38% relative to single individual compound approaches. Random forest and linear discriminant analysis reveal 93% classification accuracy for cancer. This review and meta-analysis provides insight for future research design by identifying volatile functional groups associated with disease. By incorporating our understanding of the complexities of the human body, along with accounting for variability in methodological and analytical approaches, this work demonstrates that a suite of targeted, functional volatile biomarkers, rather than individual biomarker compounds, will improve accuracy and success in diagnostic research and application.

Jonathan D Beauchamp and Chris A Mayhew 2023 J. Breath Res. 17 042001

In this perspective, we review the evidence for the efficacy of face masks to reduce the transmission of respiratory viruses, specifically severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and consider the value of mandating universal mask wearing against the widespread negative impacts that have been associated with such measures. Before the SARS-CoV-2 pandemic, it was considered that there was little to no benefit in healthy people wearing masks as prophylaxis against becoming infected or as unwitting vectors of viral transmission. This accepted policy was hastily reversed early on in the pandemic, when districts and countries throughout the world imposed stringent masking mandates. Now, more than three years since the start of the pandemic, the amassed studies that have investigated the use of masks to reduce transmission of SARS-CoV-2 (or other pathogens) have led to conclusions that are largely inconsistent and contradictory. There is no statistically significant or unambiguous scientific evidence to justify mandatory masking for general, healthy populations with the intention of lessening the viral spread. Even if mask wearing could potentially reduce the transmission of SARS-CoV-2 in individual cases, this needs to be balanced against the physical, psychological and social harms associated with forced mask wearing, not to mention the negative impact of innumerable disposed masks entering our fragile environment. Given the lack of unequivocal scientific proof that masks have any effect on reducing transmission, together with the evident harms to people and the environment through the use of masks, it is our opinion that the mandatory use of face masks in the general population is unjustifiable and must be abandoned in future pandemic countermeasures policies.

Qizhong Liang et al 2023 J. Breath Res. 17 036001

Rapid testing is essential to fighting pandemics such as coronavirus disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exhaled human breath contains multiple volatile molecules providing powerful potential for non-invasive diagnosis of diverse medical conditions. We investigated breath detection of SARS-CoV-2 infection using cavity-enhanced direct frequency comb spectroscopy (CE-DFCS), a state-of-the-art laser spectroscopic technique capable of a real-time massive collection of broadband molecular absorption features at ro-vibrational quantum state resolution and at parts-per-trillion volume detection sensitivity. Using a total of 170 individual breath samples (83 positive and 87 negative with SARS-CoV-2 based on reverse transcription polymerase chain reaction tests), we report excellent discrimination capability for SARS-CoV-2 infection with an area under the receiver-operating-characteristics curve of 0.849(4). Our results support the development of CE-DFCS as an alternative, rapid, non-invasive test for COVID-19 and highlight its remarkable potential for optical diagnoses of diverse biological conditions and disease states.

Rohit Vadala et al 2023 J. Breath Res. 17 024002

Lung cancer is one of the common malignancies with high mortality rate and a poor prognosis. Most lung cancer cases are diagnosed at an advanced stage either due to limited resources of infrastructure, trained human resources, or delay in clinical suspicion. Low-dose computed tomography has emerged as a screening tool for lung cancer detection but this may not be a feasible option for most developing countries. Electronic nose is a unique non-invasive device that has been developed for lung cancer diagnosis and monitoring response by exhaled breath analysis of volatile organic compounds. The breath-print have been shown to differ not only among lung cancer and other respiratory diseases, but also between various types of lung cancer. Hence, we postulate that the breath-print analysis by electronic nose could be a potential biomarker for the early detection of lung cancer along with monitoring treatment response in a resource-limited setting. In this review, we have consolidated the current published literature suggesting the use of an electronic nose in the diagnosis and monitoring treatment response of lung cancer.

Ruth P Cusack et al 2024 J. Breath Res. 18 026009

Detection of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) relies on real-time-reverse-transcriptase polymerase chain reaction (RT-PCR) on nasopharyngeal swabs. The false-negative rate of RT-PCR can be high when viral burden and infection is localized distally in the lower airways and lung parenchyma. An alternate safe, simple and accessible method for sampling the lower airways is needed to aid in the early and rapid diagnosis of COVID-19 pneumonia. In a prospective unblinded observational study, patients admitted with a positive RT-PCR and symptoms of SARS-CoV-2 infection were enrolled from three hospitals in Ontario, Canada. Healthy individuals or hospitalized patients with negative RT-PCR and without respiratory symptoms were enrolled into the control group. Breath samples were collected and analyzed by laser absorption spectroscopy (LAS) for volatile organic compounds (VOCs) and classified by machine learning (ML) approaches to identify unique LAS-spectra patterns (breathprints) for SARS-CoV-2. Of the 135 patients enrolled, 115 patients provided analyzable breath samples. Using LAS-breathprints to train ML classifier models resulted in an accuracy of 72.2%–81.7% in differentiating between SARS-CoV2 positive and negative groups. The performance was consistent across subgroups of different age, sex, body mass index, SARS-CoV-2 variants, time of disease onset and oxygen requirement. The overall performance was higher than compared to VOC-trained classifier model, which had an accuracy of 63%–74.7%. This study demonstrates that a ML-based breathprint model using LAS analysis of exhaled breath may be a valuable non-invasive method for studying the lower airways and detecting SARS-CoV-2 and other respiratory pathogens. The technology and the ML approach can be easily deployed in any setting with minimal training. This will greatly improve access and scalability to meet surge capacity; allow early and rapid detection to inform therapy; and offers great versatility in developing new classifier models quickly for future outbreaks.

Anna Paleczek and Artur Rydosz 2022 J. Breath Res. 16 026003

Currently, intensive work is underway on the development of truly noninvasive medical diagnostic systems, including respiratory analysers based on the detection of biomarkers of several diseases including diabetes. In terms of diabetes, acetone is considered as a one of the potential biomarker, although is not the single one. Therefore, the selective detection is crucial. Most often, the analysers of exhaled breath are based on the utilization of several commercially available gas sensors or on specially designed and manufactured gas sensors to obtain the highest selectivity and sensitivity to diabetes biomarkers present in the exhaled air. An important part of each system are the algorithms that are trained to detect diabetes based on data obtained from sensor matrices. The prepared review of the literature showed that there are many limitations in the development of the versatile breath analyser, such as high metabolic variability between patients, but the results obtained by researchers using the algorithms described in this paper are very promising and most of them achieve over 90% accuracy in the detection of diabetes in exhaled air. This paper summarizes the results using various measurement systems, feature extraction and feature selection methods as well as algorithms such as support vector machines, k -nearest neighbours and various variations of neural networks for the detection of diabetes in patient samples and simulated artificial breath samples.

Hsuan Chou et al 2024 J. Breath Res. 18 026008

Exhaustive exercise can induce unique physiological responses in the lungs and other parts of the human body. The volatile organic compounds (VOCs) in exhaled breath are ideal for studying the effects of exhaustive exercise on the lungs due to the proximity of the breath matrix to the respiratory tract. As breath VOCs can originate from the bloodstream, changes in abundance should also indicate broader physiological effects of exhaustive exercise on the body. Currently, there is limited published data on the effects of exhaustive exercise on breath VOCs. Breath has great potential for biomarker analysis as it can be collected non-invasively, and capture real-time metabolic changes to better understand the effects of exhaustive exercise. In this study, we collected breath samples from a small group of elite runners participating in the 2019 Ultra-Trail du Mont Blanc ultra-marathon. The final analysis included matched paired samples collected before and after the race from 24 subjects. All 48 samples were analyzed using the Breath Biopsy Platform with GC-Orbitrap™ via thermal desorption gas chromatography-mass spectrometry. The Wilcoxon signed-rank test was used to determine whether VOC abundances differed between pre- and post-race breath samples (adjusted P -value < .05). We identified a total of 793 VOCs in the breath samples of elite runners. Of these, 63 showed significant differences between pre- and post-race samples after correction for multiple testing (12 decreased, 51 increased). The specific VOCs identified suggest the involvement of fatty acid oxidation, inflammation, and possible altered gut microbiome activity in response to exhaustive exercise. This study demonstrates significant changes in VOC abundance resulting from exhaustive exercise. Further investigation of VOC changes along with other physiological measurements can help improve our understanding of the effect of exhaustive exercise on the body and subsequent differences in VOCs in exhaled breath.

P Mochalski et al 2023 J. Breath Res. 17 037101

We summarize the history and review the literature on isoprene in exhaled breath and discuss the current evidence and models that describe its endogenous origin and consequence for understanding isoprene levels and their variations in exhaled breath.

Om Prakash Singh et al 2018 J. Breath Res. 12 026003

The development of a human respiration carbon dioxide (CO 2 ) measurement device to evaluate cardiorespiratory status inside and outside a hospital setting has proven to be a challenging area of research over the few last decades. Hence, we report a real-time, user operable CO 2 measurement device using an infrared CO 2 sensor (Arduino Mega2560) and a thin film transistor (TFT, 3.5''), incorporated with low pass (cut-off frequency, 10 Hz) and moving average (span, 8) filters. The proposed device measures features such as partial end-tidal carbon dioxide (EtCO 2 ), respiratory rate (RR), inspired carbon dioxide (ICO 2 ), and a newly proposed feature—Hjorth activity—that annotates data with the date and time from a real-time clock, and is stored onto a secure digital (SD) card. Further, it was tested on 22 healthy subjects and the performance (reliability, validity and relationship) of each feature was established using (1) an intraclass correlation coefficient (ICC), (2) standard error measurement (SEM), (3) smallest detectable difference (SDD), (4) Bland–Altman plot, and (5) Pearson's correlation ( r ). The SEM, SDD, and ICC values for inter- and intra-rater reliability were less than 5% and more than 0.8, respectively. Further, the Bland–Altman plot demonstrates that mean differences ± standard deviations for a set limit were 0.30 ± 0.77 mmHg, −0.34 ± 1.41 mmHg and 0.21 ± 0.64 breath per minute (bpm) for CO 2 , EtCO 2 and RR. The findings revealed that the developed device is highly reliable, providing valid measurements for CO 2 , EtCO 2 , ICO 2 and RR, and can be used in clinical settings for cardiorespiratory assessment. This research also demonstrates that EtCO 2 and RR ( r , −0.696) are negatively correlated while EtCO 2 and activity ( r , 0.846) are positively correlated. Thus, simultaneous measurement of these features may possibly assist physicians in understanding the subject's cardiopulmonary status. In future, the proposed device will be tested with asthmatic patients for use as an early screening tool outside a hospital setting.

Latest articles

Teny M John et al 2024 J. Breath Res. 18 026011

Clostridioides difficile infection (CDI) is the leading cause of hospital-acquired infective diarrhea. Current methods for diagnosing CDI have limitations; enzyme immunoassays for toxin have low sensitivity and Clostridioides difficile polymerase chain reaction cannot differentiate infection from colonization. An ideal diagnostic test that incorporates microbial factors, host factors, and host-microbe interaction might characterize true infection. Assessing volatile organic compounds (VOCs) in exhaled breath may be a useful test for identifying CDI. To identify a wide selection of VOCs in exhaled breath, we used thermal desorption-gas chromatography-mass spectrometry to study breath samples from 17 patients with CDI. Age- and sex-matched patients with diarrhea and negative C.difficile testing (no CDI) were used as controls. Of the 65 VOCs tested, 9 were used to build a quadratic discriminant model that showed a final cross-validated accuracy of 74%, a sensitivity of 71%, a specificity of 76%, and a receiver operating characteristic area under the curve of 0.72. If these findings are proven by larger studies, breath VOC analysis may be a helpful adjunctive diagnostic test for CDI.

Linda Mezmale et al 2024 J. Breath Res. 18 026010

Volatilomics is a powerful tool capable of providing novel biomarkers for the diagnosis of gastric cancer. The main objective of this study was to characterize the volatilomic signatures of gastric juice in order to identify potential alterations induced by gastric cancer. Gas chromatography with mass spectrometric detection, coupled with headspace solid phase microextraction as the pre-concentration technique, was used to identify volatile organic compounds (VOCs) released by gastric juice samples collected from 78 gastric cancer patients and two cohorts of controls (80 and 96 subjects) from four different locations (Latvia, Ukraine, Brazil, and Colombia). 1440 distinct compounds were identified in samples obtained from patients and 1422 in samples provided by controls. However, only 6% of the VOCs exhibited an incidence higher than 20%. Amongst the volatiles emitted, 18 showed differences in their headspace concentrations above gastric juice of cancer patients and controls. Ten of these (1-propanol, 2,3-butanedione, 2-pentanone, benzeneacetaldehyde, 3-methylbutanal, butylated hydroxytoluene, 2-pentyl-furan, 2-ethylhexanal, 2-methylpropanal and phenol) appeared at significantly higher levels in the headspace of the gastric juice samples obtained from patients; whereas, eight species showed lower abundance in patients than found in controls. Given that the difference in the volatilomic signatures can be explained by cancer-related changes in the activity of certain enzymes or pathways, the former set can be considered potential biomarkers for gastric cancer, which may assist in developing non-invasive breath tests for the diagnosis of this disease. Further studies are required to elucidate further the mechanisms that underlie the changes in the volatilomic profile as a result of gastric cancer.

Robert van Vorstenbosch et al 2024 J. Breath Res. 18 026007

Disease detection and monitoring using volatile organic compounds (VOCs) is becoming increasingly popular. For a variety of (gastrointestinal) diseases the microbiome should be considered. As its output is to large extent volatile, faecal volatilomics carries great potential. One technical limitation is that current faecal headspace analysis requires specialized instrumentation which is costly and typically does not work in harmony with thermal desorption units often utilized in e.g. exhaled breath studies. This lack of harmonization hinders uptake of such analyses by the Volatilomics community. Therefore, this study optimized and compared two recently harmonized faecal headspace sampling platforms: High-capacity Sorptive extraction (HiSorb) probes and the Microchamber thermal extractor (Microchamber) . Statistical design of experiment was applied to find optimal sampling conditions by maximizing reproducibility, the number of VOCs detected, and between subject variation. To foster general applicability those factors were defined using semi-targeted as well as untargeted metabolic profiles. HiSorb probes were found to result in a faster sampling procedure, higher number of detected VOCs, and higher stability. The headspace collection using the Microchamber resulted in a lower number of detected VOCs, longer sampling times and decreased stability despite a smaller number of interfering VOCs and no background signals. Based on the observed profiles, recommendations are provided on pre-processing and study design when using either one of both platforms. Both can be used to perform faecal headspace collection, but altogether HiSorb is recommended.

Review articles

Manoj Khokhar 2024 J. Breath Res. 18 024001

Breath biomarkers are substances found in exhaled breath that can be used for non-invasive diagnosis and monitoring of medical conditions, including kidney disease. Detection techniques include mass spectrometry (MS), gas chromatography (GC), and electrochemical sensors. Biosensors, such as GC-MS or electronic nose (e-nose) devices, can be used to detect volatile organic compounds (VOCs) in exhaled breath associated with metabolic changes in the body, including the kidneys. E-nose devices could provide an early indication of potential kidney problems through the detection of VOCs associated with kidney dysfunction. This review discusses the sources of breath biomarkers for monitoring renal disease during dialysis and different biosensor approaches for detecting exhaled breath biomarkers. The future of using various types of biosensor-based real-time breathing diagnosis for renal failure is also discussed.

Glívia Maria Barros Delmondes et al 2024 J. Breath Res. 18 014001

Pulmonary function is usually assessed by measuring Vital Capacity (VC) using equipment such as a spirometer or ventilometer, but these are not always available to the population, as they are relatively expensive tests, difficult to transport and require trained professionals. However, the single breath counting technique (SBCT) appears as a possible alternative to respiratory function tests, to help in the pathophysiological understanding of lung diseases. The objective is to verify the applicability of the SBCT as a parameter for evaluating VC. This is a systematic review registered in the International Prospective Register of Systematic Reviews (CRD42023383706) and used for PubMed ® , Scientific Electronic Library Online, LILACS, EMBASE, and Web of Science databases of articles published until January 2023. Methodological quality regarding the risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 and National Institutes of Health tools. Eleven of a total of 574 studies were included, of these, nine showed a correlation between VC and SBCT (weak in healthy, moderate in neuromuscular and strong in hospitalized patients). One study of hospitalized patients accurately identified a count value of 21 for a VC of 20 ml kg −1 (Sensitivity = 94% and Specificity = 77%), and another estimated a count lower than 41 for a VC below 80% of predicted in patients with neuromuscular dystrophy (Sensitivity = 89% and Specificity = 62%), and another showed good intra and inter-examiner reproducibility in young, adult, and elderly populations. A meta-analysis of three studies showed a moderate correlation in subjects with neuromuscular diseases ( r = 0.62, 95% CI = 0.52–0.71, p < 0.01). A high risk of bias was identified regarding the justification of the sample size and blinding of the evaluators. SBCT has been presented as an alternative to assess VC in the absence of specific equipment. There is a clear relationship between SBCT and VC, especially in neuromuscular and hospitalized individuals. New validation studies conducted with greater control of potential bias risks are necessary.

Veronika Ruzsányi and Miklós Péter Kalapos 2023 J. Breath Res. 17 044001

Owing to its connection to cancer metabolism, lactate is a compound that has been a focus of interest in field of cancer biochemistry for more than a century. Exhaled breath volatile organic compounds (VOCs) and condensate analyses can identify and monitor volatile and non-VOCs, respectively, present in exhaled breath to gain information about the health state of an individual. This work aims to take into account the possible use of breath lactate measurements in tumor diagnosis and treatment control, to discuss technical barriers to measurement, and to evaluate directions for the future improvement of this technique. The use of exhaled breath condensate (EBC) lactic acid levels in disorders other than cancer is also discussed in brief. Whilst the use of EBC for the detection of lactate in exhaled breath is a promising tool that could be used to monitor and screen for cancer, the reliability and sensitivity of detection are uncertain, and hence its value in clinical practice is still limited. Currently, lactate present in plasma and EBC can only be used as a biomarker for advanced cancer, and therefore it presently has limited differential diagnostic importance and is rather of prognostic value.

Haripriya P et al 2023 J. Breath Res. 17 024001

Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.

Accepted manuscripts

Eichinger et al 

We explored appropriate technical setups for the detection of volatile organic compounds (VOCs) from exhaled cow breath by comparing six different polymer-based solid-phase extraction (SPE) cartridges currently on the market for GC-MS screening. Exhaled breath was sampled at a single timepoint from five lactating dairy cows using six different SPE cartridges (Bond Elut ENV; Chromabond HRX; Chromabond HRP; Chromabond HLB; Chromabond HR-XCW and Chromabond HR-XAW). The trapped VOCs were analyzed by Dynamic Headspace Vacuum In-Tube Extraction gas chromatography/mass spectrometry (DHS-V-ITEX-GC-MS). Depending on the SPE cartridge, we detected 1174 to 1312 VOCs per cartridge. Most VOCs were alkenes, alkanes, esters, ketones, alcohols, aldehydes, amines, nitriles, ethers, amides, carboxylic acids, alkynes, azoles, terpenes, pyridines, or sulfur-containing compounds. The six SPE cartridges differed in their specificity for the chemical compounds, with the XAW cartridge showing the best specificity for ketones. The greatest differences between the tested SPE cartridges appeared in the detection of specific VOCs. In total, 176 different VOCs were detected with a match factor >80%. The greatest number of specific VOCs was captured by XAW (149), followed by ENV (118), HLB (117), HRP (115), HRX (114), and XCW (114)). We conclude that the tested SPE cartridges are suitable for VOC sampling from exhaled cow breath, but the SPE cartridge choice enormously affects the detected chemical groups and the number of detected VOCs. Therefore, an appropriate SPE adsorbent cartridge should be selected according to our proposed inclusion criteria. For targeted metabolomics approaches, the SPE cartridge choice depends on the VOCs or chemical compound groups of interest based on our provided VOC list. For untargeted approaches without information on the animals' metabolic condition, we suggest using multi-sorbent SPE cartridges or multiple cartridges per animal.

Open access

Julia Eichinger et al 2024 J. Breath Res.

Xiaoxiao Li et al 2024 J. Breath Res. 18 026004

The correlation between propofol concentration in exhaled breath ( C E ) and plasma ( C P ) has been well-established, but its applicability for estimating the concentration in brain tissues ( C B ) remains unknown. Given the impracticality of directly sampling human brain tissues, rats are commonly used as a pharmacokinetic model due to their similar drug-metabolizing processes to humans. In this study, we measured C E , C P , and C B in mechanically ventilated rats injected with propofol. Exhaled breath samples from the rats were collected every 20 s and analyzed using our team's developed vacuum ultraviolet time-of-flight mass spectrometry. Additionally, femoral artery blood samples and brain tissue samples at different time points were collected and measured using high-performance liquid chromatography mass spectrometry. The results demonstrated that propofol concentration in exhaled breath exhibited stronger correlations with that in brain tissues compared to plasma levels, suggesting its potential suitability for reflecting anesthetic action sites' concentrations and anesthesia titration. Our study provides valuable animal data supporting future clinical applications.

Zachary Joseph Sasiene et al 2024 J. Breath Res. 18 026003

The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human 'profile' against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant ( p < 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

Hannah Schanzmann et al 2024 J. Breath Res. 18 016009

Exhaled breath analysis is evolving into an increasingly important non-invasive diagnostic tool. Volatile organic compounds (VOCs) in breath contain information about health status and are promising biomarkers for several diseases, including respiratory infections caused by bacteria. To monitor the composition of VOCs in breath or the emission of VOCs from bacteria, sensitive analytical techniques are required. Next to mass spectrometry, ion mobility spectrometry (IMS) is considered a promising analytical tool for detecting gaseous analytes in the parts per billion by volume to parts per trillion by volume range. This work presents a new, dual coupling of thermal desorption gas chromatography to a quadrupole mass spectrometer (MS) and an IMS by operating a simple splitter. Nearly identical retention times can be reached in the range of up to 30 min with slight deviations of 0.06 min–0.24 min. This enables the identification of unknown compounds in the IMS chromatogram using unambiguous mass spectral identification, as there are still no commercially available databases for IMS. It is also possible to discriminate one of the detectors using the splitter to improve detection limits. Using a test liquid mixture of seven ketones, namely 2-butanone, 2-pentanone, 2-hexanone, 2-heptanone, 2-octanone, 2-nonanone, and 2-decanone with a concentration of 0.01 g l −1 reproducibilities ranging from 3.0% to 7.6% for MS and 2.2%–5.3%, for IMS were obtained, respectively. In order to test the system optimized here for the field of breath analysis, characteristic VOCs such as ethanol, isoprene, acetone, 2-propanol, and 1-propanol were successfully identified in exhaled air using the dual detector system due to the match of the corresponding IMS, and MS spectra. The presented results may be considered to be a starting point for the greater use of IMS in combination with MS within the medical field.

Anne E Jung et al 2024 J. Breath Res. 18 016008

Due to the overall low abundance of volatile compounds in exhaled breath, it is necessary to preconcentrate the sample prior to traditional thermal desorption (TD) gas chromatography mass spectrometry analysis. While certain aspects of TD tubes, such as volatile storage, have been evaluated, many aspects remain uncharacterized. Two common TD tubes, Tenax TA and Biomonitoring 5TD tubes, were evaluated for background content and flow rate variability. The data illustrate that the Biomonitoring 5TD tubes have the highest number (23) and abundance of background contamination greater than 3x the mean noise when compared to Tenax TA (13) and empty tubes (9). Tentative identifications of the compounds in the background contamination experiment show that greater than 59% (16/27) of the compounds identified have been reported in the breath literature. The data illustrate the TD tube background abundance could account for more than 70% of the chromatographic signal from exhaled breath for these select compounds. Flow rate measurements of 200 Tenax TA and 200 Biomonitoring 5TD tubes show a large range in measured flow rates among the TD tubes (Tenax: 252.9–284.0 ml min −1 , 5TD: 220.6–255.1 ml min −1 ). Finally, TD tubes of each type, Tenax TA and Biomonitoring 5TD, previously established to have high, medium, and low flow rates, show insignificant differences ( p > 0.05) among the tubes of different flow rates, using both gas standards and an exhaled breath from a peppermint experiment. Collectively, these results establish overall background compounds attributed to each TD tube type tested. Additionally, while measured flow rate variability is present and plausibly impacts exhaled breath results, the data demonstrate no statistically significant difference was observed between tubes showing high, medium, and low flow rates from two separate sample types.

Rosa A Sola-Martínez et al 2024 J. Breath Res. 18 011002

Secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) is an established technique in the field of breath analysis characterized by its short analysis time, as well as high levels of sensitivity and selectivity. Traditionally, SESI-HRMS has been used for real-time breath analysis, which requires subjects to be at the location of the analytical platform. Therefore, it limits the possibilities for an introduction of this methodology in day-to-day clinical practice. However, recent methodological developments have shown feasibility on the remote sampling of exhaled breath in Nalophan® bags prior to measurement using SESI-HRMS. To further explore the range of applications of this method, we conducted a proof-of-concept study to assess the impact of the storage time of exhaled breath in Nalophan® bags at different temperatures (room temperature and dry ice) on the relative intensities of the compounds. In addition, we performed a detailed study of the storage effect of 27 aldehydes related to oxidative stress. After 2 h of storage, the mean of intensity of all m/z signals relative to the samples analyzed without prior storage remained above 80% at both room temperature and dry ice. For the 27 aldehydes, the mean relative intensity losses were lower than 20% at 24 h of storage, remaining practically stable since the first hour of storage following sample collection. Furthermore, the mean relative intensity of most aldehydes in samples stored at room temperature was higher than those stored in dry ice, which could be related to water vapor condensation issues. These findings indicate that the exhaled breath samples could be preserved for hours with a low percentage of mean relative intensity loss, thereby allowing more flexibility in the logistics of off-line SESI-HRMS studies.

Nils Oskar Jõgi et al 2024 J. Breath Res. 18 011001

Primary ciliary dyskinesia (PCD) is a genetic respiratory disease characterized by chronic cough, recurrent respiratory infections, and rhinosinusitis. The measurement of nasal nitric oxide (nNO) against resistance has been suggested as a sensitive screening method. However, current recommendations argue for the use of expensive, chemiluminescence devices to measure nNO. This study aimed to compare nNO measurement using three different devices in distinguishing PCD patients from healthy controls and cystic fibrosis (CF) patients and to evaluate their diagnostic precision. The study included 16 controls, 16 PCD patients, and 12 CF patients matched for age and sex. nNO measurements were performed using a chemiluminescence device (Eco Medics CLD 88sp), and two devices based on electrochemical sensors (Medisoft FeNO+ and NIOX Vero) following standardized guidelines. Correlation estimation, Bland–Altman, ROC curve, and one-way ANOVA were used to assess device differences and diagnostic performance. Significantly lower nNO output values were observed in PCD and CF patients compared to controls during exhalation against resistance. The correlation analysis showed high agreement among the three devices. ROC curve analysis demonstrated 100% sensitivity and specificity at different cut-off values for all devices in distinguishing PCD patients from controls (optimal cut-offs: EcoMedics 73, Medisoft 92 and NIOX 87 (nl min −1 )). Higher nNO output values were obtained with the Medisoft and NIOX devices as compared to the EcoMedics device, with a bias of−19 nl min −1 (95% CI: −73–35) and −21 nl min −1 (−73–31) accordingly. These findings indicate that all three tested devices can potentially serve as diagnostic tools for PCD if device specific cut-off values are used. This last-mentioned aspect warrants further studies and consideration in defining optimal cut-offs for individual device.

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• 2007-present Journal of Breath Research doi: 10.1088/issn.1752-7163 Online ISSN: 1752-7163 Print ISSN: 1752-7155

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• Published: 23 January 2023

Wearable breath analysis

• H. Ceren Ates   ORCID: orcid.org/0000-0001-7882-4745 1 , 2 &
• Can Dincer   ORCID: orcid.org/0000-0003-3301-1198 1 , 2  

Nature Reviews Bioengineering volume  1 ,  pages 80–82 ( 2023 ) Cite this article

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• Bionanoelectronics
• Diagnostic devices
• Lab-on-a-chip
• Nanoparticles
• Sensors and biosensors

Biomarkers in breath can be related to certain diseases, which makes breath-based analysis a powerful diagnostic tool. Here we highlight milestones and remaining challenges for the broad clinical implementation of wearables for breath analysis.

Breath was first analysed by chromatography in the 1970s, demonstrating the presence of organic substances in exhaled breath. Since then, more than 3,000 volatile organic components (VOCs) have been identified in breath, which could be explored in medical applications 1 , 2 . However, except for breath analysers that measure alcohol levels, only few sensing devices have reached high technology readiness levels 2 , and diagnostic application has been limited to chromatographic laboratory tests. Advances in material science, synthetic biology and engineering, in combination with an increase in interest in the diagnostics of infectious diseases from exhaled breath, have recently pushed the popularity of breath analysis.

Breath analysis as diagnostic tool

Breath analysis can be broadly interpreted as a two-step process: verifying the presence of diagnostic breath markers, and establishing a method of their detection. The identification of specific VOCs that are related to certain diseases or metabolic activities in so-called ‘breath prints’ has been established by clinical trials. Thus, breath analysis can be used as a non-invasive, qualitative diagnostic tool 2 . Although there is still no full consensus on how to interpret the measured biomarker levels to identify their association with diseases, inference of targeted concentrations in breath is not out of reach. Breath sampling offers a unique advantage compared to other non-invasive sampling methods, because the transportation of analytes from blood into the lungs bypasses complex transport mechanisms 2 . For example, the transportation of secreted molecules into the saliva and sweat depends on their dissociation constant, lipophilicity, pH, protein-binding affinity and ionizability, and thus can be much more complex than capillary diffusion through lung alveoli. Recent studies demonstrated a good correlation between antibiotic levels in exhaled breath condensates and blood, underlining this hypothesis 3 .

Wearable breath sensors

The transition from laboratory-based measurement techniques to wearable biosensors is necessary to accelerate the translation of breath analysis. The former relies on the collection of a breath snapshot, typically in the form of an exhaled breath condensate, which is then analyzed by chromatographic and/or spectroscopic methods. However, these methods are limited by a lack of standardization in workflows, long turnaround times, high instrumentation costs and complex sample preparation. Alternatively, wearable sensors offer simultaneous sample collection and analysis. Wearables allow the collection of breath over a long period of time, providing real-time sampling and analysis, instead of a snapshot. In addition, biomarkers can be concentrated for the detection of small amounts, and differential physiological changes can be detected from an individual baseline.

Wearables in the form of face masks have been tested for the detection of hydrogen peroxide (a biomarker for several respiratory illnesses, such as asthma, chronic obstructive pulmonary disease and lung cancer) by electrochemical sensing 4 , and for breath-condition monitoring (for example, respiration rate, cough and breath holding) by the integration of a self-powered pressure sensor 5 . The COVID-19 pandemic has further brought breath analysis to the front line as a method for detecting airborne-transmitted infectious diseases from virus-containing aerosols. For example, face masks with a lyophilized CRISPR sensor can detect nucleic acids of SARS-CoV-2 using conventional lateral flow assays 6 , and an optical sniffer (colourimetric sensor array) can provide semi-quantitative analysis of COVID-19 severity (from very mild to severe) by using the relationship between colour patterns and the medical reports of patients, together with real-time polymerase chain reaction (RT-PCR) results 7 .

Sensitivity

To realize the clinical potential of wearable breath analysis, several challenges need to be addressed. A variety of breath analytes (around 3,500) have been identified, including exogenous markers that are not physiologically produced; however, they typically occur at very low concentrations in breath (1,000–10,000 times lower than in blood) 2 , 8 , depending on age, diet, smoking and medication, as well as the expiratory flow rate. Therefore, the sensitivity of wearable breath analysers has to be high to enable the detection of breath analytes. Concentrating target molecules is necessary, either on the wearable device or at the source (such as the lung and/or respiratory tract).

In wearable devices, breath can be segregated within a microfluidic system as a pre-concentration step (for example, μ-gas chromatography). In addition, the sensing element can be improved with synthetic biology-based bioassays (such as CRISPR–Cas-based systems, microbial enzymes and proteins) to augment sensitivity, or nanostructures can be implemented to increase the effective sensing area. Target molecules can also be concentrated at the source by stimulating metabolic activity; for example, volatile markers can be released in response to protease activity 9 . Alternatively, exogenous biomarkers can be expressed at the source through the exploitation of metabolic activities associated with a condition, such as lung cancer, or through the application of engineered living organisms 9 . For example, genetically engineered synthetic biomarkers can be designed that are specific for tumour-associated gene expression or dysregulated activities through the implementation of tumour-specific promoters that encode secretable reporters that are transcriptionally targeted to cancer cells 9 . Analyte reactivity can also be increased by chemical pre-treatment or through the formation of analyte–nanoparticle conjugates.

Selectivity

To measure specific analytes in a mixture of substances with similar chemical and/or physical properties, an antithetical design approach can be followed. The bottom-up approach aims for absolute selectivity and starts with the selection of a well-defined target (bio)marker. The sensing technology is designed around that particular compound in an idealized lab environment. Measurement complexities owing to the analyte (the number of interfering substances with similar chemical properties) and environmental factors (for example, temperature and humidity effects can be subtracted by the addition of a blank as a reference system) are systematically increased to improve the generalizability of the measurement technique. The interaction strength between the target and receptor should be optimized to allow sensor replenishment for continuous measurement 8 . Synthetic breath biomarkers can help to improve the signal-to-noise ratio and enable optimization of analyte capture–release cycles for sensor regeneration. Similarly, synthetic biology-empowered bioreceptors (such as molecularly imprinted polymers or aptamers) enable controlled analyte capture and release (by changing surface charge, temperature or pH) and, thus, continuous monitoring 2 .

In the top-down approach, an array of sensors is used to increase selectivity. Such sensing units need to be robust and apply a range of chemical interactions to capture different combinations of potentially informative compounds. The interpretation of results then relies on similarities or dissimilarities across measurements. Therefore, a large amount of data must be compiled and processed with the assistance of pattern-extraction models 1 to correlate the physiological status with the sensory fingerprint. However, the same subset of sensors can be stimulated by different analyte combinations, which makes it difficult to correlate patterns with certain conditions. Therefore, sensory patterns associated with certain health conditions could be observed even in the absence of physiologically relevant biomarkers. This dilemma can be overcome by equilibrating the complexity between the sensory problem, hardware and model architecture. Breath has a rich chemical composition of analytes, and a priori prediction of the relevant subset of analytes remains challenging. Therefore, multiarray sensing technology should be complex enough to respond to the variances in composition. The only known sensing unit that reflects such complexity are olfactory receptors, which could be incorporated into biohybrid sensors of wearable breath analysers 10 . Furthermore, the data must be processed with black-box models of similar complexity, such as deep-learning methods 1 , which can be trained only with large volumes of data.

The composition of breath is strongly influenced by the sample-collection method, which has not yet been standardized. The relative ratio of analytes changes with the selection of the breath portion (late or end-tidal breath), breathing patterns, sample contamination (for example, with saliva), mode of sample collection (on-line continuous or off-line discrete) and phase of the sample (vapour (gaseous) or condensate) 8 . Thus, end-to-end wearable design studies should select a sample-collection strategy that allows continuous access to the physiological state. For example, disposable face masks could integrate sampling, sample preparation (if required) and sensing modules. Alternatively, under or in-nose patches, or implants mounted to the respiratory tract (possibly self-powered using metabolites, such as lactate or glucose) could be applied. Sensor-integrated vaping devices could enable closed-loop drug delivery for theranostic applications (Fig.  1 ).

Robust analysis can be achieved through the use of face masks integrated with sampling, sample preparation (if required) and sensing modules, in- or under-nose patches, in-trachea patches and vaping devices.

Ethical considerations

Ethical considerations related to wearable breath analysis include patient data collection, patient safety, liability, legal responsibility, user compliance, accessibility and equity, which need to be accounted for in the design and clinical application of wearable breath sensors 1 , 8 . Liability and patient safety are special concerns for wearables for theragnostic applications. Legal responsibility arises from the integration of patient data into data pipelines, and error or bias in the selection of model and training databases, which in turn determines the contribution of wearable output to the final diagnostic judgement. In addition, misuse of the device and lack of software updates, considering programming languages, libraries and medical cues of certain diseases, lead to liability concerns 1 , 8 .

By addressing the remaining technological and ethical challenges, wearable breath analysis could become a complementary tool for distributed, preventive healthcare monitoring and transform our understanding of diagnostics.

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Acknowledgements

The authors would like to acknowledge Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) for funding this work (grant numbers 404478562 and 446617142) and also thank N. Brasier for insightful discussions.

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Smelling the Disease: Diagnostic Potential of Breath Analysis

• Review Article
• Published: 02 February 2023
• Volume 27 , pages 321–347, ( 2023 )

Cite this article

• Anju Sharma 1 ,
• Rajnish Kumar 2 &
• Pritish Varadwaj 1  

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Breath analysis is a relatively recent field of research with much promise in scientific and clinical studies. Breath contains endogenously produced volatile organic components (VOCs) resulting from metabolites of ingested precursors, gut and air-passage bacteria, environmental contacts, etc. Numerous recent studies have suggested changes in breath composition during the course of many diseases, and breath analysis may lead to the diagnosis of such diseases. Therefore, it is important to identify the disease-specific variations in the concentration of breath to diagnose the diseases. In this review, we explore methods that are used to detect VOCs in laboratory settings, VOC constituents in exhaled air and other body fluids (e.g., sweat, saliva, skin, urine, blood, fecal matter, vaginal secretions, etc.), VOC identification in various diseases, and recently developed electronic (E)-nose-based sensors to detect VOCs. Identifying such VOCs and applying them as disease-specific biomarkers to obtain accurate, reproducible, and fast disease diagnosis could serve as an alternative to traditional invasive diagnosis methods. However, the success of VOC-based identification of diseases is limited to laboratory settings. Large-scale clinical data are warranted for establishing the robustness of disease diagnosis. Also, to identify specific VOCs associated with illness states, extensive clinical trials must be performed using both analytical instruments and electronic noses equipped with stable and precise sensors.

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1 Introduction

Breath analysis is a young field of research with much promise in scientific and clinical studies.

During breathing, the inhaled gas molecules diffuse from the alveolar region and are dissolved into the bloodstream. Gas molecules are then taken up by tissues through a simple physical dissolution process, which allows them to be partitioned between the air and blood during absorption and between the blood and other tissues during distribution. A chemical remains long enough in the alveoli to attain equilibrium with the blood [ 1 ], i.e., equilibrium wherein the ratio of chemical concentration in the blood to that in the gas phase remains constant. This relatively fast equilibrium between alveolar air and pulmonary capillary blood is the basis for breath analysis [ 2 ]. The number of volatile organic compounds (VOCs) exhaled through the lungs varies in direct proportion to their blood concentrations and vapor pressure and is indirectly proportional to their absorption by the lungs [ 3 ]. Hence, a single breath contains hundreds of different volatile compounds that represent distinct and instant changes because of various pathophysiological processes that alter an individual's metabolic state and provide vital proof of important biochemical changes in the body. These VOCs, both odorous and odorless, are produced by metabolites in the airways and gut, metabolites of ingested precursors, or after environmental exposure. VOCs in exhaled breath include both exogenous and endogenous chemicals [ 4 , 5 , 6 ]. Compounds inhaled or absorbed from the environment and derived from smoking cigarettes are all examples of exogenous volatiles [ 7 ]. Compounds released during cellular biochemical processes or physiological processes in the body and generated by all types of symbiotic bacteria/microbial pathogens/commensals or produced in response to microbial infections are all examples of endogenous volatiles [ 7 , 8 ]. Additionally, the VOC concentrations in breath range from nanomolar to picomolar; thus, distinguishing contaminated environment exogenous compounds from normally produced VOCs is always difficult. Metabolically produced VOCs are often secreted into blood and eventually emitted via breath and/or sweat. Age, sex, physiological status, genetic makeup, and diet all influence the amount of VOCs released. Thus, VOCs might be considered unique “odor fingerprints” [ 3 , 5 , 6 ]. When a person contracts an infectious or metabolic disease, their odor fingerprints change due to the production of new VOCs or a variation in the ratio of VOCs that are normally produced. As a result, their breath and body odor changes. For example, breath in the case of some prominent diseases smells differently, for example, the ‘fruity smell’ of acetone in diabetes, “musty and fishy smell” in advanced hepatic disease, ‘urine-like smell’ in severe kidney disease and “putrid smell” in lung abscess [ 9 , 10 ]. Therefore, the measurement of VOCs in exhaled breath might thus reveal important information on the pathophysiological state of the participants. These molecules can serve as indicators and potential biomarkers for a variety of diseases and metabolic activities, making disease detection easier.

The first attempts to use breath analysis to determine a person's physiological state date back to Hippocrates' (460–370 BC) time, when ancient Greek physicians realized that human breath provides useful information on an individual’s health and that the odor of a patient's breath could be used to diagnose some diseases [ 1 , 11 , 12 , 13 , 14 , 15 , 16 ]. Lavoisier investigated the breath CO 2 of guinea pigs for the first time in 1782–1783, and demonstrated that exhaled breath is a result of combustion in the body [ 11 , 15 ]. Nobel Laureate Linus Pauling is considered the forerunner in the field of breath analysis [ 17 ]. He identified 30 different peaks in the gas chromatogram that indicated the presence of various volatile compounds in the exhaled breath, most of them at very low concentrations (parts per billion (ppb) or parts per trillion (ppt)). Later, Phillips et al. revealed 3,481 VOCs in healthy controls' exhaled air, with an average of approximately 200 VOCs identifiable in each person's breath using gas chromatography‒mass spectrometry (GC/MS) [ 5 ]. The first comprehensive review on breath analysis was published by Manolis et al. [ 4 ], which discussed the presence of VOCs in exhaled breath, followed by a plethora of studies [ 18 , 19 , 20 ]. A recent review published by Drabinska et al. reported 4,412 VOCs found in healthy human breath and other bodily fluids (including 1,488 in breath, 623 in skin, 549 in saliva, 444 in urine, 443 in faeces, 379 in blood, 290 in milk and 196 in semen) for better understanding of the metabolic pathways involved in VOCs production and might be helpful in distinguishing diseases [ 21 ].

Another reason for which exhaled breath analysis and related VOCs are receiving much attention in the scientific, clinical, and research communities is because of their ability to examine biochemical processes in the human body in real time without being invasive, and they can also be carried out often under any circumstances, such as during surgery or in intensive care units [ 13 , 18 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 ]. Unlike blood and urine, breath samples have the advantage of having an unlimited supply of samples, which might be collected in time frames as little as seconds and on demand for as long as needed. As a result, changes in VOC absorption, metabolism, and excretion can be detected. In comparison to traditional approaches, which are expensive, invasive and time-consuming methods to diagnose various diseases that typically require trained and qualified specialists, clinical applications of breath analysis are non-invasive, less time consuming, consistent and safe.

Since clinicians are now aware of disease-specific (infectious, metabolic, cancers) and genetic disorder-specific odors, VOC profiles could be employed as olfactory biomarkers for fatal diseases and disorder identification [ 33 , 34 ]. The understanding of the pathophysiological mechanisms that govern the generation of disease-specific VOCs could lead to new therapeutic approaches for a variety of disorders. From this perspective, various attempts have been made to identify detectible volatile biomarkers that can assist in the diagnosis and classification of diseases [ 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. Some of the VOCs that may be present in the breath are oxygen-containing compounds (acetone, methanol, ethanol, etc.) [ 42 , 43 , 44 , 45 ], hydrocarbons (ethane, pentane, isoprene, etc.) [ 46 , 47 , 48 ], sulfur-containing compounds (ethyl mercaptane, dimethyl sulfide, dimethyl disulfide, etc.) [ 49 , 50 , 51 ] and nitrogen containing compounds (ammonia, dimethylamine, trimethylamine, etc.) [ 52 ]. Identifying such VOCs and applying them as disease-specific biomarkers to obtain accurate, reproducible and fast disease diagnosis could serve as an alternative to traditional invasive diagnosis methods. Therefore, breath analysis might be further expanded, not just to detect disease but also to provide a more precise determination of stage, which could help healthcare professionals understand the pathogenesis and etiology to support therapy [ 53 ].

The goal of this article is to summarise the potential uses of exhaled breath analysis as a non-invasive approach of disease detection. It covers types of VOCs observed from breath, techniques used to identify VOCs in laboratory settings and using electronic (E)-nose, disease-specific VOCs particularly in exhaled breath, as well as a brief glance at disease-specific VOCs produced by other body fluids and the future of olfaction-based diagnosis. The study summarizes 144 studies that used breath analysis and 21 studies based on other body fluids to investigate and identify disease-specific VOCs by evaluating the exhaled breath of patients and healthy individuals. The identification of disease-specific VOCs offers a tremendous potential in disease detection at various stages; however, the usefulness of these biomarkers for disease screening needs to be confirmed in large-scale studies carried out in actual screening settings.

2 Methodology

An extensive literature search in PubMed, Web of Science, MEDLINE, and SCISEARCH databases was carried out using following keywords: ((exhaled breath analysis OR VOCs OR breath) AND (diseases OR diagnosis OR cancer OR carcinoma OR neurodegenerative disorders OR diabetes OR heart disease OR lung diseases)), ((volatile compounds OR organic compounds OR exhaled compounds) AND (diseases OR disorders)), ((exhaled breath analysis AND sensors) OR disease detection). Duplicate studies and non-English studies were eliminated from a total of 1,638 studies. The remaining titles and abstracts were checked and studies not relevant to the topic were excluded along with papers for which no full-text could be accessed. The titles and abstracts of the remaining papers were examined and studies that were unrelated to the subject and publications for which there was no full-text available were both eliminated. In total, 144 studies matched our inclusion criteria, and their findings are described in this review. The majority of them focused on VOCs determined in cancer patient’s exhaled breath, highlighting the fact that exhaled breath has the greatest potential for diagnosing cancers. Other diseases also investigated with breath analysis included: heart diseases, lung diseases, liver diseases, gastric-related diseases, renal diseases, neurodegenerative disorders, toxicity, etc. The study also summarizes the findings of 21 studies that examined VOCs found in patients' and healthy individual's other bodily fluids.

3 Techniques for Exhaled Breath Volatile Organic Compound Analysis

Exhaled breath analysis has the potential to be useful in a wide range of diagnostic studies. This necessitates a detector with high sensitivity and accurate selectivity that can detect many VOCs in ultralow concentrations in exhaled breath samples for qualitative and quantitative analysis [ 54 ]. VOCs in exhaled breath can be detected using a variety of analytical techniques (Fig. 1 ). Gas chromatography (GC) and GC/MS methods were initially employed for separating and identifying VOCs in exhaled breath and included both exogenous and endogenous chemicals [ 4 , 5 , 6 ]. In the 1990s, a GC/MS-olfactometer (GC/MS-O) was developed, which allowed researchers to detect and analyze the mass spectra and odor characteristics of individual GC-separated odorants that are present in low concentrations in complex mixes of VOCs [ 55 ]. Electron impact ionization techniques are used in GC/MS, where each analyte molecule’s unique fragmentation pattern is used for its identification, which is accomplished using chromatographic retention data and mass spectral data obtained from spectral libraries [ 56 ]. These methods can identify VOCs at concentrations as low as ppb or even ppt, and they can determine and identify many chemicals at once [ 57 , 58 ]. Despite its many benefits (high sensitivity), GC frequently yields unreliable results, especially when many compounds are present in trace amounts. Additionally, even though it is now possible to carry out GC/MS for sufficiently short run times for ‘real-time’ analysis, they still require expensive instruments and complicated sample preparation, have poor portability and require trained personnel for their operation.

Volatile organic compounds (VOCs) from breath to clinical diagnosis and disease identification

During the second half of the twentieth century, advanced analytical techniques for breath analysis were also developed, such as laser spectrometry [ 59 ], proton-transfer reaction time-of-flight mass spectrometry (PTR-TOFMS) [ 60 ], ion mobility spectrometry (IMS) [ 61 ], and selected ion flow tube mass spectrometry (SIFT-MS) [ 62 ]. PTR-TOFMS characterize analytes as per their mass-to-charge (m/z) ratio, where TOF analyzers separate ions based on variations in their velocities after being accelerated by a constant potential. PTR-TOFMS comprises an ion source, a drift tube and an MS detector. At the top of the drift tube, a sample of flowing air is mixed with H3O+ produced in the ion source section, and proton transfer occurs as the gas sample travels through the tube [ 63 ]. PTR-MS is faster and more accurate than GC-MS for detecting VOC concentrations (ppt and ppb levels) [ 64 , 65 , 66 ], and it does not involve the time-consuming preconcentration phase. PTR-MS, however, is unable to distinguish between compounds with the same molecular mass [ 64 ]. SIFT-MS, a potential tool for real-time quantification of gases, employs a chemical ionization technique using reactant ions (H 3 O + , NO + , O 2 ) generated in an ion source. In SIFT-MS each species present in the sample is represented by distinctive productions created by ion-molecule reactions in SIFT-MS and a downstream detection system mass sorts and counts these product ions; thus, mass spectra consist of only molecular ions of VOCs, hence obviating the need for separate chromatographic experimentation [ 67 , 68 , 69 , 70 , 71 , 72 ]. Like PTR-MS, SIFT-MS outperforms GC-MS in terms of the identification and analysis of small molecules and can detect several VOCs at low concentrations (ppt/pptv and ppb/ppbv levels) [ 56 , 65 ]. IMS detects and measure disease-specific combinations of VOCs by quantifying the time it takes for an ion to travel through a drift tube [ 65 ]. It is a rapid approach that can detect VOCs at ppm (parts per million) − ppb levels, and has been used to identify various bacteria and metabolites in human breath [ 7 , 61 ]. IMS suffers from its inability to identify unknown volatile compounds in a sample [ 73 ]. IMS, PTR-TOFMS and SIFT-MS are usually operated with a multicapillary column (MCC) [ 22 , 61 , 74 ] to separate chemical isomers having the same mass-to-charge ratios. Optical or laser absorption spectroscopy-based methods have recently experienced a surge in gas detection [ 75 , 76 , 77 ]. They are extremely selective, low-cost and portable, and carry out ppb-level and online real-time analysis of VOCs. The method detects VOCs based on the intensity or displacement change of the absorption spectrum of the gas-sensitive material (pH indicators, metalloporphyrins, etc.) once the gas is absorbed. Laser spectrometry was found to selectively identify carbon monoxide [ 78 ] or ethane [ 79 ]. After the development of mid-infrared light laser sources such as the quantum cascade laser (QCL), Manne et al. [ 69 , 80 ] employed the cavity ring-down spectroscopy (CRDS) approach to quantify ammonia (NH 3 ) in exhaled breath. A recent and the most promising technique for real-time trace gas detection, cavity-enhanced absorption spectroscopy (CEAS) is based on spectral distribution and line shape theories, which can detect gaseous components in low concentrations with high sensitivity and accurately identify them even in the presence of other interfering gases. The CEAS employs an optical frequency comb (OFC), a light source developed by the Ye group, to simultaneously detect several components [ 54 , 81 ]. Once a specific molecule linked with the disease has been identified, optical absorption can be used to diagnose the disease. This approach is highly selective and can be utilized to perform real-time on-line analysis of a specific molecule down to the ppb level [ 65 ]. The limitations of the approach are the use of expensive and bulky instruments and poor portability. The use of a variety of approaches presents a significant standardization challenge even though technological advancements have been effective at detecting VOCs in real time. This is because there are no accepted standards for the interoperability and normalization of methodologies, data analysis, and evaluation that would make these processes clinically useful and comparable across independent studies [ 12 ].

Methods using an E-nose have received much attention in recent years because they could help produce highly sensitive, quick, and low-cost detection systems, and the results are reliable and reproducible [ 82 ]. E-noses have been developed and improved since the 1960s [ 83 , 84 , 85 ]. The concept of an E-nose as an intelligent system containing an array of sensors was first reported in 1982 by Persaud and Dodd [ 86 ], while the term ‘electronic nose’ was first used in 1987 [ 87 ]. Various studies have reported the use of E-noses in the food industry [ 88 , 89 ], changes in the environment [ 90 ], and medical diagnostics [ 91 , 92 , 93 ], which have sparked worldwide interest in the intriguing application of this technology. E-noses are made up of a collection of typically nonspecific sensors that interact with VOCs in different ways: each VOC generates a unique fingerprint because of its interaction with the sensor array, which is further analyzed using a pattern recognition system to determine its nature and origin. In general, an E-nose device is made up of three components: a sample delivery system, a VOC detection system, and a data processing system [ 87 ]. The sample delivery system collects the sample and feeds samples into the detection system. It may include a pretreatment step to increase the percentage of VOCs detected and improve detection quality. The detection system, or the second part, consists of a set of gas sensors that interact directly with the odors to be analyzed. The most used sensors are metal-oxide sensors (MOSs), quartz crystal microbalance (QCM) sensors, conducting polymer (CP) sensors, surface acoustic wave (SAW) sensors, optical sensors, and amperometric electrochemical (EC) sensors. The characteristics (operating principles, processed signals, advantages, and limitations) of commonly used sensors in an E-nose are nicely detailed by Wojnowski et al. [ 94 ]. Each sensor reacts differently to different components of the odor sample to be analyzed. The data generated by the detection system are further analyzed using a variety of multivariate statistical approaches [ 95 , 96 ], the most prevalent of which are linear regression [ 97 ], principal component analysis (PCA) [ 98 , 99 ], linear discriminant analysis (LDA) [ 100 , 101 ], discriminant factor analysis (DFA) [ 102 , 103 ], support vector machine (SVM) [ 104 , 105 ], artificial neural network (ANN) [ 106 , 107 ], etc. The E-nose has several advantages, including being noninvasive, affordable, portable, simple to use, and enabling real-time analysis. The major limitation with an E-nose is the drift, reaction to the VOCs in the environment, inability to preserve diagnostic integrity over the long term, and reproducibility (even though they are from the same manufacturer, test results may change between devices; hence, the results cannot be generalized).

Monitoring VOCs in human breath has been demonstrated in various studies using nanomaterial-based VOC/gas sensors (NMVSs) [ 1 , 18 , 19 , 108 ]. Several nanomaterials, such as nanoparticles and nanowires [ 109 ] produced from various materials, including carbon nanotubes [ 110 ], have been employed as VOC sensing elements [ 111 , 112 , 113 ]. Nanomaterials in conjunction with well-known transducers (such as QCM, SAW, microcantilever-based gravimetric transducers, and surface plasma resonance (SPR)) [ 114 , 115 , 116 , 117 ] have been employed as extremely sensitive recognition elements. Traditional transducer-based NMVSs include sensors with specific receptor layers or with semi-selective recognition layers. One of the important features of NMVSs is their dynamic range and selectivity, which can be modified to precisely identify specific breath VOCs in given conditions. The first challenge with NMVS is immobilizing receptors on solid/gas interfaces without compromising their functionality; to overcome this, nanomaterials covered with biomaterials such as single-stranded deoxyribonucleic acid (DNA) oligomers [ 118 ] and peptides [ 113 ] are being used as VOC-specific receptors. This high selectivity gives rise to a second challenge in NMVS, i.e., the irreversibility in the reaction between VOCs and receptors, which results in a long recovery time and memory effects. This problem can be solved by exposing the nanomaterial to ultraviolet radiation or thermal cycles, but care must be taken to ensure that the nanomaterial does not degrade under high temperatures or UV radiation. The third issue is that the small surface area of nanoscale elements reduces the likelihood of VOC-receptor interactions, so sensors based on random networks of carbon nanotubes (RN-CNTs) [ 112 ], monolayer capped metal nanoparticles (MCNPs) [ 119 , 120 ], and silicon nanowires [ 113 ] are used. Because the pattern of VOCs might indicate not just a disease but also the host's metabolism and other associated conditions, pattern recognition can make compound identification difficult. Thus, only a few NMVS-based techniques exist because of these constraints.

Several reviews have reported substantial developments in breath analysis using defined analytical techniques and VOC detection methods [ 82 , 94 , 121 , 122 , 123 , 124 , 125 ]. Table 1 summarizes the characteristics of the analytical methods used for breath analysis. Despite substantial development in the field of breath analysis, only a few breath tests are currently used in clinics due to technological problems, the inherent complexity of VOCs in exhaled breath [low concentration of VOCs (nanomolar (10–9) to picomolar (10–12))], lack of sampling, and use of the wide range of methodology pose a significant standardization issue. It is currently vital to enhance the selectivity/specificity of technologies/sensors to marker VOCs. These improvements will increase the accuracy and sensitivity of disease-specific VOC detection, which could be employed for more frequent and effective diagnoses.

4 Constituents of Exhaled Breath

Generally, the major components of exhaled breath (in decreasing order by volume) are nitrogen (78.04%), oxygen (O 2, 16%), carbon dioxide (CO 2 , 4–5%), hydrogen (5%), inert gases (0.9%), water (H 2 O), and thousands of VOCs in parts per billion (ppb) concentration [ 23 , 126 , 127 , 128 , 129 ]. Exhaled breath VOCs are chemically very diverse and are commonly classified as inorganic (nitric oxide (NO, 10–50 ppb), nitrous oxide (N 2 O, 1–20 ppb), ammonia, carbon monoxide (CO, 0–6 ppm), hydrogen sulphide (H 2 S, 0–1.3 ppm), etc.)) [ 126 , 130 , 131 , 132 ], organic VOCs (acetone (, 0.3-1 ppm), methane (2–10 ppm), ethane (, 0–10 ppb), pentane (0-10 ppb), alcohols, isoprene (~105 ppb), aldehydes, ketones, ethanol, etc.) [ 130 , 133 , 134 ], and non-volatile substances found in breath condensate (hydrogen peroxide (H 2 O 2 ), cytokines, leukotrienes, isoprostanes) [ 135 ]. Among the most prevalent VOCs identified in exhaled breath are alkanes, NO, CO, ammonia, isoprene and alcohols [ 2 ]. Isoprene (hydrocarbon) produced in the mevalonate pathway is found to be abundant in the exhaled breath of relaxed, seated and healthy volunteers (median concentration: 100 ppb) [ 47 , 48 , 69 , 136 , 137 ]. However, during exertion of an activity, such as leg contractions, the isoprene concentration was shown to be ten times higher. This is most likely due to the production and storage of isoprene in muscle tissues, which results in isoprene accumulation and relatively high muscle concentrations. The perfusion of the muscles increases as an activity is performed. Isoprene is thus taken up by the blood in larger amounts from the muscles, transported to the lungs, and exhaled [ 69 , 138 , 139 ]. During exhalation, a large number of airway cells, both native and those recruited during the inflammatory process, release NO, which is crucial for controlling healthy airways and blood vessels. The endogenous CO is released during metabolism of haem by haem-oxygenase (HO) 1 [ 140 ]. Ammonia (NH3) is also commonly found in exhaled human breath, with a concentration of 0.5–2.0 ppm for a healthy person.

5 VOCs Identified in Various Diseases

The VOCs indicative of a disease state are present in all breath samples but have different concentrations depending on the disease. Philips et al. investigated the variations in VOCs in exhaled breath samples and reported a total of 3,481 different VOCs (1,753 with positive alveolar gradients (abundance in breath minus abundance in air) and 1,728 with negative alveolar gradients) [ 5 , 141 ] that have been observed at least once in exhaled breath. A large part of the VOC spectrum differs between individuals because of various factors (lifestyle, genetics, microbiome, food intake, environmental influence, physical condition etc.) [ 2 , 142 ], while few common VOCs are observed among individuals sharing a common health issue/disease [ 18 , 143 ]. It is generally known that patients with specific diseases have breath volatile profiles that differ from the typical volatile profile [ 23 ]. The number of common VOCs found in all patients' breath samples, which may be indicative of a certain disease, ranges from a few to tens of VOCs (Fig. 2 ). These VOCs have low breath concentrations (spans of various orders of magnitude, ranging from pptv to ppmv (usual)) when compared to the entire breath composition [ 23 , 128 , 129 ]. Aside from a few exceptions, no distinct VOC is discovered in the breath of diseased individuals [ 144 ]. Therefore, a small but signification change in VOC spectrum (in concentration and composition) is observed when a switch from healthy to diseases state occurs; this phenomenon is known as breath metabolomics (breathomics) [ 145 ]. It is possible to identify this alteration and use it for monitoring and diagnosis.

Disease- and toxicity-specific symptoms. The majority of the odors are from breath unless otherwise specified

Studies have linked single VOCs or sets and patterns of exhaled VOCs as biomarkers to various diseases. There are two ways whereby VOCs that indicate the presence of a disease will appear in the breath. (i) VOC blood content changes because of disease-related metabolic and oxidative stress, which are then manifested in breath after pulmonary material exchange in the lungs. (ii) VOCs produced by cells and tissues connected to a diseased state and located near the epithelial tissues lining the respiratory system or gastrointestinal tract [ 23 , 128 , 129 ]. The role of VOCs in the early detection of diseases such as cancer, lung diseases (asthma, respiratory (inflammation, chronic obstructive pulmonary)), renal failure, neurodegeneration, organ failure, oxidative stress and metabolic disorders and how they been utilized to determine appropriate medical therapies have been reported [ 11 , 12 , 23 , 41 , 121 , 128 , 129 ]. Table 2 summarizes the identified VOCs, analytical methods and data analysis in various diseases based on exhaled breath.

Cancer is a leading cause of mortality worldwide. Cancers are detected at various stages, but some cancers remain hard to diagnose because of subtle symptoms and are only identified once they have progressed to the point where there is no cure. As a result, early detection of cancer is critical for better treatment outcomes and reducing cancer mortality. There is a need for a reliable non-invasive cancer screening technology. Exhaled breath analysis can be supplemented with research into the cancer cell cultures [ 146 , 147 , 148 , 149 ] and patient cancer tissues [ 150 ], i.e., the VOC profile of exhaled breath can be compared with the chemical profile of cancerous tissue. Over the last 10 years, more than 100 volatile biomarkers found in exhaled breath have been linked to cancer [ 151 ].

5.1.1 Lung Cancer

The majority of exhaled breath analysis studies are focused on lung cancers. Various pilot studies [ 64 , 129 , 134 , 152 , 153 , 154 , 155 , 156 ] have examined the exhaled breath of lung cancer patients and observed that butanedione is present in higher concentrations in comparison to a healthy individual. Bajtarevic et al. reported three primary compounds found in everyone's exhaled breath (isoprene, acetone and methanol) to be present in lower amounts in breath samples of lung cancer patients [ 134 ]. Some aldehydes, such as pentanal, hexanal, octanal and nonanal, are also observed in increased concentrations [ 157 ], while isoprene showed a negative correlation (i.e., in low concentrations) among lung cancer patients [ 158 ]. Another study reported a high concentration of alkanes in the exhaled breath of lung cancer patients [ 159 ]. Bajtarevic et al. identified 21 VOCs that may be used to distinguish lung cancer patients from healthy people [ 134 ]. Butan-1-ol and 3-hydroxybutan-2-one were found in various concentrations in lung cancer samples by Song et al. [ 160 ]. Zou et al. [ 161 ] reported five VOCs (5-(2-methylpropyl) nonane; 2,6-di-tert-butyl-4-methylphenol; 2,6,11-trimethyldodecane; hexadecanal; 8-hexylpentadecane) as possible VOCs observed in lung cancer breath samples. Wang et al. [ 162 ] confirmed 23 VOCs as biomarkers for lung cancer. Ten compounds, including hexadecanal and dodecane, were identified in exhaled breath from lung cancer patients by Handa et al. [ 163 ]. A mixture of 20 VOCs, mostly alkanes and their derivatives, benzene derivatives, aniline, and o-toluidine, as well as lipid peroxidation activity, was observed at a 70% probability level in patients with lung cancer [ 164 ]. Over 100 volatile biomarkers have been proposed as being linked to lung cancer in the last 10 years [ 6 , 64 , 98 , 106 , 108 , 152 , 155 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 ], and are potential marker compounds broadly classified as alcohols, aldehydes, ketones and hydrocarbons [ 134 ]. Clinical testing in cases of lung cancer is still a long way off. All suggested potential VOCs will need to be thoroughly validated. Furthermore, because smoking cigarettes is the leading cause of lung cancer and chronic obstructive pulmonary disease (COPD), it is critical to ignore tobacco combustion products when looking for biomarkers.

5.1.2 Breast Cancer

Similar to lung cancer, breast cancer patients can be identified from healthy individuals by utilizing aggregate low-dimensional summaries and compound quantities that result in discrete patterns [ 104 ]. A unique combination of alkanes and monomethylated alkanes has been identified in breath samples of patients [ 190 ]. Mangler et al. [ 164 ] reported five compounds observed in various concentrations in breast cancer patients' breath samples (3-methylhexane, dec-1-ene, caryophyllene, naphthalene, and trichloroethene) as potential markers. Philips et al. [ 191 , 192 ] conducted many breath analysis investigations utilizing various analytical techniques and data-processing approaches, reporting the highest VOCs in the breath samples of breast cancer patients [ 193 , 194 ]. Aldehydes (hexanal, heptanal, octanal and nonanal) found in the breath of breast cancer patients by Li et al. [ 195 ] and formaldehyde (methanal) by Miller et al. [ 196 ] are also likely to be biomarkers for the disease.

5.1.3 Prostate and Bladder Cancer

In addition to breast cancer, formaldehyde has been proposed as a possible biomarker for prostate and bladder cancers [ 197 ]. Using a specially designed array of cross-reactive nanosensors based on organically functionalized Au nanoparticles, Peng et al. investigated the exhaled alveolar breath of 177 volunteers between the ages of 20 and 75 years for different cancers (lung, colon, breast and prostate cancers) in a single study. Regardless of age, sex, lifestyle or other complicating factors, the nanosensor array was able to distinguish between the breath patterns of cancers and healthy samples, and a distinct pattern of VOCs was revealed, with almost no overlapping for different type of cancers in GC/MS [ 198 ].

5.1.4 Liver Cancer

Three VOCs (3-hydroxybutan-2-one, styrene and decane) with varied concentrations were identified when the breath of liver cancer patients and healthy controls were compared [ 199 ].

5.1.5 Ovarian Cancer

Based on GCMS breath analysis of ovarian cancer patients, Amal et al. [ 200 ] found four VOCs (decanal, nonanal, styrene, 2-butanone and hexadecane) that could serve as possible volatile markers for ovarian cancer.

5.1.6 Colorectal Cancer

In a breath sample from colorectal cancer patients, a pattern of 15 chemicals demonstrated a discriminant performance with an accuracy of 85% [ 201 ].

5.1.7 Head and Neck Cancer

Studies were also performed to identify possible markers for squamous cell carcinoma of the head and neck (HNSCC) or benign tumors of the head and neck [ 170 , 202 ], and three VOCs (ethanol, 2-propenenitrile and undecane) were identified using GC/MS [ 203 ].

Similar to lung cancer, the biological/clinal significance and metabolic pathways of VOCs produced in other cancers are unclear [ 191 , 192 , 204 , 205 ], and must be determined as soon as possible. A review of potential cancer-specific compounds was published by Haick et al. [ 151 ]. However, there is currently no "universal" cancer VOC marker that can detect any type of cancer; nevertheless, advancements in breath analysis may offer a promising tool in the near future. These studies are still in the early stages, but they will provide a greater understanding of the biochemistry of the compounds present in exhaled breath.

5.1.8 Gastric Cancer

Various studies have been performed to identify potential biomarkers to diagnose gastric cancers [ 206 , 207 , 208 , 209 ]. Pilot studies conducted to screen gastric cancer observed 6-methyl-5-hepten-2-one (CAS: 110-93-0) in increased concentrations in exhaled breath of gastric patients in comparison to healthy individuals. Amla et al. [ 207 ] found eight significant VOCs (2-propenenitrile, furfural, 2-butoxyethanol, hexadecane, 4-methyl octane, 1,2,3-tri-methylbenzene, α-methyl-styrene, and 2-butanone) in the exhaled breath of patients with stomach malignancies. In another study, 12 VOCs (mostly aldehydes and alcohols) were found in significantly higher concentrations in exhaled breath samples from gastric cancer patients than in healthy people [ 208 ].

5.2 Diabetes

Ketones have the potential to be used as diabetes indicators. Patients with type 1 diabetes mellitus (T1DM) are unable to produce insulin, causing glucose to accumulate in the blood and be discharged into the urine. Fatty acids begin to replace glucose as a source of energy for cells. Ketones (acetone, acetoacetate, 3-hydroxybutyrate) are produced during fatty acid breakdown, causing blood acidity and ketoacidosis. Excess ketones are then produced in the urine and breath; thus, the urine and breath of the patients emanate a fruity odor (acetone) [ 4 , 23 , 210 , 211 , 212 ]. Excess acetone was found in the breath samples of individuals with type 1 diabetes in three different studies [ 12 , 213 , 214 ]. Increased levels of CO, isoprene, pentanal, dimethyl sulphide, methyl nitrate and isopropanol have also been observed in exhaled breath of T1DM patients [ 215 , 216 , 217 , 218 ]. In exhaled breath of individuals suffering from type 2 diabetes mellitus (T2DM), apart from acetone, isopropanol and CO, higher levels of ammonia, ethylene, toluene, tridecane, undecane, 2,3,4-trimethylhexane and 2,6,8-trimethyldecane were observed [ 219 , 220 , 221 , 222 ]. These findings, however, are based on research with a very small population, therefore a reliable standalone biomarker for T2DM has not yet been identified.

5.3 Scarlet Fever

Scarlet fever, caused by Streptococcus pyrogenase bacterial infection, is characterized by a reddish-brown rash on the body, a sore throat, fever and a distinct bad odor emanating from the patient's skin and breath [ 190 ]. VOCs linked to fever are still unknown.

5.4 Gastric-Related Disorders

In bowel disease, 1-pentane has been directly quantified using gas-phase ion molecule reactions and SIFT-MS in exhaled breath samples, indicating that this molecule is a possible biomarker of bowel disease [ 223 ]. A fecal odor is observed in the breath of patients with ileus or intestinal blockage, which causes regurgitation of stool contents backward into the stomach. The urea breath test can be used to detect stomach cancer or gastritis caused by Helicobacter pylori bacteria [ 11 , 164 ]. Timms et al. used the Cyranose 320 E-nose to analyze exhaled breath and found that patients with obstructive pulmonary disease and gastro-oesophageal reflux disease (GORD) had considerably higher levels of EBC pepsin [ 224 ].

5.5 Heart Diseases

In patients with persistent heart failure, lower amounts of isoprene have been discovered [ 225 ]. After cardiopulmonary bypass and in ischemic heart disease [ 30 , 226 ], increased exhaled n-alkane concentrations have been observed in the patient's breath. Increased concentrations of n-alkanes have been observed in the exhaled breath of patients with myocardial infarction [ 227 ]. Therefore, isoprene and n-alkanes could be used as potential biomarkers for heart-related ailments.

5.6 Lipid Peroxidation

Lipid peroxidation disrupts membrane function (altering ion transport, fluidity, and permeability), inhibits metabolic processes, and generates toxic by-products that have been associated with inflammatory illnesses, cancer, atherosclerosis, ageing and other conditions [ 228 ]. It is a chain of oxidative lipid breakdown processes (attack of oxidants on lipids), wherein free radicals "steal" electrons from the lipids in cell membranes, unsaturated lipid double bonds are rearranged, lipid radicals are produced and propagated, the uptake of oxygen and membrane lipids is eventually destroyed, causing oxidative damage to the cell structure as well as being implicated in the toxicity process that results in cell death. Lipid peroxidation in pathological circumstances (where the production of reactive oxygen and nitrogen species is elevated) is triggered by a tocopherol deficiency. This results in the production of a variety of breakdown products, including alkanes, aldehydes, alcohols, ethers and ketones [ 220 , 229 ]. Among these products aldehydes are found in the breath, which could be indicative of lipid peroxidation [ 230 ]. Few studies have found propane and butane to be biomarkers of lipid peroxidation [ 12 ].

5.7 Liver Diseases

Patients with liver disease [ 231 ] or those who have received a liver transplant [ 232 ] have been found to have a higher concentration of sulfur-containing compounds. The concentrations of n-alkanes in the exhaled breath of patients with ischemic liver disease were also found to be higher [ 27 ]. In liver failure and cirrhotic patients, the amounts of sulfur-containing (dimethyl sulfide, dimethyl disulfide, ethyl mercaptane) substances exhaled were observed to be higher [ 12 , 164 ]. A higher concentration of ammonia in the breath has been reported in patients with acute liver failure and hepatic encephalopathy [ 233 , 234 ]. Isoprene breath concentrations were observed to be higher during and after hemodialysis in several studies [ 235 ].

5.8 Respiratory/Lung Diseases

Exhaled breath has the greatest potential for diagnosing the respiratory system [ 236 , 237 , 238 , 239 , 240 , 241 , 242 , 243 , 244 , 245 , 246 , 247 , 248 , 249 , 250 , 251 , 252 , 253 , 254 , 255 , 256 , 257 , 258 , 259 ]. Exhaled NO is a common biological and neurological transmitter that is crucial for regulating healthy blood vessel tone and normal airways. Numerous airway cells, both resident and those that are recruited during the inflammatory phase, release NO [ 140 ].

5.8.1 Tuberculosis

Tuberculosis, a bacterial infection caused by Mycobacterium tuberculosis, targets the lungs and generates a foul odor in the breath [ 236 ]. A unique combination of VOCs (methyl phenylacetate, methyl nicotinate, methyl p-anisate and o-phenylanisole) in samples of tuberculosis patients was identified using an E-nose sensor [ 237 , 238 ]. Phillips et al. [ 239 ] used two separate mathematical techniques—fuzzy logic analysis and pattern recognition analysis—to identify a set of breath VOCs that discriminated normal controls from tuberculosis patients. Both procedures yielded similar results. In a limited number of people with tuberculosis of the neck, scrofula, ulcerated lymph nodes, have been observed that smell like old beer. These discoveries may aid in the development of non-invasive tuberculosis-testing methods.

5.8.2 Asthma

In spontaneous or induced asthma, an increase in the fraction of exhaled nitric oxide (FeNO) was observed, which is flow dependent [ 241 , 242 , 243 , 244 , 245 , 246 , 247 , 248 ]. Pentane and ethane levels were also found to be higher in asthmatic patients [ 249 , 250 ].

5.8.3 Chronic Obstructive Pulmonary Disease (COPD)

In individuals with COPD, the presence of 13 VOCs (mainly ethane) has been confirmed [ 251 , 252 ]. Hatteshol et al. [ 253 ] also identified a set of six breath VOCs that might be utilized to collect samples from COPD patients.

5.8.4 Acute Respiratory Distress Syndrome (ARDS)

Exhaled isoprene concentrations were found to be significantly reduced [ 254 , 255 ] in patients with acute respiratory distress syndrome (ARDS), while pentane and ethane concentrations were found to be significantly higher [ 254 , 256 ].

5.8.5 Pneumonia

Foul-smelling breath is one of the many symptoms of pneumonia (fluid-filled lungs, difficulty breathing, pulmonary inflammation, fever, etc.), which is caused by a bacterial, viral, or fungal infection of the lungs [ 33 ]. Patients with pneumonia had higher levels of pentane and ethane in their exhaled air [ 255 ]. However, all VOCs associated with pneumonia have not yet been identified. Experiments have shown that exhaling isoprene causes oxidative damage to the fluid lining of the lungs [ 258 ].

5.8.6 Diphtheria

Diphtheria , a bacterial infection produced by Corynebacterium diphtheria , generates a sore throat and a sweetish or putrid odor in the breath [ 259 ], although there are no recognized VOCs related to it. A detailed review on the clinical usage of volatile chemicals in respiratory diseases was published by Kant et al. [ 251 ].

5.9 Neurodegenerative Disorders

The progressive loss of structure or function of neurons causes neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), schizophrenia, bipolar disorders, etc. AD is characterized by amyloid plaques and neurofibrillary tangles that cause progressive cognitive and behavioral impairment [ 260 ]. PD, characterized by resting tremor, postural instability, rigidity, and bradykinesia, is connected to depigmentation and progressive neuronal death in the substantia nigra, dopamine depletion, and pervasive α-synuclein aggregation [ 261 , 262 , 263 , 264 ]. Both AD and PD are diagnosed mostly through clinical symptoms, which have a wide range of sensitivity and specificity depending on the treating physician's expertise [ 265 ]. Thus, the identification of biomarkers could allow for the early detection of pathogenic changes before neuronal damage occurs. Tisch et al. [ 266 ] used an array of 20 organically functionalized nanomaterial-based sensors (random networks of single-walled carbon nanotubes (RN-CNTs) [ 267 , 268 ] and gold nanoparticles (GNPs) [ 269 , 270 ]) to identify potential VOC biomarkers to distinguish AD and PD patients from healthy individuals. The analysis of breath samples from AD patients and healthy individuals revealed 24 VOCs in varying concentrations, which may be considered potential biomarkers for AD. In the same study, seven chemicals were discovered as possible biomarkers for distinguishing PD patients' breath samples from healthy persons [ 266 ]. In PD patients, alkanes and methylation alkanes were detected in higher concentrations, while styrene was found in higher concentrations in both AD and PD. H. pylori infection affects breath ammonia, which disrupts cerebral function and causes AD symptoms [ 271 ]. Some of the substances tentatively identified as AD and PD biomarkers may have plausible explanations (such as increased oxidative stress, which causes lipid peroxidation [ 272 , 273 ]), whereas the sources of others remain unknown.

Schizophrenia is another severe neurological condition defined by hallucinations and cognitive abnormalities. It is caused by multiple factors, including inherited and environmental influences. Because the genetic and molecular pathways underlying schizophrenia susceptibility are unknown, as with AD and PD, in the absence of obvious biological markers, the diagnosis is typically based on behavioral indications, symptoms, and cognitive testing [ 274 ]. As a result, discovering new biomarkers that can aid in early detection is critical. High levels of CS 2 (neurotoxin) and pentane, a marker of lipid peroxidation, were observed in the breath samples of patients with schizophrenia [ 275 ]; however, the origin of CS 2 is still unknown.

According to a recent study [ 276 ], patients with schizophrenia and bipolar disorder had significantly higher levels of ethane and butane in their breath. Patients with mental health problems [ 277 ] were found to have significant (high) levels of ammonia in their breath.

5.10 Organ Transplantation

Exhaled alkane concentrations have been associated with allograft rejection after organ donation. Acute rejection of transplanted hearts causes an increase in pentane levels. However, rather than being a unique marker for allograft rejection, pentane is a lipid peroxidation marker and is associated with inflammation [ 278 ]. Another volatile marker identified for acute rejection of lung allograft is carbonyl sulfide, which is not observed in the exhaled breath of healthy people [ 279 ]. This chemical is produced as a by-product of methionine metabolism and could serve as an early indicator of organ rejection following lung transplantation [ 279 ]. In another study, a higher concentration of sulfur-containing substances was observed in liver failure and allograft rejection [ 41 ].

5.11 Oral Health Problems

Halitosis is an oral health condition characterized by foul-smelling breath. E-nose sensors have been used to identify potential VOCs that are known to cause halitosis. Studies have reported that hydrogen sulfide [ 280 , 281 , 282 ] and two acids (butyric acid and valeric acid) [ 280 ] are compatible with halitosis detection and could be used as potential biomarkers. The sniff-cam has been utilized to quantify the extremely low concentration of breath ethanol (EtOH), which has been connected to the activity of the oral or gut bacterial flora [ 283 ].

5.12 Renal Disease

Uremia, or kidney failure, is characterized by the presence of excessive nitrogenous waste products (urea) in the bloodstream, as well as an ammonia or urine-like odor in the breath, caused by the breakdown of urea into ammonia and trimethylamine in the saliva [ 55 , 284 , 285 ]. It was also observed that patients with end-stage renal illness have higher levels of trimethylamine in their exhaled breath [ 286 ]. Therefore, both ammonia and trimethylamine could be used as biomarkers for the detection of renal diseases [ 286 , 287 ]. In one study, it was observed that patients with uraemia and end-stage renal failure had higher levels of ammonia in their exhaled breath [ 288 , 289 ].

6 Environmental or Mechanism-Based Exhaled VOCs

6.1 smoking.

Smokers' breath, blood, and urine contain prominent concentrations of acetone and acetonitrile [ 290 , 291 ]. The concentration of acetone was found to be variable (approximately 400 ppb as the median), while acetonitrile depends on an individual’s smoking habits (30–60 ppb in active smokers and 2–3 ppb in passive/nonsmokers) [ 134 ]. Isoprene levels in the breath have been reported to increase after smoking [ 142 ]. The presence of toxic compounds such as tetrachloroethylene was quantified among marijuana addicts [ 4 ]. In particular, ∼ 80 volatile compounds are attributed to smoking [ 37 ].

6.2 Oxidative Stress

Oxygen is essential to sustain cellular metabolism, and organisms have evolved sophisticated protective systems to preserve oxygen homeostasis. A stepwise one-electron reduction takes place in 1–5% of molecular oxygen. These one-electron reduction intermediates, i.e., reactive oxygen species (ROS) (superoxide, hydrogen peroxide, and hydroxyl radicals), are toxic to biological systems. To protect organisms from the toxic effects of ROS, biological systems have evolved many antioxidant defenses, such as enzymes (catalase, glutathione peroxidase, etc.) and nonenzymatic species (vitamins A, C, and E; bilirubin, etc.). Oxidative stress status refers to the equilibrium between ROS and antioxidant defenses. During oxidative stress and inflammatory conditions, exhaled ethane and pentane concentrations are elevated in patients with heart transplant rejection, obstructive sleep apnea, ARDS, asthma, and mental and physical stress [ 11 , 12 , 164 ]. Phillips and his collaborators [ 164 , 283 ] have reported the presence of methylated alkanes in oxidative stress using thermal or adsorption capillary GCMS.

It is also important to monitor oxidative stress levels, particularly during surgery. Two oxidative stress biomarkers that can be measured in real time are ethane and pentane. Other breath biomarkers (such as dimethyl sulfide, indicative of bacterial infection in lungs) may be used in the critical care unit [ 31 ].

6.3 Toxicity

Poisoning with specific chemicals also influences the odor of exhaled breath [ 292 , 293 ]. The consumption of cyanide causes a bitter-almond odor in the breath, whereas the intake of arsenic, thallium, or organic phosphate pesticides causes a garlic-like breath and body odor. Toxic substances have not yet been linked to VOCs.

7 VOCs Identified from Other Sources

Breath is not the only source of VOCs, and other major sources of VOCs include blood, sweat, skin, vaginal secretions, feces, cancerous cell culture, urine, and other body fluids [ 35 , 294 ].

7.1 Sweat and Skin VOCs

Most VOCs emitted from the skin surface come from sweat and sebum. Many VOCs are formed because of chemical metabolism or modification by symbiotic bacteria that live on the skin's surface, but some are produced because of internal hormonal or metabolic processes. A shift in homeostatic balance caused by a hereditary metabolic disorder or bacterial infection of the diseased area can produce changes in both the quality and number of VOCs [ 295 ]. For example, a few patients (5%) with advanced cancer (breast cancer, head and neck cancer, leg ulcer) have unpleasant odors emanating from fungating wounds [ 296 , 297 , 298 , 299 ], i.e., ulcerative lesions that develop when tumor cells infiltrate and erode through skin due to the presence of dimethyl trisulphide (DMTS) [ 55 , 300 ]. While bacterial infection produces DMTS in fungating wounds, the source of DMTS is still unknown.

Infected lesions or pus-filled rashes that develop in smallpox, caused by viral infection with variola virus , have a sweetish, pungent odor [ 301 ]. Patients with typhoid fever, caused by an infection of the intestinal tract with Salmonella typhi , have a musty or baked-bread body odor [ 33 , 34 ], while odor resembling butcher’s shop is emanated by patients with yellow fever, a viral infection caused by female mosquitoes. Patients with yellow fever often have a body odor that smells like a butcher’s shop [ 33 ]. The source of VOC and composition in all diseases mentioned in this section has yet to be determined.

Isovaleric acid was identified as a biomarker for patients suffering from isovaleric acidemia (IVA), an autosomal recessive inherited leucine metabolism disorder that possesses a specific body odor (cheesy, acrid or resembling sweaty feet). IVA is caused by a deficiency of the mitochondrial enzyme isovaleryl-CoA dehydrogenase [ 302 ]. Scurvy disease is caused by a lack of vitamin C, which is essential for collagen formation and results in a putrid odor in the patient's sweat [ 295 ].

7.2 Urine VOCs

Urine contains various types of end or intermediate products (ketones, alcohols, furan, etc.) from different metabolic processes, all of which have distinct odors. Urinary VOCs are influenced not only by metabolic processes but also by the foods and beverages consumed.

Maple syrup urine disease is caused by the loss of an enzyme activity that catalyses the oxidative decarboxylation of 2-oxocarboxylic acids in the breakdown of branched chain amino acids (BCAAs). This deficit causes the accumulation of 2-oxocarboxylic acids and their reduced metabolites in tissues, blood, and urine; hence, a distinctive maple syrup or caramelised sugar-like odor emanates in urine and sweat [ 303 ].

Isovalerylglycine and 3-hydroxyisovaleric acid (IVA) [ 304 , 305 , 306 ], which give urine samples an unpleasant odor, are found in urine samples from IVA disorder patients. The conversion of unabsorbed methionine into alpha-hydroxybutyric acid by intestinal bacteria results in a yeasty, malty odor in the urine of patients with methionine malabsorption syndrome [ 307 ]. Urine odors have also been linked to specific metabolic disorders, and the reasons for the odors have been revealed in some cases [ 308 ] but not all.

7.3 Blood VOCs

VOCs are often released into the circulation during metabolism, which provides information about the body's internal environment and metabolic, nutritional, and physiological state. Studies have shown that distinct odors in blood can be utilized to identify and diagnose a variety of diseases [ 309 , 310 , 311 ]. However, more research is needed to assess the findings and apply them to clinical diagnosis.

7.4 Fecal VOCs

End-products of digestive and excretory processes, as well as intestinal bacterial metabolism, have been linked to specific patterns of VOCs in feces samples from diseased people. Cholera ( Vibrio cholerae bacterial infection) patients' feces have a distinct sweetish odor due to the presence of dimethyl disulphide and p-menth-1-en-8-ol, both of which have been identified as possible biomarkers [ 312 , 313 ].

7.5 Vaginally Secreted VOCs

Chemicals found in vaginal secretions usually indicate the stages of menstrual cycles. Vaginal secretions are almost doorless at all stages of the menstrual cycle. However, if vaginal secretions have a cheesy or fishy odor, it is indicative of bacterial infection in the genital organ (vaginal and/or cervical). In gynecological tumors, heavy vaginal discharge with an unpleasant and offensive odor is reported, which is caused by the presence of volatile fatty acids (acetic acids, isovaleric acids, and butyric acids) [ 298 ].

Even though the various sources of VOCs described in this section may be more beneficial in specific circumstances, considerable caution must be exercised when taking samples in any of the cases to avoid contamination from the environment, equipment, or cosmetics. Breath sample collection, on the other hand, is non-invasive and painless for patients and can be collected in real time, which is a major advantage of breath VOCs. However, a lack of standardization in breath collection and analysis, sample storage, and data handling in breath-based analysis are still critical challenges. Amann et al. [ 314 ] proposed a standardized protocol that may become widely adopted in the future. To encourage the use of breath analysis in clinical practice, larger studies should be conducted in comprehensive screening settings, with a special focus on breath collection standardization and validation in diverse and independent population samples [ 315 ].

8 Conclusion

VOCs from breath represent a relatively new field of research, and their analysis for disease detection and diagnosis holds great potential. Apart from breath, VOCs are emitted through the skin, saliva, urine, and feces. However, exhaled breath is the most accessible and effective VOC source among all sources for monitoring diseases and disorders. The advantages of VOCs include easy accessibility of exhaled air and availability of a variety of recognized VOCs. The diagnosis is non-invasive, suited for high compliance, and has low complexity. Additionally, it can be handled securely, yields reproducible outcomes, is fast in diagnosing diseases, and can be repeated as many times as desired. It can enable healthcare professionals to quickly activate the therapeutic control mechanism and monitoring. Microanalyzes of VOCs from breath, as well as detailed investigation of their metabolic pathways and exhalation kinetics, would be interesting and could facilitate a better understanding of the pathophysiological mechanisms that cause a specific disease and improve the quality of life of distressed patients.

Traditional GC, GC/MS, and other techniques are expensive, time consuming, and difficult to adapt to high-throughput applications. Technological improvements in analytical and data analysis techniques have made it possible to discover VOCs linked to diseases in research facilities. With the ongoing developments in the field and real-data analysis, breath test analysis holds promise to become a useful screening tool that will not only aid but also improve existing diagnoses for several diseases and disorders. Large studies in real-world screening settings, with a focus on standardizing the breath collection protocol and validation in different and independent population samples, should be carried out to accelerate the use of breath analysis for disease diagnosis.

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The authors acknowledge the logistic support of Systems Biology Lab—Department of Applied Science, Indian Institute of Information Technology—Allahabad (IIITA).

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Sharma, A., Kumar, R. & Varadwaj, P. Smelling the Disease: Diagnostic Potential of Breath Analysis. Mol Diagn Ther 27 , 321–347 (2023). https://doi.org/10.1007/s40291-023-00640-7

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Accepted : 11 January 2023

Published : 02 February 2023

Issue Date : May 2023

DOI : https://doi.org/10.1007/s40291-023-00640-7

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