Smelling the Disease: Diagnostic Potential of Breath Analysis

Abstract

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.

Key Points

Volatile organic components (VOCs) serve as markers for identification of various diseases.

Recognition and diagnosis of complex diseases may be possible by analyzing VOCs released in breath or other body fluids.

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 [4–6]. 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, 11–16]. Lavoisier investigated the breath CO₂ 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 [18–20]. 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, 22–32]. 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 [35–41]. Some of the VOCs that may be present in the breath are oxygen-containing compounds (acetone, methanol, ethanol, etc.) [42–45], hydrocarbons (ethane, pentane, isoprene, etc.) [46–48], sulfur-containing compounds (ethyl mercaptane, dimethyl sulfide, dimethyl disulfide, etc.) [49–51] 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.

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.

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 [4–6]. 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.

Fig. 1.

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) [64–66], 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 (H₃O⁺, NO⁺, O₂) 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 [67–72]. 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 [75–77]. 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 (NH₃) 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 [83–85]. 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 [91–93], 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 [111–113]. Nanomaterials in conjunction with well-known transducers (such as QCM, SAW, microcantilever-based gravimetric transducers, and surface plasma resonance (SPR)) [114–117] 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, 121–125]. 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.

Table 1.

Summary of analytical methods used for breath analysis [1, 18, 65, 66]

Analytical method	Limit of detection	Advantages	Disadvantages
GC/MS	ppt-ppb	Highly selectivity and sensitivity	Expensive instruments, complicated sample preparation, large sampling time, require standardization, require trained personnel, no real-time analysis
PTR-MS	ppt	Real-time analysis	Expensive instrumentation, complicated sample preparation, compounds in very small concentrations cannot be identified, require trained personnel
SIFT-MS	ppt-ppb	Real-time analysis Wide range of detection	Require standardization, compounds cannot be identified
IMS	ppt-ppb	Hand-held devices/portability	Cannot identify unknown volatile compounds
Optical absorption	Ppt	Real-time analysis Portability, miniaturization	Require selectivity for practical use
E-noses	N/A	Real-time analysis, high selectivity and sensitivity, portability and miniaturization	Difficulty in recognizing VOCs pattern
NMVS	Dynamic detection range	Real-time analysis, dynamic range, high selectivity	Difficulty in recognizing VOC pattern, immobilizing receptors without losing functionality, Less VOC-receptor interaction due to small surface area

GC gas chromatography, MS mass spectrometry, SIFT selected ion flow tube, IMS ion mobility spectrometry, E-nose electronic nose, NMVS nanomaterial-based VOC/gas sensor, VOC volatile organic compound, ppt parts per trillion, ppb parts per billion

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 (CO₂, 4–5%), hydrogen (5%), inert gases (0.9%), water (H₂O), and thousands of VOCs in parts per billion (ppb) concentration [23, 126–129]. Exhaled breath VOCs are chemically very diverse and are commonly classified as inorganic (nitric oxide (NO, 10–50 ppb), nitrous oxide (N₂O, 1–20 ppb), ammonia, carbon monoxide (CO, 0–6 ppm), hydrogen sulphide (H₂S, 0–1.3 ppm), etc.)) [126, 130–132], 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 (H₂O₂), 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.

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.

Fig. 2.

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.

Table 2.

Summary of identified volatile organic compounds (VOCs), analytical methods and data analysis in various diseases based on exhaled breath

Disease	#VOCs	VOC	Analytical method	Data analysis	References
Cancer
Breast cancer	8	Nonane; Tridecane, 5-methyl; Undecane, 3-methyl; Pentadecane, 6-methyl; Propane, 2-methyl; Nonadecane, 3-methyl; Dodecane, 4-methyl; Octane, 2-methyl	GC/MS	DA	[191]
Breast cancer	5	2-propanol; 2,3-dihydro-1-phenyl-4(1H)-quinazolinone; 1-phenyl-ethanone; heptanal; isopropyl myristate.	GC/MS	FL function	[192]
Breast cancer	29	Cyclopropane, ethylidene; 1,4-Pentadiene; 1,3-Butadiene, 2-methyl-; Cyclotetrasiloxane, octamethyl-; 3-Ethoxy-1,1,1,5,5,5-hexamethyl-3-(trimethylsiloxy)trisiloxane; Benzoic acid, 4-methyl-2-2-trimethylsilyloxy-,trimethylsilyl ester; D-Limonene; Cyclohexene, 1-methyl-5-1-methylethenyl)-,(R)-; Cyclohexene, 1-methyl-5-(1-methylethenyl)-; Benzene, 1,2,4,5-tetramethyl-; Benzene,1,2,3,5-tetramethyl-; Benzene,1-ethyl-3,5-dimethyl-; Tridecane; Dodecane; Undecane; Dodecane, 2,7,10-trimethyl-; Dodecane, 2,6,11-trimethyl-; Tetradecane; Pentadecane; (+)_Longifolene; 1H-Cycloprop[e]azulene, decahydro-1,1,7-trimethyl-4-methylene-; Longifolene-(V4); 2-Hexyl-1-octanol; 1-Octanol, 2-butyl-; Trifluoroacetuc acid, n-octadecyl ester; 2,5-Cyclohexadiene-1,4-dione,2,6-bis(1,1-dimethylethyl)-; 2,5-di-tert-Butyl-1,4-benzoquinone; Acetic acid, 2,6,6-trimethyl-3-methylene-7-(3-oxobutylidene)oxepan-2-yl ester	GC/MS	MC, multivariate WDA	[193]
Breast cancer	–	–	GC/MS	LDA, QDA, SVM	[104]
Breast cancer	10	Hexanal; Heptanal; Octanal; Nonanal; Decanal; Amphetamine; Phenyglyoxal; Phenol; Silane, tetramethyl; Cyclohexanecarboxaldehyde, 6-methyl-3-(1-methylethyl)-2-oxo-	GC/MS	Binary LR	[194]
Breast cancer	29	Same as Ref 167	GC coupled to SAW detector	MC, WDA	[194]
Colorectal cancer	15	Nonanal; 4-Methyl-2-pentanone; Decanal; 2-Methylbutane; 1,2-Pentadiene; 2-Methylpentane; 3-Methylpentane; Methylcyclopentane; Cyclohexane; Methylcyclohexane; 1,3-Dimethylbenzene; 4-Methyloctane; 1,4-Dimethylbenzene; 4-methylundecane; Trimethyldecane	GC/MS	PNN	[201]
Head and neck cancer	–	–	NA-NOSE, GC/MS	PCA, t test, SVM	[170]
Head and neck cancer	–	–	Prototype E-nose (12 MOS sensors)	LR	[202]
Head and neck cancer	3	Ethanol; 2-Propanenitrile; Undecane	GC/MS, Prototype-NMVS	DFA	[203]
Liver cancer	3	3-Hydroxy-2-butanone; Styrene; Decane	SPME-GC/MS	Classification	[199]
Lung cancer	–	–	IMS	LDA	[165]
Lung cancer	8	1-propanol; 2-butanone; 3-butyn2-ol; benzaldehyde; 2-methyl-pentane; 3-methyl-pentane; n-pentane; n-hexane	SPME-GC/MS	–	[166]
Lung cancer	3	Aniline; o-toluidine; Cyclopentane	LibraNose (8 QCM sensors)	PLS-DA	[167]
Lung cancer	3	Aniline; o-toluidine; Cyclopentane	ENS Mk 3 (6 MOS sensors)	PCA	[168]
Lung cancer	7	Nonanal; Hexanal; Octanal; Heptanal; Butanal; Pentanal; Propanal	SPME-GC/MS	ANOVA, DA	[169]
Lung cancer	6	4,6-Dimethyl-dodecane; 2,2-Dimethyl-propanoic acid; 5-methyl-3-hexanone; 2,2-Dimethyl-decane; Limonene; 2,2,3-Erimethyl-,exo-bicyclo[2,2,1]heptane	NA-NOSE, GC/MS	PCA-ANOVA, t test, SVM	[170]
Lung cancer	–	–	Prototype E-Nose (2 gas sensors and SAW sensor		[171]
Lung cancer	–	–	Calorimetric sensor array	LR	[172]
Lung cancer	1	1-Octene	SPME-GC/MS	DFA	[173]
Lung cancer	–	–	Prototype E-nose (8 QCM sensors)	PLS-DA	[174]
Lung cancer	5	Benzene; Styrene; Hexane; Tridecane; Tridecanone	Hybrid E-nose (HENS) (MOS and MOS-SAW sensors)	ANN	[106]
Lung cancer	23	hexadecanal; 2,6,10,14-tetramethylpentadecane; eicosane; 5-(2-methyl-)propylnonane; 7-methylhexadecane; 8-methylheptadecane; 2,6-di-tert-butyl-,4-methylphenol; 2,6,11-trimethyldodecane; 3,7-dimethylpentadecane; nonadecane; 8-hexylpentadecane; 4-methyltetradecane; 2,6,10-trimethyltetradecane; 5-(1-methyl-)propylnonane; 2-methylnaphthalene; 2-methylhendecanal; nonadecanol; 2-pentadecanone; 3,7-dimethyldecane; tridecanone; 5-propyltridecane; 2,6-dimethylnaphthalene; tridecane; 3,8-dimethylhendecane; 5-butylnonane	SPME-GC/MS	LDA	[162]
Lung cancer	5	2-Methyl-1-pentene; 2-Hexanone; 3-Heptanone; Styrene; 2,3,4-Trimethyl-hexane	NMVS (Au NPs and cubic Pt NPs), SPME-GC/MS	DFA	[108]
Lung cancer	4	2-butanone; 3-hydroxy-2-butanone; 2-hydroxy-acetaldehyde; 4-hydroxyhexenal	FT-ICR-MS	W-test	[175]
Lung cancer	4	2-butanone; 2-hydroxyacetaldehyde; 3-hydroxy-2-butanone; 4-hydroxyhexenal	FT_ICR-MS	W-test	[176]
Lung cancer	–	–	DNA hypermethylation markers and Cyranose 320	t test, PCA	[177]
Lung cancer	7	Acetone; Isoprene; Ethanol; 1-propanol; 2-propanol; hexanal; Dimethyl sulfide	GC/MS	ANN	[178]
Lung cancer	10	n-Dodecane; 3-Methyl1-1=Butanol; 2-Hexanol; Cyclohexanon; Iso-propylamin; Cyclohexanon; Ethylbenzol; Hexanal; Heptanal; 3-Methyl-1-butanol	IMS	Plots	[163]
Lung cancer	–	–	Cyranose 320	Regression, DFA	[179]
Lung cancer	3	Acetone; Methyl ethyl ketone; N-propanol	GC‒MS	t test, U test	[180]
Lung cancer	22	Predominantly alkanes, alkane derivatives, and benzene derivatives (Styrene; Heptane, 2,2,4,6,6-pentamethyl; Heptane, 2-methyl; Decane; Benzene, propyl; Undecane; Cyclopentane, methyl; Cyclopropane, 1-methyl-2-pentyl; Methane, trichlorofluoro; Benzene; Benzene, 1,2,4-trimethyl; 1,3-butadiene, 2-methyl- (isoprene); Octane, 3-methyl; 1-hexene; Nonane, 3-methyl; 1-heptene; Benzene, 1,4-dimethyl; Heptane, 2,4-dimethyl; Hexanal; Cyclohexane; Benzene, 1-methylethenyl; Hepatanal)	GC‒MS	Forward-Stepwise DA	[6]
Lung cancer	9	Butane; Tridecane, 3-methyl; Tridecane, 7-methyl; Octane, 4-methyl; Hexane, 3-methyl; Heptane; Hexane, 2-methyl; Pentane; Decane, 5-methyl	GC‒MS	Forward-Stepwise DA	[153]
Lung cancer	3	Aniline; alkanes; benzene derivatives	LibraNose (8 QCM)	PLS-DA	[181]
Lung cancer	11	Styrene; Decane; Isoprene; Benzene; Undecane; 1-hexene; Hexanal; Propyl benzene; 1,2,4-Trimethyl benzene; Hepatanal; Methyl cyclopentane	Prototype E-nose (2 SAW gas sensor)	ANN	[175]
Lung cancer	11	Isobutane; Methanol; Ethanol; Acetone; Pentane; Isoprene; Isopropanol; Dimethylsulfide; Carbon disulfide; Benzene; Toulene	Cyranose 320/GC‒MS	PCA and CDA	[98]
Lung cancer	13	Isoprene; 2-Methylpentane; Pentane; Ethylbenzene; Xylenes; Trimethylbenzene; Toluene; Benzene; Hepatne; Decane; Styrene; Octane; Pentamethylheptane	GC/MS	Multinomial LR	[183]
Lung cancer		36 chemically sensitive spots	Colorimetric sensor array	Random Forest	[184]
Lung cancer	10	16 VOCs (1,5,9-Cyclododecatriene, 1,5,9-trimethyl-; Pentan-1,3-dioldiisobutyrate, 2,2,4-trimethyl; Benzoic acid, 4-ethoxy-, ethyl ester; Propanoic acid, 2-methyl-, 1-(1,1-dimethylethyl)-2-methyl-1,3-propanediyl ester; 10,11-dihydro-5H-dibenz-(B,F)-azepine; 2,5-Cyclohexadiene-1,4-dione, 2,6-bis(1,1-dimethylethyl)-; Benzene, 1,1-oxybis-; Furan, 2,5-dimethyl-; 1,1-Biphenyl, 2,2-diethyl-; 3-Pentanone, 2,4-dimethyl-; trans-Caryophyllene; 1H-Indene, 2,3-dihydro-1,1,3-trimethyl-3-phenyl-; 1-Propanol; Decane, 4-methyl-; 1,2-Benzenedicarboxylic acid, diethyl ester; 2,4-Hexadiene, 2,5-dimethyl-	GC‒MS	Multivariate analysis with FL and MLR	[155]
Lung cancer	4	4 VOCs (Methanol; Acetaldehyde; Acetone; Isoprene)	PTR-MS		[178]
Lung cancer	2	Formaldehyde; Isopropanol	PTR-MS	Fisher’s quadratic DA	[147]
Lung cancer	2	1-butanol; 3-hydroxy-2-butanone	SPME-GC	W-test	[160]
Lung cancer	30	Isopropyl alcohol; 4-Penten-2-ol; Ethane, 1,1,2-trichloro-1,2,2-trifluoro-; Propane, 2-methoxy-2-methyl-; 1-Propene, 1-methylthio)-, (E)-; 2,3-Hexanedione; 5,5-Dimethyl-1,3-hexadiene; 3-Hexanone, 2-methyl-; 1H-Indene,2,3-dihydro-4-methyl-; Camphor; Bicyclo[2.2.1]heptan-2-one, 1,7,7-trimethyl-,(1S)-; 3-Cyclohexene-1-methanol, a,a4-trimethyl-; p-mentha-1-en-8-ol; 5-Isopropenyl-2-methyl-7-oxabicyclo[4.1.0]heptan-2-ol; Isomethyl ionone; 2,2,7,7-Tetramethyltricyclo[6.2.1.0(1,6)]undec-4-en-3-one; 2,2,4-Trimethyl-1,3-pentanediol diisobutyrate; Benzoic acid,4-ethoxy-,ethyl ester; Bicyclo[3.2.2]nonane-1,5-dicarboxylic acid, 5-ethyl ester; Pentanoic acid, 2,2,4-trimethyl-3-carboxyisopropyl, isobutyl ester; Propanoic acid, 2-methyl-, 1-(1,1-dimethylethyl)-2-methyl-1,3-; propanediyl ester; 1,2,4,5-Tetroxane, 3,3,6,6-tetraphenyl-; Benzophenone; 2,5-Cyclohexadien-1-one, 2,6-bis(1,1-dimethylethyl)-4-ethylidene-; Furan, 2-[(2-ethoxy-3,4-dimethyl-2-cyclohexen-1-ylidene)methyl]-; Benzene,1,1-((1,2-cyclobutanediyl)bis-, cis-; Benzene, 1,1-[1-(ethylthio)propylidene]bis-; Anthracene, 1,2,3,4-tetrahydro-9-propyl-; 9,10-Anthracenediol,2-ethyl-; Benzene,1,1-ethylidenebis[4-ethyl-	GC‒MS	WDA	[152]
Lung cancer	4	Isoprene; alkanes; methylalkanes; benzene derivatives	Prototype E-nose (14 Au NP (GNP)	PCA	[186]
Lung cancer	21	2-Butanone; Benzaldehyde; 2,3-Butanedione; 1-Propanol; 2-Butanone, 3-hydroxy-; 3-Butyn-2-ol; Buatne, 2-methyl-; 2-Butene,2-methyl-; Acetophenone; 1-Cyclopentene; Methyl propyl sulfide; Urea, tetramethyl; n-Pentanal; 1,3-Cyclopentadiene,1-methyl-; 2-Butanol, 2,3-dimethyl-; Isoquinoline, 1,2,3,4-tetrahydro-; Undecane, 3,7-dimethyl-; Benzene, cyclobutyl-; Butyl acetate; Ethylenimine; n-Undecane	PTR-MS, SPME-GC/MS	KW-test	[134]
Lung cancer		-Not identified	Cyranose 320	PCA-CDA	[187]
Lung cancer	4	Nonane,5-(2-methyl-)propyl-; phenol,2,6-di-tert-butyl-,4-methyl-; dodecane,2,6,11-trimethyl-; hexadecanal; pentadecane,8-hexyl-	SPME-GC/MS	PCA	[161]
Lung cancer	7	Acetaldehyde; Formaldehyde; Undecane; Isopropene; Methanol; Ethylbenzene; Acetone	Na-Nose	PCA	[188]
Lung cancer	11	Styrene; Decane; Isoprene; Benzene; Undecane; 1-hexene; Hexanal; Propyl benzene; 1,2,4-trimethyl benzene; Heptanal; Methyl cyclopentane	SPME-GC	Corr.	[189]
Malignant mesothelioma	3	8-isoprostane; Hydrogen peroxide; Nitrogen oxide	Cryanose 320	PCA	[204]
Malignant mesothelioma	15	Cyclohexane; Toluene; Xylene; Benzaldehyde; Trimethylbenzene; Limonene; 2-ethyl-1-hexanol; Acetophenone; Cyclopenthane; Dodecanoic; Decane; Methylcyclohexane; Dimethyl-nonanoic; Benzylaldehyde; b-pinene	Cyranose 320	CDA, PCA	[205]
Ovarian cancer	5	Decanal; Nonanal; Styrene; 2-Butanone; Hexadecane	GC/MS	DFA	[200]
Prostate cancer	4	Toluene; 2,3,4-trimethyl decane; p-xylene; 2,2-dimethyl decane	Prototype E-nose (14 GNP)	PCA	[198]
Diabetes
Diabetes	1	Acetone	Prototype E-nose (4CP sensors)	ANN, PCA	[211]
Diabetes	1	Acetone	Prototype E-nose (12 MOS sensors)	PCA	[212]
Gastric-related diseases
Gastric cancer	5	2-Propenenitrile; 2-Butoxy-ethanol; Furfural; 6-Methyl-5-hepten-2-one; Isoprene	GC/MS, Prototype 14 sensor array	DFA	[206]
Gastric cancer	8	2-Propenenitrile; Furfural; 2-Butoxy-ethanol; Hexadecane; 4-Methyl octane; 1,2,3-Tri-methyl-benzene; α-methyl-styrene; 2-Butanone	GC/MS, nanoarray sensor	DFA	[207]
Gastric cancer	12	Pentanoic acid; Hexanoic acid; Phenol; Methyl phenol Ethyl phenol; Butanal; Pentanal; Hexanal; Heptanal; Octanal; Nonanal; Decanal	SIFT-MS	U test	[208]
Gastric Cancer	5	2-Propenenitrile; 6-Methyl-5-Hepten-2-one; Furfural; 2-Ethyl-1-Hexanol; Nonanal	Silicon-NW FET sensors	DFA	[209]
GORD	2	Pepsin, pH	Cryanose 320	PCA, CDA	[224]
Heart-related diseases
Chronic heart failure	1	Isoprene	GC/MS	MWR-test	[225]
Ischemic heart disease	3	Plasma malonidialdehyde; Propane; Isoprene	HPLC	Fisher's exact test	[226]
Ischemic heart disease	1	Pentane	SPME-GS	U test, Corr.	[30]
Liver diseases
Hemodialysis	1	Isoprene	GC	t test	[22]
Ischemic liver disease	1	Ethane	GC	Var.	[27]
Liver transplant	7	Carbonyl sulphide; Dimethyl sulphide; Dimethyl disulphide; Carbon disulphide; Three congeners of Allyl methyl sulphide	GC	LR, MLR	[232]
Neurodegenerative diseases/disorders
Parkinson's disease (PD)	7	Styrene; 2,3,6,7-tetramethyl-octane; Butylated hydroxytoluene; 5-ethyl-2-methyl-octane; Decamethyl-cyclopentasiloxane; Ethylbenzene; 1-methyl-3-(1-methylethyl)benzene	NMVS (C-nt and GNP)	DFA	[266]
Alzhiemer	24	Styrene; 1-methyl-2-(1-methylethyl)-benzene; 4-methyloctane; 2,6,10-trimethyldodecane; 3,7-dimethyldecane; Butylated hydroxytoluene; 2,4-dimethyl-1-heptene; 2,3-dimethylheptane; Propyl-benzene; 2,2,4,6,6-pentamethylheptane; 2,5,6-trimethyloctane; 5-ethyl-2-methyloctane; 2,6,10,14-tetramethylhexadecane; 3,7-dimethyl-propanoate (E)-2,6-octadien-1-ol; 2,3,5-trimethylhexane; (1-methylethyl)benzene; (1-methylpropyl)cyclooctane; 2,2-dimethylpropanoic acid; 2-ethylhexyl tetradecyl ester oxalic acid; 2-butyl-1-octanol; Dodecane; 1-chloro-nonadecane; 3-ethyl-2,2-dimethylpentane; 1,1’-oxybis-octane). Seven VOCs were discovered in the same study that separated PD patients' breath samples from healthy people’s which could be the potential biomarkers for PD (Styrene; 2,3,6,7-tetramethyl-octane; butylated hydroxytoluene; 5-ethyl-2-methyl-octane; decamethyl-cyclopentasiloxane; ethylbenzene; 1-methyl-3-(1-methylethyl)benzene)	NMVS (C-nt and GNP)	DFA	[266]
Oral health issues
Halitosis		Sulphides	FF -1 (6 MOS sensors)	LR	[281]
Halitosis		Sulphides	FF -1 (6 MOS sensors)	LR	[282]
Halitosis	3	Hydrogen sulfide; Butyric acid; Valeric acid	Prototype E-nose (7QCM sensor)	PCA	[280]
Oral cavity	1	Gaseous Ethanol	Sniff-CAM: Gas imaging system	Image analysis	[283]
Renal diseases
Uremia	3	Dimethylamine; Trimethylamine; Ammonia	Prototype E-nose (6 QCM sensors)	PCA	[284]
Respiratory/lung diseases
Asthma	1	Nitrogen oxide	Cyranose 320 (32 CP sensors)	PCA, ANN	[247]
Asthma	1	Nitrogen oxide	LibraNose	PCA, ANN	[248]
COPD	6	Nitric oxide; Hydrogen peroxide; Aldehydes; 8-isoprostane; Nitrotyrosine; Cytokines	Cryanose 320	LDA	[253]
COPD	1	Ethane	GC	Corr.	[252]
Pneumonia	1	Bacterial metabolites	DiagNose (12 MOS sensors)	PCA, LR	[257]
Tuberculosis	4	Methyl phenylacetate; Methyl nicotinate; Methyl p-anisate; o-phenylanisole	SPME-GC/MS		[237]
Tuberculosis	4	Methyl phenylacetate; Methyl nicotinate; Methyl p-anisate; o-phenylanisole	E-nose [14 CP sensors]	PCA, DFA, ANN	[238]
Tuberculosis	–	–	DiagNose (12 MOS sensors)	ANN	[240]
Tuberculosis	14	Cyclohexane, 1,3-dimethyl- trans-; Benzene, 1,4-dichloro-; Cyclohexane, 1,4-dimethyl-; 1-Octanol, 2-butyl-; 2-Butanone; Naphthalene, 1-methyl-; Camphene; Decane, 4-methyl-; Heptane, 3-ethyl-2-methyl-; Octane,2,6-dimethyl-; Benzene, 1,2,3,4-tetramethyl-; Bicyclo_3_1_1_hept-2-ene, 3,6,6- trimethyl-; Cyclohexane, 1-ethyl-4-methyl-, trans-; l-beta_-Pinene	GC/MS	FL, Pattern recognition	[239]
Smoking	6	Acetaldehyde; Propionaldehyde; Acetone; Methyl ethyl ketone; Methanol; Acetonitrile	GC	t test	[290, 291]

Au gold, C-nt carbon nanotube, CP conducting polymer sensor, FTR-IC-MS Fourier transform-ion cyclotron resonance-mass spectrometry, GC gas chromatography, GC/MS gas chromatography‒mass spectrometry, GNP gold nanoparticle, HPLC high-performance liquid chromatography, IMS ion mobility spectrometry, MOS metal oxide sensors, MS mass spectrometry, NA-NOSE nanoscale artificial nose, NMVS nanomaterial-based sensors, NT nanotube, Pt platinum, PTR-MS protein-transfer-reaction mass spectrometry, QCM quartz crystal microbalance sensor, SAW sound acoustic wave sensor, SIFT-MS selected ion flow tube mass spectrometry, SPME solid phase microextraction, ANN Artificial neural network, ANOVA Analysis of variance, CDA Canonical discriminant analysis, Corr. correlation analysis, DA discriminant analysis, DFA discriminant factor analysis, FL fuzzy logic, KW-test Kruskal‒Wallis test, LDA linear discriminant analysis, LR logistic regression, MC Monte Carlo simulations, MLR multiple linear regression, MWR-test Mann‒Whitney rank sum test, PCA principal component analysis, PNN probabilistic neural network, QDA quadratic discriminant analysis, SVM support vector machine, t test Student’s t test, U test Mann‒Whitney U test, Var. Variance analysis, WDA Weighted digital analysis, W-test Wilcoxon test

Cancer

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 [146–149] 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].

Lung Cancer

The majority of exhaled breath analysis studies are focused on lung cancers. Various pilot studies [64, 129, 134, 152–156] 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, 160–189], 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.

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.

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].

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].

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.

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].

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.

Gastric Cancer

Various studies have been performed to identify potential biomarkers to diagnose gastric cancers [206–209]. 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].

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, 210–212]. 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 [215–218]. 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 [219–222]. These findings, however, are based on research with a very small population, therefore a reliable standalone biomarker for T2DM has not yet been identified.

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.

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].

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.

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].

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].

Respiratory/Lung Diseases

Exhaled breath has the greatest potential for diagnosing the respiratory system [236–259]. 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].

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.

Asthma

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

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.

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].

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].

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].

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 [261–264]. 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 CS₂ (neurotoxin) and pentane, a marker of lipid peroxidation, were observed in the breath samples of patients with schizophrenia [275]; however, the origin of CS₂ 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.

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].

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 [280–282] 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].

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].

Environmental or Mechanism-Based Exhaled VOCs

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].

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].

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.

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].

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 [296–299], 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].

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) [304–306], 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.

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 [309–311]. However, more research is needed to assess the findings and apply them to clinical diagnosis.

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].

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].

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.

Declarations

Conflicts of interest

The authors have no conflicts of interest.

Funding

The authors are thankful to the Ministry of Human Resource Development (MHRD), Government of India, for providing financial support as a monthly Research Scholarship. There is no other funding to report.

Ethics approval

Not applicable.

Consent (participate and publication)

Not applicable.

Data availability statement

Not applicable.

Code availability

Not applicable.

Author’s Contributions

Conceptualization: AS, PV; methodology and data curation: AS; writing—original draft preparation: AS; writing—review and editing: AS, RK, PV; supervision: PV; All authors have read and agreed to the final manuscript.