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Journal of Analytical Methods in Chemistry
Volume 2019, Article ID 7247802, 14 pages
https://doi.org/10.1155/2019/7247802
Review Article

Volatile Organic Compounds as Biomarkers of Gastrointestinal Diseases and Nutritional Status

1IRCCS Mondino Foundation, Pavia 27100, Italy
2Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia 27100, Italy
3Endocrinology and Nutrition Unit, Azienda di Servizi alla Persona “Istituto Santa Margherita”, University of Pavia, Pavia 27100, Italy
4Department of Biomedical Sciences and Human Oncology, University of Bari Aldo Moro, Bari 70121, Italy
5General Management, Azienda di Servizi alla Persona “Istituto Santa Margherita”, Pavia 27100, Italy
6Department of Biology, College of Science, University of Bahrain, Sakhir Campus P.O. Box 32038, Zallaq, Bahrain
7Department of Medicine and Surgery, University of Milano-Bicocca, Milano 20126, Italy

Correspondence should be addressed to Gabriella Peroni; ti.aivapidatisrevinu@10inorep.alleirbag

Received 7 June 2019; Accepted 24 July 2019; Published 10 September 2019

Academic Editor: Eliseo Herrero-Hernández

Copyright © 2019 Mariangela Rondanelli et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose. The purpose of this review was to identify the best solution for rapid and noninvasive diagnosis and long-term monitoring of patients affected by inflammatory gastrointestinal diseases, colon and gastric cancer, obesity in correlation to diet, and breast milk to evaluate exposure to VOCs in women and infants. Methods. This review included 20 previously published eligible studies. VOC analysis has allowed us to highlight differences in lifestyles, intestinal microbiota, and metabolism. New innovative methods have been described that allow the detection and quantification of a broad spectrum of metabolites present in exhaled breath even at very low levels, some of which have been shown to be indicators of pathological conditions. Results. Five studies were analyzed that involved VOC analysis in relation to type of diet. All of them showed that the type of diet can have an impact on metabolites excreted and therefore can be a useful tool in the nutritional studies related to metabolism and health and disease status. Two studies concerned VOC analysis in inflammatory bowel diseases, and the results showed that VOCs can distinguish active disease from remission; VOC profile is clearly different in patients. In particular, C15H30 1-pentadecene, 3-methyl-1-butanal, octane, acetic acid, alpha-pinene, and m-cymene are elevated in active ulcerative colitis. Four studies examined VOCs in gastric and colorectal tumors showing a change in metabolic biomarkers of cancer patients compared to the control group. Finally, the study of VOCs in breast milk has improved the understanding of the potential health risks of exposure of children to chemical pollutants. Conclusions. VOC analysis allowed to highlight differences in behavior, lifestyle, and metabolism of individuals. Analytical methods are continuously developed to allow for better detection and quantification of metabolites, thus enabling the detection of a broader spectrum of pathophysiology and disease biomarkers.

1. Introduction

Intermediate products of metabolism are considered biomarkers specific to human clinical and nutritional status and therefore can be a useful diagnostic support to monitoring metabolic disease, including chronic inflammatory disease and gastrointestinal disease, using noninvasive methods. In fact, it is possible to construct specific metabolic profiles for volatile organic compounds (VOCs) with low-molecular weight, which are divided into the gaseous phase by the alveolar blood and appear in the exhaled breath. Breath analysis is a noninvasive and sensitive medical diagnostic tool and offers the possibility of rapid measurements, thanks to the development of more robust analytical methods that allow the detection of volatile metabolites present in the breath at low concentrations [1]. Breath collection offers a method for assessing VOCs not only in blood but also in feces, milk, saliva, and urine, thus providing information on the state of health of the lung, the gastrointestinal tract, and urinary tract, respectively. The origin of intermediate products is not yet fully understood. Some VOCs present in the breath are not found in the blood, urine, or saliva, so it is thought that some organs are involved in their conversion. In particular, the liver is an organ that can be involved in the conversion of VOCs present in the bloodstream bringing the concentration of VOCs under the detectable level and increasing the concentration of new VOCs in the blood flow. VOCs produced from the fecal matter in the gastrointestinal tract can be transported into the blood and eventually reach the lungs and appear in breath. However, they may not be detected in the breath due to conversion in the liver. In fact, the human liver has an array of highly specific enzymes that are able to oxidize nonpolar compounds to more polar, hydrophilic compounds that are easily removed through the excretory system. In addition to the liver, other organs like the lungs, kidneys, and bladder may have biotransformation activities. Furthermore, evidence of VOCs transformation is also reported in the nose [2].

No single analytical method is sufficient for measuring all the VOCs present in the bodily fluids and in the breath. Gas chromatography by mass spectrometry technique (GC-MS) is the method mainly used; however, other methods including proton-transfer-reaction mass spectrometry (PTR-MS) and selected ion flow tube mass spectrometry (SIFT-MS) are very much used in the characterization of VOCs. Methods involving solvent extraction techniques have been used in studies of VOCs in milk. The GC-MS technique in association with sample collection and concentration techniques such as solid phase microextraction (SPME) and thermal desorption has provided promising results [3]. The reproducibility of SIFT-MS analyses of VOCs had been previously evaluated by determining the variability coefficients for acetone, ammonia, isoprene, propanol, ethanol, acetic acid, and cyanitrate [46].

For example, in the study by Martin et al. [4], the SPME technique in combination with GC-MS was used for the analysis of VOCs in samples of human breath without collecting and condensing the exhaled breath. The authors of the study described a new procedure that involves active sampling and preconcentration of exhaled breath vapor (EBV) and respiratory vapor collection with a modified SPME Fiber, mounted within a range of commercial products the RTube™. Immediately after sample collection, at −80°C and at room temperature, the compounds are desorbed from the SPME Fiber in the GC-MS injector at 250°C. The methods were compared in terms of ease of use, speed of analysis, and limits of detection. A supply of clean air was needed for the study subjects, as demonstrated using several localized sources of VOC contaminants including nail polish, lemonade, and gasoline. The authors of the study concluded that the SPME method offers advantages in terms of collection and analysis of EBV, field-portability, elimination of power or cooling requirements, and ability to perform sample collection in a contaminated environment.

Another technique used for the analysis of VOCs is the use of electronic noses (eNoses), which provide fingerprints of VOCs exhaled, called breathprints [7]. It has been shown that the breathprints are modified according to different pathological states such as asthma and chronic obstructive pulmonary disease (COPD). In their study, the authors describe the application of electronic noses in the analysis of exhaled breath, as a rapid and noninvasive diagnostic tool, in the diagnosis and monitoring of chronic diseases of the respiratory tract. Furthermore, they recommended the construction of a database comprising of disease-specific breathprints.

In particular, some authors [8] have recently evaluated the ability of eNose to detect airway inflammation such as chronic obstructive sleep apnea (OSA), a pathology often associated with obesity, which is becoming a world epidemic. The authors demonstrated how using the electronic nose allowed the rapid analysis of VOC spectra. The authors Dragoneri et al. [9] demonstrate in another study that the electronic nose can detect obstructive sleep apnea (OSA) such as chronic obstructive pulmonary disease (COPD). Sometimes, OSA and COPD are associated in the so-called overlap syndrome (OVS). In this pilot study, the authors hypothesize that the electronic nose could discriminate the exhaled breath of OVS patients from that of subjects with OSA and COPD alone. In particular, 13 patients with OSA, 15 patients with COPD, and 13 with OVS participated in a cross-section study. The exhaled breath was collected by a previously validated and sampled method using an electronic nose (Cyranose 320). Raw data were analyzed by canonical discriminant analysis on principal component reduction. Cross-validation accuracy (CVA) and ROC-curves were calculated. Breathprints of patients with clustered OSA distinctly from those with OVS (CVA = 96.2%) as well with those with COPD (CVA = 82.1%). Breathprints from OVS were not significantly separated from those of COPD (CVA = 67.9%). External validation in newly recruited patients (6 OSA, 6 OVS, and 6 COPD) was tested using the previous training set. The authors concluded that the electronic nose can accurately distinguish the exhaled VOC profile of patients with OSA from those with OVS and those with COPD. It was also reported that the exhaled breath of obese patients with OSA differed from that of nonobese controls. The study evaluated the influence of obesity on the composition of exhaled VOCs by comparing obese subjects with and without OSA and identified the discriminating VOCs in the two groups. The exhaled breath was collected and analyzed using eNose and GC-MS. The authors highlighted how the presence of OSA altered the pattern of exhaled VOCs in obese subjects. They proposed that the incomplete separation of breathprints may be due to the underlying inflammation.

In the present study, a research was carried out to evaluate how the analysis of VOCs can be used in clinical practice for rapid and early diagnosis and for the long-term monitoring of patients suffering from various diseases, focusing our attention on inflammatory gastrointestinal diseases, colorectal and gastric cancer, obesity in correlation with diet, and breast milk to assess the exposure to VOCs of lactating women and infants.

2. Materials and Methods

The present systematic review was performed following the steps by Egger et al. [10] as follows: (1) a working group was configured as follows: three operators skilled in clinical nutrition, of whom one acting as a methodological operator and two participating as clinical operators; (2) the revision question on the basis of considerations made in the abstract was formulated as follows: “the state of the art on role on VOCs in the nutritional field focusing in particular on the analysis of VOCs in gastrointestinal diseases, colon and gastric cancer, breast milk, obesity and correlation with diet,” (3) relevant studies were identified as follows: a research strategy was planned, on PubMed (Public Medline run by the National Center of Biotechnology Information (NCBI) of the National Library of Medicine of (USA)) as follows: (a) definition of the key words (volatile organic compounds, gastrointestinal diseases, colon and gastric cancer, breast milk, obesity, and diet), allowing the definition of the interest field of the documents to be searched, grouped in quotation marks (“. . .”) and used separately or in combination; (b) use of the Boolean AND operator that allows the establishment of logical relations among concepts; (c) research modalities: advanced search; (d) limits: time limits: papers published in the last 30 years; languages: English; (e) manual search performed by the senior researchers experienced in clinical nutrition through revision of reviews and individual articles on VOCs in the nutritional field focusing in particular on the analysis of VOCs in gastrointestinal diseases, colon and gastric cancer, breast milk, obesity, and correlation with diet in published in journals qualified in the Index Medicus; 4. the analysis was carried out in the form of a narrative review of the reports.

3. Results

Figure 1 shows the flowchart of the study selection process, while Table 1 summarizes the studies presented in the narrative review.

Figure 1: Study selection process.
Table 1: Studies presented in the narrative review.
3.1. Breast Milk

The study by Blount et al. [17] provides an in-depth evaluation of methods for collecting and analyzing human breast milk samples for the presence of VOCs.

This study describes the development and validation of methods for collecting, storing, and analyzing 36 different VOCs in breast milk to evaluate the exposure to VOCs of lactating women and nursing infants. The loss of volatile analyzed was minimized by collecting and storing 3 mL samples in small containers resulting in 70% recovery for all 10 VOCs detected in the majority of breast milk samples collected from 12 women. Potential contamination from chloroform, benzene, toluene, ethylbenzene, xylenes, and methyl-tert-butyl ether was reduced to a minimum with the collection materials. The detection of the method was obtained using SPME and selective monitoring of mass spectrometry ions. The authors reported that 10 of the 36 VOCs were detectable in most samples, namely, m/p-xilene (0.539 ng/mL), toluene (0.464 ng/mL), 1,4-dichlorobenzene (0.170 ng/mL), tetrachlorethylene (0.165 ng/mL), o-xylene (0.159 ng/mL), ethylbenzene (0.0149 ng/mL), styrene (0.129 ng/mL), benzene (0.080 ng/mL), chloroform (0.030 ng/mL), and methyl-tert-butyl ether (0.016 ng/mL).

Measuring the levels of VOCs in milk makes it possible to better understand the exposure of infants to chemical pollutants and the potential risk to health. However, the collection and analysis of milk for these compounds are difficult, and robust methods are needed for accurate assessments of child exposure. The presence of lipids is a characteristic of milk that presents many challenges in ensuring an unbiased analysis of VOCs. The relatively high lipid content compared to other biological matrices (e.g., blood and urine) means that milk is more susceptible to contamination through contact with air and laboratory materials commonly used for collection, storage, and analysis of samples. As a result, the collection and storage of samples in sealed containers are important. Furthermore, adequate control samples are crucial for the identification of analytes, including furan, methyl tert-butyl ether (MTBE), tetrachloroethylene, and toluene. Using the methods described in this study, a wide range of VOCs can be accurately quantified in human milk.

3.2. Diet

Regarding the study of VOCs and the effect of diet on them, some works have been found in the literature. For example, Raninen et al. [12] performed a pilot study on exhaled breath to evaluate the metabolic effects of dietary fiber (DF). In particular, they hypothesized that a diet high in DF containing whole grain may increase the levels of VOCs. In the exhaled breath, 2-methylbutyric acid and 1-propanol decreased at 120 minutes postprandial with the high DF diet, while an increase in ethanol, 1-propanol, acetoin, and propionic acid was observed in patients with the high DF diet. The results of this study suggest that exhaled breath is one matrix used to study the metabolic effects of DF. The high DF rye diet had an effect on the VOCs present in the exhaled breath although the changes in many compounds were individual. Furthermore, by consuming only one meal, an effect was noted on the levels of VOCs, which were indicative of the digestion status of patients, a factor that must be taken into account in the studies on the metabolic effects of nutrients.

Vuholm et al. [11] investigated whether whole-grain wheat (WGW) and whole-grain rye (WGR) improve gut health compared to refined wheat (RW) with the primary outcomes of microbiota composition and gastrointestinal symptoms. The authors reported that the microbiota composition was not affected by diet and that fecal butyrate concentrations decreased in the RW group compared to the WGW and WGR groups. The study concluded that regular consumption of WGR and WGW affected butyrate production and gastrointestinal symptoms and supporting the hypothesis that WGR and WGW can be included in diet equally to maintain gut health. In the same study, respiratory hydrogen was evaluated using a handheld Gastro + Gastrolyzer® (Bedfont Scientific Ltd.) measuring in parts per million (ppm). The subjects were instructed to take a deep breath, hold it for 15 seconds, and exhale steadily in the plastic mouthpiece of the device. Analysis of breath hydrogen concentration was performed during the fasting level and at the peak value, defined as the highest measured hydrogen value within 4 hours of ingesting the disaccharide solution. Subjects were accordingly grouped as hydrogen producers and nonproducers. The findings of the study revealed that fasting level and peak value of breath hydrogen did not differ in any of the diet groups when analyzed as the relative change from baseline to week 6. The number of nonhydrogen producers (subjects with an increase <20 ppm) were equally distributed between diet groups, and excluding the subjects from the analyses did not change the results.

Another study by Baranska et al. [13] examined the profile of VOCs excreted in exhaled breath of 20 healthy individuals over a 13-week period while adhering to a gluten-free diet for 4 weeks before adhering to a normal diet. Thermal desorption gas chromatography combined with time-of-flight mass spectrometry (TD-GC-tof-MS) was used in combination with chemometric analysis to detect a mixture of VOCs in the exhaled breath. Dietary intake was assessed during the study to confirm adherence to the diet and to obtain a better insight into differences in macronutrient intake during the intervention period. A set of 12 VOCs distinguished the samples obtained during the gluten-free diet from those obtained during a normal diet. Seven compounds could be chemically identified (2-butanol, octane, 2-propyl-1pentanol, nonanal, dihydro-4-methyl-2 (3H)-furanone, nonanoic acid, and dodecanal). The results suggest that a gluten-free diet has a reversible impact on the excreted metabolites of the participants as evident in their breath. Several explanations are proposed on the influence of the metabolic state through the diet, although the exact origin of the discriminating compounds is not yet known. The authors managed to demonstrate a new potential use of exhaled air analysis, which represents a useful tool in the fields of nutrition and metabolism.

There are relatively few studies that have highlighted the urinary metabolic signature in relation to excess body weight and obesity. Cozzolino et al. [14] evaluated the urinary VOCs profile of 21 overweight/obese subjects (OW/Ob) and 28 children of normal weight (NW) from the Italian cohort of the I. Family study. Urine samples were analyzed by SPME GC-MS under acid and alkaline conditions to profile a VOC library of urinary metabolites with different physicochemical properties. The authors used multivariate statistical techniques to visualize case clusters and detect VOCs that differentiated OW/Ob from NW children. Fourteen VOCs were identified, in alkaline conditions, which appeared to be pivotal in distinguishing OW/Ob from NW children. The results suggested a difference in the VOCs profile between OW/Ob and NW children. Nevertheless, the authors of the study concluded that the biological and pathophysiologic significance of the observed differences should still continue to be investigated, in order to better understand the potential of urinary VOCs as early metabolic biomarkers of childhood obesity.

Another recent study [15] described a high-throughput quantitative analytical method for the simultaneous measurement of small aliphatic nitrogen biomarkers, i.e., 1,6-hexamethylenediamine (HDA), isophoronediamine (IPDA), p-methylamino-1-alanine (BMAA), and trimethylamine N-oxide (TMAO), in human urine. The urinary metabolites, 1,6-hexamethylenediamine (HDA) and isophoronediamine (IPDA), are biomarkers of environmental exposure to their corresponding diisocyanates, while β-methylamino-l-alanine (BMAA) is formed as a result of human exposure to food contaminated with blue-green algae. Trimethylamine N-oxide (TMAO) is excreted in the urine due to the consumption of diets rich in carnitine and choline, which include animal products and by-products. All of these urinary biomarkers represent classes of small aliphatic nitrogen-containing compounds that have a high aqueous solubility, low logP, and/or high alkaline pKa. Because of their highly polar nature, the analysis of these compounds in complex sample matrices is often challenging. In the aforementioned study, the authors used ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for simultaneous measurement of VOCs in human urine. Optimization of separation was obtained using heptafluorobutyric acid as a mobile phase and carried out on reversed-phase C18 column. The four analytes were baseline separated within 2.6 minutes with a total run time of 5 minutes, and the detection limits ranged between 0.05 and 1.60 parts per billion (ppb). All samples were acid-hydrolyzed for 4 hours and treated, prior to analysis, by solid-phase extraction (SPE) using a strong cationic sorbent bed with 7N ammonia solution in methanol as eluent. The authors concluded that this method can be applied to determine human exposure to HDI, IPDI, BMAA, and carnitine/choline in population-based studies, such as the National Health and Nutritional Examination Survey (NHANES), in addition to other clinical studies that desire noninvasive urine sampling.

Another similar study was conducted by Alkhouri et al. [16] who used SIFT-MS to evaluate exhaled breath VOCs from OW/Ob children compared to lean children. The results showed differences in concentration of more than 50 compounds between the obese group and the lean controls. The authors identified four VOCs, namely, isoprene-1decene, 1-octene, ammonia, and hydrogen sulphide, that were significantly higher in the obese group compared to lean the group. They concluded that obese children have a unique pattern of exhaled VOCs, which can be utilized in the screening of obesity-related comorbidities, as well as gaining insight into the process and pathways leading to the development of childhood obesity.

3.3. Inflammatory Bowel Disease

Smolinska et al. [18] evaluated the potential of VOCs for detecting active disease in patients with ulcerative colitis (UC). Current practice involves the endoscopic assessment of mucosal inflammation to optimise treatment of UC. Nevertheless, simple, inexpensive, and effective tool for the assessment of mucosal inflammation is desirable. Detection of exhaled VOCs may serve as a noninvasive approach for Chron’s disease diagnosis. In their study, the authors concluded that VOCs can accurately distinguish active disease from remission in UC, and profiles in UC were distinctly different from profiles in non-UC patients. In particular, C15H30 pentadecene, 3-methyl-1-butanol, octane, acetic-acid, alfa-pinene, and m-cymene were elevated in the active UC group.

Another study [19] evaluated fecal VOCs in healthy donors and patients with gastrointestinal disease. The authors of that study hypothesized that VOCs would be shared in health; VOCs would be constant in individuals; and specific changes in VOCs would occur in the disease. VOCs by the asymptomatic donors were analyzed and identified by SPME GC-MS in a cohort and in a longitudinal study. Subsequently, the fecal VOCs found in the cohort study were compared with that found in patients with ulcerative colitis, Campylobacter jejuni and Clostridium difficile. A total of 297 VOCs were identified in the cohort study, among them, ethane, butanoic, pentanoic acid, benzaldehyde, ethanol, carbon disulfide, dimethyldisulphide, acetone, 2-butanone, 2,3-butanedione, 6-methyl-5-hepten-2-one, indole, and 4-methylphenol were present in all the samples. Moreover, the results showed that the majority of donors (80%) shared 44 VOCs in the cohort study. In the longitudinal study, 292 volatiles were identified, with some inter- and intradonor variations of VOC concentrations over time. In comparison to healthy donors, the fecal VOCs of patients with UC, C. difficile, and C. jejuni were reported to be significantly different [19].

3.4. Gastrointestinal Cancer

Recently, several studies have focused on the connection between the composition of specific VOCs in exhaled breath and various forms of cancer. In particular, a study by Wang et al. [20] on 16 colorectal cancer (CRC) patients showed a change in metabolic biomarkers compared to the control group. CRC patients were reported having lower levels of phenyl methylcarbamate, ethylhexanol, and 6-t-butyl-2,2,9,9-tetramethyl-3-5-decadien-7-yne, while having high levels of 1,1, 4,4,-tetramethyl-2,5-cyclohexane-dimethilene. The analysis of blood VOCs appears to have clinical applications for CRC patients.

Another study [23] investigated whether patients with colorectal cancer have a specific VOC compared with the healthy population. Exhaled breath was collected in an inert bag from patients with colorectal cancer and healthy controls and processed offline by thermal-desorber gas chromatography-mass spectrometry to evaluate the VOC profile. During the trial phase, VOCs of interest were identified and selected, and VOC patterns able to discriminate patients from controls were set up; in the validation phase, their discriminant performance was tested on blinded samples. A probabilistic neural network (PNN) validated by the leave-one-out method was used to identify the pattern of VOCs that better discriminated between the two groups. 37 patients and 41 controls were included in the trial phase. Application of a PNN to a pattern of 15 compounds showed a discriminant performance with a sensitivity of 86 per cent, a specificity of 83 per cent and an accuracy of 85 per cent. The pattern of VOCs in patients with colorectal cancer was different from that in healthy controls. The PNN in this study was able to discriminate patients with colorectal cancer with an accuracy of over 75 per cent. Breath VOC analysis appears to have potential clinical application in colorectal cancer screening.

Two further studies highlighted the correlation between VOCs and gastric cancer (GC). Leja et al. [21] demonstrated that although VOCs measurements were well reproducible in GC patients, and specific modifications of the intestinal microbiome may have influenced the VOC results. The authors concluded that gastrointestinal interventions, including the use of antibiotics in Helicobacter pylori eradication and bowel cleansing for colonoscopy, could potentially affect the diagnostic accuracy of breath VOCs. The other study by Kumar et al. [22] used SIFT-MS to monitor the VOCs in the exhaled breath of 81 patients with esophageal or gastric adenocarcinoma and 129 healthy controls. VOC levels of pentanoic acid, hexanoic acid, phenol, methyl phenol, ethyl phenol, butanal, pentanal, hexanal, heptanal, octanal, nonanal, and decanal were reportedly to be significantly higher in the cancer group compared to the noncancer controls (). In addition, the authors of the study were able to distinguish patients with esophageal and gastric adenocarcinoma from healthy control subjects through their specific VOCs profiles.

4. Discussion

This narrative review of the recently published literature indicates that breath analysis is a noninvasive method for assessing individuals’ health or disease status and provides support for clinical trials, diagnosis, and therapeutic monitoring. The exhaled breath is a complex mixture of low-molecular weight VOCs that are derived from the diet and endogenous metabolism or from the microbiota of the gastrointestinal and respiratory tracts. Metabolic, inflammatory, and neoplastic conditions are associated with characteristic respiratory profiles, and breath analysis has been identified as a potentially simple and noninvasive method for the screening and monitoring of pathological or metabolic disorders such as asthma, diabetes mellitus, obesity, and cancer. Compared to the study of the subjects’ health status, with traditional biomarkers, the analysis of VOCs reflects the individual’s fingerprint and represents an example of personalized medicine. However, there are a number of factors that influence the concentrations of VOCs in the exhaled air, including diet, nutritional status, physical activity, and smoking habits. Analysis of VOCs allows to highlight the differences in behaviour and lifestyle habits and variations in the metabolism of individuals. Analytical methods are continuously being improved which allows for better detection and quantification of the metabolites. This, in turn, will allow for the identification of a wide spectrum of biomarkers present in exhaled breath even at very low levels, some of which may be indicators of pathologies. In order to improve this research, it is necessary to give greater emphasis to the identification and quantification of disease biomarkers through further development of more sensitive analytical methods capable of analyzing exhaled breath in real time and avoiding contamination by exogenous compounds. Furthermore, to apply breath analysis to studies in human nutrition, it is imperative to consider any concomitant comorbidity, and breath sampling should take place under standardized conditions, for example, after an overnight fast with daytime monitoring.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

SP and TAA were responsible for critical revision and drafting of the manuscript. MR, FP, and CC involved in the study concept and design. VI, GP, and SN were responsible for acquisition and interpretation of data. AR, PA, CG, MAF, and MN critically revised the article. All authors read and approved the final manuscript.

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