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In contrast to blood and urine samples, breath is invisible and ubiquitous in the environment. Different precautions are now necessary beyond the usual 'Universal Precautions'. In the era of COVID-19, breath (especially the aerosol fraction) can no longer be considered as harmless in the clinic or laboratory. As Journal of Breath Research is a primary resource for breath-related research, we (the editors) are presently developing safety guidance applicable to all breath research , not just for those projects that involve known COVID-19 infected subjects. We are starting this process by implementing requirements on reporting safety precautions in research papers and notes. This editorial announces that authors of all new submissions to JBR henceforth must state clearly the procedures undertaken for assuring laboratory and clinical safety, much like the existing requirements for disclosing Ethics Committee or Institutional Review Board protocols for studies on human subjects. In the following, we additionally make some recommendations based on best practices drawn from our experience and input from the JBR Editorial Board.

Breath analysis is the study of volatile organic compounds (VOC's) in exhaled breath. This analysis provides information on the body's condition. In this study we investigated the relationship between 22 VOC's detected in exhaled breath and plasma headspace using a selected ion flow tube mass spectrometer (SYFT-MS). We compared pairs of exhaled breath and plasma samples from patients with pulmonary hypertension inflammatory bowel disease (IBD), and IBD patients after J-pouch surgery (pouch group). Half of the measured VOC's from exhaled breath were significantly associated with the VOC's from plasma headspace. Interestingly, six breath VOC's (trimethyl amine (FDR p = 0.02), hydrogen sulfide (FDR p = 7.64 × 10 -30 ), ethanol (FDR p = 1.56 × 10 -4 ), dimethyl sulfide (FDR p = 5.70 × 10 -19 ), benzene (FDR p = 8.40 × 10 -27 ), and acetaldehyde (FDR p = 4.27 × 10 -17 )) and two plasma headspace VOC's (1-Octene (FDR p = 0.02) and 2-propanol (FDR p = 2.47 × 10 -9 )) were able to differentiate between the three groups. Breath and plasma headspace share a similar signature with significant association in half of the measured VOCs. The disease discriminatory capacity of breath and plasma headspace appear to be different. Therefore, using the VOC's print from both breath and plasma headspace may better help diagnose patients.

Volatile organic compounds (VOCs) are generated during pathologic processes, and their assessment can be used to diagnose and monitor a variety of diseases. Given the role of the microbiome in graft-versus-host disease (GVHD), we hypothesized that microorganisms producing volatile metabolites may alter VOCs expelled in breath in patients with gastrointestinal (GI) GVHD. In this pilot study, exhaled breath samples were obtained from 19 patients with grade 2 to 4 acute GI GVHD, 10 patients with no GVHD at day 100, and 10 healthy control subjects; the samples were analyzed by using mass spectrometry. Overall, nine (47%) patients had grade 2 GVHD, eight (42%) patients had grade 3 GVHD, and two (11%) patients had grade 4 GVHD; 26% had upper GI, 21% had lower GI, and 53% had both upper and lower GI manifestations. Stepwise canonical discriminant analysis identified 5 VOCs distinguishing patients with and without GI GVHD: 2-propanol, acetaldehyde, dimethyl sulfide, isoprene, and 1-decene (Wilks' Λ, 0.43; F statistic, 6.08; P = .001). The model correctly classified 89% (17 of 19) and 90% (9 of 10) of patients with and without GI GVHD, respectively. Breath analysis is a feasible and promising noninvasive method to detect acute GI GVHD. Further study of serial breath analysis and the gut microbiome in a larger cohort are ongoing to validate these findings., (© 2019 by The American Society of Hematology.)

Many uremic solutes retained in chronic kidney disease are volatile, and can be detected by breath testing. We compared the exhaled breath of subjects with end stage renal disease (ESRD) to healthy volunteers to identify volatile compounds that can serve as a potential breathprint for renal failure. We analyzed the exhaled breath of 86 ESRD subjects and 25 healthy volunteers using selected-ion flow-tube mass spectrometry (SIFT-MS). Using a random forests classification model, we identified three known volatiles (2-propanol, ammonia, acetaldehyde) and two unknown volatiles ([Formula: see text] NO + 76) that were highly significant for discriminating individuals with renal failure from individuals without renal failure (C statistic > 0.99). This study provides preliminary support for the use of exhaled breath as a potential noninvasive screening tool in renal failure.

Objective: The objective of this study was to investigate changes in volatile organic compounds (VOCs) in exhaled breath in overweight/obese children compared with their lean counterparts., Study Design: Single exhaled breath was collected and analyzed per protocol using selective ion flow tube mass spectrometry (SIFT-MS)., Results: Sixty overweight/obese children and 55 lean controls were included. Compared with the lean group, the obese group was significantly older (14.1 ± 2.8 vs. 12.1 ± 3.0 years), taller (164.8 ± 10.9 vs. 153.3 ± 17.1 cm) and more likely to be Caucasian (60% vs. 35.2%); P < 0.05 for all. A comparison of the SIFT-MS results of the obese group with the lean group revealed differences in concentration of more than 50 compounds. A panel of four VOCs can identify the presence of overweight/obesity with excellent accuracy. Further analysis revealed that breath isoprene, 1-decene, 1-octene, ammonia and hydrogen sulfide were significantly higher in the obese group compared with the lean group (P value < 0.01 for all)., Conclusion: Obese children have a unique pattern of exhaled VOCs. Changes in VOCs observed in this study may help to gain insight into pathophysiological processes and pathways leading to the development of childhood obesity., (© 2014 The Authors. Pediatric Obesity © 2014 International Association for the Study of Obesity.)

Background & Aims: Selected-ion flow-tube mass spectrometry can precisely identify trace gases in the human breath, in the parts-per-billion range. We investigated whether concentrations of volatile compounds in breath samples correlate with the diagnosis of alcoholic hepatitis (AH) and the severity of liver disease in patients with AH., Methods: We recruited patients with liver disease from a single tertiary care center. The study population was divided between those with AH with cirrhosis (n = 40) and those with cirrhosis with acute decompensation from etiologies other than alcohol (n = 40); individuals without liver disease served as control subjects (n = 43). We used selected-ion flow-tube mass spectrometry to identify and measure 14 volatile compounds in breath samples from fasted subjects. We used various statistical analyses to compare clinical characteristics and breath levels of compounds among groups and to test the correlation between levels of compounds and severity of liver disease. Logistic regression analysis was performed to build a predictive model for AH., Results: We identified 6 compounds (2-propanol, acetaldehyde, acetone, ethanol, pentane, and trimethylamine [TMA]) whose levels were increased in patients with liver disease compared with control subjects. Mean concentrations of TMA and pentane (TAP) were particularly high in breath samples from patients with AH, compared with those with acute decompensation or control subjects (for both, P < .001). Using receiver operating characteristic curve analysis, we developed a model for the diagnosis of AH based on breath levels of TAP. TAP scores of 36 or higher identified the patients with AH (area under the receiver operating characteristic curves = 0.92) with 90% sensitivity and 80% specificity. The levels of exhaled TMA had a low level of correlation with the severity of AH based on model for end-stage liver disease score (r = 0.38; 95% confidence interval, 0.07-0.69; P = .018)., Conclusions: Based on levels of volatile compounds in breath samples, we can identify patients with AH vs patients with acute decompensation or individuals without liver disease. Levels of exhaled TMA moderately correlate with the severity of AH. These findings might be used in diagnosis of AH or in determining patient prognosis., (Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.)

With each breath that we exhale, thousands of molecules are expelled in our breath, giving individuals a "breath-print" that can tell a lot about them and their state of health. Breath analysis is rapidly evolving as the new frontier in medical testing. The end of the 20th century and the beginning of the 21st century have arguably witnessed a revolution in our understanding of the constituents of exhaled breath and the development of the field of breath analysis and testing. Thanks to major breakthroughs in new technologies (infrared, electrochemical, chemiluminescence, and others) and the availability of mass spectrometers, the field of breath analysis has made considerable advances in the 21st century. Several methods are now in clinical use or nearly ready to enter that arena. Breath analysis has the potential to offer relatively inexpensive, rapid, noninvasive methods for detecting and/or monitoring a variety of diseases. Breath analysis also has applications in fields beyond medicine, including environmental monitoring, security, and others. This review will focus on exhaled breath as a potential source of biomarkers for medical applications with specific attention to applications (and potential applications) in cardiovascular disease., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Background: Measurement of fractional nitric oxide (NO) concentration in exhaled breath (Fe(NO)) is a quantitative, noninvasive, simple, and safe method of measuring airway inflammation that provides a complementary tool to other ways of assessing airways disease, including asthma. While Fe(NO) measurement has been standardized, there is currently no reference guideline for practicing health care providers to guide them in the appropriate use and interpretation of Fe(NO) in clinical practice., Purpose: To develop evidence-based guidelines for the interpretation of Fe(NO) measurements that incorporate evidence that has accumulated over the past decade., Methods: We created a multidisciplinary committee with expertise in the clinical care, clinical science, or basic science of airway disease and/or NO. The committee identified important clinical questions, synthesized the evidence, and formulated recommendations. Recommendations were developed using pragmatic systematic reviews of the literature and the GRADE approach., Results: The evidence related to the use of Fe(NO) measurements is reviewed and clinical practice recommendations are provided., Conclusions: In the setting of chronic inflammatory airway disease including asthma, conventional tests such as FEV(1) reversibility or provocation tests are only indirectly associated with airway inflammation. Fe(NO) offers added advantages for patient care including, but not limited to (1) detecting of eosinophilic airway inflammation, (2) determining the likelihood of corticosteroid responsiveness, (3) monitoring of airway inflammation to determine the potential need for corticosteroid, and (4) unmasking of otherwise unsuspected nonadherence to corticosteroid therapy.

Background: Exhaled breath condensate (EBC) pH is 2 log orders below normal during acute asthma exacerbations and returns to normal with antiinflammatory therapy. However, the determinants of EBC pH, particularly in stable asthma, are poorly understood. We hypothesized that patients with severe asthma would have low EBC pH and that there would be an asthma subpopulation of patients with characteristically low values., Methods: We studied the association of EBC pH with clinical characteristics in 572 stable subjects enrolled in the Severe Asthma Research Program. These included 250 subjects with severe asthma, 291 with nonsevere asthma, and 31 healthy control subjects., Results: Overall, EBC in this population of stable, treated study subjects was not lower in severe asthma (8.02; interquartile range [IQR], 7.61-8.41) or nonsevere asthma (7.90; IQR, 7.52-8.20) than in control subjects (7.9; IQR, 7.40-8.20). However, in subjects with asthma the data clustered below and above pH 6.5. Subjects in the subpopulation with pH < 6.5 had lower fraction of exhaled NO (FeNO) values (FeNO = 22.6 ± 18.1 parts per billion) than those with pH ≥ 6.5 (39.9 ± 40.2 parts per billion; P < .0001). By multiple linear regression, low EBC pH was associated with high BMI, high BAL neutrophil counts, low prebronchodilator FEV(1) ratio, high allergy symptoms, race other than white, and gastroesophageal reflux symptoms., Conclusion: Asthma is a complex syndrome. Subjects who are not experiencing an exacerbation but have low EBC pH appear to be a unique subpopulation.

We tested reproducibility of exhaled nitric oxide (FE(NO)) and inter-operator handling when measured with a handheld device, NIOX MINO. We enrolled 20 volunteers using a priori goals of acceptable reproducibility to be mean within-subject standard deviation less than 3 parts per billion (ppb) for FE(NO) measurements less than 30 ppb, and mean coefficient of variation less than 10% for FE(NO) measurements more than 30 ppb. Seventeen subjects with measurements less than 30 ppb displayed a mean standard deviation of 1.15, and 3 subjects with FE(NO) more than 30 ppb had a mean coefficient of variation of 2.4%. We conclude that NIOX MINO demonstrates excellent reproducibility for all ranges of FE(NO).

Rationale: Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry., Objectives: We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma., Methods: In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma and 45 healthy control subjects or control subjects without cancer was analyzed. Principal components and canonic discriminant analysis of the sensor data was used to determine whether exhaled gases could discriminate between cancer and noncancer. Discrimination between classes was performed using Mahalanobis distance. Support vector machine analysis was used to create and apply a cancer prediction model prospectively in a separate group of 76 individuals, 14 with and 62 without cancer., Main Results: Principal components and canonic discriminant analysis demonstrated discrimination between samples from patients with lung cancer and those from other groups. In the validation study, the electronic nose had 71.4% sensitivity and 91.9% specificity for detecting lung cancer; positive and negative predictive values were 66.6 and 93.4%, respectively. In this population with a lung cancer prevalence of 18%, positive and negative predictive values were 66.6 and 94.5%, respectively., Conclusion: The exhaled breath of patients with lung cancer has distinct characteristics that can be identified with an electronic nose. The results provide feasibility to the concept of using the electronic nose for managing and detecting lung cancer.

(1) Background: The treatment goal of ketogenic glycogen storage diseases (GSDs) is appropriate control of hypoglycemia and other disturbances such as dyslipidemia. Monitoring and treatment of ketosis are known to improve outcomes. We used breath analysis to identify volatile organic compounds (VOCs) that correlate with serum ketones in order to provide a non-invasive method of monitoring ketosis. (2) Methods: Consecutive children with ketogenic GSDs were recruited from a single center during routine admission to monitor serum glucose and ketone levels. Five breath samples were collected from every patient at the same time of blood draws. SIFT-mass spectrometry was used to analyze breath samples. Univariate linear mixed-effects regression models for 22 known VOCs and either serum ketones or glucose were performed. (3) Results: Our cohort included 20 patients aged 5–15 years with a mean BMI of 20 kg/m2 (72% tile). Most patients had GSD type 0 (35%), while 25% had type IX. VOCs that showed a significant correlation with serum ketone levels included acetone (p < 0.0001), trimethylamine (p < 0.0001), pentane (p = 0.0001), 3-methylhexane (p = 0.0047), and carbon disulfide (p = 0.0499). No correlation was found between serum glucose and any VOC. (4) Conclusions: Breath analysis is a promising noninvasive tool that can be used to predict ketone serum levels in patients with GSD. [ABSTRACT FROM AUTHOR]

Abstract: The analysis of volatile biomarkers of disease in breath is attractive because breath analysis is non-invasive and quick, and allows for repeated sampling. Challenges faced in the development of breath analysis include developing techniques that can measure analytes at very low concentrations, gaining an understanding of the exhalation physiology of individual volatiles, and determining the relationship between the proposed biomarker and the underlying condition. A small number of breath tests are used in clinical practice, but there is great potential for the development and wider application of clinical breath analysis in infection, inflammation, cancer and metabolic disease. [Copyright &y& Elsevier]