Exhaled volatile organic compounds as markers for medication use in asthma

Associations of urinary volatile organic compounds with cardiovascular disease among the general adult population

This study was to estimate the associations of volatile organic compounds (VOCs) exposure with the prevalence of total and specific cardiovascular disease (CVD) among the general adult population. This cross-sectional study analyzed 15 urinary VOC metabolites in the general population using the 2011-2016 National Health and Nutrition Examination Survey (n = 5,213). The weighted study population with 47.0 years median age, was primarily female (51.2%). The prevalence of total CVD in the overall population was 7.9%. The single-exposure analyzes of AAMA, ATCA, CEMA, CYMA, DHBMA, 3HPMA, and 3MHA +4MHA were significantly associated with increased prevalence of total CVD. Qgcomp regression consistently showed that urinary VOCs-mixed exposure was positively correlated with the prevalence of total and specific CVDs (chronic heart failure, angina, and stroke), and highlighted each VOCs metabolite weights and direction. The similar results were observed for the WQS regression using mixed analysis methods. In conclusion, exposure to VOCs increases CVD prevalence and advances the identification of risk factors for CVD for environmental study.

A Clinical Breathomics Dataset

This study entailed a comprehensive GC‒MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological states and the microbiome, were of particular interest due to their non-invasive nature. The highlighted noninvasive approach for detecting these breath molecules significantly enhances diagnostic and monitoring capacities. This dataset cataloged volatile organic compounds (VOCs) from the breath of individuals with asthma, bronchiectasis, and chronic obstructive pulmonary disease. Uniform and consistent sample collection protocols were strictly adhered to during the accumulation of this extensive dataset, ensuring its reliability. It encapsulates extensive human clinical breath molecule data pertinent to three specific diseases. This consequential clinical breathomics dataset is a crucial resource for researchers and clinicians in identifying and exploring important compounds within the patient's breath, thereby augmenting future diagnostic and therapeutic initiatives.

Breath Biopsy Reveals Systemic Immunothrombosis and Its Resolution through Bioorthogonal Dendritic Nanoprobes

Immunothrombosis, an inflammation-dependent activation of the coagulation cascade, leads to microthrombi formations in small vessels. It is a dreaded complication of COVID-19 and a major cause of respiratory failure. Due to their size and disseminated nature, microthrombi are currently undetectable. Here, noninvasive detection of a volatile reporter in the exhaled air is introduced for assessment of systemic immunothrombosis. A dendritic nanoprobe, containing high loading of a thrombin-sensitive substrate, is selectively cleaved by thrombin, resulting in release of a synthetic bioorthogonal volatile organic compound (VOC). The VOC is quantitated in the exhaled air biopsies via gas chromatography-mass spectrometry (GC-MS), allowing near real-time assessment of systemic immunothrombosis. The VOC detection can be further improved with more rapid and sensitive MS-based technologies. The amount of the VOC in the exhaled air decreases with resolution of the microvascular inflammation and intravascular fibrin depositions. Through conjugation of the thrombin-sensitive peptide with a rhodol derivative, a novel thrombin-sensitive fluorescent nanoprobe is developed for intravital visualization of thrombin activity in actively growing thrombi. These results establish unprecedented detection of thrombin activity in vivo, addressing this unmet medical need. This novel approach facilitates diagnosis of immunothrombosis in diseases such as diabetic complications, disseminated intravascular coagulation, and COVID-19.

Prediction of systemic free and total valproic acid by off-line analysis of exhaled breath in epileptic children and adolescents

Therapeutic drug monitoring (TDM) of medications with a narrow therapeutic window is a common clinical practice to minimize toxic effects and maximize clinical outcomes. Routine analyses rely on the quantification of systemic blood concentrations of drugs. Alternative matrices such as exhaled breath are appealing because of their inherent non-invasive nature. This is especially the case for pediatric patients. We have recently showcased the possibility of predicting systemic concentrations of valproic acid (VPA), an anti-seizure medication by real-time breath analysis in two real clinical settings. This approach, however, comes with the limitation of the patients having to physically exhale into the mass spectrometer. This restricts the possibility of sampling from patients not capable or available to exhale into the mass spectrometer located on the hospital premises. In this work, we developed an alternative method to overcome this limitation by collecting the breath samples in customized bags and subsequently analyzing them by secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). A total ofn= 40 patients (mean ± SD, 11.5 ± 3.5 y.o.) diagnosed with epilepsy and taking VPA were included in this study. The patients underwent three measurements: (i) serum concentrations of total and free VPA, (ii) real-time breath analysis and (iii) off-line analysis of exhaled breath collected in bags. The agreement between the real-time and the off-line breath analysis methods was evaluated using Lin's concordance correlation coefficient (CCC). CCC was computed for ten mass spectral predictors of VPA concentrations. Lin's CCC was >0.6 for all VPA-associated features, except for two low-signal intensity isotopic peaks. Finally, free and total serum VPA concentrations were predicted by cross validating the off-line data set. Support vector machine algorithms provided the most accurate predictions with a root mean square error of cross validation of 29.0 ± 7.4 mg l-1and 3.9 ± 1.4 mg l-1for total and free VPA (mean ± SD), respectively. As a secondary analysis, we explored whether exhaled metabolites previously associated with side-effects and response to medication could be rendered by the off-line analysis method. We found that five features associated with side effects showed a CCC > 0.6, whereas none of the drug response-associated peaks reached this cut-off. We conclude that the clinically relevant free fraction of VPA can be predicted by this combination of off-line breath collection with rapid SESI-HRMS analysis. This opens new possibilities for breath based TDM in clinical settings.

Exhaled volatile organic compounds for diagnosis and monitoring of asthma

The asthmatic inflammatory process results in the generation of volatile organic compounds (VOCs), which are subsequently secreted by the airways. The study of these elements through gas chromatography-mass spectrometry (GC-MS), which can identify individual molecules with a discriminatory capacity of over 85%, and electronic-Nose (e-NOSE), which is able to perform a quick onboard pattern-recognition analysis of VOCs, has allowed new prospects for non-invasive analysis of the disease in an "omics" approach. In this review, we aim to collect and compare the progress made in VOCs analysis using the two methods and their instrumental characteristics. Studies have described the potential of GC-MS and e-NOSE in a multitude of relevant aspects of the disease in both children and adults, as well as differential diagnosis between asthma and other conditions such as wheezing, cystic fibrosis, COPD, allergic rhinitis and last but not least, the accuracy of these methods compared to other diagnostic tools such as lung function, FeNO and eosinophil count. Due to significant limitations of both methods, it is still necessary to improve and standardize techniques. Currently, e-NOSE appears to be the most promising aid in clinical practice, whereas GC-MS, as the gold standard for the structural analysis of molecules, remains an essential tool in terms of research for further studies on the pathophysiologic pathways of the asthmatic inflammatory process. In conclusion, the study of VOCs through GC-MS and e-NOSE appears to hold promise for the non-invasive diagnosis, assessment, and monitoring of asthma, as well as for further research studies on the disease.

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

Background

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

Methods

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

Results

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

Conclusion

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

Definitions of non-response and response to biological therapy for severe asthma: a systematic review

Background

Biologics have proven efficacy for patients with severe asthma but there is lack of consensus on defining response. We systematically reviewed and appraised methodologically developed, defined and evaluated definitions of non-response and response to biologics for severe asthma.

Methods

We searched four bibliographic databases from inception to 15 March 2021. Two reviewers screened references, extracted data, and assessed methodological quality of development, measurement properties of outcome measures and definitions of response based on COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). A modified GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach and narrative synthesis were undertaken.

Results

13 studies reported three composite outcome measures, three asthma symptoms measures, one asthma control measure and one quality of life measure. Only four measures were developed with patient input; none were composite measures. Studies utilised 17 definitions of response: 10 out of 17 (58.8%) were based on minimal clinically important difference (MCID) or minimal important difference (MID) and 16 out of 17 (94.1%) had high-quality evidence. Results were limited by poor methodology for the development process and incomplete reporting of psychometric properties. Most measures rated "very low" to "low" for quality of measurement properties and none met all quality standards.

Conclusions

This is the first review to synthesise evidence about definitions of response to biologics for severe asthma. While high-quality definitions are available, most are MCIDs or MIDs, which may be insufficient to justify continuation of biologics in terms of cost-effectiveness. There remains an unmet need for universally accepted, patient-centred, composite definitions to aid clinical decision making and comparability of responses to biologics.

A chemiresistive-potentiometric multivariate sensor for discriminative gas detection

Highly efficient gas sensors able to detect and identify hazardous gases are crucial for numerous applications. Array of conventional single-output sensors is currently limited by problems including drift, large size, and high cost. Here, we report a sensor with multiple chemiresistive and potentiometric outputs for discriminative gas detection. Such sensor is applicable to a wide range of semiconducting electrodes and solid electrolytes, which allows to tailor and optimize the sensing pattern by tuning the material combination and conditions. The sensor performance is boosted by equipping a mixed-conducting perovskite electrode with reverse potentiometric polarity. A conceptual sensor with dual sensitive electrodes achieves superior three-dimensional (sub)ppm sensing and discrimination of humidity and seven hazardous gases (2-Ethylhexanol, ethanol, acetone, toluene, ammonia, carbon monoxide, and nitrogen dioxide), and enables accurate and early warning of fire hazards. Our findings offer possibilities to design simple, compact, inexpensive, and highly efficient multivariate gas sensors.

Precision Medicine Intervention in Severe Asthma (PRISM) study: molecular phenotyping of patients with severe asthma and response to biologics

Severe asthma represents an important clinical unmet need despite the introduction of biologic agents. Although advanced omics technologies have aided researchers in identifying clinically relevant molecular pathways, there is a lack of an integrated omics approach in severe asthma particularly in terms of its evolution over time. The collaborative Korea-UK research project Precision Medicine Intervention in Severe Asthma (PRISM) was launched in 2020 with the aim of identifying molecular phenotypes of severe asthma by analysing multi-omics data encompassing genomics, epigenomics, transcriptomics, proteomics, metagenomics and metabolomics. PRISM is a prospective, observational, multicentre study involving patients with severe asthma attending severe asthma clinics in Korea and the UK. Data including patient demographics, inflammatory phenotype, medication, lung function and control status of asthma will be collected along with biological samples (blood, sputum, urine, nasal epithelial cells and exhaled breath condensate) for omics analyses. Follow-up evaluations will be performed at baseline, 1 month, 4-6 months and 10-12 months to assess the stability of phenotype and treatment responses for those patients who have newly begun biologic therapy. Standalone and integrated omics data will be generated from the patient samples at each visit, paired with clinical information. By analysing these data, we will identify the molecular pathways that drive lung function, asthma control status, acute exacerbations and the requirement for daily oral corticosteroids, and that are involved in the therapeutic response to biological therapy. PRISM will establish a large multi-omics dataset of severe asthma to identify potential key pathophysiological pathways of severe asthma.

Common Strategies and Factors Affecting Off-Line Breath Sampling and Volatile Organic Compounds Analysis Using Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS)

An analysis of exhaled breath enables specialists to noninvasively monitor biochemical processes and to determine any pathological state in the human body. Breath analysis holds the greatest potential to remold and personalize diagnostics; however, it requires a multidisciplinary approach and collaboration of many specialists. Despite the fact that breath is considered to be a less complex matrix than blood, it is not commonly used as a diagnostic and prognostic tool for early detection of disordered conditions due to its problematic sampling, analysis, and storage. This review is intended to determine, standardize, and marshal experimental strategies for successful, reliable, and especially, reproducible breath analysis.

The Role of Systems Biology in Deciphering Asthma Heterogeneity

Asthma is one of the most common and lifelong and chronic inflammatory diseases characterized by inflammation, bronchial hyperresponsiveness, and airway obstruction episodes. It is a heterogeneous disease of varying and overlapping phenotypes with many confounding factors playing a role in disease susceptibility and management. Such multifactorial disorders will benefit from using systems biology as a strategy to elucidate molecular insights from complex, quantitative, massive clinical, and biological data that will help to understand the underlying disease mechanism, early detection, and treatment planning. Systems biology is an approach that uses the comprehensive understanding of living systems through bioinformatics, mathematical, and computational techniques to model diverse high-throughput molecular, cellular, and the physiologic profiling of healthy and diseased populations to define biological processes. The use of systems biology has helped understand and enrich our knowledge of asthma heterogeneity and molecular basis; however, such methods have their limitations. The translational benefits of these studies are few, and it is recommended to reanalyze the different studies and omics in conjugation with one another which may help understand the reasons for this variation and help overcome the limitations of understanding the heterogeneity in asthma pathology. In this review, we aim to show the different factors that play a role in asthma heterogeneity and how systems biology may aid in understanding and deciphering the molecular basis of asthma.

Exhaled Breath Analysis for Investigating the Use of Inhaled Corticosteroids and Corticosteroid Responsiveness in Wheezing Preschool Children

Exhaled breath analysis has great potential in diagnosing various respiratory and non-respiratory diseases. In this study, we investigated the influence of inhaled corticosteroids (ICS) on exhaled volatile organic compounds (VOCs) of wheezing preschool children. Furthermore, we assessed whether exhaled VOCs could predict a clinical steroid response in wheezing preschool children. We performed a crossover 8-week ICS trial, in which 147 children were included. Complete data were available for 89 children, of which 46 children were defined as steroid-responsive. Exhaled VOCs were measured by GC-tof-MS. Statistical analysis by means of Random Forest was used to investigate the effect of ICS on exhaled VOCs. A set of 20 VOCs could best discriminate between measurements before and after ICS treatment, with a sensitivity of 73% and specificity of 67% (area under ROC curve = 0.72). Most discriminative VOCs were branched C11H24, butanal, octanal, acetic acid and methylated pentane. Other VOCs predominantly included alkanes. Regularised multivariate analysis of variance (rMANOVA) was used to determine treatment response, which showed a significant effect between responders and non-responders (p < 0.01). These results show that ICS significantly altered the exhaled breath profiles of wheezing preschool children, irrespective of clinical treatment response. Furthermore, exhaled VOCs were capable of determining corticosteroid responsiveness in wheezing preschool children.

AuNP@ZeNose (ZIF-based electrochemical nose) for detection of flu biomarker in breath

A novel electrochemical sensor is reported for the detection of isoprene levels in breath using a ZIF-based electrochemical nose. This sensor incorporates a hybrid detection system using gold nanoparticles encapsulated inside the ZIF-8 moiety. Breath-based analysis is widely being used for monitoring the metabolic state of the body. It is associated with the change in the concentration of volatile organic compounds and inorganic gases released endogenously and can be tracked using breath as the sample. One such volatile organic compound, isoprene, has been correlated to the presence of influenza virus or respiratory inflammation. Analytical techniques such as powder X-ray diffraction, scanning electron microscopy, atomic force microscopy, Fourier transform infrared spectroscopy, and tunneling electron microscopy were used to understand the structural features of the composite. The electrochemical nose system uses chronoamperometry as the transduction mechanism to monitor the diffusion kinetics of the target analyte across the electrode-electrolyte interface. The presented work demonstrates isoprene sensing with high sensitivity and specificity and a detection limit of 10 parts per billion in air. We successfully demonstrate the functionality of the ZIF-based electrochemical nose for point-of-care screening of isoprene levels by developing a prototype device using a commercially available development board. We foresee that the developed sensing platform can help in early screening for the presence of influenza virus and help control the infection rate.

pyAIR-A New Software Tool for Breathomics Applications-Searching for Markers in TD-GC-HRMS Analysis

Volatile metabolites in exhaled air have promising potential as diagnostic biomarkers. However, the combination of low mass, similar chemical composition, and low concentrations introduces the challenge of sorting the data to identify markers of value. In this paper, we report the development of pyAIR, a software tool for searching for volatile organic compounds (VOCs) markers in multi-group datasets, tailored for Thermal-Desorption Gas-Chromatography High Resolution Mass-Spectrometry (TD-GC-HRMS) output. pyAIR aligns the compounds between samples by spectral similarity coupled with retention times (RT), and statistically compares the groups for compounds that differ by intensity. This workflow was successfully tested and evaluated on gaseous samples spiked with 27 model VOCs at six concentrations, divided into three groups, down to 0.3 nL/L. All analytes were correctly detected and aligned. More than 80% were found to be significant markers with a p-value < 0.05; several were classified as possibly significant markers (p-value < 0.1), while a few were removed due to background level. In all group comparisons, low rates of false markers were found. These results showed the potential of pyAIR in the field of trace-level breathomics, with the capability to differentially examine several groups, such as stages of illness.

STOP: an open label crossover trial to study ICS withdrawal in patients with a combination of obesity and low-inflammatory asthma and evaluate its effect on asthma control and quality of life

Background

Asthma patients with obesity often have a high disease burden, despite the use of high-dose inhaled corticosteroids (ICS). In contrast to asthmatics with normal weight, the efficacy of ICS in patients with obesity and asthma is often relatively low. Meanwhile, patients do suffer from side effects, such as weight gain, development of diabetes, cataract, or high blood pressure. The relatively poor response to ICS might be explained by the low prevalence of type 2 inflammatory patterns (T2-low) in patients with asthma and obesity. T2-low inflammation is characterized by low eosinophilic count, low Fractional exhaled NO (FeNO), no clinically allergy-driven asthma, and no need for maintenance oral corticosteroids (OCS). We aim to study whether ICS can be safely withdrawn in patients with T2-low asthma and obesity while maintaining an equal level of asthma control. Secondary outcomes focus on the prevalence of ‘false-negative’ T2-low phenotypes (i.e. T2-hidden) and the effect of ICS withdrawal on parameters of the metabolic syndrome. This study will lead to a better understanding of this poorly understood subgroup and might find new treatable traits.

Methods

The STOP trial is an investigator-initiated, multicenter, non-inferiority, open-label, crossover study aiming to assess whether ICS can be safely withdrawn in adults aged 17–75 years with T2-low asthma and obesity (body mass index (BMI) ≥ 30 kg/m2). Patients will be randomly divided into two arms (both n = 60). One arm will start with fixed-dose ICS (control group) and one arm will taper and subsequently stop ICS (intervention group). Patients in the intervention group will remain ICS naïve for ten weeks. After a washout of 4 weeks, patients will crossover to the other study arm. The crossover study takes 36 weeks to complete. Patients will be asked to participate in the extension study, to investigate the long-term metabolic benefits of ICS withdrawal.

Discussion

This study yields valuable data on ICS tapering in patients with T2-low asthma and obesity. It informs future guidelines and committees on corticosteroid-sparing algorithms in these patients.

Trial registration Netherlands Trial Register, NL8759, registered 2020–07-06, https://www.trialregister.nl/trial/8759.

Protocol version and date: version 2.1, 20 November 2020.

Biomarkers of asthma

Biomarkers may be diagnostic of asthma, they may predict or reflect response to therapy or they may identify patients at risk of asthma exacerbation. A biomarker is most often measured in biologic fluids that are sampled using relatively non-invasive sampling techniques such as blood, sputum, urine or exhaled breath. Biomarkers should be stable, readily quantifiable and their measurement should be reproducible and not confounded by other host factors, or the presence of comorbidities. However, asthma comprises multiple molecular endotypes and single, sensitive, specific, biomarkers reflecting these endotypes may not exist. Combining biomarkers may improve their predictive capability in asthma. The most well-established endotypes are those described as Type2 and non-Type2 asthma. Clinical trials established the fraction of exhaled nitric oxide (FeNO) and blood eosinophil counts as key biomarkers of response to corticosteroid or targeted anti-inflammatory therapy in Type2 asthma. However, these biomarkers may have limited value in the management of asthma in real-life settings or routine clinical practise. Biomarkers for Type2 asthma are not well described or validated and more research is needed. Breathomics has provided evidence to propose a number of exhaled volatile organic compounds (VOCs) as surrogate biomarkers for airway inflammatory phenotypes, disease activity and adherence to therapy. Analysis of urinary eicosanoids has identified eicosanoids related to Type2 and non-Type2 inflammation. Future clinical trials will be important in determining how exhaled VOCs or urinary eicosanoid profiles can be used to direct precision treatments. Their future clinical use will also depend on developing simplified instrumentation for biomarker analysis at the point-of-care.

A systematic review of the diagnostic accuracy of volatile organic compounds in airway diseases and their relation to markers of type-2 inflammation

BACKGROUND

Asthma and COPD continue to cause considerable diagnostic and treatment stratification challenges. Volatile organic compounds (VOCs) have been proposed as feasible diagnostic and monitoring biomarkers in airway diseases.

AIMS

To 1) conduct a systematic review evaluating the diagnostic accuracy of VOCs in diagnosing airway diseases; 2) understand the relationship between reported VOCs and biomarkers of type-2 inflammation; 3) assess the standardisation of reporting according to STARD and TRIPOD criteria; 4) review current methods of breath sampling and analysis.

METHODS

A PRISMA-oriented systematic search was conducted (January 1997 to December 2020). Search terms included: "asthma", "volatile organic compound(s)", "VOC" and "COPD". Two independent reviewers examined the extracted titles against review objectives.

RESULTS

44 full-text papers were included; 40/44 studies were cross-sectional and four studies were interventional in design; 17/44 studies used sensor-array technologies (e.g. eNose). Cross-study comparison was not possible across identified studies due to the heterogeneity in design. The commonest airway diseases differentiating VOCs belonged to carbonyl-containing classes (i.e. aldehydes, esters and ketones) and hydrocarbons (i.e. alkanes and alkenes). Although individual markers that are associated with clinical biomarkers of type-2 inflammation were recognised (i.e. ethane and 3,7-dimethylnonane for asthma and α-methylstyrene and decane for COPD), these were not consistently identified across studies. Only 3/44 reported following STARD or TRIPOD criteria for diagnostic accuracy and multivariate reporting, respectively.

CONCLUSIONS

Breath VOCs show promise as diagnostic biomarkers of airway diseases and for type-2 inflammation profiling. However, future studies should focus on transparent reporting of diagnostic accuracy and multivariate models and continue to focus on chemical identification of volatile metabolites.

Metal oxide-based gas sensors for detection of exhaled breath markers

Exhaled breath test is a typical disease monitoring method for replacing blood and urine samples that may create discomfort for patients. To monitor exhaled breath markers, gas biomedical sensors have undergone rapid progress for non‐invasive and point‐of‐care diagnostic devices. Among gas sensors, metal oxide‐based biomedical gas sensors have received remarkable attention owing to their unique properties, such as high sensitivity, simple fabrication, miniaturization, portability and real‐time monitoring. Herein, we reviewed the recent advances in chemoresistive metal oxide‐based gas sensors with ZnO, SnO₂ and In₂O₃ as sensing materials for monitoring a range of exhaled breath markers (i.e., NO, H₂, H₂S, acetone, isoprene and formaldehyde). We focused on the strategies that improve the sensitivity and selectivity of metal oxide‐based gas sensors. The challenges to fabricate a functional gas sensor with high sensing performance along with suggestions are outlined.

Volatile organic compounds in a headspace sampling system and asthmatics sputum samples

Background:The headspace of a biological sample contains exogenous VOCs present within the sampling environment which represent the background signal.Study aims:This study aimed to characterise the background signal generated from a headspace sampling system in a clinical site, to evaluate intra- and inter-day variation of background VOC and to understand the impact of a sample itself upon commonly reported background VOC using sputum headspace samples from severe asthmatics.Methods:The headspace, in absence of a biological sample, was collected hourly from 11am to 3pm within a day (time of clinical samples acquisition), and from Monday to Friday in a week, and analysed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Chemometric analysis identified 1120 features, 37 of which were present in at least the 80% of all the samples. The analyses of intra- and inter-day background variations were performed on thirteen of the most abundant features, ubiquitously present in headspace samples. The concentration ratios relative to background were reported for the selected abundant VOC in 36 asthmatic sputum samples, acquired from 36 stable severe asthma patients recruited at Glenfield Hospital, Leicester, UK.Results:The results identified no significant intra- or inter-day variations in compounds levels and no systematic bias of z-scores, with the exclusion of benzothiazole, whose abundance increased linearly between 11am and 3pm with a maximal intra-day fold change of 2.13. Many of the identified background features are reported in literature as components of headspace of biological samples and are considered potential biomarkers for several diseases. The selected background features were identified in headspace of all severe asthma sputum samples, albeit with varying levels of enrichment relative to background.Conclusion:Our observations support the need to consider the background signal derived from the headspace sampling system when developing and validating headspace biomarker signatures using clinical samples.

The Role of Electronic Noses in Phenotyping Patients with Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a common progressive disorder of the respiratory system which is currently the third leading cause of death worldwide. Exhaled breath analysis is a non-invasive method to study lung diseases, and electronic noses have been extensively used in breath research. Studies with electronic noses have proved that the pattern of exhaled volatile organic compounds is different in COPD. More recent investigations have reported that electronic noses could potentially distinguish different endotypes (i.e., neutrophilic vs. eosinophilic) and are able to detect microorganisms in the airways responsible for exacerbations. This article will review the published literature on electronic noses and COPD and help in identifying methodological, physiological, and disease-related factors which could affect the results.

Breathomics in Asthmatic Children Treated with Inhaled Corticosteroids

BACKGROUND

"breathomics" enables indirect analysis of metabolic patterns underlying a respiratory disease. In this study, we analyze exhaled breath condensate (EBC) in asthmatic children before (T0) and after (T1) a three-week course of inhaled beclomethasone dipropionate (BDP).

METHODS

we recruited steroid-naive asthmatic children for whom inhaled steroids were indicated and healthy children, evaluating asthma control, spirometry and EBC (in asthmatics at T0 and T1). A liquid-chromatography-mass-spectrometry untargeted analysis was applied to EBC and a mass spectrometry-based target analysis to urine samples.

RESULTS

metabolomic analysis discriminated asthmatic (n = 26) from healthy children (n = 16) at T0 and T1, discovering 108 and 65 features relevant for the discrimination, respectively. Searching metabolomics databases, seven putative biomarkers with a plausible role in asthma biochemical-metabolic processes were found. After BDP treatment, asthmatic children, in the face of an improved asthma control (p < 0.001) and lung function (p = 0.01), showed neither changes in EBC metabolomic profile nor in urinary endogenous steroid profile.

CONCLUSIONS

"breathomics" can discriminate asthmatic from healthy children, with prostaglandin, fatty acid and glycerophospholipid as putative markers. The three-week course of BDP-in spite of a significant clinical improvement-was not associated with changes in EBC metabolic arrangement and urinary steroid profile.

Changes of Exhaled Volatile Organic Compounds in Postoperative Patients Undergoing Analgesic Treatment: A Prospective Observational Study

Assessment and treatment of postoperative pain can be challenging as objective examination techniques to detect and quantify pain are lacking. We aimed to investigate changes of exhaled volatile organic compounds (VOCs) in patients with postoperative pain before and after treatment with opioid analgesics. In an observational study in 20 postoperative patients, we monitored for postoperative pain, hemodynamic parameters, and catecholamines before and during treatment. VOCs in the patients were determined by direct real-time proton transfer reaction time-of-flight mass spectrometry prior (0 min) and after piritramide application (15 min as well as 30 min). Cardiovascular variables changed and norepinephrine levels decreased during treatment. The VOCs acetonitrile (<0.001), acetaldehyde (p = 0.002), benzopyran (p = 0.004), benzene (p < 0.001), hexenal (p = < 0.001), 1-butanethiol (p = 0.004), methanethiol (p < 0.001), ethanol (p = 0.003), and propanol (p = < 0.001) changed significantly over time. Patients with Numeric Rating Scale (NRS) < 4 showed a significantly lower concentration of hexenal compared to patients with NRS > 4 at the time points 15 min (45.0 vs. 385.3 ncps, p = 0.047) and 30 min (38.3 vs. 334.6 ncps, p = 0.039). Breath analysis can provide additional information for noninvasive monitoring for analgesic treatment in postoperative patients.

Volatomic analysis identifies compounds that can stratify non-alcoholic fatty liver disease

Background & aims

Analysis of volatile organic compounds (VOCs) in exhaled breath, ‘volatomics’, provides opportunities for non-invasive biomarker discovery and novel mechanistic insights into a variety of diseases. The purpose of this pilot study was to compare breath VOCs in an initial cohort of patients with non-alcoholic fatty liver disease (NAFLD) and healthy controls.

Methods

Breath samples were collected from 15 participants with Child-Pugh class A NAFLD cirrhosis, 14 with non-cirrhotic NAFLD, and 14 healthy volunteers. Exhaled breath samples were collected using an established methodology and VOC profiles were analysed by gas chromatography-mass spectrometry. The levels of 19 VOCs previously associated with cirrhosis were assessed. Peaks of the VOCs were confirmed and integrated using Xcalibur® software, normalised to an internal standard. Receiver-operating characteristic (ROC) curves were used to determine the diagnostic accuracy of the candidate VOCs.

Results

Terpinene, dimethyl sulfide, and D-limonene provided the highest predictive accuracy to discriminate between study groups. Combining dimethyl sulfide with D-limonene led to even better discrimination of patients with NAFLD cirrhosis from healthy volunteers (AUROC 0.98; 95% CI 0.93–1.00; p <0.001) and patients with NAFLD cirrhosis from those with non-cirrhotic NAFLD (AUROC 0.91; 95% CI 0.82–1.00; p <0.001). Breath terpinene concentrations discriminated between patients with non-cirrhotic NAFLD and healthy volunteers (AUROC 0.84; 95% CI 0.68–0.99; p = 0.002).

Conclusion

Breath terpinene, dimethyl sulfide, and D-limonene are potentially useful volatomic markers for stratifying NAFLD; in addition, a 2-stage approach enables the differentiation of patients with cirrhosis from those without. However, these observations require validation in a larger NAFLD population. (ClinicalTrials.gov Identifier: NCT02950610).

Lay summary

Breath malodour has been associated with a failing liver since the ancient Greeks. Analytical chemistry has provided us an insight into ubiquitous volatile organic compounds associated with liver (and other) diseases. This has vastly improved our understanding of the mechanistic processes of liver damage. Our study aims to identify volatile organic compounds which are specific to non-alcoholic fatty liver disease and that can be exploited for rapid diagnostics.

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Metabolic dysfunction in liver disease is reflected in the biocomposition of exhaled breath.

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Specific volatile organic compounds can be measured in breath samples (volatomics) and have diagnostic potential in chronic liver disease.

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Levels of alfa-terpinene, dimethyl sulfide, and D-limonene in exhaled breath can be used to stratify patients with non-alcoholic fatty liver disease.