Analysis of volatile organic compounds in the breath of patients with stable or acute exacerbation of chronic obstructive pulmonary disease

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.

Metabolic insights at the finish line: deciphering physiological changes in ultramarathon runners through breath VOC analysis

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

Disease diagnosis and severity classification in pulmonary fibrosis using carbonyl volatile organic compounds in exhaled breath

BACKGROUND

Pathophysiological conditions underlying pulmonary fibrosis remain poorly understood. Exhaled breath volatile organic compounds (VOCs) have shown promise for lung disease diagnosis and classification. In particular, carbonyls are a byproduct of oxidative stress, associated with fibrosis in the lungs. To explore the potential of exhaled carbonyl VOCs to reflect underlying pathophysiological conditions in pulmonary fibrosis, this proof-of-concept study tested the hypothesis that volatile and low abundance carbonyl compounds could be linked to diagnosis and associated disease severity.

METHODS

Exhaled breath samples were collected from outpatients with a diagnosis of Idiopathic Pulmonary Fibrosis (IPF) or Connective Tissue related Interstitial Lung Disease (CTD-ILD) with stable lung function for 3 months before enrollment, as measured by pulmonary function testing (PFT) DLCO (%), FVC (%) and FEV1 (%). A novel microreactor was used to capture carbonyl compounds in the breath as direct output products. A machine learning workflow was implemented with the captured carbonyl compounds as input features for classification of diagnosis and disease severity based on PFT (DLCO and FVC normal/mild vs. moderate/severe; FEV1 normal/mild/moderate vs. moderately severe/severe).

RESULTS

The proposed approach classified diagnosis with AUROC=0.877 ± 0.047 in the validation subsets. The AUROC was 0.820 ± 0.064, 0.898 ± 0.040, and 0.873 ± 0.051 for disease severity based on DLCO, FEV1, and FVC measurements, respectively. Eleven key carbonyl VOCs were identified with the potential to differentiate diagnosis and to classify severity.

CONCLUSIONS

Exhaled breath carbonyl compounds can be linked to pulmonary function and fibrotic ILD diagnosis, moving towards improved pathophysiological understanding of pulmonary fibrosis.

GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review

Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.

Breath biomarkers in Non-Carcinogenic diseases

The analysis of volatile organic compounds (VOCs) from human matrices like breath, perspiration, and urine has received increasing attention from academic and medical researchers worldwide. These biological-borne VOCs molecules have characteristics that can be directly related to physiologic and pathophysiologic metabolic processes. In this work, gathers a total of 292 analytes that have been identified as potential biomarkers for the diagnosis of various non-carcinogenic diseases. Herein we review the advances in VOCs with a focus on breath biomarkers and their potential role as minimally invasive tools to improve diagnosis prognosis and therapeutic monitoring.

Phenotypes, Etiotypes, and Endotypes of Exacerbations of Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease is a major health problem with a high prevalence, a rising incidence, and substantial morbidity and mortality. Its course is punctuated by acute episodes of increased respiratory symptoms, termed exacerbations of chronic obstructive pulmonary disease (ECOPD). ECOPD are important events in the natural history of the disease, as they are associated with lung function decline and prolonged negative effects on quality of life. The present-day therapy for ECOPD with short courses of antibiotics and steroids and escalation of bronchodilators has resulted in only modest improvements in outcomes. Recent data indicate that ECOPD are heterogeneous, raising the need to identify distinct etioendophenotypes, incorporating traits of the acute event and of patients who experience recurrent events, to develop novel and targeted therapies. These characterizations can provide a complete clinical picture, the severity of which will dictate acute pharmacological treatment, and may also indicate whether a change in maintenance therapy is needed to reduce the risk of future exacerbations. In this review we discuss the latest knowledge of ECOPD types on the basis of clinical presentation, etiology, natural history, frequency, severity, and biomarkers in an attempt to characterize these events.

Mass Spectrometry Analysis for Clinical Applications: A Review

Mass spectrometry (MS) has become an attractive analytical method in clinical analysis due to its comprehensive advantages of high sensitivity, high specificity and high throughput. Separation techniques coupled MS detection (e.g., LC-MS/MS) have shown unique advantages over immunoassay and have developed as golden criterion for many clinical applications. This review summarizes the characteristics and applications of MS, and emphasizes the high efficiency of MS in clinical research. In addition, this review also put forward further prospects for the future of mass spectrometry technology, including the introduction of miniature MS instruments, point-of-care detection and high-throughput analysis, to achieve better development of MS technology in various fields of clinical application. Moreover, as ambient ionization mass spectrometry (AIMS) requires little or no sample pretreatment and improves the flux of MS, this review also summarizes its potential applications in clinic.

A PVDF-based colorimetric sensor array for noninvasive detection of multiple disease-related volatile organic compounds

Detection of human-generated volatile organic compounds (VOCs) is a new pathway for assessing health. Herein, a polyvinylidene fluoride (PVDF)-based colorimetric sensor array was designed for detecting disease-related VOCs (DVOCs) within 15 min, using a complex of Cu metal-organic framework, graphene aerogel, and dyes as response materials. Fingermaps derived from 28 DVOCs were obtained for further data processing. Pattern recognition was successfully employed in the correct discrimination of 28 DVOCs in low (10 μM), medium (100 μM), and high (300 μM) concentrations. Importantly, the sensor array also presented excellent discrimination ability and application potential when detecting VOCs produced by human cancer and normal cells. In general, VOC acquisition is noninvasive and harmless, and the PVDF-based sensor arrays are simple and visual. Such advantages expand their further application potential.

Unraveling the potential of breath and sweat VOC capture devices for human disease detection: a systematic-like review of canine olfaction and GC-MS analysis

The development of disease screening methods using biomedical detection dogs relies on the collection and analysis of body odors, particularly volatile organic compounds (VOCs) present in body fluids. To capture and analyze odors produced by the human body, numerous protocols and materials are used in forensics or medical studies. This paper provides an overview of sampling devices used to collect VOCs from sweat and exhaled air, for medical diagnostic purposes using canine olfaction and/or Gas Chromatography-Mass spectrometry (GC-MS). Canine olfaction and GC-MS are regarded as complementary tools, holding immense promise for detecting cancers and infectious diseases. However, existing literature lacks guidelines for selecting materials suitable for both canine olfaction and GC-MS. Hence, this review aims to address this gap and pave the way for efficient body odor sampling materials. The first section of the paper describes the materials utilized in training sniffing dogs, while the second section delves into the details of sampling devices and extraction techniques employed for exhaled air and sweat analysis using GC-MS. Finally, the paper proposes the development of an ideal sampling device tailored for detection purposes in the field of odorology. By bridging the knowledge gap, this study seeks to advance disease detection methodologies, harnessing the unique abilities of both dogs and GC-MS analysis in biomedical research.

Alveolar gradients in breath analysis. A pilot study with comparison of room air and inhaled air by simultaneous measurements using ion mobility spectrometry

Analyzing exhaled breath samples, especially using a highly sensitive method such as MCC/IMS (multi-capillary column/ion mobility spectrometry), may also detect analytes that are derived from exogenous production. In this regard, there is a discussion about the optimal interpretation of exhaled breath, either by considering volatile organic compounds (VOCs) only in exhaled breath or by additionally considering the composition of room air and calculating the alveolar gradients. However, there are no data on whether the composition and concentration of VOCs in room air are identical to those in truly inhaled air directly before analyzing the exhaled breath. The current study aimed to determine whether the VOCs in room air, which are usually used for the calculation of alveolar gradients, are identical to the VOCs in truly inhaled air. For the measurement of inhaled air and room air, two IMS, each coupled with an MCC that provided a pre-separation of the VOCs, were used in parallel. One device was used for sampling room air and the other for sampling inhaled air. Each device was coupled with a newly invented system that cleaned room air and provided a clean carrier gas, whereas formerly synthetic air had to be used as a carrier gas. In this pilot study, a healthy volunteer underwent three subsequent runs of sampling of inhaled air and simultaneous sampling and analysis of room air. Three of the selected 11 peaks (P4-unknown, P5-1-Butanol, and P9-Furan, 2-methyl-) had significantly higher intensities during inspiration than in room air, and four peaks (P1-1-Propanamine, N-(phenylmethylene), P2-2-Nonanone, P3-Benzene, 1,2,4-trimethyl-, and P11-Acetyl valeryl) had higher intensities in room air. Furthermore, four peaks (P6-Benzaldehyde, P7-Pentane, 2-methyl-, P8-Acetone, and P10-2-Propanamine) showed inconsistent differences in peak intensities between inhaled air and room air. To the best of our knowledge, this is the first study to compare simultaneous sampling of room air and inhaled air using MCC/IMS. The simultaneous measurement of inhaled air and room air showed that using room air for the calculation of alveolar gradients in breath analysis resulted in different alveolar gradient values than those obtained by measuring truly inhaled air.

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.

Visualization of exhaled breath metabolites reveals distinct diagnostic signatures for acute cardiorespiratory breathlessness

Acute cardiorespiratory breathlessness accounts for one in eight of all emergency hospitalizations. Early, noninvasive diagnostic testing is a clinical priority that allows rapid triage and treatment. Here, we sought to find and replicate diagnostic breath volatile organic compound (VOC) biomarkers of acute cardiorespiratory disease and understand breath metabolite network enrichment in acute disease, with a view to gaining mechanistic insight of breath biochemical derangements. We collected and analyzed exhaled breath samples from 277 participants presenting acute cardiorespiratory exacerbations and aged-matched healthy volunteers. Topological data analysis phenotypes differentiated acute disease from health and acute cardiorespiratory exacerbation subtypes (acute heart failure, acute asthma, acute chronic obstructive pulmonary disease, and community-acquired pneumonia). A multibiomarker score (101 breath biomarkers) demonstrated good diagnostic sensitivity and specificity (≥80%) in both discovery and replication sets and was associated with all-cause mortality at 2 years. In addition, VOC biomarker scores differentiated metabolic subgroups of cardiorespiratory exacerbation. Louvain clustering of VOCs coupled with metabolite enrichment and similarity assessment revealed highly specific enrichment patterns in all acute disease subgroups, for example, selective enrichment of correlated C5-7 hydrocarbons and C3-5 carbonyls in heart failure and selective depletion of correlated aldehydes in acute asthma. This study identified breath VOCs that differentiate acute cardiorespiratory exacerbations and associated subtypes and metabolic clusters of disease-associated VOCs.

Incorporating Biomarkers in COPD Management: The Research Keeps Going

Globally, chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality, having a significant socioeconomic effect. Several molecular mechanisms have been related to COPD including chronic inflammation, telomere shortening, and epigenetic modifications. Nowadays, there is an increasing need for novel therapeutic approaches for the management of COPD. These treatment strategies should be based on finding the source of acute exacerbation of COPD episodes and estimating the patient’s own risk. The use of biomarkers and the measurement of their levels in conjunction with COPD exacerbation risk and disease prognosis is considered an encouraging approach. Many types of COPD biomarkers have been identified which include blood protein biomarkers, cellular biomarkers, and protease enzymes. They have been isolated from different sources including peripheral blood, sputum, bronchoalveolar fluid, exhaled air, and genetic material. However, there is still not an exclusive biomarker that is used for the evaluation of COPD but rather a combination of them, and this is attributed to disease complexity. In this review, we summarize the clinical significance of COPD-related biomarkers, their association with disease outcomes, and COPD patients’ management. Finally, we depict the various samples that are used for identifying and measuring these biomarkers.

Precision medicine in chronic obstructive pulmonary disease: how far have we come?

PURPOSE OF REVIEW

In this review, we will discuss the current status and recent developments in precision medicine in chronic obstructive pulmonary disease (COPD) through the lens of treatable traits.

RECENT FINDINGS

Although the term 'treatable traits' in the treatment of COPD is relatively recent, this concept has been used for many years if one considers interventions such as long-term oxygen therapy or alpha-1 antitrypsin replacement therapy. Recent advances have included expanding the definition of COPD to include a broader population of people with lower respiratory disease but not meeting the strict criteria for obstruction, advances in imaging to aid in the diagnosis and treatment of COPD, advances in understanding symptoms and exacerbations to define severity, using biomarkers to guide therapy and better understanding and addressing polymorbidity and frailty. In addition, there is a concerted effort to use these concepts to identify COPD patients earlier in the disease process wherein disease modification may be possible.

SUMMARY

Focusing on subsets of patients with COPD with certain characteristics should lead to better outcomes and fewer adverse effects from treatment.

VIDEO ABSTRACT

http://links.lww.com/COPM/A30.

Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors

Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.

Simultaneous measurement of inhaled air and exhaled breath by double multicapillary column ion-mobility spectrometry, a new method for breath analysis: results of a feasibility study

The high sensitivity of the methods applied in breath analysis entails a high risk of detecting analytes that do not derive from endogenous production. Consequentially, it appears useful to have knowledge about the composition of inhaled air and to include alveolar gradients into interpretation.

The current study aimed to standardise sampling procedures in breath analysis, especially with multicapillary column ion-mobility spectrometry (MCC-IMS), by applying a simultaneous registration of inhaled air and exhaled breath.

A “double MCC-IMS” device, which for the first time allows simultaneous analysis of inhaled air and exhaled breath, was developed and tested in 18 healthy individuals. For this, two BreathDiscovery instruments were coupled with each other.

Measurements of inhaled air and exhaled breath in 18 healthy individuals (mean age 46±10.9 years; nine men, nine women) identified 35 different volatile organic compounds (VOCs) for further analysis. Not all of these had positive alveolar gradients and could be regarded as endogenous VOCs: 16 VOCs had a positive alveolar gradient in mean; 19 VOCs a negative one. 12 VOCs were positive in >12 of the healthy subjects.

For the first time in our understanding, a method is described that enables simultaneous measurement of inhaled air and exhaled breath. This facilitates the calculation of alveolar gradients and selection of endogenous VOCs for exhaled breath analysis. Only a part of VOCs in exhaled breath are truly endogenous VOCs. The observation of different and varying polarities of the alveolar gradients needs further analysis.

Simultaneous analysis of inhaled air and exhaled breath by a newly invented double MCC-IMS device shows that exhaled breath contains confounding exogeneous analytes and only a smaller number of truly endogenous VOCs, which can be used for further analysishttps://bit.ly/3HGVzV5

Exhaled volatile organic compounds and lung microbiome in COPD: a pilot randomised controlled trial

Background

Breath analysis is a burgeoning field, with interest in volatile organic compounds (VOCs) as a noninvasive diagnostic tool or an outcome measure, but no randomised controlled trials (RCTs) have yet evaluated this technology in a clinical trial longitudinally. In a pilot RCT, our exploratory objectives were feasibility of measuring VOCs via multiple techniques, assessing relationships between VOCs and Haemophilus colonisation and whether CXCR2 antagonism with danirixin altered lung microbiome composition in individuals with COPD.

Method

43 participants had VOCs and sputum biomarkers evaluated. VOCs and induced sputum were collected after 6 h of fasting at screening and at days 1, 7 and 14. VOCs were analysed via gas chromatography mass spectrometry (GC-MS), field asymmetric ion mobility spectrometry (FAIMS) and eNose. The primary outcome for these analyses was the relationship between VOCs and Haemophilus abundance determined by 16S rRNA sequencing.

Results

A joint-effects model demonstrated a modest relationship between four exhaled VOCs and Haemophilus relative abundance (R²=0.55) measured only by GC-MS, but not as measured using gas chromtaography FAIMS or eNose. There was considerable variability in absolute quantities of individual VOCs longitudinally.

Conclusions

VOC measurement in clinical trials to identify subsets of COPD is feasible, but assessment of new VOC technologies must include concurrent GC-MS validation. Further work to standardise collection of VOCs and measuring a background or “housekeeper” VOC is required to understand and normalise individual VOC quantities.

VOC measurement in clinical trials to identify COPD subsets is feasible, but assessment of VOC technologies must include concurrent GC-MS validation. Further work to standardise collection of VOCs and measure a background or “housekeeper” VOC is required.https://bit.ly/3BNyKvS

Virus-induced Volatile Organic Compounds are Detectable in Exhaled Breath During Pulmonary Infection

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a condition punctuated by acute exacerbations commonly triggered by viral and/or bacterial infection. Early identification of exacerbation trigger is important to guide appropriate therapy but currently available tests are slow and imprecise. Volatile organic compounds (VOCs) can be detected in exhaled breath and have the potential to be rapid tissue-specific biomarkers of infection aetiology.

METHODS

We used serial sampling within in vitro and in vivo studies to elucidate the dynamic changes that occur in VOC production during acute respiratory viral infection. Highly sensitive gas-chromatography mass spectrometry (GC-MS) techniques were used to measure VOC production from infected airway epithelial cell cultures and in exhaled breath samples of healthy subjects experimentally challenged with rhinovirus A16 and COPD subjects with naturally-occurring exacerbations.

RESULTS

We identified a novel VOC signature comprising of decane and other related long chain alkane compounds that is induced during rhinovirus infection of cultured airway epithelial cells and is also increased in the exhaled breath of healthy subjects experimentally challenged with rhinovirus and of COPD patients during naturally-occurring viral exacerbations. These compounds correlated with magnitude of anti-viral immune responses, virus burden and exacerbation severity but were not induced by bacterial infection, suggesting they represent a specific virus-inducible signature.

CONCLUSION

Our study highlights the potential for measurement of exhaled breath VOCs as rapid, non-invasive biomarkers of viral infection. Further studies are needed to determine whether measurement of these signatures could be used to guide more targeted therapy with antibiotic/antiviral agents for COPD exacerbations.

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.

Breathomics for the clinician: the use of volatile organic compounds in respiratory diseases

Exhaled breath analysis has the potential to provide valuable insight on the status of various metabolic pathways taking place in the lungs locally and other vital organs, via systemic circulation. For years, volatile organic compounds (VOCs) have been proposed as feasible alternative diagnostic and prognostic biomarkers for different respiratory pathologies.We reviewed the currently published literature on the discovery of exhaled breath VOCs and their utilisation in various respiratory diseasesKey barriers in the development of clinical breath tests include the lack of unified consensus for breath collection and analysis and the complexity of understanding the relationship between the exhaled VOCs and the underlying metabolic pathways. We present a comprehensive overview, in light of published literature and our experience from coordinating a national breathomics centre, of the progress made to date and some of the key challenges in the field and ways to overcome them. We particularly focus on the relevance of breathomics to clinicians and the valuable insights it adds to diagnostics and disease monitoring.Breathomics holds great promise and our findings merit further large-scale multicentre diagnostic studies using standardised protocols to help position this novel technology at the centre of respiratory disease diagnostics.

Exhaled volatile organic compounds analysis in clinical pediatrics: a systematic review

BACKGROUND

Measured exhaled volatile organic compounds (VOCs) in breath also referred to as exhaled volatilome have been long claimed as a potential source of non-invasive and clinically applicable biomarkers. However, the feasibility of using exhaled volatilome in clinical practice remains to be demonstrated, particularly in pediatrics where the need for improved non-invasive diagnostic and monitoring methods is most urgent. This work presents the first formal evidence-based judgment of the clinical potential of breath volatilome in the pediatric population.

METHODS

A rigorous systematic review across Web of Science, SCOPUS, and PubMed databases following the PRISMA statement guidelines. A narrative synthesis of the evidence was conducted and QUADAS-2 was used to assess the quality of selected studies.

RESULTS

Two independent reviewers deemed 22 out of the 229 records initially found to satisfy inclusion criteria. A summary of breath VOCs found to be relevant for several respiratory, infectious, and metabolic pathologies was conducted. In addition, we assessed their associated metabolism coverage through a functional characterization analysis.

CONCLUSION

Our results indicate that current research remains stagnant in a preclinical exploratory setting. Designing exploratory experiments in compliance with metabolomics practice should drive forward the clinical translation of VOCs breath analysis.

IMPACT

What is the key message of your article? Metabolomics practice could help to achieve the clinical utility of exhaled volatilome analysis. What does it add to the existing literature? This work is the first systematic review focused on disease status discrimination using analysis of exhaled breath in the pediatric population. A summary of the reported exhaled volatile organic compounds is conducted together with a functional characterization analysis. What is the impact? Having noted challenges preventing the clinical translation, we summary metabolomics practices and the experimental designs that are closer to clinical practice to create a framework to guide future trials.

Volatile Organic Compounds in Exhaled Breath as Fingerprints of Lung Cancer, Asthma and COPD

Lung cancer, chronic obstructive pulmonary disease (COPD) and asthma are inflammatory diseases that have risen worldwide, posing a major public health issue, encompassing not only physical and psychological morbidity and mortality, but also incurring significant societal costs. The leading cause of death worldwide by cancer is that of the lung, which, in large part, is a result of the disease often not being detected until a late stage. Although COPD and asthma are conditions with considerably lower mortality, they are extremely distressful to people and involve high healthcare overheads. Moreover, for these diseases, diagnostic methods are not only costly but are also invasive, thereby adding to people’s stress. It has been appreciated for many decades that the analysis of trace volatile organic compounds (VOCs) in exhaled breath could potentially provide cheaper, rapid, and non-invasive screening procedures to diagnose and monitor the above diseases of the lung. However, after decades of research associated with breath biomarker discovery, no breath VOC tests are clinically available. Reasons for this include the little consensus as to which breath volatiles (or pattern of volatiles) can be used to discriminate people with lung diseases, and our limited understanding of the biological origin of the identified VOCs. Lung disease diagnosis using breath VOCs is challenging. Nevertheless, the numerous studies of breath volatiles and lung disease provide guidance as to what volatiles need further investigation for use in differential diagnosis, highlight the urgent need for non-invasive clinical breath tests, illustrate the way forward for future studies, and provide significant guidance to achieve the goal of developing non-invasive diagnostic tests for lung disease. This review provides an overview of these issues from evaluating key studies that have been undertaken in the years 2010–2019, in order to present objective and comprehensive updated information that presents the progress that has been made in this field. The potential of this approach is highlighted, while strengths, weaknesses, opportunities, and threats are discussed. This review will be of interest to chemists, biologists, medical doctors and researchers involved in the development of analytical instruments for breath diagnosis.

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.

Spatial mapping of VOC exhalation by means of bronchoscopic sampling

Breath analysis holds promise for non-invasive in vivo monitoring of disease related processes. However, physiological parameters may considerably affect profiles of exhaled volatile organic substances (VOCs). Volatile substances can be released via alveoli, bronchial mucosa or from the upper airways. The aim of this study was the systematic investigation of the influence of different sampling sites in the respiratory tract on VOC concentration profiles by means of a novel experimental setup. After ethical approval, breath samples were collected from 25 patients undergoing bronchoscopy for endobronchial ultrasound or bronchoscopic lung volume reduction from different sites in the airways. All patients had total intravenous anaesthesia under pressure-controlled ventilation. If necessary, respiratory parameters were adjusted to keep P_ETCO₂ = 35-45 mm Hg. 30 ml gas were withdrawn at six sampling sites by means of gastight glass syringes: S1 = Room air, S2 = Inspiration, S3 = Endotracheal tube, S4 = Trachea, S5 = Right B6 segment, S6 = Left B6 segment (S4-S6 through the bronchoscope channel). 10 ml were used for VOC analysis, 20 ml for PCO₂ determination. Samples were preconcentrated by solid-phase micro-extraction (SPME) and analysed by gas chromatography-mass spectrometry (GC-MS). PCO₂ was determined in a conventional blood gas analyser. Statistically significant differences in substance concentrations for acetone, isoprene, 2-methyl-pentane and n-hexane could be observed between different sampling sites. Increasing substance concentrations were determined for acetone (15.3%), 2-methyl-pentane (11.4%) and n-hexane (19.3%) when passing from distal to proximal sampling sites. In contrast, isoprene concentrations decreased by 9.9% from proximal to more distal sampling sites. Blank bronchoscope measurements did not show any contaminations. Increased substance concentrations in the proximal respiratory tract may be explained through substance excretion from bronchial mucosa while decreased concentrations could result from absorption or reaction processes. Spatial mapping of VOC profiles can provide novel insights into substance specific exhalation kinetics and mechanisms.

Identification of recent exacerbations in COPD patients by electronic nose

Molecular profiling of exhaled breath by electronic nose (eNose) might be suitable as a noninvasive tool that can help in monitoring of clinically unstable COPD patients. However, supporting data are still lacking. Therefore, as a first step, this study aimed to determine the accuracy of exhaled breath analysis by eNose to identify COPD patients who recently exacerbated, defined as an exacerbation in the previous 3 months. Data for this exploratory, cross-sectional study were extracted from the multicentre BreathCloud cohort. Patients with a physician-reported diagnosis of COPD (n=364) on maintenance treatment were included in the analysis. Exacerbations were defined as a worsening of respiratory symptoms requiring treatment with oral corticosteroids, antibiotics or both. Data analysis involved eNose signal processing, ambient air correction and statistics based on principal component (PC) analysis followed by linear discriminant analysis (LDA). Before analysis, patients were randomly divided into a training (n=254) and validation (n=110) set. In the training set, LDA based on PCs 1-4 discriminated between patients with a recent exacerbation or no exacerbation with high accuracy (receiver operating characteristic (ROC)-area under the curve (AUC)=0.98, 95% CI 0.97-1.00). This high accuracy was confirmed in the validation set (AUC=0.98, 95% CI 0.94-1.00). Smoking, health status score, use of inhaled corticosteroids or vital capacity did not influence these results. Exhaled breath analysis by eNose can discriminate with high accuracy between COPD patients who experienced an exacerbation within 3 months prior to measurement and those who did not. This suggests that COPD patients who recently exacerbated have their own exhaled molecular fingerprint that could be valuable for monitoring purposes.

Dependence of the Staphylococcal Volatilome Composition on Microbial Nutrition

In vitro cultivation of staphylococci is fundamental to both clinical and research microbiology, but few studies, to-date, have investigated how the differences in rich media can influence the volatilome of cultivated bacteria. The objective of this study was to determine the influence of rich media composition on the chemical characteristics of the volatilomes of Staphylococcus aureus and Staphylococcus epidermidis. S. aureus (ATCC 12600) and S. epidermidis (ATCC 12228) were cultured in triplicate in four rich complex media (brain heart infusion (BHI), lysogeny broth (LB), Mueller Hinton broth (MHB), and tryptic soy broth (TSB)), and the volatile metabolites produced by each culture were analyzed using headspace solid-phase microextraction combined with comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS). When comparing the chemical compositions of the staph volatilomes by the presence versus absence of volatiles produced in each medium, we observed few differences. However, when the relative abundances of volatiles were included in the analyses, we observed that culturing staph in media containing free glucose (BHI and TSB) resulted in volatilomes dominated by acids and esters (67%). The low-glucose media (LB and MHB) produced ketones in greatest relative abundances, but the volatilome compositions in these two media were highly dissimilar. We conclude that the staphylococcal volatilome is strongly influenced by the nutritional composition of the growth medium, especially the availability of free glucose, which is much more evident when the relative abundances of the volatiles are analyzed, compared to the presence versus absence.

Fish oil supplementation and maintaining muscle mass in chronic disease: state of the evidence

PURPOSE OF REVIEW

Providing eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), in the form of fish oils, to benefit muscle is an emerging area of interest. The aim of this work was to evaluate the current literature that has assessed muscle mass as an outcome during a fish oil intervention in any chronic disease.

RECENT FINDINGS

The vast majority of studies published in the last 3 years (12 of 15) have been conducted in the oncological setting, in patients undergoing treatment for cancers of the gastrointestinal tract, breast, head and neck, lung, cervix, and hematological cancers. Three studies were conducted in patients with chronic obstructive pulmonary disease (COPD). Fish oil was provided as part of nutrient mixtures in 12 studies and as capsules in three studies.

SUMMARY

Overall, the evidence for an effect of fish oil supplementation on muscle mass in patients with cancer undergoing treatment and in COPD remains unequivocal and reveals limited new knowledge in the area of fish oil supplementation in the cancer setting. Recent literature continues to provide mixed evidence on the efficacy of fish oil on muscle mass and function. The present review highlights challenges in comparing and interpreting current studies aimed at testing fish oil supplementation for muscle health.

Acute exacerbations of chronic obstructive pulmonary disease: in search of diagnostic biomarkers and treatable traits

Acute exacerbations of chronic obstructive pulmonary disease (COPD) are associated with a significant mortality, health and economic burden. Their diagnosis, assessment and management remain suboptimal and unchanged for decades. Recent clinical and translational studies revealed that the significant heterogeneity in mechanisms and outcomes of exacerbations could be resolved by grouping them etiologically. This is anticipated to lead to a better understanding of the biological processes that underlie each type of exacerbation and to allow the introduction of precision medicine interventions that could improve outcomes. This review summarises novel data on the diagnosis, phenotyping, targeted treatment and prevention of COPD exacerbations.

Breathomics and treatable traits for chronic airway diseases

PURPOSE OF REVIEW

The long-term management goals of the inflammatory airway diseases asthma and chronic obstructive pulmonary disease (COPD) are similar and focus on symptom control and reduction of exacerbation frequency and severity. Treatable traits have recently been postulated as a management concept which complements the traditional diagnostic labels 'asthma' and 'COPD', thereby focusing on therapy targeted to a patients' individual disease-associated characteristics. Exhaled volatile organic compounds (VOCs) may be utilized as noninvasive biomarker for disease activity or manifestation in asthma and COPD. In this review, we provide an overview of the current achievements concerning exhaled breath analysis in the field of uncontrolled chronic airways diseases.

RECENT FINDINGS

Monitoring of (airway) inflammation and identification of (molecular) phenotypic characteristics in asthma and COPD through exhaled VOC analysis by either mass spectrometry (MS) based or sensor-driven electronic nose technology (eNose) seems to be feasible, however pending confirmation could hamper the valorization of breathomics into clinical tests.

SUMMARY

Exhaled VOC analysis and the management of asthma and COPD through the concept of pulmonary treatable traits are an interesting match. To develop exhaled breath analysis into an added value for pulmonary treatable traits, multicentre studies are required following international standards for study populations, sampling methods and analytical strategies enabling external validation.

Influence of media on the differentiation of Staphylococcus spp. by volatile compounds

Staphylococcus aureus asymptomatically colonizes a third of the world's population, and it is an opportunistic pathogen that can cause life threatening diseases. To diagnose S. aureus infections, it is necessary to differentiate S. aureus from the ubiquitous human commensal Staphylococcus epidermidis, which beneficially colonizes the skin of all humans. Efforts are underway to identify volatile biomarkers for diagnosing S. aureus infections, but to date no studies have investigated whether S. aureus and S. epidermidis can be reliably differentiated under a variety of growth conditions. The overall goal of this study was to evaluate the influence of growth medium on the ability to differentiate S. aureus and S. epidermidis based on their volatile profiles. We used headspace solid-phase microextraction (HS-SPME) and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS) to examine the headspace volatiles of S. aureus and S. epidermidis when aerobically grown in four different complex media. We detected 337 volatile features when culturing S. aureus and S. epidermidis in four complex media, termed the staph volatiles, and found only 20%-40% concurrence in the volatiles produced by these two species in any single medium. Using principal components analysis and hierarchical clustering analysis on the staph volatiles, we observed that S. aureus and S. epidermidis clustered independently from each other, and distinctly clustered by growth medium within species. Removing volatiles that are species and/or media-specific from the analysis reduced the resolution between species clusters, but in all models clustering by species overrode clustering by media type. These analyses suggest that, while volatile profiles are media-specific, species differences dominate the staph volatilome. These data enable future investigations into the identification of volatile biomarkers to discriminate staphylococcal pathogens versus commensals, which will improve staph diagnoses and provide insights into the biochemistry of staph infections and immunity.

Exhaled Breath Profiles Before, During and After Exacerbation of COPD: A Prospective Follow-Up Study

Many patients with chronic obstructive lung disease (COPD) experience exacerbations. The diagnosis of an exacerbation is solely based on symptoms. We hypothesized that exhaled breath profiles, measured by Gas Chromatography-Mass Spectrometry (GC-MS) or electronic nose (eNose), are different between stable disease and exacerbations and may have the potential to serve as biomarkers for COPD exacerbations. In this prospective follow-up study, breath samples were taken during stable COPD, during a subsequent exacerbation and after recovery. Samples were analyzed by GC-MS and eNose. CCQ symptom scores were associated with univariate outcomes of GC-MS and eNose using analysis of covariance (ANCOVA). After multivariate modeling by Principal Component Analysis (PCA), paired student t-tests were performed. Sixty-eight patients were included, 31 had an exacerbation and 16 patients had breath sampled at all three time points. Significant differences were found in breathprints taken during exacerbation as compared to baseline and recovery for both GC-MS and eNose. Breath profiles obtained by GC-MS as well as by eNose showed a correct classification of 71% (10/14) for baseline vs exacerbation and of 78% (11/14) for exacerbation vs recovery. These results provide proof of principle that exhaled breath can serve as a noninvasive biomarker for the diagnosis of COPD exacerbations.

Breath selection methods for compact mass spectrometry breath analysis

Compact mass spectrometry (CMS) is a versatile and transportable analytical instrument that has the potential to be used in clinical settings to quickly and non-invasively detect a wide range of relevant conditions from breath samples. The purpose of this study is to optimise data preprocessing protocols by three proposed methods of breath sampling, using the CMS. It also lays out a general framework for which data processing methods can be evaluated.

METHODS

This paper considers data from three previous studies, each using a different breath sampling method. These include a peppermint washout study using continuous breath sampling with a purified air source, an exercise study using continuous breath sampling with an ambient air source, and a single breath sampling study with an ambient air source. For each dataset, different breath selection (data preprocessing) methods were compared and benchmarked according to predictive performance on a validation set and quantitative reliability of m/z bin intensity measurements.

RESULTS

For both continuous methods, the best breath selection method improved the predictive model compared to no preselection, as measured by the 95% CI range for Youden's index, from 0.68-0.86 to 0.86-0.97 for the exercise study and 0.69-0.82 to 1.00-1.00 for the peppermint study. The reliability of intensity measurements for both datasets (as measured by median relative standard deviation (RSD)), was improved slightly by the best selection method compared to no preselection, from 18% to 14% for the exercise study and 7%-5% for the peppermint study. For the single breath samples, all the models resulted in perfect prediction, with a 95% CI range for Youden's index of 1.00-1.00. The reliability of the proposed method was 38%.

CONCLUSION

The method of selecting exhaled breath from CMS data can affect the reliability of the measurement and the ability to distinguish between breath samples taken under different conditions. The application of appropriate data processing methods can improve the quality of the data and results obtained from CMS. The methods presented will enable untargeted analysis of breath VOCs using CMS to be performed.

Ultrafast gas chromatography coupled to electronic nose to identify volatile biomarkers in exhaled breath from chronic obstructive pulmonary disease patients: A pilot study

An analytical method to identify volatile organic compounds (VOCs) in the exhaled breath from patients with a diagnosis of chronic obstructive pulmonary disease (COPD) using a ultrafast gas chromatography system equipped with an electronic nose detector (FGC eNose) has been developed. A prospective study was performed in 23 COPD patients and 33 healthy volunteers; exhalation breathing tests were performed with Tedlar bags. Each sample was analyzed by FCG eNose and the identification of VOCs was based on the Kovats index. Raw data were reduced by principal component analysis (PCA) and canonical discriminant analysis [canonical analysis of principal coordinates (CAP)]. The FCG eNose technology was able to identify 17 VOCs that distinguish COPD patients from healthy volunteers. At all stages of PCA and CAP the discrimination between groups was obvious. Chemical prints were correctly classified up to 82.2%, and were matched with 78.9% of the VOCs detected in the exhaled breath samples. Receiver operating characteristic curve analysis indicated the sensitivity and specificity to be 96% and 91%, respectively. This pilot study demonstrates that FGC eNose is a useful tool to identify VOCs as biomarkers in exhaled breath from COPD patients. Further studies should be performed to enhance the clinical relevance of this quick and ease methodology for COPD diagnosis.

Discovery of Volatile Biomarkers of Parkinson's Disease from Sebum

Parkinson's disease (PD) is a progressive, neurodegenerative disease that presents with significant motor symptoms, for which there is no diagnostic chemical test. We have serendipitously identified a hyperosmic individual, a "Super Smeller" who can detect PD by odor alone, and our early pilot studies have indicated that the odor was present in the sebum from the skin of PD subjects. Here, we have employed an unbiased approach to investigate the volatile metabolites of sebum samples obtained noninvasively from the upper back of 64 participants in total (21 controls and 43 PD subjects). Our results, validated by an independent cohort (n=31), identified a distinct volatiles-associated signature of PD, including altered levels of perillic aldehyde and eicosane, the smell of which was then described as being highly similar to the scent of PD by our "Super Smeller".

Machine Learning in Human Olfactory Research

The complexity of the human sense of smell is increasingly reflected in complex and high-dimensional data, which opens opportunities for data-driven approaches that complement hypothesis-driven research. Contemporary developments in computational and data science, with its currently most popular implementation as machine learning, facilitate complex data-driven research approaches. The use of machine learning in human olfactory research included major approaches comprising 1) the study of the physiology of pattern-based odor detection and recognition processes, 2) pattern recognition in olfactory phenotypes, 3) the development of complex disease biomarkers including olfactory features, 4) odor prediction from physico-chemical properties of volatile molecules, and 5) knowledge discovery in publicly available big databases. A limited set of unsupervised and supervised machine-learned methods has been used in these projects, however, the increasing use of contemporary methods of computational science is reflected in a growing number of reports employing machine learning for human olfactory research. This review provides key concepts of machine learning and summarizes current applications on human olfactory data.

Orthogonal gas sensor arrays by chemoresistive material design

Gas sensor arrays often lack discrimination power to different analytes and robustness to interferants, limiting their success outside of research laboratories. This is primarily due to the widely sensitive (thus weakly-selective) nature of the constituent sensors. Here, the effect of orthogonality on array accuracy and precision by selective sensor design is investigated. Therefore, arrays of (2-5) selective and non-selective sensors are formed by systematically altering array size and composition. Their performance is evaluated with 60 random combinations of ammonia, acetone and ethanol at ppb to low ppm concentrations. Best analyte predictions with high coefficients of determination (R²) of 0.96 for ammonia, 0.99 for acetone and 0.88 for ethanol are obtained with an array featuring high degree of orthogonality. This is achieved by using distinctly selective sensors (Si:MoO₃ for ammonia and Si:WO₃ for acetone together with Si:SnO₂) that improve discrimination power and stability of the regression coefficients. On the other hand, arrays with collinear sensors (Pd:SnO₂, Pt:SnO₂ and Si:SnO₂) hardly improve gas predictions having R² of 0.01, 0.86 and 0.28 for ammonia, acetone and ethanol, respectively. Sometimes they even exhibited lower coefficient of determination than single sensors as a Si:MoO₃ sensor alone predicts ammonia better with a R² of 0.68. Graphical abstract Conventional arrays (red) with weakly-selective sensors span a significantly smaller volume in the analyte space than arrays containing distinctly-selective sensors (orthogonal array, green). Orthogonal arrays feature better accuracy and precision than conventional arrays in mixtures of ammonia, acetone and ethanol.