Exhaled Volatile Organic Compounds Are Able to Discriminate between Neutrophilic and Eosinophilic Asthma

Porosity Engineering of Dried Smart Poly(N-isopropylacrylamide) Hydrogels for Gas Sensing

A recent study unveiled the potential of acrylamide-based stimulus-responsive hydrogels for volatile organic compound detection in gaseous environments. However, for gas sensing, a large surface area, that is, a highly porous material, offering many adsorption sites is crucial. The large humidity variation in the gaseous environment constitutes a significant challenge for preserving an initially porous structure, as the pores tend to be unstable and irreversibly collapse. Therefore, the present investigation focuses on enhancing the porosity of smart PNiPAAm hydrogels under the conditions of a gaseous environment and the preservation of the structural integrity for long-term use. We have studied the influence of polyethylene glycol (PEG) as a porogen and the application of different drying methods and posttreatment. The investigations lead to the conclusion that only the combination of PEG addition, freeze-drying, and subsequent conditioning in high relative humidity enables a long-term stable formation of a porous surface and inner structure of the material. The significantly enhanced swelling response in a gaseous environment and in the test gas acetone is confirmed by gravimetric experiments of bulk samples and continuous measurements of thin films on piezoresistive pressure sensor chips. These measurements are furthermore complemented by an in-depth analysis of the morphology and microstructure. While the study was conducted for PNiPAAm, the insights and developed processes are general in nature and can be applied for porosity engineering of other smart hydrogel materials for VOC detection in gaseous environments.

Identification of exhaled volatile organic compounds that characterize asthma phenotypes: A J-VOCSA study

BACKGROUND

Asthma is characterized by phenotypes of different clinical, demographic, and pathological characteristics. Identifying the profile of exhaled volatile organic compounds (VOCs) in asthma phenotypes may facilitate establishing biomarkers and understanding asthma background pathogenesis. This study aimed to identify exhaled VOCs that characterize severe asthma phenotypes among patients with asthma.

METHODS

This was a multicenter cross-sectional study of patients with severe asthma in Japan. Clinical data were obtained from medical records, and questionnaires were collected. Exhaled breath was sampled and subjected to thermal desorption gas chromatography-mass spectrometry (GC/MS).

RESULTS

Using the decision tree established in the previous nationwide asthma cohort study, 245 patients with asthma were divided into five phenotypes and subjected to exhaled VOC analysis with 50 healthy controls (HCs). GC/MS detected 243 VOCs in exhaled breath samples, and 142 frequently detected VOCs (50% of all samples) were used for statistical analyses. Cluster analysis assigning the groups with similar VOC profile patterns showed the highest similarities between phenotypes 3 and 4 (early-onset asthma phenotypes), followed by the similarities between phenotypes 1 and 2 (late-onset asthma phenotypes). Comparisons between phenotypes 1-5 and HC revealed 19 VOCs, in which only methanesulfonic anhydride showed p < 0.05 adjusted by false discovery rate (FDR). Comparison of these phenotypes yielded several VOCs showing different trends (p < 0.05); however, no VOCs showed p < 0.05 adjusted by FDR.

CONCLUSIONS

Exhaled VOC profiles may be useful for distinguishing asthma and asthma phenotypes; however, these findings need to be validated, and their pathological roles should be clarified.

Exhaled breath analyses for bronchial thermoplasty in severe asthma patients

BACKGROUND

Bronchial thermoplasty (BT) is a bronchoscopic treatment for severe asthma. Although multiple trials have demonstrated clinical improvement after BT, optimal patient selection remains a challenge and the mechanism of action is incompletely understood. The aim of this study was to examine whether exhaled breath analysis can contribute to discriminate between BT-responders and non-responders at baseline and to explore pathophysiological insights of BT.

METHODS

Exhaled breath was collected from patients at baseline and six months post-BT. Patients were defined as responders or non-responders based on a half point increase in asthma quality of life questionnaire scores. Gas chromatography-mass spectrometry was used for volatile organic compounds (VOCs) detection and analyses. Analytical workflow consisted of: 1) detection of VOCs that differentiate between responders and non-responders and those that differ between baseline and six months post-BT, 2) identification of VOCs of interest and 3) explore correlations between clinical biomarkers and VOCs.

RESULTS

Data was available from 14 patients. Nonanal, 2-ethylhexanol and 3-thujol showed a significant difference in intensity between responders and non-responders at baseline (p = 0.04, p = 0.01 and p = 0.03, respectively). After BT, no difference was found in the compound intensity of these VOCs. A negative correlation was observed between nonanal and IgE and BALF eosinophils (r = -0.68, p < 0.01 and r = -0.61, p = 0.02 respectively) and 3-thujol with BALF neutrophils (r = -0.54, p = 0.04).

CONCLUSIONS

This explorative study identified discriminative VOCs in exhaled breath between BT responders and non-responders at baseline. Additionally, correlations were found between VOC's and inflammatory BALF cells. Once validated, these findings encourage research in breath analysis as a non-invasive easy to apply technique for identifying airway inflammatory profiles and eligibility for BT or immunotherapies in severe asthma.

Phenotyping of Severe Asthma in the Era of Broad-Acting Anti-Asthma Biologics

Severe asthma is associated with significant morbidity and mortality despite the maximal use of inhaled corticosteroids and additional controller medications, and has a high economic burden. Biologic therapies are recommended for the management of severe, uncontrolled asthma to help to prevent exacerbations and to improve symptoms and health-related quality of life. The effective management of severe asthma requires consideration of clinical heterogeneity that is driven by varying clinical and inflammatory phenotypes, which are reflective of distinct underlying disease mechanisms. Phenotyping patients using a combination of clinical characteristics such as the age of onset or comorbidities and biomarker profiles, including blood eosinophil counts and levels of fractional exhaled nitric oxide and serum total immunoglobulin E, is important for the differential diagnosis of asthma. In addition, phenotyping is beneficial for risk assessment, selection of treatment, and monitoring of the treatment response in patients with asthma. This review describes the clinical and inflammatory phenotypes of asthma, provides an overview of biomarkers routinely used in clinical practice and those that have recently been explored for phenotyping, and aims to assess the value of phenotyping in severe asthma management in the current era of biologics.

Real-Time Monitoring of Air Pollution Health Impacts Using Breath-Borne Gaseous Biomarkers from Rats

Offline techniques are adopted for studying air pollution health impacts, thus failing to provide in situ observations. Here, we have demonstrated their real-time monitoring by online analyzing an array of gaseous biomarkers from rats' exhaled breath using an integrated exhaled breath array sensor (IEBAS) developed. The biomarkers include total volatile organic compounds (TVOC), CO2, CO, NO, H2S, H2O2, O2, and NH3. Specific breath-borne VOCs were also analyzed by a gas chromatography-ion mobility spectrometer (GC-IMS). After real-life ambient air pollution exposures (2 h), the pollution levels of PM2.5 and O3 were both found to significantly affect the relative levels of multiple gaseous biomarkers in rats' breath. Eleven biomarkers, especially NO, H2S, and 1-propanol, were detected as significantly correlated with PM2.5 concentration, while heptanal was shown to be significantly correlated with O3. Likewise, significant changes were also detected in multiple breath-borne biomarkers from rats under lab-controlled O3 exposures with levels of 150, 300, and 1000 μg/m3 (2 h), compared to synthetic air exposure. Importantly, heptanal was experimentally confirmed as a reliable biomarker for O3 exposure, with a notable dose-response relationship. In contrast, conventional biomarkers of inflammation and oxidative stress in rat sera exhibited insignificant differences after the 2 h exposures. The results imply that breath-borne gaseous biomarkers can serve as an early and sensitive indicator for ambient pollutant exposure. This work pioneered a new research paradigm for online monitoring of air pollution health impacts while obtaining important candidate biomarker information for PM2.5 and O3 exposures.

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.

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.

Theoretical modeling and machine learning-based data processing workflows in comprehensive two-dimensional gas chromatography-A review

In recent years, comprehensive two-dimensional gas chromatography (GC × GC) has been gradually gaining prominence as a preferred method for the analysis of complex samples due to its higher peak capacity and resolution power compared to conventional gas chromatography (GC). Nonetheless, to fully benefit from the capabilities of GC × GC, a holistic approach to method development and data processing is essential for a successful and informative analysis. Method development enables the fine-tuning of the chromatographic separation, resulting in high-quality data. While generating such data is pivotal, it does not necessarily guarantee that meaningful information will be extracted from it. To this end, the first part of this manuscript reviews the importance of theoretical modeling in achieving good optimization of the separation conditions, ultimately improving the quality of the chromatographic separation. Multiple theoretical modeling approaches are discussed, with a special focus on thermodynamic-based modeling. The second part of this review highlights the importance of establishing robust data processing workflows, with a special emphasis on the use of advanced data processing tools such as, Machine Learning (ML) algorithms. Three widely used ML algorithms are discussed: Random Forest (RF), Support Vector Machine (SVM), and Partial Least Square-Discriminate Analysis (PLS-DA), highlighting their role in discovery-based analysis.

The State of the Art on Graphene-Based Sensors for Human Health Monitoring through Breath Biomarkers

The field of organic-borne biomarkers has been gaining relevance due to its suitability for diagnosing pathologies and health conditions in a rapid, accurate, non-invasive, painless and low-cost way. Due to the lack of analytical techniques with features capable of analysing such a complex matrix as the human breath, the academic community has focused on developing electronic noses based on arrays of gas sensors. These sensors are assembled considering the excitability, sensitivity and sensing capacities of a specific nanocomposite, graphene. In this way, graphene-based sensors can be employed for a vast range of applications that vary from environmental to medical applications. This review work aims to gather the most relevant published papers under the scope of "Graphene sensors" and "Biomarkers" in order to assess the state of the art in the field of graphene sensors for the purposes of biomarker identification. During the bibliographic search, a total of six pathologies were identified as the focus of the work. They were lung cancer, gastric cancer, chronic kidney diseases, respiratory diseases that involve inflammatory processes of the airways, like asthma and chronic obstructive pulmonary disease, sleep apnoea and diabetes. The achieved results, current development of the sensing sensors, and main limitations or challenges of the field of graphene sensors are discussed throughout the paper, as well as the features of the experiments addressed.

Increased breath naphthalene in children with asthma and wheeze of the All Age Asthma Cohort (ALLIANCE)

Exhaled breath contains numerous volatile organic compounds (VOCs) known to be related to lung disease like asthma. Its collection is non-invasive, simple to perform and therefore an attractive method for the use even in young children. We analysed breath in children of the multicenter All Age Asthma Cohort (ALLIANCE) to evaluate if 'breathomics' have the potential to phenotype patients with asthma and wheeze, and to identify extrinsic risk factors for underlying disease mechanisms. A breath sample was collected from 142 children (asthma: 51, pre-school wheezers: 55, healthy controls: 36) and analysed using gas chromatography-mass spectrometry (GC/MS). Children were diagnosed according to Global Initiative for Asthma guidelines and comprehensively examined each year over up to seven years. Forty children repeated the breath collection after 24 or 48 months. Most breath VOCs differing between groups reflect the exposome of the children. We observed lower levels of lifestyle-related VOCs and higher levels of the environmental pollutants, especially naphthalene, in children with asthma or wheeze. Naphthalene was also higher in symptomatic patients and in wheezers with recent inhaled corticosteroid use. No relationships with lung function or TH2 inflammation were detected. Increased levels of naphthalene in asthmatics and wheezers and the relationship to disease severity could indicate a role of environmental or indoor air pollution for the development or progress of asthma. Breath VOCs might help to elucidate the role of the exposome for the development of asthma. The study was registered at ClinicalTrials.gov (NCT02496468).

Enhanced real-time mass spectrometry breath analysis for the diagnosis of COVID-19

Background

Although rapid screening for and diagnosis of coronavirus disease 2019 (COVID-19) are still urgently needed, most current testing methods are long, costly or poorly specific. The objective of the present study was to determine whether or not artificial-intelligence-enhanced real-time mass spectrometry breath analysis is a reliable, safe, rapid means of screening ambulatory patients for COVID-19.

Methods

In two prospective, open, interventional studies in a single university hospital, we used real-time, proton transfer reaction time-of-flight mass spectrometry to perform a metabolomic analysis of exhaled breath from adults requiring screening for COVID-19. Artificial intelligence and machine learning techniques were used to build mathematical models based on breath analysis data either alone or combined with patient metadata.

Results

We obtained breath samples from 173 participants, of whom 67 had proven COVID-19. After using machine learning algorithms to process breath analysis data and further enhancing the model using patient metadata, our method was able to differentiate between COVID-19-positive and -negative participants with a sensitivity of 98%, a specificity of 74%, a negative predictive value of 98%, a positive predictive value of 72% and an area under the receiver operating characteristic curve of 0.961. The predictive performance was similar for asymptomatic, weakly symptomatic and symptomatic participants and was not biased by COVID-19 vaccination status.

Conclusions

Real-time, noninvasive, artificial-intelligence-enhanced mass spectrometry breath analysis might be a reliable, safe, rapid, cost-effective, high-throughput method for COVID-19 screening.

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.

Phenotype overlap in the natural history of asthma

The heterogeneity of asthma makes it challenging to unravel the pathophysiologic mechanisms of the disease. Despite the wealth of research identifying diverse phenotypes, many gaps still remain in our knowledge of the disease's complexity. A crucial aspect is the impact of airborne factors over a lifetime, which often results in a complex overlap of phenotypes associated with type 2 (T2), non-T2 and mixed inflammation. Evidence now shows overlaps between the phenotypes associated with T2, non-T2 and mixed T2/non-T2 inflammation. These interconnections could be induced by different determinants such as recurrent infections, environmental factors, T-helper plasticity and comorbidities, collectively resulting in a complex network of distinct pathways generally considered as mutually exclusive. In this scenario, we need to abandon the concept of asthma as a disease characterised by distinct traits grouped into static segregated categories. It is now evident that there are multiple interplays between the various physiologic, cellular and molecular features of asthma, and the overlap of phenotypes cannot be ignored.

Cytokine-targeted therapies for asthma and COPD

Asthma affects over 300 million people worldwide and its prevalence is increasing. COPD is the third leading cause of death globally. Asthma and COPD are complex inflammatory diseases of the airways in which impaired host defences lead to increased susceptibility to pathogens, pollutants and allergens. There is a constant interplay between host and the environment. Environmental exposures can alter the lung microbiome and influence the development of sensitisation by disrupting normal immunoregulation. The underlying airway inflammation in severe asthma is heterogeneous, with upregulation of type 2 cytokines in most cases but increased neutrophilic inflammation and activated T-helper 17 mediated immunity in others. COPD may also comprise several different phentoypes that are driven by different molecular mechanisms or endotypes. This disease heterogeneity is affected by comorbidities, treatments and environmental exposures. Recent intervention trials have shed light on the pathways beyond type 2 inflammation that can lead to beneficial outcomes versus potentially deleterious effects. We have made a great deal of progress over the last 10 years in terms of immunology and the pathophysiology of asthma and this has led to the development of novel treatments and major improvements in severe asthma outcomes. In COPD, however, no targeted treatments have demonstrated great improvements. This article reviews the mechanism of action and efficacy of the available biologics in asthma and COPD.

Comprehensive Insight into Colorectal Cancer Metabolites and Lipids for Human Serum: A Proof-of-Concept Study

Colorectal cancer (CRC) ranks as the third most frequently diagnosed cancer and the second leading cause of cancer-related deaths. The current endoscopic-based or stool-based diagnostic techniques are either highly invasive or lack sufficient sensitivity. Thus, there is a need for less invasive and more sensitive screening approaches. We, therefore, conducted a study on 64 human serum samples representing three different groups (adenocarcinoma, adenoma, and control) using cutting-edge GC×GC-LR/HR-TOFMS (comprehensive two-dimensional gas chromatography coupled with low/high-resolution time-of-flight mass spectrometry). We analyzed samples with two different specifically tailored sample preparation approaches for lipidomics (fatty acids) (25 μL serum) and metabolomics (50 μL serum). In-depth chemometric screening with supervised and unsupervised approaches and metabolic pathway analysis were applied to both datasets. A lipidomics study revealed that specific PUFA (ω-3) molecules are inversely associated with increased odds of CRC, while some PUFA (ω-6) analytes show a positive correlation. The metabolomics approach revealed downregulation of amino acids (alanine, glutamate, methionine, threonine, tyrosine, and valine) and myo-inositol in CRC, while 3-hydroxybutyrate levels were increased. This unique study provides comprehensive insight into molecular-level changes associated with CRC and allows for a comparison of the efficiency of two different analytical approaches for CRC screening using same serum samples and single instrumentation.

Synergistic Effect of Diet and Physical Activity on a NAFLD Cohort: Metabolomics Profile and Clinical Variable Evaluation

Together with its comorbidities, nonalcoholic fatty liver disease (NAFLD) is likely to rise further with the obesity epidemic. However, the literature's evidence shows how its progression can be reduced by the administration of calorie-restrictive dietary interventions and physical activity regimens. The liver function and the gut microbiota have been demonstrated to be closely related. With the aim of ascertaining the impact of a treatment based on the combination of diet and physical activity (versus physical activity alone), we recruited 46 NAFLD patients who were divided into two groups. As a result, we traced the connection between volatile organic compounds (VOCs) from fecal metabolomics and a set of statistically filtered clinical variables. Additionally, we identified the relative abundances of gut microbiota taxa obtained from 16S rRNA gene sequencing. Statistically significant correlations emerged between VOCs and clinical parameters, as well as between VOCs and gut microbiota taxa. In comparison with a physical activity regimen alone, we disclose how ethyl valerate and pentanoic acid butyl ester, methyl valerate, and 5-hepten-2-one, 6-methyl changed because of the positive synergistic effect exerted by the combination of the Mediterranean diet and physical activity regimens. Moreover, 5-hepten-2-one, 6-methyl positively correlated with Sanguinobacteroides, as well as the two genera Oscillospiraceae-UCG002 and Ruminococcaceae UCG010 genera.

Metabolomics of asthma, COPD, and asthma-COPD overlap: an overview

The two common progressive lung diseases, asthma and chronic obstructive pulmonary disease (COPD), are the leading causes of morbidity and mortality worldwide. Asthma-COPD overlap, referred to as ACO, is another complex pulmonary disease that manifests itself with features of both asthma and COPD. The disease has no clear diagnostic or therapeutic guidelines, thereby making both diagnosis and treatment challenging. Though a number of studies on ACO have been documented, gaps in knowledge regarding the pathophysiologic mechanism of this disorder exist. Addressing this issue is an urgent need for improved diagnostic and therapeutic management of the disease. Metabolomics, an increasingly popular technique, reveals the pathogenesis of complex diseases and holds promise in biomarker discovery. This comprehensive narrative review, comprising 99 original research articles in the last five years (2017-2022), summarizes the scientific advances in terms of metabolic alterations in patients with asthma, COPD, and ACO. The analytical tools, nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS), commonly used to study the expression of the metabolome, are discussed. Challenges frequently encountered during metabolite identification and quality assessment are highlighted. Bridging the gap between phenotype and metabotype is envisioned in the future.

Evaluating the effects of vitamin D Level on airway obstruction in two asthma endotypes in humans and in two mouse models with different intake of vitamin D during early-life

Introduction

Asthma is primarily divided into two categories: type 2 (T2-high) and non-type 2 (T2-low). A relationship between asthma severity and vitamin D deficiency has been identified, but its impact on each asthma endotype remains unknown.

Methods

We clinically examined the influence of vitamin D on patients with T2-high (n = 60) or T2-low asthma (n = 36) compared with controls (n = 40). Serum 25(OH)D levels, inflammatory cytokines and spirometry were measured. Mouse models were then used to further analyze the effects of vitamin D on both asthmatic endotypes. BALB/c mice were fed with vitamin D-deficient (LVD), -sufficient (NVD), or -supplemented diets (HVD) throughout lactation and offspring followed the same diet after weaning. Offspring were sensitized/challenged with ovalbumin (OVA) to establish "T2-high" asthma or OVA combined with ozone exposure (OVA + ozone) to induce "T2-low" asthma. Spirometry and serum, bronchoalveolar lavage fluid (BALF), and lung tissues were analyzed.

Results

Serum 25(OH)D levels were decreased in asthmatic patients compared with controls. Patients with vitamin D deficiency (Lo) had varying degrees of elevation of the pro-inflammatory cytokines IL-5, IL-6, and IL-17A, decreased expression of the anti-inflammatory cytokine IL-10, and altered forced expiratory volume in the first second as a percentage of predicted value (FEV₁%pred) in both asthmatic endotypes. Vitamin D status had a stronger correlation with FEV₁%pred in T2-low asthma than T2-high asthma, and 25(OH)D level was only positively linked to maximal mid-expiratory flow as a percentage of predicted value (MMEF%pred) in the T2-low group. Inflammation, hyperresponsiveness, and airway resistance (R_L) was increased in both asthma models compared with controls while vitamin D deficiency further increased airway inflammation and airway obstruction. These findings were particularly prominent in T2-low asthma.

Discussion

The potential function and mechanisms of vitamin D and both asthma endotypes should be studied individually, and further analysis of the potential signaling pathways involved with vitamin D on T2-low asthma is warranted.

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.

Top-Down Approach to Retention Time Prediction in Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry

In this contribution, we describe a novel modeling approach to predicting retention times (t_r) in comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-ToF-MS) with a particular emphasis on the second-dimension (²D) retention time predictions (²t_r). This approach is referred to as a "top-down" approach in that it breaks down the complete GC × GC separation into two independent one-dimensional gas chromatography separations (1D-GC). In this regard, both dimensions, that is, first dimension (¹D) and second dimension (²D) are treated separately, and the cryogenic modulator is simply considered as a second consecutive injection device. Separate 1D-GC t_r predictions are performed on both dimensions using the same flow rate as the one deployed in the conventional GC × GC system. The separate t_r predictions are then combined to account for the two-dimensional separation. This model was applied to 24 analytes from 2 standard mixtures (Grob Test Mix and Fragrance Materials Test Mix) and assessed across 9 GC × GC chromatographic conditions. The experimental and predicted chromatographic retention space occupations were assessed by using the convex hull approach defined by the Delaunay triangulation. The predicted percentage of space occupation corresponded favorably with the experimental values. Furthermore, the top-down approach enabled an accurate prediction of the ²t_r of all investigated analytes, providing an average ²t_r modeling error of 0.26 ± 0.01 s.

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.

Recent advances in the treatment of childhood asthma: a clinical pharmacology perspective

INTRODUCTION

Childhood asthma is a complex heterogenous inflammatory disease that can pose a large burden on patients and their caregivers. There is a strong need to adapt asthma treatment to the individual patient taking into account underlying inflammatory profiles, moving from a 'one size fits all' approach toward a much-needed personalized approach.

AREAS COVERED

This review article aims to provide an overview of recent advances in the management and treatment of pediatric asthma, including novel insights on the molecular heterogeneity of childhood asthma, the emergence of biologicals to treat severe asthma, and innovative e-health and home monitoring techniques to make asthma management more convenient and accessible.

EXPERT OPINION

Molecular technologies have provided new treatment leads. E-health and home monitoring technologies have helped to gain more insights into disease dynamics and improve adherence to treatment while bringing health care to the patient. However, uncontrolled childhood asthma is still a major unmet clinical need and precision-medicine approaches are still scarce in clinical practice. Advanced omics methods may help researchers or clinicians to more accurately phenotype and treat subtypes of childhood asthma and gain more insight into the complexity of the disease.

Measurement of Exhaled Volatile Organic Compounds as a Biomarker for Personalised Medicine: Assessment of Short-Term Repeatability in Severe Asthma

The measurement of exhaled volatile organic compounds (VOCs) in exhaled breath (breathomics) represents an exciting biomarker matrix for airways disease, with early research indicating a sensitivity to airway inflammation. One of the key aspects to analytical validity for any clinical biomarker is an understanding of the short-term repeatability of measures. We collected exhaled breath samples on 5 consecutive days in 14 subjects with severe asthma who had undergone extensive clinical characterisation. Principal component analysis on VOC abundance across all breath samples revealed no variance due to the day of sampling. Samples from the same patients clustered together and there was some separation according to T2 inflammatory markers. The intra-subject and between-subject variability of each VOC was calculated across the 70 samples and identified 30.35% of VOCs to be erratic: variable between subjects but also variable in the same subject. Exclusion of these erratic VOCs from machine learning approaches revealed no apparent loss of structure to the underlying data or loss of relationship with salient clinical characteristics. Moreover, cluster evaluation by the silhouette coefficient indicates more distinct clustering. We are able to describe the short-term repeatability of breath samples in a severe asthma population and corroborate its sensitivity to airway inflammation. We also describe a novel variance-based feature selection tool that, when applied to larger clinical studies, could improve machine learning model predictions.

Effects of carbon black nanoparticles and high humidity on the lung metabolome in Balb/c mice with established allergic asthma

In respiratory diseases, the induction of allergic asthma has gradually aroused public concerns. Co-exposures of environmental risk factors such as nanoparticles and high humidity could play important roles in the development of allergic asthma. However, the relevant researches are still lacking and the involved mechanisms, especially metabolic changes, remain unclear. We took the lead in studying the combined induction effect and underlying mechanisms of carbon black nanoparticles (CB NPs) and high humidity on allergic asthma. In this work, murine models of allergic asthma were established with ovalbumin under the single and combined exposures of 15 μg/kg CB NPs and 90% relative humidity. The two risk factors, particularly their co-exposure, exhibited adjuvant effect on airway hyperresponsiveness, remodeling, and inflammation in Balb/c mice. Untargeted metabolomics identified the potential biomarkers in lung for asthma occurrence and for asthma exacerbation caused by CB NPs and high humidity. The significantly dysregulated metabolic pathways in asthmatic mice were proposed, and the disturbed metabolic pathways under the exposures of CB NPs and/or high humidity were mainly implicated in asthma symptoms. This work sheds light on the understanding for health risks of NP pollutions and high environmental humidity and contributes to useful biomarker identification and asthma control.

Hybrid learning method based on feature clustering and scoring for enhanced COVID-19 breath analysis by an electronic nose

Breath pattern analysis based on an electronic nose (e-nose), which is a noninvasive, fast, and low-cost method, has been continuously used for detecting human diseases, including the coronavirus disease 2019 (COVID-19). Nevertheless, having big data with several available features is not always beneficial because only a few of them will be relevant and useful to distinguish different breath samples (i.e., positive and negative COVID-19 samples). In this study, we develop a hybrid machine learning-based algorithm combining hierarchical agglomerative clustering analysis and permutation feature importance method to improve the data analysis of a portable e-nose for COVID-19 detection (GeNose C19). Utilizing this learning approach, we can obtain an effective and optimum feature combination, enabling the reduction by half of the number of employed sensors without downgrading the classification model performance. Based on the cross-validation test results on the training data, the hybrid algorithm can result in accuracy, sensitivity, and specificity values of (86 ± 3)%, (88 ± 6)%, and (84 ± 6)%, respectively. Meanwhile, for the testing data, a value of 87% is obtained for all the three metrics. These results exhibit the feasibility of using this hybrid filter-wrapper feature-selection method to pave the way for optimizing the GeNose C19 performance.

Haze Air Pollution Health Impacts of Breath-Borne VOCs

Here, we investigated the use of breath-borne volatile organic compounds (VOCs) for rapid monitoring of air pollution health effects on humans. Forty-seven healthy college students were recruited, and their exhaled breath samples (n = 235) were collected and analyzed for VOCs before, on, and after two separate haze pollution episodes using gas chromatography-ion mobility spectrometry (GC-IMS). Using a paired t-test and machine learning model (Gradient Boosting Machine, GBM), six exhaled VOC species including propanol and isoprene were revealed to differ significantly among pre-, on-, and post-exposure in both haze episodes, while none was found between clean control days. The GBM model was shown capable of differentiating between pre- and on-exposure to haze pollution with a precision of 90-100% for both haze episodes. However, poor performance was detected for the same model between two different clean days. In addition to gender and particular haze occurrence influences, correlation analysis revealed that NH₄⁺, NO₃^-, acetic acid, mesylate, CO, NO₂, PM_2.5, and O₃ played important roles in the changes in breath-borne VOC fingerprints following haze air pollution exposure. This work has demonstrated direct evidence of human health impacts of haze pollution while identifying potential breath-borne VOC biomarkers such as propanol and isoprene for haze air pollution exposure.

Response of earthworm coelomocytes and catalase to pentanone and hexanone: a revelation of the toxicity of conventional solvents at the cellular and molecular level

Organic solvents like 2-pentanone and 2-hexanone which are widely used in industrial production make up a large proportion of the source of chemical pollution. What is worrisome is that the cellular and molecular toxicity of 2-pentanone and 2-hexanone has not been reported yet. Based on this, earthworms and catalase (CAT) were chosen as target receptors for the toxicity studies. The cytotoxicity of 2-pentanone and 2-hexanone was revealed by measuring the multiple intracellular indicators of oxidative stress. At the molecular level, changes in the structure and function of CAT were characterized in vitro by the spectroscopy and molecular docking. The results show that 2-pentanone and 2-hexanone that induced the accumulation of reactive oxygen species can eventually reduce coelomocytes viability, accompanying by the regular changes of antioxidant activity and lipid peroxidation level. In addition, the exposure of 2-pentanone and 2-hexanone can shrink the backbone structure of CAT, quench the fluorescence, and misfold the secondary structure. The decrease in enzyme activity should be attributed to the structural changes induced by surface binding. This study discussed the toxicological effects and mechanisms of conventional solvents at the cellular and molecular level, which creatively proposed a joint research method.

Changes of breath volatile organic compounds in healthy volunteers following segmental and inhalation endotoxin challenge

Background It is still unclear how airway inflammation affects the breath volatile organic compounds (VOC) profile in exhaled air. We therefore analyzed breath following well-defined pulmonary endotoxin (lipopolysaccharide, LPS) challenges. Methods Breath was collected from 10 healthy non-smoking subjects at eight time points before and after segmental and whole lung LPS inhalation challenge. Four Tenax-TA® adsorption tubes were simultaneously loaded from an aluminum reservoir cylinder and independently analyzed by two research groups using gas chromatography - mass spectrometry. Airway inflammation was assessed in bronchoalveolar lavage (BAL) and in sputum after segmental and inhaled LPS challenge, respectively. Results Segmental LPS challenge significantly increased the median (interquartile range, IQR) percentage of neutrophils in BAL from 3.0 (4.2) % to 64.0 (7.3) %. The inhalation challenge increased sputum neutrophils from 33.9 (26.8) % to 78.3 (13.5) %. We observed increases in breath aldehydes at both time points after segmental and inhaled LPS challenge. These results were confirmed by an independent laboratory. The longitudinal breath analysis also revealed distinct VOC patterns related to environmental exposures, clinical procedures, and to metabolic changes after food intake. Conclusions Changes in breath aldehydes suggest a relationship to LPS induced inflammation compatible with lipid peroxidation processes within the lung. Findings from our longitudinal data highlight the need for future studies to better consider the potential impact of the multiple VOCs from detergents, hygiene or lifestyle products a subject is continuously exposed to. We suspect that this very individual "owncloud" exposure is contributing to an increased variability of breath aldehydes, which might limit a use as inflammatory markers in daily clinical practice.

Breathing new life into clinical testing and diagnostics: perspectives on volatile biomarkers from breath

Human breath offers several benefits for diagnostic applications, including simple, noninvasive collection. Breath is a rich source of clinically-relevant biological information; this includes a volatile fraction, where greater than 1,000 volatile organic compounds (VOCs) have been described so far, and breath aerosols that carry nucleic acids, proteins, signaling molecules, and pathogens. Many of these factors, especially VOCs, are delivered to the lung by the systemic circulation, and diffusion of candidate biomarkers from blood into breath allows systematic profiling of organismal health. Biomarkers on breath offer the capability to advance early detection and precision medicine in areas of global clinical need. Breath tests are noninvasive and can be performed at home or in a primary care setting, which makes them well-suited for the kind of public screening program that could dramatically improve the early detection of conditions such as lung cancer. Since measurements of VOCs on breath largely report on metabolic changes, this too aids in the early detection of a broader range of illnesses and can be used to detect metabolic shifts that could be targeted through precision medicine. Furthermore, the ability to perform frequent sampling has envisioned applications in monitoring treatment responses. Breath has been investigated in respiratory, liver, gut, and neurological diseases and in contexts as diverse as infectious diseases and cancer. Preclinical research studies using breath have been ongoing for some time, yet only a few breath-based diagnostics tests are currently available and in widespread clinical use. Most recently, tests assessing the gut microbiome using hydrogen and methane on breath, in addition to tests using urea to detect Helicobacter pylori infections have been released, yet there are many more applications of breath tests still to be realized. Here, we discuss the strengths of breath as a clinical sampling matrix and the technical challenges to be addressed in developing it for clinical use. Historically, a lack of standardized methodologies has delayed the discovery and validation of biomarker candidates, resulting in a proliferation of early-stage pilot studies. We will explore how advancements in breath collection and analysis are in the process of driving renewed progress in the field, particularly in the context of gastrointestinal and chronic liver disease. Finally, we will provide a forward-looking outlook for developing the next generation of clinically relevant breath tests and how they may emerge into clinical practice.

European Respiratory Society Guidelines for the Diagnosis of Asthma in Adults

Although asthma is very common affecting 5-10% of the population, the diagnosis of asthma in adults remains a challenge in the real world that results in both over- and under-diagnosis. A task force (TF) was set up by the European Respiratory Society to systematically review the literature on the diagnostic accuracy of tests used to diagnose asthma in adult patients and provide recommendation for clinical practice.The TF defined eight PICO (Population, Index, Comparator, and Outcome) questions that were assessed using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach, The TF utilised the outcomes to develop an evidenced-based diagnostic algorithm, with recommendations for a pragmatic guideline for everyday practice that was directed by real-life patient experiences.The TF support the initial use of spirometry followed, and if airway obstruction is present, by bronchodilator reversibility testing. If initial spirometry fails to show obstruction, further tests should be performed in the following order: FeNO, PEF variability or in secondary care, bronchial challenge. We present the thresholds for each test that are compatible with a diagnosis of asthma in the presence of current symptoms.The TF reinforce the priority to undertake spirometry and recognise the value of measuring blood eosinophils and serum IgE to phenotype the patient. Measuring gas trapping by body plethysmography in patients with preserved FEV1/FVC ratio deserves further attention. The TF draw attention on the difficulty of making a correct diagnosis in patients already receiving inhaled corticosteroids, the comorbidities that may obscure the diagnosis, the importance of phenotyping, and the necessity to consider the patient experience in the diagnostic process.

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.

Advances in microfluidics devices and its applications in personalized medicines

Microfluidics is an exponentially growing area and is being used for numerous applications from basic science to advanced biotechnology and medicines. Microfluidics provides a platform to the research community for studying and building new strategies for the diagnosis and therapeutics applications. In the last decade, microfluidic have enriched the field of diagnostics by providing new solutions which was not possible with conventional detection and treatment methods. Microfluidics has the ability to precisely control and perform high-throughput functions. It has been proven as an efficient and rapid method for biological sample preparation, analysis and controlled drug delivery system. Microfluidics plays significant role in personalized medicine. These personalized medicines are used for medical decisions, practices and other interventions as well as for individual patients based on their predicted response or risk of disease. This chapter highlights microfluidics in developing personalized medical applications for its applications in diseases such as cancer, cardiovascular disease, diabetes, pulmonary disease and several others.

Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies

This review highlights the current state of knowledge in the development of GC × GC-MS for the analysis of clinical metabolites. Selected applications are described as well as our perspectives on current challenges and potential future directions.

Latest Progresses in Allergic Diseases Biomarkers: Asthma and Atopic Dermatitis

In the last years, the understanding of the pathologic mechanisms of asthma and atopic dermatitis, both characterized by allergic inflammation, has greatly improved. However, it is evident that both diseases present with high heterogeneity, which complicates the diagnosis and the therapeutic approach of the patients. Moreover, some of the currently available strategies to treat asthma and atopic dermatitis are still mostly controlling the symptoms, but not to lead towards full healing, thus having these two diseases labelled as unmet clinical needs by WHO. Therefore, the "one-size-fits-all" strategy is outdated for asthma and atopic dermatitis, and there is the need of better methods to clearly diagnose the disease and tailor the therapy according to the specific symptomatology. In this regard, the use of biomarkers has been advanced in order to characterize both diseases according to their clinical signs and to facilitate the subsequent treatment. Despite the advancements made in this regard, there is still need for better and more sensitive biomarkers and for less invasive sampling methodologies, with the aim to diagnose specifically each manifestation of asthma and atopic dermatitis and to provide the best treatment with the least suffering for the patients.

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

Recent Insights into the Management of Inflammation in Asthma

The present prevailing inflammatory paradigm in asthma is of T2-high inflammation orchestrated by key inflammatory cells like Type 2 helper lymphocytes, innate lymphoid cells group 2 and associated cytokines. Eosinophils are key components of this T2 inflammatory pathway and have become key therapeutic targets. Real-world evidence on the predominant T2-high nature of severe asthma is emerging. Various inflammatory biomarkers have been adopted in clinical practice to aid asthma characterization including airway measures such as bronchoscopic biopsy and lavage, induced sputum analysis, and fractional exhaled nitric oxide. Blood measures like eosinophil counts have also gained widespread usage and multicomponent algorithms combining different parameters are now appearing. There is also growing interest in potential future biomarkers including exhaled volatile organic compounds, micro RNAs and urinary biomarkers. Additionally, there is a growing realisation that asthma is a heterogeneous state with numerous phenotypes and associated treatable traits. These may show particular inflammatory patterns and merit-specific management approaches that could improve asthma patient outcomes. Inhaled corticosteroids (ICS) remain the mainstay of asthma management but their use earlier in the course of disease is being advocated. Recent evidence suggests potential roles for ICS in combination with long-acting beta-agonists (LABA) for as needed use in mild asthma whilst maintenance and reliever therapy regimes have gained widespread acceptance. Other anti-inflammatory strategies including ultra-fine particle ICS, leukotriene receptor antagonists and macrolide antibiotics may show efficacy in particular phenotypes too. Monoclonal antibody biologic therapies have recently entered clinical practice with significant impacts on asthma outcomes. Understanding of the efficacy and use of those agents is becoming clearer with a growing body of real-world evidence as is their potential applicability to other treatable comorbid traits. In conclusion, the evolving understanding of T2 driven inflammation alongside a treatable traits disease model is enhancing therapeutic approaches to address inflammation in asthma.

Breath Biomarkers in Diagnostic Applications

The detection of chemical compounds in exhaled human breath presents an opportunity to determine physiological state, diagnose disease or assess environmental exposure. Recent advancements in metabolomics research have led to improved capabilities to explore human metabolic profiles in breath. Despite some notable challenges in sampling and analysis, exhaled breath represents a desirable medium for metabolomics applications, foremost due to its non-invasive, convenient and practically limitless availability. Several breath-based tests that target either endogenous or exogenous gas-phase compounds are currently established and are in practical and/or clinical use. This review outlines the concept of breath analysis in the context of these unique tests and their applications. The respective breath biomarkers targeted in each test are discussed in relation to their physiological production in the human body and the development and implementation of the associated tests. The paper concludes with a brief insight into prospective tests and an outlook of the future direction of breath research.

Metabolic Phenotypes in Asthmatic Adults: Relationship with Inflammatory and Clinical Phenotypes and Prognostic Implications

Bronchial asthma is a chronic disease that affects individuals of all ages. It has a high prevalence and is associated with high morbidity and considerable levels of mortality. However, asthma is not a single disease, and multiple subtypes or phenotypes (clinical, inflammatory or combinations thereof) can be detected, namely in aggregated clusters. Most studies have characterised asthma phenotypes and clusters of phenotypes using mainly clinical and inflammatory parameters. These studies are important because they may have clinical and prognostic implications and may also help to tailor personalised treatment approaches. In addition, various metabolomics studies have helped to further define the metabolic features of asthma, using electronic noses or targeted and untargeted approaches. Besides discriminating between asthma and a healthy state, metabolomics can detect the metabolic signatures associated with some asthma subtypes, namely eosinophilic and non-eosinophilic phenotypes or the obese asthma phenotype, and this may prove very useful in point-of-care application. Furthermore, metabolomics also discriminates between asthma and other “phenotypes” of chronic obstructive airway diseases, such as chronic obstructive pulmonary disease (COPD) or Asthma–COPD Overlap (ACO). However, there are still various aspects that need to be more thoroughly investigated in the context of asthma phenotypes in adequately designed, homogeneous, multicentre studies, using adequate tools and integrating metabolomics into a multiple-level approach.

Management Strategies to Reduce Exacerbations in non-T2 Asthma

There have been considerable advances in our understanding of asthmatic airway inflammation, resulting in a paradigm shift of classifying individuals on the basis of either the presence or the absence of type 2 (T2) inflammatory markers. Several novel monoclonal antibody therapies targeting T2 cytokines have demonstrated significant clinical effects including reductions in acute exacerbations and improvements in asthma-related quality of life and lung function for individuals with T2-high asthma. However, there have been fewer advancements in developing therapies for those without evidence of T2 airway inflammation (so-called non-T2 asthma). Here, we review the heterogeneity of molecular mechanisms responsible for initiation and regulation of non-T2 inflammation and discuss both current and potential future therapeutic options for individuals with non-T2 asthma.

Metabolomics in asthma: A platform for discovery

Asthma, characterized by airway hyperresponsiveness, inflammation and remodeling, is a chronic airway disease with complex etiology. Severe asthma is characterized by frequent exacerbations and poor therapeutic response to conventional asthma therapy. A clear understanding of cellular and molecular mechanisms of asthma is critical for the discovery of novel targets for optimal therapeutic control of asthma. Metabolomics is emerging as a powerful tool to elucidate novel disease mechanisms in a variety of diseases. In this review, we summarize the current status of knowledge in asthma metabolomics at systemic and cellular levels. The findings demonstrate that various metabolic pathways, related to energy metabolism, macromolecular biosynthesis and redox signaling, are differentially modulated in asthma. Airway smooth muscle cell plays pivotal roles in asthma by contributing to airway hyperreactivity, inflammatory mediator release and remodeling. We posit that metabolomic profiling of airway structural cells, including airway smooth muscle cells, will shed light on molecular mechanisms of asthma and airway hyperresponsiveness and help identify novel therapeutic targets.

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.

Exhaled volatilome analysis as a useful tool to discriminate asthma with other coexisting atopic diseases in women of childbearing age

The prevalence of asthma is considerably high among women of childbearing age. Most asthmatic women also often have other atopic disorders. Therefore, the differentiation between patients with atopic diseases without asthma and asthmatics with coexisting diseases is essential to avoid underdiagnosis of asthma and to design strategies to reduce symptom severity and improve quality of life of patients. Hence, we aimed for the first time to conduct an analysis of volatile organic compounds in exhaled breath of women of childbearing age as a new approach to discriminate between asthmatics with other coexisting atopic diseases and non-asthmatics (with or without atopic diseases), which could be a helpful tool for more accurate asthma detection and monitoring using a noninvasive technique in the near future. In this study, exhaled air samples of 336 women (training set (n = 211) and validation set (n = 125)) were collected and analyzed by thermal desorption coupled with gas chromatography-mass spectrometry. ASCA (ANOVA (analysis of variance) simultaneous component analysis) and LASSO + LS (least absolute shrinkage and selection operator + logistic regression) were employed for data analysis. Fifteen statistically significant models (p-value < 0.05 in permutation tests) that discriminated asthma with other coexisting atopic diseases in women of childbearing age were generated. Acetone, 2-ethyl-1-hexanol and a tetrahydroisoquinoline derivative were selected as discriminants of asthma with other coexisting atopic diseases. In addition, carbon disulfide, a tetrahydroisoquinoline derivative, 2-ethyl-1-hexanol and decane discriminated asthma disease among patients with other atopic disorders. Results of this study indicate that refined metabolomic analysis of exhaled breath allows asthma with other coexisting atopic diseases discrimination in women of reproductive age.

Diagnosis of COVID-19 by exhaled breath analysis using gas chromatography-mass spectrometry

BACKGROUND

The ongoing coronavirus disease 2019 (COVID-19) pandemic has claimed over two and a half million lives worldwide so far. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is perceived to be seasonally recurrent, and a rapid noninvasive biomarker to accurately diagnose patients early on in their disease course will be necessary to meet the operational demands for COVID-19 control in the coming years.

OBJECTIVE

The aim of this study was to evaluate the role of exhaled breath volatile biomarkers in identifying patients with suspected or confirmed COVID-19 infection, based on their underlying PCR status and clinical probability.

METHODS

A prospective, real-world, observational study was carried out, recruiting adult patients with suspected or confirmed COVID-19 infection. Breath samples were collected using a standard breath collection bag, modified with appropriate filters to comply with local infection control recommendations, and samples were analysed using gas chromatography-mass spectrometry (TD-GC-MS).

RESULTS

81 patients were recruited between April 29 and July 10, 2020, of whom 52 out of 81 (64%) tested positive for COVID-19 by reverse transcription-polymerase chain reaction (RT-PCR). A regression analysis identified a set of seven exhaled breath features (benzaldehyde, 1-propanol, 3,6-methylundecane, camphene, beta-cubebene, iodobenzene and an unidentified compound) that separated PCR-positive patients with an area under the curve (AUC): 0.836, sensitivity: 68%, specificity: 85%.

CONCLUSIONS

GC-MS-detected exhaled breath biomarkers were able to identify PCR-positive COVID-19 patients. External replication of these compounds is warranted to validate these results.

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.

Selected ion flow tube mass spectrometry for targeted analysis of volatile organic compounds in human breath

The analysis of volatile organic compounds (VOCs) within breath for noninvasive disease detection and monitoring is an emergent research field that has the potential to reshape current clinical practice. However, adoption of breath testing has been limited by a lack of standardization. This protocol provides a comprehensive workflow for online and offline breath analysis using selected ion flow tube mass spectrometry (SIFT-MS). Following the suggested protocol, 50 human breath samples can be analyzed and interpreted in <3 h. Key advantages of SIFT-MS are exploited, including the acquisition of real-time results and direct compound quantification without need for calibration curves. The protocol includes details of methods developed for targeted analysis of disease-specific VOCs, specifically short-chain fatty acids, aldehydes, phenols, alcohols and alkanes. A procedure to make custom breath collection bags is also described. This standardized protocol for VOC analysis using SIFT-MS is intended to provide a basis for wider application and the use of breath analysis in clinical studies.

Pursuing breath research in unprecedented circumstances-report from the Breath Biopsy Conference 2020

The global outbreak of Sars-CoV-2 commencing early in 2020 had a dramatic impact on breath research, imposing abrupt restrictions but also presenting unforeseen opportunities. Taking place against the background of the COVID-19 pandemic, the 2020 Breath Biopsy Conference provided the breath research community with a platform to showcase and discuss the latest findings, including COVID-19 related research. As with most conferences under the present circumstance, it differed from its predecessor meetings by shifting to a virtual format, but retained its broad scope and interactive nature. The conference centred on four key themes, featuring applications of volatile organic compounds, breath biomarkers for liver disease, study design and data analytics, and, notably this year, breath-based endeavours to detect COVID-19 infection. This meeting report summarizes the events of the conference and spotlights selected contributions.