Volatile organic compounds in asthma diagnosis: a systematic review and meta-analysis

Expose to volatile organic compounds is associated with increased risk of depression: A cross-sectional study

With increasing prevalence rate of depression by years, more attention has been paid to the influence of environmental pollutants on depression, but relationship between exposure to volatile organic compounds (VOCs) and depression is rarely studied. Therefore, this cross-sectional study use the National Center for Health Statistics (NHANES) database (2013-2016 years) to explore association between exposure to multiple VOCs and depression in general population. Multiple linear and logistic regression models were used to analyze the association between urinary VOC metabolism (mVOCs) and depression. To further analyze effect of multiple mVOCs mixed exposure, Bayesian kernel machine regression (BKMR) models were performed. A total of 3240 participants and 16 mVOCs were included in the analysis. Results showed that 10 mVOCs exposure were positively correlated with depression by multiple linear and logistic regression models, especially CYMA and MHBMA3, which also showed significant positive association with depression in BKMR model. Mixed exposure of multiple mVOCs was significantly positively correlated with depression. Gender differences were existed in effects of some VOCs concentrations on depression. AAMA, CYMA and MA had significant positive correlations with depression by women, and DHBMA had significant positive correlations with depression by men. Hence, this study showed that exposing to VOCs might have negative impacts on depression, and impact of CYMA and MHBMA3 on depression may be more evident, which provide new ideas for prevention and control of depression. But further research and exploration are needed to clarify the mechanism and influence factors of this relationship, to demonstrate the reliability of these relationship.

The breath volatilome is shaped by the gut microbiota

The gut microbiota is widely implicated in host health and disease, inspiring translational efforts to implement our growing body of knowledge in clinical settings. However, the need to characterize gut microbiota by its genomic content limits the feasibility of rapid, point-of-care diagnostics. The microbiota produces a diverse array of xenobiotic metabolites that disseminate into tissues, including volatile organic compounds (VOCs) that may be excreted in breath. We hypothesize that breath contains gut microbe-derived VOCs that inform the composition and metabolic state of the microbiota. To explore this idea, we compared the breath volatilome and fecal gut microbiomes of 27 healthy children and found that breath VOC composition is correlated with gut microbiomes. To experimentally interrogate this finding, we devised a method for capturing exhaled breath from gnotobiotic mice. Breath volatiles are then profiled by gas-chromatography mass-spectrometry (GC-MS). Using this novel methodology, we found that the murine breath profile is markedly shaped by the composition of the gut microbiota. We also find that VOCs produced by gut microbes in pure culture can be identified in vivo in the breath of mice monocolonized with the same bacteria. Altogether, our studies identify microbe-derived VOCs excreted in breath and support a mechanism by which gut bacterial metabolism directly contributes to the mammalian breath VOC profiles.

Associations of individual and mixture exposure to volatile organic compounds with metabolic syndrome and its components among US adults

BACKGROUND

People are exposed to various volatile organic compounds (VOCs) in their environment. Our study aims to examine the links between VOCs exposure and metabolic syndrome (MetS) and its components, as well as identify critical VOCs.

METHOD

In this study, we enrolled 8223 adults from the National Health and Nutrition Examination Survey (NHANES) and analyzed 15 kinds of urinary VOCs metabolites. The Spearman correlation model, generalized linear regression model, restricted cubic spline (RCS), weighted quantile sum (WQS) analysis, and Bayesian kernel machine regression (BKMR) were used to evaluate the association between individual VOC/VOCs mixture and MetS as well as its components.

RESULTS

In generalized linear regression model, compared to the lowest quartile of urinary VOCs metabolites, the highest quartiles of urinary VOC metabolites were positively associated with MetS including N-Acetyl-S-(N-methylcarbamoyl)-l-cysteine (AMCC) (OR: 1.22, 95%CI: 1.00, 1.49), N-Acetyl-S-(2-carboxyethyl)-l-cysteine (CEMA) (OR: 1.71, 95%CI: 1.41, 2.07), N-Acetyl-S-(3-hydroxypropyl)-l-cysteine (3HPMA) (OR: 1.32, 95%CI: 1.11, 1.63), and N-Acetyl-S-(3-hydroxypropyl-1-methyl)-l-cysteine (HMPMA) (OR: 1.34, 95%CI: 1.09, 1.64). Consistent results were found in the dose-response relationship in RCS model. Results of WQS showed that VOCs mixture was positively associated with MetS (OR: 1.16, 95%CI: 1.06, 1.28), elevated WC (OR: 1.25, 95%CI: 1.13, 1.37), elevated FBG (OR: 1.24, 95%CI: 1.12, 1.37), elevated TG (OR: 1.34, 95%CI: 1.21, 1.49), and reduced HDL-C (OR: 1.20, 95%CI: 1.09, 1.33). However, the WQS index was negatively associated with elevated BP (OR: 0.81; 95%CI: 0.70, 0.94). BKMR analysis confirmed that the urinary VOCs mixture was positively associated with MetS, elevated WC, elevated TG, reduced HDL-C, elevated FBG, but negatively associated with elevated BP. CEMA was defined as the most heavily weighted chemical in the WQS and BKMR models.

CONCLUSION

Our findings suggested that exposure to specific VOC or VOCs mixture is associated with the higher risk of MetS and its components, except for elevated BP.

Metabolomics in Animal Models of Bronchial Asthma and Its Translational Importance for Clinics

Bronchial asthma is an extremely heterogenous chronic respiratory disorder with several distinct endotypes and phenotypes. These subtypes differ not only in the pathophysiological changes and/or clinical features but also in their response to the treatment. Therefore, precise diagnostics represent a fundamental condition for effective therapy. In the diagnostic process, metabolomic approaches have been increasingly used, providing detailed information on the metabolic alterations associated with human asthma. Further information is brought by metabolomic analysis of samples obtained from animal models. This article summarizes the current knowledge on metabolomic changes in human and animal studies of asthma and reveals that alterations in lipid metabolism, amino acid metabolism, purine metabolism, glycolysis and the tricarboxylic acid cycle found in the animal studies resemble, to a large extent, the changes found in human patients with asthma. The findings indicate that, despite the limitations of animal modeling in asthma, pre-clinical testing and metabolomic analysis of animal samples may, together with metabolomic analysis of human samples, contribute to a novel way of personalized treatment of asthma patients.

Volatile organic compounds analysis as promising biomarkers for Parkinson's disease diagnosis: A systematic review and meta-analysis

OBJECTIVE

Researchers are investigating the potential of volatile organic compounds (VOCs) obtained from exhaled breath and sebum as non-invasive tools for early Parkinson's disease (PD) diagnosis. The present study aims to assess the feasibility of using VOC analysis for PD diagnosis and determine the overall diagnostic accuracy of the proposed tests.

METHODS

We performed systematic searches based on the PRISMA guidelines to identify relevant studies on VOCs in PD diagnosis using exhaled breath or sebum samples. The selected articles were described, and meta-analysis was conducted on those that provided the sensitivity and specificity data.

RESULTS

Out of 1268 articles initially identified, 8 met the inclusion criteria and provided specific sensitivity and specificity data for PD, which were included in the current meta-analysis. The pooled analysis of these findings showed a mean area under the receiver operating characteristic curve of 0.85, a sensitivity of 0.81 (95% confidence interval (CI): 0.72, 0.88), and a specificity of 0.76 (95% CI: 0.66, 0.84).

CONCLUSION

The analysis of VOCs in exhaled breath and sebum has shown promise as a new avenue for non-invasive diagnosis of PD. VOCs' ability to distinguish PD from healthy controls suggests their potential clinical application in screening for the disease. Consequently, VOCs hold significant potential as biomarkers for PD diagnosis and offer a promising novel approach to identifying and diagnosing the condition.

The RNA binding proteins ZFP36L1 and ZFP36L2 are dysregulated in airway epithelium in human and a murine model of asthma

Introduction: Asthma is the most common chronic inflammatory disease of the airways. The airway epithelium is a key driver of the disease, and numerous studies have established genome-wide differences in mRNA expression between health and asthma. However, the underlying molecular mechanisms for such differences remain poorly understood. The human TTP family is comprised of ZFP36, ZFP36L1 and ZFP36L2, and has essential roles in immune regulation by determining the stability and translation of myriad mRNAs encoding for inflammatory mediators. We investigated the expression and possible role of the tristetraprolin (TTP) family of RNA binding proteins (RBPs), poorly understood in asthma. Methods: We analysed the levels of ZFP36, ZFP36L1 and ZFP36L2 mRNA in several publicly available asthma datasets, including single cell RNA-sequencing. We also interrogated the expression of known targets of these RBPs in asthma. We assessed the lung mRNA expression and cellular localization of Zfp36l1 and Zfp36l2 in precision cut lung slices in murine asthma models. Finally, we determined the expression in airway epithelium of ZFP36L1 and ZFP36L2 in human bronchial biopsies and performed rescue experiments in primary bronchial epithelium from patients with severe asthma. Results: We found ZFP36L1 and ZFP36L2 mRNA levels significantly downregulated in the airway epithelium of patients with very severe asthma in different cohorts (5 healthy vs. 8 severe asthma; 36 moderate asthma vs. 37 severe asthma on inhaled steroids vs. 26 severe asthma on oral corticoids). Integrating several datasets allowed us to infer that mRNAs potentially targeted by these RBPs are increased in severe asthma. Zfp36l1 was downregulated in the lung of a mouse model of asthma, and immunostaining of ex vivo lung slices with a dual antibody demonstrated that Zfp36l1/l2 nuclear localization was increased in the airway epithelium of an acute asthma mouse model, which was further enhanced in a chronic model. Immunostaining of human bronchial biopsies showed that airway epithelial cell staining of ZFP36L1 was decreased in severe asthma as compared with mild, while ZFP36L2 was upregulated. Restoring the levels of ZFP36L1 and ZFP36L2 in primary bronchial epithelial cells from patients with severe asthma decreased the mRNA expression of IL6, IL8 and CSF2. Discussion: We propose that the dysregulation of ZFP36L1/L2 levels as well as their subcellular mislocalization contributes to changes in mRNA expression and cytoplasmic fate in asthma.

Changes in exhaled volatile organic compounds following indirect bronchial challenge in suspected asthma

BACKGROUND

Inhaled mannitol provokes bronchoconstriction via mediators released during osmotic degranulation of inflammatory cells, and, hence represents a useful diagnostic test for asthma and model for acute attacks. We hypothesised that the mannitol challenge would trigger changes in exhaled volatile organic compounds (VOCs), generating both candidate biomarkers and novel insights into their origin.

METHODS

Participants with a clinical diagnosis of asthma, or undergoing investigation for suspected asthma, were recruited. Inhaled mannitol challenges were performed, followed by a sham challenge after 2 weeks in participants with bronchial hyper-responsiveness (BHR). VOCs were collected before and after challenges and analysed using gas chromatography-mass spectrometry.

RESULTS

Forty-six patients (mean (SD) age 52 (16) years) completed a mannitol challenge, of which 16 (35%) were positive, and 15 of these completed a sham challenge. Quantities of 16 of 51 identified VOCs changed following mannitol challenge (p<0.05), of which 11 contributed to a multivariate sparse partial least square discriminative analysis model, with a classification error rate of 13.8%. Five of these 16 VOCs also changed (p<0.05) in quantity following the sham challenge, along with four further VOCs. In patients with BHR to mannitol distinct postchallenge VOC signatures were observed compared with post-sham challenge.

CONCLUSION

Inhalation of mannitol was associated with changes in breath VOCs, and in people with BHR resulted in a distinct exhaled breath profile when compared with a sham challenge. These differentially expressed VOCs are likely associated with acute airway inflammation and/or bronchoconstriction and merit further investigation as potential biomarkers in asthma.

Severe Asthma and Biological Therapies: Now and the Future

Recognition of phenotypic variability in pediatric asthma allows for a more personalized therapeutic approach. Knowledge of the underlying pathophysiological and molecular mechanisms (endotypes) of corresponding biomarkers and new treatments enables this strategy to progress. Biologic therapies for children with severe asthma are becoming more relevant in this sense. The T2 phenotype is the most prevalent in childhood and adolescence, and non-T2 phenotypes are usually rare. This document aims to review the mechanism of action, efficacy, and potential predictive and monitoring biomarkers of biological drugs, focusing on the pediatric population. The drugs currently available are omalizumab, mepolizumab, benralizumab, dupilumab, and 1ezepelumab, with some differences in administrative approval prescription criteria between the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Previously, we described the characteristics of severe asthma in children and its diagnostic and therapeutic management.

Breath volatile organic compounds (VOCs) as biomarkers for the diagnosis of pathological conditions: A review

Normal and abnormal/pathological status of physiological processes in the human organism can be characterized through Volatile Organic Compounds (VOCs) emitted in breath. Recently, a wide range of volatile analytes has risen as biomarkers. These compounds have been addressed in the scientific and medical communities as an extremely valuable metabolic window. Once collected and analysed, VOCs can represent a tool for a rapid, accurate, non-invasive, and painless diagnosis of several diseases and health conditions. These biomarkers are released by exhaled breath, urine, faeces, skin, and several other ways, at trace concentration levels, usually in the ppbv (μg/L) range. For this reason, the analytical techniques applied for detecting and clinically exploiting the VOCs are extremely important. The present work reviews the most promising results in the field of breath biomarkers and the most common methods of detection of VOCs. A total of 16 pathologies and the respective database of compounds are addressed. An updated version of the VOCs biomarkers database can be consulted at: https://neomeditec.com/VOCdatabase/.

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

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

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.

Detection of trace volatile organic compounds in spiked breath samples: a leap towards breathomics

Breathomics is the future of non-invasive point-of-care devices. The field of breathomics can be split into the isolation of disease-specific volatile organic compounds (VOCs) and their detection. In the present work, an array of five quartz tuning fork (QTF)-based sensors modified by polymer with nanomaterial additive has been utilized. The array has been used to detect samples of human breath spiked with ∼0.5 ppm of known VOCs namely, acetone, acetaldehyde, octane, decane, ethanol, methanol, styrene, propylbenzene, cyclohexanone, butanediol, and isopropyl alcohol which are bio-markers for certain diseases. Polystyrene was used as the base polymer and it was functionalized with 4 different fillers namely, silver nanoparticles-reduced graphene oxide composite, titanium dioxide nanoparticles, zinc ferrite nanoparticles-reduced graphene oxide composite, and cellulose acetate. Each of these fillers enhanced the selectivity of a particular sensor towards a certain VOC compared to the pristine polystyrene-modified sensor. Their interaction with the VOCs in changing the mechanical properties of polymer giving rise to change in the resonant frequency of QTF is used as sensor response for detection. The interaction of functionalized polymers with VOCs was analyzed by FTIR and UV-vis spectroscopy. The collective sensor response of five sensors is used to identify VOCs using an ensemble classifier with 92.8% accuracy of prediction. The accuracy of prediction improved to 96% when isopropyl alcohol, ethanol, and methanol were considered as one class.

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.

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.

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.

A Current Perspective of Allergic Asthma: From Mechanisms to Management

Asthma is a result of heterogenous, complex gene-environment interactions with variable clinical phenotypes, inflammation, and remodeling. It affects more than 330 million of people worldwide throughout their educational and working lives, while exacerbations put a heavy cost/burden on productivity. Childhood asthma is characterized by a predominance of allergic sensitization and multimorbidity, while in adults polysensitization has been positively associated with asthma occurrence. Despite significant improvements in recent decades, asthma management remains challenging. Recently, a group of specialists suggested that the term "asthma" should be preferably used as a descriptive term for symptoms. Moreover, type 2 inflammation has emerged as a pivotal disease mechanism including overlapping endotypes of specific IgE production, while type 2-low asthma includes several disease endotypes. Optimal asthma control requires both appropriate pharmacological interventions, tailored to each patient, as well as trigger avoidance measures. Regular monitoring for maintenance of symptom control, preservation of lung function, and detection of treatment-related adverse effects are warranted. Allergen-specific immunotherapy and the advent of new targeted therapies for patients with difficult to control asthma offer diverse treatment options. The current review summarizes up-to-date knowledge on epidemiology, definitions, diagnosis, and current therapeutic strategies.

Real Time Breath Analysis Using Portable Gas Chromatography for Adult Asthma Phenotypes

Asthma is heterogeneous but accessible biomarkers to distinguish relevant phenotypes remain lacking, particularly in non-Type 2 (T2)-high asthma. Moreover, common clinical characteristics in both T2-high and T2-low asthma (e.g., atopy, obesity, inhaled steroid use) may confound interpretation of putative biomarkers and of underlying biology. This study aimed to identify volatile organic compounds (VOCs) in exhaled breath that distinguish not only asthmatic and non-asthmatic subjects, but also atopic non-asthmatic controls and also by variables that reflect clinical differences among asthmatic adults. A total of 73 participants (30 asthma, eight atopic non-asthma, and 35 non-asthma/non-atopic subjects) were recruited for this pilot study. A total of 79 breath samples were analyzed in real-time using an automated portable gas chromatography (GC) device developed in-house. GC-mass spectrometry was also used to identify the VOCs in breath. Machine learning, linear discriminant analysis, and principal component analysis were used to identify the biomarkers. Our results show that the portable GC was able to complete breath analysis in 30 min. A set of nine biomarkers distinguished asthma and non-asthma/non-atopic subjects, while sets of two and of four biomarkers, respectively, further distinguished asthmatic from atopic controls, and between atopic and non-atopic controls. Additional unique biomarkers were identified that discriminate subjects by blood eosinophil levels, obese status, inhaled corticosteroid treatment, and also acute upper respiratory illnesses within asthmatic groups. Our work demonstrates that breath VOC profiling can be a clinically accessible tool for asthma diagnosis and phenotyping. A portable GC system is a viable option for rapid assessment in asthma.

Dog Owners' Survey reveals Medical Alert Dogs can alert to multiple conditions and multiple people

Medical Alert Dogs (MADs) are a promising support system for a variety of medical conditions. Emerging anecdotal reports suggest that dogs may alert to additional health conditions and different people other than those that they were trained for or initially began alerting. As the use of medical alert dogs increases, it is imperative that such claims are documented empirically. The overall aims of this study were to record the proportion of MAD owners who have a dog that alerts to multiple health conditions or to people other than the target person and to determine whether any sociodemographic variables were associated with dogs alerting to multiple conditions, multiple people, or both. MAD owners completed an online survey that contained a series of forced choice questions. Sixty-one participants reported a total of 33 different conditions to which dogs alerted. Eighty-four percent of participants reported that their dog alerted to multiple conditions and 54% reported that their dog alerted to multiple people. This is the first study to document that a large percentage of people report that their MAD alerts to multiple conditions and/or to multiple people. We present a discussion of how these alerting abilities could develop, but questions about the underlying mechanisms remain.

Acrylamide Induces Mitophagy and Alters Macrophage Phenotype via Reactive Oxygen Species Generation

Acrylamide is a readily exposed toxic organic compound due to its formation in many carbohydrate rich foods that are cooked at high temperatures. Excessive production of reactive oxygen species (ROS), which is an important factor for mitophagy, has been reported to lead to airway inflammation, hyper-responsiveness, and remodeling. Epigenetic regulation is an important modification affecting gene transcription. In this study, the effects of acrylamide on ROS productions and mitophagy were investigated. The human monocytic cell line THP-1 was treated with acrylamide, and ROS productions were investigated by flow cytometry. The mitochondrial and epigenetic involvement was evaluated by quantitative real-time PCR. Histone modifications were examined by chromatin immunoprecipitation assays. Mitophagy was detected by Western blotting and confocal laser microscopy. Acrylamide promoted mitochondria-specific ROS generation in macrophages. The gene expression of mitochondrial respiratory chain complex II SDHA was increased under acrylamide treatment. Acrylamide induced histone H3K4 and H3K36 tri-methylation in an SDHA promoter and increased mitophagy-related PINK1 expression, which promoted a M2-like phenotypic switch with increase TGF-β and CCL2 levels in THP-1 cells. In conclusion, acrylamide induced ROS production through histone tri-methylation in an SDHA promoter and further increased the expression of mitophagy-related PINK-1, which was associated with a macrophage M2 polarization shift.

Pulmonary Health Effects of Indoor Volatile Organic Compounds-A Meta-Analysis

Volatile organic compounds (VOCs) are commonly found in consumer products, including furniture, sealants and paints. Thus, indoor VOCs have become a public health concern, especially in high-income countries (HICs), where people spend most of their time indoors, and indoor and outdoor air exchange is minimal due to a lack of ventilation. VOCs produce high levels of reaction with the airway epithelium and mucosa membrane and is linked with pulmonary diseases. This paper takes a stock of the literature to assess the strength of association (measured by effect size) between VOCs and pulmonary diseases with the focus on asthma and its related symptoms by conducting a meta-analysis. The literature was searched using the PubMed database. A total of 49 studies that measured VOCs or VOC types and pulmonary health outcomes were included in the analysis. The results of these studies were tabulated, and standard effect size of each study was computed. Most studies were conducted in high-income countries, including France (n = 7), Japan (n = 7) and the United States (n = 6). Our analysis suggests that VOCs have a medium-sized effect on pulmonary diseases, including the onset of asthma (effect size (or Cohen's d) ~0.37; 95% confidence interval (CI) = 0.25-0.49; n = 23) and wheezing (effective size ~0.26; 95% CI = 0.10-0.42; n = 10). The effect size also varied by country, age and disease type. Multiple stakeholders must be engaged in strategies to mitigate and manage VOC exposure and its associated pulmonary disease burden.

Early-life exposure to air pollution and childhood allergic diseases: an update on the link and its implications

INTRODUCTION

Although mounting evidence has linked environmental factors with childhood allergies, some specific key issues still remain unclear: what is the main environmental factor? what is the critical timing window? And whether these contribute to the development of disease?

AREAS COVERED

This selective review summarizes recent epidemiological studies on the association between early-life exposure to indoor/outdoor air pollution and childhood allergic diseases. A literature search was conducted in the PubMed and Web of Science for peer-reviewed articles published until April 2020. Exposure to the traffic-related air pollutant, NO₂, exposure during pregnancy and early postnatal periods is found to be associated with childhood allergies, and exposure during different trimesters causes different allergic diseases. However, exposure to classical air pollutants (PM₁₀ and SO₂) also contributes to childhood allergy in developing countries. In addition, early-life exposure to indoor renovation and mold/dampness significantly increases the risk of allergy in children. A synergistic effect between indoor and outdoor air pollution is found in the development of allergic diseases.

EXPERT OPINION

Early-life exposure to outdoor air pollution and indoor environmental factors plays an important role in the development of childhood allergic diseases, and the synergy between indoor and outdoor exposures increases allergy risk. The available findings support the hypothesis of the 'fetal origins of childhood allergy,' with new implications for the effective control and early prevention of childhood allergies.

The Effects of Indoor Pollutants Exposure on Allergy and Lung Inflammation: An Activation State of Neutrophils and Eosinophils in Sputum

BACKGROUND

To explore the inflammation phenotypes following indoor pollutants exposure based on marker expression on eosinophils and neutrophils with the application of chemometric analysis approaches.

METHODS

A cross-sectional study was undertaken among secondary school students in eight suburban and urban schools in the district of Hulu Langat, Selangor, Malaysia. The survey was completed by 96 students at the age of 14 by using the International Study of Asthma and Allergies in Children (ISAAC) and European Community Respiratory Health Survey (ECRHS) questionnaires. The fractional exhaled nitric oxide (FeNO) was measured, and an allergic skin prick test and sputum induction were performed for all students. Induced sputum samples were analysed for the expression of CD11b, CD35, CD63, and CD66b on eosinophils and neutrophils by flow cytometry. The particulate matter (PM2.5 and PM10), NO2, CO2, and formaldehyde were measured inside the classrooms.

RESULTS

Chemometric and regression results have clustered the expression of CD63 with PM2.5, CD11b with NO2, CD66b with FeNO levels, and CO2 with eosinophils, with the prediction accuracy of the models being 71.88%, 76.04%, and 76.04%, respectively. Meanwhile, for neutrophils, the CD63 and CD66b clustering with PM2.5 and CD11b with FeNO levels showed a model prediction accuracy of 72.92% and 71.88%, respectively.

CONCLUSION

The findings indicated that the exposure to PM2.5 and NO2 was likely associated with the degranulation of eosinophils and neutrophils, following the activation mechanisms that led to the inflammatory reactions.

The value of microRNAs as the novel biomarkers for colorectal cancer diagnosis: A meta-analysis

BACKGROUND

Numerous studies have reported that microRNAs (miRNAs) hold great potential as the biomarkers for colorectal cancer (CRC). However, inconsistent results have made it challenging to evaluate their diagnostic performance. Thus, the aim of this meta-analysis was to systematically assess the pooled efficacy of miRNAs for CRC diagnosis.

METHODS

A search for eligible studies up to October 30, 2019 was conducted using PubMed, Web of Science and EMBASE databases. A random-effects model was used to evaluate the pooled sensitivity and specificity. The summary receiver operator characteristic (SROC) curve and area under the curve (AUC) were calculated to assess the overall diagnostic efficacy.

RESULTS

A total of 3258 CRC patients and 2683 healthy controls were identified in 35 included studies. The overall diagnostic accuracy was as follows: sensitivity, 0.80 [95 % confidence interval (CI) 0.75-0.83]; specificity, 0.80 (95 % CI, 0.75-0.84); positive likelihood ratio (PLR), 4.0 (95 % CI, 3.2-5.0); negative likelihood ratio (NLR), 0.26 (95 % CI, 0.21-0.31); diagnostic odds ratio (DOR), 16 (95 % CI, 11-23); and AUC, 0.87 (95 % CI, 0.83-0.89).

CONCLUSION

The results indicated that miRNAs, particularly serum-derived miRNAs, can serve as the powerful and promising biomarkers for early CRC screening.

Comparison of the effect of chemically and biologically induced inflammation on the volatile metabolite production of lung epithelial cells by GC×GC-TOFMS

Exhaled breath analysis has a high potential for early non-invasive diagnosis of lung inflammatory diseases, such as asthma. The characterization and understanding of the inflammatory metabolic pathways involved into volatile organic compounds (VOCs) production could bring exhaled breath analysis into clinical practice and thus open new therapeutic routes for inflammatory diseases. In this study, lung inflammation was simulated in vitro using A549 epithelial cells. We compared the VOC production from A549 epithelial cells after a chemically induced oxidative stress in vitro, exposing the cells to H₂O₂, and a biological stress, exposing the cells to an inflammatory pool of sputum supernatants. Special attention was devoted to define proper negative and positive controls (8 different types) for our in vitro models, including healthy sputum co-culture. Sputum from 25 asthmatic and 8 healthy patients were collected to create each pool of supernatants. Each sample type was analyzed in 4 replicates using solid-phase microextraction (SPME) comprehensive two-dimensional gas chromatography hyphenated to time-of-flight mass spectrometry (GC×GC-TOFMS). This approach offers high resolving power for complex VOC mixtures. According to the type of inflammation induced, significantly different VOCs were produced by the epithelial cells compared to all controls. For both chemical and biological challenges, an increase of carbonyl compounds (54%) and hydrocarbons (31%) was observed. Interestingly, only the biological inflammation model showed a significant cell proliferation together with an increased VOC production linked to asthma airway inflammation. This study presents a complete GC×GC-TOFMS workflow for in vitro VOC analysis, and its potential to characterize complex lung inflammatory mechanisms.

Human volatilome analysis using eNose to assess uncontrolled asthma in a clinical setting

BACKGROUND

Analyses of exhaled volatile organic compounds (VOCs) have shown promising results when distinguishing individuals with asthma. Currently, there are no biomarkers for uncontrolled asthma. Therefore, we aimed to assess, in a real-life clinical setting, the ability of the exhaled VOC analysis, using an electronic nose (eNose), to identify individuals with uncontrolled asthma.

METHODS

A cross-sectional study was conducted, and breath samples from 199 participants (130 females, aged 6-78, 66% with asthma) were analysed using an eNose. A multivariate unsupervised cluster analysis, using the resistance data from 32 sensors, could distinguish three clusters of VOC patterns in the training and testing groups. Comparisons between the clusters were performed using the one-way ANOVA, Kruskal-Wallis and chi-squared tests.

RESULTS

In the training set (n = 121), three different clusters covering asthma, lung function, symptoms in the previous 4 weeks and age were identified. The pairwise comparisons showed significant differences with respect to chest tightness during exercise, dyspnoea and gender. These findings were confirmed in the testing set (n = 78) where the training model identified three clusters. The participants who reported fewer respiratory symptoms (dyspnoea and night-time awakenings) were grouped into one cluster, while the others comprised participants who showed similar poor control over symptoms with the distribution of the individuals with asthma being significantly different between them.

CONCLUSIONS

In a clinical setting, the analysis of the exhaled VOC profiles using an eNose could be used as a fast and noninvasive complementary assessment tool for the detection of uncontrolled asthma symptoms.

Volatile organic compounds associated with diagnosis and disease characteristics in asthma - A systematic review

BACKGROUND

Metabolomics refers to study of the metabolome, the entire set of metabolites produced by a biological system. The application of metabolomics to exhaled breath samples - breathomics - is a rapidly growing field with potential application to asthma diagnosis and management.

OBJECTIVES

We aimed to review the adult asthma breathomic literature and present a comprehensive list of volatile organic compounds identified by asthma breathomic models.

METHODS

We undertook a systematic search for literature on exhaled volatile organic compounds in adult asthma. We assessed the quality of studies and performed a qualitative synthesis.

RESULTS

We identified twenty studies; these were methodologically heterogenous with a variable risk of bias. Studies almost universally reported breathomics to be capable of differentiating - with moderate or greater accuracy - between samples from healthy controls and those with asthma; and to be capable of phenotyping disease. However, there was little concordance in the compounds upon which discriminatory models were based.

CONCLUSION

Results to-date are promising but validation in independent prospective cohorts is needed. This may be challenging given the high levels of inter-individual variation. However, large-scale, multi-centre studies are underway and validation efforts have been aided by the publication of technical standards likely to increase inter-study comparability. Successful validation of breathomic models for diagnosis and phenotyping would constitute an important step towards personalised medicine in asthma.

Measuring inflammation in paediatric severe asthma: biomarkers in clinical practice

Severe asthma in children is a highly heterogeneous disorder, encompassing different clinical characteristics (phenotypes) and immunopathological pathways (endotypes). Research is focusing on the identification of noninvasive biomarkers able to predict treatment response and assist in designing personalised therapies for severe asthma. Blood and sputum eosinophils, serum IgE and exhaled nitric oxide fraction mostly reflect type 2 airway inflammation in children. However, in the absence of available point-of-care biomarkers, the diagnosis of non-type 2 asthma is still reached by exclusion. In this review, we present the most recent evidence on biomarkers for severe asthma and discuss their implementation in clinical practice. We address the methods for guiding treatment decisions and patient identification, focusing on the paediatric age group.

Noninvasive biomarkers should be integrated with clinical findings to assist in diagnosing and guiding personalised therapies for severe asthma in childrenhttp://bit.ly/2JPvKFV

Evaluation of pulmonary function and respiratory symptoms among workers exposed to 1,3-Butadiene in a petrochemical industry in Iran

This study aimed to evaluate pulmonary function among workers exposed to 1,3-butadiene and was carried out in a petrochemical industry in Iran. The study participants consisted of fifty male workers with current respiratory exposure to 1,3-butadiene and fifty non-exposed workers as the control group. Exposure to 1,3-butadiene was measured according to the NIOSH 1024 method. Respiratory symptom histories were collected through the American Thoracic Society respiratory symptom questionnaire. Lung functions were evaluated using spirometry method. The results showed that exposed participants had significantly higher prevalence rates of all respiratory symptoms compared to the control group. Statistical tests demonstrated a significant difference between pulmonary function tests of exposed and non-exposed personnel. Ultimately, the results of the present study indicate that respiratory exposure to 1,3-butadiene can lead to negative effects on pulmonary functions.

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.

Exhaled volatile organic compounds in adult asthma: a systematic review

The search for biomarkers that can guide precision medicine in asthma, particularly those that can be translated to the clinic, has seen recent interest in exhaled volatile organic compounds (VOCs). Given the number of studies reporting "breathomics" findings and its growing integration in clinical trials, we performed a systematic review of the literature to summarise current evidence and understanding of breathomics technology in asthma.A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-oriented systematic search was performed (CRD42017084145) of MEDLINE, Embase and the Cochrane databases to search for any reports that assessed exhaled VOCs in adult asthma patients, using the following terms (asthma AND (volatile organic compounds AND exhaled) OR breathomics).Two authors independently determined the eligibility of 2957 unique records, of which 66 underwent full-text review. Data extraction and risk of bias assessment was performed on the 22 studies deemed to fulfil the search criteria. The studies are described in terms of methodology and the evidence narratively summarised under the following clinical headings: diagnostics, phenotyping, treatment stratification, treatment monitoring and exacerbation prediction/assessment.Our review found that most studies were designed to assess diagnostic potential rather than focus on underlying biology or treatable traits. Results are generally limited by a lack of methodological standardisation and external validation and by insufficiently powered studies, but there is consistency across the literature that exhaled VOCs are sensitive to underlying inflammation. Modern studies are applying robust breath analysis workflows to large multi-centre study designs, which should unlock the full potential of measurement of exhaled volatile organic compounds in airways diseases such as asthma.

Understanding Asthma Phenotypes, Endotypes, and Mechanisms of Disease

The model of asthma as a single entity has now been replaced by a much more complex biological network of distinct and interrelating inflammatory pathways. The term asthma is now considered an umbrella diagnosis for several diseases with distinct mechanistic pathways (endotypes) and variable clinical presentations (phenotypes). The precise definition of these endotypes is central to asthma management due to inherent therapeutic and prognostic implications. This review presents the molecular mechanisms behind the heterogeneity of airway inflammation in asthmatic patients. Asthma endotypes may be broadly regarded as type 2 (T2) high or T2-low. Several biologic agents have been approved for T2-high asthma, with numerous other therapeutics that are incipient and similarly targeted at specific molecular mechanisms. Collectively, these advances have shifted existing paradigms in the approach to asthma to tailor novel therapies.

A Binder Jet Printed, Stainless Steel Preconcentrator as an In-Line Injector of Volatile Organic Compounds

A conventional approach to making miniature or microscale gas chromatography (GC) components relies on silicon as a base material and MEMS fabrication as manufacturing processes. However, these devices often fail in medium-to-high temperature applications due to a lack of robust fluidic interconnects and a high-yield bonding process. This paper explores the feasibility of using metal additive manufacturing (AM), which is also known as metal 3D printing, as an alternative platform to produce small-scale microfluidic devices that can operate at a temperature higher than that which polymers can withstand. Binder jet printing (BJP), one of the metal AM processes, was utilized to make stainless steel (SS) preconcentrators (PCs) with submillimeter internal features. PCs can increase the concentration of gaseous analytes or serve as an inline injector for GC or gas sensor applications. Normally, parts printed by BJP are highly porous and thus often infiltrated with low melting point metal. By adding to SS316 powder sintering additives such as boron nitride (BN), which reduces the liquidus line temperature, we produce near full-density SS PCs at sintering temperatures much lower than the SS melting temperature, and importantly without any measurable shape distortion. Conversely, the SS PC without BN remains porous after the sintering process and unsuitable for fluidic applications. Since the SS parts, unlike Si, are compatible with machining, they can be modified to work with commercial compression fitting. The PC structures as well as the connection with the fitting are leak-free with relatively high operating pressures. A flexible membrane heater along with a resistance-temperature detector is integrated with the SS PCs for thermal desorption. The proof-of-concept experiment demonstrates that the SS PC can preconcentrate and inject 0.6% headspace toluene to enhance the detector's response.

Exhaled breath condensate volatilome allows sensitive diagnosis of persistent asthma

BACKGROUND

The diagnosis and phenotyping of paediatric asthma are particularly complex due to the lack of currently available sensitive diagnostic tools. This often results in uncertainties associated with inhaled steroid therapy prescription. Therefore, this study aimed to investigate whether volatile organic compounds measured in exhaled breath condensate can be used as biomarkers for asthma diagnosis in the paediatric population.

METHODS

A total of 64 participants, aged 6-18 years, were recruited on a random basis during visits to an outpatient allergy clinic and to a juvenile football team training session. Lung function, airway reversibility and skin prick tests were performed. Exhaled breath condensate samples were collected, and breathprints were assessed using an electronic nose. Information on medical diagnosis of asthma, rhinitis and atopic dermatitis was retrieved for each participant. A hierarchical cluster model based on the volatilome profiles was then created.

RESULTS

A two-cluster exhaled volatile organic compound-based hierarchical model was able to significantly discriminate individuals with asthma from those without the disease (AUC = 0.81 [0.69-0.93], P < 0.001). Individuals who had persistent asthma and were prescribed corticosteroid therapy by the physician were also significantly distinguished in the model (AUC = 0.81 [0.70-0.92], P < 0.001). Despite being less specific, the method showed higher overall accuracy, sensitivity and AUC values when compared to spirometry with bronchodilation.

CONCLUSIONS

Analysis of the exhaled breath condensate volatilome allowed the distinction of paediatric individuals with a medical diagnosis of asthma, identifying those in need of corticosteroid therapy.

Breath biomarkers in idiopathic pulmonary fibrosis: a systematic review

BACKGROUND

Exhaled biomarkers may be related to disease processes in idiopathic pulmonary fibrosis (IPF) however their clinical role remains unclear. We performed a systematic review to investigate whether breath biomarkers discriminate between patients with IPF and healthy controls. We also assessed correlation with lung function, ability to distinguish diagnostic subgroups and change in response to treatment.

METHODS

MEDLINE, EMBASE and Web of Science databases were searched. Study selection was limited to adults with a diagnosis of IPF as per international guidelines.

RESULTS

Of 1014 studies screened, fourteen fulfilled selection criteria and included 257 IPF patients. Twenty individual biomarkers discriminated between IPF and controls and four showed correlation with lung function. Meta-analysis of three studies indicated mean (± SD) alveolar nitric oxide (CalvNO) levels were significantly higher in IPF (8.5 ± 5.5 ppb) than controls (4.4 ± 2.2 ppb). Markers of oxidative stress in exhaled breath condensate, such as hydrogen peroxide and 8-isoprostane, were also discriminatory. Two breathomic studies have isolated discriminative compounds using mass spectrometry. There was a lack of studies assessing relevant treatment and none assessed differences in diagnostic subgroups.

CONCLUSIONS

Evidence suggests CalvNO is higher in IPF, although studies were limited by small sample size. Further breathomic work may identify biomarkers with diagnostic and prognostic potential.

Biomarkers in asthma: state of the art

Asthma is a heterogenous disease characterized by multiple phenotypes driven by different mechanisms. The implementation of precision medicine in the management of asthma requires the identification of phenotype-specific markers measurable in biological fluids. To become useful, these biomarkers need to be quantifiable by reliable systems, reproducible in the clinical setting, easy to obtain and cost-effective. Using biomarkers to predict asthma outcomes and therapeutic response to targeted therapies has a great clinical significance, particularly in severe asthma. In the last years, significant research has been realized in the identification of valid biomarkers for asthma. This review focuses on the existent and emerging biomarkers with clinical higher applicability in the management of asthma.

Metabolomics in asthma: where do we stand?

PURPOSE OF REVIEW

Metabolomics has been used to uncover the metabolic signatures of asthma, both for biomarker identification and pathophysiologic mechanisms research. We aimed to review recent advances in this field, published since 2016, and discuss these findings implications to future research and application into clinical practice.

RECENT FINDINGS

Experimental asthma models and clinical studies in both children and adults supported independent metabolic signatures of asthma. Common reported pathways included purine, glycerophospholipid, glutathione, fatty acids, and arginine and proline metabolism. Metabolomics-based studies identified candidate biomarkers related to asthma severity and corticosteroid resistance, and supported the definition of the obesity-related phenotype at the molecular level. A systematic review with meta-analysis and recent prospective studies favored exhaled volatile organic compounds as one of the most promising biomarkers in asthma diagnosis and monitoring.

SUMMARY

Metabolomics has provided unique and novel insights into asthma profiling at the molecular level. Current challenges include procedures standardization and control of potentially confounding variables for external validation. Point-of-care technology developments bring metabolomics closer to clinical practice. In addition to biomarkers identification, relating metabolites to their biologic role will serve as critical foundations for understanding the biology underpinning asthma heterogeneity and for specific-targeted therapies. VIDEO ABSTRACT.

Asthma Endotyping and Biomarkers in Childhood Asthma

Childhood asthma represents a heterogeneous challenging disease, in particular in its severe forms. The identification of different asthma phenotypes has stimulated research in underlying molecular mechanisms, such as the endotypes, and paved the way to the search for related specific biomarkers, which may guide diagnosis, management, and predict response to treatment. A limited number of biomarkers are currently available in clinical practice in the pediatric population, mostly reflecting type 2-high airway inflammation. The identification of biomarkers of childhood asthma is an active area of research that holds a potential great clinical utility and may represent a step forward toward tailored management and therapy: the so-called Precision Medicine. The aim of the present review is to provide an updated overview of asthma endotyping, mostly focusing on novel noninvasive biomarkers in childhood asthma.

Improving predictive asthma algorithms with modelled environment data for Scotland: an observational cohort study protocol

INTRODUCTION

Asthma has a considerable, but potentially, avoidable burden on many populations globally. Scotland has some of the poorest health outcomes from asthma. Although ambient pollution, weather changes and sociodemographic factors have been associated with asthma attacks, it remains unclear whether modelled environment data and geospatial information can improve population-based asthma predictive algorithms. We aim to create the afferent loop of a national learning health system for asthma in Scotland. We will investigate the associations between ambient pollution, meteorological, geospatial and sociodemographic factors and asthma attacks.

METHODS AND ANALYSIS

We will develop and implement a secured data governance and linkage framework to incorporate primary care health data, modelled environment data, geospatial population and sociodemographic data. Data from 75 recruited primary care practices (n=500 000 patients) in Scotland will be used. Modelled environment data on key air pollutants at a horizontal resolution of 5 km×5 km at hourly time steps will be generated using the EMEP4UK atmospheric chemistry transport modelling system for the datazones of the primary care practices' populations. Scottish population census and education databases will be incorporated into the linkage framework for analysis. We will then undertake a longitudinal retrospective observational analysis. Asthma outcomes include asthma hospitalisations and oral steroid prescriptions. Using a nested case-control study design, associations between all covariates will be measured using conditional logistic regression to account for the matched design and to identify suitable predictors and potential candidate algorithms for an asthma learning health system in Scotland.Findings from this study will contribute to the development of predictive algorithms for asthma outcomes and be used to form the basis for our learning health system prototype.

ETHICS AND DISSEMINATION

The study received National Health Service Research Ethics Committee approval (16/SS/0130) and also obtained permissions via the Public Benefit and Privacy Panel for Health and Social Care in Scotland to access, collate and use the following data sets: population and housing census for Scotland; Scottish education data via the Scottish Exchange of Data and primary care data from general practice Data Custodians. Analytic code will be made available in the open source GitHub website. The results of this study will be published in international peer reviewed journals.

Analysis of volatile organic compounds: an innovative approach to heart failure characterization in older patients

BACKGROUND

Analysis of exhaled volatile organic compounds (VOCs) may be applied for diagnostic purposes in some chronic diseases, but there are no data on their role for discriminating people with congestive heart failure (CHF), particularly in older patients where natriuretic peptides have lower accuracy. We evaluated whether VOCs analysis can discriminate patients with or without CHF, stratify CHF severity and predict the response to therapy of decompensated CHF.

METHODS AND RESULTS

We recruited 89 subjects admitted to an acute care ward with acutely decompensated CHF, 117 healthy controls and 103 chronic obstructive pulmonary disease (COPD) controls. CHF patients performed echocardiography. VOCs were collected using the Pneumopipe^® and analyzed with the BIONOTE electronic nose. Partial least square analysis was used to evaluate the discriminative capacity of VOCs. Accuracy in discrimination of CHF versus healthy and COPD controls was 81% and 69%, respectively; accuracy did not decrease in a sensitivity analysis excluding subjects younger than 65 and older than 80 years. In CHF patients VOCs pattern could predict with fair precision ejection fraction and systolic pulmonary arterial pressure, but not changes in weight due to therapy.

CONCLUSIONS

VOCs pattern is able to discriminate older CHF patients from healthy people and COPD patients and correlates with cardiac function markers.

Allergic asthma: an overview of metabolomic strategies leading to the identification of biomarkers in the field

Allergic asthma is a prominent disease especially during childhood. Indoor allergens, in general, and particularly house dust mites (HDM) are the most prevalent sensitizers associated with allergic asthma. Available data show that 65-130 million people are mite-sensitized world-wide and as many as 50% of these are asthmatic. In fact, sensitization to HDM in the first years of life can produce devastating effects on pulmonary function leading to asthmatic syndromes that can be fatal. To date, there has been considerable research into the pathological pathways and structural changes associated with allergic asthma. However, limitations related to the disease heterogeneity and a lack of knowledge into its pathophysiology have impeded the generation of valuable data needed to appropriately phenotype patients and, subsequently, treat this disease. Here, we report a systematic and integral analysis of the disease, from airway remodelling to the immune response taking place throughout the disease stages. We present an overview of metabolomics, the management of complex multifactorial diseases through the analysis of all possible metabolites in a biological sample, obtaining a global interpretation of biological systems. Special interest is placed on the challenges to obtain biological samples and the methodological aspects to acquire relevant information, focusing on the identification of novel biomarkers associated with specific phenotypes of allergic asthma. We also present an overview of the metabolites cited in the literature, which have been related to inflammation and immune response in asthma and other allergy-related diseases.

Optimisation of sampling parameters for standardised exhaled breath sampling

The lack of standardisation of breath sampling is a major contributing factor to the poor repeatability of results and hence represents a barrier to the adoption of breath tests in clinical practice. On-line and bag breath sampling have advantages but do not suit multicentre clinical studies whereas storage and robust transport are essential for the conduct of wide-scale studies. Several devices have been developed to control sampling parameters and to concentrate volatile organic compounds (VOCs) onto thermal desorption (TD) tubes and subsequently transport those tubes for laboratory analysis. We conducted three experiments to investigate (i) the fraction of breath sampled (whole versus lower expiratory exhaled breath); (ii) breath sample volume (125, 250, 500 and 1000 ml); and (iii) breath sample flow rate (400, 200, 100 and 50 ml min^-1). The target VOCs were acetone and potential volatile biomarkers for oesophago-gastric cancer belonging to the aldehyde, fatty acids and phenol chemical classes. We also examined the collection execution time and the impact of environmental contamination. The experiments showed that the use of exhaled breath-sampling devices requires the selection of optimum sampling parameters. The increase in sample volume has improved the levels of VOCs detected. However, the influence of the fraction of exhaled breath and the flow rate depends on the target VOCs measured. The concentration of potential volatile biomarkers for oesophago-gastric cancer was not significantly different between the whole and lower airway exhaled breath. While the recovery of phenols and acetone from TD tubes was lower when breath sampling was performed at a higher flow rate, other VOCs were not affected. A dedicated 'clean air supply' reduces the contamination from ambient air, but the breath collection device itself can be a source of contaminants. In clinical studies using VOCs to elicit potential biomarkers of gastro-oesophageal cancer, the optimum parameters are 500 mls sample volume of whole breath with a flow rate of 200 ml min^-1.

Faecal volatile organic compounds analysis using field asymmetric ion mobility spectrometry: non-invasive diagnostics in paediatric inflammatory bowel disease

BACKGROUND AND OBJECTIVES

Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), remains challenging to diagnose. Diagnostic work-up carries a high burden, especially in paediatric patients, due to invasive endoscopic procedures. IBD is associated with alterations in intestinal microbiota composition. Faecal volatile organic compounds (VOCs) reflect gut microbiota composition. The aim of this study was to assess the diagnostic accuracy of faecal VOC profiling as a non-invasive diagnostic biomarker for paediatric IBD.

METHODS

In this diagnostic accuracy study performed in two tertiary centres in the Netherlands, faecal VOC profiles of 36 de novo, treatment-naïve paediatric IBD patients (23 CD, 13 UC), and 24 healthy, matched controls were measured by field asymmetric ion mobility spectrometry (Owlstone Ltd, Lonestar®, UK).

RESULTS

Faecal VOC profiles of de novo paediatric IBD patients could be differentiated from healthy controls (AUC ± 95% CI, p-value, sensitivity, specificity; 0.76 ± 0.14, p < 0.001, 79%, 78%). This discrimination from controls was observed in both CD (0.90 ± 0.10, p < 0.0001, 83%, 83%) and UC (0.74 ± 0.19, p = 0.02, 77%, 75%). VOC profiles from UC could not be discriminated from CD (0.67 ± 0.19, p = 0.0996, 65%, 62%).

CONCLUSION

Field asymmetric ion mobility spectrometry allowed for discrimination between faecal VOC profiles of de novo paediatric IBD patients and healthy controls, confirming the potential of faecal VOC analysis as a non-invasive diagnostic biomarker for paediatric IBD. This method may serve as a complementary, non-invasive technique in the diagnosis of IBD, possibly limiting the number of endoscopies needed in children suspected for IBD.

Predictive Biomarkers for Asthma Therapy

PURPOSE OF REVIEW

Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma.

RECENT FINDINGS

Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

Using a chemiresistor-based alkane sensor to distinguish exhaled breaths of lung cancer patients from subjects with no lung cancer

BACKGROUND

Breath alkanes are reported to be able to discriminate lung cancer patients from healthy people. A simple chemiresistor-based sensor was designed to respond to alkanes by a change in resistance measured by a digital multimeter connected to the sensor. In preclinical experiments, the sensor response was found to have a strong positive linear relationship with alkane compounds and not responsive to water. This study aimed to determine the ability of the alkane sensor to distinguish the exhaled breaths of lung cancer patients from that of chronic obstructive pulmonary disease (COPD) patients and control subjects without lung cancer.

METHODS

In this cross-sectional study, 12 treatment-naive patients with lung cancer, 12 ex- or current smokers with COPD and 13 never-smokers without lung disease were asked to exhale through a drinking straw into a prototype breath-in apparatus made from an empty 125 mL Vitagen^® bottle with the chemiresistor sensor attached at its inside bottom to measure the sensor peak output (percentage change of baseline resistance measured before exhalation to peak resistance) and the time taken for the baseline resistance to reach peak resistance.

RESULTS

Analysis of multivariate variance and post-hoc Tukey test revealed that the peak output and the time to peak values for the lung cancer patients were statistically different from that for both the COPD patients and the controls without lung disease, Pillai's Trace =0.393, F=3.909, df = (4, 64), P=0.007. A 2.20% sensor peak output and a 90-s time to peak gave 83.3% sensitivity and 88% specificity in diagnosing lung cancer. Tobacco smoking did not affect the diagnostic accuracy of the sensor.

CONCLUSIONS

The alkane sensor could discriminate patients with lung cancer from COPD patients and people without lung disease. Its potential utility as a simple, cheap and non-invasive test for early lung cancer detection needs further studies.