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Background With the continued advancement of CFTR modulator therapies there is likely to be a burgeoning population of adult cystic fibrosis (CF) patients unable to expectorate sputum. Consequently, the detection and surveillance of pulmonary colonisation, previously reliant on sputum culture, needs re-examining. We hypothesised that cough swabs analysed with culture-independent analysis of the 16S gene could serve as a surrogate for colonisation of the lower airways. Methods Cough swabs and sputum samples were prospectively collected from consecutive adults and children with CF across two sites at regular outpatient appointments. Conventional culture analysis and next generation sequencing were used to compare paired same day samples. Results Twenty-two adults and 8 paediatric patients provided 75 paired cough swabs and sputum samples. Alpha diversity measures showed increased bacterial richness in sputum, while evenness and Simpson's diveristy index were higher in cough swabs. Within each sampling technique, microbial composition showed greater similarity when considering intra-patient variation. Poor concordance was observed between culture independent cough swabs and culture dependent/independent sputum analysis for specific pathogens, with cough swabs unable to accurately identify commonly associated CF pathogens (AUROCC range: 0.51 to 0.64). Conclusion Culture independent analysis of cough swabs provides an inaccurate diagnosis of lower respiratory tract colonisation and should not be used as a diagnostic test in patients with CF.

RATIONALE Children with preschool wheezing or school-age asthma are reported to have airway microbial imbalances. OBJECTIVE To identify clusters in children with asthma or wheezing using oropharyngeal microbiota profiles. METHODS Oropharyngeal swabs, from the Unbiased BIOmarkers for the Prediction of REspiratory Disease outcomes pediatric asthma/wheezing cohort, were characterized by 16S rRNA gene sequencing and unsupervised hierarchical clustering was performed on the Bray-Curtis β-diversity. Enrichment scores (ESs) of the MSigDB Hallmark gene sets were computed from the blood transcriptome using gene set variation analysis. Children with severe asthma or severe wheezing were followed up for 12-18 months, with assessing the frequency of exacerbations. MEASUREMENTS AND MAIN RESULTS Oropharyngeal samples of 241 children (age range: 1-17 years, 40% female) revealed 4 taxa-driven clusters dominated by Streptococcus, Veillonella, Rothia and Haemophilus, respectively. The clusters showed significant differences in atopic dermatitis, grass pollen sensitization, FEV1 % predicted post-salbutamol, and the annual asthma exacerbation frequency during follow-up. The Veillonella-cluster was the most allergic and included highest percentage of children with ≥2 exacerbations/year during follow-up. The oropharyngeal clusters were different in the ESs of transforming growth factor β (highest in Veillonella-cluster) and Wnt/β-Catenin signaling (highest in Haemophilus-cluster) transcriptomic pathways in blood (all q-values < 0.05). CONCLUSION The analysis of the oropharyngeal microbiota of children with asthma/wheezing identified four clusters with distinct clinical characteristics (phenotypes) that associate with exacerbations' risk and transcriptomic pathways involved in airway remodeling. This suggests that further exploration of the oropharyngeal microbiota may lead to novel pathophysiological insights and potentially new treatment approaches.

Background: Some children with asthma experience exacerbations despite long-acting beta2-agonist (LABA) treatment. While this variability is partly caused by genetic variation, no genome-wide study until now has investigated which genetic factors associated with risk of exacerbations despite LABA use in children with asthma. We aimed to assess whether genetic variation was associated with exacerbations in children treated with LABA from a global consortium. Methods: A meta-analysis of genome-wide association studies (meta-GWAS) was performed in 1,425 children and young adults with asthma (age 6-21 years) with reported regular use of LABA from six studies within the PiCA consortium using a random effects model. The primary outcome of each study was defined as any exacerbation within the past 6 or 12 months, including at least one of the following: 1) hospital admissions for asthma, 2) a course of oral corticosteroids or 3) emergency room visits because of asthma. Results: Genome-wide association results for a total of 82 996 common single nucleotide polymorphisms (SNPs, MAF ≥1%) with high imputation quality were meta-analysed. Eight independent variants were suggestively (P-value threshold ≤5 × 10−6) associated with exacerbations despite LABA use. Conclusion: No strong effects of single nucleotide polymorphisms (SNPs) on exacerbations during LABA use were identified. We identified two loci (TBX3 and EPHA7) that were previously implicated in the response to short-acting beta2-agonists (SABA). These loci merit further investigation in response to LABA and SABA use.

BACKGROUND: Uncontrolled pediatric asthma has a large impact on patients and their caregivers. More insight into determinants of uncontrolled asthma is needed. We aim to compare treatment regimens, inhaler techniques, medication adherence and other characteristics of children with controlled and uncontrolled asthma in the: Systems Pharmacology approach to uncontrolled Paediatric Asthma (SysPharmPediA) study. MATERIAL AND METHODS: 145 children with moderate to severe doctor-diagnosed asthma (91 uncontrolled and 54 controlled) aged 6-17 years were enrolled in this multicountry, (Germany, Slovenia, Spain, and the Netherlands) observational, case-control study. The definition of uncontrolled asthma was based on asthma symptoms and/or exacerbations in the past year. Patient-reported adherence and clinician-reported medication use were assessed, as well as lung function and inhalation technique. A logistic regression model was fitted to assess determinants of uncontrolled pediatric asthma. RESULTS: Children in higher asthma treatment steps had a higher risk of uncontrolled asthma (OR (95%CI): 3.30 (1.56-7.19)). The risk of uncontrolled asthma was associated with a larger change in FEV1% predicted post and pre-salbutamol (OR (95%CI): 1.08 (1.02-1.15)). Adherence and inhaler techniques were not associated with risk of uncontrolled asthma in this population. CONCLUSION: This study showed that children with uncontrolled moderate-to-severe asthma were treated in higher treatment steps compared to their controlled peers, but still showed a higher reversibility response to salbutamol. Self-reported adherence and inhaler technique scores did not differ between controlled and uncontrolled asthmatic children. Other determinants, such as environmental factors and differences in biological profiles, may influence the risk of uncontrolled asthma in this moderate to severe asthmatic population. The SysPharmPediA consortium is supported by ZonMW [project number: 9,003,035,001], the Ministry of Education, Science, and Sport of the Republic of Slovenia [contract number C330–16–500,106]; the German Ministry of Education and Research (BMBF) [project number FKZ 031L0088]; Instituto de Salud Carlos III (ISCIII) through Strategic Action for Health Research (AES) and European Community (EC) within the Active and Assisted Living (AAL) Program framework [award numbers AC15/00,015 and AC15/00,058] under the frame of the ERACoSysMed JTC-1 Call.”

BACKGROUND: Electronic noses (eNoses) are emerging point-of-care tools that may help in the subphenotyping of chronic respiratory diseases such as asthma.OBJECTIVE: We aimed to investigate whether eNoses can classify atopy in pediatric and adult patients with asthma.METHODS: Participants with asthma and/or wheezing from 4 independent cohorts were included; BreathCloud participants (n = 429), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adults (n = 96), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes pediatric participants (n = 100), and Pharmacogenetics of Asthma Medication in Children: Medication with Anti-Inflammatory Effects 2 participants (n = 30). Atopy was defined as a positive skin prick test result (≥3 mm) and/or a positive specific IgE level (≥0.35 kU/L) for common allergens. Exhaled breath profiles were measured by using either an integrated eNose platform or the SpiroNose. Data were divided into 2 training and 2 validation sets according to the technology used. Supervised data analysis involved the use of 3 different machine learning algorithms to classify patients with atopic versus nonatopic asthma with reporting of areas under the receiver operating characteristic curves as a measure of model performance. In addition, an unsupervised approach was performed by using a bayesian network to reveal data-driven relationships between eNose volatile organic compound profiles and asthma characteristics.RESULTS: Breath profiles of 655 participants (n = 601 adults and school-aged children with asthma and 54 preschool children with wheezing [68.2% of whom were atopic]) were included in this study. Machine learning models utilizing volatile organic compound profiles discriminated between atopic and nonatopic participants with areas under the receiver operating characteristic curves of at least 0.84 and 0.72 in the training and validation sets, respectively. The unsupervised approach revealed that breath profiles classifying atopy are not confounded by other patient characteristics.CONCLUSION: eNoses accurately detect atopy in individuals with asthma and wheezing in cohorts with different age groups and could be used in asthma phenotyping.

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Background Early detection/prediction of flare‐ups in asthma, commonly triggered by viruses, would enable timely treatment. Previous studies on exhaled breath analysis by electronic nose (eNose) technology could discriminate between stable and unstable episodes of asthma, using single/few time‐points. To investigate its monitoring properties during these episodes, we examined day‐to‐day fluctuations in exhaled breath profiles, before and after a rhinovirus‐16 (RV16) challenge, in healthy and asthmatic adults. Methods In this proof‐of‐concept study, 12 atopic asthmatic and 12 non‐atopic healthy adults were prospectively followed thrice weekly, 60 days before, and 30 days after a RV16 challenge. Exhaled breath profiles were detected using an eNose, consisting of 7 different sensors. Per sensor, individual means were calculated using pre‐challenge visits. Absolute deviations (|%|) from this baseline were derived for all visits. Within‐group comparisons were tested with Mann‐Whitney U tests and receiver operating characteristic (ROC) analysis. Finally, Spearman's correlations between the total change in eNose deviations and fractional exhaled nitric oxide (FeNO), cold‐like symptoms, and pro‐inflammatory cytokines were examined. Results Both groups had significantly increased eNose fluctuations post‐challenge, which in asthma started 1 day post‐challenge, before the onset of symptoms. Discrimination between pre‐ and post‐challenge reached an area under the ROC curve of 0.82 (95% CI = 0.65–0.99) in healthy and 0.97 (95% CI = 0.91–1.00) in asthmatic adults. The total change in eNose deviations moderately correlated with IL‐8 and TNFα (ρ ≈ .50–0.60) in asthmatics. Conclusion Electronic nose fluctuations rapidly increase after a RV16 challenge, with distinct differences between healthy and asthmatic adults, suggesting that this technology could be useful in monitoring virus‐driven unstable episodes in asthma., Electronic nose sensor fluctuations increased after a RV‐16 challenge in asthmatic and healthy adults, more evidently in asthma. In asthma, the increase in eNose fluctuations occurred before the onset of cold‐like symptoms. The magnitude of the change in eNose fluctuations was not correlated with FeNO and cold‐like symptoms, but moderately correlated with pre‐ and post‐challenge cytokine levels in asthma.

BACKGROUND: The novel cystic fibrosis transmembrane conductance regulator (CFTR) modulators, ivacaftor, lumacaftor, and tezacaftor, are the first drugs directly targeting the underlying pathophysiological mechanism in cystic fibrosis (CF); however, independent studies describing their pharmacokinetics are lacking. The aim of this study was to develop a quantification method for ivacaftor and its 2 main metabolites, lumacaftor and tezacaftor, in plasma and sputum using liquid chromatography with tandem mass spectrometry. METHODS: The developed method used a small sample volume (20 µL) and simple pretreatment method; protein precipitation solution and internal standard were added in one step to each sample. Liquid chromatography with tandem mass spectrometry was performed for a total run time of 6 minutes. The method was validated by assessing selectivity, carryover, linearity, accuracy and precision, dilution, matrix effects, and stability. RESULTS: The selectivity was good as no interference from matrices was observed. In the concentration range from 0.01 to 10.0 mg/L, calibration curves were linear with a correlation coefficient >0.9997 for all compounds. The within-run and between-run accuracy were between 99.7% and 116% at the lower limit of quantitation (LLOQ) and between 95.8% and 112.9% for all concentrations above LLOQ for all analytes in plasma and sputum. Within-run and between-run precisions were

Asthma is a heterogeneous disease with multiple clinical presentations (phenotypes). Neutrophilic asthma is characterised by increased sputum neutrophils and generally has a poor response to corticosteroids and limited other therapeutic options. Neutrophilia originates from different factors, including the defective resolution of inflammation or bacterial infections. An association between airway bacterial imbalance (disturbance) and the neutrophilic phenotype has been reported, suggesting that airway microbiota composition is involved in neutrophilic asthma. Rather than being a separate entity, neutrophilic asthma may be in part, an alliance between innate immunity and microbiota composition that prompts protective mechanisms against invading pathogens.

There is a clinical need to identify children with poor asthma control as early as possible, to optimize treatment and/or to find therapeutic alternatives. Here, we present the “Systems Pharmacology Approach to Uncontrolled Pediatric Asthma” (SysPharmPediA) study, which aims to establish a pediatric cohort of moderate-to-severe uncontrolled and controlled patients with asthma, to investigate pathophysiological mechanisms underlying uncontrolled moderate-to-severe asthma in children on maintenance treatment, using a multi-omics systems medicine approach. In this multicenter observational case–control study, moderate-to-severe asthmatic children (age, 6–17 years) were included from four European countries (Netherlands, Germany, Spain, and Slovenia). Subjects were classified based on asthma control and number of exacerbations. Demographics, current and past patient/family history, and clinical characteristics were collected. In addition, systems-wide omics layers, including epi(genomics), transcriptomics, microbiome, proteomics, and metabolomics were evaluated from multiple samples. In all, 145 children were included in this cohort, 91 with uncontrolled (median age = 12 years, 43% females) and 54 with controlled asthma (median age = 11.7 years, 37% females). The two groups did not show statistically significant differences in age, sex, and body mass index z-score distribution. Comprehensive information and diverse noninvasive biosampling procedures for various omics analyses will provide the opportunity to delineate underlying pathophysiological mechanisms of moderate-to-severe uncontrolled pediatric asthma. This eventually might reveal novel biomarkers, which could potentially be used for noninvasive personalized diagnostics and/or treatment.

More than a decade has passed since the finalization of the Human Genome Project. Omics technologies made a huge leap from trendy and very expensive to routinely executed and relatively cheap assays. Simultaneously, we understood that omics is not a panacea for every problem in the area of human health and personalized medicine. Whilst in some areas of research omics showed immediate results, in other fields, including asthma, it only allowed us to identify the incredibly complicated molecular processes. Along with their possibilities, omics technologies also bring many issues connected to sample collection, analyses and interpretation. It is often impossible to separate the intrinsic imperfection of omics from asthma heterogeneity. Still, many insights and directions from applied omics were acquired-presumable phenotypic clusters of patients, plausible biomarkers and potential pathways involved. Omics technologies develop rapidly, bringing improvements also to asthma research. These improvements, together with our growing understanding of asthma subphenotypes and underlying cellular processes, will likely play a role in asthma management strategies.

Environmental factors, such as air pollution, can affect the composition of exhaled breath, and should be well understood before biomarkers in exhaled breath can be used in clinical practice. Our objective was to investigate whether short-term exposures to air pollution can be detected in the exhaled breath profile of healthy adults. In this study, 20 healthy young adults were exposed 2–4 times to the ambient air near a major airport and two highways. Before and after each 5 h exposure, exhaled breath was analyzed using an electronic nose (eNose) consisting of seven different cross-reactive metal-oxide sensors. The discrimination between pre and post-exposure was investigated with multilevel partial least square discriminant analysis (PLSDA), followed by linear discriminant and receiver operating characteristic (ROC) analysis, for all data (71 visits), and for a training (51 visits) and validation set (20 visits). Using all eNose measurements and the training set, discrimination between pre and post-exposure resulted in an area under the ROC curve of 0.83 (95% CI = 0.76–0.89) and 0.84 (95% CI = 0.75–0.92), whereas it decreased to 0.66 (95% CI = 0.48–0.84) in the validation set. Short-term exposure to high levels of air pollution potentially influences the exhaled breath profiles of healthy adults, however, the effects may be minimal for regular daily exposures.

Background: Pseudomonas aeruginosa (PA) is an important respiratory pathogen for cystic fibrosis (CF) patients. Routine microbiology surveillance is time-consuming, and is best performed on expectorated sputum. As alternative, volatile organic compounds (VOCs) may be indicative of PA colonisation. In this study, we aimed to identify VOCs associated with PA in literature and perform targeted exhaled breath analysis to recognize PA positive CF patients non-invasively. Methods: This study consisted of 1) a literature review to select VOCs of interest, and 2) a cross-sectional CF study. Definitions used: A) PA positive, PA culture at visit/chronically; B) PA free, no PA culture in ≥12 months. Exhaled VOCs were identified via quadrupole MS. The primary endpoint was the area under the receiver operating characteristics curve (AUROCC) of individual VOCs as well as combined VOCs against PA culture. Results: 241 VOCs were identified in literature, of which 56 were further evaluated, and 13 could be detected in exhaled breath in our cohort. Exhaled breath of 25 pediatric and 28 adult CF patients, PA positive (n=16) and free (n=28) was available. 3/13 VOCs were significantly (p

Background: Asthma is a heterogeneous disease characterized by distinct phenotypes with associated microbial dysbiosis. Objectives: Our aim was to identify severe asthma phenotypes based on sputum microbiome profiles and assess their stability after 12 to 18 months. A further aim was to evaluate clusters’ robustness after inclusion of an independent cohort of patients with mild-to-moderate asthma. Methods: In this longitudinal multicenter cohort study, sputum samples were collected for microbiome profiling from a subset of the Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adult patient cohort at baseline and after 12 to 18 months of follow-up. Unsupervised hierarchical clustering was performed by using the Bray-Curtis β-diversity measure of microbial profiles. For internal validation, partitioning around medoids, consensus cluster distribution, bootstrapping, and topological data analysis were applied. Follow-up samples were studied to evaluate within-patient clustering stability in patients with severe asthma. Cluster robustness was evaluated by using an independent cohort of patients with mild-to-moderate asthma. Results: Data were available for 100 subjects with severe asthma (median age 55 years; 42% males). Two microbiome-driven clusters were identified; they were characterized by differences in asthma onset, smoking status, residential locations, percentage of blood and/or sputum neutrophils and macrophages, lung spirometry results, and concurrent asthma medications (all P values < .05). The cluster 2 patients displayed a commensal-deficient bacterial profile that was associated with worse asthma outcomes than those of the cluster 1 patients. Longitudinal clusters revealed high relative stability after 12 to 18 months in those with severe asthma. Further inclusion of an independent cohort of 24 patients with mild-to-moderate asthma was consistent with the clustering assignments. Conclusion: Unbiased microbiome-driven clustering revealed 2 distinct robust phenotypes of severe asthma that exhibited relative overtime stability. This suggests that the sputum microbiome may serve as a biomarker for better characterizing asthma phenotypes.

BACKGROUND: Patients with severe asthma not meeting the strict trial eligibility criteria for mepolizumab are now routinely treated with this biological in clinical practice, but it remains unclear whether these ineligible patients respond differently to mepolizumab treatment.OBJECTIVE: This study investigated the extent and reasons for trial ineligibility of real-life, mepolizumab-treated patients with severe asthma and compared the characteristics of these patients with trial populations. Subsequently, therapeutic response in ineligible patients was assessed on the basis of oral corticosteroid (OCS) reduction.METHODS: Trial eligibility, population differences, and therapeutic response were assessed using the baseline characteristics of mepolizumab-receiving patients with severe asthma treated in the Amsterdam University Medical Centres and OCS dose at 6 months for OCS-dependent patients extracted from patients' electronic health records. Eligibility criteria and population characteristics from trials investigating mepolizumab were extracted from their original publications.RESULTS: A total of 82.4% of 119 mepolizumab-receiving, reallife patients with severe asthma were ineligible for trial inclusion, wherein 42.9% and 39.5% were excluded on the basis of inclusion and exclusion criteria, respectively. The clinical care population was older, more often male and demonstrating a better lung function under lower OCS maintenance dosages in comparison with trial populations. A total of 50% of 66 ineligible, OCS-dependent mepolizumab-treated patients were able to reduce their maintenance OCS dosage to

RationaleRecent studies reported elevated concentrations of ultrafine particles (UFP) near airports. Since UFP can deposit deep into the lungs and other organs, they may lead to adverse health effects. We investigated if controlled short-term exposures to UFP near an airport and two highways were associated with adverse cardiopulmonary outcomes. Methods: In this cross-over study, 21 healthy non-smoking adults (age range: 18-35 years) were repeatedly (2-5 visits) exposed for 5 hours to ambient air near Schiphol Airport, while performing intermittent cycling. Associations between pre-post exposure changes in cardiopulmonary parameters (spirometry, FeNO, ECG, blood pressure (BP)) and both total- and size-specific particle number concentrations (PNC) were assessed, using linear mixed effect models. Results: The total PNC was on average 53,500 #/cm3 (range 10,500-173,200) and was significantly associated with decreased FVC and prolonged QTc (table 1). These associations correlated with particles 50 nm (mainly UFP from road traffic). Conclusion: Short-term exposures to aviation-related UFP near a major airport were associated with decreased FVC and prolonged QTc intervals in healthy adults. Effects of long-term exposure to high UFP levels might have health implications and should be further investigated.

Background: Cross-sectional and longitudinal studies capture different aspects of physiological signals. Objective: To investigate whether single snapshots of exhaled breathprints from eNose can discriminate asthmatics from healthy controls and capture differences in breath profiles triggered by a viral challenge. Methods: The study followed-up 12 asthmatic and 12 healthy controls thrice weekly for 2 months before and 1 month after a rhinovirus challenge. The eNose ability to classify asthmatics from controls at each visit and between pre and post-viral states, was estimated by area under receiver operating characteristic curves (AUCs-ROC) for eNose sensors. The influence of the viral challenge on longitudinal variations of eNose signals was estimated by a mixed effects model (MEM). Results: The eNose was able to provide 100% discrimination between asthmatics and controls at each study visit, irrespective of the viral-challenge (Fig A). However, more changes in VOCs were found in asthmatics than in controls as indicated from the MEM. Discrimination of pre and post-viral phases was highest at visits 1, 3 and 7 in asthmatics vs only visit 7 in controls (Fig B & C). Conclusion: Cross-sectional study designs may uncover biomarkers distinguishing disease from health, but longitudinal designs are essential to detect influences by external triggers. In both cases, eNose may serve as a non-invasive asthma monitoring tool.

Introduction: The complexity and heterogeneous nature of asthma and chronic obstructive pulmonary disease (COPD) results in difficulties in diagnosing and treating patients. Biomarkers that can identify underlying mechanisms, identify patient phenotypes and to predict treatment response could be of great value for adequate treatment. Areas covered: Biomarkers play an important role for the development of novel targeted therapies in airways disease. Blood biomarkers are relatively non-invasive, easy to obtain and easy to apply in routine care. Several blood biomarkers are being used to diagnose and monitor chronic airways diseases, as well as to predict response to treatment and long-term prognosis. Blood eosinophils are the best studied biomarker, the most applied in clinical practice, and until now the most promising of all blood biomarkers. Other blood biomarkers, including serum periostin, IgE and ECP and plasma fibrinogen are less studied and less relevant in clinical practice. Recent developments include the use of antibody assays of many different cytokines at the same time, and ‘omics’ techniques and systems medicine. Expert commentary: With the exception of blood eosinophils, the use of blood biomarkers in asthma and COPD has been rather disappointing. Future research using new technologies like big-data analysis of blood samples from real-life patient cohorts will probably gain better insight into underlying mechanisms of different disease phenotypes. Identification of specific molecular pathways and associated biomarkers will then allow the development of new targets for precision medicine.

Introduction: Asthmatic patients show a large heterogeneity in response to asthma medication. Rapidly evolving genotyping technologies have led to the identification of various genetic variants associated with treatment outcomes.Areas covered: This review focuses on the current knowledge of genetic variants influencing treatment response to the most commonly used asthma medicines: short- and long-acting beta-2 agonists (SABA/LABA), inhaled corticosteroids (ICS) and leukotriene modifiers. This review shows that various genetic variants have been identified, but none are currently used to guide asthma treatment. One of the most promising genetic variants is the Arg16 variant in the ADRB2 gene to guide LABA treatment in asthmatic children.Expert commentary: Poor replication of initially promising results and the low fraction of variability accounted for by single genetic variants inhibit pharmacogenetic findings to reach the asthma clinic. Nevertheless, the identification of genetic variation influencing treatment response does provide more insights in the complex processes underlying response and might identify novel targets for treatment. There is a need to report measures of clinical validity, to perform precision-medicine guided trials, as well as to understand how genetic variation interacts with environmental factors. In addition, systems biology approaches might be able to show a more complete picture of these complex interactions

Introduction: Asthmatics have been reported to have airway microbial dysbiosis [Chung JACI 2017]. We aimed to detect severe asthma phenotypes using induced sputum microbiome profiles and to assess cluster-wise stability after 12-18 months of prospective follow-up. Methods: Induced sputum samples were collected from a subset of the U-BIOPRED adult severe asthmatics. 16s rRNA sequencing and metagenomics were used to characterize the sputum microbiome. Unsupervised hierarchical clustering was performed by Bray-Curtis β-diversity measure of 16s microbiome data. The clustering was validated using partition around medoids, topological data analysis, consensus cluster distribution and bootstrapping. Sputum samples collected after 12-18 months were used to assess patient cluster migration. Results: Analysis of sputum samples of 100 severe asthmatics (median age: 55 years, 42% male) revealed two microbiome-driven clusters. The clusters were significantly different in: age of asthma onset, residential location, smoking status, percentage of sputum neutrophils, and spirometry (p-values Conclusion: Induced sputum microbiome identified two distinct severe asthma phenotypes. The relative stability of microbiome-driven phenotypic clusters indicates its suitability for diagnostic and therapeutic precision medicine approaches.

Introduction: Electronic noses (eNoses) detect mixtures of volatile organic compounds (VOCs) in exhaled breath via a set of cross reactive sensors. eNose breathprints have the potential to reveal asthma phenotypes. We aim to reveal diagnostic potential of asthmatics’ breathprints to detect atopy. Methods: Standardized eNose platforms (De Vries ERJ 2018, Brinkman JACI 2018) captured breathprints in 4 independent cohorts; U-BIOPRED adults (n=106), U-BIOPRED pediatrics (n=101), BreathCloud (n=532) and PACMAN2 (n=33). Atopy was defined as positive skin prick test (⩾3mm), positive specific IgE (⩾0.35kU·L−1) and/or doctor diagnosed in the absence of the previous. Data analysis involved signal processing and statistics based on sparse partial least square discriminant analysis (sPLS-DA) and ROC curves. Results: A total number of 772 patients were analyzed (mean age: 50.6±14.9, 7.5±4.6, 48.4±18.1, and 11.9±2.3 for the U-BIOPRED adults, U-BIOPRED pediatrics, BreathCloud and PACMAN2 cohorts, respectively). Patients were adequately classified as atopic or not using sPLS-DA in the 4 cohorts (Figure 1), where the AUC-ROC curves ranged between 0.77-0.98 (p Conclusion: Exhaled breath analysis by eNose can identify atopy in asthmatics across all ages. This suggests that eNose technology might be a non-invasive and rapid alternative for skin- and specific IgE tests and may therefore be used to direct therapeutic decisions in asthma patients.

Rationale: Analysis of exhaled volatile organic compounds (VOCs) by sensor-driven electronic nose (eNose) technology is a widely suggested measure for non-invasive monitoring of chronic airway diseases. While this technology allows probabilistic (clinical) advise, it is incapable of providing details regarding involved metabolites. Modelling sensor deflections by matching Gas Chromatography-Mass Spectrometry (GC-MS) samples could help to ascertain which VOCs induce a sensor response. Objective: To determine the association between eNose sensor deflections and exhaled VOCs measured by GC-MS. Methods: Paired samples of breath from asthma patients (n=22) were collected on sorbent tubes. One tube was analysed by four different eNoses and the second one by GC-MS. Pooling of resulting datasets consisted of 1) Partial Least Square Regression (PLSR) analysis and 2) clustered heat-mapping of PLSR loadings. Results: Matching data was available for 158 eNose sensors and 1025 GC-MS features, whereby PLSR resulted in R2‘s from 0.25 to 0.72. Figure 1 shows clustered heat-mapping outcomes. Conclusion: This explorative analysis revealed distinctive and associated patterns of exhaled VOCs between eNose and GC-MS. This data matching could help to identify which VOCs are responsible for clinically relevant results obtained by eNose and will facilitate valorisation of breathomics into clinical tests.

Pseudomonas aeruginosa (PA) is one of the most pathogenic bacteria infecting the airways of patients with cystic fibrosis (CF). Sputum culture is the gold standard for detecting PA. However, this method is time-consuming. In this study we hypothesized that volatile organic compounds (VOCs) in exhaled breath can discriminate between PA infected and non-infected CF patients. Design: Cross-sectional baseline analysis of longitudinal cohort study. We collected exhaled air of both pediatric and adult CF patients with and without PA airways infection, in which VOCs were identified using Gas Chromatography – Mass Spectrometry (GC-MS). Infection was defined as culturing PA on the day of breath sampling, or chronic colonization with PA (in >50% of cultures (minimum of 4 samples) over the previous 12 months, or chronic maintenance treatment for PA). To identify VOCs relevant for distinction between the groups, univariate analysis (Mann Withney U test) was applied for each GC-MS compound. Features with a p-value below 0.05 retained for linear discriminant analysis. Diagnostic performed was evaluated by calculation of the area under the receiver operating characteristic - curve including 95% confidence Interval (CI). Complete data was available of 18 pediatric and 22 adult CF patients; 20 with and 20 without PA infection. Exploratory analysis of unselected patients showed that 3 out of 138 VOCs were consistently different in PA infected and non-infected patients, resulting in an AUC of 0.75 (CI 0.59 – 0.92). We discriminated PA infected and non-infected CF patients based on 3 VOCs with moderate accuracy. However, these preliminary results need to be validated in an independent patient cohort.

PURPOSE OF REVIEW: Asthma features a high degree of heterogeneity in both pathophysiology and therapeutic response, resulting in many asthma patients being treated inadequately. Biomarkers indicative of underlying pathological processes could be used to identify disease subtypes, determine prognosis and to predict or monitor treatment response. However, the newly identified as well as more established biomarkers have different applications and limitations. RECENT FINDINGS: Conventional markers for type 2-high asthma, such as blood eosinophils, fraction of exhaled nitric oxide, serum IgE and periostin, feature limited sensitivity and specificity despite their significant correlations. More distinctive models have been developed by combining biomarkers and/or using omics techniques. Recently, a model with a positive predictive value of 100% for identification of type 2-high asthma based on a combination of minimally invasive biomarkers was developed. SUMMARY: Individualisation of asthma treatment regimens on the basis of biomarkers is necessary to improve asthma control. However, the suboptimal properties of currently available conventional biomarkers limit its clinical utility. Newly identified biomarkers and models based on combinations and/or omics analysis must be validated and standardised before they can be routinely applied in clinical practice. The development of robust biomarkers will allow development of more efficacious precision medicine-based treatment approaches for asthma.

We report on the development of a compact prototype near-infrared DBR laser-based spectrometer employing off-axis integrated cavity output spectroscopy. The spectrometer is capable of simultaneous detection of acetylene (C2H2) and CO2 at 1,529.2 nm as well as hydrogen cyanide (HCN) at 1,533.5 nm. The detection limits of 8 ppbv for C2H2 and 80 ppbv for HCN are achieved for the acquisition time of 1 s. The setup has been tested for online measurements of C2H2 in exhaled breath of a smoking subject and HCN resulting from the metabolism of Pseudomonas aeruginosa bacteria in vitro. Further improvements of the performance of the spectrometer are discussed.

Asthma is the most common chronic disease in children, and is characterized by airway inflammation, bronchial hyperresponsiveness, and airflow obstruction. Asthma diagnosis, phenotyping, and monitoring are still challenging with currently available methods, such as spirometry, FE NO or sputum analysis. The analysis of volatile organic compounds (VOCs) in exhaled breath could be an interesting non-invasive approach, but has not yet reached clinical practice. This review describes the current status of breath analysis in the diagnosis and monitoring of pediatric asthma. Furthermore, features of an ideal breath test, different breath analysis techniques, and important methodological issues are discussed. Although only a (small) number of studies have been performed in pediatric asthma, of which the majority is focusing on asthma diagnosis, these studies show moderate to good prediction accuracy (80-100%, with models including 6-28 VOCs), thereby qualifying breathomics for future application. However, standardization of procedures, longitudinal studies, as well as external validation are needed in order to further develop breathomics into clinical tools. Such a non-invasive tool may be the next step toward stratified and personalized medicine in pediatric respiratory disease.

A compact, cost-effective sensor is developed for detection of hydrogen cyanide (HCN) in exhaled breath within seconds. For this, an off-axis integrated cavity output spectroscopy setup is combined with a widely tunable compact near-infrared laser (tunability 1527–1564 nm). For HCN a detection sensitivity has been obtained of 8 ppbv in nitrogen (within 1 s), equal to a noise equivalent absorption sensitivity of 1.9 × 10−9 cm−1 Hz−1/2. With this sensor we demonstrated the presence of HCN in exhaled breath; its detection could be a good indicator for bacterial lung infection. Due to its compact, cost-effective and user-friendly design, this laser-based sensor has the potential to be implemented in future clinical applications.

Revealing the biochemistry associated to micro-organismal interspecies interactions is highly relevant for many purposes. Each pathogen has a characteristic metabolic fingerprint that allows identification based on their unique multivariate biochemistry. When pathogen species come into mutual contact, their co-culture will display a chemistry that may be attributed both to mixing of the characteristic chemistries of the mono-cultures and to competition between the pathogens. Therefore, investigating pathogen development in a polymicrobial environment requires dedicated chemometric methods to untangle and focus upon these sources of variation. The multivariate data analysis method Projected Orthogonalised Chemical Encounter Monitoring (POCHEMON) is dedicated to highlight metabolites characteristic for the interaction of two micro-organisms in co-culture. However, this approach is currently limited to a single time-point, while development of polymicrobial interactions may be highly dynamic. A well-known multivariate implementation of Analysis of Variance (ANOVA) uses Principal Component Analysis (ANOVA-PCA). This allows the overall dynamics to be separated from the pathogen-specific chemistry to analyse the contributions of both aspects separately. For this reason, we propose to integrate ANOVA-PCA with the POCHEMON approach to disentangle the pathogen dynamics and the specific biochemistry in interspecies interactions. Two complementary case studies show great potential for both liquid and gas chromatography - mass spectrometry to reveal novel information on chemistry specific to interspecies interaction during pathogen development.

Ethylene is a major plant hormone mediating developmental processes and stress responses to stimuli such as infection. We show here that ethylene is also produced during systemic inflammation in humans and is released in exhaled breath. Traces of ethylene were detected by laser spectroscopy both in vitro in isolated blood leukocytes exposed to bacterial lipopolysaccharide (LPS) as well as in vivo following LPS administration in healthy volunteers. Exposure to LPS triggers formation of ethylene as a product of lipid peroxidation induced by the respiratory burst. In humans, ethylene was detected prior to the increase of blood levels of inflammatory cytokines and stress-related hormones. Our results highlight that ethylene release is an early and integral component of in vivo lipid peroxidation with important clinical implications as a breath biomarker of bacterial infection.

Volatile organic compound (VOC) analysis in exhaled breath is proposed as a non-invasive method to detect respiratory infections in cystic fibrosis patients. Since polymicrobial infections are common, we assessed whether we could distinguish Pseudomonas aeruginosa and Aspergillus fumigatus mono- and co-cultures using the VOC emissions. We took headspace samples of P. aeruginosa, A. fumigatus and co-cultures at 16, 24 and 48 h after inoculation, in which VOCs were identified by thermal desorption combined with gas chromatography – mass spectrometry. Using multivariate analysis by Partial Least Squares Discriminant Analysis we found distinct VOC biomarker combinations for mono- and co-cultures at each sampling time point, showing that there is an interaction between the two pathogens, with P. aeruginosa dominating the co-culture at 48 h. Furthermore, time-independent VOC biomarker combinations were also obtained to predict correct identification of P. aeruginosa and A. fumigatus in mono-culture and in co-culture. This study shows that the VOC combinations in P. aeruginosa and A. fumigatus co-microbial environment are different from those released by these pathogens in mono-culture. Using advanced data analysis techniques such as PLS-DA, time-independent pathogen specific biomarker combinations can be generated that may help to detect mixed respiratory infections in exhaled breath of cystic fibrosis patients.

Hydrogen cyanide is produced by S. aureus in vitro and in vivo and is not an exclusive biomarker for P. aeruginosa http://ow.ly/4nsh7y

Exhaled NO (F E NO 50 ) is elevated in asthma and clinical practice guidelines are published. A F E NO 50 above 35 ppb in children indicate eosinophilic inflammation and the response to inhaled corticosteroids (ICS) is likely. Intermediate F E NO 50 should be interpreted cautiously. Children with ICS provided exhaled breath samples for off line NO measurement with Sievers NOA 280. Three flow rates 16, 90 and 230 mL/s were used for the extended NO analysis (Hogman-Merilainen algorithm, HMA) to determine the alveolar concentration-C A NO, diffusion rate of the airway wall-D aw NO and airway wall content-C aw NO. For accuracy of the HMA, calculations of F E NO 50 were compared with measured F E NO 50 . Five children with F E NO 50 35 ppb with allergy had F E NO 50 56 (47;60) ppb and C aw NO 140 (121;172) ppb. In 13 children, with intermediate F E NO 50 20-35 ppb, with allergy had F E NO 50 27 (25;30) ppb with a wide range of C aw NO. In 5 children C aw NO is comparable to healthy children, 44 (43;50) ppb, but 8 children have increased C aw NO of 108 (95;129) ppb. Using the F E NO 50 > 35 ppb, the response to ICS is likely. However, in the children with F E NO 50 20-35 ppb more than half of them could possibly benefit of an adjustment of ICS if the C aw NO is considered. These results needs to be confirmed in a larger study where anti-inflammatory treatment is guided either by F E NO 50 as in the clinical practice guidelines or with the use of extended NO analysis where a personal target value of F E NO 50 can be calculated. 1 NO values given in geometrical mean (25;75 percentile).

Volatile Organic Compounds (VOCs) analysis in exhaled breath is proposed as a non-invasive method to detect respiratory infections in cystic fibrosis (CF) patients. Since polymicrobial infections are increasingly common, we assessed whether fingerprints of VOCs emitted by mono-cultures of Pseudomonas aeruginosa (PA) and mono-cultures of Aspergillus fumigatus (AF) are consistent in a polymicrobial environment. Mono-cultures of PA (strain ATCC 27853), mono-cultures of AF (clinical isolate) , and co-cultures of PA and AF were studied. Headspace samples were taken at 16, 24 and 48 hours after inoculation. VOCs in the headspace of the cultures were identified by Gas Chromatography – Mass Spectrometry. Multivariate analysis by Partial Least Squares Discriminant Analysis (PLS-DA) was used to identify unique VOC fingerprints for the presence of PA , AF or both. We identified VOC fingerprints consisting of 104 different compounds in each experimental setting. PLS-DA analysis was able to identify distinct VOC profiles for each of the monocultures and for the co-culture. Within each culture type, there is a large variation in the VOCs detected over time. Forty eight hours after inoculation, methyl thiolacetate is prominent and discriminating in PA cultures, 8-nonen-2-one in AF cultures and 2-nonanone in co-cultures. We can identify specific VOC fingerprints for PA and AF monocultures and co-cultures in vitro . This study shows that VOC fingerprints are time-dependent and that the fingerprints of PA and AF in mono-cultures are different from the VOC fingerprint in co-cultures, complicating the in vivo determination of micro-organisms when only based on VOC patterns.

We present the real-time monitoring of hydrogen cyanide (HCN) production from Pseudomonas aeruginosa (P. aeruginosa) strains in vitro, using laser-based photoacoustic spectroscopy. Simultaneously, the production of ammonia (NH3) was measured, and the influence of different factors (e.g. the medium, temperature and antibiotics treatment) was assessed. Both reference strains and clinical isolates of patients with CF were studied, and compared to other pathogens commonly present in lungs/airways of CF patients. Hydrogen cyanide production starts to rise as soon as P. aeruginosa bacteria reach the stationary phase ((9.0-9.5) × 10(9) colony forming units, CFUs), up to concentrations of 14.5 microliters per hour (µl h(-1)). Different strains of P. aeruginosa produced HCN to varying degrees, and addition of tobramycin strongly reduced HCN production within 2 h from application. Burkholderia cepacia also produced HCN (up to 0.35µl h(-1) in 9.0 × 10(9) CFU) while other pathogens (Aspergillus fumigatus, Stenotrophomonas maltophilia, Mycobacterium abscessus) did not produce detectable levels. Our study reveals for the first time a broad overview of the dynamics of the HCN production in vitro.

Exhaled nitric oxide (F(E)NO) is elevated in asthma, and a clinical practice guideline has been published with recommendations for anti-inflammatory treatment. It summarizes that a F(E)NO at an expiratory flow rate of 50 ml s(-1) (F(E)NO50) above 35 ppb in children indicates eosinophilic inflammation, and the most likely response is to use inhaled corticosteroids. Intermediate F(E)NO50 between 20-35 ppb should be interpreted cautiously. The aim of the study was to investigate this guideline in a small group of asthmatic children. Thirty-seven asthmatic children; 23 boys and 14 girls, visited the outpatient clinic, and provided exhaled breath samples for offline NO measurement. These samples were analysed with chemiluminescence techniques. Three flow rates, namely 16, 90 and 230 ml s(-1) were used for the extended NO analysis (Högman-Meriläinen algorithm, HMA) to estimate the alveolar concentration (C(A)NO), diffusion rate of the airway wall (D(aw)NO) and airway wall content (C(aw)NO). For accuracy of the HMA, the estimated value of F(E)NO at 50 ml s(-1) (F(E)NO50) was compared with measured F(E)NO50. In nine children the difference was more than 5 ppb and the data were therefore excluded. Five children with F(E)NO5020 ppb had no known allergy and their F(E)NO50 geometrical mean (25th; 75th percentile) was 11 (10;14) and CawNO was 32 (20;43) ppb. Ten children with F(E)NO50 35 ppb had an allergy and had F(E)NO50 of 56 (47;60) ppb and C(aw)NO of 140 (121;172) ppb. Thirteen children with allergies, with intermediate F(E)NO50, had F(E)NO50 of 27 (25;30) ppb with a wide range of C(aw)NO. In five of these children, values were comparable to healthy children, 44 (43;50) ppb while eight children had elevated C(aw)NO values of 108 (95;129) ppb. Our data indicate the clinical potential use of extended NO analysis to determine the personal target value of F(E)NO50 for monitoring the treatment outcome. Furthermore, for children with intermediate F(E)NO50 more than half of them could possibly benefit from an adjustment of inhaled corticosteroids if the C(aw)NO value was considered.