Exhaled Volatile Organic Compounds for Asthma Control Classification in Children with Moderate to Severe Asthma: Results from the SysPharmPediA Study

RATIONALE

Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma.

OBJECTIVES

To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma.

METHODS

This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated.

MEASUREMENTS AND MAIN RESULTS

Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets.

CONCLUSIONS

Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.

Oropharyngeal Microbiota Clusters in Children with Asthma or Wheeze Associate with Allergy, Blood Transcriptomic Immune Pathways, and Exacerbation Risk

Rationale: Children with preschool wheezing or school-age asthma are reported to have airway microbial imbalances. Objectives: To identify clusters in children with asthma or wheezing using oropharyngeal microbiota profiles. Methods: Oropharyngeal swabs from the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) pediatric asthma or wheezing cohort were characterized using 16S ribosomal RNA gene sequencing, and unsupervised hierarchical clustering was performed on the Bray-Curtis β-diversity. Enrichment scores of the Molecular Signatures Database 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 assessment of the frequency of exacerbations. Measurements and Main Results: Oropharyngeal samples from 241 children (age range, 1-17 years; 40% female) revealed four taxa-driven clusters dominated by Streptococcus, Veillonella, Rothia, and Haemophilus. The clusters showed significant differences in atopic dermatitis, grass pollen sensitization, FEV1% predicted after salbutamol, and annual asthma exacerbation frequency during follow-up. The Veillonella cluster was the most allergic and included the highest percentage of children with two or more exacerbations per year during follow-up. The oropharyngeal clusters were different in the enrichment scores of TGF-β (transforming growth factor-β) (highest in the Veillonella cluster) and Wnt/β-catenin signaling (highest in the Haemophilus cluster) transcriptomic pathways in blood (all q values <0.05). Conclusions: Analysis of the oropharyngeal microbiota of children with asthma or wheezing identified four clusters with distinct clinical characteristics (phenotypes) that associate with risk for exacerbation and transcriptomic pathways involved in airway remodeling. This suggests that further exploration of the oropharyngeal microbiota may lead to novel pathophysiologic insights and potentially new treatment approaches.

Precision Medicine for More Oxygen (P4O2)-Study Design and First Results of the Long COVID-19 Extension

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has led to the death of almost 7 million people, however, with a cumulative incidence of 0.76 billion, most people survive COVID-19. Several studies indicate that the acute phase of COVID-19 may be followed by persistent symptoms including fatigue, dyspnea, headache, musculoskeletal symptoms, and pulmonary functional-and radiological abnormalities. However, the impact of COVID-19 on long-term health outcomes remains to be elucidated. Aims: The Precision Medicine for more Oxygen (P4O2) consortium COVID-19 extension aims to identify long COVID patients that are at risk for developing chronic lung disease and furthermore, to identify treatable traits and innovative personalized therapeutic strategies for prevention and treatment. This study aims to describe the study design and first results of the P4O2 COVID-19 cohort. Methods: The P4O2 COVID-19 study is a prospective multicenter cohort study that includes nested personalized counseling intervention trial. Patients, aged 40-65 years, were recruited from outpatient post-COVID clinics from five hospitals in The Netherlands. During study visits at 3-6 and 12-18 months post-COVID-19, data from medical records, pulmonary function tests, chest computed tomography scans and biological samples were collected and questionnaires were administered. Furthermore, exposome data was collected at the patient's home and state-of-the-art imaging techniques as well as multi-omics analyses will be performed on collected data. Results: 95 long COVID patients were enrolled between May 2021 and September 2022. The current study showed persistence of clinical symptoms and signs of pulmonary function test/radiological abnormalities in post-COVID patients at 3-6 months post-COVID. The most commonly reported symptoms included respiratory symptoms (78.9%), neurological symptoms (68.4%) and fatigue (67.4%). Female sex and infection with the Delta, compared with the Beta, SARS-CoV-2 variant were significantly associated with more persisting symptom categories. Conclusions: The P4O2 COVID-19 study contributes to our understanding of the long-term health impacts of COVID-19. Furthermore, P4O2 COVID-19 can lead to the identification of different phenotypes of long COVID patients, for example those that are at risk for developing chronic lung disease. Understanding the mechanisms behind the different phenotypes and identifying these patients at an early stage can help to develop and optimize prevention and treatment strategies.

Validation of volatile metabolites of pulmonary oxidative injury: a bench to bedside study

Background

Changes in exhaled volatile organic compounds (VOCs) can be used to discriminate between respiratory diseases, and increased concentrations of hydrocarbons are commonly linked to oxidative stress. However, the VOCs identified are inconsistent between studies, and translational studies are lacking.

Methods

In this bench to bedside study, we captured VOCs in the headspace of A549 epithelial cells after exposure to hydrogen peroxide (H₂O₂), to induce oxidative stress, using high-capacity polydimethylsiloxane sorbent fibres. Exposed and unexposed cells were compared using targeted and untargeted analysis. Breath samples of invasively ventilated intensive care unit patients (n=489) were collected on sorbent tubes and associated with the inspiratory oxygen fraction (F _IO2 ) to reflect pulmonary oxidative stress. Headspace samples and breath samples were analysed using gas chromatography and mass spectrometry.

Results

In the cell, headspace octane concentration was decreased after oxidative stress (p=0.0013), while the other VOCs were not affected. 2-ethyl-1-hexanol showed an increased concentration in the headspace of cells undergoing oxidative stress in untargeted analysis (p=0.00014). None of the VOCs that were linked to oxidative stress showed a significant correlation with F _IO2 (R_s range: -0.015 to -0.065) or discriminated between patients with F _IO2 ≥0.6 or below (area under the curve range: 0.48 to 0.55).

Conclusion

Despite a comprehensive translational approach, validation of known and novel volatile biomarkers of oxidative stress was not possible in patients at risk of pulmonary oxidative injury. The inconsistencies observed highlight the difficulties faced in VOC biomarker validation, and that caution is warranted in the interpretation of the pathophysiological origin of discovered exhaled breath biomarkers.

Epigenome-Wide Association Studies of the Fractional Exhaled Nitric Oxide and Bronchodilator Drug Response in Moderate-to-Severe Pediatric Asthma

Asthma is the most prevalent pediatric chronic disease. Bronchodilator drug response (BDR) and fractional exhaled nitric oxide (FeNO) are clinical biomarkers of asthma. Although DNA methylation (DNAm) contributes to asthma pathogenesis, the influence of DNAm on BDR and FeNO is scarcely investigated. This study aims to identify DNAm markers in whole blood associated either with BDR or FeNO in pediatric asthma. We analyzed 121 samples from children with moderate-to-severe asthma. The association of genome-wide DNAm with BDR and FeNO has been assessed using regression models, adjusting for age, sex, ancestry, and tissue heterogeneity. Cross-tissue validation was assessed in 50 nasal samples. Differentially methylated regions (DMRs) and enrichment in traits and biological pathways were assessed. A false discovery rate (FDR) < 0.1 and a genome-wide significance threshold of p < 9 × 10−8 were used to control for false-positive results. The CpG cg12835256 (PLA2G12A) was genome-wide associated with FeNO in blood samples (coefficient= −0.015, p = 2.53 × 10−9) and nominally associated in nasal samples (coefficient = −0.015, p = 0.045). Additionally, three CpGs were suggestively associated with BDR (FDR < 0.1). We identified 12 and four DMRs associated with FeNO and BDR (FDR < 0.05), respectively. An enrichment in allergic and inflammatory processes, smoking, and aging was observed. We reported novel associations of DNAm markers associated with BDR and FeNO enriched in asthma-related processes.

Medication use in uncontrolled pediatric asthma: Results from the SysPharmPediA study

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.

Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate-to-severe asthma

BACKGROUND

Uncontrolled asthma can lead to severe exacerbations and reduced quality of life. Research has shown that the microbiome may be linked with asthma characteristics; however, its association with asthma control has not been explored. We aimed to investigate whether the gastrointestinal microbiome can be used to discriminate between uncontrolled and controlled asthma in children.

METHODS

143 and 103 feces samples were obtained from 143 children with moderate-to-severe asthma aged 6 to 17 years from the SysPharmPediA study. Patients were classified as controlled or uncontrolled asthmatics, and their microbiome at species level was compared using global (alpha/beta) diversity, conventional differential abundance analysis (DAA, analysis of compositions of microbiomes with bias correction), and machine learning [Recursive Ensemble Feature Selection (REFS)].

RESULTS

Global diversity and DAA did not find significant differences between controlled and uncontrolled pediatric asthmatics. REFS detected a set of taxa, including Haemophilus and Veillonella, differentiating uncontrolled and controlled asthma with an average classification accuracy of 81% (saliva) and 86% (feces). These taxa showed enrichment in taxa previously associated with inflammatory diseases for both sampling compartments, and with COPD for the saliva samples.

CONCLUSION

Controlled and uncontrolled children with asthma can be differentiated based on their gastrointestinal microbiome using machine learning, specifically REFS. Our results show an association between asthma control and the gastrointestinal microbiome. This suggests that the gastrointestinal microbiome may be a potential biomarker for treatment responsiveness and thereby help to improve asthma control in children.

Real-life efficacy and safety of elexacaftor/tezacaftor/ivacaftor on severe cystic fibrosis lung disease patients

Elexacaftor/tezacaftor/ivacaftor (ETI) is a cystic fibrosis (CF) transmembrane conductance regulator modulator, which has shown efficacy in CF patients (≥6 years) with ≥1 Phe508del mutation and a minimal function mutation. In October 2019, ETI became available on compassionate use basis for Dutch CF patients with severe lung disease. Our objective was to investigate safety and efficacy of ETI in this patient group in a real-life setting. A multicenter longitudinal observational study was conducted to examine changes in FEV1 , BMI, and adverse events at initiation and 1, 3, 6, and 12 months after starting ETI. The number of exacerbations was recorded in the 12 months before and the 12 months after ETI treatment. Patients eligible for compassionate use had a FEV1 <40% predicted. Wilcoxon signed-rank test analyzed changes over time. Twenty subjects were included and followed up for up to 12 months after starting ETI. Treatment was well tolerated with mild side effects reported, namely, rash (15%) and stomach ache (20%) with 80% resolving within 1 month. Mean absolute increase of FEV1 was 11.8/13.7% (p ≤ .001) and BMI was 0.49/1.87 kg/m2 (p < .001-0.02) after 1/12 months, respectively. In comparison to the number of exacerbations pretrial, there was a marked reduction in exacerbations after initiation. Our findings show long-term effects of treatment with ETI in patients with severe CF lung disease in a real-life setting. Treatment with ETI is associated with increased lung function and BMI, less exacerbations, and only mild side effects.

Primary ciliary dyskinesia in Volendam: Diagnostic and phenotypic features in patients with a CCDC114 mutation

Primary ciliary dyskinesia (PCD) is a heterogeneous disease, with impaired mucociliary clearance causing respiratory tract infections. A founding CCDC114 mutation has led to a relatively homogeneous and large Dutch PCD population in Volendam. Our aim was to describe their phenotype. Therefore, all Volendam PCD patients seen at the Amsterdam UMC were included in this study. Data were collected on lung function, microbiology, radiology, and ear‐nose‐throat (ENT) symptoms. A mixed effects model estimated lung function decline in %point per year (95% confidence interval [CI]). Thirty‐three (60%) out of approximately 56 Volendam PCD patients were treated at our center and included in this study. Only 30% of patients had situs inversus. FEV₁ declined in children (−1.43%/year, CI: −1.80/−1.05), but not in adults (0.01%/year, CI: −0.36/0.38). Pseudomonas aeruginosa was cultured in 21% of children and 60% of adults, respectively. Patients who have been infected at some point with P. aeruginosa had a steeper decline in FEV₁ as compared to patients that have never been infected. Neonatal symptoms (79%) and ENT problems (94%) were common; fertility issues however, were not (11%) common. Compared to other PCD cohorts, the Volendam/CCDC114 patients have a moderately severe phenotype with lung function decline predominantly occurring in childhood.

Comparison of microbial composition of cough swabs and sputum for pathogen detection in patients with cystic fibrosis

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.

Genome-wide association studies of exacerbations in children using long-acting beta2-agonists

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.

Quantitative Method for the Analysis of Ivacaftor, Hydroxymethyl Ivacaftor, Ivacaftor Carboxylate, Lumacaftor, and Tezacaftor in Plasma and Sputum Using Liquid Chromatography With Tandem Mass Spectrometry and Its Clinical Applicability

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 <12.7% for LLOQ and <6.7% for the higher limit of quantitation. Samples were stable, with no significant degradation at examined temperatures and time points. Clinical applicability was revealed by analyzing samples from 2 patients with CF.

CONCLUSIONS

The presented method enables simultaneous quantification of ivacaftor, lumacaftor, and tezacaftor in plasma and sputum and is an improvement over previous methods because it uses smaller sample volumes, a simple pretreatment protocol, and includes tezacaftor. In future studies, it can be applied for examining pharmacokinetics characteristics of new CF transmembrane conductance regulator modulators.

Increased day-to-day fluctuations in exhaled breath profiles after a rhinovirus challenge in asthma

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.

Targeted exhaled breath analysis for detection of Pseudomonas aeruginosa in cystic fibrosis patients

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<0.05) different between PA groups in children; none were in adults. Notably, a composite model based on 5 or 1 VOC(s) showed an AUROCC of 0.86 (CI 0.71-1.0) and 0.87 (CI 0.72-1.0) for adults and children, respectively.

CONCLUSIONS

Targeted VOC analysis appears to discriminate children and adults with and without PA positive cultures with clinically acceptable sensitivity values.

Lumacaftor/ivacaftor changes the lung microbiome and metabolome in cystic fibrosis patients

Rationale

Targeted cystic fibrosis (CF) therapy with lumacaftor/ivacaftor partly restores chloride channel function and improves epithelial fluid transport in the airways. Consequently, changes may occur in the microbiome, which is adapted to CF lungs.

Objectives

To investigate the effects of lumacaftor/ivacaftor on respiratory microbial composition and microbial metabolic activity by repeatedly sampling the lower respiratory tract.

Methods

This was a single-centre longitudinal observational cohort study in adult CF patients with a homozygous Phe508del mutation. Lung function measurements and microbial cultures of sputum were performed as part of routine care. An oral and nasal wash, and a breath sample, were collected before and every 3 months after starting therapy, for up to 12 months.

Results

Twenty patients were included in this study. Amplicon 16S RNA and metagenomics sequencing revealed that Pseudomonas aeruginosa was most abundant in sputum and seemed to decrease after 6 months of treatment, although this did not reach statistical significance after correction for multiple testing. Two types of untargeted metabolomics analyses in sputum showed a change in metabolic composition between 3 and 9 months that almost returned to baseline levels after 12 months of treatment. The volatile metabolic composition of breath was significantly different after 3 months and remained different from baseline until 12 months follow-up.

Conclusions

After starting CF transmembrane conductance regulator (CFTR) modulating treatment in CF patients with a homozygous Phe508del mutation, a temporary and moderate change in the lung microbiome is observed, which is mainly characterised by a reduction in the relative abundance of Pseudomonas aeruginosa.

Lumacaftor/ivacaftor in adult cystic fibrosis patients with homozygous Phe508del results in temporal and moderate changes in lung microbiome and metabolome, that are mainly characterised by a reduction in the relative abundance of Pseudomonas aeruginosahttps://bit.ly/3pcPUfX

The Impact of Short-Term Exposure to Air Pollution on the Exhaled Breath of Healthy Adults

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.

Effects of short-term exposures to ultrafine particles near an airport in healthy subjects

BACKGROUND

Recent studies reported elevated concentrations of ultrafine particles (UFP) near airports. Little is known about the health effects of UFP from aviation. Since UFP can deposit deep into the lungs and other organs, they may cause significant adverse health effects.

OBJECTIVE

We investigated health effects of controlled short-term human exposure to UFP near a major airport.

METHODS

In this study, 21 healthy non-smoking volunteers (age range: 18-35 years) were repeatedly (2-5 visits) exposed for 5 h to ambient air near Schiphol Airport, while performing intermittent moderate exercise (i.e. cycling). Pre- to post-exposure changes in cardiopulmonary outcomes (spirometry, forced exhaled nitric oxide, electrocardiography and blood pressure) were assessed and related to total- and size-specific particle number concentrations (PNC), using linear mixed effect models.

RESULTS

The PNC was on average 53,500 particles/cm³ (range 10,500-173,200). A 5-95th percentile increase in exposure to UFP (i.e. 125,400 particles/cm³) was associated with a decrease in FVC of -73.8 mL (95% CI -138.8 - -0.4) and a prolongation of the corrected QT (QTc) interval by 9.9 ms (95% CI 2.0 - 19.1). These effects were associated with particles < 20 nm (mainly UFP from aviation), but not with particles > 50 nm (mainly UFP from road traffic).

DISCUSSION

Short-term exposures to aviation-related UFP near a major airport, was associated with decreased lung function (mainly FVC) and a prolonged QTc interval in healthy volunteers. The effects were relatively small, however, they appeared after single exposures of 5 h in young healthy adults. As this study cannot make any inferences about long-term health impacts, appropriate studies investigating potential health effects of long-term exposure to airport-related UFP, are urgently needed.

eNose breath prints as a surrogate biomarker for classifying patients with asthma by atopy

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.

Sputum microbiome profiles identify severe asthma phenotypes of relative stability at 12 to 18 months

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.

Treatment Eligibility of Real-Life Mepolizumab-Treated Severe Asthma Patients

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, real-life 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 ≤5 mg prednisone/day.

CONCLUSIONS

A large proportion of the real-life, mepolizumab-treated population with severe asthma would be excluded from trial participation, and significant differences in population characteristics exist. Regardless, a large fraction of ineligible patients in clinical care can reduce maintenance OCS dosage under mepolizumab therapy.

Omics for the future in asthma

Asthma is a common, complex, multifaceted disease. It comprises multiple phenotypes, which might benefit from treatment with different types of innovative targeted therapies. Refining these phenotypes and understanding their underlying biological structure would help to apply precision medicine approaches. Using different omics methods, such as (epi)genomics, transcriptomics, proteomics, metabolomics, microbiomics, and exposomics, allowed to view and investigate asthma from diverse angles. Technological advancement led to a large increase in the application of omics studies in the asthma field. Although the use of omics technologies has reduced the gap between bench to bedside, several design and methodological challenges still need to be tackled before omics can be applied in asthma patient care. Collaborating under a centralized harmonized work frame (such as in consortia, under consistent methodologies) could help worldwide research teams to tackle these challenges. In this review, we discuss the transition of single biomarker research to multi-omics studies. In addition, we deliberate challenges such as the lack of standardization of sampling and analytical methodologies and validation of findings, which comes in between omics and personalized patient care. The future of omics in asthma is encouraging but not completely clear with some unanswered questions, which have not been adequately addressed before. Therefore, we highlight these questions and emphasize on the importance of fulfilling them.

What did we learn from multiple omics studies in asthma?

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.

The crosstalk between microbiome and asthma: Exploring associations and challenges

With the advancement of high‐throughput DNA/RNA sequencing and computational analysis techniques, commensal bacteria are now considered almost as important as pathological ones. Understanding the interaction between these bacterial microbiota, host and asthma is crucial to reveal their role in asthma pathophysiology. Several airway and/or gut microbiome studies have shown associations between certain bacterial taxa and asthma. However, challenges remain before gained knowledge from these studies can be implemented into clinical practice, such as inconsistency between studies in choosing sampling compartments and/or sequencing approaches, variability of results in asthma studies, and not taking into account medication intake and diet composition especially when investigating gut microbiome. Overcoming those challenges will help to better understand the complex asthma disease process. The therapeutic potential of using pro‐ and prebiotics to prevent or reduce risk of asthma exacerbations requires further investigation. This review will focus on methodological issues regarding setting up a microbiome study, recent developments in asthma bacterial microbiome studies, challenges and future therapeutic potential.

Blood biomarkers in chronic airways diseases and their role in diagnosis and management

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.

Breathomics from exhaled volatile organic compounds in pediatric asthma

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, F_E 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.

Treatment response heterogeneity in asthma: the role of genetic variation

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.

Ethylene, an early marker of systemic inflammation in humans

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.

Detection of Staphylococcus aureus in cystic fibrosis patients using breath VOC profiles

Staphylococcus aureus (S. aureus) is a common bacterium infecting children with cystic fibrosis (CF). Since current detection methods are difficult to perform in children, there is need for an alternative. This proof of concept study investigates whether breath profiles can discriminate between S. aureus infected and non-infected CF patients based on volatile organic compounds (VOCs). We collected exhaled breath of CF patients with and without S. aureus airways infections in which VOCs were identified using gas chromatography-mass spectrometry. We classified these VOC profiles with sparse partial least squares discriminant analysis. Multivariate breath VOC profiles discriminated infected from non-infected CF patients with high sensitivity (100%) and specificity (80%). We identified the nine compounds most important for this discrimination. We successfully detected S. aureus infection in CF patients, using breath VOC profiles. Nine highlighted compounds can be used as a focus point in further biomarker identification research. The results show considerable potential for non-invasive diagnosis of airway infections.

Extended nitric oxide analysis may improve personalized anti-inflammatory treatment in asthmatic children with intermediate F(E)NO50

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)NO50 <20 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.

Optical parametric oscillator-based photoacoustic detection of hydrogen cyanide for biomedical applications

A versatile, continuous wave, optical parametric oscillator is used in combination with photoacoustic spectroscopy for long-term trace gas experiments of volatile compounds emitted by biological samples. The optical parametric oscillator-based spectrometer (wavelength near 3 μm, 8-MHz linewidth, output power ∼1 W) is successfully tested for the detection of hydrogen cyanide (HCN) emission from clover leaves, and Pseudomonas bacteria; in addition, the presence of HCN in exhaled human breath is measured. For specific experiments, the spectrometer is operated continuously up to 10 days and has a detection limit of 0.4 parts-per-billion volume of HCN in air over 10 s, using the P8 rotational line in the ν₃ vibrational band of HCN at 3287.25 cm⁻¹. This results in an overall sensitivity of the system of 2.5 × 10⁻⁹ cm-1 Hz⁻¹/².