Induction of IL-10-producing type 2 innate lymphoid cells by allergen immunotherapy is associated with clinical response.

The role of innate immune cells in allergen immunotherapy that confers immune tolerance to the sensitizing allergen is unclear. Here, we report a role of interleukin-10-producing type 2 innate lymphoid cells (IL-10+ ILC2s) in modulating grass-pollen allergy. We demonstrate that KLRG1+ but not KLRG1- ILC2 produced IL-10 upon activation with IL-33 and retinoic acid. These cells attenuated Th responses and maintained epithelial cell integrity. IL-10+ KLRG1+ ILC2s were lower in patients with grass-pollen allergy when compared to healthy subjects. In a prospective, double-blind, placebo-controlled trial, we demonstrated that the competence of ILC2 to produce IL-10 was restored in patients who received grass-pollen sublingual immunotherapy. The underpinning mechanisms were associated with the modification of retinol metabolic pathway, cytokine-cytokine receptor interaction, and JAK-STAT signaling pathways in the ILCs. Altogether, our findings underscore the contribution of IL-10+ ILC2s in the disease-modifying effect by allergen immunotherapy.

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.

International Care programs for Pediatric Post-COVID Condition (Long COVID) and the way forward.

BACKGROUND: Pediatric Post-COVID-Condition (PPCC) clinics treat children despite limited scientific substantiation. By exploring real-life management of children diagnosed with PPCC, the International Post-COVID-Condition in Children Collaboration (IP4C) aimed to provide guidance for future PPCC care. METHODS: We performed a cross-sectional international, multicenter study on used PPCC definitions; the organization of PPCC care programs and patients characteristics. We compared aggregated data from PPCC cohorts and identified priorities to improve PPCC care. RESULTS: Ten PPCC care programs and six COVID-19 follow-up research cohorts participated. Aggregated data from 584 PPCC patients was analyzed. The most common symptoms included fatigue (71%), headache (55%), concentration difficulties (53%), and brain fog (48%). Severe limitations in daily life were reported in 31% of patients. Most PPCC care programs organized in-person visits with multidisciplinary teams. Diagnostic testing for respiratory and cardiac morbidity was most frequently performed and seldom abnormal. Treatment was often limited to physical therapy and psychological support. CONCLUSIONS: We found substantial heterogeneity in both the diagnostics and management of PPCC, possibly explained by scarce scientific evidence and lack of standardized care. We present a list of components which future guidelines should address, and outline priorities concerning PPCC care pathways, research and international collaboration. IMPACT: Pediatric Post-COVID Condition (PPCC) Care programs have been initiated in many countries. Children with PPCC in different countries are affected by similar symptoms, limiting many to participate in daily life. There is substantial heterogeneity in diagnostic testing. Access to specific diagnostic tests is required to identify some long-term COVID-19 sequelae. Treatments provided were limited to physical therapy and psychological support. This study emphasizes the need for evidence-based diagnostics and treatment of PPCC. The International Post-COVID Collaboration for Children (IP4C) provides guidance for guideline development and introduces a framework of priorities for PPCC care and research, to improve PPCC outcomes.

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 ß-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-ß (transforming growth factor-ß) (highest in the Veillonella cluster) and Wnt/ß-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.

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.

Cisplatin-induced nephrotoxicity in childhood cancer: comparison between two countries.

BACKGROUND: Various definitions used to describe cisplatin nephrotoxicity potentially lead to differences in determination of risk factors. This study evaluated incidence of kidney injury according to commonly used and alternative definitions in two cohorts of children who received cisplatin. METHODS: This retrospective cohort study included children from Vancouver, Canada (one center), and Mexico City, Mexico (two centers), treated with cisplatin for a variety of solid tumors. Serum creatinine-based definitions (KDIGO and Pediatric RIFLE (pRIFLE)), electrolyte abnormalities consisted of hypokalemia, hypophosphatemia and hypomagnesemia (based on NCI-CTCAE v5), and an alternative definition (Alt-AKI) were used to describe nephrotoxicity. Incidence with different definitions, definitional overlap, and inter-definition reliability was analyzed. RESULTS: In total, 173 children (100 from Vancouver, 73 from Mexico) were included. In the combined cohort, Alt-AKI criteria detected more patients with cisplatin nephrotoxicity compared to pRIFLE and KDIGO criteria (82.7 vs. 63.6 vs. 44.5%, respectively). Nephrotoxicity and all electrolyte abnormalities were significantly more common in Vancouver cohort than in Mexico City cohort except when using KDIGO definition. The most common electrolyte abnormalities were hypomagnesemia (88.9%, Vancouver) and hypophosphatemia (24.2%, Mexico City). The KDIGO definition provided highest overlap of cases in Vancouver (100%), Mexico (98.6%), and the combined cohort (99.4%). Moderate overall agreement was found among Alt-AKI, KDIGO, and pRIFLE definitions (κ = 0.18, 95% CI 0.1-0.27) in which KDIGO and pRIFLE showed moderate agreement (κ = 0.48, 95% CI 0.36-0.60). CONCLUSIONS: Compared to pRIFLE and KDIGO criteria, Alt-AKI criteria detected more patients with cisplatin nephrotoxicity. pRIFLE is more sensitive to detect not only actual kidney injury but also patients at risk of cisplatin nephrotoxicity, while KDIGO seems more useful to detect clinically significant kidney injury. A higher resolution version of the Graphical abstract is available as Supplementary information.

Precision Medicine in Asthma Therapy.

Asthma is a complex, heterogeneous disease that necessitates a proper patient evaluation to decide the correct treatment and optimize disease control. The recent introduction of new target therapies for the most severe form of the disease has heralded a new era of treatment options, intending to treat and control specific molecular pathways in asthma pathophysiology. Precision medicine, using omics sciences, investigates biological and molecular mechanisms to find novel biomarkers that can be used to guide treatment selection and predict response. The identification of reliable biomarkers indicative of the pathological mechanisms in asthma is essential to unravel new potential treatment targets. In this chapter, we provide a general description of the currently available -omics techniques, focusing on their implications in asthma therapy.

Persistence of parental-reported asthma at early ages: A longitudinal twin study.

BACKGROUND: Currently, we cannot predict whether a pre-school child with asthma-like symptoms will have asthma at school age. Whether genetic information can help in this prediction depends on the role of genetic factors in persistence of pre-school to school-age asthma. We examined to what extent genetic and environmental factors contribute to persistence of asthma-like symptoms at ages 3 to asthma at age 7 using a bivariate genetic model for longitudinal twin data. METHODS: We performed a cohort study in monozygotic and dizygotic twins from the Netherlands Twin Register (NTR, n = 21,541 twin pairs). Bivariate genetic models were fitted to longitudinal data on asthma-like symptoms reported by parents at age 3 and 7 years to estimate the contribution of genetic and environmental factors. RESULTS: Bivariate genetic modeling showed a correlation on the liability scale between asthma-like symptoms at age 3 and asthma at age 7 of 0.746 and the contribution of genetics was estimated to be 0.917. The genetic analyses indicated a substantial influence of genetic factors on asthma-like symptoms at ages 3 and 7 (heritability 80% and 90%, respectively); hence, contribution of environmental factors was low. Persistence was explained by a high (rg = 0.807) genetic correlation. CONCLUSION: Parental-reported asthma-like symptoms at age 3 and asthma at age 7 are highly heritably. The phenotype of asthma-like symptoms at age 3 and 7 was highly correlated and mainly due to heritable factors, indicating high persistence of asthma development over ages 3 and 7.

Multi-ancestry genome-wide association study of asthma exacerbations.

BACKGROUND: Asthma exacerbations are a serious public health concern due to high healthcare resource utilization, work/school productivity loss, impact on quality of life, and risk of mortality. The genetic basis of asthma exacerbations has been studied in several populations, but no prior study has performed a multi-ancestry meta-analysis of genome-wide association studies (meta-GWAS) for this trait. We aimed to identify common genetic loci associated with asthma exacerbations across diverse populations and to assess their functional role in regulating DNA methylation and gene expression. METHODS: A meta-GWAS of asthma exacerbations in 4989 Europeans, 2181 Hispanics/Latinos, 1250 Singaporean Chinese, and 972 African Americans analyzed 9.6 million genetic variants. Suggestively associated variants (p ≤ 5 × 10-5 ) were assessed for replication in 36,477 European and 1078 non-European asthma patients. Functional effects on DNA methylation were assessed in 595 Hispanic/Latino and African American asthma patients and in publicly available databases. The effect on gene expression was evaluated in silico. RESULTS: One hundred and twenty-six independent variants were suggestively associated with asthma exacerbations in the discovery phase. Two variants independently replicated: rs12091010 located at vascular cell adhesion molecule-1/exostosin like glycosyltransferase-2 (VCAM1/EXTL2) (discovery: odds ratio (ORT allele ) = 0.82, p = 9.05 × 10-6 and replication: ORT allele  = 0.89, p = 5.35 × 10-3 ) and rs943126 from pantothenate kinase 1 (PANK1) (discovery: ORC allele  = 0.85, p = 3.10 × 10-5 and replication: ORC allele  = 0.89, p = 1.30 × 10-2 ). Both variants regulate gene expression of genes where they locate and DNA methylation levels of nearby genes in whole blood. CONCLUSIONS: This multi-ancestry study revealed novel suggestive regulatory loci for asthma exacerbations located in genomic regions participating in inflammation and host defense.

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 ß-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.

Genome-wide association study of asthma exacerbations despite inhaled corticosteroid use.

RATIONALE: Substantial variability in response to asthma treatment with inhaled corticosteroids (ICS) has been described among individuals and populations, suggesting the contribution of genetic factors. Nonetheless, only a few genes have been identified to date. We aimed to identify genetic variants associated with asthma exacerbations despite ICS use in European children and young adults and to validate the findings in non-Europeans. Moreover, we explored whether a gene-set enrichment analysis could suggest potential novel asthma therapies. METHODS: A genome-wide association study (GWAS) of asthma exacerbations was tested in 2681 children of European descent treated with ICS from eight studies. Suggestive association signals were followed up for replication in 538 European asthma patients. Further evaluation was performed in 1773 non-Europeans. Variants revealed by published GWAS were assessed for replication. Additionally, gene-set enrichment analysis focused on drugs was performed. RESULTS: 10 independent variants were associated with asthma exacerbations despite ICS treatment in the discovery phase (p≤5×10-6). Of those, one variant at the CACNA2D3-WNT5A locus was nominally replicated in Europeans (rs67026078; p=0.010), but this was not validated in non-European populations. Five other genes associated with ICS response in previous studies were replicated. Additionally, an enrichment of associations in genes regulated by trichostatin A treatment was found. CONCLUSIONS: The intergenic region of CACNA2D3 and WNT5A was revealed as a novel locus for asthma exacerbations despite ICS treatment in European populations. Genes associated were related to trichostatin A, suggesting that this drug could regulate the molecular mechanisms involved in treatment response.

Treating severe asthma: Targeting the IL-5 pathway.

Severe asthma is a heterogeneous disease with different phenotypes based on clinical, functional or inflammatory parameters. In particular, the eosinophilic phenotype is associated with type 2 inflammation and increased levels of interleukin (IL)-4, IL-5 and IL-13). Monoclonal antibodies that target the eosinophilic inflammatory pathways (IL-5R and IL-5), namely mepolizumab, reslizumab, and benralizumab, are effective and safe for severe eosinophilic asthma. Eosinophils threshold represents the most indicative biomarker for response to treatment with all three monoclonal antibodies. Improvement in asthma symptoms scores, lung function, the number of exacerbations, history of late-onset asthma, chronic rhinosinusitis with nasal polyposis, low oral corticosteroids use and low body mass index represent predictive clinical markers of response. Novel Omics studies are emerging with proteomics data and exhaled breath analyses. These may prove useful as biomarkers of response and non-response biologics. Moreover, future biomarker studies need to be undertaken in paediatric patients affected by severe asthma. The choice of appropriate biologic therapy for severe asthma remains challenging. The importance of finding biomarkers that can predict response continuous an open issue that needs to be further explored. This review describes the clinical effects of targeting the IL-5 pathway in severe asthma in adult and paediatric patients, focusing on predictors of response and non-response.

ADRB2 haplotypes and asthma exacerbations in children and young adults: An individual participant data meta-analysis.

BACKGROUND: The polymorphism Arg16 in ß2 -adrenergic receptor (ADRB2) gene has been associated with an increased risk of exacerbations in asthmatic children treated with long-acting ß2 -agonists (LABA). However, it remains unclear whether this increased risk is mainly attributed to this single variant or the combined effect of the haplotypes of polymorphisms at codons 16 and 27. OBJECTIVE: We assessed whether the haplotype analysis could explain the association between the polymorphisms at codons 16 (Arg16Gly) and 27 (Gln27Glu) in ADRB2 and risk of asthma exacerbations in patients treated with inhaled corticosteroids (ICS) plus LABA. METHODS: The study was undertaken using data from 10 independent studies (n = 5903) participating in the multi-ethnic Pharmacogenomics in Childhood Asthma (PiCA) consortium. Asthma exacerbations were defined as asthma-related use of oral corticosteroids or hospitalizations/emergency department visits in the past 6 or 12 months prior to the study visit/enrolment. The association between the haplotypes and the risk of asthma exacerbations was performed per study using haplo.stats package adjusted for age and sex. Results were meta-analysed using the inverse variance weighting method assuming random-effects. RESULTS: In subjects treated with ICS and LABA (n = 832, age: 3-21 years), Arg16/Gln27 versus Gly16/Glu27 (OR: 1.40, 95% CI: 1.05-1.87, I2  = 0.0%) and Arg16/Gln27 versus Gly16/Gln27 (OR: 1.43, 95% CI: 1.05-1.94, I2  = 0.0%), but not Gly16/Gln27 versus Gly16/Glu27 (OR: 0.99, 95% CI: 0.71-1.39, I2  = 0.0%), were significantly associated with an increased risk of asthma exacerbations. The sensitivity analyses indicated no significant association between the ADRB2 haplotypes and asthma exacerbations in the other treatment categories, namely as-required short-acting ß2 -agonists (n = 973), ICS monotherapy (n = 2623), ICS plus leukotriene receptor antagonists (LTRA; n = 338), or ICS plus LABA plus LTRA (n = 686). CONCLUSION AND CLINICAL RELEVANCE: The ADRB2 Arg16 haplotype, presumably mainly driven by the Arg16, increased the risk of asthma exacerbations in patients treated with ICS plus LABA. This finding could be beneficial in ADRB2 genotype-guided treatment which might improve clinical outcomes in asthmatic patients.

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.

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.

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.

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.

The Influence of Smoking Status on Exhaled Breath Profiles in Asthma and COPD Patients.

Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking <24 vs. >24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking <24 vs. >24 h. The area under the receiver-operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked <24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC: 0.74; 95% CI: 0.66-0.81), and no cigarette consumption <24h (AUC 0.54, 95% CI: 0.43-0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54; 95% CI: 0.49-0.60) and recent cigarette consumption (AUC 0.60; 95% CI: 0.50-0.69). The eNose could distinguish between ever and never-smokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles.

Exhaled volatile organic compounds as markers for medication use in asthma.

INTRODUCTION: Asthma is a heterogeneous condition, characterised by chronic inflammation of the airways, typically managed with inhaled bronchodilators and corticosteroids. In the case of uncontrolled asthma, oral corticosteroids (OCSs) are often prescribed. Good adherence and inhalation technique are associated with improved outcomes; however, it is difficult to monitor appropriate drug intake and effectiveness in individual patients. Exhaled breath contains thousands of volatile organic compounds (VOCs) that reflect changes in the body's chemistry and may be useful for monitoring drug pharmacokinetics/pharmacodynamics. We aimed to investigate the association of exhaled VOCs in severe asthma patients from the U-BIOPRED cohort (by gas chromatography coupled with time-of-flight mass spectrometry) with urinary levels of salbutamol and OCSs (by liquid chromatography coupled with high-resolution mass spectrometry). METHODS: Samples were collected at baseline and after 12-18 months of follow-up. Statistical analysis was based on univariate and multivariate modelling, followed by area under the receiver operating characteristic curve (AUC) calculation. Results were verified through longitudinal replication and independent validation. RESULTS: Data were available for 78 patients (baseline n=48, replication n=30 and validation n=30). Baseline AUC values were 82.1% (95% CI 70.4-93.9%) for salbutamol and 78.8% (95% CI 65.8-91.8%) for OCS. These outcomes could be adequately replicated and validated. Additional regression analysis between qualified exhaled VOCs and urinary concentrations of salbutamol and prednisone showed statistically significant correlations (p<0.01). CONCLUSION: We have linked exhaled VOCs to urinary detection of salbutamol and OCSs. This merits further development of breathomics into a point-of-care tool for therapeutic drug monitoring.

Early-life antibiotic use and risk of asthma and eczema: results of a discordant twin study.

RATIONALE: Early-life antibiotic use has been associated with the development of atopic diseases, but the aetiology remains unclear. To elucidate the aetiology, we used a discordant twin design to control for genetic and environmental confounding. METHODS: We conducted a retrospective cohort study in twins aged 3-10 years from the Netherlands Twin Register (NTR, n=35 365) and a replication study in twins aged 9 years from the Childhood and Adolescent Twin Study in Sweden (CATSS, n=7916). Antibiotic use was recorded at age 0-2 years. Doctor-diagnosed asthma and eczema were reported by parents when children were aged 3-12 years in both cohorts. Individuals were included in unmatched analyses and in co-twin control analyses with disease discordant twin pairs. RESULTS: Early-life antibiotic use was associated with increased risk of asthma (NTR OR 1.34, 95% CI 1.28-1.41; CATSS OR 1.45, 95% CI 1.34-1.56) and eczema (NTR OR 1.08, 95% CI 1.03-1.13; CATSS OR 1.07, 95% CI 1.01-1.14) in unmatched analyses. Co-twin analyses in monozygotic and dizygotic twin pairs showed similar results for asthma (NTR OR 1.54, 95% CI 1.20-1.98; CATSS OR 2.00, 95% CI 1.28-3.13), but opposing results for eczema in the NTR (OR 0.99, 95% CI 0.80-1.25) and the CATSS (OR 1.67, 95% CI 1.12-2.49). The risk of asthma increased for antibiotics prescribed for respiratory infections (CATSS OR 1.45, 95% CI 1.34-1.56), but not for antibiotics commonly used for urinary tract/skin infections (CATSS OR 1.02, 95% CI 0.88-1.17). CONCLUSION: Children exposed to early-life antibiotic use, particularly prescribed for respiratory infections, may be at higher risk of asthma. This risk can still be observed when correcting for genetic and environmental factors. Our results could not elucidate whether the relationship between early-life antibiotic use and eczema is confounded by familial and genetic factors.