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.

Differences in autophagy marker levels at birth in preterm vs. term infants.

BACKGROUND: Preterm infants are susceptible to oxidative stress and prone to respiratory diseases. Autophagy is an important defense mechanism against oxidative-stress-induced cell damage and involved in lung development and respiratory morbidity. We hypothesized that autophagy marker levels differ between preterm and term infants. METHODS: In the prospective Basel-Bern Infant Lung Development (BILD) birth cohort we compared cord blood levels of macroautophagy (Beclin-1, LC3B), selective autophagy (p62) and regulation of autophagy (SIRT1) in 64 preterm and 453 term infants. RESULTS: Beclin-1 and LC3B did not differ between preterm and term infants. However, p62 was higher (0.37, 95% confidence interval (CI) 0.05;0.69 in log2-transformed level, p = 0.025, padj = 0.050) and SIRT1 lower in preterm infants (-0.55, 95% CI -0.78;-0.31 in log2-transformed level, padj < 0.001). Furthermore, p62 decreased (padj-value for smoothing function was 0.018) and SIRT1 increased (0.10, 95% CI 0.07;0.13 in log2-transformed level, padj < 0.001) with increasing gestational age. CONCLUSION: Our findings suggest differential levels of key autophagy markers between preterm and term infants. This adds to the knowledge of the sparsely studied field of autophagy mechanisms in preterm infants and might be linked to impaired oxidative stress response, preterm birth, impaired lung development and higher susceptibility to respiratory morbidity in preterm infants. IMPACT: To the best of our knowledge, this is the first study to investigate autophagy marker levels between human preterm and term infants in a large population-based sample in cord blood plasma This study demonstrates differential levels of key autophagy markers in preterm compared to term infants and an association with gestational age This may be linked to impaired oxidative stress response or developmental aspects and provide bases for future studies investigating the association with respiratory morbidity.

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.

Development of Core Outcome Measures sets for paediatric and adult Severe Asthma (COMSA).

BACKGROUND: Effectiveness studies with biological therapies for asthma lack standardised outcome measures. The COMSA (Core Outcome Measures sets for paediatric and adult Severe Asthma) Working Group sought to develop Core Outcome Measures (COM) sets to facilitate better synthesis of data and appraisal of biologics in paediatric and adult asthma clinical studies. METHODS: COMSA utilised a multi-stakeholder consensus process among patients with severe asthma, adult and paediatric clinicians, pharmaceutical representatives, and health regulators from across Europe. Evidence included a systematic review of development, validity and reliability of selected outcome measures plus a narrative review and a pan-European survey to better understand patients' and carers' views about outcome measures. It was discussed using a modified GRADE (Grading of Recommendations Assessment, Development and Evaluation) Evidence to Decision framework. Anonymous voting was conducted using predefined consensus criteria. RESULTS: Both adult and paediatric COM sets include forced expiratory volume in 1 s (FEV1) as z-scores, annual frequency of severe exacerbations and maintenance oral corticosteroid use. Additionally, the paediatric COM set includes the Paediatric Asthma Quality of Life Questionnaire and Asthma Control Test or Childhood Asthma Control Test, while the adult COM set includes the Severe Asthma Questionnaire and Asthma Control Questionnaire-6 (symptoms and rescue medication use reported separately). CONCLUSIONS: This patient-centred collaboration has produced two COM sets for paediatric and adult severe asthma. It is expected that they will inform the methodology of future clinical trials, enhance comparability of efficacy and effectiveness of biological therapies, and help assess their socioeconomic value. COMSA will inform definitions of non-response and response to biological therapy for severe asthma.

Increased Impact of Air Pollution on Lung Function in Preterm versus Term Infants: The BILD Study.

Rationale: Infants born prematurely have impaired capacity to deal with oxidative stress shortly after birth. Objectives: We hypothesize that the relative impact of exposure to air pollution on lung function is higher in preterm than in term infants. Methods: In the prospective BILD (Basel-Bern Infant Lung Development) birth cohort of 254 preterm and 517 term infants, we investigated associations of particulate matter ⩽10 µm in aerodynamic diameter (PM10) and nitrogen dioxide with lung function at 44 weeks' postconceptional age and exhaled markers of inflammation and oxidative stress response (fractional exhaled nitric oxide [FeNO]) in an explorative hypothesis-driven study design. Multilevel mixed-effects models were used and adjusted for known confounders. Measurements and Main Results: Significant associations of PM10 during the second trimester of pregnancy with lung function and FeNO were found in term and preterm infants. Importantly, we observed stronger positive associations in preterm infants (born 32-36 wk), with an increase of 184.9 (95% confidence interval [CI], 79.1-290.7) ml/min [Formula: see text]e per 10-µg/m3 increase in PM10, than in term infants (75.3; 95% CI, 19.7-130.8 ml/min) (pprematurity × PM10 interaction = 0.04, after multiple comparison adjustment padj = 0.09). Associations of PM10 and FeNO differed between moderate to late preterm (3.4; 95% CI, -0.1 to 6.8 ppb) and term (-0.3; 95% CI, -1.5 to 0.9 ppb) infants, and the interaction with prematurity was significant (pprematurity × PM10 interaction = 0.006, padj = 0.036). Conclusions: Preterm infants showed significantly higher susceptibility even to low to moderate prenatal air pollution exposure than term infants, leading to increased impairment of postnatal lung function. FeNO results further elucidate differences in inflammatory/oxidative stress response when comparing preterm infants with term infants.

Mapping atopic dermatitis and anti-IL-22 response signatures to type 2-low severe neutrophilic asthma.

BACKGROUND: Transcriptomic changes in patients who respond clinically to biological therapies may identify responses in other tissues or diseases. OBJECTIVE: We sought to determine whether a disease signature identified in atopic dermatitis (AD) is seen in adults with severe asthma and whether a transcriptomic signature for patients with AD who respond clinically to anti-IL-22 (fezakinumab [FZ]) is enriched in severe asthma. METHODS: An AD disease signature was obtained from analysis of differentially expressed genes between AD lesional and nonlesional skin biopsies. Differentially expressed genes from lesional skin from therapeutic superresponders before and after 12 weeks of FZ treatment defined the FZ-response signature. Gene set variation analysis was used to produce enrichment scores of AD and FZ-response signatures in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes asthma cohort. RESULTS: The AD disease signature (112 upregulated genes) encompassing inflammatory, T-cell, TH2, and TH17/TH22 pathways was enriched in the blood and sputum of patients with asthma with increasing severity. Patients with asthma with sputum neutrophilia and mixed granulocyte phenotypes were the most enriched (P < .05). The FZ-response signature (296 downregulated genes) was enriched in asthmatic blood (P < .05) and particularly in neutrophilic and mixed granulocytic sputum (P < .05). These data were confirmed in sputum of the Airway Disease Endotyping for Personalized Therapeutics cohort. IL-22 mRNA across tissues did not correlate with FZ-response enrichment scores, but this response signature correlated with TH22/IL-22 pathways. CONCLUSIONS: The FZ-response signature in AD identifies severe neutrophilic asthmatic patients as potential responders to FZ therapy. This approach will help identify patients for future asthma clinical trials of drugs used successfully in other chronic diseases.

Childhood asthma: pathogenesis and phenotypes.

In the pathogenesis of asthma in children there is a pivotal role for a type 2 inflammatory response to early life exposures or events. Interactions between infections, atopy, genetic susceptibility and environmental exposures (such as farmyard environment, air pollution and tobacco smoke exposure) influence the development of wheezing illness and the risk of progression to asthma. The immune system, lung function and the microbiome in gut and airways develop in parallel, and dysbiosis of the microbiome may be a critical factor in asthma development. Increased infant weight gain and preterm birth are other risk factors for development of asthma and reduced lung function. The complex interplay between these factors explains the heterogeneity of asthma in children. Subgroups of patients can be identified as phenotypes, based on clinical parameters, or endotypes, based on a specific pathophysiological mechanism. Paediatric asthma phenotypes and endotypes may ultimately help to improve diagnosis of asthma, prediction of asthma development and treatment of individual children, based on clinical, temporal, developmental or inflammatory characteristics. Unbiased, data-driven clustering, using a multidimensional or systems biology approach may be needed to better define phenotypes. The present knowledge on inflammatory phenotypes of childhood asthma has now been successfully applied in the treatment with biologicals of children with severe therapy-resistant asthma, and it is to be expected that more personalised treatment options may become available.

Early-life respiratory tract infections and the risk of school-age lower lung function and asthma: a meta-analysis of 150 000 European children.

BACKGROUND: Early-life respiratory tract infections might affect chronic obstructive respiratory diseases, but conclusive studies from general populations are lacking. Our objective was to examine if children with early-life respiratory tract infections had increased risks of lower lung function and asthma at school age. METHODS: We used individual participant data of 150 090 children primarily from the EU Child Cohort Network to examine the associations of upper and lower respiratory tract infections from age 6 months to 5 years with forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, forced expiratory flow at 75% of FVC (FEF75%) and asthma at a median (range) age of 7 (4-15) years. RESULTS: Children with early-life lower, not upper, respiratory tract infections had a lower school-age FEV1, FEV1/FVC and FEF75% (z-score range: -0.09 (95% CI -0.14- -0.04) to -0.30 (95% CI -0.36- -0.24)). Children with early-life lower respiratory tract infections had a higher increased risk of school-age asthma than those with upper respiratory tract infections (OR range: 2.10 (95% CI 1.98-2.22) to 6.30 (95% CI 5.64-7.04) and 1.25 (95% CI 1.18-1.32) to 1.55 (95% CI 1.47-1.65), respectively). Adjustment for preceding respiratory tract infections slightly decreased the strength of the effects. Observed associations were similar for those with and without early-life wheezing as a proxy for early-life asthma. CONCLUSIONS: Our findings suggest that early-life respiratory tract infections affect development of chronic obstructive respiratory diseases in later life, with the strongest effects for lower respiratory tract infections.

Pollen exposure is associated with risk of respiratory symptoms during the first year of life.

BACKGROUND: Pollen exposure is associated with respiratory symptoms in children and adults. However, the association of pollen exposure with respiratory symptoms during infancy, a particularly vulnerable period, remains unclear. We examined whether pollen exposure is associated with respiratory symptoms in infants and whether maternal atopy, infant's sex or air pollution modifies this association. METHODS: We investigated 14,874 observations from 401 healthy infants of a prospective birth cohort. The association between pollen exposure and respiratory symptoms, assessed in weekly telephone interviews, was evaluated using generalized additive mixed models (GAMMs). Effect modification by maternal atopy, infant's sex, and air pollution (NO2 , PM2.5 ) was assessed with interaction terms. RESULTS: Per infant, 37 ± 2 (mean ± SD) respiratory symptom scores were assessed during the analysis period (January through September). Pollen exposure was associated with increased respiratory symptoms during the daytime (RR [95% CI] per 10% pollen/m3 : combined 1.006 [1.002, 1.009]; tree 1.005 [1.002, 1.008]; grass 1.009 [1.000, 1.23]) and nighttime (combined 1.003 [0.999, 1.007]; tree 1.003 [0.999, 1.007]; grass 1.014 [1.004, 1.024]). While there was no effect modification by maternal atopy and infant's sex, a complex crossover interaction between combined pollen and PM2.5 was found (p-value 0.003). CONCLUSION: Even as early as during the first year of life, pollen exposure was associated with an increased risk of respiratory symptoms, independent of maternal atopy and infant's sex. Because infancy is a particularly vulnerable period for lung development, the identified adverse effect of pollen exposure may be relevant for the evolvement of chronic childhood asthma.

Are children born by cesarean delivery at higher risk for respiratory sequelae?

BACKGROUND: Globally, the number of children born by cesarean delivery is constantly increasing. However, hormonal and physiological changes associated with labor and vaginal delivery are considered necessary for lung maturation. OBJECTIVE: We aimed to assess whether the mode of delivery is associated with changes in respiratory and atopic outcomes during infancy and at school age. STUDY DESIGN: We included 578 children, born at ≥37 weeks of gestation, from a prospective birth cohort study. We compared weekly respiratory symptoms throughout the first year of life and infant lung function (tidal breathing and multiple-breath washout) at 5 weeks of age between children born by cesarean delivery (N=114) and those born by vaginal delivery (N=464) after term pregnancy in healthy women. At a follow-up visit conducted at 6 years of age (N=371, of which 65 were delivered by cesarean delivery), we assessed respiratory, atopic, and lung function outcomes (spirometry, body plethysmography, and multiple-breath washout). We performed adjusted regression analyses to examine the association between cesarean delivery and respiratory and atopic outcomes. To account for multiple testing, we used the Bonferroni correction, which led to an adapted significance level of P<.002. RESULTS: During infancy, children born by cesarean delivery did not have more respiratory symptoms than those born by vaginal delivery (median, 4 weeks; interquartile range, 7 weeks vs median, 5 weeks; interquartile range, 7 weeks; adjusted incidence rate ratio, 0.8; 95% confidence interval, 0.6-1.0; P=.02). Infant lung function was similar between the groups. Children born by cesarean delivery did not have a higher incidence of "ever wheezing" (adjusted odds ratio, 0.9; 95% confidence interval, 0.5-1.8; P=.78) or current asthma (adjusted odds ratio, 0.4; 95% confidence interval, 0.0-3.5; P=.42) at school age than those born by vaginal delivery. There was no difference in the lung function parameters between the groups. CONCLUSION: Cesarean delivery was not associated with respiratory symptoms in the first year of life, nor with different respiratory or atopic outcomes at school age, when compared with vaginal delivery. Our results indicate that there are no long-term consequences on the respiratory health of the child associated with cesarean delivery.

Lung function fluctuation patterns unveil asthma and COPD phenotypes unrelated to type 2 inflammation.

BACKGROUND: In all chronic airway diseases, the dynamics of airway function are influenced by underlying airway inflammation and bronchial hyperresponsiveness along with limitations in reversibility owing to airway and lung remodeling as well as mucous plugging. The relative contribution of each component translates into specific clinical patterns of symptoms, quality of life, exacerbation risk, and treatment success. OBJECTIVE: We aimed to evaluate whether subgrouping of patients with obstructive airway diseases according to patterns of fluctuation in lung function allows identification of specific phenotypes with distinct clinical characteristics. METHODS: We applied the novel method of fluctuation-based clustering (FBC) to twice-daily FEV1 measurements recorded over a 1-year period in a mixed group of 134 adults with mild-to-moderate asthma, severe asthma, or chronic obstructive pulmonary disease from the European BIOAIR cohort. RESULTS: Independently of clinical diagnosis, FBC divided patients into 4 fluctuation-based clusters with progressively increasing alterations in lung function that corresponded to patterns of increasing clinical severity, risk of exacerbation, and lower quality of life. Clusters of patients with airway disease with significantly elevated levels of biomarkers relating to remodeling (osteonectin) and cellular senescence (plasminogen activator inhibitor-1), accompanied by a loss of airway reversibility, pulmonary hyperinflation, and loss of diffusion capacity, were identified. The 4 clusters generated were stable over time and revealed no differences in levels of markers of type 2 inflammation (blood eosinophils and periostin). CONCLUSION: FBC-based phenotyping provides another level of information that is complementary to clinical diagnosis and unrelated to eosinophilic inflammation, which could identify patients who may benefit from specific treatment strategies or closer monitoring.

Comparison of Plasma Ionization- and Secondary Electrospray Ionization- High-resolution Mass Spectrometry for Real-time Breath Analysis.

Real-time breath analysis by high-resolution mass spectrometry (HRMS) is a promising method to noninvasively retrieve relevant biochemical information. In this work, we conducted a head-to-head comparison of two ionization techniques: Secondary electrospray ionization (SESI) and plasma ionization (PI), for the analysis of exhaled breath. Two commercially available SESI and PI sources were coupled to the same HRMS device to analyze breath of two healthy individuals in a longitudinal study. We analyzed 58 breath specimens in both platforms, leading to 2,209 and 2,296 features detected by SESI-HRMS and by PI-HRMS, respectively. 60% of all the mass spectral features were detected in both platforms. However, remarkable differences were noted in terms of the signal-to-noise ratio (S/N), whereby the median (interquartile range, IQR) S/N ratio for SESI-HRMS was 115 (IQR = 408), whereas for PI-HRMS it was 5 (IQR = 5). Differences in the mass spectral profiles for the same samples make the inter-comparability of both techniques problematic. Overall, we conclude that both techniques are excellent for real-time breath analysis because of the very rich mass spectral fingerprints. However, further work is needed to fully understand the exact metabolic insights one can gather using each of these platforms.

Maternal asthma is associated with reduced lung function in male infants in a combined analysis of the BLT and BILD cohorts.

RATIONALE: Asthma in pregnancy is associated with respiratory diseases in the offspring. OBJECTIVE: To investigate if maternal asthma is associated with lung function in early life. METHODS: Data on lung function measured at 5-6 weeks of age were combined from two large birth cohorts: the Bern Infant Lung Development (BILD) and the Australian Breathing for Life Trial (BLT) birth cohorts conducted at three study sites (Bern, Switzerland; Newcastle and Sydney, Australia). The main outcome variable was time to reach peak tidal expiratory flow as a percentage of total expiratory time(tPTEF:tE%). Bayesian linear hierarchical regression analyses controlling for study site as random effect were performed to estimate the effect of maternal asthma on the main outcome, adjusting for sex, birth order, breast feeding, weight gain and gestational age. In separate adjusted Bayesian models an interaction between maternal asthma and sex was investigated by including an interaction term. MEASUREMENTS AND MAIN RESULTS: All 406 BLT infants were born to mothers with asthma in pregnancy, while 193 of the 213 (91%) BILD infants were born to mothers without asthma. A significant interaction between maternal asthma and male sex was negatively associated with tPTEF:tE% (intercept 37.5; estimate: -3.5; 95% credible interval -6.8 to -0.1). Comparing the model posterior probabilities provided decisive evidence in favour of an interaction between maternal asthma and male sex (Bayes factor 33.5). CONCLUSIONS: Maternal asthma is associated with lower lung function in male babies, which may have lifelong implications on their lung function trajectories and future risk of wheezing and asthma.

Combination of Exhaled Breath Analysis with Parallel Lung Function and FeNO Measurements in Infants.

Breath analysis by secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) offers the possibility to measure comprehensive metabolic profiles. The technology is currently being deployed in several clinical settings in Switzerland and China. However, patients are required to exhale directly into the device located in a dedicated room. Consequently, clinical implementation in patients incapable of performing necessary exhalation maneuvers (e.g., infants) or immobile (e.g., too weak, elderly, or in intensive care) remains a challenge. The aim of this study was to develop a method to extend such breath analysis capabilities to this subpopulation of patients by collecting breath samples remotely (offline) and promptly (within 10 min) transfer them to SESI-HRMS for chemical analysis. We initially assessed the method in adults by comparing breath mass spectra collected offline with Nalophan bags against spectra of breath samples collected in real time. In total, 13 adults provided 176 pairs of real-time and offline measurements. Lin's concordance correlation coefficient (CCC) was used to estimate the agreement between offline and real-time analyses. Here, 1249 mass spectral features (55% of total detected) exhibited Lin's CCC > 0.6. Subsequently, the method was successfully deployed to analyze breath samples from infants (n = 16), obtaining as a result SESI-HRMS breath profiles. To demonstrate the clinical feasibility of the method, we measured in parallel other clinical variables: (i) lung function, which characterizes the breathing patterns, and (ii) nitric oxide, which is a surrogate marker of airway inflammation. As a showcase, we focused our analysis on the exhaled oxidative stress marker 4-hydroxynonenal and its association with nitric oxide and minute ventilation.

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.

Early age exposure to moisture and mould is related to FeNO at the age of 6 years.

BACKGROUND: Exposure to indoor moisture damage and visible mold has been found to be associated with asthma and respiratory symptoms in several questionnaire-based studies by self-report. We aimed to define the prospective association between the early life exposure to residential moisture damage or mold and fractional exhaled nitric oxide (FeNO) and lung function parameters as objective markers for airway inflammation and asthma in 6-year-old children. METHODS: Home inspections were performed in children's homes when infants were on average 5 months old. At age 6 years, data on FeNO (n = 322) as well as lung function (n = 216) measurements were collected. Logistic regression and generalized additive models were used for statistical analyses. RESULTS: Early age major moisture damage and moisture damage or mold in the child's main living areas were significantly associated with increased FeNO levels (>75th percentile) at the age of 6 years (adjusted odds ratios, 95% confidence intervals, aOR (95% CI): 3.10 (1.35-7.07) and 3.16 (1.43-6.98), respectively. Effects were more pronounced in those who did not change residential address throughout the study period. For lung function, major structural damage within the whole home was associated with reduced FEV1 and FVC, but not with FEV1/FVC. No association with lung function was observed with early moisture damage or mold in the child's main living areas. CONCLUSION: These results underline the importance of prevention and remediation efforts of moisture and mold-damaged buildings in order to avoid harmful effects within the vulnerable phase of the infants and children's immunologic development.

Associations of air pollution and greenness with the nasal microbiota of healthy infants: A longitudinal study.

BACKGROUND: Air pollution and greenness are associated with short- and long-term respiratory health in children but the underlying mechanisms are only scarcely investigated. The nasal microbiota during the first year of life has been shown to be associated with respiratory tract infections and asthma development. Thus, an interplay between greenness, air pollution and the early nasal microbiota may contribute to short- and long-term respiratory health. We aimed to examine associations between fine particulate matter (PM2.5), nitrogen dioxide (NO2) and greenness with the nasal microbiota of healthy infants during the first year of life in a European context with low-to-moderate air pollution levels. METHODS: Microbiota characterization was performed using 16 S rRNA pyrosequencing of 846 nasal swabs collected fortnightly from 47 healthy infants of the prospective Basel-Bern Infant Lung Development (BILD) cohort. We investigated the association of satellite-based greenness and an 8-day-average exposure to air pollution (PM2.5, NO2) with the nasal microbiota during the first year of life. Exposures were individually estimated with novel spatial-temporal models incorporating satellite data. Generalized additive mixed models adjusted for known confounders and considering the autoregressive correlation structure of the data were used for analysis. RESULTS: Mean (SD) PM2.5 level was 17.1 (3.8 µg/m3) and mean (SD) NO2 level was 19.7 (7.9 µg/m3). Increased PM2.5 and increased NO2 were associated with reduced within-subject Ruzicka dissimilarity (PM2.5: per 1 µg/m3 -0.004, 95% CI -0.008, -0.001; NO2: per 1 µg/m3 -0.004, 95% CI -0.007, -0.001). Whole microbial community comparison with nonmetric multidimensional scaling revealed distinct microbiota profiles for different PM2.5 exposure levels. Increased NO2 was additionally associated with reduced abundance of Corynebacteriaceae (per 1 µg/m3: -0.027, 95% CI -0.053, -0.001). No associations were found between greenness and the nasal microbiota. CONCLUSION: Air pollution was associated with Ruzicka dissimilarity and relative abundance of Corynebacteriaceae. This suggests that even low-to-moderate exposure to air pollution may impact the nasal microbiota during the first year of life. Our results will be useful for future studies assessing the clinical relevance of air-pollution-induced alterations of the nasal microbiota with subsequent respiratory disease development.

Extracellular Recording of Entire Neural Networks Using a Dual-Mode Microelectrode Array With 19584 Electrodes and High SNR.

Electrophysiological research on neural networks and their activity focuses on the recording and analysis of large data sets that include information of thousands of neurons. CMOS microelectrode arrays (MEAs) feature thousands of electrodes at a spatial resolution on the scale of single cells and are, therefore, ideal tools to support neural-network research. Moreover, they offer high spatio-temporal resolution and signal to-noise ratio (SNR) to capture all features and subcellular resolution details of neuronal signaling. Here, we present a dual-mode (DM) MEA, which enables simultaneous: 1) full-frame readout from all electrodes and 2) high-SNR readout from an arbitrarily selectable subset of electrodes. The DM-MEA includes 19584 electrodes, 19584 full-frame recording channels with noise levels of 10.4 µVrms in the action potential (AP) frequency band (300 Hz-5 kHz), 246 low-noise recording channels with noise levels of 3.0 µVrms in the AP band and eight stimulation units. The capacity to simultaneously perform full-frame and high-SNR recordings endows the presented DM-MEA with great flexibility for various applications in neuroscience and pharmacology.

Connectivity patterns between multiple allergen specific IgE antibodies and their association with severe asthma.

BACKGROUND: Allergic sensitization is associated with severe asthma, but assessment of sensitization is not recommended by most guidelines. OBJECTIVE: We hypothesized that patterns of IgE responses to multiple allergenic proteins differ between sensitized participants with mild/moderate and severe asthma. METHODS: IgE to 112 allergenic molecules (components, c-sIgE) was measured using multiplex array among 509 adults and 140 school-age and 131 preschool children with asthma/wheeze from the Unbiased BIOmarkers for the PREDiction of respiratory diseases outcomes cohort, of whom 595 had severe disease. We applied clustering methods to identify co-occurrence patterns of components (component clusters) and patterns of sensitization among participants (sensitization clusters). Network analysis techniques explored the connectivity structure of c-sIgE, and differential network analysis looked for differences in c-sIgE interactions between severe and mild/moderate asthma. RESULTS: Four sensitization clusters were identified, but with no difference between disease severity groups. Similarly, component clusters were not associated with asthma severity. None of the c-sIgE were identified as associates of severe asthma. The key difference between school children and adults with mild/moderate compared with those with severe asthma was in the network of connections between c-sIgE. Participants with severe asthma had higher connectivity among components, but these connections were weaker. The mild/moderate network had fewer connections, but the connections were stronger. Connectivity between components with no structural homology tended to co-occur among participants with severe asthma. Results were independent from the different sample sizes of mild/moderate and severe groups. CONCLUSIONS: The patterns of interactions between IgE to multiple allergenic proteins are predictors of asthma severity among school children and adults with allergic asthma.

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.