TOLLIP and MUC5B modulate the effect of ambient NO2 on respiratory symptoms in infancy.

BACKGROUND: Current knowledge suggests that the gene region containing MUC5B and TOLLIP plays a role in airway defence and airway inflammation, and hence respiratory disease. It is also known that exposure to air pollution increases susceptibility to respiratory disease. We aimed to study whether the effect of air pollutants on the immune response and respiratory symptoms in infants may be modified by polymorphisms in MUC5B and TOLLIP genes. METHODS: 359 healthy term infants from the prospective Basel-Bern Infant Lung Development (BILD) birth cohort were included in the study. The main outcome was the score of weekly assessed respiratory symptoms in the first year of life. Using the candidate gene approach, we selected 10 single nucleotide polymorphisms (SNPs) from the MUC5B and TOLLIP regions. Nitrogen dioxide (NO2) and particulate matter ≤10µm in aerodynamic diameter (PM10) exposure was estimated on a weekly basis. We used generalised additive mixed models adjusted for known covariates. To validate our results in vitro, cells from a lung epithelial cell line were downregulated in TOLLIP expression and exposed to diesel particulate matter (DPM) and polyinosinic-polycytidylic acid. RESULTS: Significant interaction was observed between modelled air pollution (weekly NO2 exposure) and 5 SNPs within MUC5B and TOLLIP genes regarding respiratory symptoms as outcome: E.g., infants carrying minor alleles of rs5744034, rs3793965 and rs3750920 (all TOLLIP) had an increased risk of respiratory symptoms with increasing NO2 exposure. In vitro experiments showed that cells downregulated for TOLLIP react differently to environmental pollutant exposure with DPM and viral stimulation. CONCLUSION: Our findings suggest that the effect of air pollution on respiratory symptoms in infancy may be influenced by the genotype of specific SNPs from the MUC5B and TOLLIP regions. For validation of the findings, we provided in vitro evidence for the interaction of TOLLIP with air pollution.

Optimized algorithm for speed-of-sound-based infant sulfur hexafluoride multiple-breath washout measurements.

INTRODUCTION: Major methodological issues with the existing algorithm (WBreath) used for the analysis of speed-of-sound-based infant sulfur hexafluoride (SF6) multiple-breath washout (MBW) measurements lead to implausible results and complicate the comparison between different age groups and centers. METHODS: We developed OASIS-a novel algorithm to analyze speed-of-sound-based infant SF6 MBW measurements. This algorithm uses known context of the measurements to replace the dependence of WBreath on model input parameters. We validated the functional residual capacity (FRC) measurement accuracy of this new algorithm in vitro, and investigated its use in existing infant MBW data sets from different infant cohorts from Switzerland and South Africa. RESULTS: In vitro, OASIS managed to outperform WBreath at FRC measurement accuracy, lowering mean (SD) absolute error from 5.1 (3.2) % to 2.1 (1.6) % across volumes relevant for the infant age range, in variable temperature, respiratory rate, tidal volume and ventilation inhomogeneity conditions. We showed that changes in the input parameters to WBreath had a major impact on MBW results, a methodological drawback which does not exist in the new algorithm. OASIS produced more plausible results than WBreath in longitudinal tracking of lung clearance index (LCI), provided improved measurement stability in LCI over time, and improved comparability between centers. DISCUSSION: This new algorithm represents a meaningful advance in obtaining results from a legacy system of lung function measurement by allowing a single method to analyze measurements from different age groups and centers.

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.

Metabolic trajectories of diabetic ketoacidosis onset described by breath analysis.

Purpose: This feasibility study aimed to investigate the use of exhaled breath analysis to capture and quantify relative changes of metabolites during resolution of acute diabetic ketoacidosis under insulin and rehydration therapy. Methods: Breath analysis was conducted on 30 patients of which 5 with DKA. They inflated Nalophan bags, and their metabolic content was subsequently interrogated by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). Results: SESI-HRMS analysis showed that acetone, pyruvate, and acetoacetate, which are well known to be altered in DKA, were readily detectable in breath of participants with DKA. In addition, a total of 665 mass spectral features were found to significantly correlate with base excess and prompt metabolic trajectories toward an in-control state as they progress toward homeostasis. Conclusion: This study provides proof-of-principle for using exhaled breath analysis in a real ICU setting for DKA monitoring. This non-invasive new technology provides new insights and a more comprehensive overview of the effect of insulin and rehydration during DKA treatment.

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.

Preservation of exhaled breath samples for analysis by off-line SESI-HRMS: proof-of-concept study.

Secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) is an established technique in the field of breath analysis characterized by its short analysis time, as well as high levels of sensitivity and selectivity. Traditionally, SESI-HRMS has been used for real-time breath analysis, which requires subjects to be at the location of the analytical platform. Therefore, it limits the possibilities for an introduction of this methodology in day-to-day clinical practice. However, recent methodological developments have shown feasibility on the remote sampling of exhaled breath in Nalophan® bags prior to measurement using SESI-HRMS. To further explore the range of applications of this method, we conducted a proof-of-concept study to assess the impact of the storage time of exhaled breath in Nalophan® bags at different temperatures (room temperature and dry ice) on the relative intensities of the compounds. In addition, we performed a detailed study of the storage effect of 27 aldehydes related to oxidative stress. After 2 h of storage, the mean of intensity of allm/zsignals relative to the samples analyzed without prior storage remained above 80% at both room temperature and dry ice. For the 27 aldehydes, the mean relative intensity losses were lower than 20% at 24 h of storage, remaining practically stable since the first hour of storage following sample collection. Furthermore, the mean relative intensity of most aldehydes in samples stored at room temperature was higher than those stored in dry ice, which could be related to water vapor condensation issues. These findings indicate that the exhaled breath samples could be preserved for hours with a low percentage of mean relative intensity loss, thereby allowing more flexibility in the logistics of off-line SESI-HRMS studies.

Prediction of systemic free and total valproic acid by off-line analysis of exhaled breath in epileptic children and adolescents.

Therapeutic drug monitoring (TDM) of medications with a narrow therapeutic window is a common clinical practice to minimize toxic effects and maximize clinical outcomes. Routine analyses rely on the quantification of systemic blood concentrations of drugs. Alternative matrices such as exhaled breath are appealing because of their inherent non-invasive nature. This is especially the case for pediatric patients. We have recently showcased the possibility of predicting systemic concentrations of valproic acid (VPA), an anti-seizure medication by real-time breath analysis in two real clinical settings. This approach, however, comes with the limitation of the patients having to physically exhale into the mass spectrometer. This restricts the possibility of sampling from patients not capable or available to exhale into the mass spectrometer located on the hospital premises. In this work, we developed an alternative method to overcome this limitation by collecting the breath samples in customized bags and subsequently analyzing them by secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). A total ofn= 40 patients (mean ± SD, 11.5 ± 3.5 y.o.) diagnosed with epilepsy and taking VPA were included in this study. The patients underwent three measurements: (i) serum concentrations of total and free VPA, (ii) real-time breath analysis and (iii) off-line analysis of exhaled breath collected in bags. The agreement between the real-time and the off-line breath analysis methods was evaluated using Lin's concordance correlation coefficient (CCC). CCC was computed for ten mass spectral predictors of VPA concentrations. Lin's CCC was >0.6 for all VPA-associated features, except for two low-signal intensity isotopic peaks. Finally, free and total serum VPA concentrations were predicted by cross validating the off-line data set. Support vector machine algorithms provided the most accurate predictions with a root mean square error of cross validation of 29.0 ± 7.4 mg l-1and 3.9 ± 1.4 mg l-1for total and free VPA (mean ± SD), respectively. As a secondary analysis, we explored whether exhaled metabolites previously associated with side-effects and response to medication could be rendered by the off-line analysis method. We found that five features associated with side effects showed a CCC > 0.6, whereas none of the drug response-associated peaks reached this cut-off. We conclude that the clinically relevant free fraction of VPA can be predicted by this combination of off-line breath collection with rapid SESI-HRMS analysis. This opens new possibilities for breath based TDM in clinical settings.

Antibiotics in pregnancy influence nasal microbiome and respiratory morbidity in infancy.

Background: The effects of prenatal antibiotic exposure on respiratory morbidity in infancy and the involved mechanisms are still poorly understood. We aimed to examine whether prenatal antibiotic exposure in the third trimester is associated with nasal microbiome and respiratory morbidity in infancy and at school age, and whether this association with respiratory morbidity is mediated by the nasal microbiome. Methods: We performed 16S ribosomal RNA gene sequencing (regions V3-V4) on nasal swabs obtained from 296 healthy term infants from the prospective Basel-Bern birth cohort (BILD) at age 4-6 weeks. Information about antibiotic exposure was derived from birth records and standardised interviews. Respiratory symptoms were assessed by weekly telephone interviews in the first year of life and a clinical visit at age 6 years. Structural equation modelling was used to test direct and indirect associations accounting for known risk factors. Results: α-Diversity indices were lower in infants with antibiotic exposure compared to nonexposed infants (e.g. Shannon index p-value 0.006). Prenatal antibiotic exposure was also associated with a higher risk of any, as well as severe, respiratory symptoms in the first year of life (risk ratio 1.38, 95% CI 1.03-1.84; adjusted p-value (padj)=0.032 and risk ratio 1.75, 95% CI 1.02-2.97; padj=0.041, respectively), but not with wheeze or atopy in childhood. However, we found no indirect mediating effect of nasal microbiome explaining these clinical symptoms. Conclusion: Prenatal antibiotic exposure was associated with lower diversity of nasal microbiome in infancy and, independently of microbiome, with respiratory morbidity in infancy, but not with symptoms later in life.

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.

An interoperability framework for multicentric breath metabolomic studies.

Exhaled breath contains valuable information at the molecular level and offers promising potential for precision medicine. However, few breath tests transition to routine clinical practice, partly because of the missing validation in multicenter trials. Therefore, we developed and applied an interoperability framework for standardized multicenter data acquisition and processing for breath analysis with secondary electrospray ionization-high resolution mass spectrometry. We aimed to determine the technical variability and metabolic coverage. Comparison of multicenter data revealed a technical variability of ∼20% and a core signature of the human exhaled metabolome consisting of ∼850 features, corresponding mainly to amino acid, xenobiotic, and carbohydrate metabolic pathways. In addition, we found high inter-subject variability for certain metabolic classes (e.g., amino acids and fatty acids), whereas other regions such as the TCA cycle were relatively stable across subjects. The interoperability framework and overview of metabolic coverage presented here will pave the way for future large-scale multicenter trials.

Asthma and Wheeze Severity and the Oropharyngeal Microbiota in Children and Adolescents.

Rationale: There is a major unmet need for improving the care of children and adolescents with severe asthma and wheeze. Identifying factors contributing to disease severity may lead to improved diagnostics, biomarkers, or therapies. The airway microbiota may be such a key factor. Objectives: To compare the oropharyngeal airway microbiota of children and adolescents with severe and mild/moderate asthma/wheeze. Methods: Oropharyngeal swab samples from school-age and preschool children in the European U-BIOPRED (Unbiased BIOmarkers in the PREDiction of respiratory disease outcomes) multicenter study of severe asthma, all receiving severity-appropriate treatment, were examined using 16S ribosomal RNA gene sequencing. Bacterial taxa were defined as amplicon sequence variants. Results: We analyzed 241 samples from four cohorts: A) 86 school-age children with severe asthma; B) 39 school-age children with mild/moderate asthma; C) 65 preschool children with severe wheeze; and D) 51 preschool children with mild/moderate wheeze. The most common bacteria were Streptococcus (mean relative abundance, 33.5%), Veillonella (10.3%), Haemophilus (7.0%), Prevotella (5.9%), and Rothia (5.5%). Age group (school-age vs. preschool) was associated with the microbiota in ß-diversity analysis (F = 3.32, P = 0.011) and in a differential abundance analysis (28 significant amplicon sequence variants). Among all children, we found no significant difference in the microbiota between children with severe and mild/moderate asthma/wheeze in univariable ß-diversity analysis (F = 1.99, P = 0.08, N = 241), but a significant difference in a multivariable model (F = 2.66, P = 0.035), including the number of exacerbations in the previous year. Age was also significant when expressed as a microbial maturity score (Spearman Rho, 0.39; P = 4.6 × 10-10); however, this score was not associated with asthma/wheeze severity. Conclusions: There was a modest difference in the oropharyngeal airway microbiota between children with severe and mild/moderate asthma/wheeze across all children but not in individual age groups, and a strong association between the microbiota and age. This suggests the oropharyngeal airway microbiota as an interesting entity in studying asthma severity, but probably without the strength to serve as a biomarker for targeted intervention.

Multisite Dopamine Sensing With Femtomolar Resolution Using a CMOS Enabled Aptasensor Chip.

Many biomarkers including neurotransmitters are found in external body fluids, such as sweat or saliva, but at lower titration levels than they are present in blood. Efficient detection of such biomarkers thus requires, on the one hand, to use techniques offering high sensitivity, and, on the other hand, to use a miniaturized format to carry out diagnostics in a minimally invasive way. Here, we present the hybrid integration of bottom-up silicon-nanowire Schottky-junction FETs (SiNW SJ-FETs) with complementary-metal-oxide-semiconductor (CMOS) readout and amplification electronics to establish a robust biosensing platform with 32 × 32 aptasensor measurement sites at a 100 µm pitch. The applied hetero-junctions yield a selective biomolecular detection down to femtomolar concentrations. Selective and multi-site detection of dopamine is demonstrated at an outstanding sensitivity of ∼1 V/fM. The integrated platform offers great potential for detecting biomarkers at high dilution levels and could be applied, for example, to diagnosing neurodegenerative diseases or monitoring therapy progress based on patient samples, such as tear liquid, saliva, or eccrine sweat.

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.

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.

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.