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

Background: Asthma is a heterogeneous disease with differences in onset, severity, and inflammation. Bronchial epithelial cells (BECs) contribute to asthma pathophysiology.Objective: We determined whether transcriptomes of BECs reflect heterogeneity in inflammation and severity in asthma, and whether this was affected in BECs from patients with severe asthma after their regeneration by bronchial thermoplasty.Methods: RNA sequencing was performed on BECs obtained by bronchoscopy from healthy controls (n = 16), patients with mild asthma (n = 17), patients with moderate asthma (n = 5), and patients with severe asthma (n = 17), as well as on BECs from treated and untreated airways of the latter (also 6 months after bronchial thermoplasty) (n = 23). Lipidome and metabolome analyses were performed on cultured BECs from healthy controls (n = 7); patients with severe asthma (n = 9); and, for comparison, patients with chronic obstructive pulmonary disease (n = 7).Results: Transcriptome analysis of BECs from patients showed a reduced expression of oxidative phosphorylation (OXPHOS) genes, most profoundly in patients with severe asthma but less profoundly and more heterogeneously in patients with mild asthma. Genes related to fatty acid metabolism were significantly upregulated in asthma. Lipidomics revealed enhanced levels of lipid species (phosphatidylcholines, lysophosphatidylcholines. and bis(monoacylglycerol)phosphate), whereas levels of OXPHOS metabolites were reduced in BECs from patients with severe asthma. BECs from patients with mild asthma characterized by hyperresponsive production of mediators implicated in neutrophilic inflammation had decreased expression of OXPHOS genes compared with that in BECs from patients with mild asthma with normoresponsive production. BECs obtained after thermoplasty had significantly increased expression of OXPHOS genes and decreased expression of fatty acid metabolism genes compared with BECs obtained from untreated airways.Conclusion: BECs in patients with asthma are metabolically different from those in healthy individuals. These differences are linked with inflammation and asthma severity, and they can be reversed by bronchial thermoplasty.

Objectives Exhaled breath analysis by electronic nose (eNose) has shown to be a potential predictive biomarker before start of anti-PD-1 therapy in patients with non-small cell lung carcinoma (NSCLC). We hypothesized that the eNose could also be used as an early monitoring tool to identify responders more accurately at early stage of treatment when compared to baseline. In this proof-of-concept study we aimed to definitely discriminate responders from non-responders after six weeks of treatment. Materials and Methods This was a prospective observational study in patients with advanced NSCLC eligible for anti-PD-1 treatment. The efficacy of treatment was assessed by the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 at 3-month follow-up. We analyzed SpiroNose exhaled breath data of 94 patients (training cohort n = 62, validation cohort n = 32). Data analysis involved signal processing and statistics based on Independent Samples T-tests and Linear Discriminant Analysis (LDA) followed by Receiver Operating Characteristic (ROC) analysis. Results In the training cohort, a specificity of 73% was obtained at a 100% sensitivity level to identify objective responders. The Area Under the Curve (AUC) was 0.95 (CI: 0.89–1.00). In the validation cohort, these results were confirmed with an AUC of 0.97 (CI: 0.91–1.00). Conclusion Exhaled breath analysis by eNose early during treatment allows for a highly accurate, non-invasive and low-cost identification of advanced NSCLC patients who benefit from anti-PD-1 therapy.

Background: Although estimates of suboptimal adherence to oral corticosteroids in asthma range from 30% to 50%, no ideal method for measurement exists; the impact of poor adherence in severe asthma is likely to be particularly high. Research Questions: What is the prevalence of suboptimal adherence detected by self-reporting and direct measures? Is suboptimal adherence associated with disease activity? Study Design and Methods: Data were included from individuals with severe asthma taking part in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study and prescribed daily oral corticosteroids. Participants completed the Medication Adherence Report Scale, a five-item questionnaire used to grade adherence on a scale from 1 to 5, and provided a urine sample for analysis of prednisolone and metabolites by liquid chromatography-mass spectrometry. Results: Data from 166 participants were included in this study: mean (SD) age, 54.2 (± 11.9) years; FEV 1, 65.1% (± 20.5%) predicted; female, 58%; 37% completing the Medication Adherence Report Scale reported suboptimal adherence; and 43% with urinary corticosteroid data did not have detectable prednisolone or metabolites in their urine. Good adherence by both methods was detected in 49 of the 142 (35%) of participants in whom both methods were performed; adherence detection did not match between methods in 53%. Self-reported high adherers had better asthma control and quality of life, whereas directly measured high adherers had lower blood eosinophil levels. Interpretation: Low adherence is a common problem in severe asthma, whether measured directly or self-reported. We report poor agreement between the two methods, suggesting some disassociation between self-assessment of medication adherence and regular oral corticosteroid use, which suggests that each approach may provide complementary information in clinical practice.

Background Patients with severe asthma may have a greater risk of dying from COVID-19 disease. Angiotensin converting enzyme-2 (ACE2) and the enzyme proteases, transmembrane protease serine 2 (TMPRSS2) and FURIN, are needed for viral attachment and invasion into host cells. Methods We examined microarray mRNA expression of ACE2, TMPRSS2 and FURIN in sputum, bronchial brushing and bronchial biopsies of the European U-BIOPRED cohort. Clinical parameters and molecular phenotypes, including asthma severity, sputum inflammatory cells, lung functions, oral corticosteroid (OCS) use, and transcriptomic-associated clusters, were examined in relation to gene expression levels. Results ACE2 levels were significantly increased in sputum of severe asthma compared to mild-moderate asthma. In multivariate analyses, sputum ACE2 levels were positively associated with OCS use and male gender. Sputum FURIN levels were significantly related to neutrophils (%) and the presence of severe asthma. In bronchial brushing samples, TMPRSS2 levels were positively associated with male gender and body mass index, whereas FURIN levels with male gender and blood neutrophils. In bronchial biopsies, TMPRSS2 levels were positively related to blood neutrophils. The neutrophilic molecular phenotype characterised by high inflammasome activation expressed significantly higher FURIN levels in sputum than the eosinophilic Type 2-high or the pauci-granulocytic oxidative phosphorylation phenotypes. Conclusion Levels of ACE2 and FURIN may differ by clinical or molecular phenotypes of asthma. Sputum FURIN expression levels were strongly associated with neutrophilic inflammation and with inflammasome activation. This might indicate the potential for a greater morbidity and mortality outcome from SARS-CoV-2 infection in neutrophilic severe asthma.

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

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Most patients with chronic obstructive pulmonary disease (COPD) experience exacerbations [1]. >80% of the exacerbations are treated ambulatorily. Treatment consists of inhaled bronchodilator therapy and oral corticosteroids, whereas the contribution of antibiotics is less clear. A meta-analysis [2] recently reported less treatment failure within 4 weeks in outpatient exacerbations treated with antibiotics: 21.2% in the group treated with antibiotics versus 29.2% in the placebo group. This means that 12–13 patients must be treated with antibiotics to prevent one treatment failure (number needed to treat: 12.5)., No clinical characteristics, particularly not sputum characteristics, can guide antibiotic prescription in patients with mild to severe COPD exacerbations https://bit.ly/3e1JV8o

Background Loss of asthma control and asthma exacerbations are associated with increased sputum eosinophil counts. However, whether eosinophils, or the also present neutrophils, actively contribute to the accompanying inflammation has not been extensively investigated. Methods Twenty-three patients with mild to moderate asthma were included in a standardized prospective inhaled corticosteroid (ICS) withdrawal study; 22 of the patients experienced loss of asthma control. The study assessed various immune, inflammatory, and oxidative stress parameters, as well as markers of eosinophil and neutrophil activity, in exhaled breath condensate, plasma, and sputum collected at three phases (baseline, during loss of control, and following recovery). Results Loss of asthma control was characterized by increased sputum eosinophils, whereas no differences were detected between the three phases for most inflammatory and oxidative stress responses. There were also no differences detected for markers of activated eosinophils (eosinophil cationic protein and bromotyrosine) and neutrophils (myeloperoxidase and chlorotyrosine). However, free eosinophilic granules and citrullinated histone H3, suggestive of eosinophil cytolysis and potentially eosinophil extracellular trap formation, were enhanced. Baseline blood eosinophils and changes in asymmetric dimethylarginine (an inhibitor of nitric oxide synthase) in plasma were found to correlate with the decrease in FEV1 percent predicted upon ICS withdrawal (both, rs = 0.46; P = .03). Conclusions The clinical effect in mild to moderate asthma upon interruption of ICS therapy is not related to the classic inflammatory activation of eosinophils and neutrophils. It may, however, reflect another pathway underlying the onset of loss of disease control and asthma exacerbations. Trial Registry The Netherlands Trial Register; No.: NTR3316; URL: trialregister.nl/trial/3172.

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, T H2, and T H17/T H22 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 H22/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.

Rationale: Mast cells (MCs) play a role in inflammation and both innate and adaptive immunity, but their involvement in severe asthma (SA) remains undefined. Objectives: We investigated the phenotypic characteristics of the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) asthma cohort by applying published MC activation signatures to the sputum cell transcriptome. Methods: Eighty-four participants with SA, 20 with mild/moderate asthma (MMA), and 16 healthy participants without asthma were studied. We calculated enrichment scores (ESs) for nine MC activation signatures by asthma severity, sputum granulocyte status, and three previously defined sputum molecular phenotypes or transcriptome-associated clusters (TACs) 1, 2, and 3 using gene set variation analysis. Measurements and Main Results: MC signatures except unstimulated, repeated FceR1-stimulated and IFN-g–stimulated signatures were enriched in SA. A FceR1-IgE–stimulated and a single-cell signature from asthmatic bronchial biopsies were highly enriched in eosinophilic asthma and in the TAC1 molecular phenotype. Subjects with a high ES for these signatures had elevated sputum amounts of similar genes and pathways. IL-33– and LPS-stimulated MC signatures had greater ES in neutrophilic and mixed granulocytic asthma and in the TAC2 molecular phenotype. These subjects exhibited neutrophil, NF-kB (nuclear factor-kB), and IL-1b/TNF-a (tumor necrosis factor-a) pathway activation. The IFN-g–stimulated signature had the greatest ES in TAC2 and TAC3 that was associated with responses to viral infection. Similar results were obtained in an independent ADEPT (Airway Disease Endotyping for Personalized Therapeutics) asthma cohort. Conclusions: Gene signatures of MC activation allow the detection of SA phenotypes and indicate that MCs can be induced to take on distinct transcriptional phenotypes associated with specific clinical phenotypes. IL-33–stimulated MC signature was associated with severe neutrophilic asthma, whereas IgE-activated MC was associated with an eosinophilic phenotype.

IntroductionAsthma is a heterogeneous disease with poorly defined phenotypes. Patients with severe asthma often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication.MethodsBaseline urine was collected prospectively from healthy participants (n=100), patients with mild-to-moderate asthma (n=87) and patients with severe asthma (n=418) in the cross-sectional U-BIOPRED cohort; 12–18-month longitudinal samples were collected from patients with severe asthma (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods.ResultsA total of 90 metabolites were identified, with 40 significantly altered (p−20), OCS-treated asthmatic patients differed significantly from non-treated patients (p=9.5×10−4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings.ConclusionsThis is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the need to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma.

Patients with severe asthma may have a greater risk of dying from COVID-19 disease. Angiotensin converting enzyme-2 (ACE2) and the enzyme proteases, transmembrane protease serine 2 (TMPRSS2) and FURIN, are needed for viral attachment and invasion into host cells.We examined microarray mRNA expression of ACE2, TMPRSS2 and FURIN in sputum, bronchial brushing and bronchial biopsies of the European U-BIOPRED cohort. Clinical parameters and molecular phenotypes, including asthma severity, sputum inflammatory cells, lung functions, oral corticosteroid (OCS) use, and transcriptomic-associated clusters, were examined in relation to gene expression levels.ACE2 levels were significantly increased in sputum of severe asthma compared to mild-moderate asthma. In multivariate analyses, sputum ACE2 levels were positively associated with OCS use and male gender. Sputum FURIN levels were significantly related to neutrophils (%) and the presence of severe asthma. In bronchial brushing samples, TMPRSS2 levels were positively associated with male gender and body mass index, whereas FURIN levels with male gender and blood neutrophils. In bronchial biopsies, TMPRSS2 levels were positively related to blood neutrophils. The neutrophilic molecular phenotype characterised by high inflammasome activation expressed significantly higher FURIN levels in sputum than the eosinophilic Type 2-high or the pauci-granulocytic oxidative phosphorylation phenotypes.Levels of ACE2 and FURIN may differ by clinical or molecular phenotypes of asthma. Sputum FURIN expression levels were strongly associated with neutrophilic inflammation and with inflammasome activation. This might indicate the potential for a greater morbidity and mortality outcome from SARS-CoV-2 infection in neutrophilic severe asthma.

Defective translocation of the translational repressor TIAR (T-cell internal antigen receptor) in bronchial epithelial cells (BECs) from asthma patients underlies epithelial hyperresponsiveness, reflected by an exaggerated production of a select panel of inflammatory cytokines such as CXCL-8, interleukin (IL)-6, granulocyte colony-stimulating factor, CXCL-10, upon exposure to tumour necrosis factor (TNF) and IL-17A. With this study we aimed to clarify whether epithelial hyperresponsiveness is a consistent finding, is changed uponBECs were obtained from asthma patients (n=18) and healthy individuals (n=11), 1 day before and 6 days post-RV-A16 exposure. BECs were cultured and stimulated with TNF and IL-17A and inflammatory mediators were analysed. The bronchoalveolar lavage fluid (BALF) was obtained in parallel with BECs to correlate differential cell counts and inflammatory mediators with epithelial hyperresponsiveness.Epithelial hyperresponsiveness was confirmed in sequential samples and even increased in BECs from asthma patients after RV-A16 exposure, but not in BECs from healthy individuals. Endothelin-1 tended to increase in BECs from asthma patients collected after RV-A16 exposure, but not in BECs from healthy individuals.Epithelial hyperresponsiveness is an intrinsic defect in BECs from asthma patients, which increases upon viral exposure, but not in BECs from healthy individuals. This epithelial hyperresponsiveness also applies to the bronchoconstrictor endothelin-1, which could be involved in airway obstruction.

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

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

Serum pregnancy-associated plasma protein A (PAPPA) as a predictor of eosinophilic Type-2 high asthmaTo the Editor,Pregnancy-associated plasma protein A (PAPPA), a metalloproteinase that cleaves insulin-like growth factor (IGF)-binding proteins (IGFBPs) to increase IGF availability, is expressed systemically in pregnant women but also in other tissues (1). Higher serum PAPPA levels are reported in patients with newly-diagnosed asthma (1) and allergic rhinitis compared to healthy controls and are decreased following omalizumab treatment (2). We determined whether PAPPA could represent a novel biomarker for Type-2 (T2) asthma by exploring the relationship between asthma severity and phenotypes of severe asthma and PAPPA gene and protein expression (3).We recruited 288 severe non-smoking asthma (NSA), 102 smokers and ex-smokers with severe asthma (SSA), 86 mild/moderate non-smoking asthmatics (MMA) and 95 healthy non-smoking controls (HC) from the U-BIOPRED cohort (NCT01976767) (4) (Table S1 ). Transcriptomic and proteomic profiling of blood and sputum samples and specific serum periostin ELISA were performed (3). Gene set variation analysis (GSVA) was used to calculate the enrichment score (ES) of 34 genes that were upregulated following in vitro stimulation of primary human bronchial epithelial cells with IL-13 (T2_IL-13_IVS) (3). Eosinophilic inflammation was defined by sputum eosinophilia >1.49% (3). Local Ethics Committees of the recruiting centres approved the study and all participants gave written informed consent.Sputum cell PAPPA mRNA was elevated in NSA compared to SSA, MMA and HC subjects particularly in granulocytic asthmatics and in the transcriptomic-associated cluster (TAC)1; an eosinophilic cluster (5) (Figure 1A-C ). This was more pronounced with sputum PAPPA protein analysis according to asthma severity, in eosinophilic and mixed granulocytic asthmatics and in T2-high asthmatics identified by the T2_IL-13_IVS signature (Figure 1D-F ).PAPPA mRNA expression in blood cells was similar across asthma severities, blood granulocytes and molecular phenotypes (Supplementary Figure 1A-C ). However, serum PAPPA protein levels supported the discrimination seen in sputum with significant elevation seen in SA compared to HC, in eosinophilic and mixed granulocytic asthma and in T2-high asthma (SupplementaryFigure 1D-F ).Sputum eosinophil percentages were significantly correlated with sputum (r=0.88, p=10-6) and serum (r=0.41, p=10-6) PAPPA protein levels. Overall, sputum PAPPA protein gave a greater distinction between asthma severity, granulocyte composition and T2-high asthma than with serum although fewer samples were available.These results were validated in sputum from the Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study (6) (Supplementary Figure S2 ). Elevated PAPPA protein in the serum and sputum of severe asthmatics and in eosinophilic compared to non- eosinophilic subjects was seen (SupplementaryFigure S2A-D ). In addition, sputum PAPPA mRNA levels were also elevated in eosinophilic versus non-eosinophilic asthma in the ADEPT cohort (Supplementary Figure S2E ).The ES score of the T2_IL-13_IVS gene signature in bronchial brushings was significantly, but weakly, correlated with blood eosinophil counts (r=0.329, p=10-6), serum PAPPA (r=0.356, p=10-6), but not with serum periostin levels (r=0.07, p-value=0.48). In contrast, the T2 IL-13 IVS ES score was strongly correlated with sputum PAPPA levels (r=0.72, p=10-3). Sputum PAPPA protein levels also significantly correlated with markers of remodelling such as MMP10 (r=0.646, p

Inflammation, structural, and functional abnormalities within the airways are key features of asthma. Although these processes are well documented, their expression varies across the heterogeneous spectrum of asthma. Type 2 inflammatory responses are characterized by increased levels of eosinophils, FeNO, and type 2 cytokines in blood and/or airways. Presently, type 2 asthma is the best-defined endotype, typically found in patients with allergic asthma, but surprisingly also in nonallergic patients with (severe) asthma. The etiology of asthma with non-type 2 inflammation is less clear. During the past decade, targeted therapies, including biologicals and small molecules, have been increasingly integrated into treatment strategies of severe asthma. These treatments block specific inflammatory pathways or single mediators. Single or composite biomarkers help to identify patients who will benefit from these treatments. So far, only a few inflammatory biomarkers have been validated for clinical application. The European Academy of Allergy & Clinical Immunology Task Force on Biomarkers in Asthma was initiated to review different biomarker sampling methods and to investigate clinical applicability of new and existing inflammatory biomarkers (point-of-care) to support diagnosis, targeted treatment, and monitoring of severe asthma. Subsequently, we discuss existing and novel targeted therapies for asthma as well as applicable biomarkers.

Background Whether the clinical or pathophysiologic significance of the “treatable trait” high blood eosinophil count in COPD is the same as for asthma remains controversial. We sought to determine the relationship between the blood eosinophil count, clinical characteristics and gene expression from bronchial brushings in COPD and asthma. Methods Subjects were recruited into a COPD (emphysema versus airway disease [EvA]) or asthma cohort (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes, U‐BIOPRED). We determined gene expression using RNAseq in EvA (n = 283) and Affymetrix microarrays in U‐BIOPRED (n = 85). We ran linear regression analysis of the bronchial brushings transcriptional signal versus blood eosinophil counts as well as differential expression using a blood eosinophil > 200 cells/μL as a cut‐off. The false discovery rate was controlled at 1% (with continuous values) and 5% (with dichotomized values). Results There were no differences in age, gender, lung function, exercise capacity and quantitative computed tomography between eosinophilic versus noneosinophilic COPD cases. Total serum IgE was increased in eosinophilic asthma and COPD. In EvA, there were 12 genes with a statistically significant positive association with the linear blood eosinophil count, whereas in U‐BIOPRED, 1197 genes showed significant associations (266 positive and 931 negative). The transcriptome showed little overlap between genes and pathways associated with blood eosinophil counts in asthma versus COPD. Only CST1 was common to eosinophilic asthma and COPD and was replicated in independent cohorts. Conclusion Despite shared “treatable traits” between asthma and COPD, the molecular mechanisms underlying these clinical entities are predominately different., In a chronic obstructive pulmonary disease (COPD) cohort (EvA, n = 283), 12 genes, whereas in asthma cohort (UBIOPRED, n = 85), 1197 genes in bronchial epithelial brushes were correlated with a blood eosinophil count. The gene CST1 was common to eosinophilic asthma and COPD and was replicated in independent cohorts. Despite shared “treatable traits” between asthma and COPD, the molecular mechanisms underlying these clinical entities are predominately different.