Search

Rationale: Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker signature to predict sputum eosinophilia in asthma. Methods: VOCs emitted into the space above sputum samples (headspace) from patients with severe asthma ( n  = 36) were collected onto sorbent tubes and analyzed using thermal desorption gas chromatography-mass spectrometry (GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ⩾ 3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: 1 ) patients with acute asthma according to blood eosinophilia ⩾0.3 × 10 9 cells/L or sputum eosinophilia of ⩾3% in the UK EMBER (East Midlands Breathomics Pathology Node) consortium ( n  = 65) and 2 ) U-BIOPRED-IMI (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes Innovative Medicines Initiative) consortium ( n  = 42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analyzed by GC-MS (GC × GC-MS for EMBER or GC-MS for U-BIOPRED). Measurements and Main Results: The in vitro headspace identified 19 VOCs associated with sputum eosinophilia, and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ⩾3% in headspace (area under the receiver operating characteristic curve [AUROC] 0.90; 95% confidence interval [CI], 0.80-0.99; P  < 0.0001), correlated inversely with sputum eosinophil percentage ( r s  < 0.0001), and outperformed fractional exhaled nitric oxide (AUROC 0.61; 95% CI, 0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89 (0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90 (0.75-1.0) in U-BIOPRED, again outperforming fractional exhaled nitric oxide in U-BIOPRED (0.62 [0.33-0.90]). P  < 0.0001), and outperformed fractional exhaled nitric oxide (AUROC 0.61; 95% CI, 0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89 (0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90 (0.75-1.0) in U-BIOPRED, again outperforming fractional exhaled nitric oxide in U-BIOPRED (0.62 [0.33-0.90]). Conclusions: We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point-of-care clinical sensors.

Introduction: Difficult-to-treat asthma is defined as asthma that is uncontrolled despite high-level treatment or requires such treatment to maintain good control and reduce exacerbations. Breathing pattern disorders (BPD) have been reported as a comorbidity in ~ 24-42% % of patients with difficult-to-treat asthma. This narrative review will assess the association, impact, and management of BPD in difficult-to-treat asthma., Areas Covered: We outline current understandings of the nature of difficult-to-treat asthma and BPD. We then review the impact of BPD on difficult-to-treat asthma and Multidisciplinary Team (MDT) approaches to assessing and managing BPD in this patient group. A comprehensive literature search was performed by an asthma specialist MDT including physiotherapists, psychologists, and physicians to create a holistic perspective on this subject., Expert Opinion: BPD exerts significant negative impacts across multiple domains in patients with difficult-to treat asthma. There is a need for further observational, interventional, qualitative and quantitative research to develop better diagnosis, treatment, and awareness of the impacts of BPD including health economic analysis. Studies should develop multimodal approaches that better treat both BPD and associated comorbidities within the multimorbidity framework of difficult-to-treat asthma. Recognizing and addressing BPD should be key elements in future difficult-to-treat asthma management guidelines and clinical practice.

Background: Severe asthma (SA) encompasses several clinical phenotypes with a heterogeneous airway microbiome. We determined the phenotypes associated with a low α-diversity microbiome., Methods: Metagenomic sequencing was performed on sputum samples from SA participants. A threshold of 2 standard deviations below the mean of α-diversity of mild-moderate asthma and healthy control subjects was used to define those with an abnormal abundance threshold as relative dominant species (RDS)., Findings: Fifty-one out of 97 SA samples were classified as RDSs with Haemophilus influenzae RDS being most common (n = 16), followed by Actinobacillus unclassified (n = 10), Veillonella unclassified (n = 9), Haemophilus aegyptius (n = 9), Streptococcus pseudopneumoniae (n = 7), Propionibacterium acnes (n = 5), Moraxella catarrhalis (n = 5) and Tropheryma whipplei (n = 5). Haemophilus influenzae RDS had the highest duration of disease, more exacerbations in previous year and greatest number on daily oral corticosteroids. Hierarchical clustering of RDSs revealed a C2 cluster (n = 9) of highest relative abundance of exclusively Haemophilus influenzae RDSs with longer duration of disease and higher sputum neutrophil counts associated with enrichment pathways of MAPK, NF-κB, TNF, mTOR and necroptosis, compared to the only other cluster, C1, which consisted of 7 Haemophilus influenzae RDSs out of 42. Sputum transcriptomics of C2 cluster compared to C1 RDSs revealed higher expression of neutrophil extracellular trap pathway (NETosis), IL6-transignalling signature and neutrophil activation., Conclusion: We describe a Haemophilus influenzae cluster of the highest relative abundance associated with neutrophilic inflammation and NETosis indicating a host response to the bacteria. This phenotype of severe asthma may respond to specific antibiotics., (© 2024 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.)

Background: Clustering approaches using single omics platforms are increasingly used to characterise molecular phenotypes of eosinophilic and neutrophilic asthma. Effective integration of multi-omics platforms should lead towards greater refinement of asthma endotypes across molecular dimensions and indicate key targets for intervention or biomarker development., Objectives: To determine whether multi-omics integration of sputum leads to improved granularity of the molecular classification of severe asthma., Methods: We analyzed six -omics data blocks-microarray transcriptomics, gene set variation analysis of microarray transcriptomics, SomaSCAN proteomics assay, shotgun proteomics, 16S microbiome sequencing, and shotgun metagenomic sequencing-from induced sputum samples of 57 severe asthma patients, 15 mild-moderate asthma patients, and 13 healthy volunteers in the U-BIOPRED European cohort. We used Monti consensus clustering algorithm for aggregation of clustering results and Similarity Network Fusion to integrate the 6 multi-omics datasets of the 72 asthmatics., Results: Five stable omics-associated clusters were identified (OACs). OAC1 had the best lung function with the least number of severe asthmatics with sputum paucigranulocytic inflammation. OAC5 also had fewer severe asthma patients but the highest incidence of atopy and allergic rhinitis, with paucigranulocytic inflammation. OAC3 comprised only severe asthmatics with the highest sputum eosinophilia. OAC2 had the highest sputum neutrophilia followed by OAC4 with both clusters consisting of mostly severe asthma but with more ex/current smokers in OAC4. Compared to OAC4, there was higher incidence of nasal polyps, allergic rhinitis, and eczema in OAC2. OAC2 had microbial dysbiosis with abundant Moraxella catarrhalis and Haemophilus influenzae. OAC4 was associated with pathways linked to IL-22 cytokine activation, with the prediction of therapeutic response to anti-IL22 antibody therapy., Conclusion: Multi-omics analysis of sputum in asthma has defined with greater granularity the asthma endotypes linked to neutrophilic and eosinophilic inflammation. Modelling diverse types of high-dimensional interactions will contribute to a more comprehensive understanding of complex endotypes., Key Points: Unsupervised clustering on sputum multi-omics of asthma subjects identified 3 out of 5 clusters with predominantly severe asthma. One severe asthma cluster was linked to type 2 inflammation and sputum eosinophilia while the other 2 clusters to sputum neutrophilia. One severe neutrophilic asthma cluster was linked to Moraxella catarrhalis and to a lesser extent Haemophilus influenzae while the second cluster to activation of IL-22., (© 2024 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.)

Background: Breathing pattern disorder (BPD) reflects altered biomechanical patterns of breathing that drive breathing difficulty and commonly accompanies difficult-to-treat asthma. Diagnosis of BPD has no gold standard, but Nijmegen Questionnaire (NQ) >23 is commonly used., Objectives: We sought to advance clinical characterization of BPD and better understand the clinical utility of NQ in difficult asthma in patients from the Wessex AsThma CoHort of difficult asthma (WATCH) study., Methods: Associations between demographic and clinical factors in difficult asthma and BPD, ascertained by clinical diagnosis (yes/no, n = 476), by NQ scores (≤23: normal [no suggestion of BPD] and >23: abnormal [suggested BPD], n = 372), as well as the continuous raw NQ scores were assessed in univariate models to identify significant risk factors associated with the 3 BPD outcomes. For the clinician-diagnosed and NQ-based BPD, associations of continuous factors were assessed using the independent samples t test or the Mann-Whitney U test as appropriate for the data distribution or by the Spearman correlation test. Dichotomous associations were evaluated using χ 2 tests. Multivariable logistic (dichotomous outcomes) and linear regression models (continuous outcomes) were developed to identify predictive factors associated with clinician-diagnosed and NQ-based BPD, dichotomous and continuous. Patients with data on NQ scores were grouped into NQ quartiles (low, moderate, high, and very high). The patterns of association of the quartiles with 4 health-related questionnaire outcomes were assessed using linear regression analyses., Results: Multivariable regression identified that clinically diagnosed BPD was associated with female sex (odds ratio [OR]: 1.85; 95% confidence interval [CI]: 1.07, 3.20), comorbidities (rhinitis [OR: 2.46; 95% CI: 1.45, 4.17], gastroesophageal reflux disease [GORD] [OR: 2.77; 95% CI: 1.58, 4.84], inducible laryngeal obstruction [OR: 4.37; 95% CI: 2.01, 9.50], and any psychological comorbidity [OR: 1.86; 95% CI: 1.13, 3.07]), and health care usage (exacerbations [OR: 1.07; 95% CI: 1.003, 1.14] and previous intensive care unit (ICU) admissions [OR: 2.03; 95% CI: 1.18, 3.47]). Abnormal NQ-based BPD diagnosis was associated with history of eczema (OR: 1.83; 95% CI: 1.07, 3.14), GORD (OR: 1.94; 95% CI: 1.15, 3.27), or any psychological comorbidity (OR: 4.29; 95% CI: 2.64, 6.95) at multivariable regression. Differences between clinical and NQ-based BPD traits were also found with 42% discordance in BPD state between these definitions. Multivariable linear regression analysis with NQ as a continuous outcome showed positive association with worse asthma outcomes (admission to ICU, P = .037), different phenotypic traits (female sex, P = .001; ever smoker, P = .025), and greater multimorbidity (GORD, P = .002; sleep apnea, P = .04; and any psychological comorbidity, P < .0001)., Conclusion: BPD is associated with worse health outcomes and negative health impacts in difficult asthma within a multimorbidity disease model. It therefore merits better recognition and prompt treatment. Clinical diagnosis and NQ offer different perspectives on BPD, so this goal may be best addressed by considering clinical features alongside the magnitude of NQ., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Eosinophilic and neutrophilic asthma defined by high levels of blood and sputum eosinophils and neutrophils exemplifies the inflammatory heterogeneity of asthma, particularly severe asthma. We analysed the serum and sputum proteome to identify biomarkers jointly associated with these different phenotypes., Methods: Proteomic profiles (N = 1129 proteins) were assayed in sputum (n = 182) and serum (n = 574) from two cohorts (U-BIOPRED and ADEPT) of mild-moderate and severe asthma by SOMAscan. Using least absolute shrinkage and selection operator (LASSO)-penalised logistic regression in a stability selection framework, we sought sparse sets of proteins associated with either eosinophilic or neutrophilic asthma with and without adjustment for established clinical factors including oral corticosteroid use and forced expiratory volume., Findings: We identified 13 serum proteins associated with eosinophilic asthma, including 7 (PAPP-A, TARC/CCL17, ALT/GPT, IgE, CCL28, CO8A1, and IL5-Rα) that were stably selected while adjusting for clinical factors yielding an AUC of 0.84 (95% CI: 0.83-0.84) compared to 0.62 (95% CI: 0.61-0.63) for clinical factors only. Sputum protein analysis selected only PAPP-A (AUC = 0.81 [95% CI: 0.80-0.81]). 12 serum proteins were associated with neutrophilic asthma, of which 5 (MMP-9, EDAR, GIIE/PLA2G2E, IL-1-R4/IL1RL1, and Elafin) complemented clinical factors increasing the AUC from 0.63 (95% CI: 0.58-0.67) for the model with clinical factors only to 0.89 (95% CI: 0.89-0.90). Our model did not select any sputum proteins associated with neutrophilic status., Interpretation: Targeted serum proteomic profiles are a non-invasive and scalable approach for subtyping of neutrophilic and eosinophilic asthma and for future functional understanding of these phenotypes., Funding: U-BIOPRED has received funding from the Innovative Medicines Initiative (IMI) Joint Undertaking under grant agreement no. 115010, resources of which are composed of financial contributions from the European Union's Seventh Framework Programme (FP7/2007-2013), and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in-kind contributions (www.imi.europa.eu). ADEPT was funded by Johnson & Johnson/Janssen pharmaceutical Company., Competing Interests: Declaration of interests Prof M Chadeau-Hyam holds shares in the O-SMOSE company; consulting activities conducted by the company are independent of the present work. Prof Adcock reports consulting fees from GSK, Sanofi, Chiesi and Kinaset; speaker fees from AZ, Sanofi, Eurodrug and Sunovion; travel support from AZ; grants from GSK, MRC, EPSRC, Sanofi and NIEHS, which were independent of the present work. Dr. Dahlén reports consulting fees from Affiboby, AZ, Cayman Chemicals, GSK and Regeneron, and speaker fees from AZ, GSK and Sanofi, outside the submitted work. Prof Chung has received speaker fees from Novartis, AZ and Merck; honoraria for participating in Advisory Board meetings of GSK, Novartis, Roche, Merck, Trevi, Rickett-Beckinson, Nocion and Shionogi; and has received grants from MRC, EPSRC and GSK. Prof Chung is a member of the Scientific Advisory Board of the Clean Breathing Institute supported by Haleon. Dr Djukanovic declares consulting fees from Synairgen plc and lecture fees from GSK, ZenasBio and Celltrion. He holds shares from Synairgen and is Chair of the European Respiratory Society's Clinical collaboration on severe asthma (SHARP). The other authors have no conflict of interest to disclose., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Competing Interests: Declaration of competing interest ZD: received consultancy fees/lecture fees/fees for attending advisory boards from ALK, Antabio, Foresee Pharmaceuticals, GlaxoSmithKline, Hippo-Dx, QPS-Netherlands, Sanofi-Genzyme; she served as Director Respiratory & Allergy at QPS-NL and this CRO received research grants for clinical trials from HAL Allergy, Janssen Research & Development LLC, Patara pharma, Cerbios, Merck Sharp & Dohme, Novartis, Foresee Pharmaceuticals and ERA4TB (IMI-project). MJ: ALK, Stallergenes-Greer, Chiesi, GSK, Pfizer, Novartis, AstraZeneca and SANOFI. NH: Received honoraria for serving as advisor or consultant for GSK, AstraZeneca, Sanofi, Regeneron, Amgen, Genentech, Novartis and Teva. His institution received research grant support of his behalf from GSK, Genentech, Sanofi, Teva, Novartis, and AstraZeneca. LH: Has received grant funding, participated in advisory boards and given lectures at meetings supported by Amgen, AstraZeneca, Boehringer Ingelheim, Chiesi, Circassia, Hoffmann la Roche, GlaxoSmithKline, Novartis, Theravance, Evelo Biosciences, Sanofi, and Teva; he has received grants from MedImmune, Novartis UK, Roche/ Genentech Inc, and Glaxo Smith Kline, Amgen, Genentech/Hoffman la Roche, Astra Zeneca, MedImmune, Glaxo Smith Kline, Aerocrine and Vitalograph; he has received sponsorship for attending international scientific meetings from AstraZeneca, Boehringer Ingelheim, Chiesi, GSK and Napp Pharmaceuticals; he has also taken part in asthma clinical trials sponsored by AstraZeneca, Boehringer Ingelheim, Hoffmann la Roche, and GlaxoSmithKline for which his institution received remuneration; he is the Academic Lead for the Medical Research Council Stratified Medicine UK Consortium in Severe Asthma which involves industrial partnerships with a number of pharmaceutical companies including Amgen, AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Hoffmann la Roche, and Janssen. RD: Declares consulting fees from Synairgen, Sanofi and Galapagos, lecture fees from GSK, AZ and Airways Vista and he holds shares from Synairgen. DR: No COIs related to this work. SQ: ALK, Allergy Therapeutics, AstraZeneca, Chiesi, GSK, Leti, Mundipharma, Novartis, Sanofi-Genzyme, Teva. VB: Has worked as advisor, supervisor, investigator of pharmaceutical studies, unrestricted grants, and others with: AstraZeneca, GSK, MSD & Shering Plough, ALK-Abello; Chiesi,Novartis, Pharmaxis, Pfizer, Boehringer Ingelheim, Aerocrine, Teva, Sanofi, Birk NPC as. MG: No COIs related to this work. IP: In the last 5 years IDP has received speaker’s honoraria for speaking at sponsored meetings from Astra Zeneca, Boehringer Ingelheim, Aerocrine, Almirall, Novartis, Teva, Chiesi, Sanofi/Regeneron, Menarini and GSK and payments for organising educational events from AZ, GSK, Sanofi/Regeneron and Teva. He has received honoraria for attending advisory panels with Genentech, Sanofi/ Regeneron, Astra Zeneca, Boehringer Ingelheim, GSK, Novartis, Teva, Merck, Circassia, Chiesi and Knopp and payments to support FDA approval meetings from GSK. He has received sponsorship to attend international scientific meetings from Boehringer Ingelheim, GSK, AstraZeneca, Teva and Chiesi. He has received a grant from Chiesi to support a phase 2 clinical trial in Oxford. DAA: Has received honoraria as grants/contracts from Sociedad Española de Alergología e Inmunología Clínica (SEAIC), as consulting fees from ALK-Abelló, AstraZeneca, Chiesi and Gebro, as speaker from AstraZeneca, Chiesi, Gebro, GSK, Leti Pharma, Mundipharma, Novartis, Roxall, Sanofi. AS: GSK support for an asthma biologic clinical trial 2021-ongoing. PB: Has received honoraria for presentations and consultancy fees from AstraZeneca, Boehringer Ingelheim, Chiesi, ELPEN, GSK, Menarini, Novartis, Sanofi, and Gilead. AB: Takeda, Novartis, Viatris, ALK, Zentiva, MERCK, Stallergenes Greer, Ewopharma, Astra Zeneca, Chiesi, S&D Pharma, Mundipharma, Berlin Chemie. WB: GlaxoSmithKline, Sanofi, Regeneron. JK: Grants and/or personal fees from ALK, Chiesi, GSK, Novartis, AstraZeneca, Sanofi, Boerhinger, Teva, Viatris, Stallergen, Abbot, all outside the submitted work. SL: Honorarium AstraZeneka, GSK, Chiesi Hellas, Sanofi, Elpen, Menarini, Guidoti. MVM: No COIs related to this work. PP: ALK, AstraZeneca, Stallergenes. HP: No COIs related to this work. AS: Reports lecture fees and/or consultancies from AstraZeneca, Chiesi, B.I., GSK, Merck, Novartis, Zambon, Sanofi. HS: No COIs related to this work. IS: No COIs related to this work. BT: No COIs related to this work. MKV: GlaxoSmithKline, AstraZeneca. Diego Conti: No COIs related to this work. WF: The department of Otorhinolaryngology of the Amsterdam University Medical centre, location AMC received grants for research in Rhinology from: ALK, AllergyTherapeutics, Novartis, EU, GSK, MYLAN, Sanofi-Aventis, and Zon-MW; personal COIs: for consultation and/or speaker fees from Dianosic, GSK, Novartis and Sanofi-Aventis/Regeneron. SL: Advisory Board Sanof-Aventis, GSK and Leo-Pharma. Honoraria by DBV Technologies, Allergopharma, Leti, Nutricia, Sanofi-Aventis. GKS: Honoraria for articles, speaker and advisory boards: ALK, AstraZeneca, Capnia, Church & Dwight, Circassia, Noucor, GSK, Meda/Mylan/Viatris, Merck, Sanofi- Regeneron, Stallergenes. Scientific Chief Editor, Rhinology Section, Frontiers in Allergy. Board Member, Lead for Allergic Rhinitis, EUFOREA. Chair of Data Monitoring Board for Paediatric AR trials of HDM SLIT. EVS: No COIs related to this work. PH: Recipient of research grants, honoraria and/or lecture fees of Sanofi, Regeneron, Viatris, GSK, and Novartis. LB: No COIs related to this work.

Background: Because of altered airway microbiome in asthma, we analysed the bacterial species in sputum of patients with severe asthma., Methods: Whole genome sequencing was performed on induced sputum from non-smoking (SAn) and current or ex-smoker (SAs/ex) severe asthma patients, mild/moderate asthma (MMA) and healthy controls (HC). Data were analysed by asthma severity, inflammatory status and transcriptome-associated clusters (TACs)., Results: α-diversity at the species level was lower in SAn and SAs/ex, with an increase in Haemophilus influenzae and Moraxella catarrhalis, and Haemophilus influenzae and Tropheryma whipplei, respectively, compared to HC. In neutrophilic asthma, there was greater abundance of Haemophilus influenzae and Moraxella catarrhalis and in eosinophilic asthma, Tropheryma whipplei was increased. There was a reduction in α-diversity in TAC1 and TAC2 that expressed high levels of Haemophilus influenzae and Tropheryma whipplei, and Haemophilus influenzae and Moraxella catarrhalis, respectively, compared to HC. Sputum neutrophils correlated positively with Moraxella catarrhalis and negatively with Prevotella, Neisseria and Veillonella species and Haemophilus parainfluenzae. Sputum eosinophils correlated positively with Tropheryma whipplei which correlated with pack-years of smoking. α- and β-diversities were stable at one year., Conclusions: Haemophilus influenzae and Moraxella catarrhalis were more abundant in severe neutrophilic asthma and TAC2 linked to inflammasome and neutrophil activation, while Haemophilus influenzae and Tropheryma whipplei were highest in SAs/ex and in TAC1 associated with highest expression of IL-13 type 2 and ILC2 signatures with the abundance of Tropheryma whipplei correlating positively with sputum eosinophils. Whether these bacterial species drive the inflammatory response in asthma needs evaluation., (© 2023 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)

Background: Patients with type-2 (T2) cytokine-low severe asthma often have persistent symptoms despite suppression of T2 inflammation with corticosteroids., Objectives: We sought to analyze whole blood transcriptome from 738 samples in T2-biomarker-high/-low patients with severe asthma to relate transcriptomic signatures to T2 biomarkers and asthma symptom scores., Methods: Bulk RNA-seq data were generated for blood samples (baseline, week 24, week 48) from 301 participants recruited to a randomized clinical trial of corticosteroid optimization in severe asthma. Unsupervised clustering, differential gene expression analysis, and pathway analysis were performed. Patients were grouped by T2-biomarker status and symptoms. Associations between clinical characteristics and differentially expressed genes (DEGs) associated with biomarker and symptom levels were investigated., Results: Unsupervised clustering identified 2 clusters; cluster 2 patients were blood eosinophil-low/symptom-high and more likely to be receiving oral corticosteroids (OCSs). Differential gene expression analysis of these clusters, with and without stratification for OCSs, identified 2960 and 4162 DEGs, respectively. Six hundred twenty-seven of 2960 genes remained after adjusting for OCSs by subtracting OCS signature genes. Pathway analysis identified dolichyl-diphosphooligosaccharide biosynthesis and assembly of RNA polymerase I complex as significantly enriched pathways. No stable DEGs were associated with high symptoms in T2-biomarker-low patients, but numerous associated with elevated T2 biomarkers, including 15 that were upregulated at all time points irrespective of symptom level., Conclusions: OCSs have a considerable effect on whole blood transcriptome. Differential gene expression analysis demonstrates a clear T2-biomarker transcriptomic signature, but no signature was found in association with T2-biomarker-low patients, including those with a high symptom burden., (Crown Copyright © 2023. Published by Elsevier Inc. All rights reserved.)

Background: Asthma is conventionally stratified as type 2 inflammation (T2)-high or T2-low disease. Identifying T2 status has therapeutic implications for patient management, but a real-world understanding of this T2 paradigm in difficult-to-treat and severe asthma remains limited., Objectives: To identify the prevalence of T2-high status in difficult-to-treat asthma patients using a multicomponent definition and compare clinical and pathophysiologic characteristics between patients classified as T2-high and T2-low., Methods: We evaluated 388 biologic-naive patients from the Wessex Asthma Cohort of difficult asthma (WATCH) study in the United Kingdom. Type 2-high asthma was defined as 20 parts per billion or greater FeNO , 150 cells/μL or greater peripheral blood eosinophils, the need for maintenance oral corticosteroids, and/or clinically allergy-driven asthma., Results: This multicomponent assessment identified T2-high asthma in 93% of patients (360 of 388). Body mass index, inhaled corticosteroid dose, asthma exacerbations, and common comorbidities did not differ by T2 status. Significantly worse airflow limitation was found in T2-high compared with T2-low patients (FEV 1 /FVC 65.9% vs 74.6%). Moreover, 75% of patients defined as having T2-low asthma had raised peripheral blood eosinophils within the preceding 10 years, which left only seven patients (1.8%) who had never had T2 signals. Incorporation of sputum eosinophilia 2% or greater into the multicomponent definition in a subset of 117 patients with induced sputum data similarly found that 96% (112 of 117) met criteria for T2-high asthma, 50% of whom (56 of 112) had sputum eosinophils 2% or greater., Conclusions: Almost all patients with difficult-to-treat asthma have T2-high disease; less than 2% of patients never display T2-defining criteria. This highlights a need to assess T2 status comprehensively in clinical practice before labeling a patient with difficult-to-treat asthma as T2-low., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Rationale: Children with preschool wheezing or school-age asthma are reported to have airway microbial imbalances. Objectives: To identify clusters in children with asthma or wheezing using oropharyngeal microbiota profiles. Methods: Oropharyngeal swabs from the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) pediatric asthma or wheezing cohort were characterized using 16S ribosomal RNA gene sequencing, and unsupervised hierarchical clustering was performed on the Bray-Curtis β-diversity. Enrichment scores of the Molecular Signatures Database hallmark gene sets were computed from the blood transcriptome using gene set variation analysis. Children with severe asthma or severe wheezing were followed up for 12-18 months, with assessment of the frequency of exacerbations. Measurements and Main Results: Oropharyngeal samples from 241 children (age range, 1-17 years; 40% female) revealed four taxa-driven clusters dominated by Streptococcus , Veillonella , Rothia , and Haemophilus . The clusters showed significant differences in atopic dermatitis, grass pollen sensitization, FEV 1 % predicted after salbutamol, and annual asthma exacerbation frequency during follow-up. The Veillonella cluster was the most allergic and included the highest percentage of children with two or more exacerbations per year during follow-up. The oropharyngeal clusters were different in the enrichment scores of TGF-β (transforming growth factor-β) (highest in the Veillonella cluster) and Wnt/β-catenin signaling (highest in the Haemophilus cluster) transcriptomic pathways in blood (all q values <0.05). Conclusions: Analysis of the oropharyngeal microbiota of children with asthma or wheezing identified four clusters with distinct clinical characteristics (phenotypes) that associate with risk for exacerbation and transcriptomic pathways involved in airway remodeling. This suggests that further exploration of the oropharyngeal microbiota may lead to novel pathophysiologic insights and potentially new treatment approaches.

Background: Severe neutrophilic asthma is resistant to treatment with glucocorticoids. The immunomodulatory protein macrophage migration inhibitory factor (MIF) promotes neutrophil recruitment to the lung and antagonises responses to glucocorticoids. We hypothesised that MIF promotes glucocorticoid resistance of neutrophilic inflammation in severe asthma., Methods: We examined whether sputum MIF protein correlated with clinical and molecular characteristics of severe neutrophilic asthma in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort. We also investigated whether MIF regulates neutrophilic inflammation and glucocorticoid responsiveness in a murine model of severe asthma in vivo., Results: MIF protein levels positively correlated with the number of exacerbations in the previous year, sputum neutrophils and oral corticosteroid use across all U-BIOPRED subjects. Further analysis of MIF protein expression according to U-BIOPRED-defined transcriptomic-associated clusters (TACs) revealed increased MIF protein and a corresponding decrease in annexin-A1 protein in TAC2, which is most closely associated with airway neutrophilia and NLRP3 inflammasome activation. In a murine model of severe asthma, treatment with the MIF antagonist ISO-1 significantly inhibited neutrophilic inflammation and increased glucocorticoid responsiveness. Coimmunoprecipitation studies using lung tissue lysates demonstrated that MIF directly interacts with and cleaves annexin-A1, potentially reducing its biological activity., Conclusion: Our data suggest that MIF promotes glucocorticoid-resistance of neutrophilic inflammation by reducing the biological activity of annexin-A1, a potent glucocorticoid-regulated protein that inhibits neutrophil accumulation at sites of inflammation. This represents a previously unrecognised role for MIF in the regulation of inflammation and points to MIF as a potential therapeutic target for the management of severe neutrophilic asthma., Competing Interests: Competing interests: VSRRA, SPa, GL, NZK, JS, JT, SD, Y-KG, PMH, SPh, JH and MBS have nothing to disclose. EFM reports grants from Janssen, Bristol Myers Squibb, UCB, Merck Serono and Eli Lilly outside the submitted work. In addition, EFM has patents 7,709,514 and 7,863,313 issued. KFC has received honoraria for participating in advisory board meetings of GlaxoSmithKline, AstraZeneca, Novartis, Merck, Boehringer Ingelheim and TEVA regarding treatments for asthma and chronic obstructive pulmonary disease and has also been renumerated for speaking engagements. IA and PS report grants from the public private European Union Innovative Medicines Initiative during the conduct of the study. RD reports receiving fees for lectures at symposia organised by Novartis, AstraZeneca and TEVA; consultation for TEVA and Novartis as member of advisory boards; and participation in a scientific discussion about asthma organised by GlaxoSmithKline. RD is a cofounder and current consultant and has shares in Synairgen, a University of Southampton spin-out company., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

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 (FEV 1 ) 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., Competing Interests: Conflict of interest: E. Khaleva and A. Rattu declare funding from 3TR European Union Innovative Medicines Initiative 2 to their institution for the present manuscript. C. Brightling declares grants from GlaxoSmithKline, AstraZeneca, Novartis, Chiesi, Boehringer Ingelheim, Genentech, Roche, Sanofi, Mologic and 4DPharma; consulting fees from GlaxoSmithKline, AstraZeneca, Novartis, Chiesi, Boehringer Ingelheim, Genentech, Roche, Sanofi, Mologic, 4DPharma and Teva; and support from the 3TR project. G.W. Clarke declares that he is an employee of AstraZeneca; and that he holds stock or stock options in AstraZeneca. M. van den Berge declares grants from GlaxoSmithKline, AstraZeneca, Roche, Genentech and Novartis paid to the university. A. Bossios declares honoraria for lectures from GlaxoSmithKline, AstraZeneca, Teva and Novartis; support for attending meetings from AstraZeneca and Novartis; honoraria for advisory board meetings from GlaxoSmithKline, AstraZeneca, Teva, Novartis and Sanofi; being a member of the Steering Committee of SHARP, Secretary of Assembly 5 (Airway Diseases, Asthma, COPD and Chronic Cough) of the European Respiratory Society; Vice-chair of the Nordic Severe Asthma Network (NSAN). V. Ramiconi and S. Romagosa Vilarnau declare unrestricted educational grants paid to the organisation from Novartis, Pfizer, AstraZeneca, Chiesi Farmaceutici, GlaxoSmithKline, AbbVie, LeoPharma, Boehringer Ingelheim, Sanofi, Regeneron, OM Pharma, MSD, Roche and DBV Technologies; support for attending meetings from Novartis. S-E. Dahlén declares a 3TR Innovative Medicines Initiative grant; consulting fees for AstraZeneca, Cayman Co., GlaxoSmithKline, Novartis, Regeneron, Sanofi and Teva; payment for lectures from AstraZeneca and Sanofi. S. Principe declares support for provision of study materials and medical writing. G. Hedlin declares participation in advisory boards of AstraZeneca and Sanofi. F. Singer reports grants from Lung League Bern, grants from the Swiss Cystic Fibrosis Society (CFCH), personal fees from Vertex Pharmaceuticals, personal fees from Novartis, outside the submitted work. A. Deschildre reports personal consulting fees from Sanofi-Regeneron, ALK, Novartis and GlaxoSmithKline; honoraria for lectures from ALK, Boehringer Ingelheim and Novartis; support for attending meetings from AstraZeneca, Stallergènes-Greer, MEDA, Nutricia, Sanofi and Novartis, outside the submitted work; and being on the scientific committee of SFA (Société Française d'Allergologie). L.J. Fleming declares participation in advisory boards and honoraria for lectures from Sanofi, Respiri UK, AstraZeneca, Novartis and Teva, outside of the scope of this publication; all payments were made to her institution. H. Staudinger reports that he is a salaried employee of Sanofi Genzyme and owns company stock of Sanofi and Merck & Co. K.C. Pike declares consultancy fees from Novartis, Adherium and Respiri, and honoraria for a lecture from Novartis. J. Grigg declares payments from GlaxoSmithKline, OM Pharma, Omron and Novartis (advisory boards), Sanofi (for lectures) and AstraZeneca (CI clinical trial). N. Rutjes reports personal fees for advisory board work from Sanofi. G.H. Koppelman reports receiving research grants from the Lung Foundation of the Netherlands, Ubbo Emmius Foundation, H2020 European Union, Teva, GlaxoSmithKline and Vertex, outside this work (money to institution); he reports memberships of advisory boards to GlaxoSmithKline and PURE-IMS, outside this work (money to institution). D. Cunoosamy holds shares in AstraZeneca and Sanofi. A.H. Maitland-van der Zee has received research grants outside the submitted work from GlaxoSmithKline, Boehringer Ingelheim and Vertex, she is the PI of a P4O2 (Precision Medicine for more Oxygen) public private partnership sponsored by Health Holland involving many private partners that contribute in cash and/or in kind (Boehringer Ingelheim, Breathomix, Fluidda, Ortec Logiqcare, Philips, Quantib-U, Roche, Smartfish, SODAQ, Thirona, TopMD and Novartis), and she has served in advisory boards for AstraZeneca, GlaxoSmithKline and Boehringer Ingelheim with money paid to her institution. K.F. Chung has received honoraria for participating in advisory board meetings of GlaxoSmithKline, AstraZeneca, Roche, Novartis, Merck and Shionogi, regarding treatments for asthma, COPD and chronic cough, and has also been remunerated for speaking engagements for Novartis and AstraZeneca; received a MRC grant on Precision Medicine for severe asthma, EPSRC grant on air pollution and asthma, and a GlaxoSmithKline grant on mepolizumab and eosinophils in asthma. P. Nagakumar received speaker fees for talks on severe asthma from GlaxoSmithKline and Novartis. G. Brusselle declares payments from AstraZeneca, Novartis, Boehringer Ingelheim, Chiesi, Sanofi, GlaxoSmithKline and MSD, outside the submitted work. E. Hamelmann declares support from the German Ministry of Education and Research (BMBF) and German Asthma Net (GAN) eV; funding for research in severe asthma in children (CHAMP-01GL1742D) and for Severe Asthma Register. S. Vijverberg is PI of the PERMEABLE consortium. The PERMEABLE consortium is a research consortium focused on severe asthma and allergy and supported by ZonMW (456008004), the Swedish Research Council (2018-05619), the Ministry of Education, Science and Sport of the Republic of Slovenia (C3330-19-252012), and the German Ministry of Education and Research (BMBF) FKZ01KU1909A), under the frame of the ERA PerMed JTC 2018 Call. In addition, S. Vijverberg has received research funding for a project on severe paediatric asthma from the Lung Foundation Netherlands (6.2.18.244JO). A-M.M. Schoos has participated on an advisory board for ALK. B. Dahlén reports personal fees for lectures from AstraZeneca, Novartis and Sanofi; and grants from Novartis and GlaxoSmithKline, outside the submitted work; participation on an advisory board for AstraZeneca and Sanofi. A. Exley declares being a minority shareholder in GlaxoSmithKline Plc. E.A. Gaillard reports consultancy work for Boehringer Ingelheim with money paid to the institution (University of Leicester); investigator-led research grants from Circassia Group, Gilead Sciences, Chiesi Limited and Propeller Health; and has a research collaboration with Medimmune. M. Pijnenburg declares payments to her institution from Sanofi Genzyme (advisory work) and Novartis (speakers fee). E. Melén declares consulting fees from AstraZeneca, Chiesi, Novartis and Sanofi, outside the submitted work. R. Chaudhuri has received lecture fees from GlaxoSmithKline, AstraZeneca, Teva, Chiesi, Sanofi and Novartis; honoraria for advisory board meetings from GlaxoSmithKline, AstraZeneca, Teva, Chiesi and Novartis; sponsorship to attend international scientific meetings from Chiesi, Napp, Sanofi and GlaxoSmithKline, and a research grant to her institute from AstraZeneca for a UK multi-centre study. C. Pilette declares grants, consulting fees and honoraria for lectures (paid to institution) from AstraZeneca, Chiesi, GlaxoSmithKline, Novartis, Mundipharma, Teva, Sanofi and ALK. C. Porsbjerg declares grants (paid to institution), consulting fees (paid to institution and personal honoraria) and honoraria for lectures (paid to institution and personal honoraria) from AstraZeneca, GlaxoSmithKline, Novartis, Teva, Sanofi, Chiesi and ALK; participation on an advisory board (paid to institution and personal honoraria) for AstraZeneca, Novartis, Teva, Sanofi and ALK. C. Coleman and C. Williams declare funding received to support this work by the European Lung Foundation (ELF) from the European Commission's Innovative Medicines Initiative 2 Joint Undertaking under grant agreement number 831434 (3TR), and are employees of the ELF. B. Ahrens, S. Kaul, D. Hartenstein and V. Mahler declare no conflict of interest for this article and state that the views expressed in this review are the personal views of the author and may not be understood or quoted as being made on behalf of or reflecting the position of the respective national competent authorities, the European Medicines Agency or one of its committees or working parties. L.G. Heaney declares support from the 3TR; grants from industrial pharma partners Amgen, AstraZeneca, Medimmune, Janssen, Novartis, Roche/Genentech, GlaxoSmithKline and Boehringer Ingelheim; project grant funding from Medimmune, Novartis UK, Roche/Genentech and GlaxoSmithKline, outside the submitted work; payments for lectures by AstraZeneca, Novartis, Roche/Genentech, GlaxoSmithKline, Chiesi and Teva, outside the submitted work; travel funding support to international respiratory meetings by AstraZeneca, Chiesi, Novartis, Boehringer Ingelheim, Teva and GlaxoSmithKline, outside the submitted work; advisory boards for AstraZeneca, Novartis, GlaxoSmithKline, Chiesi, Teva, Theravance and Vectura, outside the submitted work. R. Djukanovic declares funding from the European Respiratory Society, Teva, GlaxoSmithKline, Novartis, Sanofi and Chiesi for the SHARP Clinical Research Collaboration; consulting fees for Synairgen; honorarium for a lecture from GlaxoSmithKline; participation on a data safety monitoring board or advisory board for Kymab (Cambridge) and shares in Synairgen outside of the submitted work. A. Bourdin declares grants from Boehringer and AstraZeneca; consulting fees and payments from Boehringer, AstraZeneca, GlaxoSmithKline, Novartis, Chiesi, Regeneron, Sanofi and Amgen outside of the submitted work. B. Karadag declares participation in a trial conducted by Sanofi (payment to institution) and attending advisory board meetings for GlaxoSmithKline (personal fees). K. Blumchen declares grants from Aimmune Therapeutics, DBV Technologies and Hipp GmbH; consulting fees from Aimmune Therapeutics, DBV Technologies and Allergy Therapeutics; payments for lectures from Aimmune Therapeutics, DBV Technologies, Novartis, Allergy Therapeutics, HAL, ALK, Allergopharma, Nutricia, Thermo Fisher Scientific, and Bausch and Lomb; personal fees for expert discussions from Novartis and Nestle; fees for attending meetings from Aimmune Therapeutics and DBV Technologies; being on data safety monitoring board of Charité, IIT. A. Gupta received speaker/advisory board fees from GlaxoSmithKline, Novartis, AstraZeneca and Boehringer Ingelheim; received research grants from GlaxoSmithKline, Novartis, AstraZeneca and Boehringer Ingelheim, paid to institution. L. Giovannini-Chami declares consulting fees from ALK, AstraZeneca and Novartis; honoraria for lectures, presentations from Novartis, ALK, Stallergènes, Sanofi and AstraZeneca; support for attending meetings from Stallergènes; participation on a data safety monitoring board or advisory board for Sanofi; being head of the Scientific Committee of the French Pediatric Pulmonology and Allergology Society. C.S. Murray has received lecture fees from GlaxoSmithKline and Novartis; received grants from Asthma UK and National Institute for Health Research; and has participated on an advisory board for Boehringer Ingelheim. G. Roberts declares European Union Innovative Medicines Initiative funding and AstraZeneca paid to the institution. Other co-authors declare no conflicts of interest for this article., (Copyright ©The authors 2023.)

Background: Valid outcome measures are imperative to evaluate treatment response, yet the suitability of existing end-points for severe asthma is unclear. This review aimed to identify outcome measures for severe asthma and appraise the quality of their measurement properties., Methods: A literature search was performed to identify "candidate" outcome measures published between 2018 and 2020. A modified Delphi exercise was conducted to select "key" outcome measures within healthcare professional, patient, pharmaceutical and regulatory stakeholder groups. Initial validation studies for "key" measures were rated against modified quality criteria from COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). The evidence was discussed at multi-stakeholder meetings to ratify "priority" outcome measures. Subsequently, four bibliographic databases were searched from inception to 20 July 2020 to identify development and validation studies for these end-points. Two reviewers screened records, extracted data, assessed their methodological quality and graded the evidence according to COSMIN., Results: 96 outcome measures were identified as "candidates", 55 as "key" and 24 as "priority" for severe asthma, including clinical, healthcare utilisation, quality of life, asthma control and composite. 32 studies reported measurement properties of 17 "priority" end-points from the latter three domains. Only the Severe Asthma Questionnaire and Childhood Asthma Control Test were developed with input from severe asthma patients. The certainty of evidence was "low" to "very low" for most "priority" end-points across all measurement properties and none fulfilled all quality standards., Conclusions: Only two outcome measures had robust developmental data for severe asthma. This review informed development of core outcome measures sets for severe asthma., Competing Interests: Conflict of interest: A. Rattu and E. Khaleva declare funding from the European Commission's Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement number 831434 (3TR) for this manuscript. C. Brightling declares grants from GlaxoSmithKline, AstraZeneca, Novartis, Chiesi, Boehringer Ingelheim, Genentech, Roche, Sanofi, Mologic and 4DPharma, consulting fees from GlaxoSmithKline, AstraZeneca, Novartis, Chiesi, Boehringer Ingelheim, Genentech, Roche, Sanofi, Mologic, 4DPharma and Teva, and support from the 3TR project. S-E. Dahlén declares a 3TR IMI grant, consulting fees from AstraZeneca, Cayman Co., GlaxoSmithKline, Novartis, Regeneron, Sanofi and Teva, and payment for lectures from AstraZeneca and Sanofi. A. Bossios declares honoraria for lectures from GlaxoSmithKline, AstraZeneca, Teva and Novartis, support for attending meetings from AstraZeneca and Novartis, honoraria for advisory board meetings from GlaxoSmithKline, AstraZeneca, Teva, Novartis and Sanofi, and being a member of the Steering Committee of SHARP, Secretary of Assembly 5 (Airway Diseases, Asthma, COPD and Chronic Cough) of the European Respiratory Society, and Vice-chair of the Nordic Severe Asthma Network (NSAN). L. Fleming declares participation in advisory boards and honoraria for lectures from Sanofi, Respiri UK, AstraZeneca, Novartis and Teva, outside the submitted work; all payments were made to her institution. K.F. Chung has received honoraria for participating in advisory board meetings of GlaxoSmithKline, AstraZeneca, Roche, Novartis, Merck and Shionogi regarding treatments for asthma, COPD and chronic cough, and has also been remunerated for speaking engagements for Novartis and AstraZeneca; has received an MRC grant on precision medicine for severe asthma, an EPSRC grant on air pollution and asthma, and a GlaxoSmithKline grant on mepolizumab and eosinophils in asthma. E. Melén declares consulting fees from AstraZeneca, Chiesi, Novartis and Sanofi, outside the submitted work. R. Chaudhuri has received lecture fees from GlaxoSmithKline, AstraZeneca, Teva, Chiesi, Sanofi and Novartis, honoraria for advisory board meetings from GlaxoSmithKline, AstraZeneca, Teva, Chiesi and Novartis, sponsorship to attend international scientific meetings from Chiesi, Napp, Sanofi and GlaxoSmithKline, and a research grant to her institute from AstraZeneca for a UK multicentre study. R. Djukanovic declares funding from the European Respiratory Society, Teva, GlaxoSmithKline, Novartis, Sanofi and Chiesi for the SHARP CRC, consulting fees for Synairgen, honorarium for a lecture from GlaxoSmithKline, participation on a data safety monitoring board or advisory board for Kymab (Cambridge), and shares in Synairgen, outside the submitted work. A. Exley declares being a minority shareholder in GlaxoSmithKline PLC. G.H. Koppelman reports receiving research grants from the Lung Foundation of the Netherlands, Ubbo Emmius Foundation, H2020 European Union, Teva, GlaxoSmithKline and Vertex, outside this work (money to institution); he reports memberships of advisory boards to GlaxoSmithKline and PURE-IMS, outside this work (money to institution). A. Bourdin declares unrestricted grants from AstraZeneca and Boehringer Ingelheim to his institute; consulting fees, honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events, and support for attending meetings and travel from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis and Sanofi; participation on a data safety monitoring board or advisory board for AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Sanofi and Abs science. C. Porsbjerg declares grants (paid to institution), consulting fees (paid to institution and personal honoraria) and honoraria for lectures (paid to institution and personal honoraria) from AstraZeneca, GlaxoSmithKline, Novartis, Teva, Sanofi, Chiesi and ALK; participation on an advisory board (paid to institution and personal honoraria) for AstraZeneca, Novartis, Teva, Sanofi and ALK. C. Coleman and C. Williams declare funding received to support this work by the European Lung Foundation (ELF) from the European Commission's Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement number 831434 (3TR), and are employees of the ELF. E. Davin bought and sold shares on the public market during 2021–2022 in Regeneron, Roche and ICON Plc, and declares no current holdings. P. Taverner declares honorarium for being a lay member of Asthma and Lung UK's research funding panel, and chairing a Patient and Community Oversight Group for two NIHR health protection research units on environmental and chemical hazards; and payment for chairing a NICE guideline committee on advocacy services. S. Romagosa Vilarnau declares unrestricted educational grants paid to the organisation from Novartis, Pfizer, AstraZeneca, Chiesi Farmaceutici, GlaxoSmithKline, AbbVie, LeoPharma, Boehringer Ingelheim, Sanofi, Regeneron, OM Pharma, MSD, Roche and DBV Technologies. G. Roberts declares EU IMI funding and consulting fees from AstraZeneca paid to his institution. No other author has any conflict of interest to declare., (Copyright ©The authors 2023. For reproduction rights and permissions contact permissions@ersnet.org.)

Background: Approximately 5% to 10% of patients with asthma have severe disease, with a consistent preponderance in females. Current asthma guidelines recommend stepwise treatment to achieve symptom control with no differential treatment considerations for either sex., Objective: To examine whether patient sex affects outcomes when using a composite T2-biomarker score to adjust corticosteroid (CS) treatment in patients with severe asthma compared with standard care., Methods: This is a post hoc analysis, stratifying patient outcomes by sex, of a 48-week, multicenter, randomized controlled clinical trial comparing a biomarker-defined treatment algorithm with standard care. The primary outcome was the proportion of patients with a reduction in CS treatment (inhaled and oral corticosteroids). Secondary outcomes included exacerbation rates, hospital admissions, and lung function., Results: Of the 301 patients randomized, 194 (64.5%) were females and 107 (35.5%) were males. The biomarker algorithm led to a greater proportion of females being on a lower CS dose versus standard care, which was not seen in males (effect estimate: females, 3.57; 95% CI, 1.14-11.18 vs males, 0.54; 95% CI, 0.16-1.80). In T2-biomarker-low females, reducing CS dose was not associated with increased exacerbations. Females scored higher in all domains of the 7-item Asthma Control Questionnaire, apart from FEV1, but with no difference when adjusted for body mass index/anxiety and/or depression. Dissociation between symptoms and T2 biomarkers were noted in both sexes, with a higher proportion of females being symptom high/T2-biomarker low (22.8% vs 15.6%; P = .0002), whereas males were symptom low/T2-biomarker high (22.3% vs 11.4%; P < .0001)., Conclusions: This exploratory post hoc analysis identified that females achieved a greater benefit from biomarker-directed CS optimization versus symptom-directed treatment., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

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 β-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 β-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.

Rationale: The past 25 years have seen huge progress in understanding of the pathobiology of type-2 (T2) asthma, identification of measurable biomarkers, and the emergence of novel monoclonal antibody treatments. Although present in a minority of patients with severe asthma, very little is known about the mechanisms underlying T2-low asthma, making it a significant unmet need in asthma research. Objectives: The objective of this study was to explore the differences between study exacerbators and nonexacerbators, to describe physiological changes at exacerbation in those who are T2 HIGH and T2 LOW at the time of exacerbation, and to evaluate the stability of inflammatory phenotypes when stable and at exacerbation. Methods: Exacerbation assessment was a prespecified secondary analysis of data from a 48-week, multicenter, randomized controlled clinical study comparing the use of biomarkers and symptoms to adjust steroid treatment in a T2-low severe asthma-enriched cohort. Participants were phenotyped as T2 LOW (fractional exhaled nitric oxide ⩽ 20 ppb and blood eosinophil count ⩽ 150 cells/µl) or T2 HIGH (fractional exhaled nitric oxide > 20 or blood eosinophil count > 150) at study enrollment and at each exacerbation. Here, we report the findings of the exacerbation analyses, including comparison of exacerbators and nonexacerbators, the physiological changes at exacerbation in those who had evidence of T2 biology at exacerbation versus those that did not, and the stability of inflammatory phenotypes when stable and at exacerbation. Measurements and Main Results: Of the 301 participants, 60.8% (183) had one or more self-reported exacerbations (total of 390). Exacerbators were more likely to be female, have a higher body mass index, and have more exacerbations requiring oral corticosteroid and unscheduled primary care attendances for exacerbations. At enrollment, 23.6% (71) were T2 LOW and 76.4% (230) T2 HIGH . The T2 LOW group had more asthma primary care attendances, were more likely to have a previous admission to HDU (high dependency unit)/ICU and to be receiving maintenance oral corticosteroids. At exacerbation, the T2 LOW events were indistinguishable from T2 HIGH exacerbations in terms of lung function (mean fall in T2 LOW FEV 1, 200 [400] ml vs. T2 HIGH 200 [300] ml; P  = 0.93) and symptom increase (ACQ5: T2 LOW , 1.4 [0.8] vs. T2 HIGH , 1.3 [0.8]; P  = 0.72), with no increase in T2 biomarkers from stable to exacerbation state in the T2 LOW exacerbations. The inflammatory phenotype within individual patients was dynamic; inflammatory phenotype at study entry did not have a significant association with exacerbation phenotype. Conclusions: Asthma exacerbations demonstrating a T2 LOW phenotype were physiologically and symptomatically similar to T2 HIGH exacerbations. T2 LOW asthma was an unstable phenotype, suggesting that exacerbation phenotyping should occur at the time of exacerbation. The clinically significant exacerbations in participants without evidence of T2 biology at the time of exacerbation highlight the unmet and pressing need to further understand the mechanisms at play in non-T2 asthma. Clinical trial registered with www.clinicaltrials.gov (NCT02717689).

Background: Severe asthma is associated with multiple comorbidities, including gastro-oesophageal reflux disease (GORD), which can contribute to exacerbation frequency and poor quality of life. Since epithelial dysfunction is an important feature in asthma, we hypothesised that in severe asthma the bronchial epithelium is more susceptible to the effects of acid reflux., Methods: We developed an in vitro model of GORD using differentiated bronchial epithelial cells (BECs) from normal or severe asthmatic donors exposed to a combination of pepsin, acid pH and bile acids using a multiple challenge protocol (MCP-PAB). In addition, we analysed bronchial biopsies and undertook RNA sequencing of bronchial brushings from controls and severe asthmatics without or with GORD., Results: Exposure of BECs to the MCP-PAB caused structural disruption, increased permeability, interleukin (IL)-33 expression, inflammatory mediator release and changes in gene expression for multiple biological processes. Cultures from severe asthmatics were significantly more affected than those from healthy donors. Analysis of bronchial biopsies confirmed increased IL-33 expression in severe asthmatics with GORD. RNA sequencing of bronchial brushings from this group identified 15 of the top 37 dysregulated genes found in MCP-PAB treated BECs, including genes involved in oxidative stress responses., Conclusions and Clinical Implication: By affecting epithelial permeability, GORD may increase exposure of the airway submucosa to allergens and pathogens, resulting in increased risk of inflammation and exacerbations. These results suggest the need for research into alternative therapeutic management of GORD in severe asthma., Competing Interests: Conflict of interest: J-M. Perotin, G. Wheway, K. Tariq, A. Azim, R.A. Ridley, J.A. Ward, C. Barber and D.E. Davies have nothing to disclose. J.P.R. Schofield reports being director and shareholder in TopMD Precision Medicine Ltd. P. Howarth reports personal fees from GSK outside the submitted work. R. Djukanovic reports receiving fees for lectures at symposia organised by Novartis, AstraZeneca and TEVA, consultation for TEVA and Novartis as member of advisory boards, and participation in a scientific discussion about asthma organised by GlaxoSmithKline; and is a co-founder and current consultant, and has shares in Synairgen, a University of Southampton spin-out company., (Copyright ©The authors 2022. For reproduction rights and permissions contact permissions@ersnet.org.)

Introduction: Asthma 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., Methods: Baseline 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., Results: A total of 90 metabolites were identified, with 40 significantly altered (p<0.05, false discovery rate <0.05) in severe asthma and 23 by OCS use. Multivariate modelling showed that observed metabotypes in healthy participants and patients with mild-to-moderate asthma differed significantly from those in patients with severe asthma (p=2.6×10 -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., Conclusions: This 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., Competing Interests: Conflict of interest: S.N. Reinke reports grants from Canadian Institutes of Health Research, during the conduct of the study. Conflict of interest: S. Naz has nothing to disclose. Conflict of interest: R. Chaleckis has nothing to disclose. Conflict of interest: H. Gallart-Ayala has nothing to disclose. Conflict of interest: J. Kolmert reports personal fees for consultancy from Gesynta Pharma AB, outside the submitted work. Conflict of interest: N.Z. Kermani has nothing to disclose. Conflict of interest: A. Tiotiu has nothing to disclose. Conflict of interest: D.I. Broadhurst has nothing to disclose. Conflict of interest: A. Lundqvist has nothing to disclose. Conflict of interest: H. Olsson is an employee and shareholder of AstraZeneca. Conflict of interest: M. Ström has nothing to disclose. Conflict of interest: Å.M. Wheelock has nothing to disclose. Conflict of interest: C. Gómez has nothing to disclose. Conflict of interest: M. Ericsson has nothing to disclose. Conflict of interest: A.R. Sousa has nothing to disclose. Conflict of interest: J.H. Riley works for and own shares in GlaxoSmithKline. Conflict of interest: S. Bates is an employee of Johnson & Johnson and has previously worked for and holds stock in GlaxoSmithKline. Conflict of interest: J. Scholfield reports grants from Innovative Medicines Initiative, during the conduct of the study; and is director and employee of TopMD Precision Medicine Ltd. Conflict of interest: M. Loza is an employee of and owns stock in Johnson & Johnson. Conflict of interest: F. Baribaud is a shareholder of Johnson & Johnson and a current employee of Bristol Myers Squibb. Conflict of interest: P.S. Bakke reports personal fees for advisory board work and lectures from AstraZeneca, and personal fees for lectures from Novartis and Boehringer Ingelheim, outside the submitted work. Conflict of interest: M. Caruso has nothing to disclose. Conflict of interest: P. Chanez reports grants and personal fees from AstraZeneca, ALK, Boehringer Ingelheim, Chiesi, Sanofi-Aventis, Novartis and GlaxoSmithKline, outside the submitted work. Conflict of interest: S.J. Fowler reports personal fees from AstraZeneca, Novartis, TEVA and Chiesi, outside the submitted work. Conflict of interest: T. Geiser has nothing to disclose. Conflict of interest: P. Howarth has nothing to disclose. Conflict of interest: I. Horvath has nothing to disclose. Conflict of interest: N. Krug has nothing to disclose. Conflict of interest: P. Montuschi has nothing to disclose. Conflict of interest: A. Behndig has nothing to disclose. Conflict of interest: F. Singer reports personal fees from Vertex Pharmaceuticals (CH) and Novartis, outside the submitted work. Conflict of interest: J. Musial has nothing to disclose. Conflict of interest: D.E. Shaw has nothing to disclose. Conflict of interest: B. Dahlén reports personal fees for advisory board work and lectures from AstraZeneca, TEVA and Sanofi, and grants from Novartis and GlaxoSmithKline, outside the submitted work. Conflict of interest: S. Hu has nothing to disclose. Conflict of interest: J. Lasky-Su has nothing to disclose. Conflict of interest: P.J. Sterk reports a public private grant from the Innovative Medicines Initiative (IMI) covered by the EU and EFPIA, during the conduct of the study. Conflict of interest: K.F. Chung has received honoraria for participating in advisory board meetings of GlaxoSmithKline, AstraZeneca, Roche, Novartis, Merck, Nocion and Shionogi regarding treatments for asthma, COPD and chronic cough and has also been remunerated for speaking engagements. Conflict of interest: R. Djukanovic reports receiving fees for lectures at symposia organised by Novartis, AstraZeneca and TEVA, consultation for TEVA and Novartis as member of advisory boards, and participation in a scientific discussion about asthma organised by GlaxoSmithKline; and is a co-founder and current consultant, and has shares in Synairgen, a University of Southampton spin out company. Conflict of interest: S-E. Dahlén reports personal fees for consultancy from AstraZeneca, Cayman Chemical, GlaxoSmithKline, Novartis, Merck, Regeneron, Sanofi and TEVA, outside the submitted work. Conflict of interest: I.M. Adcock has nothing to disclose. Conflict of interest: C.E. Wheelock has nothing to disclose., (Copyright ©The authors 2022.)

Background: Exacerbation-prone asthma is a feature of severe disease. However, the basis for its persistency remains unclear., Objectives: To determine the clinical and transcriptomic features of frequent exacerbators (FEs) and persistent FEs (PFEs) in the U-BIOPRED cohort., Methods: We compared features of FE (≥2 exacerbations in past year) to infrequent exacerbators (IE, <2 exacerbations) and of PFE with repeat ≥2 exacerbations during the following year to persistent IE (PIE). Transcriptomic data in blood, bronchial and nasal epithelial brushings, bronchial biopsies and sputum cells were analysed by gene set variation analysis for 103 gene signatures., Results: Of 317 patients, 62.4% had FE, of whom 63.6% had PFE, while 37.6% had IE, of whom 61.3% had PIE. Using multivariate analysis, FE was associated with short-acting beta-agonist use, sinusitis and daily oral corticosteroid use, while PFE was associated with eczema, short-acting beta-agonist use and asthma control index. CEA cell adhesion molecule 5 (CEACAM5) was the only differentially expressed transcript in bronchial biopsies between PE and IE. There were no differentially expressed genes in the other four compartments. There were higher expression scores for type 2, T-helper type-17 and type 1 pathway signatures together with those associated with viral infections in bronchial biopsies from FE compared to IE, while there were higher expression scores of type 2, type 1 and steroid insensitivity pathway signatures in bronchial biopsies of PFE compared to PIE., Conclusion: The FE group and its PFE subgroup are associated with poor asthma control while expressing higher type 1 and type 2 activation pathways compared to IE and PIE, respectively., (© 2022 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.)

Rationale: Asthma phenotyping requires novel biomarker discovery., Objectives: To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs)., Methods: An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED., Results: In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation., Conclusions: The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA., Competing Interests: Conflict of interest: M. Sparreman Mikus has nothing to disclose. Conflict of interest: J. Kolmert reports personal fees from Gesynta Pharma AB. Conflict of interest: L.I. Andersson has nothing to disclose. Conflict of interest: J. Östling has nothing to disclose. Conflict of interest: R.G. Knowles has nothing to disclose. Conflict of interest: C. Gómez has nothing to disclose. Conflict of interest: M. Ericsson has nothing to disclose. Conflict of interest: J-O. Thörngren has nothing to disclose. Conflict of interest: P. Emami Khoonsari has nothing to disclose. Conflict of interest: B. Dahlén reports personal fees from AstraZeneca, Teva, Sanofi and grants from Novartis and GlaxoSmithKline outside the submitted work. Conflict of interest: M. Kupczyk has nothing to disclose. Conflict of interest: B. De Meulder report grants from the Innovative Medicines Initiative during the conduct of the study. Conflict of interest: C. Auffray report grants from the Innovative Medicines Initiative during the conduct of the study. Conflict of interest: P.S. Bakke reports personal fees from GlaxoSmithKline, AstraZeneca, Boehringer Ingelheim and Chiesi outside the submitted work. Conflict of interest: B. Beghe reports personal fees from AstraZeneca, Boehringer Ingelheim, Menarini and GlaxoSmithKline outside the submitted work. Conflict of interest: E.H. Bel reports grants and personal fees from GlaxoSmithKline, AstraZeneca, Novartis, TEVA, Sanofi/Regeneron, Chiesi, and Sterna outside the submitted work. Conflict of interest: M. Caruso has nothing to disclose. Conflict of interest: P. Chanez has nothing to disclose. Conflict of interest: B. Chawes has nothing to disclose. Conflict of interest: S.J. Fowler has nothing to disclose. Conflict of interest: M. Gaga reports grants and personal fees from Novartis, Menarini, Merck Sharp & Dohme, BMS, Galapagos, and AstraZeneca outside the submitted work. Conflict of interest: T. Geiser has nothing to disclose. Conflict of interest: M. Gjomarkaj has nothing to disclose. Conflict of interest: I. Horváth reports grants from EFPIA during the conduct of the study, and personal fees from AstraZeneca, GlaxoSmithKline, Novartis, Boehringer-Ingelheim, Sandoz, Teva and Chiesi outside the submitted work. Conflict of interest: P.H. Howarth has nothing to disclose. Conflict of interest: S.L. Johnston reports personal fees from Virtus Respiratory Research, Myelo Therapeutics GmbH, Concert Pharmaceuticals, Bayer, Synairgen, Novartis, Boehringer Ingelheim, Chiesi, Gerson Lehrman Group, resTORbio, Bioforce, Materia Medical Holdings, PrepBio Pharma, Pulmotect, Virion Health, Lallemand Pharma and AstraZeneca outside the submitted work. In addition, Sebastian L. Johnston also has three patents (Anti-virus therapy for respiratory diseases, UK patent application No. GB 0405634.7, Interferon-Beta for Anti-Virus Therapy for Respiratory Diseases, International Patent Application No. PCT/ GB05/50031 and Interferon Lambda therapy for the treatment of respiratory disease, UK patent application No.6779645.9). Conflict of interest: G. Joos reports grants and personal fees from AstraZeneca, Bayer, Chiesi, Eureca vzw, GlaxoSmithKline and Teva outside the submitted work. Conflict of interest: N. Krug has nothing to disclose. Conflict of interest: P. Montuschi has nothing to disclose. Conflict of interest: J. Musial has nothing to disclose. Conflict of interest: E. Niżankowska-Mogilnicka has nothing to disclose. Conflict of interest: H.K. Olsson reports other support from AstraZeneca outside the submitted work. Conflict of interest: A. Papi reports grants, personal fees, non-financial support and others from GlaxoSmithKline, AstraZeneca, Boehringer Ingelheim, Chiesi, Teva, Mundipharma, Zambon, Novartis, Menarini, Sanofi/Regeneron, Roche, Fondazione Salvatore Maugeri, Chiesi and Edmond pharma outside the submitted work. Conflict of interest: K.F. Rabe reports grants and personal fees from AstraZeneca, Boehringer Ingelheim, Sanofi Aventis, MERCK SHARP & DOHME, Novartis, Orion Cooperation, Berlin Chemie, Roche, Chiesi and grants for research from the Ministry of Education and Science, Germany. Conflict of interest: T. Sandström has nothing to disclose. Conflict of interest: D.E. Shaw reports personal fees and non-financial support from GlaxoSmithKline, Novartis and AstraZeneca outside the submitted work. Conflict of interest: N.M. Siafakas has nothing to disclose. Conflict of interest: M. Uhlen has nothing to disclose. Conflict of interest: J.H. Riley is an employee and shareholder in GlaxoSmithKline. Conflict of interest: S. Bates is an employee and shareholder in GlaxoSmithKline. Conflict of interest: R.J.M. Middelveld reports grants from the Swedish Strategic Research Foundation, AstraZeneca, the Swedish Heart Lung Foundation and the Swedish Asthma and Allergy Association outside the submitted work. Conflict of interest: C.E. Wheelock has nothing to disclose. Conflict of interest: K.F. Chung reports grants and personal fees from GlaxoSmithKline, AstraZeneca, Novartis, Merck, Boehringer Ingelheim, Roche and Shionogi outside the submitted work. Conflict of interest: I.M. Adcock has nothing to disclose. Conflict of interest: P.J. Sterk reports grants to Amsterdam UMC from the public private Innovative Medicines Initiative (IMI) covered by the European Union (EU) and the European Federation of Pharmaceutical Industries and Associations (EFPIA) during the conduct of the study. Conflict of interest: R. Djukanovic reports receiving fees for lectures at symposia organised by Novartis, GlaxoSmithKline, AstraZeneca and Teva, consultation fees from Teva and Novartis; he is a co-founder and current consultant and has shares in Synairgen. Conflict of interest: P. Nilsson has nothing to disclose. Conflict of interest: S-E. Dahlén reports personal fees from AstraZeneca, Cayman Chemicals, GlaxoSmithKline, Novartis, Regeneron, Sanofi and Teva outside the submitted work. Conflict of interest: A. James has nothing to disclose., (Copyright ©The authors 2022.)

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 FcεR1-stimulated and IFN-γ-stimulated signatures were enriched in SA. A FcεR1-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-κB (nuclear factor-κB), and IL-1β/TNF-α (tumor necrosis factor-α) pathway activation. The IFN-γ-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.

Asthma outcomes remain suboptimal, despite effective pharmacotherapy. Psychological dysfunction (such as anxiety) is common, and associated with poorer outcomes. We evaluated a digital mindfulness programme as an intervention to improve asthma-related quality of life for primary care patients, in a prospectively registered randomized-controlled feasibility study. We offered 'Headspace', a widely-used digital mindfulness intervention, to adults with asthma through 16 UK GP practices. Participants were randomized on a 2:1 basis to the mindfulness intervention, or waitlist control. Participants completed questionnaires (including asthma symptom control, asthma-related quality of life, anxiety, depression) at baseline, 6-week and 3-month follow-up. 116 participants completed primary outcomes at 3-month follow-up: intervention 73 (79%), control 43 (84%). Compared to baseline, the intervention group but not the control group reported significantly improved asthma-related quality of life, with a between-group difference favoring the intervention group that was not significant (Mean difference = 0.15, 95%CI - 0.13 to 0.42). Intervention use varied (ranging from 0 to 192 times) but was generally high. Digital mindfulness interventions are feasible and acceptable adjunct treatments for mild and moderate asthma to target quality of life. Further research should adapt 'generic' mindfulness-based stress-reduction to maximize effectiveness for asthma, and validate our findings in a fully-powered randomized controlled trial.Trial registration Prospectively registered: ISRCTN52212323., (© 2021. The Author(s).)

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 H 2, and T H 17/T H 22 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 T H 22/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., (Copyright © 2021 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Background: Understanding why patients with severe asthma do not follow healthcare provider (HCP) advice to adjust treatment is critical to achieving personalised disease management., Methods: We reviewed patient choice to follow HCP advice to adjust asthma treatment in a UK-based randomised, controlled, single-blind (study participant), multicentre, parallel group 48-week clinical study comparing biomarker-directed treatment adjustment with standard care in severe asthma., Results: Of 1572 treatment advisories (291 participants), instructions were followed in 1377 cases (87.6%). Patients were more likely to follow advice to remain on treatment (96.7%) than to either reduce (70.3%) or increase (67.1%) their treatment, with 64% of patients following all treatment advice. Multivariate analysis associated belonging to an ethnic minority group (OR 3.10, 95% CI 1.68-5.73) and prior study medication changes (two or more changes: OR 2.77, 95% CI 1.51-5.10) with failure to follow treatment advice. In contrast, emergency room attendance in the prior year (OR 0.54, 95% CI 0.32-0.92) was associated with following treatment advice. The largest effect was seen with transition onto or off oral corticosteroids (OR 29.28, 95% CI 16.07-53.36) when compared with those requested to maintain treatment. Centre was also an important determinant regarding the likelihood of patients to follow treatment advice., Conclusions: Belonging to an ethnic minority group and multiple prior treatment adjustments were associated with not following HCP treatment advice. Patients also responded differently to HCP advice across UK specialist centres. These findings have implications for the generalisability of models of care in severe asthma and require further focused studies., Competing Interests: Conflict of interest: J. Busby has nothing to disclose. Conflict of interest: J.G. Matthews has nothing to disclose. Conflict of interest: R. Chaudhuri reports grants, personal fees for advisory board work and nonfinancial support for meeting attendance from AstraZeneca, personal fees for advisory board work from GlaxoSmithKline and Novartis, personal fees for advisory board work and nonfinancial support for meeting attendance from Chiesi, nonfinancial support for meeting attendance from Napp Pharmaceuticals, outside the submitted work. Conflict of interest: I.D. Pavord reports personal fees for lectures, advisory board honoraria, sponsorship to attend scientific meetings, and payments for organising educational events from AstraZeneca, personal fees for lectures, advisory board honoraria, and sponsorship to attend scientific meetings from Boehringer Ingelheim and GlaxoSmithKline, personal fees for lectures from Aerocrine and Chiesi, personal fees for lectures and advisory board honoraria from Almirall and Novartis, advisory board honoraria from Genentech, Regeneron, Sanofi, Circassia and Knopp, personal fees for lectures, payments for organising educational events, and sponsorship to attend scientific meetings from Teva, grants from the National Institute for Health Research, outside the submitted work. Conflict of interest: T.C. Hardman has nothing to disclose. Conflict of interest: J.R. Arron has patents “Diagnosis and treatments relating to Th2 inhibition” (US 9,684,000 B2) and “Diagnosis and treatments relating to Th2 inhibition” (US 9,995,755 B2) issued with rights assigned to Genentech, a member of the Roche group, and is an employee of Genentech, Inc. and owns stocks/options in the Roche group. Conflict of interest: P. Bradding reports grants from Genentech, other (consultancy work on behalf of the University of Leicester) from Roche and Boehringer Ingelheim, outside the submitted work. Conflict of interest: C.E. Brightling reports grants and personal fees from GlaxoSmithKline, AstraZeneca, Sanofi, Novartis, Chiesi, Genentech, Gossamer, Mologic and 4D Pharma, all paid to the institution and outside the submitted work. Conflict of interest: D.F. Choy is an employee of Genentech, Inc. and owns stocks/options in the Roche group. Conflict of interest: D.C. Cowan has nothing to disclose. Conflict of interest: R. Djukanovic reports receiving fees for lectures at symposia organised by Novartis, AstraZeneca and Teva, consultation for Teva and Novartis as member of advisory boards, and participation in a scientific discussion about asthma organised by GlaxoSmithKline; he is a co-founder and current consultant, and has shares in Synairgen, a University of Southampton spin-out company. Conflict of interest: C.E. Hanratty has nothing to disclose. Conflict of interest: T.W. Harrison reports grants, personal fees and nonfinancial support from AstraZeneca, grants and personal fees from GlaxoSmithKline, personal fees from Vectura, Synairgen and Chiesi, outside the submitted work. Conflict of interest: C.T. Holweg is an employee and stock owner of Genentech Inc., a member of the Roche Group, outside the submitted work. Conflict of interest: P.H. Howarth reports employment by GlaxoSmithKline. Conflict of interest: S.J. Fowler reports personal fees for lectures and support to attend an international conference from AstraZeneca, grants and personal fees for lectures from Boehringer Ingelheim, personal fees for lectures, participation in an advisory board, and support to attend an national conference from Chiesi, personal fees for lectures from GlaxoSmithKline, Novartis and Teva, outside the submitted work. Conflict of interest: J.L. Lordan has nothing to disclose. Conflict of interest: A.H. Mansur reports personal and institution payment for talks, advisory board meetings, sponsorship to attend conferences and education grants for service developments from GlaxoSmithKline, AstraZeneca, Novartis, Sanofi, Teva and others, outside the submitted work. Conflict of interest: A. Menzies-Gow reports grants and personal fees from AstraZeneca, personal fees from Novartis, GlaxoSmithKline, Sanofi and Vectura, personal fees and nonfinancial support from Teva and Boehringer Ingelheim, outside the submitted work. Conflict of interest: R.M. Niven has received lecture fees, advisory board activity and been supported to attend international meetings/conferences in the last 5 years by the following companies: AstraZeneca, Boehringer, Boston Scientific, Chiesi, Napp, Novartis and Teva. None of these have any relevance to the manuscript; R.M. Niven owns no shares or stocks and is not personally or in any family way connected to any pharmaceutical companies. Conflict of interest: D.S. Robinson has nothing to disclose. Conflict of interest: S.M. Walker has nothing to disclose. Conflict of interest: A. Woodcock reports personal fees for lectures from GlaxoSmithKline, personal fees for lectures and consultancy from Novartis, personal fees for consultancy from Chiesi, other (chairing research projects) from Reacta Biotech, Axalbion and Medicines Evaluation Unit, outside the submitted work. Conflict of interest: L.G. Heaney reports other (sponsorship for meeting attendance) from AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline and Napp Pharmaceutical, personal fees for lectures and advisory board work from Novartis, Hoffman la Roche/Genentech Inc., Sanofi, GlaxoSmithKline, AstraZeneca, Teva, Theravance and Circassia, grants from Medimmune, Novartis UK, Roche/Genentech Inc., and GlaxoSmithKline, and is academic lead for the Medical Research Council Stratified Medicine UK Consortium in severe asthma, which involves industrial partnerships with Amgen, Genentech/Hoffman la Roche, AstraZeneca, Medimmune, GlaxoSmithKline, Aerocrine and Vitalograph, outside the submitted work., (Copyright ©The authors 2022.)

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., (Crown Copyright © 2021. Published by Elsevier Inc. All rights reserved.)

Background: Blood eosinophil measurement is essential for the phenotypic characterization of patients with difficult asthma and in determining eligibility for anti-IL-5/IL-5Rα biological therapies. However, assessing such measures over limited time spans may not reveal the true underlying eosinophilic phenotype, as treatment, including daily oral corticosteroid therapy, suppresses eosinophilic inflammation and asthma is intrinsically variable., Methods: We interrogated the electronic healthcare records of patients in the Wessex AsThma CoHort of difficult asthma (WATCH) study (UK). In 501 patients being evaluated in this tertiary care centre for difficult to control asthma, all requested full blood count test results in a 10-year retrospective period from the index WATCH assessment were investigated (n = 11,176)., Results: In 235 biological therapy-naïve participants who had 10 or more measures in this time period, 40.3% were eosinophilic (blood eosinophils ≥300 cells/µl) at WATCH enrolment whilst an additional 43.1%, though not eosinophilic at enrolment, demonstrated eosinophilia at least once in the preceding decade. Persistent eosinophilia was associated with worse post-bronchodilator airway obstruction and higher Fractional exhaled Nitric Oxide (FeNO). In contrast, the 16.6% of patients who never demonstrated eosinophilia at this blood eosinophil threshold showed preserved lung function and lower markers of Type 2 inflammation., Conclusions: This highlights the central role that type 2 inflammation, as indicated by blood eosinophilia, has in difficult asthma and suggests that longitudinal electronic healthcare record analysis can be an important tool in clinical asthma phenotyping, providing insight that may help understand disease progression and better guide more specific treatment approaches., (© 2021 The Authors. Clinical & Experimental Allergy published by John Wiley & Sons Ltd.)

Background: Airway remodelling, which may include goblet cell hyperplasia / hypertrophy, changes in epithelial integrity, accumulation of extracellular matrix components, smooth muscle hypertrophy and thickening of the lamina reticularis, is a feature of severe asthma and contributes to the clinical phenotype., Objective: Within the U-BIOPRED severe asthma study, we have assessed histological elements of airway remodelling and their relationship to computed tomography (CT) measures of proximal airway dimensions., Methods: Bronchial biopsies were collected from two severe asthma groups, one non-smoker (SAn, n = 28) and one current/ex-smoker (SAs/ex, n = 13), and a mild-moderate asthma group (MMA, n = 28) classified and treated according to GINA guidelines, plus a healthy control group (HC, n = 33). Movat's pentachrome technique was used to identify mucin, elastin and total collagen in these biopsies. The number of goblet cells (mucin+) was counted as a percentage of the total number of epithelial cells and the percentage mucin epithelial area measured. The percentage area of elastic fibres and total collagen within the submucosa was also measured, and the morphology of the elastic fibres classified. Participants in the asthma groups also had a CT scan to assess large airway morphometry., Results: The submucosal tissue elastin percentage was higher in both severe asthma groups (16.1% SAn, 18.9% SAs/ex) compared with the HC (9.7%) but did not differ between asthma groups. There was a positive relationship between elastin and airway wall area measured by CT (n = 18-20, rho=0.544, p = 0.024), which also related to an increase in elastic fibres with a thickened lamellar morphological appearance. Mucin epithelial area and total collagen were not different between the four groups. Due to small numbers of suitable CT scans, it was not feasible to compare airway morphometry between the asthma groups., Conclusion: These findings identify a link between extent of elastin deposition and airway wall thickening in severe asthma., (© 2020 The Authors. Clinical & Experimental Allergy published by John Wiley & Sons Ltd.)

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.

Rationale: New approaches are needed to guide personalized treatment of asthma. Objectives: To test if urinary eicosanoid metabolites can direct asthma phenotyping. Methods: Urinary metabolites of prostaglandins (PGs), cysteinyl leukotrienes (CysLTs), and isoprostanes were quantified in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) study including 86 adults with mild-to-moderate asthma (MMA), 411 with severe asthma (SA), and 100 healthy control participants. Validation was performed internally in 302 participants with SA followed up after 12-18 months and externally in 95 adolescents with asthma. Measurement and Main Results: Metabolite concentrations in healthy control participants were unrelated to age, body mass index, and sex, except for the PGE 2 pathway. Eicosanoid concentrations were generally greater in participants with MMA relative to healthy control participants, with further elevations in participants with SA. However, PGE 2 metabolite concentrations were either the same or lower in male nonsmokers with asthma than in healthy control participants. Metabolite concentrations were unchanged in those with asthma who adhered to oral corticosteroid treatment as documented by urinary prednisolone detection, whereas those with SA treated with omalizumab had lower concentrations of LTE 4 and the PGD 2 metabolite 2,3-dinor-11β-PGF 2α . High concentrations of LTE 4 and PGD 2 metabolites were associated with lower lung function and increased amounts of exhaled nitric oxide and eosinophil markers in blood, sputum, and urine in U-BIOPRED participants and in adolescents with asthma. These type 2 (T2) asthma associations were reproduced in the follow-up visit of the U-BIOPRED study and were found to be as sensitive to detect T2 inflammation as the established biomarkers. Conclusions: Monitoring of urinary eicosanoids can identify T2 asthma and introduces a new noninvasive approach for molecular phenotyping of adult and adolescent asthma.Clinical trial registered with www.clinicaltrials.gov (NCT01976767).

Background: Asthma treatment guidelines recommend increasing corticosteroid dose to control symptoms and reduce exacerbations. This approach is potentially flawed because symptomatic asthma can occur without corticosteroid responsive type-2 (T2)-driven eosinophilic inflammation, and inappropriately high-dose corticosteroid treatment might have little therapeutic benefit with increased risk of side-effects. We compared a biomarker strategy to adjust corticosteroid dose using a composite score of T2 biomarkers (fractional exhaled nitric oxide [FENO], blood eosinophils, and serum periostin) with a standardised symptom-risk-based algorithm (control)., Methods: We did a single-blind, parallel group, randomised controlled trial in adults (18-80 years of age) with severe asthma (at treatment steps 4 and 5 of the Global Initiative for Asthma) and FENO of less than 45 parts per billion at 12 specialist severe asthma centres across England, Scotland, and Northern Ireland. Patients were randomly assigned (4:1) to either the biomarker strategy group or the control group by an online electronic case-report form, in blocks of ten, stratified by asthma control and use of rescue systemic steroids in the previous year. Patients were masked to study group allocation throughout the entirety of the study. Patients attended clinic every 8 weeks, with treatment adjustment following automated treatment-group-specific algorithms: those in the biomarker strategy group received a default advisory to maintain treatment and those in the control group had their treatment adjusted according to the steps indicated by the trial algorithm. The primary outcome was the proportion of patients with corticosteroid dose reduction at week 48, in the intention-to-treat (ITT) population. Secondary outcomes were inhaled corticosteroid (ICS) dose at the end of the study; cumulative dose of ICS during the study; proportion of patients on maintenance oral corticosteroids (OCS) at study end; rate of protocol-defined severe exacerbations per patient year; time to first severe exacerbation; number of hospital admissions for asthma; changes in lung function, Asthma Control Questionnaire-7 score, Asthma Quality of Life Questionnaire score, and T2 biomarkers from baseline to week 48; and whether patients declined to progress to OCS. A secondary aim of our study was to establish the proportion of patients with severe asthma in whom T2 biomarkers remained low when corticosteroid therapy was decreased to a minimum ICS dose. This study is registered with ClinicalTrials.gov, NCT02717689 and has been completed., Findings: Patients were recruited from Jan 8, 2016, to July 12, 2018. Of 549 patients assessed, 301 patients were included in the ITT population and were randomly assigned to the biomarker strategy group (n=240) or to the control group (n=61). 28·4% of patients in the biomarker strategy group were on a lower corticosteroid dose at week 48 compared with 18·5% of patients in the control group (adjusted odds ratio [aOR] 1·71 [95% CI 0·80-3·63]; p=0·17). In the per-protocol (PP) population (n=121), a significantly greater proportion of patients were on a lower corticosteroid dose at week 48 in the biomarker strategy group (30·7% of patients) compared with the control group (5·0% of patients; aOR 11·48 [95% CI 1·35-97·83]; p=0·026). Patient choice to not follow treatment advice was the principle reason for loss to PP analysis. There was no difference in secondary outcomes between study groups and no loss of asthma control among patients in the biomarker strategy group who reduced their corticosteroid dose., Interpretation: Biomarker-based corticosteroid adjustment did not result in a greater proportion of patients reducing corticosteroid dose versus control. Understanding the reasons for patients not following treatment advice in both treatment strategies is an important area for future research. The prevalence of T2 biomarker-low severe asthma was low., Funding: This study was funded, in part, by the Medical Research Council UK., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Asthma is a heterogeneous disease characterized by distinct phenotypes with associated microbial dysbiosis., Objectives: Our aim was to identify severe asthma phenotypes based on sputum microbiome profiles and assess their stability after 12 to 18 months. A further aim was to evaluate clusters' robustness after inclusion of an independent cohort of patients with mild-to-moderate asthma., Methods: In this longitudinal multicenter cohort study, sputum samples were collected for microbiome profiling from a subset of the Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adult patient cohort at baseline and after 12 to 18 months of follow-up. Unsupervised hierarchical clustering was performed by using the Bray-Curtis β-diversity measure of microbial profiles. For internal validation, partitioning around medoids, consensus cluster distribution, bootstrapping, and topological data analysis were applied. Follow-up samples were studied to evaluate within-patient clustering stability in patients with severe asthma. Cluster robustness was evaluated by using an independent cohort of patients with mild-to-moderate asthma., Results: Data were available for 100 subjects with severe asthma (median age 55 years; 42% males). Two microbiome-driven clusters were identified; they were characterized by differences in asthma onset, smoking status, residential locations, percentage of blood and/or sputum neutrophils and macrophages, lung spirometry results, and concurrent asthma medications (all P values < .05). The cluster 2 patients displayed a commensal-deficient bacterial profile that was associated with worse asthma outcomes than those of the cluster 1 patients. Longitudinal clusters revealed high relative stability after 12 to 18 months in those with severe asthma. Further inclusion of an independent cohort of 24 patients with mild-to-moderate asthma was consistent with the clustering assignments., Conclusion: Unbiased microbiome-driven clustering revealed 2 distinct robust phenotypes of severe asthma that exhibited relative overtime stability. This suggests that the sputum microbiome may serve as a biomarker for better characterizing asthma phenotypes., (Copyright © 2020 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Asthma is a diverse condition that differs with age and sex. However, it remains unclear how sex, age of asthma onset, and/or their interaction influence clinical expression of more problematic adult "difficult" asthma., Objectives: To better understand the clinical features of difficult asthma within a real-world clinical setting using novel phenotypic classification, stratifying subjects by sex and age of asthma onset., Methods: Participants in a longitudinal difficult asthma clinical cohort study (Wessex AsThma CoHort of difficult asthma; WATCH), United Kingdom (n = 501), were stratified into 4 difficult asthma phenotypes based on sex and age of asthma onset (early <18 years or adult ≥18 years) and characterized in relation to clinical and pathophysiological features., Results: The cohort had more female participants (65%) but had similar proportions of participants with early- or adult-onset disease. Early-onset female disease was commonest (35%), highly atopic, with good spirometry and strong associations with some physical comorbidities but highest psychophysiologic comorbidities. Adult-onset females also had considerable psychophysiologic comorbidities and highest obesity, and were least atopic. Amongst male subjects, proportionately more had adult-onset disease. Early-onset male disease was rarest (14%) but associated with worst lung function, high smoking, atopy, and fungal sensitization. Despite shortest disease duration, adult-onset males had highest use of maintenance oral corticosteroid, poor lung function, and highest fractional exhaled nitrogen oxide in spite of highest smoking prevalence., Conclusions: This study shows that sex, age of asthma onset, and their interactions influence different clinical manifestations of difficult asthma and identifies a greater risk for lung function loss and oral corticosteroid dependence associated with smoking in adult-onset male subjects., (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2020 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Background: Effective treatment for severe asthma is a significant unmet need. While eosinophilic inflammation caused by type 2 cytokines is responsive to corticosteroid and biologic therapies, many severe asthmatics exhibit corticosteroid-unresponsive mixed granulocytic inflammation., Objective: Here, we tested the hypothesis that the pro-allergic cytokine, IL-13, can drive both corticosteroid-sensitive and corticosteroid-resistant responses., Results: By integration of in vivo and in vitro models of IL-13-driven inflammation, we identify a role for the epidermal growth factor receptor (EGFR/ERBB1) as a mediator of corticosteroid-unresponsive inflammation and bronchial hyperresponsiveness driven by IL-13. Topological data analysis using human epithelial transcriptomic data from the U-BIOPRED cohort identified severe asthma groups with features consistent with the presence of IL-13 and EGFR/ERBB activation, with involvement of distinct EGFR ligands. Our data suggest that IL-13 may play a dual role in severe asthma: on the one hand driving pathologic corticosteroid-refractory mixed granulocytic inflammation, but on the other hand underpinning beneficial epithelial repair responses, which may confound responses in clinical trials., Conclusion and Clinical Relevance: Detailed dissection of those molecular pathways that are downstream of IL-13 and utilize the ERBB receptor and ligand family to drive corticosteroid-refractory inflammation should enhance the development of new treatments that target this sub-phenotype(s) of severe asthma, where there is an unmet need., (© 2020 The Authors. Clinical & Experimental Allergy published by John Wiley & Sons Ltd.)

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., (© 2019 The Authors. Allergy published by John Wiley & Sons Ltd.)

Little is known about the characteristics and treatments of patients with severe asthma across Europe, but both are likely to vary. This is the first study in the European Respiratory Society Severe Heterogeneous Asthma Research collaboration, Patient-centred (SHARP) Clinical Research Collaboration and it is designed to explore these variations. Therefore, we aimed to compare characteristics of patients in European severe asthma registries and treatments before starting biologicals.This was a cross-sectional retrospective analysis of aggregated data from 11 national severe asthma registries that joined SHARP with established patient databases.Analysis of data from 3236 patients showed many differences in characteristics and lifestyle factors. Current smokers ranged from 0% (Poland and Sweden) to 9.5% (Belgium), mean body mass index ranged from 26.2 (Italy) to 30.6 kg·m -2 (the UK) and the largest difference in mean pre-bronchodilator forced expiratory volume in 1 s % predicted was 20.9% (the Netherlands versus Hungary). Before starting biologicals patients were treated differently between countries: mean inhaled corticosteroid dose ranged from 700 to 1335 µg·day -1 between those from Slovenia versus Poland when starting anti-interleukin (IL)-5 antibody and from 772 to 1344 µg·day -1 in those starting anti-IgE (Slovenia versus Spain). Maintenance oral corticosteroid use ranged from 21.0% (Belgium) to 63.0% (Sweden) and from 9.1% (Denmark) to 56.1% (the UK) in patients starting anti-IL-5 and anti-IgE, respectively.The severe asthmatic population in Europe is heterogeneous and differs in both clinical characteristics and treatment, often appearing not to comply with the current European Respiratory Society/American Thoracic Society guidelines definition of severe asthma. Treatment regimens before starting biologicals were different from inclusion criteria in clinical trials and varied between countries., Competing Interests: Conflict of interest: J.J.M.H. van Bragt has nothing to disclose. Conflict of interest: I.M. Adcock has nothing to disclose. Conflict of interest: E.H.D. Bel reports grants and personal fees from AstraZeneca, GSK and Novartis, grants from Teva, and personal fees from Boehringer Ingelheim, Sanofi/Regeneron, Vectura and Sterna, outside the submitted work. Conflict of interest: G-J. Braunstahl reports grants from GSK, Novartis, AstraZeneca and Chiesi, outside the submitted work. Conflict of interest: A. Ten Brinke reports institutional fees for research advisory boards and lectures from GSK, Teva and AstraZeneca, institutional fees for research advisory boards from Sanofi, Novartis and Boehringer Ingelheim, outside the submitted work. Conflict of interest: J. Busby has nothing to disclose. Conflict of interest: G.W. Canonica reports personal fees from A. Menarini, AstraZeneca, Boehringer Ingelheim, Chiesi Farmaceutici, Circassia, GSK, MSD, Novartis, Roche, Sanofi-Aventis and Teva, during the conduct of the study. Conflict of interest: H. Cao is an employee of Novartis, which is one of the funding pharmaceutical companies of SHARP. Conflict of interest: K.F. Chung has received honoraria for participating in advisory board meetings from GSK, AstraZeneca, Novartis, Merck, Boehringer Ingelheim and Teva regarding treatments for asthma and chronic obstructive pulmonary disease and has also been remunerated for speaking engagements. Conflict of interest: Z. Csoma has nothing to disclose. Conflict of interest: B. Dahlén reports advisory board membership for Teva, GSK and Sanofi, personal fees for lectures from AstraZeneca, outside the submitted work. Conflict of interest: E. Davin has nothing to disclose. Conflict of interest: S. Hansen has nothing to disclose. Conflict of interest: E. Heffler reports personal fees from AstraZeneca, Sanofi Genzyme, Teva, Novartis, GSK, Circassia and Nestle Purina, outside the submitted work. Conflict of interest: I. Horvath reports personal fees from AstraZeneca, Boehringer Ingelheim, GSK, Chiesi, Berlin-Chemie, Roche, MSD, CSL and Sager Pharma, outside the submitted work. Conflict of interest: S. Korn reports personal fees from Almirall, AstraZeneca, Boehringer Ingelheim, Chiesi, Teva and Roche, grants and personal fees from GSK and Novartis, during the conduct of the study. Conflict of interest: M. Kots is a full time Chiesi Famaceutici SpA employee, Global clinical development department. Conflict of interest: P. Kuna reports personal fees for lectures and advisory board work from AstraZeneca and Novartis, personal fees for lectures and nonfinancial support for meeting attendance from Berlin-Chemie, Menarini and Boehringer Ingelheim, outside the submitted work. Conflict of interest: N. Kwon is an employee of GSK. Conflict of interest: R. Louis reports grants and personal fees for advisory board work from GSK, AstraZeneca and Novartis, grants from Chiesi, outside the submitted work. Conflict of interest: V. Plaza reports grants, personal fees and nonfinancial support from Chiesi, grants and personal fees from AstraZeneca, personal fees from ALK, Mundipharma and Sanofi, grants from Menarini, outside the submitted work. Conflict of interest: C. Porsbjerg has nothing to disclose. Conflict of interest: D. Ramos-Barbon has nothing to disclose. Conflict of interest: L.B. Richards has nothing to disclose. Conflict of interest: S. Škrgat reports personal fees for lectures and scientific discussion at symposia from Teva and Boehringer, personal fees for lectures and advisory boards from AstraZeneca, Glaxo, Berlin-Chemie and Chiesi, outside the submitted work. Conflict of interest: J.K. Sont has nothing to disclose. Conflict of interest: S.J.H. Vijverberg has nothing to disclose. Conflict of interest: E.J. Weersink has nothing to disclose. Conflict of interest: V. Yasinska has nothing to disclose. Conflict of interest: S.S. Wagers reports consultancy fees from the European Respiratory Society, during the conduct of the study; consultancy fees from King's College Hospital NHS Foundation Trust, Academic Medical Research, AMC Medical Research BV, Asthma UK, Athens Medical School, Boehringer Ingelheim International GmbH, CHU de Toulouse, CIRO, DS Biologicals Ltd, École Polytechnique Fédérale de Lausanne, European Respiratory Society, FISEVI, Fluidic Analytics Ltd, Fraunhofer IGB, Fraunhofer ITEM, GSK R&D Ltd, Holland and Knight, Karolinska Institutet Fakturor, KU Leuven, Longfonds, National Heart and Lung Institute, Novartis Pharma AG, Owlstone Medical Ltd, PExA AB, UCB Biopharma SPRL, UCB Biosciences GmbH, Umeå University, University Hospital Southampton NHS Foundation Trust, Università Campus Bio-Medico di Roma, Universita Cattolica Del Sacro Cuore, Universität Ulm, University of Bern, University of Edinburgh, University of Hull, University of Leicester, University of Loughborough, University of Luxembourg, University of Manchester, University of Nottingham, Vlaams Brabant, Dienst Europa, Imperial College London, Boehringer Ingelheim, Breathomix, Gossamer Bio, AstraZeneca and CIBER, outside the submitted work. Conflict of interest: R. Djukanovic reports receiving fees for lectures at symposia organised by Novartis, AstraZeneca and Teva, consultation for Teva and Novartis as member of advisory boards, and participation in a scientific discussion about asthma organised by GSK; and is a co-founder and current consultant, and has shares in Synairgen, a University of Southampton spin out company. Conflict of interest: A.H. Maitland-van der Zee reports personal fees for participating in an advisory board from AstraZeneca and Boehringer Ingelheim, unrestricted research grants from Boehringer Ingelheim and GSK., (Copyright ©ERS 2020.)

This document provides clinical recommendations for the management of severe asthma. Comprehensive evidence syntheses, including meta-analyses, were performed to summarise all available evidence relevant to the European Respiratory Society/American Thoracic Society Task Force's questions. The evidence was appraised using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach and the results were summarised in evidence profiles. The evidence syntheses were discussed and recommendations formulated by a multidisciplinary Task Force of asthma experts, who made specific recommendations on six specific questions. After considering the balance of desirable and undesirable consequences, quality of evidence, feasibility, and acceptability of various interventions, the Task Force made the following recommendations: 1) suggest using anti-interleukin (IL)-5 and anti-IL-5 receptor α for severe uncontrolled adult eosinophilic asthma phenotypes; 2) suggest using a blood eosinophil cut-point ≥150 μL -1 to guide anti-IL-5 initiation in adult patients with severe asthma; 3) suggest considering specific eosinophil (≥260 μL -1 ) and exhaled nitric oxide fraction (≥19.5 ppb) cut-offs to identify adolescents or adults with the greatest likelihood of response to anti-IgE therapy; 4) suggest using inhaled tiotropium for adolescents and adults with severe uncontrolled asthma despite Global Initiative for Asthma (GINA) step 4-5 or National Asthma Education and Prevention Program (NAEPP) step 5 therapies; 5) suggest a trial of chronic macrolide therapy to reduce asthma exacerbations in persistently symptomatic or uncontrolled patients on GINA step 5 or NAEPP step 5 therapies, irrespective of asthma phenotype; and 6) suggest using anti-IL-4/13 for adult patients with severe eosinophilic asthma and for those with severe corticosteroid-dependent asthma regardless of blood eosinophil levels. These recommendations should be reconsidered as new evidence becomes available., Competing Interests: Conflict of interest: F. Holguin has nothing to disclose. Conflict of interest: J.C. Cardet has nothing to disclose. Conflict of interest: K.F. Chung has received honoraria for participating in advisory board meetings of GlaxoSmithKline, AstraZeneca, Novartis, Merck, Boehringer Ingelheim, 4D Pharma, Pieris and Teva regarding treatments for asthma, cough and chronic obstructive pulmonary disease and has also been remunerated for speaking engagements. Conflict of interest: S. Diver has nothing to disclose. Conflict of interest: D.S. Ferreira reports fellowship MTF 2015-02 from the European Respiratory Society, during the conduct of the study. Conflict of interest: A. Fitzpatrick has nothing to disclose. Conflict of interest: M. Gaga reports grants and personal fees from AstraZeneca and Chiesi, grants from Novartis, Menarini and Elpen, personal fees from MSD and BMS, outside the submitted work. Conflict of interest: L. Kellermeyer has nothing to disclose. Conflict of interest: S. Khurana reports grants from GlaxoSmithKline and Sanofi, outside the submitted work. Conflict of interest: S. Knight has nothing to disclose. Conflict of interest: V.M. McDonald reports grants from GlaxoSmithKline, grants and personal fees for lectures from AstraZeneca, personal fees for educational steering committee work from Menarini, outside the submitted work. Conflict of interest: R.L. Morgan has nothing to disclose. Conflict of interest: V.E. Ortega has nothing to disclose. Conflict of interest: D. Rigau acts as a European Respiratory Society methodologist. Conflict of interest: P. Subbarao has nothing to disclose. Conflict of interest: T. Tonia acts as a European Respiratory Society methodologist. Conflict of interest: I.M. Adcock has nothing to disclose. Conflict of interest: E.R. Bleecker undertaken clinical trials through his employer, Wake Forest School of Medicine and University of Arizona, for AstraZeneca, MedImmune, Boehringer Ingelheim, Genentech, Johnson and Johnson (Janssen), Novartis, Regeneron and Sanofi Genzyme, and has also served as a paid consultant for AstraZeneca, MedImmune, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Regeneron and Sanofi Genzyme, outside the submitted work. Conflict of interest: C. Brightling reports grants and personal fees from GlaxoSmithKline, Novartis, Genentech/Roche, Chiesi, 4D Pharma, Glenmark, Boehringer Ingelheim, Mologic, Gossamer and AstraZeneca/MedImmune, personal fees from Sanofi/Regeneron and Teva, outside the submitted work. Conflict of interest: L-P. Boulet reports research grants for participation in multicentre studies from AstraZeneca, Boston Scientific, GlaxoSmithKline, Hoffman La Roche, Novartis, Ono Pharma, Sanofi and Takeda; support for research projects submitted by the investigator from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Merck and Takeda; consulting and advisory board work for AstraZeneca, GlaxoSmithKline, Novartis and Methapharm; nonprofit grants for production of educational materials from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Merck Frosst and Novartis; conference fees from AstraZeneca, GlaxoSmithKline, Merck and Novartis; support for participation in conferences and meetings from Novartis and Takeda. Conflict of interest: M. Cabana reports personal fees for consultancy from Genentech and Novartis, outside the submitted work. Conflict of interest: M. Castro receives university grant funding from NIH, American Lung Association and PCORI; receives pharmaceutical grant funding from AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline, Novartis and Sanofi-Aventis; is a consultant for Aviragen, Boston Scientific, Genentech, Nuvaira, Neutronic, Therabron, Theravance, Vectura, 4D Pharma, VIDA, Mallinckrodt, Teva and Sanofi-Aventis; is a speaker for AstraZeneca, Boehringer Ingelheim, Boston Scientific, Genentech, Regeneron, Sanofi and Teva; and receives royalties from Elsevier. Conflict of interest: P. Chanez has undertaken consultancy services for Boehringer Ingelheim, GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi, Sanofi and SNCF, served on advisory boards for Boehringer Ingelheim, GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi and Sanofi, received lecture fees from GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi, Boston Scientific and ALK, and received industry-sponsored grants from AstraZeneca, ALK and Novartis. Conflict of interest: A. Custovic reports personal fees for consultancy from Novartis, Regeneron/Sanofi, Boehringer Ingelheim and Philips, personal fees for lectures from Thermo Fisher Scientific and Novartis, outside the submitted work. Conflict of interest: R. Djukanovic reports receiving fees for lectures at symposia organised by Novartis, AstraZeneca and Teva, consultation for Teva and Novartis as member of advisory boards, and participation in a scientific discussion about asthma organised by GlaxoSmithKline; and is a co-founder of and current consultant for, and has shares in, Synairgen, a University of Southampton spin-out company. Conflict of interest: U. Frey reports personal fees for meeting attendance from GlaxoSmithKline Scientific Advisory Board, outside the submitted work. Conflict of interest: B. Frankemölle has nothing to disclose. Conflict of interest: P. Gibson reports grants and personal fees for educational activities from GlaxoSmithKline, grants and personal fees for lectures and educational activities from AstraZeneca, personal fees for educational steering committee work from Novartis and Sanofi, outside the submitted work. Conflict of interest: D. Hamerlijnck is independent European Federation of Allergy and Airways (EFA) patient advisor to Novartis on patient involvement; patient co-chair of the ERS Severe Heterogeneous Asthma Registry, Patient-centred CRC; member of the scientific advisory board of the Veelbelovende Zorg for ZIN and ZonMw; member of the scientific advisory board of the BENEFIT (ZonMw–KBC Dutch Belgian collaboration); member of the IMI PARADIGM patient advisory group for EPF; member of the scientific advisory board for ERA-NET NEURON Biomarkers; patient reviewer for the Dutch Patient Federation and several ZonMw scientific committees. Conflict of interest: N. Jarjour reports the following, outside the submitted work: a grant from National Institutes of Health; personal fees for consultation from AstraZeneca and Boehringer Ingelheim. Conflict of interest: S. Konno reports grants from AstraZeneca, Kyorin Pharmaceutical, Japan Allergy Foundation, Novartis and Ministry of Education, Culture, Sports, Science and Technology of Japan, during the conduct of the study. Conflict of interest: H. Shen has nothing to disclose. Conflict of interest: C. Vitari has nothing to disclose. Conflict of interest: A. Bush has nothing to disclose., (Copyright ©ERS 2020.)