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Background: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features., Objective: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls., Methods: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes., Results: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts., Conclusion: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator., (Copyright © 2023 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

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: Asthma is a complex disease with multiple phenotypes that may differ in disease pathobiology and treatment response. IL33 single nucleotide polymorphisms (SNPs) have been reproducibly associated with asthma. IL33 levels are elevated in sputum and bronchial biopsies of patients with asthma. The functional consequences of IL33 asthma SNPs remain unknown., Objective: This study sought to determine whether IL33 SNPs associate with asthma-related phenotypes and with IL33 expression in lung or bronchial epithelium. This study investigated the effect of increased IL33 expression on human bronchial epithelial cell (HBEC) function., Methods: Association between IL33 SNPs (Chr9: 5,815,786-6,657,983) and asthma phenotypes (Lifelines/DAG [Dutch Asthma GWAS]/GASP [Genetics of Asthma Severity & Phenotypes] cohorts) and between SNPs and expression (lung tissue, bronchial brushes, HBECs) was done using regression modeling. Lentiviral overexpression was used to study IL33 effects on HBECs., Results: We found that 161 SNPs spanning the IL33 region associated with 1 or more asthma phenotypes after correction for multiple testing. We report a main independent signal tagged by rs992969 associating with blood eosinophil levels, asthma, and eosinophilic asthma. A second, independent signal tagged by rs4008366 presented modest association with eosinophilic asthma. Neither signal associated with FEV 1 , FEV 1 /forced vital capacity, atopy, and age of asthma onset. The 2 IL33 signals are expression quantitative loci in bronchial brushes and cultured HBECs, but not in lung tissue. IL33 overexpression in vitro resulted in reduced viability and reactive oxygen species-capturing of HBECs, without influencing epithelial cell count, metabolic activity, or barrier function., Conclusions: We identify IL33 as an epithelial susceptibility gene for eosinophilia and asthma, provide mechanistic insight, and implicate targeting of the IL33 pathway specifically in eosinophilic asthma., (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)

Background: The role of IL-17 immunity is well established in patients with inflammatory diseases, such as psoriasis and inflammatory bowel disease, but not in asthmatic patients, in whom further study is required., Objective: We sought to undertake a deep phenotyping study of asthmatic patients with upregulated IL-17 immunity., Methods: Whole-genome transcriptomic analysis was performed by using epithelial brushings, bronchial biopsy specimens (91 asthmatic patients and 46 healthy control subjects), and whole blood samples (n = 498) from the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort. Gene signatures induced in vitro by IL-17 and IL-13 in bronchial epithelial cells were used to identify patients with IL-17-high and IL-13-high asthma phenotypes., Results: Twenty-two of 91 patients were identified with IL-17, and 9 patients were identified with IL-13 gene signatures. The patients with IL-17-high asthma were characterized by risk of frequent exacerbations, airway (sputum and mucosal) neutrophilia, decreased lung microbiota diversity, and urinary biomarker evidence of activation of the thromboxane B2 pathway. In pathway analysis the differentially expressed genes in patients with IL-17-high asthma were shared with those reported as altered in psoriasis lesions and included genes regulating epithelial barrier function and defense mechanisms, such as IL1B, IL6, IL8, and β-defensin., Conclusion: The IL-17-high asthma phenotype, characterized by bronchial epithelial dysfunction and upregulated antimicrobial and inflammatory response, resembles the immunophenotype of psoriasis, including activation of the thromboxane B2 pathway, which should be considered a biomarker for this phenotype in further studies, including clinical trials targeting IL-17., (Copyright © 2019 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms., Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification., Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms., Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms., Conclusion: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies., (Copyright © 2019. Published by Elsevier Inc.)

Background: Severe asthma is a heterogeneous condition, as shown by independent cluster analyses based on demographic, clinical, and inflammatory characteristics. A next step is to identify molecularly driven phenotypes using "omics" technologies. Molecular fingerprints of exhaled breath are associated with inflammation and can qualify as noninvasive assessment of severe asthma phenotypes., Objectives: We aimed (1) to identify severe asthma phenotypes using exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses) and (2) to assess the stability of eNose-derived phenotypes in relation to within-patient clinical and inflammatory changes., Methods: In this longitudinal multicenter study exhaled breath samples were taken from an unselected subset of adults with severe asthma from the U-BIOPRED cohort. Exhaled metabolites were analyzed centrally by using an assembly of eNoses. Unsupervised Ward clustering enhanced by similarity profile analysis together with K-means clustering was performed. For internal validation, partitioning around medoids and topological data analysis were applied. Samples at 12 to 18 months of prospective follow-up were used to assess longitudinal within-patient stability., Results: Data were available for 78 subjects (age, 55 years [interquartile range, 45-64 years]; 41% male). Three eNose-driven clusters (n = 26/33/19) were revealed, showing differences in circulating eosinophil (P = .045) and neutrophil (P = .017) percentages and ratios of patients using oral corticosteroids (P = .035). Longitudinal within-patient cluster stability was associated with changes in sputum eosinophil percentages (P = .045)., Conclusions: We have identified and followed up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid use. This suggests that breath analysis can contribute to the management of severe asthma., (Copyright © 2018 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Background: Although several studies link high levels of IL-6 and soluble IL-6 receptor (sIL-6R) to asthma severity and decreased lung function, the role of IL-6 trans-signaling (IL-6TS) in asthmatic patients is unclear., Objective: We sought to explore the association between epithelial IL-6TS pathway activation and molecular and clinical phenotypes in asthmatic patients., Methods: An IL-6TS gene signature obtained from air-liquid interface cultures of human bronchial epithelial cells stimulated with IL-6 and sIL-6R was used to stratify lung epithelial transcriptomic data (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes [U-BIOPRED] cohorts) by means of hierarchical clustering. IL-6TS-specific protein markers were used to stratify sputum biomarker data (Wessex cohort). Molecular phenotyping was based on transcriptional profiling of epithelial brushings, pathway analysis, and immunohistochemical analysis of bronchial biopsy specimens., Results: Activation of IL-6TS in air-liquid interface cultures reduced epithelial integrity and induced a specific gene signature enriched in genes associated with airway remodeling. The IL-6TS signature identified a subset of patients with IL-6TS-high asthma with increased epithelial expression of IL-6TS-inducible genes in the absence of systemic inflammation. The IL-6TS-high subset had an overrepresentation of frequent exacerbators, blood eosinophilia, and submucosal infiltration of T cells and macrophages. In bronchial brushings Toll-like receptor pathway genes were upregulated, whereas expression of cell junction genes was reduced. Sputum sIL-6R and IL-6 levels correlated with sputum markers of remodeling and innate immune activation, in particular YKL-40, matrix metalloproteinase 3, macrophage inflammatory protein 1β, IL-8, and IL-1β., Conclusions: Local lung epithelial IL-6TS activation in the absence of type 2 airway inflammation defines a novel subset of asthmatic patients and might drive airway inflammation and epithelial dysfunction in these patients., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Adult-onset severe asthma is characterized by highly symptomatic disease despite high-intensity asthma treatments. Understanding of the underlying pathways of this heterogeneous disease is needed for the development of targeted treatments. Gene set variation analysis is a statistical technique used to identify gene profiles in heterogeneous samples., Objective: We sought to identify gene profiles associated with adult-onset severe asthma., Methods: This was a cross-sectional, observational study in which adult patients with adult-onset of asthma (defined as starting at age ≥18 years) as compared with childhood-onset severe asthma (<18 years) were selected from the U-BIOPRED cohort. Gene expression was assessed on the total RNA of induced sputum (n = 83), nasal brushings (n = 41), and endobronchial brushings (n = 65) and biopsies (n = 47) (Affymetrix HT HG-U133+ PM). Gene set variation analysis was used to identify differentially enriched predefined gene signatures of leukocyte lineage, inflammatory and induced lung injury pathways., Results: Significant differentially enriched gene signatures in patients with adult-onset as compared with childhood-onset severe asthma were identified in nasal brushings (5 signatures), sputum (3 signatures), and endobronchial brushings (6 signatures). Signatures associated with eosinophilic airway inflammation, mast cells, and group 3 innate lymphoid cells were more enriched in adult-onset severe asthma, whereas signatures associated with induced lung injury were less enriched in adult-onset severe asthma., Conclusions: Adult-onset severe asthma is characterized by inflammatory pathways involving eosinophils, mast cells, and group 3 innate lymphoid cells. These pathways could represent useful targets for the treatment of adult-onset severe asthma., (Copyright © 2017. Published by Elsevier Inc.)

Background: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided., Objectives: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum., Methods: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data., Results: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels., Conclusion: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways., (Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)