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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: 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.)

Type-2 (T2) immune responses in airway epithelial cells (AECs) classifies mild-moderate asthma into a T2-high phenotype. We examined whether currently available clinical biomarkers can predict AEC-defined T2-high phenotype within the U-BIOPRED cohort.The transcriptomic profile of AECs obtained from brushings of 103 patients with asthma and 44 healthy controls was obtained and gene set variation analysis used to determine the relative expression score of T2 asthma using a signature from interleukin (IL)-13-exposed AECs.37% of asthmatics (45% nonsmoking severe asthma, n=49; 33% of smoking or ex-smoking severe asthma, n=18; and 28% mild-moderate asthma, n=36) were T2-high using AEC gene expression. They were more symptomatic with higher exhaled nitric oxide fraction ( F ) and blood and sputum eosinophils, but not serum IgE or periostin. Sputum eosinophilia correlated best with the T2-high signature. eNO ) and blood and sputum eosinophils, but not serum IgE or periostin. Sputum eosinophilia correlated best with the T2-high signature. F ) gave a moderate prediction of T2-high asthma. Sputum IL-4, IL-5 and IL-13 protein levels did not correlate with gene expression.T2-high severe asthma can be predicted to some extent from raised levels of eNO , blood and sputum eosinophil counts, but serum IgE or serum periostin were poor predictors. Better bedside biomarkers are needed to detect T2-high.-1 ) gave a moderate prediction of T2-high asthma. Sputum IL-4, IL-5 and IL-13 protein levels did not correlate with gene expression.T2-high severe asthma can be predicted to some extent from raised levels of F eNO , blood and sputum eosinophil counts, but serum IgE or serum periostin were poor predictors. Better bedside biomarkers are needed to detect T2-high., Competing Interests: Conflict of interest: S. Pavlidis has nothing to disclose. Conflict of interest: K. Takahashi reports personal fees from Asahi General Hospital, during the conduct of the study. Conflict of interest: F. Ng Kee Kwong has nothing to disclose. Conflict of interest: J. Xie has nothing to disclose. Conflict of interest: U. Hoda has nothing to disclose. Conflict of interest: K. Sun has nothing to disclose. Conflict of interest: V. Elyasigomari has nothing to disclose. Conflict of interest: P. Agapow has nothing to disclose. Conflict of interest: M. Loza is employed by Janssen R&D and owns stock in parent company Johnson & Johnson, outside the submitted work. Conflict of interest: F. Baribaud reports being an employee of Janssen R&D and being a share holder of Johnson & Johnson. Conflict of interest: P. Chanez has provided consultancy services for Boehringer Ingelheim, Johnson & Johnson, GlaxoSmithKline, Merck Sharp & Dohme, AstraZeneca, Novartis, Teva, Chiesi, Sanofi and SNCF; served on advisory boards for Almirall, Boehringer Ingelheim, Johnson & Johnson, GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi and Sanofi; received lecture fees from Boehringer Ingelheim, Centocor, GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi, Boston Scientific and ALK; and received industry-sponsored grants from Roche, Boston Scientific, Boehringer Ingelheim, Centocor, GlaxoSmithKline, AstraZeneca, ALK, Novartis, Teva, ABscience and Chiesi. Conflict of interest: S.J. Fowler reports grants from IMI, during the conduct of the study; personal fees from GlaxoSmithKline, AstraZeneca, Boehringer Ingelheim and Novartis, outside the submitted work. Conflict of interest: D.E. Shaw reports personal fees for advisory board work from GSK, AZ, Teva and Boehringer Ingelheim, outside the submitted work. Conflict of interest: L.J. Fleming reports personal fees for advisory board work from Novartis, Vectura and Boehringer Ingelheim, grants from Asthma UK and BLF, and personal fees for speaking engagements from Novartis, outside the submitted work. Conflict of interest: P.H. Howarth reports grants from IMI, during the conduct of the study; part-time employment by GSK as Global Medical Expert, outside the submitted work. Conflict of interest: A.R. Sousa has nothing to disclose. Conflict of interest: J. Corfield has nothing to disclose. Conflict of interest: C. Auffray reports grants (U-BIOPRED Consortium IMI number 115010) from Innovative Medicine Initiative, during the conduct of the study. Conflict of interest: B. De Meulder reports grants (U-BIOPRED Consortium IMI number 115010) from Innovative Medicine Initiative, during the conduct of the study. Conflict of interest: R. Knowles is an employee of Knowles Consulting Ltd, outside the submitted work; and is a former employee (to 2011) and current shareholder in GlaxoSmithKline Ltd, and drug discovery consultant for Knowles Consulting Ltd, Peptinnovate Ltd and Imperial College London. Conflict of interest: P.J. Sterk reports grants from Innovative Medicines Initiative (IMI), during the conduct of the study. Conflict of interest: Y. Guo has nothing to disclose. Conflict of interest: I.M. Adcock reports personal fees for advisory board work from GSK, A-Z, Novartis, Boehringer Ingelheim and Vectura, grants from Pfizer, GSK, MRC, EU, BI and IMI, and personal fees for speaking from AZ and BI, outside the submitted work. Conflict of interest: R. Djukanovic reports personal fees for lectures at company sponsored symposia and consulting on advisory boards from TEVA, grants and personal fees for lectures at company sponsored symposia and consulting on advisory boards from Novartis, and personal fees for consultancy from and hold shares in Synairgen, outside the submitted work. Conflict of interest: K.F. Chung reports grants and personal fees for advisory board work from GlaxoSmithKline, personal fees for advisory board work and speaking from AstraZeneca and Novartis, grants and personal fees for advisory board work and speaking from Merck, and personal fees for advisory board work from Boehringer Ingelheim, TEVA and Menlo Therapeutics, outside the submitted work., (Copyright ©ERS 2019.)

Severe asthma patients with a significant smoking history have airflow obstruction with reported neutrophilia. We hypothesise that multi-omic analysis will enable the definition of smoking and ex-smoking severe asthma molecular phenotypes.The U-BIOPRED cohort of severe asthma patients, containing current-smokers (CSA), ex-smokers (ESA), nonsmokers and healthy nonsmokers was examined. Blood and sputum cell counts, fractional exhaled nitric oxide and spirometry were obtained. Exploratory proteomic analysis of sputum supernatants and transcriptomic analysis of bronchial brushings, biopsies and sputum cells was performed.Colony-stimulating factor (CSF)2 protein levels were increased in CSA sputum supernatants, with azurocidin 1, neutrophil elastase and CXCL8 upregulated in ESA. Phagocytosis and innate immune pathways were associated with neutrophilic inflammation in ESA. Gene set variation analysis of bronchial epithelial cell transcriptome from CSA showed enrichment of xenobiotic metabolism, oxidative stress and endoplasmic reticulum stress compared to other groups. CXCL5 and matrix metallopeptidase 12 genes were upregulated in ESA and the epithelial protective genes, mucin 2 and cystatin SN, were downregulated.Despite little difference in clinical characteristics, CSA were distinguishable from ESA subjects at the sputum proteomic level, with CSA patients having increased CSF2 expression and ESA patients showing sustained loss of epithelial barrier processes., Competing Interests: Conflict of interest: K. Takahashi received personal fees from Asahi General Hospital, during the conduct of the study. Conflict of interest: M. Loza is employed by and owns stock in Johnson & Johnson, the parent company of Janssen R&D. Conflict of interest: F. Baribaud is an employee and shareholder of Janssen R&D. Conflict of interest: P. Chanez has provided consultancy services for Boehringer Ingelheim, Johnson & Johnson, GlaxoSmithKline, Merck Sharp & Dohme, AstraZeneca, Novartis, Teva, Chiesi, Sanofi and SNCF; has served on advisory boards for Almirall, Boehringer Ingelheim, Johnson & Johnson, GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi and Sanofi; has received lecture fees from Boehringer Ingelheim, Centocor, GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi, Boston Scientific and ALK; and has received industry-sponsored grants from Roche, Boston Scientific, Boehringer Ingelheim, Centocor, GlaxoSmithKline, AstraZeneca, ALK, Novartis, Teva and Chiesi. Conflict of interest: I. Horvath has received personal fees from Astra Zeneca, Boehringer Ingelheim, Novartis, CSL, Chiesi, Roche, GSK, Berlin-Chemie and Sandoz, outside the submitted work. Conflict of interest: P. Montuschi reports personal fees from advisory board meetings with AstraZeneca, outside the submitted work. Conflict of interest: F. Singer has received personal fees and honoraria for speaking engagements from Vertex and Novartis, outside the submitted work. Conflict of interest: S-E. Dahlén has received research grants from several Swedish funding bodies such as MRC, Heart-Lung-Foundation and the Strategic Research Foundation, during the conduct of the study; and has received personal fees for advisory board meetings from GSK, AZ, Novartis, Teva, Regeneron/Sanofi, Merck and RSPR AB, grants on asthma phenotyping from AZ, and honoraria for speaking engagements from GSK and Teva, outside the submitted work. Conflict of interest: B. Dahlén has received personal fees from Teva (for advisory board membership) and AstraZeneca (payments for lectures), outside the submitted work. Conflict of interest: N. Krug reports grants from IMI (U-BIOPRED consortium IMI number 115010), during the conduct of the study. Conflict of interest: T. Sandström has received personal fees from advisory board meetings with pharmaceutical companies GSK, AZ, Novartis, Teva and Boehringer Ingelheim, and honoraria for speaking engagements for AZ, Novartis, Boehringer Ingelheim, outside the submitted work. Conflict of interest: D.E. Shaw has received personal fees for advisory board work from GSK, AZ, Teva and Boehringer Ingelheim, outside the submitted work. Conflict of interest: R. Lutter has received personal fees for advisory board meetings from GSK and Boehringer Ingelheim, and grants on asthma and COPD from GSK, Lung Foundation and MedImmune, outside the submitted work. Conflict of interest: P. Bakke has received personal fees for advisory board meetings from GSK, AZ, Novartis and Teva, and honoraria for speaking engagements from AZ and Boehringer Ingelheim, outside the submitted work. Conflict of interest: L.J. Fleming has received personal fees for advisory board meetings from Novartis, Vectura and Boehringer Ingelheim, grants from Asthma UK and BLF, and honoraria for speaking engagements for Novartis, outside the submitted work. Conflict of interest: P.H. Howarth was employed part time by GSK as Global Medical Expert. Conflict of interest: M. Caruso received grants (paid to institute) from the Innovative Medicines Initiative (IMI), during the conduct of the study. Conflict of interest: C. Auffray received grants from the Innovative Medicine Initiative (U-BIOPRED Consortium IMI number 115010 and eTRIKS Consortium IMI number 115446), during the conduct of the study. Conflict of interest: B. De Meulder received grants from the Innovative Medicine Initiative (U-BIOPRED Consortium IMI number 115010 and eTRIKS Consortium IMI number 115446), during the conduct of the study. Conflict of interest: D. Lefaudeux received grants from the Innovative Medicine Initiative (U-BIOPRED Consortium IMI number 115010 and eTRIKS Consortium IMI number 115446), during the conduct of the study. Conflict of interest: R. Djukanovic has received personal fees for lectures at company sponsored symposia and consulting in advisory boards from TEVA, grants (for an investigator led study of mechanisms of action of omalizumab) and personal fees (for lectures at company sponsored symposia and consulting in advisory boards) from Novartis, and is a consultant to, co-founder of, and holds shares in Synairgen, outside the submitted work. Conflict of interest: P.J. Sterk has received a public-private grant (paid to institute) from 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: I.M. Adcock has received personal fees for advisory board meetings from GSK, AZ, Novartis, Boehringer Ingelheim and Vectura, grants on asthma and COPD from Pfizer, GSK, MRC, EU, BI and IMI, and honoraria for speaking engagements for AZ and BI, outside the submitted work. Conflict of interest: K.F. Chung has received personal fees for advisory board meetings from GSK, AZ, Novartis, Teva, Boehringer Ingelheim and J&J, grants on asthma and COPD from Pfizer, GSK, MRC, EU IMI and NIH, and honoraria for speaking engagements for AZ and Merck, outside the submitted work., (Copyright ©ERS 2018.)

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.)

Keywords: asthma; bioinformatics; endotypes; precision medicine; systems biology EN asthma bioinformatics endotypes precision medicine systems biology 380 383 4 01/09/21 20210101 NES 210101 I To the Editor, i Asthma is a complex heterogeneous disease that presents with varying degrees of severity. We identified four optimal clusters (TAC*1, TAC*2, TAC*3a and TAC*3b) (Figure S3), in agreement with our previous clustering1 where TAC*3a and TAC*3b were combined. Asthma, bioinformatics, endotypes, precision medicine, systems biology. [Extracted from the article]

Oxidative stress is believed to be a major driver of inflammation in smoking asthmatics. The U-BIOPRED project recruited a cohort of Severe Asthma smokers/ex-smokers (SAs/ex) and non-smokers (SAn) with extensive clinical and biomarker information enabling characterization of these subjects. We investigated oxidative stress in severe asthma subjects by analysing urinary 8-iso-PGF2α and the mRNA-expression of the main pro-oxidant (NOX2; NOSs) and anti-oxidant (SODs; CAT; GPX1) enzymes in the airways of SAs/ex and SAn. All the severe asthma U-BIOPRED subjects were further divided into current smokers with severe asthma (CSA), ex-smokers with severe asthma (ESA) and non-smokers with severe asthma (NSA) to deepen the effect of active smoking. Clinical data, urine and sputum were obtained from severe asthma subjects. A bronchoscopy to obtain bronchial biopsy and brushing was performed in a subset of subjects. The main clinical data were analysed for each subset of subjects (urine-8-iso-PGF2α; IS-transcriptomics; BB-transcriptomics; BBr-transcriptomics). Urinary 8-iso-PGF2α was quantified using mass spectrometry. Sputum, bronchial biopsy and bronchial brushing were processed for mRNA expression microarray analysis. Urinary 8-iso-PGF2α was increased in SAs/ex, median (IQR) = 31.7 (24.5–44.7) ng/mmol creatinine, compared to SAn, median (IQR) = 26.6 (19.6–36.6) ng/mmol creatinine (p< 0.001), and in CSA, median (IQR) = 34.25 (24.4–47.7), vs. ESA, median (IQR) = 29.4 (22.3–40.5), and NSA, median (IQR) = 26.5 (19.6–16.6) ng/mmol creatinine (p = 0.004). Sputum mRNA expression of NOX2 was increased in SAs/ex compared to SAn (probe sets 203922_PM_s_at fold-change = 1.05 p = 0.006; 203923_PM_s_at fold-change = 1.06, p = 0.003; 233538_PM_s_at fold-change = 1.06, p = 0.014). The mRNA expression of antioxidant enzymes were similar between the two severe asthma cohorts in all airway samples. NOS2 mRNA expression was decreased in bronchial brushing of SAs/ex compared to SAn (fold-change = -1.10; p = 0.029). NOS2 mRNA expression in bronchial brushing correlated with FeNO (Kendal’s Tau = 0.535; p< 0.001). From clinical and inflammatory analysis, FeNO was lower in CSA than in ESA in all the analysed subject subsets (p< 0.01) indicating an effect of active smoking. Results about FeNO suggest its clinical limitation, as inflammation biomarker, in severe asthma active smokers. These data provide evidence of greater systemic oxidative stress in severe asthma smokers as reflected by a significant changes of NOX2 mRNA expression in the airways, together with elevated urinary 8-iso-PGF2α in the smokers/ex-smokers group. Trial registration ClinicalTrials.gov—Identifier: [ABSTRACT FROM AUTHOR]