Stratification of asthma phenotypes by airway proteomic signatures

© 2019 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

Stratification of asthma by lipidomic profiling of induced sputum supernatant.

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 To perform 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 healthy controls. METHODS Induced sputum supernatant was collected from 211 asthmatic adults and 41 healthy individuals enrolled in the U-BIOPRED study. Sputum lipidomes were characterised by semi-quantitative shotgun mass spectrometry, and clustered using topological data analysis to identify lipid phenotypes. RESULTS Shotgun lipidomics of induced sputum supernatant revealed a spectrum of nine molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthmatics and healthy controls, but within the asthmatic population as well. Matching clinical, pathobiological, proteomic and transcriptomic data informed on the underlying disease processes. Sputum lipid phenotypes with higher levels of non-endogenous, 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 asthmatics, 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. CLINICAL IMPLICATION Immunomodulation of extracellular vesicle secretion in the lungs may provide a novel therapeutic target for severe asthma

Stratification of asthma by lipidomic profiling of induced sputum supernatant

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.</p

IL-17–high asthma with features of a psoriasis immunophenotype

© 2019 American Academy of Allergy, Asthma & Immunology 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

Mendelian randomization implies no direct causal association between leukocyte telomere length and amyotrophic lateral sclerosis

We employed Mendelian randomization (MR) to evaluate the causal relationship between leukocyte telomere length (LTL) and amyotrophic lateral sclerosis (ALS) with summary statistics from genome-wide association studies (n = ~ 38,000 for LTL and ~ 81,000 for ALS in the European population; n = ~ 23,000 for LTL and ~ 4,100 for ALS in the Asian population). We further evaluated mediation roles of lipids in the pathway from LTL to ALS. The odds ratio per standard deviation decrease of LTL on ALS was 1.10 (95% CI 0.93–1.31, p = 0.274) in the European population and 0.75 (95% CI 0.53–1.07, p = 0.116) in the Asian population. This null association was also detected between LTL and frontotemporal dementia in the European population. However, we found that an indirect effect of LTL on ALS might be mediated by low density lipoprotein (LDL) or total cholesterol (TC) in the European population

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics

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