Characteristics of Induced-Sputum Inflammatory Phenotypes in Adults with Asthma : Predictors of Bronchial Eosinophilia

The objectives of this study were, for patients attending a specialist asthma clinic at a tertiary care hospital, to determine, from sputum induction (SI), proportions of bronchial inflammatory phenotypes, demographic, clinical and functional characteristics of each phenotype, and the most accessible non-invasive inflammatory marker that best discriminates between phenotypes. Included were 96 patients with asthma, attending a specialist asthma clinic at a tertiary care hospital, who underwent testing as follows: SI, spirometry, fractional exhaled nitric oxide (FeNO), blood eosinophilia, total immunoglobulin E (IgE), and a skin prick test. SI phenotypes were 46.9% eosinophilic, 33.3% paucigranulocytic, 15.6% neutrophilic, and 4.2% mixed. No significantly different clinical or functional characteristics were observed between the phenotypes. A positive correlation was observed between SI eosinophilia and both emergency visits in the last 12 months (p = 0.041; r = 0.214) and FeNO values (p = 0.000; r = 0.368). Blood eosinophilia correlated with SI eosinophilia (p = 0.001; r = 0.362) and was the best predictor of bronchial eosinophilia, followed by FeNO, and total blood IgE (area under the receiver operating characteristic curve (AUC-ROC) 72%, 65%, and 53%, respectively), although precision was only fair. In consultations for severe asthma, the most frequent phenotype was eosinophilic. Peripheral blood eosinophilia is a reliable marker for discriminating between different bronchial inflammatory phenotypes, is useful in enabling doctors to select a suitable biologic treatment and so prevent asthma exacerbation, and is a better predictor of bronchial eosinophilia than FeNO and IgE values

Recent Advances in Allergen-Specific Immunotherapy as Treatment for Allergic Asthma: A Practical Overview.

The Global Initiative for Asthma Report updated in 2019 stated that potential benefits of allergen immunotherapy (AIT), compared to pharmacological and avoidance options, must be weighed against the risk of adverse effects and the inconvenience and cost of the prolonged course of therapy in asthma. Thus, with the aim of clarifying some aspects with regard to the possible use of AIT in allergic asthma treatment armamentarium, a group of expert allergists from the Spanish Allergy and Clinical Immunology Scientific Society (SEAIC), particularly from the Immunotherapy and Asthma Interest Groups developed a frequently asked questions in clinical practice. This document updates relevant topics on the use of AIT in asthma and could facilitate physician clinical decisions and improve health outcomes for individual patients

Total and specific immunoglobulin E in induced sputum in allergic and non-allergic asthma.

BACKGROUND:Most patients with nonallergic asthma have normal serum immunoglobulin E (IgE) levels. Recent reports suggest that total and aeroallergen-specific IgE levels in induced sputum may be higher in nonallergic asthmatics than in healthy controls. Our objective is to compare total and dust-mite specific (Der p 1) IgE levels in induced sputum in allergic and nonallergic asthmatics and healthy controls. METHODS:Total and Der p 1-specific IgE were measured in induced sputum (ImmunoCAP immunoassay) from 56 age- and sex-matched asthmatics (21 allergic, 35 nonallergic) and 9 healthy controls. Allergic asthma was defined as asthma with a positive prick test and/or clinically-significant Der p 1-specific serum IgE levels. RESULTS:Patients with allergic asthma presented significantly higher total and Der p 1-specific serum IgE levels. There were no significant between-group differences in total sputum IgE. However, Der p 1-specific sputum IgE levels were significantly higher (p = 0.000) in the allergic asthmatics, but without differences between the controls and nonallergic asthmatics. Serum and sputum IgE levels were significantly correlated, both for total IgE (rho = 0.498; p = 0.000) and Der p 1-specific IgE (rho, 0.621; p = 0001). CONCLUSIONS:Total IgE levels measured in serum and induced sputum are significantly correlated. No significant differences were found between the differents groups in total sputum IgE. Nevertheless, the levels of Der p 1-specific sputum IgE levels were significantly higher in the allergic asthmatics, but without differences between the controls and nonallergic asthmatics. Probably due to the lack of sensitivity of the test used, but with the growing evidence for local allergic reactions better methods are need to explore its presence. The Clinical Trials Identifier for this project is NCT03640936

Identification of Two Eosinophil Subsets in Induced Sputum from Patients with Allergic Asthma According to CD15 and CD66b Expression

Altres ajuts: Spanish Allergy and Clinical Immunology Society (SEAIC) (reference 17/06); BRN-Fundació Pla i Armengol grant in the call of 2018.Two subsets of eosinophils have been described: resident eosinophils with homeostatic functions (rEOS) in healthy subjects and in patients with nonallergic eosinophilic asthma, and inflammatory eosinophils (iEOS) in blood and lung samples from patients with allergic asthma. We explored if it would be possible to identify different subsets of eosinophils using flow cytometry and the gating strategy applied to induced sputum. We conducted an observational cross-sectional single-center study of 62 patients with persistent allergic asthma. Inflammatory cells from induced sputum samples were counted by light microscopy and flow cytometry, and cytokine levels in the supernatant were determined. Two subsets of eosinophils were defined that we call E1 (CD66b-high and CD15-high) and E2 (CD66b-low and CD15-low). Of the 62 patients, 24 were eosinophilic, 18 mixed, 10 paucigranulocytic, and 10 neutrophilic. E1 predominated over E2 in the eosinophilic and mixed patients (20.86% vs. 6.27% and 14.42% vs. 4.31%, respectively), while E1 and E2 were similar for neutrophilic and paucigranulocytic patients. E1 correlated with IL-5, fractional exhaled nitric oxide, and blood eosinophils. While eosinophil subsets have been identified for asthma in blood, we have shown that they can also be identified in induced sputum

How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers?

Asthma is a heterogeneous respiratory disease that encompasses different inflammatory and functional endophenotypes. Many non-invasive biomarkers has been investigated to its pathobiology. Heany et al proposed a clinical algorithm that classifies severe asthmatic patients into likely-eosinophilic phenotypes, based on accessible biomarkers: PBE, current treatment, FeNO, presence of nasal polyps (NP) and age of onset. We assessed the concordance between the algorithm proposed by Heany et al. with sputum examination, the gold standard, in 145 asthmatic patients of the MEGA cohort with varying grades of severity. No correlation was found between both classifications 0.025 (CI = 0.013-0.037). Moreover, no relationship was found between sputum eosinophilia and peripheral blood eosinophilia count in the total studied population. In conclusion, our results suggest that grouping the biomarkers proposed by Heany et al. are insufficient to diagnose eosinophilic phenotypes in asthmatic patients. Sputum analysis remains the gold standard to assess airway inflammation

Clinical and inflammatory characteristics of patients with asthma in the Spanish MEGA project cohort

Abstract Introduction The MEGA (MEchanism underlying the Genesis and evolution of Asthma) project is a multicenter cohort study carried out in eight Spanish hospitals, gathering clinical, physiological, and molecular data from patients with asthma and multimorbidities in order to gain insight into the different physiopathological mechanisms involved in this disorder. Material and Methods We report the baseline clinical and physiological characteristics and biomarker measures of adult participants in the project with the aim of better understanding the natural history and underlying mechanisms of asthma as well as the associated multimorbidities across different levels of severity. We carried out a detailed clinical examination, pulmonary function testing, measurement of fractional exhaled nitric oxide (FeNO), blood counts, induced sputum, skin prick tests, chest computed tomography scan, asthma questionnaires, and multimorbidity assessment in 512 asthmatic patients. Results When compared to patients with milder disease, severe asthmatic patients showed greater presence of symptoms, more exacerbations, lower asthma control, increased airflow obstruction, and higher frequency of chronic rhinosinusitis with nasal polyps, severe rhinitis, anxiety and depression, gastroesophageal reflux, and bronchiectasis. Conclusion The MEGA project succeeded in recruiting a high number of asthma patients, especially those with severe disease, who showed lower control and higher frequency of multimorbidities

Identification of Asthma Phenotypes in the Spanish MEGA Cohort Study Using Cluster Analysis

Introduction: The definition of asthma phenotypes has not been fully established, neither there are cluster studies showing homogeneous results to solidly establish clear phenotypes. The purpose of this study was to develop a classification algorithm based on unsupervised cluster analysis, identifying clusters that represent clinically relevant asthma phenotypes that may share asthma-related outcomes. Methods: We performed a multicentre prospective cohort study, including adult patients with asthma (N = 512) from the MEGA study (Mechanisms underlying the Genesis and evolution of Asthma). A standardised clinical history was completed for each patient. Cluster analysis was performed using the kernel k-groups algorithm. Results: Four clusters were identified. Cluster 1 (31.5% of subjects) includes adult-onset atopic patients with better lung function, lower BMI, good asthma control, low ICS dose, and few exacerbations. Cluster 2 (23.6%) is made of adolescent-onset atopic asthma patients with normal lung function, but low adherence to treatment (59% well-controlled) and smokers (48%). Cluster 3 (17.1%) includes adult-onset patients, mostly severe non-atopic, with overweight, the worse lung function and asthma control, and receiving combination of treatments. Cluster 4 (26.7%) consists of the elderly-onset patients, mostly female, atopic (64%), with high BMI and normal lung function, prevalence of smokers and comorbidities. Conclusion: We defined four phenotypes of asthma using unsupervised cluster analysis. These clusters are clinically relevant and differ from each other as regards FEV1, age of onset, age, BMI, atopy, asthma severity, exacerbations, control, social class, smoking and nasal polyps