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

Predicting dupilumab effectiveness with Type-2 biomarkers: A real-world study of severe asthma

BACKGROUND

The therapeutic effectiveness of dupilumab for severe asthma in real-world settings is yet to be prospectively investigated across multiple institutions, and uncertainties persist regarding predictive factors for its effectiveness. We aimed to assess the effectiveness of dupilumab and identify predictors of its effectiveness in real-world settings using two type-2 biomarkers: FeNO concentration and blood eosinophil count.

METHODS

This prospective multicenter study included 103 patients with severe asthma. Exacerbations and respiratory functions were monitored for 24 weeks. Asthma control was evaluated using the Asthma Control Questionnaire-5. Clinical symptoms and their impact on cough and sputum were assessed using the Cough and Sputum Assessment Questionnaire (CASA-Q). Subgroup analyses of type-2 biomarkers were conducted based on FeNO levels and blood eosinophil counts at baseline.

RESULTS

Treatment with dupilumab led to a reduction in exacerbations and enhancement in asthma control, FEV1, and CASA-Q scores. FEV1 improvement was correlated with enhancement in the sputum domain of the CASA-Q. Patients exhibiting elevated FeNO levels and blood eosinophil counts demonstrated more significant enhancements in FEV1. CASA-Q sputum domain scores were significantly higher in the group with elevated eosinophil counts. Regression analysis revealed that FeNO levels and blood eosinophil counts are significant predictors of FEV1 improvement, with blood eosinophil counts also predicting sputum improvement in patients treated with dupilumab.

CONCLUSIONS

Type-2 biomarkers may act as indicators of improvement in FEV1 and sputum outcomes among patients with severe asthma undergoing dupilumab treatment in real-world settings.

Cellular senescence-Related genes define the immune microenvironment and molecular characteristics in severe asthma patients

Recent studies have shown that cellular senescence is involved in the pathogenesis of severe asthma (SA). The objective of this study was to investigate the role of cellular senescence-related genes (CSGs) in the pathogenesis of SA. Here, 54 differentially expressed CSGs were identified in SA patients compared to healthy control individuals. Among the 54 differentially expressed CSGs, 3 CSGs (ETS2, ETS1 and AURKA) were screened using the LASSO regression analysis and logistic regression analysis to establish the CSG-based prediction model to predict severe asthma. Moreover, we found that the protein expression levels of ETS2, ETS1 and AURKA were increased in the severe asthma mouse model. Then, two distinct senescence subtypes of SA with distinct immune microenvironments and molecular biological characteristics were identified. Cluster 1 was characterized by increased infiltration of immature dendritic cells, regulatory T cells, and other cells. Cluster 2 was characterized by increased infiltration levels of eosinophils, neutrophils, and other cells. The molecular biological characteristics of Cluster 1 included aerobic respiration and oxidative phosphorylation, whereas the molecular biological characteristics of Cluster 2 included activation of the immune response and immune receptor activity. Then, we established an Random Forest model to predict the senescence subtypes of SA to guide treatment. Finally, potential drugs were searched for each senescence subgroup of SA patients via the Connectivity Map database. A peroxisome proliferator-activated receptor agonist may be a potential therapeutic drug for patients in Cluster 1, whereas a tachykinin antagonist may be a potential therapeutic drug for patients in Cluster 2. In summary, CSGs are likely involved in the pathogenesis of SA, which may lead to new therapeutic options for SA patients.

Consensus on the management of united airways disease with type 2 inflammation: a multidisciplinary Delphi study

BACKGROUND

Scientific evidence on patients with multimorbid type 2 asthma and chronic rhinosinusitis with nasal polyps (CRSwNP) from a united airways disease (UAD) perspective remains scarce, despite the frequent coexistence of these entities. We aimed to generate expert consensus-based recommendations for the management of UAD patients.

METHODS

Using a two-round Delphi method, Spanish expert allergists, pulmonologists and otolaryngologists expressed their agreement on 32 statements (52 items) on a 9-point Likert scale, classified as appropriate (median 7-9), uncertain (4-6) or inappropriate (1-3). Consensus was considered when at least two-thirds of the panel scored within the range containing the median.

RESULTS

A panel of 30 experts reached consensus on the appropriateness of 43 out of the 52 (82.7%) items. The usefulness of certain biomarkers (tissue and peripheral blood eosinophil count, serum total IgE, and fraction of exhaled nitric oxide [FeNO]) in the identification and follow-up of type 2 inflammation, and assessment of the response to biologics, were agreed. Some of these biomarkers were also associated with disease severity and/or recurrence after endoscopic sinus surgery (ESS). Consensus was achieved on treatment strategies related to the prescription of anti-IL-4/IL-13 or anti-IgE agents, concomitant treatment with systemic corticosteroids, and combining or switching to biologics with a different mechanism of action, considering a number of UAD clinical scenarios.

CONCLUSION

We provide expert-based recommendations to assist in clinical decision-making for the management of patients with multimorbid type 2 asthma and CRSwNP. Specific clinical trials and real-world studies focusing on the single-entity UAD are required to address controversial items.

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

Purpose

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.

Patients and Methods

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.

Results

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.

Conclusion

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.

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.

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

Background and Aims

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.

Materials and Methods

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.

Results

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.

Discussion and Conclusion

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.

Chronic Rhinosinusitis and COVID-19

The COVID-19 pandemic has raised awareness about olfactory dysfunction, although a loss of smell was present in the general population before COVID-19. Chronic rhinosinusitis (CRS) is a common upper airway chronic inflammatory disease that is also one of the most common causes of olfactory dysfunction. It can be classified into different phenotypes (ie, with and without nasal polyps) and endotypes (ie, type 2 and non-type 2 inflammation). However, scientific information regarding CRS within the context of COVID-19 is still scarce. This review focuses on (1) the potential effects of severe acute respiratory syndrome coronavirus 2 infection on CRS symptoms, including a loss of smell, and comorbidities; (2) the pathophysiologic mechanisms involved in the olfactory dysfunction; (3) CRS diagnosis in the context of COVID-19, including telemedicine; (4) the protective hypothesis of CRS in COVID-19; and (5) the efficacy and safety of therapeutic options for CRS within the context of COVID-19.

The Influence of Peripheral Blood Eosinophil Counts in Asthma Comorbidities in Adults: A Real Life Study

Asthma and eosinophilia are two closely related pathologies whose interaction is key in the era of precision medicine. However, this relationship is rarely taken into account without the influence of therapeutic prescriptions. In this study involving 1296 subjects, the relationship between eosinophilia and asthma was analyzed without taking into account other biases. We observed that rhinitis only appears in non-asthmatic patients with elevated blood eosinophil levels, while atopy was elevated in parallel to eosinophilia regardless of whether the patients were asthmatic or not. In terms of lung function, a decrease was observed for higher blood eosinophil levels, which is especially relevant in the FEV1/FVC ratio. FENO is elevated in relation to higher eosinophilia, but total IgE is only elevated in patients with high peripheral blood eosinophil levels and asthma. Finally, the only feature of asthma that is altered by increased peripheral eosinophilia is persistent asthma, with all other features remaining unchanged.