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.© 2022 The Authors. Clinical and Translational Allergy published by John Wiley & Sons Ltd on behalf of European Academy of Allergy and Clinical Immunology

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

Alpha-1 antitrypsin deficiency and Pi*S and Pi*Z SERPINA1 variants are associated with asthma exacerbations

Introduction and objectives: Asthma is a chronic inflammatory disease of the airways. Asthma patients may experience potentially life-threatening episodic flare-ups, known as exacerbations, which may significantly contribute to the asthma burden. The Pi*S and Pi*Z variants of the SERPINA1 gene, which usually involve alpha-1 antitrypsin (AAT) deficiency, had previously been associated with asthma. The link between AAT deficiency and asthma might be represented by the elastase/antielastase imbalance. However, their role in asthma exacerbations remains unknown. Our objective was to assess whether SERPINA1 genetic variants and reduced AAT protein levels are associated with asthma exacerbations. Materials and methods: In the discovery analysis, SERPINA1 Pi*S and Pi*Z variants and serum AAT levels were analyzed in 369 subjects from La Palma (Canary Islands, Spain). As replication, genomic data from two studies focused on 525 Spaniards and publicly available data from UK Biobank, FinnGen, and GWAS Catalog (Open Targets Genetics) were analyzed. The associations between SERPINA1 Pi*S and Pi*Z variants and AAT deficiency with asthma exacerbations were analyzed with logistic regression models, including age, sex, and genotype principal components as covariates. Results: In the discovery, a significant association with asthma exacerbations was found for both Pi*S (odds ratio [OR]=2.38, 95% confidence interval [CI]= 1.40-4.04, p-value=0.001) and Pi*Z (OR=3.49, 95%CI=1.55-7.85, p-value=0.003)Likewise, AAT deficiency was associated with a higher risk for asthma exacerbations (OR=5.18, 95%CI=1.58-16.92, p-value=0.007) as well as AAT protein levels (OR= 0.72, 95%CI=0.57-0.91, p-value=0.005). The Pi*Z association with exacerbations was replicated in samples from Spaniards with two generations of Canary Islander origin (OR=3.79, p-value=0.028), and a significant association with asthma hospitalizations was found in the Finnish population (OR=1.12, p-value=0.007). Conclusions: AAT deficiency could be a potential therapeutic target for asthma exacerbations in specific populations

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

Analysis of Differentially Expressed MicroRNAs in Serum and Lung Tissues from Individuals with Severe Asthma Treated with Oral Glucocorticoids

Nowadays, microRNAs (miRNAs) are increasingly used as biomarkers due to their potential contribution to the diagnosis and targeted treatment of a range of diseases. The aim of the study was to analyze the miRNA expression profiles in serum and lung tissue from patients with severe asthma treated with oral corticosteroids (OCS) and those without OCS treatment. For this purpose, serum and lung tissue miRNAs of OCS and non-OCS asthmatic individuals were evaluated by miRNAs-Seq, and subsequently miRNA validation was performed using RT-qPCR. Additionally, pathway enrichment analysis of deregulated miRNAs was conducted. We observed altered expression by the next-generation sequencing (NGS) of 11 miRNAs in serum, of which five (hsa-miR-148b-3p, hsa-miR-221-5p, hsa-miR-618, hsa-miR-941, and hsa-miR-769-5p) were validated by RT-qPCR, and three miRNAs in lung tissue (hsa-miR-144-3p, hsa-miR-144-5p, and hsa-miR-451a). The best multivariate logistic regression model to differentiate individuals with severe asthma, treated and untreated with OCS, was to combine the serum miRNAs hsa-miR-221-5p and hsa-miR-769-5p. Expression of hsa-miR-148b-3p and hsa-miR-221-5p correlated with FEV/FVC (%) and these altered miRNAs act in key signaling pathways for asthma disease and the regulated expression of some genes (FOXO3, PTEN, and MAPK3) involved in these pathways. In conclusion, there are miRNA profiles differentially expressed in OCS-treated individuals with asthma and could be used as biomarkers of OCS treatment

Analysis of Differentially Expressed MicroRNAs in Serum and Lung Tissues from Individuals with Severe Asthma Treated with Oral Glucocorticoids

Nowadays, microRNAs (miRNAs) are increasingly used as biomarkers due to their potential contribution to the diagnosis and targeted treatment of a range of diseases. The aim of the study was to analyze the miRNA expression profiles in serum and lung tissue from patients with severe asthma treated with oral corticosteroids (OCS) and those without OCS treatment. For this purpose, serum and lung tissue miRNAs of OCS and non-OCS asthmatic individuals were evaluated by miRNAs-Seq, and subsequently miRNA validation was performed using RT-qPCR. Additionally, pathway enrichment analysis of deregulated miRNAs was conducted. We observed altered expression by the next-generation sequencing (NGS) of 11 miRNAs in serum, of which five (hsa-miR-148b-3p, hsa-miR-221-5p, hsa-miR-618, hsa-miR-941, and hsa-miR-769-5p) were validated by RT-qPCR, and three miRNAs in lung tissue (hsa-miR-144-3p, hsa-miR-144-5p, and hsa-miR-451a). The best multivariate logistic regression model to differentiate individuals with severe asthma, treated and untreated with OCS, was to combine the serum miRNAs hsa-miR-221-5p and hsa-miR-769-5p. Expression of hsa-miR-148b-3p and hsa-miR-221-5p correlated with FEV1/FVC (%) and these altered miRNAs act in key signaling pathways for asthma disease and the regulated expression of some genes (FOXO3, PTEN, and MAPK3) involved in these pathways. In conclusion, there are miRNA profiles differentially expressed in OCS-treated individuals with asthma and could be used as biomarkers of OCS treatment

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

The burden of mild asthma: Clinical burden and healthcare resource utilisation in the NOVELTY study

Background: Patients with mild asthma represent a substantial proportion of the population with asthma, yet there are limited data on their true burden of disease. We aimed to describe the clinical and healthcare resource utilisation (HCRU) burden of physician-assessed mild asthma.Methods: Patients with mild asthma were included from the NOVEL observational longiTudinal studY (NOVELTY; NCT02760329), a global, 3-year, real-world prospective study of patients with asthma and/or chronic obstructive pulmonary disease from community practice (specialised and primary care). Diagnosis and severity were based on physician discretion. Clinical burden included physician-reported exacerbations and patient-reported measures. HCRU included inpatient and outpatient visits.Results: Overall, 2004 patients with mild asthma were included; 22.8% experienced ≥1 exacerbation in the previous 12 months, of whom 72.3% experienced ≥1 severe exacerbation. Of 625 exacerbations reported, 48.0% lasted >1 week, 27.7% were preceded by symptomatic worsening lasting >3 days, and 50.1% required oral corticosteroid treatment. Health status was moderately impacted (St George's Respiratory Questionnaire score: 23.5 [standard deviation ± 17.9]). At baseline, 29.7% of patients had asthma symptoms that were not well controlled or very poorly controlled (Asthma Control Test score <20), increasing to 55.6% for those with ≥2 exacerbations in the previous year. In terms of HCRU, at least one unscheduled ambulatory visit for exacerbations was required by 9.5% of patients, including 9.2% requiring ≥1 emergency department visit and 1.1% requiring ≥1 hospital admission.Conclusions: In this global sample representing community practice, a significant proportion of patients with physician-assessed mild asthma had considerable clinical burden and HCRU

Treatable traits in the NOVELTY study

CorrigendumVolume 27, Issue 12, Respirology, pages: 1095-1095. First Published online: November 6, 2022 10.1111/resp.14406International audienceAsthma and chronic obstructive pulmonary disease (COPD) are two prevalent and complex diseases that require personalized management. Although a strategy based on treatable traits (TTs) has been proposed, the prevalence and relationship of TTs to the diagnostic label and disease severity established by the attending physician in a real-world setting are unknown. We assessed how the presence/absence of specific TTs relate to the diagnosis and severity of 'asthma', 'COPD' or 'asthma + COPD'