Characterization of Eosinophilic and Non-Eosinophilic Severe Asthma Phenotypes and Proportion of Patients with These Phenotypes in the International Severe Asthma Registry (ISAR)

BackgroundAsthma is a heterogeneous and complex disease, and the description of asthma phenotypes based on extrapulmonary treatable traits has not been previously reported.Objectiveto identify and characterise clusters based on clinical, functional, anthropometrical, and psychological characteristics in participants with moderate-to-severe asthma.MethodsThis is a cross-sectional multicentre study involving centres from Brazil and Australia. Participants (N=296) with moderate-to-severe asthma were consecutively recruited. Physical activity and sedentary time, clinical asthma control, anthropometric data, pulmonary function, psychological, and health-status were evaluated. Participants were classified by hierarchical cluster analysis and the clusters compared using ANOVA, Kruskal-Wallis, and Chi-square tests. Multiple logistic and linear regression models were performed to evaluate the association between variables.ResultsWe identified four clusters: (1)controlled asthma who were physically active, (2)uncontrolled asthma who were physically inactive and more sedentary, (3)uncontrolled asthma with low physical activity, who were also obese and experienced anxiety and/or depression symptoms (4)very uncontrolled asthma, who were physically inactive, more sedentary, obese and experienced anxiety and/or depression symptoms. Higher levels of sedentary time, female sex, and anxiety symptoms were associated with increased odds of exacerbation risk while being more active showed a protective factor for hospitalisation. Asthma control was associated with sex, the occurrence of exacerbation, physical activity, and health-status.ConclusionTraits such as physical inactivity, obesity, and symptoms of anxiety and/or depression were associated with worse asthma outcomes, and closely and inextricably with asthma control. This cluster analysis supports the importance of assessing extrapulmonary traits to improve personalised management and outcomes for people with moderate and severe asthma.

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Novel Comprehensive Bioinformatics Approaches to Determine the Molecular Genetic Susceptibility Profile of Moderate and Severe Asthma

International Journal of Molecular Sciences ◽

10.3390/ijms21114022 ◽

2020 ◽

Vol 21 (11) ◽

pp. 4022

Author(s):

Hatem Zayed

Keyword(s):

Severe Asthma ◽

Protein Interactions ◽

Gene Networks ◽

Molecular Genetic ◽

Enrichment Analysis ◽

Protein Protein Interactions ◽

Bioinformatics Pipeline ◽

Moderate Asthma ◽

Asthma Phenotypes ◽

Chronic Inflammatory Condition

Background: Asthma is a chronic inflammatory condition linked to hyperresponsiveness in the airways. There is currently no cure available for asthma, and therapy choices are limited. Asthma is the result of the interplay between genes and the environment. The exact molecular genetic mechanism of asthma remains elusive. Aims: The aim of this study is to provide a comprehensive, detailed molecular etiology profile for the molecular factors that regulate the severity of asthma and pathogenicity using integrative bioinformatics tools. Methods: The GSE43696 omnibus gene expression dataset, which contains 50 moderate cases, 38 severe cases, and 20 healthy controls, was used to investigate differentially expressed genes (DEGs), susceptible chromosomal loci, gene networks, pathways, gene ontologies, and protein–protein interactions (PPIs) using an intensive bioinformatics pipeline. Results: The PPI network analysis yielded DEGs that contribute to interactions that differ from moderate-to-severe asthma. The combined interaction scores resulted in higher interactions for the genes STAT3, AGO2, COL1A1, CLCN6, and KSR for moderate asthma and JAK2, INSR, ERBB2, NR3C1, and PTK6 for severe asthma. Enrichment analysis (EA) demonstrated differential enrichment between moderate and severe asthma phenotypes; the ion transport regulation pathway was significantly enhanced in severe asthma phenotypes compared to that in moderate asthma phenotypes and involved PER2, GCR, IRS-2, KCNK7, KCNK6, NOX1, and SCN7A. The most enriched common pathway in both moderate and severe asthma is the development of the glucocorticoid receptor (GR) signaling pathway followed by glucocorticoid-mediated inhibition of proinflammatory and proconstrictory signaling in the airway of smooth muscle cell pathways. Gene sets were shared between severe and moderate asthma at 16 chromosome locations, including 17p13.1, 16p11.2, 17q21.31, 1p36, and 19q13.2, while 60 and 48 chromosomal locations were unique for both moderate and severe asthma, respectively. Phylogenetic analysis for DEGs showed that several genes have been intersected in phases of asthma in the same cluster of genes. This could indicate that several asthma-associated genes have a common ancestor and could be linked to the same biological function or gene family, implying the importance of these genes in the pathogenesis of asthma. Conclusion: New genetic risk factors for the development of moderate-to-severe asthma were identified in this study, and these could provide a better understanding of the molecular pathology of asthma and might provide a platform for the treatment of asthma.

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