U-BIOPRED cohort n=91 epithelial brushings or biopsies IL-17 High Clinical phenotype Nasal polyps Smoking Antibiotic use Epithelial Gene Expression Profile Clinical phenotype FeNO Exacerbations Gene expression shared with psoriasis IDO1 IL1B DEFB4B S100A8, S100A9 PI3 CXCL3, CXCL8 CXCL10, CCL20 Gene signature SERPINB2 POSTN CLCA1 IL-13 High T cell infiltration Neutrophilia Eosinophilia IL-17-high asthma with features of a psoriasis immunophenotype From a the Respiratory,
Background: Allergic sensitization is associated with severe asthma, but assessment of sensitization is not recommended by most guidelines. Objective: We hypothesized that patterns of IgE responses to multiple allergenic proteins differ between sensitized participants with mild/moderate and severe asthma. Methods: IgE to 112 allergenic molecules (components, c-sIgE) was measured using multiplex array among 509 adults and 140 school-age and 131 preschool children with asthma/wheeze from the Unbiased BIOmarkers for the PREDiction of respiratory diseases outcomes cohort, of whom 595 had severe disease. We applied clustering methods to identify co-occurrence patterns of components (component clusters) and patterns of sensitization among participants (sensitization clusters). Network analysis techniques explored the connectivity structure of c-sIgE, and differential network analysis looked for differences in c-sIgE interactions between severe and mild/moderate asthma. Results: Four sensitization clusters were identified, but with no difference between disease severity groups. Similarly, component clusters were not associated with asthma severity. None of the c-sIgE were identified as associates of severe asthma. The key difference between school children and adults with mild/moderate compared with those with severe asthma was in the network of connections between c-sIgE. Participants with severe asthma had higher connectivity among components, but these connections were weaker. The mild/moderate network had fewer connections, but the connections were stronger. Connectivity between components with no structural homology tended to co-occur among participants with severe asthma. Results were independent from the different sample sizes of mild/moderate and severe groups. Conclusions: The patterns of interactions between IgE to multiple allergenic proteins are predictors of asthma severity among school children and adults with allergic asthma. (J Allergy Clin Immunol 2020;146:821-30.)
FENO-guided ICS titration does not appear to reduce corticosteroid usage or exacerbation frequency in paediatric outpatients with moderate to severe asthma. This may reflect limitations in FENO-driven management algorithms, as there are now concerns that FENO levels relate to atopy as much as they relate to asthma control.
To address uncertainties in the prevention and management of influenza in people with asthma, we performed a scoping review of the published literature on influenza burden; current vaccine recommendations; vaccination coverage; immunogenicity, efficacy, effectiveness, and safety of influenza vaccines; and the benefits of antiviral drugs in people with asthma. We found significant variation in the reported rates of influenza detection in individuals with acute asthma exacerbations making it unclear to what degree influenza causes exacerbations of underlying asthma. The strongest evidence of an association was seen in studies of children. Countries in the European Union currently recommend influenza vaccination of adults with asthma; however, coverage varied between regions. Coverage was lower among children with asthma. Limited data suggest that good seroprotection and seroconversion can be achieved in both children and adults with asthma and that vaccination confers a degree of protection against influenza illness and asthma-related morbidity to children with asthma. There were insufficient data to determine efficacy in adults. Overall, influenza vaccines appeared to be safe for people with asthma. We identify knowledge gaps and make recommendations on future research needs in relation to influenza in patients with asthma.
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.
The prevalence of early childhood wheeze varied considerably across Europe. Lower respiratory tract infections, day care attendance, postnatal smoke exposure and male gender are important risk factors. Further research is needed to identify additional modifiable risk factors that may differ between countries.
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