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Background: Severe asthma is associated with multiple comorbidities, including gastro-oesophageal reflux disease (GORD), which can contribute to exacerbation frequency and poor quality of life. Since epithelial dysfunction is an important feature in asthma, we hypothesised that in severe asthma the bronchial epithelium is more susceptible to the effects of acid reflux.
Methods: We developed an model of GORD using differentiated bronchial epithelial cells (BECs) from normal or severe asthmatic donors exposed to a combination of pepsin, acid pH and bile acids using a multiple challenge protocol (MCP-PAB). In addition, we analysed bronchial biopsies and undertook RNA sequencing of bronchial brushings from controls and severe asthmatics without or with GORD.
Results: Exposure of BECs to the MCP-PAB caused structural disruption, increased permeability, interleukin (IL)-33 expression, inflammatory mediator release and changes in gene expression for multiple biological processes. Cultures from severe asthmatics were significantly more affected than those from healthy donors. Analysis of bronchial biopsies confirmed increased IL-33 expression in severe asthmatics with GORD. RNA sequencing of bronchial brushings from this group identified 15 of the top 37 dysregulated genes found in MCP-PAB treated BECs, including genes involved in oxidative stress responses.
Conclusions And Clinical Implication: By affecting epithelial permeability, GORD may increase exposure of the airway submucosa to allergens and pathogens, resulting in increased risk of inflammation and exacerbations. These results suggest the need for research into alternative therapeutic management of GORD in severe asthma.
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http://dx.doi.org/10.1183/13993003.01634-2021 | DOI Listing |
Immunotherapy
September 2025
aGuangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Asthma is a chronic respiratory disorder characterized by airway inflammation, hyperresponsiveness, and reversible airflow obstruction. Despite therapeutic strategies, asthma remains inadequately controlled in many patients. Genetic predisposition plays a significant role in asthma pathogenesis, and the Proteinase-Activated Receptor 2 (PAR-2), encoded by the F2RL1 gene, has been associated with asthma.
View Article and Find Full Text PDFThorax
September 2025
Usher Institute, The University of Edinburgh, Edinburgh, UK
Background: The long-acting monoclonal antibody nirsevimab and respiratory syncytial virus (RSV) vaccines became available for prevention of severe RSV-associated disease in 2023. While clinical trials showed good efficacy and safety, their restrictive inclusion criteria, small sample sizes and short follow-up limit generalisability. We aimed to summarise real-world evidence on the effectiveness and safety of nirsevimab, RSV maternal vaccine and RSV vaccines for older adults.
View Article and Find Full Text PDFPharmacoepidemiol Drug Saf
September 2025
Sanofi, Cambridge, Massachusetts, USA.
Purpose: Given the increased likelihood for individuals with severe asthma to experience comorbidities, disease complications, emergency room visits, and hospitalizations, the ability to stratify asthma populations on severity is often important. Although pharmacoepidemiologic studies using administrative healthcare databases sometimes categorize asthma severity, there is no consensus on an approach.
Methods: Individuals with asthma (≥ 2 ICD-10-CM diagnosis codes J45) aged ≥ 6 years were identified in Optum's de-identified Clinformatics Data Mart Database between January 2017 and November 2023.
J Allergy Clin Immunol
September 2025
Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA. Electronic address:
Background: Genetic control of gene expression in asthma-related tissues is not well-characterized, particularly for African-ancestry populations, limiting advancement in our understanding of the increased prevalence and severity of asthma in those populations.
Objective: To create novel transcriptome prediction models for asthma tissues (nasal epithelium and CD4+ T cells) and apply them in transcriptome-wide association study to discover candidate asthma genes.
Methods: We developed and validated gene expression prediction databases for unstimulated CD4+ T cells and nasal epithelium using an elastic net framework.