ArticleFrontiers in allergy2021
Translational Analysis of Moderate to Severe Asthma GWAS Signals Into Candidate Causal Genes and Their Functional, Tissue-Dependent and Disease-Related Associations.
Article in Frontiers in allergy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 4 citations in OpenAlex.
- Genome-wide association study of asthma with high treatment burden and/or worse outcomes defined using electronic healthcare data in UK Biobank.ERJ open research · 2026Article
- Role of miR-191-3p in HDM-induced airway epithelial inflammation by targeting CD247 in allergic asthma.BMC immunology · 2026Article
- Estimating in silico causal effects of DNA methylation on gene expression through genetic anchors in airway epithelium in asthma.Science advances · 2026Article
- Effect of air pollution on asthma.Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology · 2024Review
- Effect of Obesity on the Expression of Genes Associated with Severe Asthma-A Pilot Study.Journal of clinical medicine · 2023Article
- StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
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Abstract
Asthma affects more than 300 million people globally and is both under diagnosed and under treated. The most recent and largest genome-wide association study investigating moderate to severe asthma to date was carried out in 2019 and identified 25 independent signals. However, as new and in-depth downstream databases become available, the translational analysis of these signals into target genes and pathways is timely. In this study, unique (U-BIOPRED) and publicly available datasets (HaploReg, Open Target Genetics and GTEx) were investigated for the 25 GWAS signals to identify 37 candidate causal genes. Additional traits associated with these signals were identified through PheWAS using the UK Biobank resource, with asthma and eosinophilic traits amongst the strongest associated. Gene expression omnibus dataset examination identified 13 candidate genes with altered expression profiles in the airways and blood of asthmatic subjects, including
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