ArticleHealth science reports2026
Identifying Therapeutic Targets for Bronchial Asthma: Systematic Druggable Genome-Wide Mendelian Randomization.
Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Systematic Druggable Genome-Wide Analysis Identifies Therapeutic Targets for Aging: A Mendelian Randomization Study.Health science reports · 2026Article
- Identifying Therapeutic Targets for Bronchial Asthma: Systematic Druggable Genome-Wide Mendelian Randomization.Health science reports · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The treatment and prevention of bronchial asthma continue to present significant challenges. Mendelian randomization (MR) has been extensively employed to identify novel therapeutic targets. Consequently, we conducted a systematic MR analysis across the druggable genome to identify potential therapeutic targets for asthma. Aims: Exploring new potential therapeutic targets for the treatment of asthma. Methods: We obtained data on druggable genes and screened genes within lung expression quantitative trait loci (eQTL) and blood eQTL. Then, MR analysis and colocalization analysis were performed to identify genes highly associated with asthma. In addition, phenome-wide analysis, enrichment analysis and protein-protein interaction network construction (PPI) have been carried out, providing valuable guidance for the development of more effective therapeutic targets. Results: Druggable genes were sourced from the Drug-Gene Interaction Database (DGIdb) and supplemented by a compilation of druggable genes outlined in a review by Finan et al. The eQTL data sets are derived from eQTLGene and GTEx v8. We obtained asthma GWAS data sets from two large-scale genotypic data sets, FinnGen, and UK Biobank. Finally, we identified six druggable genes significantly associated with asthma. Five druggable genes in whole blood (IRF1, OXER1, PSMA4, UNC13D and HLA-DRB1) and one in lung tissue (CD226). These positive gene interactions were shown to be associated with asthma pathways by enrichment analysis. In the end, phenome-wide analysis showed that most had no side effects. Conclusion: This study identified six potential drug targets for the treatment of asthma. This discovery provides promising insights for more effective treatments for asthma, with the potential to reduce drug development costs.
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