ArticleRespiratory research2025
Potential drug targets for asthma identified through mendelian randomization analysis.
Article in Respiratory research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- ADAM19: biological characteristics and implications in disease pathology and clinical applications.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Review
- Polygenic risk scores associate with asthma phenotypes and proteomic analyses implicate IL1R1 in two family-based studies.medRxiv : the preprint server for health sciences · 2026Article
- Modulation of the NF-κB signaling pathway by the combined strategy of tocilizumab and dexamethasone for asthma therapy.Respiratory research · 2026Article
- Network pharmacology and experimental validation reveal that betulin alleviates 5-fluorouracil-induced intestinal injury by inhibiting intestinal senescence and enhances antitumor efficacy.The Journal of pharmacology and experimental therapeutics · 2025Article
- Causal Relationships Between Immune Cell Traits, Plasma Metabolites, and Asthma: A Two-Step, Two-Sample Mendelian Randomization Study.The clinical respiratory journal · 2025Article
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7 authors.
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Abstract
backgroundThe emergence of new molecular targeted drugs marks a breakthrough in asthma treatment, particularly for severe cases. Yet, options for moderate-to-severe asthma treatment remain limited, highlighting the urgent need for novel therapeutic drug targets. In this study, we aimed to identify new treatment targets for asthma using the Mendelian randomization method and large-scale genome-wide association data (GWAS).
methodsWe utilized GWAS data from the UK Biobank (comprising 56,167 patients and 352,255 control subjects) and the FinnGen cohort (including 23,834 patients and 228,085 control subjects). Genetic instruments for 734 plasma proteins and 154 cerebrospinal fluid proteins were derived from recently published GWAS. Bidirectional Mendelian randomization analysis, Steiger filtering, colocalization, and phenotype scanning were employed for reverse causal inference detection, further substantiating the Mendelian randomization results. A protein-protein interaction network was also constructed to reveal potential associations between proteins and asthma medications.
resultsUnder Bonferroni significance conditions, Mendelian randomization analysis revealed causal relationships between seven proteins and asthma. In plasma, we observed that an increase of one standard deviation in IL1R1[1.30 (95% CI 1.20-1.42)], IL7R[1.07 (95% CI 1.04-1.11)], ECM1[1.03 (95% CI 1.02-1.05)], and CD200R1[1.18 (95% CI 1.09-1.27)] were associated with an increased risk of asthma, while an increase in ADAM19 [0.87 (95% CI 0.82-0.92)] was found to be protective. In the brain, each 10-fold increase in IL-6 sRa [1.29 (95% CI 1.15-1.45)] was associated with an increased risk of asthma, while an increase in Layilin [0.61 (95% CI 0.51-0.73)] was found to be protective. None of the seven proteins exhibited a reverse causal relationship. Colocalization analysis indicated that ECM1 (coloc.abf-PPH4 = 0.953), IL-6 sRa (coloc.abf-PPH4 = 0.966), and layilin (coloc.abf-PPH4 = 0.975) shared the same genetic variation as in asthma.
conclusionA causal relationship exists between genetically determined protein levels of IL1R1, IL7R, ECM1, CD200R1, ADAM19, IL-6 sRa, and Layilin (LAYN) and asthma. Moreover, the identified proteins may serve as attractive drug targets for asthma, especially ECM1 and Layilin (LAYN). However, further research is required to comprehensively understand the roles of these proteins in the occurrence and progression of asthma.
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