ArticleScientific reports2025
Exploring the causal influence of 731 immune cells on 4 different glaucoma subtypes using a two-sample mendelian randomization method.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Anti-Inflammatory Cytokine Signatures in Primary Glaucoma Subtypes: Diagnostic and Pathophysiological Insights From IL-36Ra, IL-37, and IL-38.Journal of ophthalmology · 2026Article
- Mendelian randomization and bioinformatics analysis identify the association between plasma proteins and cataract.Scientific reports · 2025Article
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5 authors.
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Abstract
In the pathological progression of glaucoma, damage to the ocular nerves and associated tissue alterations can induce a systemic immune response, leading to the activation of various immune cells such as T cells, B cells, and macrophages. This complex process has the potential to intensify the clinical manifestations of glaucoma. Utilising Mendelian randomisation methods to identify the types and quantities of activated immune cells in different glaucoma-related lesions could provide robust evidence for the development of novel immunomodulators and immunosuppressants tailored to specific types of glaucoma, thereby facilitating personalised treatment strategies. We used five Mendelian randomisation (MR) methods-inverse variance weighted (IVW), MR-Egger, simple model, weighted median, and weighted mediation model - to assess causal relationships between immune cells and four glaucoma subtypes: neovascular glaucoma (NVG), primary open-angle glaucoma (POAG), primary closed-angle glaucoma (PACG), and normal-tension glaucoma (NTG). IVW aggregated causal estimates using Wald ratios and variance-weighted meta-analysis. MR-Egger considered horizontal pleiotropy under the InSIDE assumption. The weighted median model required ≥ 50% valid instrumental variables (IVs) for robust inference, while the weighted mediation model adjusted for SNP correlations. The simple model provided additional insight into causality. Glaucoma GWAS data were obtained from FinnGen ( https://finngen.gitbook.io/documentation/ ). Summary statistics for immune cell phenotypes (GWAS IDs: GCST90001391-GCST90002121) were obtained from the GWAS catalogue ( https://www.ebi.ac.uk/gwas/studies/GCST90002121 ). The study has identified a causal relationship between various immune cells and different types of glaucoma. It was found that 21 different types of immune cells had a causal relationship with NVG, 37 types of immune cells had a causal relationship with POAG, 40 different types of immune cells had a causal relationship with PACG, and 24 different types of immune cells had a causal relationship with NTG.
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