ArticleInvestigative ophthalmology & visual science2025
Does Age Modify the Relation Between Genetic Predisposition to Glaucoma and Various Glaucoma Traits in the UK Biobank?
Article in Investigative ophthalmology & visual science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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
3 citing papers in PubMed.
- Carotid intima-media thickness in relation to primary open-angle glaucoma: epidemiological and structural evidence from a cross-sectional study.BMJ open ophthalmology · 2026Article
- Pro-Homeostatic Effects of Estrogen on Intraocular Pressure and the Trabecular Meshwork.Investigative ophthalmology & visual science · 2026Article
- The Association of Polygenic Risk Score With Glaucoma and Its Related Traits: Results From Two German Population-Based Studies.Investigative ophthalmology & visual science · 2025Article
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Authors and funding
12 authors.
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Abstract
Purpose: Glaucoma polygenic risk scores could guide glaucoma public health screening initiatives. We investigated how age influences the relationship between a multitrait glaucoma polygenic risk score (mtGPRS) and primary open-angle glaucoma indicators, including intraocular pressure (IOP), retinal structure, and glaucoma prevalence. Methods: We analyzed UK Biobank participants with demographic and genetic data, assessing IOP (n = 118,153), macular retinal nerve fiber layer thickness (mRNFL; n = 42,132), macular ganglion cell inner plexiform layer thickness (mGCIPL; n = 42,042), and prevalent glaucoma status (8982 cases among 192,283 participants). An mtGPRS was constructed using 2673 genetic variants. We used multivariable linear regression to assess how age modifies the relationship between mtGPRS and glaucoma traits (IOP, mRFNL, and mGCIPL) and multivariable logistic regression for prevalent glaucoma risk. We analyzed age quartiles (Q1 = <51, Q2 = 51-57, Q3 = 58-62, and Q4 = ≥63 years) - glaucoma trait interaction tests with the Wald test. All analyses were adjusted for confounders, including nonlinear age effects. Results: Age significantly modified the relationship between the mtGPRS and IOP (Pinteraction = 2.7e-27). Mean IOP differences (millimeters of mercury [mm Hg]) per standard deviation (SD) of mtGPRS were 0.95, 1.02, 1.18, and 1.24 across age quartiles. Similar trends were observed for glaucoma risk (odds ratio per SD of mtGPRS = 2.38, 2.57, 2.80, and 2.75; Pinteraction = 1.0e-06). Relationships between mtGPRS and inner retinal thickness (mRNFL and mGCIPL) across age strata were inconsistently modified by age (Pinteraction ≥ 0.01). Conclusions: With increasing age, an mtGPRS was a better predictor of higher IOP and glaucoma prevalence. It is useful to consider chronological age with genetic information in designing glaucoma screening strategies.
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