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Published on: July 14, 2016
Does Age Modify the Relation Between Genetic Predisposition to Glaucoma and Various Glaucoma Traits in the UK
Jihye Kim1, Jae H Kang2, Janey L Wiggs3
1Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States.
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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