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Published on: July 14, 2016
Associations Between Structural Phenotype and Polygenic Risk Scores in Intermediate Age-Related Macular Degeneration
Lukas Schloesser1,2, Jan H Terheyden1, Charlotte Behning3
1Department of Ophthalmology, University of Bonn, Bonn, Germany.
Polygenic risk scores (PRS) are linked to structural biomarkers in intermediate age-related macular degeneration (iAMD). These genotype-phenotype associations highlight iAMD heterogeneity and identify patient subgroups for targeted clinical trials.
Area of Science:
- Ophthalmology
- Genetics
- Biomarkers
Background:
- Intermediate age-related macular degeneration (iAMD) is a complex condition with varying clinical presentations.
- Understanding the genetic underpinnings of iAMD is crucial for identifying disease subtypes and progression risks.
Purpose of the Study:
- To investigate genotype-phenotype associations in iAMD using global and pathway-specific polygenic risk scores (psPRS).
- To analyze these associations in participants of the prospective European multicenter cohort study MACUSTAR.
Main Methods:
- Assessed structural biomarkers: reticular pseudodrusen (RPD), pigmentary abnormalities, hyper-reflective foci (HRF), and retinal pigment epithelium/outer retinal atrophy (iRORA/cRORA).
- Calculated global and pathway-specific PRS (complement PRS [C-PRS], C-PRS without ARMS2/HTRA1 [C+AH-PRS and AH-PRS], extracellular matrix PRS [E-PRS], and lipid PRS [L-PRS]).
- Utilized multivariable regression models to assess PRS associations with structural iAMD biomarkers, controlling for age and sex.
Main Results:
- RPD was significantly associated with higher AH-PRS, C+AH-PRS, and E-PRS.
- cRORA was significantly associated with higher AH-PRS and C+AH-PRS.
- These associations suggest differential risk characteristics across the iAMD spectrum.
Conclusions:
- Structural risk biomarkers in iAMD are associated with psPRS.
- Findings underscore the heterogeneity of pathogenic pathways in AMD.
- Identified patient subgroups based on genotype-phenotype associations can aid in risk stratification and clinical trial endpoint development.
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