Age-Related Macular Degeneration and Its Genetic Risk: A Population-based Study.

PURPOSE: Specific genetic factors might serve as markers for risk stratification of AMD progression, but their association with key features of AMD has not been fully elucidated. Thus, we investigated the association between overall and pathway-specific genetic risk scores (GRS) and lead loci () with AMD stages and features of high-risk nonlate AMD, including reticular pseudodrusen (RPD) and large drusen area (LDA).

METHODS: We performed a cross-sectional analysis of data from the Rhineland Study, a population-based study in Bonn, Germany. We included 4016 individuals aged 50 years and older of European descent. GRS and pathway-specific subscores were constructed based on a large genome-wide association study of AMD. Subscores were generated based on gene-pathways associations (complement, extracellular matrix remodeling (ECM) and lipid metabolism). Associations were assessed using logistic and multinomial regression.

RESULTS: The mean age of participants was 63.36 years and 1813 (45.1%) were men. The GRS was positive in 48.1% of individuals and increased, but did not fully overlap, across AMD stages. Pathway-specific subscores increased across AMD stages except for the ECM subscore, which only showed a trend for increasing in late AMD. Increasing overall GRS was associated with RPD and LDA (OR [95%CI] for RPD: 1.70 [1.33-2.15], for LDA: 1.64 [1.29-2.07]) among individuals with AMD. Similarly, higher complement and ECM subscores was associated with RPD, while for LDA, only an association with complement subscore was observed.

CONCLUSIONS: In a population-based setting, we confirmed higher genetic risk to be associated with more severe AMD and identified associations with high-risk features of intermediate AMD. Conjoint analyses suggested that high-risk features and late AMD might be differentially associated with genetic architecture in AMD, such as ECM remodeling. Incorporation of genetic information such as GRSs might improve AMD risk prediction strategies.

PMID: 39155542