PURPOSE Age-related macular degeneration(AMD) is a common multifactorial disease in elderly with a prominent genetic basis. Many risk variants have been identified, but the interpretation is still challenging. We investigated… Click to show full abstract
PURPOSE Age-related macular degeneration(AMD) is a common multifactorial disease in elderly with a prominent genetic basis. Many risk variants have been identified, but the interpretation is still challenging. We investigated the genetic distribution of AMD-associated risk variants in a large European consortium, calculated attributable, and pathway-specific genetic risks, and assessed the influence of lifestyle on genetic outcomes. DESIGN Pooled analysis of cross-sectional data from the E3 consortium. PARTICIPANTS 17.174 individuals aged 45+ participating in 6 population-based cohort studies, 2 clinic based studies, 1 case-control study. METHODS AMD was diagnosed and graded based on fundus photographs. Data on genetics, lifestyle, and diet were harmonized and completed where necessary. Minor allele frequencies and population attributable fraction (PAF) were calculated per single nucleotide polymorphism (SNP). A total genetic risk score (GRS) and pathway-specific risk scores (complement, lipid, extra-cellular matrix, other) were constructed based on the dosage of SNPs and conditional beta's; a lifestyle score was constructed based on smoking and dietary intake. RESULTS The risk variants with the largest difference between late AMD cases and controls, and the highest PAFs were located in ARMS2 (rs3750846) and CHF (rs570618 and rs10922109). Both risk increasing and protective variants had the highest PAFs. Combining all genetic variants, the total genetic risk score ranged from -3.50 to 4.63, was normally distributed and increased with AMD severity. Of the late AMD cases, 1581/1777 (89%) had a positive total GRS. The complement pathway and ARMS2 were by far the most prominent genetic pathways contributing to late AMD (positive GRS 90% of late cases), but risk in three pathways was most frequent (35% of late cases). Lifestyle was a strong determinant of the outcome in each genetic risk category; unfavorable lifestyle increased the risk of late AMD at least twofold. CONCLUSIONS Genetic risk variants contribute to late AMD in the majority of cases. However, lifestyle factors have a strong influence on the outcome of genetic risk, and should be a strong focus in patient management. Genetic risks in ARMS2 and the complement pathway are present in the majority of late AMD, but are mostly combined with risks in other pathways.
               
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