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Originally published In Press as doi:10.1167/iovs.08-3064 on December 30, 2008
(Investigative Ophthalmology and Visual Science. 2009;50:2044-2053.)
© 2009 by The Association for Research in Vision and Ophthalmology, Inc.
doi:10.1167/iovs.08-3064

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Prediction Model for Prevalence and Incidence of Advanced Age-Related Macular Degeneration Based on Genetic, Demographic, and Environmental Variables

Johanna M. Seddon,1 Robyn Reynolds,1 Julian Maller,2 Jesen A. Fagerness,2 Mark J. Daly,2 and Bernard Rosner3

1From the Ophthalmic Epidemiology and Genetics Service, Tufts University School of Medicine and Tufts Medical Center, Boston, Massachusetts; the 2Center for Human Genetic Research, Massachusetts General Hospital and Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Boston, Massachusetts; and the 3Channing Laboratory, Harvard Medical School, Boston, Massachusetts.

PURPOSE. The joint effects of genetic, ocular, and environmental variables were evaluated and predictive models for prevalence and incidence of AMD were assessed.

METHODS. Participants in the multicenter Age-Related Eye Disease Study (AREDS) were included in a prospective evaluation of 1446 individuals, of which 279 progressed to advanced AMD (geographic atrophy or neovascular disease) and 1167 did not progress during 6.3 years of follow-up. For prevalent AMD, 509 advanced cases were compared with 222 controls. Covariates for the incidence analysis included age, sex, education, smoking, body mass index (BMI), baseline AMD grade, and the AREDS vitamin–mineral treatment assignment. DNA specimens were evaluated for six variants in five genes related to AMD. Unconditional logistic regression analyses were performed for prevalent and incident advanced AMD. An algorithm was developed and receiver operating characteristic curves and C statistics were calculated to assess the predictive ability of risk scores to discriminate progressors from nonprogressors.

RESULTS. All genetic polymorphisms were independently related to prevalence of advanced AMD, controlling for genetic factors, smoking, BMI, and AREDS treatment. Multivariate odds ratios (ORs) were 3.5 (95% confidence interval [CI], 1.7–7.1) for CFH Y402H; 3.7 (95% CI, 1.6–8.4) for CFH rs1410996; 25.4 (95% CI, 8.6–75.1) for LOC387715 A69S (ARMS2); 0.3 (95% CI, 0.1–0.7) for C2 E318D; 0.3 (95% CI, 0.1–0.5) for CFB; and 3.6 (95% CI, 1.4–9.4) for C3 R102G, comparing the homozygous risk/protective genotypes to the referent genotypes. For incident AMD, all these variants except CFB were significantly related to progression to advanced AMD, after controlling for baseline AMD grade and other factors, with ORs from 1.8 to 4.0 for presence of two risk alleles and 0.4 for the protective allele. An interaction was seen between CFH402H and treatment, after controlling for all genotypes. Smoking was independently related to AMD, with a multiplicative joint effect with genotype on AMD risk. The C statistic for the full model with all variables was 0.831 for progression to advanced AMD.

CONCLUSIONS. Factors reflective of nature and nurture are independently related to prevalence and incidence of advanced AMD, with excellent predictive power.





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