April 2009
Volume 50, Issue 13
ARVO Annual Meeting Abstract  |   April 2009
Prediction Model for Prevalence and Incidence of Advanced Age-Related Macular Degeneration Based on Genetic, Demographic, and Environmental Variables
Author Affiliations & Notes
  • J. M. Seddon
    Ophthalmology, Tufts Med Ctr, Tufts University School of Medicine, Boston, Massachusetts
  • R. Reynolds
    Ophthalmology, Tufts Med Ctr, Boston, Massachusetts
  • J. Maller
    Broad Institute, Boston, Massachusetts
  • J. Fagerness
    Massachusetts General Hospital, Boston, Massachusetts
  • M. Daly
    Broad Institute, Harvard, MIT, Boston, Massachusetts
  • B. Rosner
    Channing Laboratory, Boston, Massachusetts
  • Footnotes
    Commercial Relationships  J.M. Seddon, Tufts Medical Center, P; R. Reynolds, None; J. Maller, None; J. Fagerness, None; M. Daly, Tufts Medical Center, P; B. Rosner, None.
  • Footnotes
    Support  NIH grant EY11309;Foundation Fighting Blindness; Mass. Lions Res. Fund; Research to Prevent Blindness; Macular Degen. Res. Fund, Ophthalmic Epidemiology and Genetics Service,Tufts Medical Center.
Investigative Ophthalmology & Visual Science April 2009, Vol.50, 3453. doi:
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      J. M. Seddon, R. Reynolds, J. Maller, J. Fagerness, M. Daly, B. Rosner; Prediction Model for Prevalence and Incidence of Advanced Age-Related Macular Degeneration Based on Genetic, Demographic, and Environmental Variables. Invest. Ophthalmol. Vis. Sci. 2009;50(13):3453.

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      © ARVO (1962-2015); The Authors (2016-present)

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Purpose: : Several genes are associated with age-related macular degeneration (AMD), but their independent effects on prevalence and incidence of AMD have not been evaluated while controlling for all genetic as well as environmental factors. We evaluated the joint effects of genetic, ocular, and environmental variables and assessed predictive models for AMD.

Methods: : Caucasian participants in the multi-center 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 included smoking, body mass index (BMI), AMD grade and 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. Receiver operating characteristic curves and C statistics were calculated to assess the predictive ability of risk scores to discriminate progressors from non-progressors.

Results: : All genetic polymorphisms were independently related to prevalence of advanced AMD, controlling for genetic factors, smoking, BMI, and AREDS trreatment. Multivariate ddds ratios (OR’s) 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 variants except CFB were significantly related to progression to advanced AMD, controlling for baseline AMD grade and other factors, with OR’s from 1.8 to 4.0 for one or two risk alleles, and 0.4 for the protective allele. An interaction was seen between CFH402H and treatment controlling for all genotypes. Smoking was independently related to AMD, with no interaction with genotypes. 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.

Keywords: age-related macular degeneration • genetics • clinical (human) or epidemiologic studies: prevalence/incidence 

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