Statistical model predicts risk of advanced AMD AREDS investigators have constructed a statistical model using known genetic, demographic and environmental risk factors that is able to accurately predict the progression to advanced AMD with 81.3% certainty.

Knowledge about genetic and epidemiologic risk factors for age-related macular degeneration (AMD) has grown exponentially in recent years. Several genetic variants with strong and consistent associations with AMD have recently been identified. We also know that in addition to age, ethnicity, and family history, there are modifiable factors: smoking, nutritional antioxidants and omega-3 fatty acid intake, and obesity. However, it remains unknown whether all these genetic and environmental factors act independently or jointly and to what extent they as a group can predict the occurrence of AMD or progression to advanced AMD from early and intermediate stages. Such information may be useful for screening those at high risk due to a positive family history or having signs of early or intermediate disease, among whom some progress to advanced stages of AMD with visual loss. Early detection could reduce the growing societal burden due to AMD by targeting and emphasizing modifiable habits earlier in life and recommending more frequent surveillance for those highly susceptible to the disease.

Participants in the 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.

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 for complement factor H (CFH) Y402H; 3.7 for CFH rs1410996; 25.4 for LOC387715 A69S (ARMS2); 0.3 for C2 E318D; 0.3 for CFB; and 3.6 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.

This study, for the first time to our knowledge, shows the independent association of six genetic variants with both prevalence and incidence of advanced AMD, with adjustment for all the genetic variants in addition to ocular, demographic, behavioral, and treatment factors. Discrimination between persons who progressed to advanced AMD and those who did not progress was excellent. Clearly, genetic factors play a major role in this disease. However, modifiable factors also have an impact. Cigarette smoking increased risk for all genotypes. For example, risk of advanced AMD increased from over 3-fold for nonsmokers to almost 10-fold for smokers among individuals with the same homozygous C3 risk genotype compared with nonsmokers with the nonrisk genotype. Higher BMI also contributed to the risk profile for all genotypes.

The investigators show that a model with six genetic factors significantly contributes to the prediction of AMD progression, above and beyond knowledge of the ocular phenotype (presence or absence of existing AMD). In other words, the prediction of advanced AMD progressively improves beyond knowledge of only the demographic (eg. age) and ocular factors (eg. grade of AMD) when the behavioral factors smoking and BMI are added to the model, and improves even more when genetic factors are known.

Previous research has found a significant interaction between the CFH Y402H variant and treatment benefit, whereby patients with the CC (i.e., high risk) genotype are less likely to benefit from the AREDS antioxidant–mineral supplementation than are subjects with the TT and CT genotypes. However, inclusion of this effect increased the C statistic by less than 1%. Therefore, this was omitted from the risk prediction algorithm.

These results indicate the potential for individual prediction of risk for advanced AMD. In calculating a risk score, one could estimate "points" for smoking, BMI, antioxidant use, and genetic status to obtain an overall risk assessment for an individual to progress to advanced AMD. This process could be refined as new genetic and environmental predictors are established.

Targeting high-risk individuals could lead to heightened awareness and more frequent surveillance and clinical examinations, as well as identification of high-risk individuals for inclusion in clinical trials of new therapies. Other advantages of knowing such a risk score include the possibility of more targeted education and counseling about known modifiable factors. Screening would identify high-risk individuals who would be encouraged to follow a healthy lifestyle by not smoking, eating vegetables and fish, maintaining a normal weight and getting exercise, and taking antioxidant–mineral supplements. All of these factors are known to influence the inflammatory and immune pathways that are involved in the pathogenesis of AMD.

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Invest Ophthalmol Vis Sci. 2009;50:2044-2053.