Modelling the Genetic Risk in Age-Related Macular Degeneration

Late-stage age-related macular degeneration (AMD) is a common sight-threatening disease of the central retina affecting approximately 1 in 30 Caucasians. Besides age and smoking, genetic variants from several gene loci have reproducibly been associated with this condition and likely explain a large proportion of disease. Here, we developed a genetic risk score (GRS) for AMD based on 13 risk variants from eight gene loci. The model exhibited good discriminative accuracy, area-under-curve (AUC) of the receiver-operating characteristic of 0.820, which was confirmed in a cross-validation approach. Noteworthy, younger AMD patients aged below 75 had a significantly higher mean GRS (1.87, 95% CI: 1.69–2.05) than patients aged 75 and above (1.45, 95% CI: 1.36–1.54). Based on five equally sized GRS intervals, we present a risk classification with a relative AMD risk of 64.0 (95% CI: 14.11–1131.96) for individuals in the highest category (GRS 3.44–5.18, 0.5% of the general population) compared to subjects with the most common genetic background (GRS −0.05–1.70, 40.2% of general population). The highest GRS category identifies AMD patients with a sensitivity of 7.9% and a specificity of 99.9% when compared to the four lower categories. Modeling a general population around 85 years of age, 87.4% of individuals in the highest GRS category would be expected to develop AMD by that age. In contrast, only 2.2% of individuals in the two lowest GRS categories which represent almost 50% of the general population are expected to manifest AMD. Our findings underscore the large proportion of AMD cases explained by genetics particularly for younger AMD patients. The five-category risk classification could be useful for therapeutic stratification or for diagnostic testing purposes once preventive treatment is available

CFH, C3 and ARMS2 Are Significant Risk Loci for Susceptibility but Not for Disease Progression of Geographic Atrophy Due to AMD

Age-related macular degeneration (AMD) is a prevalent cause of blindness in Western societies. Variants in the genes encoding complement factor H (CFH), complement component 3 (C3) and age-related maculopathy susceptibility 2 (ARMS2) have repeatedly been shown to confer significant risks for AMD; however, their role in disease progression and thus their potential relevance for interventional therapeutic approaches remains unknown. Here, we analyzed association between variants in CFH, C3 and ARMS2 and disease progression of geographic atrophy (GA) due to AMD. A quantitative phenotype of disease progression was computed based on longitudinal observations by fundus autofluorescence imaging. In a subset of 99 cases with pure bilateral GA, variants in CFH (Y402H), C3 (R102G), and ARMS2 (A69S) are associated with disease (P = 1.6x10(-9), 3.2x10(-3), and P = 2.6x10(-12), respectively) when compared to 612 unrelated healthy control individuals. In cases, median progression rate of GA over a mean follow-up period of 3.0 years was 1.61 mm(2)/year with high concordance between fellow eyes. No association between the progression rate and any of the genetic risk variants at the three loci was observed (P>0.13). This study confirms that variants at CFH, C3, and ARMS2 confer significant risks for GA due to AMD. In contrast, our data indicate no association of these variants with disease progression which may have important implications for future treatment strategies. Other, as yet unknown susceptibilities may influence disease progression

Area-under-the-curve of the receiver operating characteristic for the 13-SNP genetic risk score and by gene locus.

<p>Observed AUC was 0.820 and the locus-specific AUCs were 0.513, 0.524, 0.536, 0.547, 0.555, 0.571, 0.686 and 0.710 from bottom to top.</p

Five genetic risk groups and relative risk of AMD (ORs and 95% confidence intervals).

1<p>Fraction of individuals in 1000 Genome Project European Ancestry Samples residing in risk groups.</p

Absolute risks for AMD by modeling a general population for various prevalences of AMD (reflecting various age-groups).

1<p>Approximate age-groups corresponding to the modeled prevalences for 65 and 79 years <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037979#pone.0037979-Augood1" target="_blank">[30]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037979#pone.0037979-Friedman1" target="_blank">[31]</a> and for those above 80 years <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037979#pone.0037979-Jonasson1" target="_blank">[32]</a>.</p>2<p>see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037979#pone-0037979-t004" target="_blank">Table 4</a>.</p

Genetic risk score distribution in the study population and in a modeled population.

<p>AMD cases are shown in red, controls in blue, while overlapping bars are shaded blue/red. (<b>A</b>) Genetic risk score distribution for cases (N = 986) and controls (N = 796) in the present study. (<b>B</b>) Counts of cases in (A) were scaled to represent 15% of the total population (assumed as AMD prevalence of the 85–90 year old general population). The density curve represents the risk score distribution in 381 European ancestry samples available through the 1000 Genomes Project (Release 20110521).</p

Risk estimates for each of thirteen AMD risk variants from eight gene loci.

<p>Odds ratios (OR) per risk allele were derived from multiple logistic regression models. Horizontal lines indicate 95% confidence intervals.</p