Age-related macular degeneration (AMD) is characterized by complex interactions between genetic and environmental factors. Here we genotyped the selected 25 single-nucleotide polymorphisms (SNPs) in 983 cases with advanced AMD and 271 cases with intermediate AMD and build an AMD life-risk score model for assessment of progression from intermediate to advanced AMD. We analyzed the performance of the prediction model for geographic atrophy progressors or choroidal neovascularization progressors versus non-progressors based on the 25 SNPs plus body mass index and smoking status. Our results suggest that a class prediction algorithm can be used for the risk assessment of progression from intermediate to late AMD stages. The algorithm could also be potentially applied for therapeutic response, and toward personalized care and precision medicine.

https://doi.org/10.1038/sigtrans.2016.16

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