The discovery of genetic predictors of AMD has enabled the identification of individuals at heightened risk, laying the foundation for a new clinical approach targeted to early detection and personalized management of this disease. 

) gene encodes a mitochondrial protein localized in the photoreceptors outer segment. C3 (

) genes encode respectively the pivotal protein and the major inhibitor of the alternative pathway of the complement system. 

Mathematical models have been progressively used to prepare algorithms capable of calculating the probability of progression of an individual toward the advanced stages of AMD.

  Former algorithms provided an original tool for identification of high-risk subjects among patients with early AMD. Though, their diffusion among Ophthalmologists has been limited, so far. 

Starting from this experience, and based upon data coming from recent and consistent population-based studies, we have elaborated a mathematical model to predict the clinical risk of advanced AMD. Both genetic and epigenetic variables were combined, for a total amount of 13 parameters. 

We divided the risk scores into 5 levels: 

I = low, II = mild, III = medium, IV = medium-high, V = high

. The average risk of progression toward advanced stages of the disease, among the population over 60, is about 10%. People in the first level have a risk of late AMD lower than the average risk. People in the fourth and fifth levels have substantial chance of advanced disease, although only 3% belongs to these two categories. 

The patients' risk level is calculated with software, originally designed for the AMDGeneticTest6 (Sooft Italia, Montegiorgio, Italy). The software follows a two-step procedure. First, it calculates the hypothetical pure 'genetic predisposition', based on genotype obtained from the collected sample (buccal cytobrushes). Then, after incorporating the OR of epigenetic parameters, it determines the overall 'clinical risk' of the patient of developing an advanced form of AMD within a certain period of time. 

New clinical approach targeted to early detection