For in-depth analysis of multimodal data, an EYE-RISK database was set up and continuously supplied with data. This database includes epidemiological and genetic data from pre-existing cohorts of the European Eye Epidemiology (E3) consortium, which collaborates with EYE-RISK.
To our knowledge, it has grown to be the largest data repository on AMD worldwide. By in-depth analysis of these data we determined the prevalence and incidence of AMD in Europe and made projections for the future. The number of patients within the E.U. is predicted to rise by 50% in 2040 as the population is growing and more people live longer.
Since genetic predispositi on is a major risk factor for AMD, we have designed and optimized an AMD genotyping assay, including published loci strongly associated to AMD risk (International Age-related Macular Degeneration Genomics Consortium; Nature Genetics 2016 with contributions from EYE-RISK partners). This test was used to genotype AMD patients within the EYE-RISK database and correlations between genotypes, AMD phenotpyes as well as lifestyle factors were investigated. For data analysis, statistical and algorithmic software tools have been used.
Results showed that diet influences the risk to develop AMD and that a Mediterranean diet can be protective. Further, we identified a correlation of serum lipid levels with AMD and studied the phenotypic features that correlate to the defined disease states. In addition, we have been creating a network model of genes and their corresponding proteins, built a computational simulation of disease pathways that centres on the genetic risk loci and in-depth investigated candidate markers and network components for their role in AMD pathogenesis. This knowledge was used to characterise several of these proteins by protein chemistry, cellular assays, organotypic cultures and patient derived induced pluripotent stem cells (iPSC) differentiated into RPE.
EYE-RISK partners have extensively analysed primary human blood and tissue as well as iPSC derived cultures of non-risk and genetic risk affected individuals on the level of their RNA and protein expression, metabolism and higher order pathological features including drusen and deposit formation and inflammatory activity. The output of this analysis has been subjected to patient versus control biomaterial for significance. The focus here was on the alternative complement pathway, one of the main drivers for AMD, and on the analysis of lipid and protein deposits in the choreocapillaris-Bruch’s membrane-retinal pigment interface. Two protein arrays of proteins that confer risk have been produced and commercialized and are now under clinical validation.
Integrating the obtained knowledge, EYE-RISK researchers have developed a tool for AMD risk prediction. From information on age, genetic predisposition, physiology, clinical features and lifestyle the model can predict an individual person’s risk to develop AMD. The model shows excellent discriminative performances and has been integrated into a website, which will be made available soon. This will make the provision of personalised health care easier in the future.
