Metabolomics a Novel Tool for Investigating the Pathogenesis of Age-related Macular Degeneration

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PROJECT SUMMARY Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly in developed nations, representing a significant socioeconomic burden. Even though its multifactorial nature is well recognized, the pathogenesis of AMD is not fully understood. This has led to the current absence of treatments for dry AMD and lack of reliable ways to determine risk prediction for progression. Thus, there is great need for better understanding of AMD pathobiology and identification of biomarkers. Our group has reported (PMID 28542375, 28916333 and 30672297) and there is new data showing that metabolomics—the qualitative and quantitative analysis of metabolites (molecules <1 kDa)—is an appropriate approach to address these needs. While the metabolome is downstream of the genome, transcriptome, and proteome, it is simultaneously impacted by a wide range of environmental exposures. Therefore, the metabolome closely represents phenotype, as demonstrated in complex conditions, such as cancer and Alzheimer’s disease. To evaluate the role of metabolomics in AMD, we initiated a cross sectional study in which we prospectively recruited 491 patients, obtained an ophthalmological exam and collected fasting blood and urine samples. Analysis of the blood samples identified changes in the metabolomics profile of patients with AMD compared to controls, with differences across AMD severity stages. These differences were mostly found in the lipid pathways, in particular glycerophospholipids and sphingolipids, and purines. In this application, our goal is to provide novel insights into the pathogenesis of AMD, and to identify metabolomic signals that can lead to future biomarkers of this disease and its progression. To do so, we will further characterize the metabolome of AMD. This will be achieved by: 1) performing tissue metabolomics in donor eyes with AMD and control eyes using mass spectrometry (Aim 1A), and assessing correlations between the metabolomic profiles of AMD in tissue and biofluids (i.e. plasma and urine) (Aim 1B); 2) re- assessing our study cohort with early and intermediate AMD, five years after the initial enrolment, with the same protocols, to compare the metabolome of AMD-progressors versus non progressors (Aim 2); and 3) studying the associations between genes linked with AMD risk and metabolomics profiles (Aim 3A), and identifying new metabolite-AMD associations (Aim 3B). This project will provide a unique strategy to increase the current understanding of AMD pathogenesis. By performing tissue metabolomics and studying metabolomics-gene interactions, this proposal will help in identifying new targets for prevention and earlier intervention, thus reducing the burden of AMD. Additionally, this work has the potential to identify biological biomarkers of AMD and disease progression at five years in accessible biofluids, which may contribute to improved screening and risk assessment of AMD and usher in an era of precision medicine for this blinding condition.