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

Age-related macular degeneration (AMD) is the leading cause of adult blindness in developed countries and the third cause of global blindness. It is an eye-ageing disease with tremendous impact in daily quality of life. Clinically, AMD is a progressive disease, which evolves from early to late stages - geographic atrophy (GA) or choroidal neovascularization (CNV). GA has currently no treatment and CNV requires several costly intravitreal injections. Patients with late stages of AMD represent a huge economic burden to society, with enormous medical and non-medical costs.

Predicting progression is therefore of utmost importance. It is established that AMD progression has a multifactorial nature, combining phenotypic and several environmental and genetic risk factors. Attempts have been made to include the different risk-factors in theoretical predicting models, however they are not practical on the clinical setting and fail to explain biological interactions. Thus, in the current clinical practice, risk prediction is still being assessed on a phenotypic basis, not considering AMD multifactorial nature.

A new approach that may allow the integration of all AMD interacting factors is metabolomics, the simultaneous multiparametric measurement of metabolic changes in living organisms as a response to perturbation (disease, diet, environment, others). The value of metabolomics in medical research has become clear through several studies on cancer, cardiovascular disease, and Alzheimer disease (AD), the latter sharing common pathways with AMD, as well as by increasing investments in this area. The metabolome reflects the occurring biochemical processes, therefore forming a fingerprint of the organism's health status, at a given time, which can be measured through nuclear magnetic resonance (NMR) spectroscopy and/or mass spectrometry (MS). The research team's previous work showed that metabolomics can be a powerful tool to study AMD as well, enabling the identification of specific plasma metabolomic profiles in AMD, which vary with the severity stages, and are primarily lipid metabolites linked to glycerophospholipid and sphingolipid pathways, as well as purines The current study will further elucidate the role of metabolomics in the understanding of AMD, and will also identify potential biologically robust biomarkers that can address the problem of predicting progression. The investigators hypothesize that the plasma and urinary metabolomic profile of subjects who progress over a five-year period (progressors) is distinct from those who remain at the same AMD severity stage (non-progressors). Based on our preliminary data, The investigators hypothesize that a panel of metabolites will distinguish these two groups (progressors vs non-progressors), and that this will mostly consist of lipids and amino acids.

To achieve these purposes, subjects who participated in our group's previous prospective study on AMD metabolomics will be recruited. Eligible subjects will be all that participated in the the IN654 study (between January 2015 and July 2016). These will be recalled and progression will be phenotypically assessed, thus defining the AMD-progressors and non-progressors groups.

Metabolomic signatures of AMD progression and disease will lay the path for the future definition of progression metabolic biomarkers, which can represent a rapid, reliable and potentially affordable methodology for progression prediction. Overall, this approach should offer an opportunity to identify new valuable supplemental tools for routine clinical evaluation. This will allow medical interventions based on preventive strategies to reduce progression to blindness stages, which will, ultimately, also reduce societal costs of AMD.