Alzheimer's disease (AD} is a debilitating neurodegenerar!ve conditlon that dramatically impacts patients’ and
caregivers’ liyes. AD ]s preceded by a prodromal stage, Mild Cognitive Impairment (MCI). Identifying structural and functional early bipmarkers of tfie progression from MCI to AD is of ‹ritical clinical importance and is becoming a crucial step to set the course of anti-amylo)d disease-modifying therapies that will soon be available. These therapies are expensive and expected to work only in a selected subset of patients showing early signs of cognitive decline and brain amyloidosls. To date, the identification of at-risk for AD subjects makes use of the combination of neuropsycho)ogicaI testing, Magnetic Resonance Imaging (MRI)-based nevroimaglng, brain biomarkers in the cerebrospinal fluid (CSF), or the assessment of amylold radiollgands with Position Emission Tomography (PET). However, CSF and PET-based biomarkers are subjected to substantial instrumental error acros5 laboratorles, arid Invasive procedures as CS F sampling necessitates In mbar pm B ctures, a procedure requiring tra Ined specialists, while PET-imaging requires advanced and time-consuming methodological approaches. In recent years, growing interest has been gathered to identify, develop, and validate diagnostic and prognostic retinal b!omarkers for AD. Our proposal addresses the investigation of the AD-related and AD- driven changes in peripheral retina's functlonlng and e’yaIuates a relatively Inexpensive, readily applicable, standardized, reproducible, and cost-effective way to identify MCI patients at risk for dementia. Retinal changes will be correlated with parallel undergoing neurodegenerative processes occurring In the brain (assessed wlth MRI, and PET imaging and/or CSfi sampllng} as well as in the blood (assessed with omics-based approaches). All these alterations will be then competed along with co8nitive variations by employing a machlne-learning based approach to predict individual patterns of susceptibility or resistance to the progression to AD and identify at- risk for AD MCI individuals. If successful, the project will generate highly exploitable clinica| and therapeutic outcomes. Using widely employed eye-based screening tools, the project w1II provide a set of novel and unbiased b!omarkers to assess tfie early stages of the MCI-AD spectrum and generate tailored diagnostic, prognostic, profiles, and therapeutic plans.