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| Funder | NATIONAL INSTITUTE ON AGING |
|---|---|
| Recipient Organization | University of Rhode Island |
| Country | United States |
| Start Date | Sep 15, 2022 |
| End Date | May 31, 2027 |
| Duration | 1,719 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10704641 |
Project Summary/Abstract Alzheimer’s disease (AD) is a gradually progressive neurodegenerative disorder that results in total cognitive and functional loss. To date, disease-modifying therapeutics and secondary prevention efforts have proven ineffective in combating this public health burden, which impacts over 5.8 million individuals, and is the 6th
leading cause of death in the United States. The proposed study addresses the critical need for minimally invasive, cost-efficient, scalable, and accessible AD risk screening biomarkers capable of detecting AD in the earliest pathologic stages (preclinical AD) before clinical symptoms are evident. We target biomarkers in the
human retina, a part of the central nervous system (CNS), as they can be visualized non-invasively using standard ophthalmologic techniques and show promise for early AD risk detection and disease monitoring. The Atlas of Retinal Imaging in Alzheimer’s Study (ARIAS) is a longitudinal, observational cohort study to identify
sensitive and specific retinal biomarkers of preclinical AD and define their context of use. The objective of the proposed project is to leverage the existing ARIAS infrastructure, adding reference standard brain imaging biomarkers (3T MRI, Ab PET) and novel plasma biomarkers (ptau231, ptau181) to test the central hypothesis
that retinal biomarker alterations will predict cerebral biomarker changes and mirror longitudinal cerebral biomarker changes in preclinical AD. Four specific aims will be pursued: (1) identify retinal biomarker differences between preclinical AD participants and cognitively unimpaired (CU) older adults; (2) validate candidate retinal
biomarkers cross-sectionally against cerebral biomarkers using Ab PET as a measure of cerebral amyloidosis and MRI as a measure of neurodegeneration; (3) determine the longitudinal relationship between retinal and brain imaging biomarkers, and the ability of baseline retinal biomarkers to predict cognitive and/or brain imaging
biomarker changes over 3-year follow-up; and (4) (exploratory) assess the combined sensitivity and specificity of candidate retinal biomarkers with emergent plasma biomarkers in AD risk prediction. Work will be carried out at one existing ARIAS site and two high performing AD research sites. CU participants will complete 5 study
visits: screening, baseline, year (Y) 1, Y2, and Y3 follow-up. Brain imaging (MRI and Ab PET) and plasma analysis will occur at baseline and Y3 follow-up. Retinal imaging and cognitive evaluation will occur at baseline and Y1, Y2, and Y3 follow-up. Brain imaging, retinal imaging, cognitive evaluation, and plasma analysis will be
supported by four respective cores. Validating retinal biomarkers in preclinical AD is expected to shift focus in AD retinal biomarker development towards systemic, quantitative characterization of retinal risk biomarkers scalable for population-based AD risk screening. Combining plasma biomarkers with sensitive and specific
retinal biomarkers could transform AD risk assessment, allowing identification of AD-related changes decades before clinical onset, which may offer the best chance of therapeutic success. Clinical applications include population-based screening for ideal candidates for emerging secondary prevention therapeutics.
University of Rhode Island
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