ABSTRACT Community detection of Mild cognitive impairment (MCI) and early Alzheimer’s disease and related dementias (ADRD) may be limited due to the lack of screening tests characterizing the earliest signs of impairment and correspondence to biomarkers as defined by the amyloid-tau-neuronal injury/neurodegeneration (ATN) framework. Accumulating evidence suggests that neuronal injury and neurodegeneration begins decades before clinically evident cognitive decline. Thus, by the time ADRD is clinically diagnosed, irreversible neuronal damage has already occurred. This has the potential of lessening the therapeutic benefits of disease modifying medications. In R01AG071514, we are examining novel ways to overcome major challenges to improve the detection of MCI and early AD by emphasizing deep phenotyping to enhance the research value of data and biospecimens contributed by individual participants and cross validate screening efforts linking prevalence data to brain biomarkers, leveraging the ATN research framework to anchor this work. However most current ATN biomarkers are expansive, invasive and not readily accessible for clinical care. To address this critical need, we aim to develop non-invasive, easily acquired biomarkers conducive for the early detection of ADRD. The retina and brain share similar anatomic and physiologic features, but, unlike the brain, the retina is easily accessible for imaging. The retina and brain share similar anatomic and physiologic features, but, unlike the brain, the retina is easily accessible for imaging. Recent studies showed that amyloid deposition occurs not only in the brain but also in the retina, greater in patients with AD compared to normal healthy controls. For this administrative supplement, we teamed with Drs. Jianhua Wang and Hong Jiang, experts in ophthalmic imaging of the Advanced Ophthalmic Imaging lab at the Bascom Palmer Eye Institute. Confocal scanning laser ophthalmoscopy (cSLO) will be used along with OCT/OCTA to image the retina before and after oral curcumin intake. This proposed work takes advantage of well-characterized and deeply phenotyped cohort from our funded R01 AG071514. We propose 3 SPECIFIC AIMS: (1) Develop and validate retinal amyloid imaging; (2) Determine relationship of retinal amyloid imaging to brain amyloid imaging; and (3) test whether baseline retinal amyloid imaging can predict transition. At the conclusion of our study, we will collect sufficient preliminary data for future R01 proposal and the cost-effective and noninvasive method for in vivo imaging of amyloid deposition in the retina will be fully developed to be used for screening and clinical trials.