Distinguishing normal aging from age-related macular degeneration at the level of single cells in the living human eye

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Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly in the developed world; no cure exists and prevalence is rising rapidly. Because only primates have a macula and since no model of AMD exists in non-human primates, the disease course can only be elucidated through in-depth study of humans. Blindness in AMD is caused by progressive and irreversible death of rod and cone photoreceptors secondary to degeneration of the retinal pigment epithelium (RPE) that is essential for their health and function. Clinical imaging and histology have informed us greatly about the later stages of disease but fundamental knowledge to understand how AMD diverges from normal aging at onset is lacking. With advanced adaptive optics ophthalmoscopy (AOO) imaging methods, combined with clinical imaging and visual function testing, we will characterize healthy human retinal aging in cross-sectional study, by defining the in vivo RPE-photoreceptor cellular organization and microscopic autofluorescence variation with age and wavelength. This will produce the largest quantitative in vivo normative dataset of AOO cell-based metrics to date and we will use this data to generate new quantitative analysis tools needed to evaluate emerging therapies designed to prevent or slow vision loss in AMD (Aim 1). In a case-control study, we will then compare normal photoreceptor topography and RPE cell morphometry to clinically defined early AMD to quantitatively define the earliest cellular changes in AMD that can be detected in vivo. This work will identify the cellular alterations and phenotypes that differentiate normal aging from early AMD to facilitate early onset detection. These results will be contextualized by comparison to tissue-level alterations seen with aging and early AMD in clinical imaging, specifically choriocapillaris decline and drusen (Aim 2). The results of this study will result in a paradigm shift from the use of clinical diagnosis and classification systems for AMD that rely solely on tissue- level biomarkers or traditional funduscopic clinical signs to those that rely on rigorous quantitative in vivo cell- based metrics. Together, this knowledge and these tools will lay the foundation needed to develop and evaluate new preventative therapies that are needed to limit or prevent vision loss in AMD.