Dissertations, Theses, and Capstone Projects

Date of Degree

5-2019

Document Type

Dissertation

Degree Name

Ph.D.

Program

Biology

Advisor

Stephen Redenti

Committee Members

Hyungsik Lim

Daniel Casper

Dianne Cox

Konstantinos Krampis

Subject Categories

Bioinformatics | Disease Modeling | Endocrine System Diseases | Eye Diseases | Molecular and Cellular Neuroscience | Molecular Biology | Nervous System Diseases

Keywords

extracellular vesicles, diabetes, diabetic retinopathy, proteomics, next generation sequencing, biomarker

Abstract

Diabetic Retinopathy (DR) is a neurovascular complication associated with diabetes mellitus that affects approximately 120 million people worldwide and its prevalence is expected to reach 190 million by 2030. DR diagnosis is accomplished with fundus ophthalmoscopy often when retinal damage and vision loss have already occurred. A group of biomarker being explored for early detection of diseases are extracellular vesicles (EVs), which are nanometer diameter lipid enclosed vesicles, released from all cell types and containing genetic cargo reflective of releasing cell state. EV biomarkers are currently being explored to help monitor disease predisposition, pathogenesis and response to treatment. While an increasing number of studies are analyzing EVs in the brain, EV morphology, release rates and content have yet to be elucidated in retinal disease. The approach to characterizing retinal EVs in this work is based on the premise that unique aspects of DR retinal cell expression patterns can be detected in retinal EV release rate and genetic cargo. This initial work has identified molecular signatures that have been shown to be involved in DR pathogenesis to be present in EVs and may be built on in future studies to develop a biomarker for early detection of DR prior to retinal damage and vision loss.

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