Abstract

Alzheimer's disease (AD) involves progressive neurodegeneration leading to the loss of normal neuronal function. Extracellular accumulation of amyloid-beta (Aß), through the abnormal cleavage of the amyloid precursor protein (APP) by ß- and γ-secretases, is one of the hallmarks of AD. Current research focuses on finding potential candidates for biomarkers and techniques with improved sensitivity for early disease detection. Extracellular vesicles (EVs) found in body fluids are a source of biomarkers for AD diagnosis. EVs transport pathologically significant biomolecules, like nucleic acids and proteins, across the blood-brain barrier, mediating local and distant cell-to-cell communication. Therefore, this study evaluated EV-associated DNA and a novel immuno-qPCR (iqPCR) technique for their prospective use in AD diagnosis. In the first part of the study, EVs secreted by AD iPS-derived neural cells (iPS-NCs) were analyzed for deviant sequences of APP DNA. Results indicate that AD EVs carry two nucleotide deletions in the sequence located upstream of the γ-secretase cleavage site, which could affect APP processing. For the second part of the study, various conditions were set up and optimized to test a novel iqPCR model for the detection of Aß. Results confirm the immunocapture of Aß and suggest that the proposed iqPCR model could detect and quantify Aß at concentrations as low as 10 picogram/mL. The differential sequences of EV-associated APP DNA and the highly sensitive iqPCR technique for the detection of Aß presented in this study create a crucial groundwork for research on early diagnosis, prognosis, and assessment of therapy response in AD.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu

Graduation Date

2022

Semester

Fall

Advisor

Sugaya, Kiminobu

Degree

Master of Science (M.S.)

College

College of Medicine

Department

Burnett School of Biomedical Sciences

Degree Program

Biotechnology

Identifier

CFE0009822; DP0027763

URL

https://purls.library.ucf.edu/go/DP0027763

Language

English

Release Date

June 2024

Length of Campus-only Access

1 year

Access Status

Masters Thesis (Open Access)

Location

College of Medicine

Download

Included in

Biotechnology Commons

Share

COinS