Abstract

Background and Objective: The early diagnosis of neurodegenerative diseases, such as Parkinson's disease (PD), is particularly challenging because symptoms appear only after significant neuronal damage has already occurred. This study is utilizing variant call format (VCF) analysis to identify genetic variants and novel genes that could serve as early prognostic markers for prodromal PD. Materials and Methods: Data were sourced from the Parkinson's Progression Markers Initiative (PPMI), focusing on prodromal patients with gVCF data from the 2021 cohort. The study included 304 participants, comprising 100 healthy controls, 146 individuals with prodromal genetic indicators, 21 individuals with prodromal hyposmia, and 37 individuals with prodromal REM sleep behavior disorder (RBD). A specialized pipeline was developed to process the gVCF samples for variant annotation, as well as pathway and disease association analysis. Results: The analysis of prodromal subgroups revealed novel variant percentages: 1.0% in genetic males, 1.2% in genetic females, 0.6% in hyposmia males, 0.3% in hyposmia females, 0.5% in RBD males, and 0.4% in RBD females. Notably, 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300, and PPP6R2) previously identified in PD patients were also detected in the prodromal stage. Conclusion: Genetic biomarkers are playing a vital role in the early detection of Parkinson's disease and its prodromal phase. The identification of these novel PD genes in prodromal patients highlights the potential for gene biomarkers to enable early diagnosis, beyond relying only on phenotypic traits.

School

School of Sciences and Engineering

Department

Biotechnology Program

Degree Name

PhD in Applied Sciences

Graduation Date

Winter 2-19-2025

Submission Date

12-18-2024

First Advisor

Mohamed Salama

Committee Member 1

Hassan El-Fawal

Committee Member 2

May Bakr

Committee Member 3

Shiamaa El-Jaafary & Noha Yousri (External Examiners)

Extent

138 p.

Document Type

Doctoral Dissertation

Institutional Review Board (IRB) Approval

Not necessary for this item

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