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Insights into ancestral diversity in Parkinson’s disease risk: a comparative assessment of polygenic risk scores
Journal article   Open access

Insights into ancestral diversity in Parkinson’s disease risk: a comparative assessment of polygenic risk scores

Paula Saffie-Awad, Spencer M Grant, Mary B Makarious, Inas Elsayed, Arinola O Sanyaolu, Peter Wild Crea, Artur F Schumacher Schuh, Kristin S Levine, Dan Vitale, Mathew J Koretsky, …
NPJ PARKINSON'S DISEASE, Vol.11(1), 201
2025
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CC BY V4.0 Open Access

Abstract

Risk prediction models play a crucial role in advancing healthcare by enabling early detection and supporting personalized medicine. Nonetheless, polygenic risk scores (PRS) for Parkinson’s disease (PD) have not been extensively studied across diverse populations, contributing to health disparities. In this study, we constructed 105 PRS using individual-level data from seven ancestries and compared two different models. Model 1 was based on the cumulative effect of 90 known European PD risk variants, weighted by summary statistics from four independent ancestries (European, East Asian, Latino/Admixed American, and African/Admixed). Model 2 leveraged multi-ancestry summary statistics using a p-value thresholding approach to improve prediction across diverse populations. Our findings provide a comprehensive assessment of PRS performance across ancestries and highlight the limitations of a “one-size-fits-all” approach to genetic risk prediction. We observed variability in predictive performance between models, underscoring the need for larger sample sizes and ancestry-specific approaches to enhance accuracy. These results establish a foundation for future research aimed at improving generalizability in genetic risk prediction for PD.

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Collaboration types
Industry collaboration
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Citation topics
1 Clinical & Life Sciences
1.189 Genome Studies
1.189.455 Genome-Wide Association Studies
Web Of Science research areas
Neurosciences
ESI research areas
Neuroscience & Behavior
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