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, Jeffrey Kim, Thiago Peixoto Leal, María Teresa Periñán, Sumit Dey, Alastair J. Noyce, Armando Reyes-Palomares, Noela Rodriguez-Losada, Jia Nee Foo, Wael Mohamed, Karl Heilbron, Lucy Norcliffe-Kaufmann, Mie Rizig, Njideka Okubadejo, Mike A. Nalls, Cornelis Blauwendraat, Andrew Singleton, Hampton Leonard, Ignacio F. Mata, Sara Bandres-Ciga
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In this study, we constructed 105 PRS using individual-level data from seven ancestries and compared two different models. <i>Model 1</i> 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). <i>Model 2</i> leveraged multi-ancestry summary statistics using a <i>p</i>-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.</p>","PeriodicalId":19706,"journal":{"name":"NPJ Parkinson's Disease","volume":"70 1","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Insights into ancestral diversity in Parkinson’s disease risk: a comparative assessment of polygenic risk scores\",\"authors\":\"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, Jeffrey Kim, Thiago Peixoto Leal, María Teresa Periñán, Sumit Dey, Alastair J. Noyce, Armando Reyes-Palomares, Noela Rodriguez-Losada, Jia Nee Foo, Wael Mohamed, Karl Heilbron, Lucy Norcliffe-Kaufmann, Mie Rizig, Njideka Okubadejo, Mike A. 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Insights into ancestral diversity in Parkinson’s disease risk: a comparative assessment of polygenic risk scores
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.
期刊介绍:
npj Parkinson's Disease is a comprehensive open access journal that covers a wide range of research areas related to Parkinson's disease. It publishes original studies in basic science, translational research, and clinical investigations. The journal is dedicated to advancing our understanding of Parkinson's disease by exploring various aspects such as anatomy, etiology, genetics, cellular and molecular physiology, neurophysiology, epidemiology, and therapeutic development. By providing free and immediate access to the scientific and Parkinson's disease community, npj Parkinson's Disease promotes collaboration and knowledge sharing among researchers and healthcare professionals.