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Nonetheless, polygenic risk scores (PRS) for Parkinson\u2019s 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.\n                    <jats:italic>Model 1<\/jats:italic>\n                    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).\n                    <jats:italic>Model 2<\/jats:italic>\n                    leveraged multi-ancestry summary statistics using a\n                    <jats:italic>p<\/jats:italic>\n                    -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 \u201cone-size-fits-all\u201d 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.\n                  <\/jats:p>","DOI":"10.1038\/s41531-025-00967-4","type":"journal-article","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T04:47:02Z","timestamp":1751518022000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Insights into ancestral diversity in Parkinson\u2019s disease risk: a comparative assessment of polygenic risk scores"],"prefix":"10.1038","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8056-365X","authenticated-orcid":false,"given":"Paula","family":"Saffie-Awad","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Spencer 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