Recent Developments for Context Specificity in PRS

Recent Developments for Context Specificity in PRS | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Recent Developments for Context Specificity in PRS Elia Tiso, Kristi Läll, Märt Möls, Massimo Mezzavilla, Luca Pagani, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9341544/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Polygenic Risk Scores (PRS) are increasingly used in precision medicine, yet their predictive performance varies across ancestry, sex, and other contexts, raising concerns about fairness and clinical utility. Recent methodological advances aim to improve portability and fairness through ancestry-aware modelling, privacy-preserving frameworks, and more interpretable designs, on top of increasing the overall performance. Despite progress, challenges remain in balancing accuracy, scalability, and transparency, which are essential for clinical implementation. Given the rapid pace of methodological development, existing reviews may no longer fully capture the state of the field. We present a systematic review that addresses this gap by highlighting strategies to improve PRS portability and fairness, methodological innovations and future directions for clinical translation. We focused on methodological developments from mid-2023 to late 2025, prioritising approaches that address context-specificity, especially ancestry. Using a structured PubMed query, we retrieved methods that introduced innovative frameworks for ancestry-aware or context-calibrated prediction which we classified into focus-related categories. For each method, we extracted core features and commented on the improvements over the PRS landscape. We then concluded with some notes on privacy-preserving strategies and ensemble learning pipelines, relevant challenges and opportunities to reach a broader application of PRS in disease prediction. We recognise notable improvements in ancestry-awareness and handling, and, overall, general improvements in input variability and framework's techniques are clear, narrowing the gap between PRS and clinical application. Despite these advances, challenges remain in balancing accuracy, interpretability, and scalability. Personalized Medicine Epigenetics & Genomics Statistical Epidemiology PRS genomics review context-specific ancestry prediction methods Full Text Additional Declarations The authors declare no competing interests. Supplementary Files Tiso2026ReviewPRSsuppl.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9341544","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":618742871,"identity":"1a7f3579-9dd1-4f31-b009-eb8f7c97602b","order_by":0,"name":"Elia Tiso","email":"","orcid":"https://orcid.org/0009-0003-1371-0108","institution":"Institute of Genomics, University of Tartu","correspondingAuthor":false,"prefix":"","firstName":"Elia","middleName":"","lastName":"Tiso","suffix":""},{"id":618742872,"identity":"6cdcc4ae-b8f6-4acb-a67f-2ba6c9817684","order_by":1,"name":"Kristi 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