{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T22:37:26Z","timestamp":1789252646557,"version":"build-2803163510"},"posted":{"date-parts":[[2026,9,7]]},"group-title":"Genetic and Genomic Medicine","reference-count":63,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,9,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Introduction<\/jats:title>\n                  <jats:p>Polygenic risk scores (PRS) may improve Alzheimer\u2019s disease (AD) risk prediction before symptom onset, yet choosing an appropriate model can be challenging.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>\n                    Using the standardized GenoPred pipeline, 1,752 PRS models (9 algorithms; 584 configurations; 3 genome-wide association studies) were evaluated and stratified by genetic ancestry and\n                    <jats:italic>APOE<\/jats:italic>\n                    diplotype. PRS models were evaluated using 11,200 clinical or autopsy-confirmed AD cases and 19,321 controls age \u226565 from the Alzheimer\u2019s Disease Sequencing Project Release 5.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    PRS results were not consistent across methodologies (Spearman\u2019s \u03c1: \u20130.49 to 1), with &gt;95% of individuals having PRS in both the top and bottom risk deciles. Top-performing PRS were effective at stratifying AD risk across ancestries (AFR:\n                    <jats:italic>P<\/jats:italic>\n                    =2.04\u00d710\n                    <jats:sup>-<\/jats:sup>\n                    <jats:sup>26<\/jats:sup>\n                    ; AMR:\n                    <jats:italic>P<\/jats:italic>\n                    =4.57\u00d710\n                    <jats:sup>-21<\/jats:sup>\n                    ; EAS:\n                    <jats:italic>P<\/jats:italic>\n                    =6.21\u00d710\n                    <jats:sup>-40<\/jats:sup>\n                    ; EUR:\n                    <jats:italic>P<\/jats:italic>\n                    =7.90\u00d710\n                    <jats:sup>-187<\/jats:sup>\n                    ).\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>PRS parameters should be optimized for each ancestry. Contradictory signals across methodologies underscore the need for carefully choosing suitable PRS methods and fine-tuning algorithmic parameters to ensure accuracy and consistency.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Data Availability<\/jats:title>\n                  <jats:p>\n                    Access to the ADSP is controlled by The National Institute on Aging Genetics of Alzheimer\u2019s Disease (NIAGADS). All scripts used to analyze the data are freely available at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/jmillerlab\/prs_comparisons\">https:\/\/github.com\/jmillerlab\/prs_comparisons<\/jats:ext-link>\n                    .\n                  <\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.09.02.26362060","type":"posted-content","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T05:10:18Z","timestamp":1788844218000},"source":"Crossref","is-referenced-by-count":1,"title":["Alzheimer\u2019s Polygenic Risk Scores Are Not Interchangeable: Evidence from 1,752 Models"],"prefix":"10.64898","author":[{"given":"Elizabeth L.","family":"Ward","sequence":"first","affiliation":[{"name":"Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Division of Biomedical Informatics, Department of Internal Medicine, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Department of Pathology and Laboratory Medicine, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Department of Neuroscience, University of Kentucky, Lexington, KY 40506, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter T.","family":"Nelson","sequence":"additional","affiliation":[{"name":"Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Department of Pathology and Laboratory Medicine, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Department of Neuroscience, University of Kentucky, Lexington, KY 40506, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuriko","family":"Katsumata","sequence":"additional","affiliation":[{"name":"Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Department of Biostatistics, University of Kentucky, Lexington, KY 40506, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David W.","family":"Fardo","sequence":"additional","affiliation":[{"name":"Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Department of Biostatistics, University of Kentucky, Lexington, KY 40506, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory A.","family":"Jicha","sequence":"additional","affiliation":[{"name":"Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"the Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5309-1570","authenticated-orcid":false,"given":"Justin B.","family":"Miller","sequence":"additional","affiliation":[{"name":"Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Division of Biomedical Informatics, Department of Internal Medicine, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Department of Neuroscience, University of Kentucky, Lexington, KY 40506, USA"},{"name":"Department of Microbiology, Immunology, and Molecular Genetics, University of Kentucky, Lexington, KY 40506, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026090912200539000_2026.09.02.26362060v1.1","doi-asserted-by":"publisher","DOI":"10.1001\/archpsyc.63.2.168"},{"key":"2026090912200539000_2026.09.02.26362060v1.2","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-022-01024-z"},{"key":"2026090912200539000_2026.09.02.26362060v1.3","doi-asserted-by":"publisher","DOI":"10.1001\/archpsyc.1987.01800170026005"},{"key":"2026090912200539000_2026.09.02.26362060v1.4","doi-asserted-by":"crossref","first-page":"1307","DOI":"10.1016\/j.jalz.2017.04.011","article-title":"Incidence of cognitively defined late-onset Alzheimer\u2019s dementia subgroups from a prospective cohort study","volume":"13","year":"2017","journal-title":"Alzheimer\u2019s & Dementia"},{"key":"2026090912200539000_2026.09.02.26362060v1.5","doi-asserted-by":"publisher","DOI":"10.1016\/S0197-4580(00)00183-4"},{"key":"2026090912200539000_2026.09.02.26362060v1.6","doi-asserted-by":"crossref","unstructured":"Ferreira D , Verhagen C , Hernandez-Cabrera JA , Cavallin L , Guo CJ , Ekman U , et al. 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