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The genetic risk remains largely unexplained because of limited sample sizes and heterogeneous phenotypes in genome\u2010wide association studies (GWAS). This study investigates whether current GWAS data can be used to construct a polygenic score (PGS) capturing genetic susceptibility to severe PD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>\n                      A PGS was developed in a three\u2010step design, using a German EO\u2010III\/IV\u2010C\u2010PD GWAS (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009692 cases, \u2264\u200935\u2009years at diagnosis) as the base dataset, a Spanish EO\u2010III\/IV\u2010C\u2010PD GWAS (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009441 cases) to optimise the score, and as validation a Dutch EO\u2010III\/IV\u2010C\u2010PD GWAS (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009171 cases) and a German population\u2010based GWAS with later\u2010onset III\/IV\u2010PD (Studies of Health in Pomerania [SHIP],\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20092941 cases).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The PGS showed a trend towards association with disease status in the Spanish sample (Nagelkerke\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u20090.4%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.06; AUC\u2009=\u20090.52; 95% confidence interval [CI]:\u20090.49\u20130.56), but not in the smaller Dutch dataset (\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u20090.2%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.18; AUC\u2009=\u20090.52; 95% CI:\u20090.48\u20130.57) or in the SHIP dataset (AUC\u2009=\u20090.50, 95% CI:\u20090.48\u20130.52). Case\u2013control distributions overlapped substantially. Genetic correlation analyses revealed no strong overlap with other associated traits.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Current PGS models have limited case\u2013control discriminative ability for PD. Larger harmonised studies are needed to enhance genetic risk prediction and clarify pleiotropic relationships.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jcpe.70195","type":"journal-article","created":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T05:19:42Z","timestamp":1787375982000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Polygenic Risk Modelling in Periodontitis: Insights From a Feasibility Study of 4243 European Cases and Current Limitations"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4825-4670","authenticated-orcid":false,"given":"Gesa M.","family":"Richter","sequence":"first","affiliation":[{"name":"Department of Periodontology, Oral Medicine and Oral Surgery Charit\u00e9\u2014Universit\u00e4tsmedizin Berlin  Berlin Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3251-514X","authenticated-orcid":false,"given":"O. Mercy","family":"Akinloye","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics and Statistics University Medical Center Schleswig\u2010Holstein, Campus Kiel  Kiel Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2816-7168","authenticated-orcid":false,"given":"M. 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