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Polygenic Risk Modelling in Periodontitis: Insights From a Feasibility Study of 4243 European Cases and Current Limitations

Gesa M. Richter, O. Mercy Akinloye, M. Kamal Nasr, Birte Holtfreter, Alicia de Coo, Silvia Diz De Almeida, Bruno G. Loos, Søren Jepsen, Henrik Dommisch, Corinna Bruckmann, Ines Kapferer‐Seebacher, Georg Homuth, Thomas Kocher, Henry Völzke, Klaus Berger, Matthias Laudes, Wolfgang Lieb, Nathalie van der Velde, Natasja van Schoor, Lisette de Groot, Juan Blanco, Angel Carracedo, Raquel Cruz, Astrid Dempfle, Alexander Teumer, Arne S. Schaefer, Sandra Freitag‐Wolf

Journal of Clinical Periodontology · 2026

Vollständiger Abstract

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ABSTRACT Background and Aim Genetic susceptibility plays a particularly important role in early‐onset (EO) and severe periodontitis (PD). The genetic risk remains largely unexplained because of limited sample sizes and heterogeneous phenotypes in genome‐wide 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. Materials and Methods A PGS was developed in a three‐step design, using a German EO‐III/IV‐C‐PD GWAS ( n = 692 cases, ≤ 35 years at diagnosis) as the base dataset, a Spanish EO‐III/IV‐C‐PD GWAS ( n = 441 cases) to optimise the score, and as validation a Dutch EO‐III/IV‐C‐PD GWAS ( n = 171 cases) and a German population‐based GWAS with later‐onset III/IV‐PD (Studies of Health in Pomerania [SHIP], n = 2941 cases). Results The PGS showed a trend towards association with disease status in the Spanish sample (Nagelkerke R 2 = 0.4%, p = 0.06; AUC = 0.52; 95% confidence interval [CI]: 0.49–0.56), but not in the smaller Dutch dataset ( R 2 = 0.2%, p = 0.18; AUC = 0.52; 95% CI: 0.48–0.57) or in the SHIP dataset (AUC = 0.50, 95% CI: 0.48–0.52). Case–control distributions overlapped substantially. Genetic correlation analyses revealed no strong overlap with other associated traits. Conclusions Current PGS models have limited case–control discriminative ability for PD. Larger harmonised studies are needed to enhance genetic risk prediction and clarify pleiotropic relationships.

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Autor:innen
Gesa M. Richter, O. Mercy Akinloye, M. Kamal Nasr, Birte Holtfreter, Alicia de Coo, Silvia Diz De Almeida, Bruno G. Loos, Søren Jepsen, Henrik Dommisch, Corinna Bruckmann, Ines Kapferer‐Seebacher, Georg Homuth, Thomas Kocher, Henry Völzke, Klaus Berger, Matthias Laudes, Wolfgang Lieb, Nathalie van der Velde, Natasja van Schoor, Lisette de Groot, Juan Blanco, Angel Carracedo, Raquel Cruz, Astrid Dempfle, Alexander Teumer, Arne S. Schaefer, Sandra Freitag‐Wolf
Quelle
Journal of Clinical Periodontology
Publikation
2026-01-01
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Nicht angegeben
Seiten
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ISSN / ISBN
0303-6979, 1600-051X
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Gesa M. Richter, O. Mercy Akinloye, M. Kamal Nasr, Birte Holtfreter, Alicia de Coo, Silvia Diz De Almeida, Bruno G. Loos, Søren Jepsen, Henrik Dommisch, Corinna Bruckmann, Ines Kapferer‐Seebacher, Georg Homuth, Thomas Kocher, Henry Völzke, Klaus Berger, Matthias Laudes, Wolfgang Lieb, Nathalie van der Velde, Natasja van Schoor, Lisette de Groot, Juan Blanco, Angel Carracedo, Raquel Cruz, Astrid Dempfle, Alexander Teumer, Arne S. Schaefer, Sandra Freitag‐Wolf (2026). Polygenic Risk Modelling in Periodontitis: Insights From a Feasibility Study of 4243 European Cases and Current Limitations. Journal of Clinical Periodontology. https://doi.org/10.1111/jcpe.70195
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