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Genetic modeling study finds poor discriminative accuracy of polygenic scores for severe periodontitis across European cohorts, indicating current GWAS data lack sufficient predictive power.
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: = 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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Richter et al. (2026) studied this question.
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