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Genetic Polymorphisms and Predisposition to Peri-Implantitis: A Systematic Review
Filomena Salazar1, María Belén Alvarez1, Marta Relvas1
1UNIPRO, Oral Pathology and Rehabilitation Research Unit, University Institute of Health Sciences (IUCS-CESPU), 4585-116 Gandra, Portugal.
None:
Peri-implantitis is a multifactorial inflammatory disease that can compromise the longevity of dental implants. Several studies have investigated the association between genetic variants. This systematic review aimed to assess the contribution of genetic polymorphisms to the risk of developing peri-implantitis. A systematic search was conducted in the PubMed database up to 2025 following the PICO strategy and PRISMA guidelines. Eligible studies met the following inclusion criteria: articles written in English, addressing genetic associations with peri-implantitis in human subjects, designed as clinical trials or observational (prospective or retrospective) studies, with full-text availability, and published within the last ten years. Exclusion criteria included studies in languages other than English, those not addressing the main research question, publications older than ten years, studies without full text, and secondary research such as meta-analyses or review articles. Selection and data extraction were performed independently by two reviewers. Risk of bias was evaluated qualitatively for control studies. Twenty-three studies met the inclusion criteria. Polymorphisms in genes related to inflammatory cytokines (e.g., IL-1β +3954 C/T, IL-10, TNF-α), bone metabolism (OPG, BMP4, FGF10), and immune regulation (CD14 rs2569190, miR-27a-3p) were frequently reported. IL-1β +3954 C/T, ET-1 and IL-1β, MMP-8 rs11225395 (T allele), MMP8 (-799 C/T), and CD14 rs2569190 showed consistent associations with increased peri-implantitis risk, while the results for TNF-α -308 G/A were inconsistent across populations. These findings suggest a potential role of genetic predisposition in peri-implantitis development. Identifying genetic biomarkers may help predict susceptibility and personalize management strategies.
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