Background: The present study focused on the inflammatory disease progress after periodontal defect induction and aimed to specifically determine periodontal tissue responses following dental plaque accumulation by ligatures on a site with/without standardized periodontal defect induction. Methods: After 1 month from extraction of the adjacent teeth, semi-circumferential defects were surgically created in the unilateral second and fourth premolars (test group), whereas no defects were being induced at the contralateral sites (control group). One week later, silk was used to ligate the tooth cervix at both sites to encourage the accumulation of dental plaque. Four weeks later, the tissue samples were collected for histological/histomorphometric and microarray analysis. Microbiological analysis was performed before defect induction and at ligatures, and after 4 weeks of dental plaque accumulation. Results: Remarkable inflammation was clinically and histologically observed in both groups after plaque accumulation, and the intrabony type of periodontal defect exaggerated inflammatory cell infiltration into the connective tissue layer. Expression of genes related to inflammation such as IL-1 was highly up-regulated in test sites. However, these inflammatory infiltrations did not invade to a boundary of periodontal ligament and connective tissue attachment in both groups, and histomorphometric results corresponds to these observational results. Bacterial findings also showed no significant differences in detected microbiome compositions between control and test groups at three-time points. Conclusion: Intrabony defect might exaggerate the plaque-induced inflammation in the aspect of inflammatory cell infiltration and the related gene expression, but both dental plaque and the pre-existing periodontal defect negligibly disrupt periodontal attachment and the underlying alveolar bone.
Bibliographical noteFunding Information:
This study was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (grant no. NRF‐2019R1A2C4069942).
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