Untargeted Metabolomics Analysis of Gingival Tissue in Patients with Severe Periodontitis.

The purpose of this study was to determine potential metabolic biomarkers and therapeutic drugs in the gingival tissue of individuals with periodontitis. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) were used to analyze the gingival tissue samples from 20 patients with severe periodontitis and 20 healthy controls. Differential metabolites were identified using variable important in projection (VIP) values from the orthogonal partial least squares discrimination analysis (OPLS-DA) model and then verified for significance between groups using a two-tailed Student's t test. In total, 65 metabolites were enriched in 33 metabolic pathways, with 40 showing a significant increase and 25 expressing a significant decrease. In addition, it was found that patients with severe periodontitis have abnormalities in metabolic pathways, such as glucose metabolism, purine metabolism, amino acid metabolism, and so on. Furthermore, based on a multidimensional analysis, 12 different metabolites may be the potential biomarkers of severe periodontitis. The experiment's raw data have been uploaded to the MetaboLights database, and the project number is MTBLS8357. Moreover, osteogenesis differentiation characteristics were detected in the selected metabolites. The findings may provide a basis for the study of diagnostic biomarkers and therapeutic metabolites in severe periodontitis.

Accuracy of dental implant placement with a robotic system in partially edentulous patients: A prospective, single-arm clinical trial.

OBJECTIVES: This clinical study aimed to assess the accuracy of implant positions using a robotic system in partially edentulous patients. MATERIALS AND METHODS: Twenty-eight partially edentulous patients received 31 implants using the robotic system. Deviations between the planned and placed implants were calculated after surgery. The deviations were compared with objective performance goals (OPGs) from reported studies of fully guided static computer-assisted implant surgery (CAIS) and dynamic CAIS. A multiple linear regression analysis was performed to investigate the possible effects of the type and side of the arch, implant location, and implant dimensions on the deviations. RESULTS: The evaluation of 31 implants resulted in a mean angle deviation of 2.81 ± 1.13° (95% confidence interval (CI): 2.40-3.23°), while the 3D deviations at the implant shoulder and apex were 0.53 ± 0.23 mm (95% CI 0.45-0.62 mm) and 0.53 ± 0.24 mm (95% CI 0.44-0.61 mm), respectively. The upper limits of the 95% CI of 3D deviations were lower than those of the corresponding OPGs; however, the angle deviation was similar to that of the OPG. No statistically significant differences were found for the type and side of the arch, implant location, and implant dimensions to the deviations (p > .05). CONCLUSIONS: The robotic system appears to achieve higher accuracy in implant positions than static and dynamic CAIS in partially edentulous patients (Chinese Clinical Trial Registry ChiCTR2300067587).

The association of aldehyde exposure with the risk of periodontitis: NHANES 2013-2014.

OBJECTIVES: Three distinct models were utilized to investigate the combined impacts of serum aldehyde exposure and periodontitis. MATERIALS AND METHODS: We performed a cross-sectional analysis using data from 525 participants in the 2013-2014 National Health and Nutrition Examination Survey (NHANES). The directed acyclic graphs (DAG) were used to select a minimal sufficient adjustment set of variables (MSAs). To investigate the relationship between aldehydes and periodontitis, we established three models including multiple logistic regression model, restricted cubic spline (RCS) model, and Bayesian kernel machine regression (BKMR) model. RESULTS: After taking all covariates into account, the multiple logistic regression model revealed that elevated concentrations of isopentanaldehyde and propanaldehyde were strongly associated with periodontitis (isopentanaldehyde: OR: 2.38, 95% CI: 1.34-4.23; propanaldehyde: OR: 1.51, 95% CI: 1.08-2.13). Furthermore, the third tertile concentration of isopentanaldehyde was associated with a 2.04-fold increase in the incidence of periodontitis (95% CI: 1.05-3.95) compared to the first tertile concentration, with a P for trend = 0.04. RCS models showed an "L"-shaped relationship between isopentanaldehyde and periodontitis (P for nonlinear association < 0.01), with inflection point of 0.43 ng/mL. BKMR identified a strong connection between mixed aldehydes and periodontitis, with isopentanaldehyde exhibiting the greatest posterior inclusion probability (PIP) with 0.901 and propanaldehyde exhibiting a PIP with 0.775. CONCLUSIONS: Isopentanaldehyde and propanaldehyde are positively associated with the risk of periodontitis. CLINICAL RELEVANCE: Periodontitis may be associated with exposure to mixed aldehyde. This study emphasizes the important role of aldehydes in primary prevention of periodontitis.

Macrophages induce gingival destruction via Piezo1-mediated MMPs-degrading collagens in periodontitis.

Macrophages are an integral part of the innate immune response in periodontal tissue and play a crucial role in the progression of periodontitis. Here we reported that macrophages also provoke periodontitis-induced gingival destruction through Piezol-mediated collagen degradation. We discovered that the PIEZO1 expression was markedly elevated in patients with periodontitis through transcriptomic profiling. Moreover, Piezo1 promoted macrophage polarization toward the M1 type in response to lipopolysaccharide (LPS) and induced production of proinflammatory cytokines, which in turn stimulated production of matrix metalloproteinases (MMPs) leading to collagen degradation. Our study suggests that Piezol might be a potential therapeutic target for treating periodontitis-induced gingival destruction.