Paired Transcriptional Analysis of Periodontitis and Peri-Implantitis within same host: a Pilot study.

BACKGROUND: Peri-implantitis, a plaque-associated pathological condition, has been on the rise with the increasing prevalence of dental implants. Despite its similarities to periodontitis, peri-implantitis is difficult to control completely and has high relapse rates. This has sparked interest in exploring the pathogenic differences between the two conditions. METHODS: This cross-sectional study involved 10 participants to concurrently examine periodontitis and peri-implantitis within the same patients, thereby minimizing inter-individual variation. Gingival tissue samples were collected from each participant, comprising 10 periodontitis and 10 peri-implantitis tissues, and RNAs were extracted. Using RNA sequencing and bioinformatics analysis, we investigated complex gene interactions, immune responses, and the role of the extracellular matrix in both conditions. We identified hub genes in each enhanced Protein-Protein Interaction network, providing crucial insights into these diseases' pathogenesis. RESULTS: Our findings highlighted the potential involvement of activated fibroblasts in the pathogenesis of peri-implantitis, identifying three marker genes (ACTA2, FAP, and PDGFRß) overexpressed in peri-implantitis, thus highlighting their potential as disease-specific biomarkers. CONCLUSIONS: Our study uncovered a novel connection between peri-implantitis and activated fibroblasts, examining specific markers and microbial differences between periodontitis and peri-implantitis. These insights improve our understanding of peri-implantitis pathogenesis, encouraging future research for better management and prevention strategies. CLINICAL SIGNIFICANCE: This study identifies key insights into the pathogenesis of peri-implantitis compared to periodontitis. These findings promise to advance clinical approaches for better managing and preventing peri-implantitis, addressing its complexities and high relapse rates effectively.

Comparative transcriptome analysis of periodontitis and peri-implantitis in human subjects.

BACKGROUND: Peri-implantitis is similar to periodontitis, but there are some differences. For the effective control of peri-implantitis, it is necessary to clarify its similarities and differences with periodontitis in terms of gene expression. METHODS: This cross-sectional study included 20 participants (10 healthy subjects and 10 patients with periodontitis and peri-implantitis). Gingival tissue samples (10 healthy, 10 periodontitis, and 10 peri-implantitis tissues) were collected, RNAs were extracted, and RNA sequencing and analysis were performed. RESULTS: Differentially expressed gene (DEG) analysis identified 757 upregulated and 159 downregulated genes common between periodontitis and peri-implantitis. Periodontitis tissues uniquely showed 186 overexpressed and 22 suppressed genes compared with peri-implantitis and healthy tissues, while peri-implantitis had 1974 and 642, respectively. Each common and unique differential gene set showed distinct enriched biological features between periodontitis and peri-implantitis after the pathway enrichment analysis. The expression pattern of selected DEGs focused on the representability of the disease was validated by RT-qPCR. CONCLUSIONS: Although periodontitis and peri-implantitis showed common gene expression that was clearly differentiated from healthy conditions, there were also unique gene patterns that were differentially expressed only in peri-implantitis. These findings will help elucidate the mechanisms involved in the progression of peri-implantitis.

Shear stress induces monocyte/macrophage-mediated inflammation by upregulating cell-surface expression of heat shock proteins.

The loss of endothelial cells is associated with the accumulation of monocytes/macrophages underneath the surface of the arteries, where cells are prone to mechanical stimulation, such as shear stress. However, the impact of mechanical stimuli on monocytic cells remains unclear. To assess whether mechanical stress affects monocytic cell function, we examined the expression of inflammatory molecules and surface proteins, whose levels changed following shear stress in human THP-1 cells. Shear stress increased the inflammatory chemokine CCL2, which enhanced the migration of monocytic cells and tumor necrosis factor (TNF)-α and interleukin (IL)- 1ß at transcriptional and protein levels. We identified that the surface levels of heat shock protein 70 (HSP70), HSP90, and HSP105 increased using mass spectrometry-based proteomics, which was confirmed by western blot analysis, flow cytometry, and immunofluorescence. Treatment with HSP70/HSP105 and HSP90 inhibitors suppressed the expression and secretion of CCL2 and monocytic cell migration, suggesting an association between HSPs and inflammatory responses. We also demonstrated the coexistence and colocalization of increased HSP90 immunoreactivity and CD68 positive cells in atherosclerotic plaques of ApoE deficient mice fed a high-fat diet and human femoral artery endarterectomy specimens. These results suggest that monocytes/macrophages affected by shear stress polarize to a pro-inflammatory phenotype and increase surface protein levels involved in inflammatory responses. The regulation of the abovementioned HSPs upregulated on the monocytes/macrophages surface may serve as a novel therapeutic target for inflammation due to shear stress.

Clinical Characteristics and Metabolic Health Status of Obese Korean Children and Adolescents.

BACKGROUND: This study aimed to determine the prevalence of metabolically healthy and unhealthy obesity (MHO and MUO, respectively) and examine the demographic, anthropometric, and lifestyle predictors of metabolic health status in Korean children and adolescents. METHODS: This study was based on data collected from the Korean Children-Adolescent Study in 2010. A total of 1,700 children (846 boys and 854 girls) were included in the primary cohort and classified into metabolically healthy and unhealthy groups according to factors related to the metabolic syndrome. Demographic and biochemical features were evaluated in study participants. Logistic regression estimated the odds ratios of having more fat mass among MUO compared with MHO children after adjusting for confounding factors. RESULTS: Mean body mass index was higher in the MUO group than in the MHO group (24.83 vs. 23.02 kg/m(2), respectively). The proportion of obese participants was also higher in the MUO group (59.4%) than in the MHO group (20.7%). MHO children were more likely to have parents with better socioeconomic status and a higher fruit and vegetable intake compared with MUO children. Higher fat mass and percent fat was associated with MUO according to multiple logistic regression analysis. CONCLUSION: Fat mass and percent fat are associated with metabolically healthy phenotypes of obesity among children and adolescents.