Profiling of plasma-derived exosomal RNA expression in patients with periodontitis: A pilot study.

OBJECTIVE: This study aimed to profile differentially expressed (DE) exosomal RNAs in healthy subjects and periodontitis patients and compare their levels before and after treatment. MATERIALS AND METHODS: Plasma samples from healthy subjects and patients with periodontitis (pre-/post-periodontal treatment) were collected for this case-control study. After isolation of exosomes from the plasma, the RNA was extracted and small RNA sequencing was performed (3 healthy samples, 4 pre-treatment samples, and 5 post-treatment samples). Two-way analyses were conducted according to the treatment status in the periodontitis group, unpaired analysis (grouping as pre-/post-treatment) and paired analysis (matching pre- and post-treatment in the same subject). The DE exosomal RNAs were screened by sequencing and visualized using the R software. Gene Ontology analysis was performed, and target genes were identified. RESULTS: In both paired and unpaired analyses, two DE microRNAs (DEmiRs; miR-1304-3p and miR-200c-3p) and two DE small nucleolar RNAs (DEsnoRs; SNORD57 and SNODB1771) were common, and they were found to be downregulated during periodontitis and recovered to healthy levels after treatment. The top three target genes (NR3C1, GPR158, and CNN3) commonly regulated by DEmiRs were identified. CONCLUSIONS: Plasma-derived exosomal miRs (miR-1304-3p and miR-200c-3p) and snoRs (SNORD57 and SNODB1771) could be valuable biomarkers for periodontitis.

Single-cell RNA sequencing reveals rebalancing of immunological response in patients with periodontitis after non-surgical periodontal therapy.

BACKGROUND: Periodontitis is a major inflammatory disease of the oral mucosa that is not limited to the oral cavity but also has systemic consequences. Although the importance of chronic periodontitis has been emphasized, the systemic immune response induced by periodontitis and its therapeutic effects remain elusive. Here, we report the transcriptomes of peripheral blood mononuclear cells (PBMCs) from patients with periodontitis. METHODS: Using single-cell RNA sequencing, we profiled PBMCs from healthy controls and paired pre- and post-treatment patients with periodontitis. We extracted differentially expressed genes and biological pathways for each cell type and calculated activity scores reflecting cellular characteristics. Intercellular crosstalk was classified into therapy-responsive and -nonresponsive pathways. RESULTS: We analyzed pan-cellular differentially expressed genes caused by periodontitis and found that most cell types showed a significant increase in CRIP1, which was further supported by the increased levels of plasma CRIP1 observed in patients with periodontitis. In addition, activated cell type-specific ligand-receptor interactions, including the BTLA, IFN-γ, and RESISTIN pathways, were prominent in patients with periodontitis. Both the BTLA and IFN-γ pathways returned to similar levels in healthy controls after periodontal therapy, whereas the RESISTIN pathway was still activated even after therapy. CONCLUSION: These data collectively provide insights into the transcriptome changes and molecular interactions that are responsive to periodontal treatment. We identified periodontitis-specific systemic inflammatory indicators and suggest unresolved signals of non-surgical therapy as future therapeutic targets.

Association between coffee consumption and periodontal diseases: a systematic review and meta-analysis.

BACKGROUND: Several studies have demonstrated association between coffee consumption and periodontal diseases. However, no systematic review and meta-analysis was performed. Therefore, we performed a systematic review and meta-analysis to evaluate the association between coffee intake and periodontitis. METHODS: We defined PICO statement as "Do coffee drinkers have a higher association of periodontitis or tooth loss than non-coffee drinkers?". We searched for articles using the Embase and Medline databases. The odds ratio was used as an effect measure to evaluate the association between coffee and periodontitis We divided coffee intake doses into three groups: no intake (≤ 0.03 cups/day), low intake (0.03 < x < 1 cups/day), and high intake (≥ 1 cup/day). Cohort and cross-sectional studies were eligible for inclusion in this study. The Newcastle-Ottawa scale was used to qualitatively assess the risk of bias. The degree of heterogeneity between studies was quantified using I2 statistics. RESULTS: Six articles were analysed, including two cohort studies and four cross-sectional studies. The pooled unadjusted odds ratios of periodontitis were 1.14 (0.93-1.39), 1.05 (0.73-1.52), 1.03 (0.91-1.16) and 1.10 (0.84-1.45) in the 4 meta-analyses (coffee drinker vs. non-coffee drinker, high intake vs. low intake, low intake vs. no intake, high intake vs. no intake), respectively. CONCLUSION: This is the first meta-analysis to investigate the relationship between coffee consumption and periodontitis. There was no relationship between coffee consumption and periodontitis. Further studies are required to assess whether a relationship between coffee consumption and periodontitis exists or not. PROSPERO registration number: CRD42022301341.

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.

Immunological link between periodontitis and type 2 diabetes deciphered by single-cell RNA analysis.

BACKGROUND: Type 2 diabetes mellitus (DM) is a complex metabolic disorder that causes various complications, including periodontitis (PD). Although a bidirectional relationship has been reported between DM and PD, their immunological relationship remains poorly understood. Therefore, this study aimed to compare the immune response in patients with PD alone and in those with both PD and DM (PDDM) to expand our knowledge of the complicated connection between PD and DM. METHODS: Peripheral blood mononuclear cells were collected from 11 healthy controls, 10 patients with PD without DM, and six patients with PDDM, followed by analysis using single-cell RNA sequencing. The differences among groups were then compared based on intracellular and intercellular perspectives. RESULTS: Compared to the healthy state, classical monocytes exhibited the highest degree of transcriptional change, with elevated levels of pro-inflammatory cytokines in both PD and PDDM. DM diminished the effector function of CD8+ T and natural killer (NK) cells as well as completely modified the differentiation direction of these cells. Interestingly, a prominent pathway, RESISTIN, which is known to increase insulin resistance and susceptibility to diabetes, was found to be activated under both PD and PDDM conditions. In particular, CAP1+ classical monocytes from patients with PD and PDDM showed elevated nuclear factor kappa B-inducing kinase activity. CONCLUSIONS: Overall, this study elucidates how the presence of DM contributes to the deterioration of T/NK cell immunity and the immunological basis connecting PD to DM.

Association between Four Dietary Patterns and the Risk of Periodontal Diseases: A Systematic Review and Meta-Analysis.

BACKGROUND: Several dietary patterns are reported as risk factors for several chronic diseases including oral diseases. However, thus far, there has been no comprehensive quantitative analysis of nutrition and periodontal diseases. METHODS: This systematic review was conducted according to the PRISMA guidelines. Cohort, case-control, and cross-sectional studies were eligible for inclusion in this study. The Newcastle-Ottawa scale was used to qualitatively assess the risk of bias in the included studies. The number of samples was used for odds ratio calculation, followed by the unadjusted value and 95% confidence interval. RESULTS: Nine papers were included for the systematic review and meta-analysis. The results of screening for database search records showed that four diet patterns (western diet, dairy product intake, sugar intake, and vitamin C intake) have enough data for meta-analysis. The risk of periodontal disease in the western-diet group and the lowest dairy product intake group was 1.05 (0.51-2.13) and 1.28 (0.89-1.84), respectively. The risk of periodontal disease in the highest sugar intake group and the lowest vitamin C intake group was 1.52 (0.79-2.91) and 1.15 (1.08-1.23), respectively. CONCLUSIONS: With aging of the population globally, the prevalence of periodontal disease increases, and the associated cost also increases. Though this study, we found foods related to the risk of periodontal disease, and we are confident that it will contribute to lowering the incidence of the disease.

Obesity and periodontitis: A systematic review and updated meta-analysis.

Background: A previous 2014 meta-analysis reported a positive association between obesity and periodontitis. It was considered necessary to update the recently published papers and to analyse subgroups on important clinical variables that could affect the association between obesity and periodontitis. Therefore, we updated the latest studies and attempted to derive more refined results. Methods: All observational studies were eligible for inclusion. The Newcastle-Ottawa scale was used to qualitatively evaluate the risk of bias. Subgroup analyses were conducted for patients aged 18-34, 35-54, and 55+ years and the countries (European countries, USA, Brazil, Japan, Korea, and other Asian countries). Results: Thirty-seven full-text articles were included. Obesity conferred increased odds of periodontal disease with an odds ratio (1.35, 95% CI: 1.05-1.75). In the subgroup analysis by age, the odds ratio was the highest in the 18-34 years group (2.21, 95% CI: 1.26-3.89). In the subgroup analysis by country, European countries had the highest odds ratio (2.46, 95% CI: 1.11-5.46). Conclusion: Despite the differences in degree, a positive association between obesity and periodontitis was found regardless of country or age. Therefore, medical professionals should try to prevent periodontitis by controlling patient weights, and more studies should be conducted to determine the association between obesity and oral health. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022301343.

Differential microbiota network in gingival tissues between periodontitis and periodontitis with diabetes.

Periodontitis and diabetes mellitus (DM) have a bidirectional relationship. Periodontitis is initiated by dysbiosis of oral microorganisms, and in particular, the characteristics of the microorganisms that have penetrated the tissue are directly related to the disease; therefore, we investigated the effect of DM on intragingival microbial profiling of patients with periodontitis. A total of 39 subjects were recruited and divided into three groups in this case control study as follows: healthy (NA, 10), periodontitis only (PD, 18), and periodontitis with DM (PD_DM, 11). Gingival tissue was collected, DNA was extracted, and whole-genome sequencing was performed. PD and PD_DM showed different characteristics from NA in diversity and composition of the microbial community; however, no difference was found between the PD nad PD_DM. PD_DM showed discriminatory characteristics for PD in the network analysis. PD showed a network structure in which six species were connected, including three red complex species, and PD_DM's network was more closely connected and expanded, with six additional species added to the PD network. Although DM did not significantly affect α- and ß-diversity or abundance of phyla and genera of microbiota that invaded the gingival tissue of patients with periodontitis, DM will affect the progression of periodontitis by strengthening the bacterial network in the gingival tissue.

Identification of Shared Genes and Pathways in Periodontitis and Type 2 Diabetes by Bioinformatics Analysis.

Introduction: It is well known that the presence of diabetes significantly affects the progression of periodontitis and that periodontitis has negative effects on diabetes and diabetes-related complications. Although this two-way relationship between type 2 diabetes and periodontitis could be understood through experimental and clinical studies, information on common genetic factors would be more useful for the understanding of both diseases and the development of treatment strategies. Materials and Methods: Gene expression data for periodontitis and type 2 diabetes were obtained from the Gene Expression Omnibus database. After preprocessing of data to reduce heterogeneity, differentially expressed genes (DEGs) between disease and normal tissue were identified using a linear regression model package. Gene ontology and Kyoto encyclopedia of genes and genome pathway enrichment analyses were conducted using R package 'vsn'. A protein-protein interaction network was constructed using the search tool for the retrieval of the interacting genes database. We used molecular complex detection for optimal module selection. CytoHubba was used to identify the highest linkage hub gene in the network. Results: We identified 152 commonly DEGs, including 125 upregulated and 27 downregulated genes. Through common DEGs, we constructed a protein-protein interaction and identified highly connected hub genes. The hub genes were up-regulated in both diseases and were most significantly enriched in the Fc gamma R-mediated phagocytosis pathway. Discussion: We have identified three up-regulated genes involved in Fc gamma receptor-mediated phagocytosis, and these genes could be potential therapeutic targets in patients with periodontitis and type 2 diabetes.