IL-23与种植体周黏膜炎

Background/Objectives: Cytokines related to the Th17 response have been associated with peri-implant diseases; however, the effect of peri-implant therapy on their modulation remains underexplored. To evaluate the effect of peri-implant therapy on the expression of cytokines related to the Th17 response in the peri-implant crevicular fluid (PICF) (GM-CSF, IFN-γ, IL-1β, IL-4, IL-6, IL-10, IL-12 (p70), IL-17A, IL-21, IL-23, and TNF-α) of partially edentulous patients with peri-implant disease (PID). Methods: Thirty-seven systemically healthy individuals presenting with peri-implant mucositis (PIM) (n = 20) or peri-implantitis (PI) (n = 17) were treated and evaluated at baseline (T0) and three months after therapy (T1). Clinical parameters (probing depth (PD), clinical attachment level (CAL), plaque index, and bleeding on probing index (BoP), were evaluated. The PIM group underwent non-surgical therapy, while the PI group received a surgical approach. PICF was collected with absorbent paper strips and analyzed with a multiplex assay. Results: Eighty-eight implants were treated in 37 patients (56 in the PIM group and 32 in the PI group). After therapy, significant reductions in PD, CAL, plaque index, and BoP were observed in the PIM group (p < 0.05). In the PI group, significant reductions in PD, CAL, and BoP were noted (p < 0.05). The PIM group showed a significant reduction of IL-17A and TNF-α after therapy, while the PI group showed a significant reduction of IL-1β, IL-6, and TNF-α (p < 0.05). Conclusions: The peri-implant therapy for patients with PID reduced the expression of cytokines related to the Th17 response in PICF.

Objective: To assess various inflammatory biomarkers CCL-20, BAF, RANK-L, IL-23, and osteoprotegerin from PICF along with clinical parameters in participants with peri-implant mucositis and peri-implantitis. Material and Methods: Participants were gathered i.e., 30 with periimplantitis, 32 with peri-implant mucositis, and 32 healthy. Peri-implant parameters PIPD, BoP, and PIPI were measured in all participants. PICF samples were collected to assess the level of biomarkers CCL-20; BAF; IL-23; RANK-L, and OPG. For periodontal parameters, ranges and means were measured. Kruskal Wallis test was used for comparison between groups. For categorical data sets, the Pearson Chi-Square test was applied. The Bonferroni test was used for multiple comparisons. Results: Peri-implant parameter BoP in peri-implant mucositis and peri-implantitis was significantly higher compared to controls (p < 0.05). PIPD with healthy peri-implant conditions was, significantly less compared to peri-implantitis, and peri-implant mucositis (p<0.05). PIPI demonstrated no significant difference throughout different peri-implant conditions. CCL-20 ng/mL in patients with peri-implant mucositis was found to be significantly higher (p < 0.05). BAF levels in peri-implantitis and peri-implant mucositis were comparable. The concentration of IL-23 ng/mL was found to be significantly lower in healthy controls (p < 0.05). Conclusion: Inflammatory biomarkers showed high levels of PICF in peri-implant disease patients compared to healthy controls. Individuals with peri-implant conditions experience the poor peri-implant probing depth and bleeding on probing.

Background: The aim of this feasibility study was to investigate the concentration level of CCL-20/MIP-3α, BAFF/BLyS, IL-23, RANKL, and Osteoprotegerin in the Peri-Implant Crevicular Fluid (PICF), from patients diagnosed with peri-implant mucositis and peri-implantitis, and to compare them with PICF from patients with healthy implants. Methods: Participants with at least one dental implant with healthy peri-implant tissues, peri-implant mucositis, or peri-implantitis were included. PICF was collected using paper strips from healthy and diseased peri-implant sites (n = 19). Biomarker levels were analyzed using a custom Multiplex ELISA Assay Kit. Results: In comparison to peri-implant health, the peri-implant mucositis group showed an increased concentration of CCL-20 MIP-3α, BAFF/BLyS, IL-23, RANKL, and Osteoprotegerin. The peri-implantitis group had the lowest median concentration of Osteoprotegerin (1963 ng/mL); this group had a similar concentration of RANKL (640.84 ng/mL) when compared to the peri-implant health group. BAFF/BLyS (17.06 ng/mL) showed the highest concentration in the peri-implantitis group. Conclusions: This feasibility study suggests that IL-23 and RANKL may help to elucidate the pathogenesis during the conversion from peri-implant health to peri-implantitis. Further research is required in BAFF/BLyS for the early diagnosis of peri-implantitis.

To study the biomarker profile in peri-implant crevicular fluid (PICF) of A proliferation-inducing ligand (APRIL), receptor activator of nuclear factor κβ (RANKL) and interleukin (IL)-23, in healthy, periimplant mucositis and peri-implantitis sites, and to explore their diagnostic accuracy on periimplantitis (PI) diagnosis. An exploratory cross-sectional study was conducted. Sociodemographic and clinical were recorded. Implant diagnosis was made based on the latest classification consensus. PICF samples were collected with paper strips from healthy, mucositis and PI implants. The biomarkers were analyzed by Luminex assay. The diagnostic accuracy was determined through sensitivity, specificity, predictive values (PV), and receiver operating characteristic (ROC) curves. Overall, 54 patients were recruited; 17 were healthy implants, 19 with mucositis and 18 have PI. RANKL and APRIL levels in PICF were significantly increased in PI implants compared to healthy implants (p < 0.001 and p = 0.005). IL-23 did not present differences between groups (p > 0.05). Positive correlations between PICF-RANKL levels and clinical attachment loss, plaque index score and bleeding on probing were observed (rho = 0.33; rho = 0.35; rho = 0.33; p < 0.05, respectively). Additionally, PICF-IL-23 and APRIL were correlated with the plaque index score and peri-implant probing depth (rho = 0.28; rho = 0.28, p < 0.05). PICF-APRIL concentrations and plaque index score were associated with PI (OR:3.01; 95%CI [1.08–8.38], p = 0.035, and OR:11.24; 95% CI [2.63–48.16], p = 0.001, respectively). The regression model, which included PICF-APRIL and plaque index, showed an AUC-ROC of 0.95, a sensitivity of 94.4%, 83.3% specificity, a positive PV of 73.9%, and a negative PV of 96.8%. Implants with PI have higher levels of APRIL and RANKL in PICF compared to healthy implants. The model that includes the levels of APRIL in PICF combined with the plaque index score leads to an enhanced accuracy of PI diagnosis. Clinical relevance: Clinical diagnosis of peri-implant disease can be improved with molecular tools, in this case, APRIL demonstrated high accuracy for the diagnosis of PI.

OBJECTIVES Notch signaling pathway, known to influence bone resorption in several oral diseases, has not been analyzed in peri-implantitis yet. Therefore, the aims of the present study were to determine the levels of Notch cascade, bone remodeling mediators and pro-inflammatory cytokines, in conjunction with clinical parameters, in subjects with peri-implant mucositis and peri-implantitis. MATERIAL AND METHODS Clinical parameters: peri-implant probing depth (PPD), bleeding on probing (BOP), suppuration on probing (SUP) and plaque index (PI) were recorded. Samples were collected from 130 participants, divided into peri-implantitis (PI), peri-implant mucositis (PM) and healthy implants (HI) group. Relative expression levels (REL) of Notch 1, Notch 2, Jagged 1, Hes 1, Hey 1, TNF-α, IL-17, IL-1β, IL-6, RANKL and OPG mRNA were determined by reverse transcriptase-real-time polymerase chain reaction (RT-qPCR). Quantitation of Notch 1, Il-17 and IL-6 proteins was performed using ELISA assays. RESULTS All clinical parameters were significantly higher in PI compared to HI. Significant decrease of Notch 1, and higher REL of Hey 1, IL-1β, IL-6 and RANKL were found in PI compared to HI. PM showed significant increase of IL-1β REL in comparison to HI. In PI vs PM, significantly higher REL was found for Hey 1, TNF-α, IL-17, IL-1β, IL-6 and RANKL. Additionally, higher protein concentrations of IL-6 and IL-17 were detected in PI vs. PM and vs. HI group. CONCLUSION The combined effect of Notch 1 down-regulation and elevated expression of some key inflammation modulators might result in osteoclast activity increase and subsequent osteolysis in peri-implantitis.

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OBJECTIVE Peri-implantitis, caused by an inflammatory response to pathogens, is the leading cause of dental implant failure. Poor soft tissue healing surrounding implants - caused by inadequate surface properties - leads to infection, inflammation, and dysregulated keratinocyte and macrophage function. One activated inflammatory response, active around peri-implantitis compared to healthy sites, is the IL-23/IL-17A cytokine axis. Implant surfaces can be synthesized with peptide nanocoatings to present immunomodulatory motifs to target peri-implant keratinocytes to control macrophage polarization and regulate inflammatory axises toward enhancing soft tissue healing. METHODS We synthesized an IL-23 receptor (IL-23R) noncompetitive antagonist peptide nanocoating using silanization and evaluated keratinocyte secretome changes and macrophage polarization (M1-like "pro-inflammatory" vs. M2-like "pro-regenerative"). RESULTS IL-23R antagonist peptide nanocoatings were successfully synthesized on titanium, to model dental implant surfaces, and compared to nonfunctional nanocoatings and non-coated titanium. IL-23R antagonist nanocoatings significantly decreased keratinocyte IL-23, and downstream IL-17A, expression compared to controls. This peptide noncompetitive antagonistic function was demonstrated under lipopolysaccharide stimulation. Large scale changes in keratinocyte secretome content, toward a pro-regenerative milieu, were observed from keratinocytes cultured on the IL-23R antagonist nanocoatings compared to controls. Conditioned medium collected from keratinocytes cultured on the IL-23R antagonist nanocoatings polarized macrophages toward a M2-like phenotype, based on increased CD163 and CD206 expression and reduced iNOS expression, compared to controls. SIGNIFICANCE Our results support development of IL-23R noncompetitive antagonist nanocoatings to reduce the pro-inflammatory IL-23/17A pathway and augment macrophage polarization toward a pro-regenerative phenotype. Immunomodulatory implant surface engineering may promote soft tissue healing and thereby reduce rates of peri-implantitis.

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OBJECTIVE To describe and compare cytokines levels in clinically healthy sites of dental implants and natural teeth. MATERIALS AND METHODS A total of 90 dental implants in 71 periodontal healthy patients with function time of less than 6 months after the completion of the implant prosthesis were included in this study. PICF (peri-implant crevicular fluid) and GCF (gingival crevicular fluid) samples were collected from implants and the contralateral natural teeth. In addition, we performed a dynamic collection of crevicular fluid from 18 dental implants and their contralateral natural teeth at four time nodes (first day, first week, first month, third month). The profiles of 45 common cytokines in PICF and GCF were analyzed by Luminex multiplex assays. RESULTS The total volume of PICF was significantly higher when compared to the volume of GCF (p < 0.01). In contrast, the concentrations of IL-18, IL-2, IL-23, IL-21, IL-1α, IL-12p70, VEGF-A, HGF, FGF-2, BDNF, PlGF-1, MIP-1β, TNF-α, and IFN-γ in PICF were significantly lower than those in GCF (p < 0.05). In the longitudinal component of the study, the cytokines found in PICF underwent a brief wave of expression in the 3-month period, with the smallest gap difference of cytokine expression between the PICF and the GCF being at first month. CONCLUSIONS This study observed that the levels of 14 cytokine profiles were lower in PICF than in GCF. Within the implants load for one month, the levels of above differential cytokines in PICF increased and gradually approached the cytokine profiles in GCF.

Abstract Peri-implantitis (PI) and periodontitis (PD) are common oral inflammatory diseases, which seem to exhibit critical differences in some of their molecular features. Thus, we assessed the immune cell composition of PI and PD lesions and the corresponding inflammatory profile in soft tissues and crevicular fluid. PI, PD, and control patients were recruited (n = 62), and soft tissue biopsies were collected during surgery. Crevicular fluid around implant or tooth was collected. The proportions of major immune cell populations in tissues were analyzed by flow cytometry, and the inflammatory profile in tissue and crevicular fluid by a multiplex immunoassay. No significant difference was seen between PI and PD lesions in the proportions of immune cells. PI tissues showed an increased frequency of B cells in comparison with control tissues, along with higher levels of IL-1β, TNF-α, IL-4, and BAFF in tissue and crevicular fluid. Moreover, TNF-α, IL-17A, and BAFF were higher in PI tissues, but not in PD, than in control tissues. The immune cell composition did not differ significantly between PI and PD, but an enhanced inflammatory profile was seen in PI tissue. PI lesions were enriched in B cells, and displayed increased levels of IL-1β, TNF-α, IL-4, and BAFF in both tissue and crevicular fluid.

Objectives The aim of this study was to assess the microcirculation and the expression patterns of wound-healing-related cytokines around narrow-diameter implants in type 2 diabetes mellitus (T2DM) and normo-glycemic patients. Materials and methods A total of 31 patients, 16 of which diagnosed with T2DM (HbA1c > 6.5) and 15 normo-glycemic patients, received narrow diameter implants in the posterior mandible or maxilla. During the 3-month healing period, soft-tissue perfusion was monitored via laser Doppler flowmetry. Peri-implant fluid (PICF) was harvested and analyzed for concentrations of interleukin-1ß (IL-1ß), interleukin-23 (IL-23), interleukin-17 (IL-17), and granulocyte colony-stimulating factor (G-CSF) by a multiplex, bead-based immunoassay. Results Microcirculatory perfusion patterns during wound healing exhibited no significant differences throughout the observation period. IL-1ß concentrations were expectedly elevated during the early phases of wound healing. At the first visit after surgery, IL-23 concentrations were significantly higher in implants of diabetic patients. This difference was diminished over the course of the observation period. For the other tested analytes, no differences were observable between both groups. Conclusion Wound healing after implant surgery was similar in T2DM and healthy patients. Hydrophilic-surface titanium-zirconium implants with reduced diameter may be considered for implant therapy of diabetes mellitus type II patients. Registration number NCT04630691 (clinicaltrials.gov).

Dental implants are a common treatment option offered to patients for tooth replacement. However, little is known regarding initial colonization of the subgingival microbiome and simultaneous longitudinal cytokine production in humans during the early healing phase following implant placement. We report findings from an in vivo study that assessed initial colonization of the subgingival microbiome and concomitant early cytokine production in a newly formed anatomical space, namely, an implant sulcus. This approach may be useful in future interventional studies to influence dental implant success. Our data showed that the subgingival microbiome and cytokine profile were similar for control natural teeth and dental implants at both 4 and 12 weeks after implant placement. These data suggest that these profiles are driven by the patient and not by anatomical location (i.e., tooth versus dental implant). ABSTRACT Little is known about longitudinal development of the peri-implant subgingival microbiome and cytokine production as a new sulcus forms after dental implant placement. Therefore, the purpose of this observational study was to evaluate simultaneous longitudinal changes in the oral microbiome and cytokine production in the developing peri-implant sulcus compared to control natural teeth. Four and 12 weeks after implant placement and abutment connection, a dental implant and a natural tooth were sampled in 25 patients for subgingival plaque and gingival crevicular fluid (GCF [around teeth] and peri-implant crevicular fluid [PICF] around implants). DNA from plaque samples was extracted and sequenced using Illumina-based 16S rRNA sequencing. GCF and PICF samples were analyzed using a customized Milliplex human cytokine and chemokine magnetic bead panel. Beta diversity analysis revealed that natural teeth and implants had similar subgingival microbiomes, while teeth had greater alpha diversity than implants. At the genus level, however, few differences were noted between teeth and dental implants over 12 weeks. Specifically, Actinomyces and Selenomonas were significantly elevated around teeth versus dental implants at both 4 weeks and 12 weeks, while Corynebacterium and Campylobacter were significantly elevated only at 4 weeks around teeth. The only difference between PICF and GCF biomarkers was significantly elevated granulocyte-macrophage colony-stimulating factor levels around teeth versus dental implants at the 4-week visit. The subgingival microbiome and cytokine production were similar between teeth and implants during early healing, suggesting that these profiles are driven by the patient following dental implant placement and are not determined by anatomical niche. IMPORTANCE Dental implants are a common treatment option offered to patients for tooth replacement. However, little is known regarding initial colonization of the subgingival microbiome and simultaneous longitudinal cytokine production in humans during the early healing phase following implant placement. We report findings from an in vivo study that assessed initial colonization of the subgingival microbiome and concomitant early cytokine production in a newly formed anatomical space, namely, an implant sulcus. This approach may be useful in future interventional studies to influence dental implant success. Our data showed that the subgingival microbiome and cytokine profile were similar for control natural teeth and dental implants at both 4 and 12 weeks after implant placement. These data suggest that these profiles are driven by the patient and not by anatomical location (i.e., tooth versus dental implant).

Abstract Objective To study the effect of implanting the percutaneous bone‐anchored hearing system (BAHS) itself and inflammation of the peri‐abutment skin warrant clarification. In this study, we aimed to acquire further insight into the immune responses related to BAHS surgery and peri‐implant skin inflammation. Materials and Methods During surgery and 12 weeks post‐implantation, skin biopsies were obtained. If applicable, additional biopsies were taken during cases of inflammation. The mRNA expression of IL‐1β, IL‐6, IL‐8, TNFα, IL‐17, IL‐10, TGF‐ß, MIP‐1α, MMP‐9, TIMP‐1, COL1α1, VEGF‐A, FGF‐2 TLR‐2, and TLR‐4 was quantified using qRT‐PCR. Results Thirty‐five patients agreed to the surgery and 12‐week biopsy. Twenty‐two patients had mRNA of sufficient quality for analysis. Ten were fitted with a BAHS using the minimally invasive Ponto surgery technique. Twelve were fitted with a BAHS using the linear incision technique with soft‐tissue preservation. Five biopsies were obtained during episodes of inflammation. The post‐implantation mRNA expression of IL‐1β (P = .002), IL‐8 (P = .003), MMP9 (P = .005), TIMP‐1 (P = .002), and COL1α1 (P < .001) was significantly up‐regulated. IL‐6 (P = .009) and FGF‐2 (P = .004) mRNA expression was significantly down‐regulated after implantation. Within patients, no difference between post‐implantation mRNA expression (at 12 weeks) and when inflammation was observed. Between patients, the expression of IL‐1β (P = .015) and IL‐17 (P = .02) was higher during cases of inflammation compared with patients who had no inflammation at 12‐week follow‐up. Conclusions As part of a randomized, prospective, clinical trial, the present study reports the molecular profile of selected cytokines in the soft tissue around BAHS. Within the limit of this study, the results showed that 12 weeks after BAHS implantation the gene expression of some inflammatory cytokines (IL‐8 and IL‐1β) is still relatively high compared with the baseline, steady‐state, expression. The up‐regulation of anabolic (COL1α1) and tissue‐remodeling (MMP‐9 and TIMP1) genes indicates an ongoing remodeling process after 12 weeks of implantation. The results suggest that IL‐1β, IL‐17, and TNF‐α may be interesting markers associated with inflammation.

PURPOSE To compare pro-inflammatory cytokine levels in the peri-implant crevicular fluid (PICF) in unused and reused healing abutments. MATERIALS AND METHOD This study was a controlled randomized, double-blind clinical trial. Seventy-two patients who met the inclusion criteria were divided into two groups. After one-stage implant placement, in group A, an unused healing abutment, and in group B, a reused healing abutment, was connected to the implant fixture. After 2 months, clinical measurements for keratinized gingiva (KG), plaque index (PI), and bleeding index (BI) (Ainamo and Bay) were taken, and PICF sampling was performed to evaluate pro-inflammatory IL-1β and TNF-α cytokine levels using the ELISA test. Comparison of clinical measurements and cytokine levels between the two study groups was made using the Mann-Whitney test. RESULT Clinical measurements and sampling were performed on 60 patients (nA = 27, nB = 33). There was no significant difference between the two groups in clinical measurements (BI (p-value=0.96) and PI (p-value=0.06)) or TNF-α (p-value=0.63) and IL-1β (p-value=0.26) cytokine levels. CONCLUSION Reused healing abutments that are cleaned and sterilized properly do not appear to induce further peri-implant pro-inflammatory response; therefore, they can be utilized temporarily until implant abutment insertion. This article is protected by copyright. All rights reserved.

BACKGROUND Tobacco smoking compromises the prognosis of dental implant treatment and is associated with increased risk of peri-implant bone loss and increased implant failure rate. There is a dearth of studies that have compared clinical, radiographic, and immunological peri-implant parameters among cigarette smokers (CS), individuals vaping e-cigarettes (e-cigs), and non-smokers (NS). This study aimed to compare clinical and radiographic peri-implant parameters and levels of matrix metalloproteinase (MMP)-9 and interleukin (IL)-1β levels among CS, individuals' vaping e-cigs, and NS. METHODS Thirty-two CS (group 1), 31 individuals vaping e-cigs (group 2), and 32 NS (group 3) were included. Demographic- and implant-related data were collected using a structured baseline questionnaire. Peri-implant plaque index (PI), bleeding on probing (BOP), and probing depth (PD) were recorded and marginal bone loss (MBL) were assessed using standardized digital radiographs. Enzyme-linked immunosorbent assay was used to assess levels of MMP-9 and IL-1β in peri-implant sulcular fluid. Pearson correlation coefficient was used to analyze for correlations of MMP-9 and IL-1β levels with peri-implant parameters. RESULTS BOP showed significantly higher values in group 3 as compared with groups 1 and 2 (P < 0.01). PI (P < 0.01), PD ≥ 4 mm (P < 0.01), and mean concentrations of MMP-9 (P < 0.001) and IL-1β (P < 0.01) were significantly higher in groups 1 and 2 than group 3. MBL was significantly higher in group 1 as compared with group 2 and group 3 (P < 0.01). Significant positive correlations were found between MMP-9 (P = 0.0198) and IL-1β (P = 0.0047) levels and MBL in group 1; and a significant positive correlation between IL-1β and MBL in group 2 (P = 0.0031). CONCLUSIONS Peri-implant health was compromised among CS than vaping individuals and NS. Increased levels of proinflammatory cytokines in CS and vaping individuals may suggest greater peri-implant inflammatory response.

There is a complex interaction between titanium dental implants, bone, and the immune system. Among them, specific immune cells, macrophages play a crucial role in the osseointegration dynamics. Infiltrating macrophages and resident macrophages (osteomacs) contribute to achieving an early pro-regenerative peri-implant environment. Also, multinucleated giant cells (MNGCs) in the bone-implant interface and their polarization ability, maintain a peri-implant immunological balance to preserve osseointegration integrity. However, dental implants can display cumulative levels of antigens (ions, nano and microparticles and bacterial antigens) at the implant–tissue interface activating an immune-inflammatory response. If the inflammation is not resolved or reactivated due to the stress signals and the immunogenicity of elements present, this could lead implants to aseptic loosening, infections, and subsequent bone loss. Therefore, to maintain osseointegration and prevent bone loss of implants, a better understanding of the osteoimmunology of the peri-implant environment would lead to the development of new therapeutic approaches. In this line, depicting osteoimmunological mechanisms, we discuss immunomodulatory strategies to improve and preserve a long-term functional integration between dental implants and the human body. Scientific field of dental science: implant dentistry.

Mucosal surfaces are typical sites of initial entry into the human body for infectious pathogens. At these barriers, mucosal epithelial cells respond to pathogens and prime the immune system to mount a strong defense against agent spread; dysregulation of these responses can lead to overactivation manifesting in inflammatory diseases like periodontitis and peri-implantitis. The lack of an in-depth understanding of how these epithelial cells influence the regulation of associated microbiome and innate and adaptive immunity at mucosal barriers is a major challenge in the design of targeted oral therapies and mucosal vaccines for oral inflammatory diseases. Here, leveraging parallel single-nucleus transcriptomics and 16S microbial sequencing, we investigate the role of specialized mucosal epithelial populations, like junctional epithelial cells, in recruiting immune cells & regulating specific pathogenic microbial species that inform oral health. Our data highlight how changes in these populations regulate inflammation around natural teeth and artificial implants. Overall, our study yields insights into the specific epithelial cytokine-mediated immune crosstalk associated with oral mucosal barrier health and immunity that can be leveraged to develop improved preventions and cures for a wide variety of oral cavity diseases. Mucosal and Regional Immunology (MUC)