Salivary Osteocalcin as Potential Diagnostic Marker of Periodontal Bone Destruction among Smokers

Host Markers of Periodontal Diseases: Meta-Analysis of Diagnostic Accuracy Studies

OBJECTIVE

To identify host markers with optimal diagnostic performance for clinical implementation in the diagnosis of periodontal diseases and prediction of future disease progression and/or disease resolution.

MATERIAL AND METHODS

Cross-sectional and prospective studies with ≥ 20 participants per group, reporting diagnostic accuracy (e.g., area under the curve [AUC]) of host markers for periodontal diagnosis (focused question 1 [FQ1]), periodontitis progression/relapse (FQ2) or resolution (FQ3) were searched in three electronic databases. Meta-analyses estimating diagnostic accuracy (DA) for individual host markers and for grouped salivary and gingival crevicular fluid (GCF) markers independently were performed whenever two or more studies were identified.

RESULTS

Sixty-one eligible studies were identified, of which 13 were included in meta-analyses for FQ1 (discrimination between health and periodontitis). Matrix metalloproteinase-8 (MMP-8) was the most reported biomarker in both saliva and GCF, with comparable AUC (0.70-0.90), sensitivity (0.49-0.84) and specificity (0.62-0.79) in both sample types. Cytokines had good ability for discrimination of periodontitis/gingivitis versus health, although they were substantially less accurate for periodontitis versus gingivitis. Combinations of cytokines and MMPs tended to increase overall diagnostic accuracy but without significant improvement in the case of periodontitis/gingivitis discrimination. Bone markers were the best performing group of salivary markers (AUC = 0.91) when compared to cytokines (AUC = 0.86) and MMPs (AUC = 0.77). GCF microRNAs (MiRs) were a singly meta-analysed group of biomarkers demonstrating AUC = 0.79.

CONCLUSION

Reported studies on host periodontal markers exhibit serious limitations regarding clinical and validation standards, being the main cause for lack of progress in clinical implementation of biomarkers in periodontal classification. Disease-specific markers such as bone markers showed better diagnostic performance (from limited number of studies) for the diagnosis of periodontitis when compared to cytokines and MMPs.

Oral and Gingival Crevicular Fluid Biomarkers for Jawbone Turnover Diseases: A Scoping Review

Gingival crevicular fluid (GCF) and oral fluid have emerged as promising diagnostic tools for detecting biomarkers. This review aimed to evaluate the existing literature on using oral fluids as a source of biomarkers for bone turnover diseases affecting the jawbone. A comprehensive search strategy was executed between August 2014 and August 2024 across five major databases (Web of Science, EBSCOhost Dentistry & Oral Sciences Source, Cochrane Library, Scopus, and PubMed) and grey literature sources. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) was applied. The screening was facilitated using Rayyan at rayyan.ai and Endnote X20 software tools, culminating in the evaluation of 14,965 citations from databases and 34 from grey literature. Following rigorous scrutiny, 37 articles were selected for inclusion in this review, encompassing diseases such as periodontitis, medication-related osteonecrosis of the jaw (MRONJ), and osteoporosis. The quality of the included observational studies was assessed using the Revised Risk of Bias Assessment Tool for Non-Randomized Studies (RoBANS 2). Interleukin-1 beta (IL-1β), sclerostin, osteoprotegerin (OPG), and interleukin-34 (IL-34) emerged as significant biomarkers in GCF, and they were mainly from periodontitis and osteoporosis. Osteocalcin (OC), IL-1β, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), OPG, and matrix metalloproteinase-9 (MMP-9) were significant in oral fluid or saliva, and they were from periodontitis, MRONJ, and osteoporosis. These findings underscore the potential use of oral fluids, which are regarded as non-invasive tools for biomarker identification in bone turnover. Many biomarkers overlap, and it is important to identify other specific biomarkers to enable accurate diagnosis of these conditions.

Clinical Significance of Inflammatory Factors, Osteocalcin, and Matrix Metalloproteinase-8 in Gingival Crevicular Fluid in Drug Treatment of Severe Periodontitis

Whether gingival crevicular fluid (GCF) indexes in patients with severe periodontitis affect the efficacy of drug treatment was a new direction of recent research. At present, there were few studies on the effects of inflammatory indicators, BGP, and MMP-8 levels in GCF on the efficacy of drug treatment in such patients. So the purpose of this study was to observe the changes in osteocalcin (BGP), matrix metalloproteinase-8 (MMP-8), and inflammatory indexes levels in GCF of patients with severe periodontitis. The correlation between the above indexes and the effect of drug treatment in the patients was analyzed, in order to provide guidance for improving the clinical curative effect of severe periodontitis. A retrospective analysis was conducted to collect the baseline data of patients with severe periodontitis who were treated with Minocycline Hydrochloride Ointment in our hospital. The inflammatory indicators, BGP, and MMP-8 levels in GCF were analyzed before drug treatment, and the treatment effect on the patients was counted. Logistic regression was used to analyze the correlation between BGP, MMP-8, and inflammatory indicators levels in GCF and the drug treatment effect on the patients. After statistical analysis, we found that the response rate was 69% and the inefficiency was 31%. There were no significant differences in C-reactive protein (CRP) and tumor necrosis factor-α (TNF-α) levels between the inefficacy group and efficacy group (P > 0.05). Compared with the efficacy group, the levels of interleukin-6 (IL-6), interleukin-1β (IL-1β), interleukin-8 (IL-8), BGP, and MMP-8 were increased in the inefficacy group. High levels of IL-6, IL-1β, IL-8, BGP, and MMP-8 were associated with ineffective drug treatment in patients with severe periodontitis (all OR >1 and P < 0.05). Levels of IL-6, IL-1β, IL-8, BGP, and MMP-8 predicted that the AUCs of drug treatment failure in patients with severe periodontitis were all greater than 0.7, which were 1.398, 1.458, 1.244, 1.012, and 1.012, respectively. From this, we can conclude that increased levels of BGP, MMP-8, and inflammatory indicators such as IL-6, IL-1β, and IL-8 in GCF would increase the risk of ineffective drug treatment in patients with severe periodontitis. The clinical treatment plan could be adjusted according to the levels of the above indicators in GCF to improve the effectiveness of drug treatment in patients.

Histological and Immunohistochemical Analysis of Peri-Implant Soft and Hard Tissues in Patients with Peri-Implantitis

Currently, researchers are focused on the study of cytokines as predictive biomarkers of peri-implantitis (PI) in order to obtain an early diagnosis and prognosis, and for treatment of the disease. The aim of the study was to characterize the peri-implant soft and hard tissues in patients with a peri-implantitis diagnosis. A descriptive observational study was conducted. Fifteen soft tissue (ST) samples and six peri-implant bone tissue (BT) samples were obtained from 13 patients who were diagnosed with peri-implantitis. All the samples were processed and embedded in paraffin for histological and immunohistochemical analyses. A descriptive and quantitative analysis of mast cells and osteocytes, A proliferation-inducing ligand (APRIL), B-cell activating factor (BAFF), osteonectin (ON), and ∝-smooth muscle actin (∝-SMA) was performed. We observed the presence of mast cells in peri-implant soft tissue in all samples (mean 9.21 number of mast cells) and osteocytes in peri-implant hard tissue in all samples (mean 37.17 number of osteocytes). The expression of APRIL-ST was 32.17% ± 6.39%, and that of APRIL-BT was 7.09% ± 5.94%. The BAFF-ST expression was 17.26 ± 12.90%, and the BAFF-BT was 12.16% ± 6.30%. The mean percentage of ON was 7.93% ± 3.79%, and ∝-SMA was 1.78% ± 3.79%. It was concluded that the expression of APRIL and BAFF suggests their involvement in the bone resorption observed in peri-implantitis. The lower expression of osteonectin in the peri-implant bone tissue can also be associated with a deficiency in the regulation of bone remodeling and the consequent peri-implant bone loss.

Comparison of Salivary IGF-1, IGFBP-3, and CTX with Periodontal Status among Patients Belonging to Various Skeletal Maturity Groups

PURPOSE

To compare the levels of salivary IGF-1, IGFBP-3, and CTX with periodontal status among patients belonging to various skeletal maturity groups.

MATERIALS AND METHODS

This cross-sectional study was conducted on 80 participants 6 to 25 years of age. Based on skeletal maturity, the participants were categorised into 3 different stages: prepubertal, pubertal, and post-pubertal stages. The periodontal status of the participants was assessed using the simplified oral hygiene index (OHI-S), bleeding on probing (BOP), probing pocket depth (PPD), clinical attachment loss (CAL), and community periodontal index (CPI). The saliva samples were examined for IGF-1, IGFBP-3, and CTX using the respective ELISA kits. One-way ANOVA was used to determine statistically significant differences of means across the study groups for continuous variables.

RESULTS

The study demonstrated statistically significant differences for the parameters OHI-S, bleeding on probing, PPD, CPI, and CAL (p < 0.05) depending on skeletal maturity stage. ANOVA test showed a statistically significant difference by stage in IGF-1, IGFPB3, and CTX (p < 0.01).

CONCLUSION

An association exists between periodontal status and levels of salivary IGF-1, IGFBP-3, and CTX in patients belonging to various skeletal maturity groups.

Evaluation of the Papillary Gingival Vasculature in Smokers and Nonsmokers with Chronic Periodontitis: A Clinical In Vivo Study

AIM

Cigarette smoking has been recognized as an important risk factor in periodontal diseases. One of the suggested mechanisms behind this association is that nicotine alters the microcirculation and causes vasoconstriction and reduced blood flow through the periodontal tissues. Scarce information is currently available relative to the microvascular alterations associated with smoking and the distribution of capillaries through the various areas of the gingival tissues. The aims of this study were to assess, in human interproximal gingival biopsies, the number and diameter of gingival capillaries in periodontally affected smokers and nonsmokers using the CD34 immunohistochemical staining method. The pattern of distribution of vessels in the different areas of the gingival tissues was also assessed.

MATERIALS AND METHODS

Systemically healthy patients with moderate chronic periodontitis and ranging in age between 30 and 60 years were recruited for the study from the patient population attending the Periodontology Department of the Faculty of Dental Medicine at the Lebanese University of Beirut. The patients were selected to have a group of 10 patients (Group SP) of smokers (>10 cigarettes/day for the last 10 years) and a second group (Group NP) consisting of nonsmoking periodontally affected patients. Three to four weeks following initial preparation, one interproximal gingival biopsy was obtained from each patient. Immunohistochemical staining with CD34 mouse monoclonal antibody was used to identify the endothelial cells of the blood vessels within each sample. Twelve biopsy samples (five in Group NP and seven in Group SP) were chosen for the measurement of the number and diameter of vessels in three regions of the connective tissue of the biopsy under a blinded protocol.

RESULTS

In the two groups, the quantitative distribution of small, medium, and large vessels followed a similar trend with the number of small vessels being significantly greater than both medium and large vessels. Small vessels prevailed in the peripheral regions, whereas large vessels were more abundant in the deeper connective tissue areas. The total number of vessels seemed unaffected by chronic cigarette smoking in both groups in the entire biopsy area and in the separate connective tissue regions. Quantitative alteration in the total number of gingival capillaries was not observed in chronic smokers. A redistribution of small and large vessels in the superficial and deeper connective tissue areas of the gingival papilla was noted as a result of smoking in periodontal patients.

CONCLUSION

The quantitative distribution of small, medium, and large vessels follows a similar trend with the content in small vessels being significantly more important than both medium and large vessels. Smoking and periodontitis result in a redistribution of small and large vessels in the superficial and deeper connective tissue areas of the gingival papilla compared to nonsmoking periodontal patients. The significance and clinical implications of such rearrangement of vasculature within the gingival tissue need to be further investigated.