The clinical value of salivary biomarkers for periodontal disease

Accuracy of periodontitis diagnosis obtained using multiple molecular biomarkers in oral fluids: A systematic review and meta-analysis

AIM

To determine the accuracy of biomarker combinations in gingival crevicular fluid (GCF) and saliva through meta-analysis to diagnose periodontitis in systemically healthy subjects.

METHODS

Studies on combining two or more biomarkers providing a binary classification table, sensitivity/specificity values or group sizes in subjects diagnosed with periodontitis were included. The search was performed in August 2022 through PUBMED, EMBASE, Cochrane, LILACS, SCOPUS and Web of Science. The methodological quality of the articles selected was evaluated using the QUADAS-2 checklist. Hierarchical summary receiver operating characteristic modelling was employed to perform the meta-analyses (CRD42020175021).

RESULTS

Twenty-one combinations in GCF and 47 in saliva were evaluated. Meta-analyses were possible for six salivary combinations (median sensitivity/specificity values): IL-6 with MMP-8 (86.2%/80.5%); IL-1β with IL-6 (83.0%/83.7%); IL-1β with MMP-8 (82.7%/80.8%); MIP-1α with MMP-8 (71.0%/75.6%); IL-1β, IL-6 and MMP-8 (81.8%/84.3%); and IL-1β, IL-6, MIP-1α and MMP-8 (76.6%/79.7%).

CONCLUSIONS

Two-biomarker combinations in oral fluids show high diagnostic accuracy for periodontitis, which is not substantially improved by incorporating more biomarkers. In saliva, the dual combinations of IL-1β, IL-6 and MMP-8 have an excellent ability to detect periodontitis and a good capacity to detect non-periodontitis. Because of the limited number of biomarker combinations evaluated, further research is required to corroborate these observations.

Mass Spectrometry-Based Proteomics for Discovering Salivary Biomarkers in Periodontitis: A Systematic Review

Periodontitis is one of the primary causes of tooth loss, and is also related to various systemic diseases. Early detection of this condition is crucial when it comes to preventing further oral damage and the associated health complications. This study offers a systematic review of the literature published up to April 2023, and aims to clearly explain the role of proteomics in identifying salivary biomarkers for periodontitis. Comprehensive searches were conducted on PubMed and Web of Science to shortlist pertinent studies. The inclusion criterion was those that reported on mass spectrometry-driven proteomic analyses of saliva samples from periodontitis cohorts, while those on gingivitis or other oral diseases were excluded. An assessment for risk of bias was carried out using the Newcastle-Ottawa Scale and Quality Assessment of Diagnostic Accuracy Studies or the NIH quality assessment tool, and a meta-analysis was performed for replicable candidate biomarkers, i.e., consistently reported candidate biomarkers (in specific saliva samples, and periodontitis subgroups, reported in ≥2 independent cohorts/reports) were identified. A Gene Ontology enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery bioinformatics resources, which consistently expressed candidate biomarkers, to explore the predominant pathway wherein salivary biomarkers consistently manifested. Of the 15 studies included, 13 were case-control studies targeting diagnostic biomarkers for periodontitis participants (periodontally healthy/diseased, n = 342/432), while two focused on biomarkers responsive to periodontal treatment (n = 26 participants). The case-control studies were considered to have a low risk of bias, while the periodontitis treatment studies were deemed fair. Summary estimate and confidence/credible interval, etc. determination for the identified putative salivary biomarkers could not be ascertained due to the low number of studies in each case. The results from the included case-control studies identified nine consistently expressed candidate biomarkers (from nine studies with 230/297 periodontally healthy/diseased participants): (i) those that were upregulated: alpha-amylase, serum albumin, complement C3, neutrophil defensin, profilin-1, and S100-P; and (ii) those that were downregulated: carbonic anhydrase 6, immunoglobulin J chain, and lactoferrin. All putative biomarkers exhibited consistent regulation patterns. The implications of the current putative marker proteins identified were reviewed, with a focus on their potential roles in periodontitis diagnosis and pathogenesis, and as putative therapeutic targets. Although in its early stages, mass spectrometry-based salivary periodontal disease biomarker proteomics detection appeared promising. More mass spectrometry-based proteomics studies, with or without the aid of already available clinical biochemical approaches, are warranted to aid the discovery, identification, and validation of periodontal health/disease indicator molecule(s). Protocol registration number: CRD42023447722; supported by RD-02-202410 and GRF17119917.

Biomarkers for diagnosis of stage III, grade C with molar incisor pattern periodontitis in children and young adults: a systematic review and meta-analysis

AIM

To explore the existing salivary, gingival crevicular fluid (GCF), blood, and serum biomarkers associated with grade C molar-incisor pattern (C/MIP) periodontitis in systemically healthy children and young adults.

MATERIALS AND METHODS

Cross-sectional, case-control, and cohort studies on stage III grade C periodontitis or former equivalent diagnosis with analysis of molecular biomarkers in saliva, GCF, blood, or serum were retrieved from six databases and screened based on the eligibility criteria. The risk of bias in included studies was evaluated. Meta-analysis was planned for biomarkers assessed using the same detection methods and sample type in at least two papers.

RESULTS

Out of 5621 studies identified at initial screening, 28 papers were included in the qualitative analysis of which 2 were eligible for meta-analysis for IgG in serum samples. Eighty-seven biomarkers were assessed with the majority being higher in cases than in controls. Only the meta-analysis of total serum IgG with low heterogeneity value revealed a significant increase in its levels in C/MIPs compared to controls (standardised mean difference: 1.08; 95% CI: 0.76, 1.40).

CONCLUSION

There is a paucity of data on biomarkers associated with molar-incisor pattern periodontitis. Although serum IgG levels are raised, other more specific biomarkers in saliva, GCF, and blood/serum may be promising but require further investigation.

Can the salivary urea and stimulated saliva concentration be a marker of periodontal diseases in opioid users? A case-control study

Introduction

& Aim: Microbial plaque is the primary cause of periodontal diseases, and smoking and opioid addiction can accelerate microbial plaque formation and disease progression. Adequate saliva flow and salivary urea concentration are important parameters for a healthy periodontium. In this study, the relationship between Periodontal Diseases and the History of opioid addiction was investigated by measuring the Salivary Urea and Stimulated Saliva Concentration.

Materials & methods

This case-control study was conducted on 240 patients (120 cases and 120 controls) in 2021 referred to addiction treatment centers and the dental clinic in Iran, Birjand. The control and case groups were matched in terms of age. Demographic, base data, and clinical examination results were collected by a checklist. Data were analyzed using SPSS 19 and one-way ANOVA and chi-square tests. P-value <0.05 was considered as the significance level.

Results

Periodontitis severity was significantly higher in the case group than in the control group (P-value = 0/000). Salivary urea concentration significantly increased in both case and control groups with an increase in periodontitis severity (P-value = 0/003 in the case group and P-value = 0/000 in the control group), but there was no significant relationship between the stimulated saliva flow rate and the severity of periodontitis in these two groups (P-value>0.05).

Conclusion

Following the use of opioids, the flow of saliva decreases, and with the exacerbation of the periodontal disease, the concentration of urea in saliva increases. Therefore, it seems that the analysis of saliva parameters, including urea concentration, can be useful for the diagnosis of periodontal disease, and saliva urea concentration is not directly related to opioid use.

Effects of Nonsurgical Periodontal Therapy on Glycemic Control in Diabetic Patients under Systemic Administration of Antidiabetic Ayurvedic Drug

AIM

This study aimed to monitor the metabolic response of nonsurgical periodontal therapy in type-2 diabetic patients with chronic periodontitis under systemic administration of antidiabetic ayurvedic drug.

MATERIALS AND METHODS

About 90 newly diagnosed mild-to-moderate forms of type-2 diabetes mellitus (DM) subjects with generalized chronic periodontitis were selected according to the inclusion and exclusion criteria and were randomly divided into group A and group B with 45 patients in each group. Clinical parameters, including plaque index, probing pocket depth, clinical attachment level, and glycemic status, were assessed at baseline. Following initial periodontal clinical examination, the drug Nishamalaki (NA) 2 gm twice daily for 3 months was prescribed after food by an Ayurvedic physician to all the patients enrolled in group A and group B, and scaling and root planing were completed only for group B patients. Patients were recalled for review, and all the parameters were reassessed at the end of the 1st, 2nd, and 3rd months following interventions.

RESULTS

Regarding clinical and metabolic parameters at baseline, no statistically significant differences were displayed between the two groups. However, at the 3-months follow-up period, the patients in group B demonstrated significantly better clinical and metabolic outcomes than patients in group A.

CONCLUSION

Periodontal therapy improved glycemic control in patients with type-2 DM in both groups; however, the reduction in FBS values reached statistical significance only in the group receiving scaling and root planing alone.

CLINICAL SIGNIFICANCE

Nonsurgical periodontal therapy may have a beneficial effect on the periodontal clinical and glycemic levels in type-2 diabetic patients with chronic periodontitis.

Effect of psoralen on the regulation of osteogenic differentiation induced by periodontal stem cell-derived exosomes

Periodontitis is a chronic inflammatory disease that is the main cause of tooth loss in adults, and the key to periodontitis treatment is the repair and regenerate of periodontal bone tissue. Psoralen is the main component of the Psoralea corylifolia Linn, which shows antibacterial, anti-inflammatoryand osteogenic activities. It promotes the differentiation of periodontal ligament stem cells toward osteogenesis. Exosomes secreted by stem cells play important roles in information transmission during the osteogenic differentiation process. The aim of this paper was to investigate the role of psoralen in regulating osteogenic miRNA information in periodontal stem cells and in periodontal stem cells exosomes and the specific mechanism of its action. Experimental results show that exosomes of human periodontal ligament stem cell origin treated with psoralen (hPDLSCs + Pso-Exos) were not significantly different from untreated exosomes (hPDLSC-Exos) in terms of size and morphology. Thirty-five differentially expressed miRNAs were found to be upregulated and 58 differentially expressed miRNAs were found to be downregulated in the hPDLSCs + Pso-Exos compared to the hPDLSC-Exos (P < 0.05). hsa-miR-125b-5p was associated with osteogenic differentiation. Among them, hsa-miR-125b-5p was associated with osteogenic differentiation. After hsa-miR-125b-5p was inhibited, the osteogenesis level of hPDLSCs was enhanced. In summary, the osteogenic differentiation of hPDLSCs was promoted by psoralen through the downregulation of hsa-miR-125b-5p gene expression in hPDLSCs, and the expression of the hsa-miR-125b-5p gene was also downregulated in exosomes. This finding provides a new therapeutic idea for using psoralen to promote periodontal tissue regeneration.

Ceramide Phosphoethanolamine as a Possible Marker of Periodontal Disease

Periodontal disease is a chronic oral inflammatory disorder initiated by pathobiontic bacteria found in dental plaques—complex biofilms on the tooth surface. The disease begins as an acute local inflammation of the gingival tissue (gingivitis) and can progress to periodontitis, which eventually leads to the formation of periodontal pockets and ultimately results in tooth loss. The main problem in periodontology is that the diagnosis is based on the assessment of the already obvious tissue damage. Therefore, it is necessary to improve the current diagnostics used to assess periodontal disease. Using lipidomic analyses, we show that both crucial periodontal pathogens, Porphyromonas gingivalis and Tannerella forsythia, synthesize ceramide phosphoethanolamine (CPE) species, membrane sphingolipids not typically found in vertebrates. Previously, it was shown that this particular lipid can be specifically detected by an aegerolysin protein, erylysin A (EryA). Here, we show that EryA can specifically bind to CPE species from the total lipid extract from P. gingivalis. Furthermore, using a fluorescently labelled EryA-mCherry, we were able to detect CPE species in clinical samples of dental plaque from periodontal patients. These results demonstrate the potential of specific periodontal pathogen-derived lipids as biomarkers for periodontal disease and other chronic inflammatory diseases.

Comparative Evaluation of Salivary Enzyme in Patients With Gingivitis and Periodontitis: A Clinical-Biochemical Study

Objective This study aims to relate aspartate aminotransferase (AST) in saliva and periodontal status in patients with gingivitis and periodontitis. Methods Forty-five patients have undergone a periodontal detailed examination as well as indexes sorted and classified into three gingival-based groups: healthy, gingivitis and periodontitis. Fifteen (15) patients were assigned for each group. Ten milliliter of stimulated saliva from a patient was collected after rinsing the mouth with 15 mL of water in a sterile tube. Biochemical analysis was conducted using the study GOT (ASAT) IFCC mod. liquiUV kit from HUMAN. Kinetic method for the determination of GOT (ASAT) activity and TC 84 Teco diagnostics chemistry analyzer. Result Acquired results indicated statically significant increases of AST level in saliva from patients with periodontitis and gingivitis (p < 0.01) in relation to the control group. Conclusion These results revealed that salivary AST level is higher in patients that have periodontal destruction, pocket depth and bleeding in probing. This clinically indicated that salivary biomarkers can be used as a diagnostic tool for the evaluation of periodontal health status.

Biochemical Interaction between Materials Used for Interim Prosthetic Restorations and Saliva

The purpose of this study was to analyze the oxidative stress level and inflammatory status of saliva in the presence of certain materials used for obtaining interim prosthetic restorations. Four types of interim resin materials were investigated: a pressure/heat-cured acrylic resin (Superpont C+B, SpofaDental a.s Czech Republic, /KaVo Kerr Group), a milled resin (Telio CAD polymethyl methacrylate, Ivoclar Vivadent AG, Liechtenstein), a 3D printed resin (NextDent C&B MFH, NextDent by 3D Systems, the Netherlands), and a pressure/heat-cured micro-filled indirect composite resin (SR Chromasit, Ivoclar Vivadent AG, Liechtenstein). The disk-shaped resin samples (30 mm diameter, 2 mm high) were obtained in line with the producers' recommendations. The resulting resin specimens were incubated with saliva samples collected from twenty healthy volunteers. In order to analyze the antioxidant activity of the tested materials, certain salivary parameters were evaluated before and after incubation: uric acid, gamma glutamyl transferase (GGT), oxidative stress responsive kinase-1 (OXSR-1), and total antioxidant capacity (TAC); the salivary levels of tumor necrosis factor (TNFα) and interleukin-6 (IL-6) (inflammatory markers) were measured as well. The obtained results are overall favorable, showing that the tested materials did not cause significant changes in the salivary oxidative stress level and did not influence the inflammatory salivary status.

The Potential Impact of Salivary IL-1 on the Diagnosis of Periodontal Disease: A Pilot Study

The aim of this study was to identify inflammatory cytokines as salivary biomarkers for periodontal disease. The subjects were 33 Korean adults aged 23 to 71 years. Using a multiplexed bead immunoassay called Luminex, the levels of inflammatory cytokines related to periodontal disease were evaluated. Oral examination for periodontal disease and gingival bleeding was conducted. With these two independent variables, differences in inflammatory cytokines were analyzed by an independent t-test and age-adjusted ANCOVA. Among the subjects, 21 had periodontal disease and 12 were healthy subjects. The gingival bleeding status was classified into low and high levels. Among 13 inflammatory cytokines in saliva, IL-1α, IL-1β, IL-4, IL-8, CCL2/MCP-1, CCL3/MIP-1α, and TNF-α were found to be significant biomarkers within the standard curve. The quantity of IL-1β was increased in subjects with high levels of gingival bleeding. IL-1α levels were increased in subjects with periodontal disease. After adjusting for age, the significant biomarkers for gingival bleeding and periodontal disease were IL-1β and IL-1α, respectively. Using the receiver operating characteristic (ROC) curve, IL-1β was confirmed as a significant biomarker. The sensitivity and specificity of IL-1β for predicting periodontitis were 88.24% and 62.5%, respectively. Therefore, IL-1 was found to be a significant biomarker for periodontal disease, and it could be used in the diagnosis of periodontal disease using saliva.

Predictive Periodontitis: The Most Promising Salivary Biomarkers for Early Diagnosis of Periodontitis

The primary cause of tooth loss in the industrialized world is periodontitis, a bacterial anaerobic infection whose pathogenesis is characterized by composite immune response. At present, the diagnose of periodontitis is made by a complete status check of the patient’s periodontal health; full-mouth plaque score, full-mouth bleeding score, probing depth, clinical attachment level, bleeding on probing, recessions, mobility, and migration are evaluated in order to provides a clear picture of the periodontal conditions of a single patient. Chair-side diagnostic tests based on whole saliva could be routinely used by periodontists for a very early diagnosis of periodontitis, monitoring, prognosis, and management of periodontal patients by biomarker detection, whose diagnostic validity is related to sensitivity and specificity. Recent paper reviews and meta-analyses have focused on five promising host derived biomarkers as candidate for early diagnosis of periodontitis: MMP-8 (Metalloproteinase-8), MIP-1α (Macrophage inflammatory protein-1 alpha), IL-1 β (Interleukin-1 beta), IL-6 (Interleukin-6), and HB (Hemoglobin), and their combinations. Chair-side Lab-on-a-chip (LOC) technology may soon become an important part of efforts to detect such biomarkers in saliva medium to improve worldwide periodontal health in developed nations as well as in underserved communities and poor countries. Their applications in preventive and predictive medicine is now fundamental, and is aimed at the early detection of risk factors or the presence or evolution of the disease, and in personalized medicine, which aims to identify tailor-made treatments for individual patients. The aim of the present paper is to be informative about host derived periodontal biomarkers and, in particular, we intend to report information about the most important immune response derived biomarkers and Hemoglobin as candidates to be routinely utilized in order to obtain a chair-side early diagnosis of periodontal disease.

Peptidomic changes of saliva after nonsurgical treatment of stage I / II generalized periodontitis

OBJECTIVE

To explore the changes of peptidome profiles of saliva, serum and gingival crevicular fluid (GCF) before and after nonsurgical periodontal treatment in patients with generalized periodontitis (stage I / II).

SUBJECTS AND METHODS

Saliva, serum and GCF samples were collected from 17 patients at baseline (T₀ ), one week after ultrasonic supragingival scaling (T₁ ) and eight weeks after subgingival scaling and root planning (T₂ ). Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) was carried out to detect changes in peptidomic profiles. Then nano-liquid chromatography-electrospray ionization-tandem mass spectrometry (nano-LC/ESI-MS/MS) was performed to identify potential peptide biomarkers.

RESULTS

Most of the peptides from the patients exhibited a decreasing trend from the time point of pre-treatment to that of post-treatment. Cluster analysis and scatter plots using these peptides indicated that salivary peptidome has an acceptable capability of reflecting the status of stage I / II generalized periodontitis. Seven of these peptides were successfully identified as α-1-antitrypsin, immunoglobulin κ variable 4-1, haptoglobin and immunoglobulin heavy constant γ2.

CONCLUSIONS

Certain peptides in saliva, serum and GCF were down-regulated after nonsurgical periodontal treatment, demonstrating the application prospects of saliva in monitoring and surveillance of periodontal diseases in both clinical settings and communities.

The trefoil factor family 1 (TFF-1) and 3 (TFF-3) are upregulated in the saliva, gingival crevicular fluid and serum of periodontitis patients

OBJECTIVE

This study aimed to investigate the levels of trefoil factor family (TFF)-1, TFF-3 and interleukin (IL)-1β in gingival crevicular fluid (GCF), saliva and serum of patients with gingivitis, stage 3 periodontitis and healthy individuals.

MATERIALS AND METHODS

A total of 100 individuals consisting of 25 periodontally healthy, 25 gingivitis and 50 stage 3 periodontitis, were enrolled in the study. Clinical periodontal examinations were recorded and GCF, saliva and serum samples were obtained. TFF-1, TFF-3 and IL-1β were measured by ELISA.

RESULTS

TFF-1 and TFF-3 levels in both GCF, saliva and serum were higher in periodontitis patients than healthy controls (p < .001) and gingivitis group (p < .01). The levels of these peptides in all biofluids were similar between gingivitis and healthy control groups (p > .05). GCF, saliva and serum IL-1β levels were also higher in periodontitis patients than the controls (p < .01). Periodontitis patients had elevated GCF and saliva IL-β levels than gingivitis group (p < .001).

CONCLUSION

Elevated TFF-1 and TFF-3 levels both locally and systemically in periodontitis in parallel to increased IL-1β levels might suggest that these peptides are involved in host response during the periodontal tissue destruction.

Changes in Inflammatory Cytokines in Saliva after Non-Surgical Periodontal Therapy: A Systematic Review and Meta-Analysis

To determine the diagnostic value of inflammatory cytokines in periodontal disease, we performed a systematic review of the changes in inflammatory cytokines after non-surgical periodontal therapy and a meta-analysis of the utility of interleukin (IL)-1β and matrix metalloproteinase (MMP)-8 as salivary biomarkers. All available papers published in English until 20 August 2020, were searched in the MEDLINE and EMBASE databases. Population, intervention, comparison, and outcome data were extracted from the selected studies, and the roles of IL-1β and MMP-8 were assessed in a meta-analysis. Eleven studies, including two meta-analyses, were assessed in the systematic review. Biomarkers showing high levels in periodontal disease were salivary IL-1β, IL-4, IL-6, MMP-8, and tissue inhibitor of matrix metalloproteinases (TIMP)-2, and those in the controls were tumor necrosis factor (TNF)-α, IL-10, IL-17, and IL-32. Biomarkers that decreased after scaling and root planning (SRP) and oral hygiene instruction (OHI) in periodontitis patients were IL-1β, MMP-8, MMP-9, prostaglandin E2 (PGE₂), and TIMP-2. The pooled standardized mean difference of IL-1β and MMP-8 was −1.04 and 35.90, respectively, but the differences between periodontitis patients and healthy controls were not significant. Although the changes in salivary IL-1β and MMP-8 levels after non-surgical periodontal therapy were not significant, salivary cytokines could be used to confirm the effect of periodontal therapy or diagnose periodontal disease.

Transcriptomic profiles and their correlations in saliva and gingival tissue biopsy samples from periodontitis and healthy patients

Purpose

This study was conducted to analyze specific RNA expression profiles in gingival tissue and saliva samples in periodontitis patients and healthy individuals, and to determine their correlations in light of the potential use of microarray-based analyses of saliva samples as a periodontal monitoring tool.

Methods

Gingival tissue biopsies and saliva samples from 22 patients (12 with severe periodontitis and 10 with a healthy periodontium) were analyzed using transcriptomic microarray analysis. Differential gene expression was assessed, and pathway and clustering analyses were conducted for the samples. The correlations between the results for the gingival tissue and saliva samples were analyzed at both the gene and pathway levels.

Results

There were 621 differentially expressed genes (DEGs; 320 upregulated and 301 downregulated) in the gingival tissue samples of the periodontitis group, and 154 DEGs (44 upregulated and 110 downregulated) in the saliva samples. Nine of these genes overlapped between the sample types. The periodontitis patients formed a distinct cluster group based on gene expression profiles for both the tissue and saliva samples. Database for Annotation, Visualization and Integrated Discovery analysis revealed 159 enriched pathways from the tissue samples of the periodontitis patients, as well as 110 enriched pathways In the saliva samples. Thirty-four pathways overlapped between the sample types.

Conclusions

The present results indicate the possibility of using the salivary transcriptome to distinguish periodontitis patients from healthy individuals. Further work is required to enhance the extraction of available RNA from saliva samples.

The combined use of salivary biomarkers and clinical parameters to predict the outcome of scaling and root planing: A cohort study

AIM

To explore the application of the combined use of baseline salivary biomarkers and clinical parameters in predicting the outcome of scaling and root planing (SRP).

MATERIALS AND METHODS

Forty patients with advanced periodontitis were included. Baseline saliva samples were analysed for interleukin-1β (IL-1β), matrix metalloproteinase-8 and the loads of Porphyromonas gingivalis, Prevotella intermedia, Aggregatibacter actinomycetemcomitans and Tannerella forsythia. After SRP, pocket closure and further attachment loss at 6 months post-treatment were chosen as outcome variables. Models to predict the outcomes were established by generalized estimating equations.

RESULTS

The combined use of baseline clinical attachment level (CAL), site location and IL-1β (area under the curve [AUC] = 0.764) better predicted pocket closure than probing depth (AUC = 0.672), CAL (AUC = 0.679), site location (AUC = 0.654) or IL-1β (AUC = 0.579) alone. The combination of site location, tooth loss, percentage of deep pockets, detection of A. actinomycetemcomitans and T. forsythia load (AUC = 0.842) better predicted further clinical attachment loss than site location (AUC = 0.715), tooth loss (AUC = 0.530), percentage of deep pockets (AUC = 0.659) or T. forsythia load (AUC = 0.647) alone.

CONCLUSION

The combination of baseline salivary biomarkers and clinical parameters better predicted SRP outcomes than each alone. The current study indicates the possible usefulness of salivary biomarkers in addition to tooth-related parameters in predicting SRP outcomes.

Diagnostic and Prognostic ability of salivary MMP-9 and S100A8 for periodontitis

OBJECTIVES

Salivary diagnostic using matrix metalloproteinase (MMP) and S100 for periodontitis is a promising issue. However, its prognostic effect is still unclear. This study aimed to evaluate the prognostic ability of salivary MMP-9 and S100A8 for periodontitis through non-surgical periodontitis treatment clinical trial.

MATERIALS AND METHODS

Total 149 participants, 99 periodontitis and 50 healthy, were recruited. Among 99 non-surgical periodontitis treatment participants, 74 participants were revisited after three months. Periodontitis was classified as stage II-IV of new classification of periodontitis proposed at 2018. Enzyme-linked immunosorbent assay kit was used to quantify salivary MMP-9 and S100A8. Receiver operating characteristic curve was applied for diagnostic ability. Paired t test was applied for prognostic ability evaluating changes in salivary markers between pre- and post-treatment.

RESULTS

Salivary MMP-9 and S100A8 were associated with periodontitis (p < .05). The screening ability of algorithm using salivary MMP-9 and S100A8 for periodontitis was 0.86 (p < .05). After treatment, reduction rate of salivary S100A8 and MMP-9 was 83.7% and 23.5%, respectively, (p < .05): only salivary S100A8 was superior compared to clinical parameters.

CONCLUSION

Algorithm using salivary MMP-9 and S100A8 showed high diagnostic power for periodontitis. Both salivary S100A8 and MMP-9 showed prognostic ability for periodontitis, but S100A8 was better.

Omega-3 Polyunsaturated Fatty Acids EPA and DHA as an Adjunct to Non-Surgical Treatment of Periodontitis: A Randomized Clinical Trial

Periodontitis is a chronic multifactorial inflammatory disease that leads to the loss of supportive tissues around the teeth with gradual deterioration of masticatory function and esthetics, resulting eventually in the decrease of the life quality. Host immune response triggered by bacterial biofilm is responsible for the chronic periodontal inflammation and ongoing tissue loss. Omega-3 polyunsaturated fatty acids (PUFA) such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have anti-inflammatory properties, thus may be used for the treatment of chronic inflammatory diseases. In this study, we aimed to evaluate the effect of dietary supplementation with omega-3 PUFA in the patients with stage III and IV periodontitis. Thirty otherwise healthy patients were treated with scaling and root planning (SRP). In the test group (n = 16), patients were additionally supplemented with 2.6 g of EPA and 1.8 g of DHA. In the control group (n = 14), patients received only SRP. Periodontal examination was performed at baseline and three months following initial therapy. Salivary samples were taken twice at baseline and at the end of the experiment. We found that there was a statistically significant reduction in the bleeding on probing (BOP) and improvement of clinical attachment loss (CAL) at three months in the test group compared to the control group. Moreover, a statistically significant higher percentage of closed pockets (probing depth ≤ 4 mm without BOP) was achieved in the test group vs. control group after three months of treatment. Accordingly, the levels of pro-inflammatory cytokines/chemokines interleukin (IL)-8 and IL-17 were markedly lower, while the level of anti-inflammatory IL-10 was significantly higher in the salivary samples of the patients supplemented with omega-3 PUFA at three months in comparison to the patients treated with SRP alone. Our findings demonstrate that dietary intervention with high-dose of omega-3 PUFA during non-surgical therapy may have potential benefits in the management of periodontitis.

Salivary proteomic profile of dogs with and without dental calculus

BACKGROUND

Dogs' saliva is a complex mixture of inorganic and organic constituents, rich in proteins. Therefore, knowing the saliva composition of these animals is extremely important to identify the presence of proteins that may be involved in physiological and pathological mechanisms of their oral cavity. The present study aimed to characterize the proteomic profile of saliva from dogs with and without dental calculus.

RESULTS

Saliva samples were collected from 20 dogs. Before the collection, a visual clinical examination was performed and 8 subjects (40%) did not present any signs of dental calculus, while 12 (60%) presented dental calculus. After saliva collection, the samples were submitted to protein quantification (mBCA), and then they were prepared for analysis by nLC-ESI-MS/MS. A total of 658 unique proteins were identified, of which 225 were specific to dogs without dental calculus, 300 were specific to dogs with dental calculus, and 133 were common to all subjects. These proteins presented functions including transportation, immune response, structural, enzymatic regulation, signal transduction, transcription, metabolism, and some proteins perform functions as yet unknown. Several salivary proteins in dogs with dental calculus differed from those found in the group without dental calculus. Among the abundant proteins detected in periodontal affected cases, can be highlighting calcium-sensing receptor and transforming growth factor beta. Enrichment analysis reveled the presence of Rho GTPases signaling pathway.

CONCLUSIONS

This research identified salivary proteins, that should be further investigated as potencial biomarkers of chronic periodontits with dental calculus formation in dogs.

Biochemical analysis of oral fluids for disease detection

The field of diagnostics using invasive blood testing represents the majority of diagnostic tests used as part of routine health monitoring. The relatively recent introduction of salivary diagnostics has lead to a major paradigm shift in diagnostic analyses. Additionally, in this era of big data, oral fluid testing has shown promising outcomes in a number of fields, particularly the areas of genomics, microbiomics, proteomics, metabolomics, and transcriptomics. Despite the analytical challenges involved in the interpretation of large datasets generated from biochemical studies involving bodily fluids, including saliva, many studies have identified novel oral biomarkers for diagnosing oral and systemic diseases. In this regard, oral biofluids, including saliva, gingival crevicular fluid (GCF), peri-implant crevicular fluid (PICF), dentinal tubular fluid (DTF), are now attracting increasing attention due to their important attributes, such as noninvasive sampling, easy handling, low cost, and more accurate diagnosis of oral diseases. Recently, the utilization of salivary diagnostics to evaluate systemic diseases and monitor general health has increased in popularity among clinicians. Saliva contains a wide range of protein, DNA and RNA biomarkers, which assist in the diagnosis of multiple diseases and conditions, including cancer, cardiovascular diseases (CVD), auto-immune and degenerative diseases, respiratory infections, oral diseases, and microbial (viral, bacterial and fungal) diseases. Moreover, due to its noninvasive nature and ease-of-adoption by children, it is now being used in mass screening programs, oral health-related studies and clinical trials in support of the development of therapeutic agents. The recent advent of highly sensitive technologies, such as next-generation sequencing, mass spectrometry, highly sensitives ELISAs, and homogeneous immunoassays, suggests that even small quantities of salivary biomarkers are able to be assayed accurately, providing opportunities for the development of many future diagnostic applications (including emerging technologies, such as point-of-care and rapid molecular technologies). The present article explores the omics and biochemical compositions of various oral biofluids with important value in diagnostics and monitoring.

Evaluation of salivary biomarkers of periodontitis among smokers and nonsmokers: A novel study

Background:

The analysis of salivary enzymes contributes to the clarification of pathogenesis and improvement in the diagnosis of periodontal disease. The present study aimed to examine the prospective association between smoking and periodontal disease progression and the effects of smoking on the following salivary biomarkers related to periodontitis: Alkaline phosphatase (ALP), acid phosphatase (ACP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), creatinine (CRE), blood urea nitrogen (BUN), urea (UA), free-hemoglobin (f-Hb), and neopterin.

Materials and Methods:

A total of 64 male patients aged 21–60 years were recruited and grouped as Group 1: 16 healthy nonsmokers, who had never smoked. Group 2: 16 smokers with gingivitis. Group 3: 16 smokers with moderate periodontitis. Group 4: 16 smokers with severe periodontitis. Stimulated saliva was collected for at least 5 min and clinical measurements; salivary biomarkers were assessed in automated analyzer.

Results:

Data showed significant correlation among salivary ACP, AST, LDH, CRE, BUN, UA, and f-Hb and neopterin levels showed higher in group 4 compared with other groups.

Conclusion:

This study indicated that smoking has several detrimental effects on periodontal tissues. A higher level of salivary biomarkers was seen in smokers with severe periodontitis. Hence, these biomarkers are helpful in future for the earlier detection of periodontal diseases progression and can also be used as potential salivary biomarkers for assessing smoking status and severity in chronic periodontitis.

Saliva as a diagnostic tool for dental caries, periodontal disease and cancer: is there a need for more biomarkers?

Introduction: A biomarker is a biological indicator of normal or pathogenic processes. Identification of biomarkers is useful for the prevention, diagnosis and prognosis of diseases as well as for monitoring the progression of pathological disorders. Several types of molecules present in biological fluids can act as biomarkers such as DNA, coding and non-coding RNA, lipids, metabolites, proteins and even microbes. In this context, saliva emerges as a useful diagnostic tool for the detection of biomarkers involved with oral and systemic diseases, since it reflects the pathophysiological conditions of the organism and allows early, rapid, practical and noninvasive detection of biomarkers.Areas covered: This review discusses the properties of saliva as a diagnostic tool and addresses the main identified biomarkers related to dental caries, periodontal disease, head and neck cancer and other types of cancer of considerable incidence among the world population.Expert commentary: Despite extensive efforts which have been directed toward the identification of one or a combination of biomarkers with good predictive values for the early detection of dental caries, periodontal disease and cancer, these biomarkers still need validation before chairside point-of-care devices can be widely used in the clinic.

Salivary Fingerprinting of Periodontal Disease by Infrared-ATR Spectroscopy

PURPOSE

Periodontal diseases, the most common chronic inflammatory diseases in humans, do not only affect tooth-supporting tissues but also other body parts by contributing to the development of life-threatening conditions. Since currently available diagnostic methods in periodontics lack the ability to identify patients at high risk for periodontal disease progression, development of innovative, non-invasive, rapid detection methods for diagnosing periodontal diseases is needed. This study aims to assess the potential of infrared attenuated total reflection (IR-ATR) spectroscopy to detect differences in composition of saliva supernatant in non-periodontitis individuals (control) and patients with generalized aggressive periodontitis (G-AgP).

EXPERIMENTAL DESIGN

IR-ATR is performed with a wavelength interval from 1230 to 1180 cm^-1 , analyzed with a simple subtraction in absorbance data.

RESULTS

Ten samples show in the analysis of variance of the two data sets a true difference (99.8%). A principal component analysis (PCA) is able to discriminate between G-AgP and control groups.

CONCLUSION AND CLINICAL RELEVANCE

This study demonstrates for the first time that IR-ATR spectroscopy is a promising tool for the analysis of saliva supernatant for the diagnosis of periodontitis, and potentially other periodontal conditions. IR-ATR spectroscopy holds the potential to be miniaturized and utilized as a non-invasive screening test.

Association of Periodontal Disease and Polycystic Ovarian Syndrome: A Systematic Review and Meta-analysis with Trial Sequential Analysis

Introduction:

Several articles have suggested a potential synergistic relationship between periodontal disease and systemic inflammatory diseases, such as Polycystic Ovarian Syndrome (PCOS) and diabetes mellitus. However, the associations between periodontal disease and PCOS population remain unclear in the literature.

Objective:

The primary aim of this review is to examine the associations between periodontal disease and PCOS with different scoring methods, namely clinical attachment loss, probing depth, gingival index, percentage of bleeding on probing and plaque index.

Methods:

MEDLINE, EMBASE and CENTRAL were systematically searched for observational studies and case-control studies from its inception until 2nd June, 2019. Case reports, case series, non-systematic reviews and trials published as abstracts were excluded.

Results:

Four articles (614 subjects) were included for analysis. Out of 614 subjects, 329 PCOS patients were compared to 285 healthy subjects. In comparison to healthy cohort, women with PCOS had a statistically significant increase in clinical attachment loss (MD: 0.34, 95% CI: 0.13-0.55, ρ=0.002), probing depth (MD: 0.35, 95%CI: 0.21-0.48, ρ<0.001), gingival index (MD: 0.70, 95% CI: 0.70-1.11, ρ<0.001) and percentage of bleeding on probing (MD: 34.41, 95% CI: 20.23-48.59, ρ<0.001). No difference was demonstrated in plaque index (MD: 0.42, 95% CI: -0.29-1.12, ρ=0.24) for both PCOS and healthy cohort.

Conclusion:

PCOS is significantly associated with a higher severity of the periodontal disease. This association should be emphasized during the management of PCOS patients, by including referral to dentists or periodontists for regular mechanical debridement of plaque and periodontal maintenance.

Correlations between Interleukin-33 and -1α Levels in Gingival Crevicular Fluid and Plasma in Patients with Chronic or Aggressive Periodontitis and Disease-free Subjects

Interleukin (IL)-33 is a dual-function protein that may play important roles as both a cytokine and intracellular nuclear factor. It may also function similarly to prototypical alarmin IL-1α, as an endogenous danger signal to alert innate immune system cells to tissue damage during trauma or infection, as it can be released in the extracellular space after endothelial cell damage or mechanical injury. The aim of this study was to determine possible correlations between concentrations of IL-33 and IL-1α in gingival crevicular fluid (GCF) and plasma obtained from healthy patients, those with chronic periodontitis (CP), and those with generalized aggressive periodontitis (GAP) patients. Forty-five patients with an age range of 20-60 years were enrolled and divided into 3 groups: Group H, 30 samples (15 GCF and 15 plasma) from 15 patients with healthy periodontium; Group CP, 30 samples from 15 patients with CP; and Group GAP, 30 samples from 15 patients with GAP. The clinical periodontal parameters investigated in all groups comprised the gingival index score, probing pocket depth, and clinical attachment level. The GCF and plasma levels of IL-33 and IL-1α were quantitated using enzyme linked immunosorbent assay. The mean IL-33 concentrations in GCF and plasma were highest in Group GAP, followed by Group CP, with the lowest in Group H; the difference among them was statistically significant (p<0.05). Concentration of IL-1α followed the same trend as that of IL-33 in GCF, but was lower than detection levels in plasma. The GCF and plasma concentrations of IL-33 correlated with IL-1α concentrations in GCF. Concentrations of IL-33 and IL-1α in GCF varied significantly between healthy patients and those with disease, allowing healthy patients to be distinguished from those with GAP or CP. The results of this study suggest that IL-33 offers a potential inflammatory marker of periodontal disease, similar to IL-1α.

Accuracy of single molecular biomarkers in saliva for the diagnosis of periodontitis: A systematic review and meta-analysis

AIM

To analyse, using a meta-analytical approach, the diagnostic accuracy of single molecular biomarkers in saliva for the detection of periodontitis in systemically healthy subjects.

MATERIALS AND METHODS

Articles on molecular biomarkers in saliva providing a binary contingency table (or sensitivity and specificity values and group sample sizes) in individuals with clinically diagnosed periodontitis were considered eligible. Searches for candidate articles were conducted in six electronic databases. The methodological quality was assessed through the tool Quality Assessment of Diagnostic Studies. Meta-analyses were performed using the Hierarchical Summary Receiver Operating Characteristic model.

RESULTS

Meta-analysis was possible for 5 of the 32 biomarkers studied. The highest values of sensitivity for the diagnosis of periodontitis were obtained for IL1beta (78.7%), followed by MMP8 (72.5%), IL6 and haemoglobin (72.0% for both molecules); the lowest sensitivity value was for MMP9 (70.3%). In terms of specificity estimates, MMP9 had the best result (81.5%), followed by IL1beta (78.0%) and haemoglobin (75.2%); MMP8 had the lowest specificity (70.5%).

CONCLUSIONS

MMP8, MMP9, IL1beta, IL6 and Hb were salivary biomarkers with good capability to detect periodontitis in systemically healthy subjects. MMP8 and IL1beta are the most researched biomarkers in the field, both showing clinically fair effectiveness for the diagnosis of periodontitis.

Periodontal condition, changes in salivary biochemical parameters, and oral health-related quality of life in patients with anorexia and bulimia nervosa

BACKGROUND

Anorexia and bulimia nervosa can have significant effects on oral health. Assessment of enzyme concentrations in saliva can be useful for obtaining information on molecular biomarkers for the prevention, monitoring, and diagnosis of oral diseases. This study investigated the periodontal condition, changes in salivary biochemical parameters, and oral health-related quality of life (OHRQoL) in patients with anorexia and bulimia nervosa.

METHODS

The study comprised 60 women patients who attended a Brazilian medical school. Participants were divided into two groups: patients with anorexia and bulimia nervosa (ABN; n = 30) and control patients (CN; n = 30). Oral clinical examinations were carried out to evaluate the periodontal condition by Community Periodontal Index, and interviews using the Oral Health Impact Profile (OHIP-14) were conducted to assess OHRQoL. Saliva samples were collected for the evaluation of salivary concentrations of total protein, alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), and thiobarbituric acid reactive substance (TBARS), and salivary flow rate.

RESULTS

Periodontal condition in the ABN group was significantly worse than that in the CN group. The ABN group showed significantly higher salivary concentrations of total protein, AST, ALT, and LDH than the CN group. There was no significant difference in the salivary concentrations of TBARS among the groups. The OHIP-14 score was higher in the ABN group than in the CN group.

CONCLUSION

Anorexia and bulimia nervosa are associated with poor periodontal condition, elevated salivary concentrations of total protein, AST, ALT, and LDH, decreased salivary flow rate and a significant adverse impact on OHRQoL.

Fretibacterium sp. human oral taxon 360 is a novel biomarker for periodontitis screening in the Japanese population

Background

Periodontitis is a common inflammatory disease, leading to bone destruction and tooth loss. Screening for periodontitis is important in preventing the progress of this disease. Various types of bacteria have been examined as potential screening targets, but only culturable pathogenic bacteria have been considered candidates. Recently, the various uncultivable bacteria have been identified in microbiome studies, but the value of these bacteria in periodontitis screening remains unknown.

Objectives

The aim of this study was to evaluate the diagnostic use of uncultivable bacteria Fretibacterium sp. HOT 360 and TM7 sp. HOT 356 for periodontitis screening in the Japanese population.

Material and methods

Stimulated saliva samples were collected from 217 participants (periodontitis group, n = 157; healthy group, n = 60). The two uncultivable bacterial species selected were: Fretibacterium sp. human oral taxon 360 (Fretibacterium sp. HOT 360) and TM7 sp. human oral taxon 356 (TM7 sp. HOT 356). The levels of these two bacterial species were compared with those of Porphyromonas gingivalis (P. gingivalis), a keystone pathogen in periodontitis. These three species of bacteria were then quantified using qualitative real-time polymerase chain reaction (qPCR) with specific primers and Taqman probes. Statistical analysis was performed by SPSS 20.0 software. P value was statistically significant at .05.

Results

The populations of uncultivable bacterial species TM7 sp. HOT 356 and Fretibacterium sp. HOT 360 were significantly higher in periodontitis group than in healthy group. Only Fretibacterium sp. HOT 360 showed a significantly positive correlation with such periodontal parameters as probing pocket depth (PPD) and bleeding on probing (BOP).

Conclusion

These findings indicate that uncultivable bacteria Fretibacterium sp. HOT 360 can be used as a saliva-based diagnostic bacterial biomarker for periodontitis screening.

Cytokine Thresholds in Gingival Crevicular Fluid with Potential Diagnosis of Chronic Periodontitis Differentiating by Smoking Status

The objective of the present study was to determine cytokine thresholds derived from predictive models for the diagnosis of chronic periodontitis, differentiating by smoking status. Seventy-five periodontally healthy controls and 75 subjects affected by chronic periodontitis were recruited. Sixteen mediators were measured in gingival crevicular fluid (GCF) using multiplexed bead immunoassays. The models were obtained using binary logistic regression, distinguishing between non-smokers and smokers. The area under the curve (AUC) and numerous classification measures were obtained. Model curves were constructed graphically and the cytokine thresholds calculated for the values of maximum accuracy (ACC). There were three cytokine-based models and three cytokine ratio-based models, which presented with a bias-corrected AUC > 0.91 and > 0.83, respectively. These models were (cytokine thresholds in pg/ml for the median ACC using bootstrapping for smokers and non-smokers): IL1alpha (46099 and 65644); IL1beta (4732 and 5827); IL17A (11.03 and 17.13); IL1alpha/IL2 (4210 and 7118); IL1beta/IL2 (260 and 628); and IL17A/IL2 (0.810 and 1.919). IL1alpha, IL1beta and IL17A, and their ratios with IL2, are excellent diagnostic biomarkers in GCF for distinguishing periodontitis patients from periodontally healthy individuals. Cytokine thresholds in GCF with diagnostic potential are defined, showing that smokers have lower threshold values than non-smokers.

Deep sequencing salivary proteins for periodontitis using proteomics

OBJECTIVES

Saliva is a bodily fluid transuded from gingival crevice fluid and blood and contains many proteins. Proteins in saliva have been studied as markers for periodontal diseases. Mass spectrometric analysis is applied to investigate biomarker proteins that are related to periodontitis.

MATERIAL AND METHODS

Saliva samples were collected from 207 participants including 36 pairs matched for age, sex, and smoking who joined Yangpyeong health cohort. Periodontitis was defined by 2005 5th European guideline. Shotgun proteomics was applied to detect proteins from saliva samples. Principal component analysis and Ingenuity Pathway Analysis for canonical pathway and protein pathway were applied. Protein-protein interaction was also applied. Enzyme-linked immunosorbent assay (ELISA) was used to verify the candidate protein markers among another matched participants (n = 80).

RESULTS

Shotgun proteomics indicated that salivary S100A8 and S100A9 were candidate biomarkers for periodontitis. ELISA confirmed that both salivary S100A8 and S100A9 were higher in those with periodontitis compared to those without periodontitis (paired-t test, p < 0.05).

CONCLUSION

Our proteomics data showed that S100A8 and S100A9 in saliva could be candidate biomarkers for periodontitis. The rapid-test-kit using salivary S100A8 and S100A9 will be a practical tool for reducing the risk of periodontitis and promotion of periodontal health.

CLINICAL RELEVANCE

A rapid-test-kit using salivary biomarkers, S100A8 and S100A9, could be utilized by clinicians and individuals for screening periodontitis, which might reduce the morbidity of periodontitis and promote periodontal health.

Comparative proteomic study of dog and human saliva

Saliva contains many proteins that have an important role in biological process of the oral cavity and is closely associated with many diseases. Although the dog is a common companion animal, the composition of salivary proteome and its relationship with that of human are unclear. In this study, shotgun proteomics was used to compare the salivary proteomes of 7 Thai village dogs and 7 human subjects. Salivary proteomes revealed 2,532 differentially expressed proteins in dogs and humans, representing various functions including cellular component organization or biogenesis, cellular process, localization, biological regulation, response to stimulus, developmental process, multicellular organismal process, metabolic process, immune system process, apoptosis and biological adhesion. The oral proteomes of dogs and humans were appreciably different. Proteins related to apoptosis processes and biological adhesion were predominated in dog saliva. Drug-target network predictions by STITCH Version 5.0 showed that dog salivary proteins were found to have potential roles in tumorigenesis, anti-inflammation and antimicrobial processes. In addition, proteins related to regeneration and healing processes such as fibroblast growth factor and epidermal growth factor were also up-regulated in dogs. These findings provide new information on dog saliva composition and will be beneficial for the study of dog saliva in diseased and health conditions in the future.

Salivary arginase activity after mechanical-chemical therapy

Abstract Introduction Salivary components can be used as biomarkers for diagnosing and monitoring oral diseases. There is evidence that one potential biomarker, arginase, is associated with the inflammatory processes of periodontal disease, and its enzymatic activity is reduced according to the improvement in the clinical parameters after treatment. Objective The present study aimed to evaluate the salivary arginase activity in gingivitis and periodontitis patients treated with full-mouth mechanical procedures combined with the adjunctive use of essential oils or chlorhexidine mouthwash, respectively. Material and method Twenty-six gingivitis and 16 periodontitis patients received complete periodontal examinations at the baseline and 3 months after therapy, in which the periodontal probing depth, clinical attachment loss, plaque index, and gingival index measurements were taken. At these same appointments, the salivary total protein level and salivary arginase activity were also established via spectrophotometry. Result There were improvements in all of the clinical parameters (p < 0.05) evaluated from the baseline to 3 months in both groups. In addition, the salivary arginase activity and total protein levels were reduced after the gingivitis treatment. Conclusion Similar to the clinical results, both therapeutic protocols positively affected the salivary arginase activity; however, further studies are necessary to clarify its potential as a salivary biomarker for periodontal monitoring.

High-throughput proteomic analysis of candidate biomarker changes in gingival crevicular fluid after treatment of chronic periodontitis

BACKGROUND AND OBJECTIVE

Untargeted, high-throughput proteomics methodologies have great potential to aid in identifying biomarkers for the diagnosis of periodontal disease. The application of such methods to the discovery of candidate biomarkers for the resolution of periodontal inflammation after periodontal therapy has been investigated.

MATERIAL AND METHODS

Gingival crevicular fluid samples were collected from 10 patients diagnosed with chronic periodontitis at baseline and 1, 5, 9 and 13 weeks after completion of mechanical periodontal treatment. Clinical indices of periodontal disease, including probing depth, recession, clinical attachment level and bleeding on probing, were recorded at baseline and 13 weeks. Samples were analyzed using an online liquid chromatography-nanoelectrospray-hybrid ion trap-Orbitrap mass spectrometer. Spectra were processed with the PILOT_PROTEIN proteomics software suite.

RESULTS

Clinical parameters were significantly improved 13 weeks after treatment (Wilcoxon signed ranks test, P < .05). From the substantial number of identified proteins, a small subset was extracted by filter methods that included temporal pattern matching, logistic function fitting and mixed-integer linear optimization. This subset includes azurocidin, lysozyme C and myosin-9 as candidate biomarkers prominent at baseline and alpha-smooth muscle actin as prominent 13 weeks after treatment. Cross-validation studies yielded average predictive accuracy and area under the curve of 0.900 and 0.930, respectively.

CONCLUSION

High-throughput proteomic analysis can contribute to identifying endpoints of periodontal therapy. These candidate biomarkers should be evaluated for clinical efficacy.

Correlative analysis of plasma and urine neopterin levels in the pre- and post-menopausal women with periodontitis, following nonsurgical periodontal therapy

Context:

Periodontitis is an inflammatory condition which is distinguished by the devastation of the supported tooth structures. In such inflammatory conditions, some biomarkers such as neopterin will be secreted and elevated in the body fluids, which can be used as a diagnostic marker for the present and future disease activity.

Aims:

Assessment of the neopterin as a biomarker in inflammatory conditions such as menopause and periodontitis.

Settings and Design:

A cross-sectional interventional study.

Materials and Methods:

Sixty female individuals with a mean age of 40–60 years with chronic periodontitis were included in this study. All were categorized into two groups of thirty each, depending on their menstrual history: Group I – thirty premenopausal women and Group II – thirty postmenopausal women. Urine and plasma were collected from both groups to estimate neopterin levels. ELISA kit was used to assess the neopterin levels at baseline and after 3 months of nonsurgical periodontal therapy (NSPT).

Statistical Analysis Used:

IBM SPSS version 21 software.

Results:

A significant depreciation in the mean values of all the parameters from baseline to 3 months (P < 0.001), in the intragroup analysis, was observed. Plasma (0.006) and urine (0.004) reduction was seen.

Conclusions:

In both the groups, in 3 months after NSPT, decreased neopterin levels were found, suggesting that the NSPT is the definitive therapy. Further, suggesting that, neopterin levels in the plasma and urine can be used as an index to identify the periodontal inflammation and destruction.

Matrix metalloproteinase-8 analysis in patients with periodontal disease with prediabetes or type 2 diabetes mellitus: A systematic review

OBJECTIVES

The objective of this systematic review was to evaluate information on the levels of MMP-8 in patients diagnosed with prediabetes or type 2 diabetes mellitus with periodontal disease, analyzing its validity as a possible biomarker for the diagnosis and progression of periodontal disease (PD).

METHODS

A systematic search of the following databases was performed: PubMed/Medline, CENTRAL (The Cochrane Library), EMBASE and Web of Science. Studies involving the evaluation of MMP-8 in patients with prediabetes or patients presenting type 2 diabetes mellitus concomitantly with PD were selected. The evaluation of the methodological quality of the selected studies was based on the methodological bias risk analysis (QUADAS-2).

RESULTS

Eight of the initially identified 2683 articles were selected. In all the selected studies, evaluator calibration and the use of clear methods for patient diagnosis with periodontal disease were present. Studies have demonstrated significantly higher MMP-8 concentrations in PD patients compared to controls, as well as in patients presenting more advanced stages of PD. However, controversies regarding MMP-8 levels in prediabetes/diabetes type 2 patients with PD.

CONCLUSIONS

Higher MMP-8 levels in patients with PD compared to controls imply the potential use of MMP-8 in the diagnosis of PD. The influence of patient glycemic state, as well as medications these patients make use of, are factors that possibly contribute to the modulation of MMP-8 concentrations in patients with diabetes and should be analyzed, aiming at a better understanding of the relationship between glycemic state and MMP-8 levels in patients with PD.

Cytokine-based Predictive Models to Estimate the Probability of Chronic Periodontitis: Development of Diagnostic Nomograms

Although a distinct cytokine profile has been described in the gingival crevicular fluid (GCF) of patients with chronic periodontitis, there is no evidence of GCF cytokine-based predictive models being used to diagnose the disease. Our objectives were: to obtain GCF cytokine-based predictive models; and develop nomograms derived from them. A sample of 150 participants was recruited: 75 periodontally healthy controls and 75 subjects affected by chronic periodontitis. Sixteen mediators were measured in GCF using the Luminex 100™ instrument: GMCSF, IFNgamma, IL1alpha, IL1beta, IL2, IL3, IL4, IL5, IL6, IL10, IL12p40, IL12p70, IL13, IL17A, IL17F and TNFalpha. Cytokine-based models were obtained using multivariate binary logistic regression. Models were selected for their ability to predict chronic periodontitis, considering the different role of the cytokines involved in the inflammatory process. The outstanding predictive accuracy of the resulting smoking-adjusted models showed that IL1alpha, IL1beta and IL17A in GCF are very good biomarkers for distinguishing patients with chronic periodontitis from periodontally healthy individuals. The predictive ability of these pro-inflammatory cytokines was increased by incorporating IFN gamma and IL10. The nomograms revealed the amount of periodontitis-associated imbalances between these cytokines with pro-inflammatory and anti-inflammatory effects in terms of a particular probability of having chronic periodontitis.

Quantification by qPCR of Pathobionts in Chronic Periodontitis: Development of Predictive Models of Disease Severity at Site-Specific Level

Currently, there is little evidence available on the development of predictive models for the diagnosis or prognosis of chronic periodontitis based on the qPCR quantification of subgingival pathobionts. Our objectives were to: (1) analyze and internally validate pathobiont-based models that could be used to distinguish different periodontal conditions at site-specific level within the same patient with chronic periodontitis; (2) develop nomograms derived from predictive models. Subgingival plaque samples were obtained from control and periodontal sites (probing pocket depth and clinical attachment loss <4 mm and >4 mm, respectively) from 40 patients with moderate-severe generalized chronic periodontitis. The samples were analyzed by qPCR using TaqMan probes and specific primers to determine the concentrations of Actinobacillus actinomycetemcomitans (Aa), Fusobacterium nucleatum (Fn), Parvimonas micra (Pm), Porphyromonas gingivalis (Pg), Prevotella intermedia (Pi), Tannerella forsythia (Tf), and Treponema denticola (Td). The pathobiont-based models were obtained using multivariate binary logistic regression. The best models were selected according to specified criteria. The discrimination was assessed using receiver operating characteristic curves and numerous classification measures were thus obtained. The nomograms were built based on the best predictive models. Eight bacterial cluster-based models showed an area under the curve (AUC) ≥0.760 and a sensitivity and specificity ≥75.0%. The PiTfFn cluster showed an AUC of 0.773 (sensitivity and specificity = 75.0%). When Pm and AaPm were incorporated in the TdPiTfFn cluster, we detected the two best predictive models with an AUC of 0.788 and 0.789, respectively (sensitivity and specificity = 77.5%). The TdPiTfAa cluster had an AUC of 0.785 (sensitivity and specificity = 75.0%). When Pm was incorporated in this cluster, a new predictive model appeared with better AUC and specificity values (0.787 and 80.0%, respectively). Distinct clusters formed by species with different etiopathogenic role (belonging to different Socransky’s complexes) had a good predictive accuracy for distinguishing a site with periodontal destruction in a periodontal patient. The predictive clusters with the lowest number of bacteria were PiTfFn and TdPiTfAa, while TdPiTfAaFnPm had the highest number. In all the developed nomograms, high concentrations of these clusters were associated with an increased probability of having a periodontal site in a patient with chronic periodontitis.

Comparative Evaluation of Salivary Neopterin Levels and Its Effects to Periodontal Therapy in Pre- and Post-Menopausal Women

OBJECTIVES

Neopterin is a valuable diagnostic biomarker, which is elevated in inflammatory conditions like periodontitis, that is characterized by destruction of the supporting structures of the teeth. Among the biomarkers, neopterin occurs in body fluids, and acts as a diagnostic marker for present and future disease activity.

METHODS

Thirty female subjects with chronic periodontitis, mean age 50 years (40-60 years) were included in this study. Depending upon their menstrual history, subjects were categorized into two groups of fifteen each. Group I 15 pre-menopausal women, and Group II 15 post-menopausal women. Saliva was collected, and neopterin levels were assessed by enzyme-linked immunosorbent assay in both the groups, at base line and after three months of nonsurgical periodontal therapy (NSPT). Periodontal parameters like pocket probing depth (PD) and Russell's periodontal disease index (PDI) were assessed before treatment as well as after three months of scaling and root planning.

RESULTS

Intra group analysis showed significant markdown in the mean values of all the parameters from baseline to three months (P < 0.001), for all patients. The intergroup comparison, from baseline to 3 months also showed no significant change in PD and PDI values, but there was a statistically significant difference in the salivary neopterin levels (P = 0.04).

CONCLUSIONS

Neopterin levels were found to be reduced in three months after NSPT in both the groups, suggesting that the NSPT is the gold standard therapy, and also that neopterin levels in saliva can be used as an indicator to identify periodontal inflammation and destruction.

Inter-personal diversity and temporal dynamics of dental, tongue, and salivary microbiota in the healthy oral cavity

Oral microbes form a complex and dynamic biofilm community, which is subjected to daily host and environmental challenges. Dysbiosis of the oral biofilm is correlated with local and distal infections and postulating a baseline for the healthy core oral microbiota provides an opportunity to examine such shifts during the onset and recurrence of disease. Here we quantified the daily, weekly, and monthly variability of the oral microbiome by sequencing the largest oral microbiota time-series to date, covering multiple oral sites in ten healthy individuals. Temporal dynamics of salivary, dental, and tongue consortia were examined by high-throughput 16S rRNA gene sequencing over 90 days, with four individuals sampled additionally 1 year later. Distinct communities were observed between dental, tongue, and salivary samples, with high levels of similarity observed between the tongue and salivary communities. Twenty-six core OTUs that classified within Streptococcus, Fusobacterium, Haemophilus, Neisseria, Prevotella, and Rothia genera were present in ≥95% samples and accounted for ~65% of the total sequence data. Phylogenetic diversity varied from person to person, but remained relatively stable within individuals over time compared to inter-individual variation. In contrast, the composition of rare microorganisms was highly variable over time, within most individuals. Using machine learning, an individual's oral microbial assemblage could be correctly assigned to them with 88–97% accuracy, depending on the sample site; 83% of samples taken a year after initial sampling could be confidently traced back to the source subject.

A study of bacteria in the mouth reveals insights into their diversity, stability, and variability among people and over time. By tracking daily, weekly, and monthly fluctuations of plaque and salivary bacteria in ten healthy volunteers, Dilani Senadheera at the Faculty of Dentistry, University of Toronto and co-researchers in Canada reveal significant differences in the “microbiome” present in dental, tongue and saliva samples over time. They found considerable variation in these communities between individuals, sufficient to identify a person with “bacterial fingerprints” using plaque or saliva even after 1 year. The researchers reveal a “core community” that spans different persons, oral sites, and time, suggesting some level of stability. This study is useful to understand the diversity and community drifts in different oral sites over time, which is important when plaque and saliva are used for bacterial analysis in diagnostic, risk-prediction, and forensic applications.

Assessment of periodontal health status in postmenopausal women visiting dental hospital from in and around Meerut city: Cross-sectional observational study

Background:

Puberty, menses, pregnancy, and menopause are the different phases of a woman's life which have a varied influence on oral health. During the menopause, women go through biological and endocrine changes, particularly in their sex steroid hormone production which affects their health. Because the oral mucosa contains estrogen receptors, variations in hormone levels can be seen directly in the oral cavity leading to a few oral conditions and diseases seen more frequently during postmenopausal years.

Objective:

The objective of this study is to assess periodontal health status in postmenopausal women in and around Meerut city.

Materials and Methods:

The study sample comprised ninety postmenopausal women. History of menopause was recorded, and the dental examinations were done by measuring the following parameters of periodontal health: plaque index (PI), gingival index (GI), bleeding on probing (BOP), pocket probing depth, and Russell's periodontal index. The collected data were subjected to statistical analyses.

Results and Conclusion:

In the study group, mean age was 55 years, mean missing teeth were 10.3, mean duration of menopause was 9.23. Eleven percent females were completely edentulous, and 5 females had never brushed. Mean PI-s was 1.99, mean GI-s was 1.74, mean BOP was 52.85, and mean Russell's periodontal index was 4.34. Eleven patients were at the initial stages of destructive periodontal disease, 34 had established destructive periodontal disease while thirty patients had the terminal periodontal disease. These findings suggest that females after menopause are at a risk of developing destructive periodontal disease if proper oral hygiene practices are not followed.

Rapid assessment of salivary MMP-8 and periodontal disease using lateral flow immunoassay

OBJECTIVE

The objective of this study was to determine the efficacy of a novel point-of-care immunoflow device (POCID) for detecting matrix metalloproteinase (MMP)-8 concentrations in oral fluids in comparison with a gold standard laboratory-based immunoassay.

METHODS

Oral rinse fluid and whole expectorated saliva samples were collected from 41 participants clinically classified as periodontally healthy or diseased. Samples were analyzed for MMP-8 by Luminex immunoassay and POCID. Photographed POCID results were assessed by optical scan and visually by two examiners. Data were analyzed by Pearson's correlation and receiver-operating characteristics.

RESULTS

MMP-8 was readily detected by the POCID, and concentrations correlated well with Luminex for both saliva and rinse fluids (r = 0.57-0.93). Thresholds that distinguished periodontitis from health were delineated from both the optical scans and visual reads of the POCID (sensitivity: 0.7-0.9, specificity: 0.5-0.7; P < 0.05).

CONCLUSIONS

Performance of this POCID for detecting MMP-8 in oral rinse fluid or saliva was excellent. These findings help demonstrate the utility of salivary biomarkers for distinguishing periodontal disease from health using a rapid point-of-care approach.