Salivary Biomarkers in Periodontitis: A Scoping Review

Periodontal disease is a prevalent and potentially impactful oral health condition, ranging from gingivitis to severe periodontitis. Early detection and precise management are crucial in modern dentistry due to its prevalence and potential systemic health implications. Traditional clinical assessments and radiographic imaging have been the primary diagnostic tools. However, recent advances in oral diagnostics have introduced the concept of non-invasive, easily accessible salivary biomarkers. This review explores the evolving landscape of salivary biomarkers associated with periodontal disease, offering a comprehensive analysis of recent studies. It delves into the key findings, clinical significance, and potential impact of these biomarkers in revolutionizing periodontal disease diagnostics and treatment monitoring. The study emphasizes their diagnostic and prognostic capabilities, including their ability to assess disease severity, correlate with clinical parameters, aid in early detection, and enhance personalized treatment planning. As the field of oral diagnostics continues to advance, understanding the role of salivary biomarkers in periodontal disease management holds the promise of improving precision and effectiveness in oral healthcare. This review underscores the potential for salivary biomarkers to become integral components of routine periodontal care, offering a minimally invasive and patient-centered approach to oral health management.

Salivary histone deacetylase in periodontal disease: A cross-sectional pilot study

OBJECTIVE

The objective of the study was to profile the expression level of histone deacetylase enzymes (HDACs) in human saliva in periodontal health, gingivitis and periodontitis.

BACKGROUND

HDACs are epigenetic modulators and a group of enzymes that catalyse the removal of acetyl functional groups from the lysine residues of both histone and nonhistone proteins. HDACs have been detected in gingival tissues and may provide valuable insight into the periodontal inflammatory response. However, no studies have investigated the expression of HDACs in saliva from periodontitis-affected individuals and their capacity for periodontal diagnostics and screening.

MATERIALS AND METHODS

Whole unstimulated saliva was collected from 53 participants (17 healthy, 14 gingivitis and 22 stages III/IV periodontitis). The expression of 11 HDACs in saliva samples was determined using RT-qPCR and diagnostic power was calculated using the receiver operating characteristic (ROC) curves and area under the ROC Curve (AUC).

RESULTS

Relative to health, the expression of HDAC4, 8 and 10 was downregulated in gingivitis, and the expression of HDAC4, 6, 8 and 9 was downregulated in periodontitis. Increased HDAC1 and decreased HDAC9 expression were observed in periodontitis compared to gingivitis. Higher HDAC1 and lower HDAC6 and 9 expression was observed in periodontitis compared to non-periodontitis (combining health and gingivitis). Expression of HDAC3, 4, 8, 9 and 10 was significantly decreased in periodontal disease (combining gingivitis and periodontitis) compared to health. HDAC4 and 8 exhibited an excellent diagnostic capacity for distinguishing gingivitis and periodontal disease from health (AUC 0.79-0.86). HDAC9 showed an acceptable power in discriminating periodontitis from health, gingivitis and non-periodontitis (AUC 0.76-0.80). Salivary HDAC enzyme activity showed no significant difference among the groups.

CONCLUSION

This pilot study has demonstrated the differential expression of HDACs in human saliva for the first time and identified HDAC4, 8 and 9 as potential biomarkers in periodontal diagnosis.

Salivary bactericidal/permeability-increasing protein: A novel inflammatory marker associated with periodontitis

OBJECTIVES

The present case-control study aims to investigate the salivary levels of bactericidal/permeability-increasing protein (BPI) and interleukin-1beta (IL-1ß) in systemically healthy individuals with periodontitis and periodontally healthy for the evaluation of BPI's relation with periodontal inflammation and clinical diagnosis of periodontitis.

MATERIALS AND METHODS

A total of 100 participants were enrolled in this study and divided into periodontitis (P group) (n = 50) and periodontally healthy (H group) (n = 50) groups based on their full-mouth periodontal examination results including plaque index, probing pocket depth, gingival index, bleeding on probing, and clinical attachment level. Unstimulated whole saliva was collected. Salivary BPI and IL-1β levels were determined using an enzyme-linked immunosorbent assay. Receiver operating characteristic (ROC) curves were created to determine the diagnostic value of BPI.

RESULTS

The levels of BPI and IL-1ß in saliva were significantly higher in the P group than in the H group (p<0.001). Moreover, salivary BPI and IL-1ß levels correlated significantly with all clinical periodontal parameters (all p<0.001). Interestingly, there was a strong positive correlation between salivary levels of BPI and IL-1ß (r=0.544, p<0.001). In addition, the results of the ROC curve analysis showed that BPI had a high diagnostic potential to distinguish periodontitis from healthy controls with an area under the curve value of 0.94% (p<0.000).

CONCLUSION

The significantly higher salivary levels of BPI in periodontitis patients together with strong positive correlations between all periodontal parameters and salivary IL-1ß levels suggest that BPI may be involved in the inflammatory process of periodontal disease.

CLINICAL RELEVANCE

The present study for the first time report that salivary BPI levels may serve as a potential biomarker of inflammation in periodontal disease.

TRIAL REGISTRATION NUMBER

Thai Clinical Trials.gov (TCTR20211222008) (22 December 2021).

The role of Th17 cells: explanation of relationship between periodontitis and COPD?

Periodontitis and chronic obstructive pulmonary disease (COPD) are chronic inflammatory diseases with common risk factors, such as long-term smoking, age, and social deprivation. Many observational studies have shown that periodontitis and COPD are correlated. Moreover, they share a common pathophysiological process involving local accumulation of inflammatory cells and cytokines and damage of soft tissues. The T helper 17 (Th17) cells and the related cytokines, interleukin (IL)-17, IL-22, IL-1β, IL-6, IL-23, and transforming growth factor (TGF)-β, play a crucial regulatory role during the pathophysiological process. This paper reviewed the essential roles of Th17 lineage in the occurrence of periodontitis and COPD. The gaps in the study of their common pathological mechanism were also evaluated to explore future research directions. Therefore, this review can provide study direction for the association between periodontitis and COPD and new ideas for the clinical diagnosis and treatment of the two diseases.

Increasing risk factors of non-alcoholic fatty liver disease, a look into chronic periodontitis and insulin resistance

Non-alcoholic fatty liver disease (NAFLD) is marked by the excessive intrusion of triglycerides into hepatocytes without any role of alcohol consumption. Various risk factors have been attributed to this disease pathogenesis which involves metabolic disorders, immune response, and even an intricate relationship between the two. The role of insulin resistance (IR) in NAFLD has long been known; however, the molecular basis of disease progression under this metabolic backdrop is still being investigated. Similarly, the periodontitis-mediated immune response is another major factor involved in NAFLD manifestation which has generated huge interest. The prevalence of pathogenic bacteria elicits a strong immune response which according to studies shows a strong correlation with NAFLD state. Such pre-existing conditions have a strong probability of explaining the disease onset. Additionally, increasing reports of inflammatory response and its links to insulin resistance have further increased the scope of understanding NAFLD. Through this review, we aim to elaborate on these factors explaining their role in the disease progression.

Comparison of three qPCR-based commercial tests for detection of periodontal pathogens

In periodontal practice microbial results of periodontal test kits for identification of key pathogens are an aid in the treatment planning. Information on the performance of commercially available test kits is therefore essential for the clinician. In this retrospective analysis three commercially available qPCR kits for detection and quantification of selected periodontal bacterial species were compared, using 100 clinical samples from patients with untreated periodontitis. The analysis involved two separate comparisons in which kit A (LabOral Diagnostics, The Netherlands) was compared with kit B (Advanced Dental Diagnostics, The Netherlands), and with kit C (OralDent diagnostics, The Netherlands). Analytic procedures for detection and quantification of selected periodontal bacterial species were carried out according to the instructions of the laboratories. Kit A detected target species more often, and absolute numbers of bacterial cells were higher than with kit B. A high degree of similarity was found between the test outcomes by kit A and kit C. All three kits performed satisfactory but small and significant differences exist between kits.

Development of a periodontitis risk assessment model for primary care providers in an interdisciplinary setting

BACKGROUND

Periodontitis (PD), a form of gum disease, is a major public health concern as it is globally prevalent and harms both individual quality of life and economic productivity. Global cost in lost productivity is estimated at US$54 billion annually. Moreover, current PD assessment applies only after the damage has already occurred.

OBJECTIVE

This study proposes and tests a new PD risk assessment model applicable at point-of-care, using supervised machine learning methods.

METHODS

We compare the performance of five algorithms using retrospective clinical data: Naïve Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), Artificial Neural Network (ANN), and Decision Tree (DT).

RESULTS

DT and ANN demonstrated higher accuracy in classifying the patients with high or low PD risk as compared to NB, LR and SVM. The resultant model with DT showed a sensitivity of 87.08% (95% CI 84.12% to 89.76%) and specificity of 93.5% (95% CI 91% to 95.49%).

CONCLUSIONS

A predictive model with high sensitivity and specificity to stratify individuals into low and high PD risk tiers was developed. Validation in other populations will inform translational value of this approach and its potential applicability as clinical decision support tool.

Salivary biomarkers for discriminating periodontitis in the presence of diabetes

AIM

Salivary biomarkers can help in assessment of periodontitis; however, concentrations may be altered in the presence of diabetes. Hence, the ability of salivary biomarkers to discriminate periodontally healthy type II diabetics (T2DM) from T2DM who have periodontitis was examined.

METHODS

Ninety-two participants (29 with T2DM with chronic periodontitis, DWP; 32 T2DM without chronic periodontitis, DWoP; and 31 Not Periodontitis, NP) provided saliva and clinical parameters of periodontal health were recorded. Salivary concentrations of interleukin (IL)-1β, IL-6, matrix metalloproteinase-8 (MMP-8), macrophage inflammatory protein-1α (MIP-1α), adiponectin and resistin were measured by immunoassay.

RESULTS

Salivary analyte concentrations for IL-1β, MMP-8 and resistin correlated with clinical parameters of periodontitis, with MMP-8 demonstrating the strongest positive correlation with PD ≥5 mm (p < 0.0001). Periodontal health was reflected in salivary analyte concentrations by group, with concentrations of IL-1β and MMP-8 showing significant associations with periodontitis (p ≤ 0.04) that increased in concentration from health to DWoP to DWP. Odds ratio (OR) analyses showed that MMP-8 discriminated periodontitis from NP (OR of 8.12; 95% CI: 1.01-65.33; p = 0.03) and in the presence of T2DM (DWP vs DWoP, OR = 5.09; 95% CI: 1.24-20.92; p = 0.03).

CONCLUSION

Salivary MMP-8 and IL-1β discriminate periodontitis in T2DM.

A review of T helper 17 cell-related cytokines in serum and saliva in periodontitis

Periodontitis is a chronic inflammatory disease with a complex underlying immunopathology. Cytokines, as molecular mediators of inflammation, play a role in all stages of disease progression. T helper 17 (Th17) cells are thought to play a role in periodontitis. Th17 cell development and maintenance requires a pro-inflammatory cytokine milieu, with many of the cytokines implicated in the pathogenesis of periodontitis. Serum and saliva are easily accessible biofluids which can represent the systemic and local environment to promote the development of Th17 cells. Here we review human clinical studies that investigate IL-1β, IL-4, IL-6, IL-10, IL-17A, IL-17F, IL-21, IL-22, IL-23, IL-25, IL-31, IL-33, IFN-γ, sCD40L and TNF-α in serum and saliva in periodontitis. We highlight their putative role in the pathogenesis of periodontitis and place them within a wider context of animal and other clinical studies.

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.

Investigation of the Effect of Formaldehyde on the Condition of Periodontal Tissues of Woodworking Industry Workers

The high prevalence of periodontal diseases in workers with professional contact with unfavorable factors of the production environment is an unresolved problem of dentistry. This study aimed to investigate the harmful effects of formaldehyde on periodontal tissues in woodworkers who have long-term contact with formaldehyde in their professional activities. Sixty-nine men with occupational exposure to formaldehyde were examined to study the effect of formaldehyde on the human periodontal tissues, looking particularly at signs of the periodontal tissues’ inflammatory process using a series of periodontal indices. The study results showed that the condition of periodontal tissues was statistically significantly worse in woodworkers who have long-term contact with formaldehyde in their professional activities. However, the hygiene status was not significantly different in the main group and the comparison group. Thus, we concluded that working under conditions of constant exposure to formaldehyde has a negative effect on the condition of periodontal tissues.

Antimicrobial activity of honey in periodontal disease: a systematic review

BACKGROUND

Honey has shown positive antimicrobial and anti-inflammatory actions in several dermatological studies; however, it is unclear if it could be effective in the treatment of periodontal disease.

OBJECTIVES

To answer the question: Does honey have antimicrobial activity against periodontopathogens?

METHODS

Six electronic databases were screened from initiation to 31 January 2019 for randomized clinical trials (RCTs) and controlled in vitro studies exploring the antimicrobial effect of honey against periodontopathogens. Honey's botanical origin, periopathogens that showed microbial susceptibility to honey, MICs, microbial growth conditions, control product and clinical follow-up were the main investigated outcomes. The risk of bias (RoB) of included RCTs was assessed using the Cochrane Collaboration RoB tool. The RoB of in vitro studies was evaluated based on the Sarkis-Onofre judgement model adapted to the context of honey.

RESULTS

A total of 1448 publications were found as search results in the screened databases. Sixteen eligible papers were included based on predetermined inclusion criteria. Retained studies included 5 RCTs and 11 in vitro controlled trials. Manuka and multifloral honeys were the most studied varieties. The tested honeys showed a significant antimicrobial action, with different MICs, against eight periopathogens. Four of the five RCTs showed a high RoB, while 4 of the 11 retained in vitro studies showed a medium RoB.

CONCLUSIONS

Honey showed a significant antimicrobial activity against all targeted periopathogens. Additional experiments are required to explore the entire antimicrobial spectrum of honey towards all pathogens involved in periodontal disease.

The expression of inducible nitric oxide synthase in the gingiva of rats with periodontitis and diabetes mellitus

OBJECTIVE

To ascertain the role of inducible nitric oxide synthase (iNOS) in the periodontitis response during diabetes.

METHODS

Twenty-four male SD rats were randomly divided into four groups: control group (Control), diabetes mellitus group (D), diabetes mellitus plus periodontitis group (DP), and periodontitis group (P). Periodontitis and diabetes were established separately. Then the gingival tissue and alveolar bone were collected. A stereomicroscope was used to evaluate bone loss. The expression of iNOS, TNF-α, and NF-κB in the gingiva was detected by immunohistochemical staining, real-time PCR, and western blot analysis.

RESULTS

Significant bone loss was observed in the DP and P groups and more extensive bone resorption was discovered in the DP group than in the P group (P < 0.05). The immunohistochemical staining analysis revealed enhanced expression of iNOS located in the gingiva of the three disease groups compared with the control group (P < 0.05). In particular, the level of iNOS was significantly higher in the DP group than in the P group (P < 0.05). This elevated trend of iNOS was further demonstrated by quantitative PCR and western blot analysis. Similarly, the mRNA and protein expression levels of NF-κB in the D, DP, and P groups were significantly higher than those of the control group, as was the level of TNF-α protein (P < 0.05).

CONCLUSIONS

Our results proved diabetes exacerbated alveolar bone resorption in a periodontitis rat model. iNOS may be the inflammatory mediator in the course of periodontal injury promoted by diabetes.

Microbiome Profiles of Ligature-Induced Periodontitis in Nonhuman Primates across the Life Span

This investigation compared the microbiomes colonizing teeth during the initiation, progression, and resolution of periodontitis in nonhuman primates (Macaca mulatta) at different ages. Subgingival plaque samples were collected at baseline; 0.5, 1, and 3 months following ligature-induced periodontitis; and following naturally occurring disease resolution at 5 months. Samples were analyzed using 16S amplicon sequencing to identify bacterial profiles across age groups: young (<3 years of age), adolescent (3 to 7 years), adult (12 to 15 years), and aged (17 to 23 years). α-Diversity of the microbiomes was greater in the adult/aged samples than in the young/adolescent samples. β-Diversity of the samples demonstrated clear age group differences, albeit individual variation in microbiomes between animals within the age categories was noted. Phylum distributions differed between the young/adolescent animals and the adult/aged animals at each of the time points, showing an enrichment of the phyla Spirochetes, Fusobacteria, and Bacteroidetes associated with periodontitis. Major differences in the top 50 operational taxonomic units (OTUs) were noted in the young and adolescent microbiomes during initiation and progression postligation compared to the adult and aged animals. The proportions of a large number of species in the top 50 OTUs were lower at baseline and in resolved disease microbiomes in the young samples, while profiles in adolescent animals were more consistent with the disease microbiomes. Microbiome profiles for resolution for adults and aged animals appeared more resilient and generally maintained a pattern similar to that of disease. Use of the model can expand our understanding of the crucial interactions of the oral microbiome and host responses in periodontitis.