Editorial: Use of Saliva in Diagnosis of Periodontitis: Cumulative Use of Bacterial and Host-Derived Biomarkers

Artificial intelligence in salivary biomarker discovery and validation for oral diseases

Salivary biomarkers can improve the efficacy, efficiency, and timeliness of oral and maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which salivary biomarkers have been utilized for disease-related outcomes include periodontal diseases, dental caries, oral cancer, temporomandibular joint dysfunction, and salivary gland diseases. However, given the equivocal accuracy of salivary biomarkers during validation, incorporating contemporary analytical techniques for biomarker selection and operationalization from the abundant multi-omics data available may help improve biomarker performance. Artificial intelligence represents one such advanced approach that may optimize the potential of salivary biomarkers to diagnose and manage oral and maxillofacial diseases. Therefore, this review summarized the role and current application of techniques based on artificial intelligence for salivary biomarker discovery and validation in oral and maxillofacial diseases.

Does smoking influence tryptophan metabolism in periodontal inflammation? A cross-sectional study

OBJECTIVES

The aim of this study was to identify the effects of smoking and periodontal inflammation on tryptophan-kynurenine metabolism as well as the correlation between these findings and clinical periodontal parameters.

BACKGROUND

It has been shown that the tryptophan amino acid's primary catabolic pathway, the kynurenine pathway (KP), may serve as a key biomarker for periodontal disease. Although there are studies investigating the effect of smoking on KYN-TRP metabolism, the effect of smoking on periodontal disease through KP has not been revealed so far.

METHODS

The salivary and serum samples were gathered from 24 nonsmoker (NS-P) stage III, grade B generalized periodontitis and 22 smoker (S-P) stage III, grade C generalized periodontitis patients, in addition to 24 nonsmoker (NS-C) and 24 smoker (S-C) periodontally healthy control individuals. Saliva and serum IL-6, kynurenine (KYN), and tryptophan (TRP) values, and KYN/TRP ratio were analyzed by liquid chromatography-mass spectrometry. Clinical periodontal measurements were recorded.

RESULTS

Salivary TRP values were significantly higher in both periodontitis groups than control groups (p < .05). Salivary KYN values were highest in NS-P group (p < .05). Salivary KYN values did not differ significantly between periodontitis groups (p = .84). Salivary KYN/TRP ratio was significantly lower in NS-P group compared to other groups (p < .001). Serum TRP value is higher in S-P group than other groups; however, significant difference was found in S-C group (p < .05). Serum KYN values were significantly lower in smokers than nonsmokers. Serum KYN/TRP ratio is higher in NS-P group. NS-P group has the highest salivary IL-6 levels, NS-C group has the lowest values (p < .05).

CONCLUSIONS

Our results point out that smoking exacerbates inflammation in the periodontium and increases TRP destruction and decreases IDO activity by suppressing KP in serum. As a result, kynurenine and its metabolites may be significant biomarkers in the link between smoking and periodontal disease.

Salivary Microbial Dysbiosis Is Associated With Peri-Implantitis: A Case-Control Study in a Brazilian Population

Background and Objectives

The aim of this study was to examine the salivary microbiome in healthy peri-implant sites and those with peri-implantitis.

Methods

Saliva samples were collected from 21 participants with healthy peri-implant sites and 21 participants with peri-implantitis. The V4 hypervariable region of the 16S rRNA gene was sequenced using the Ion Torrent PGM System (Ion 318™ Chip v2 400). The NGS analysis and composition of the salivary microbiome were determined by taxonomy assignment. Downstream bioinformatic analyses were performed in QIIME (v 1.9.1).

Results

Clinical differences according to peri-implant condition status were found. Alpha diversity metrics revealed that the bacterial communities of participants with healthy peri-implant sites tended to have a richer microbial composition than individuals with peri-implantitis. In terms of beta diversity, bleeding on probing (BoP) may influence the microbial diversity. However, no clear partitioning was noted between the salivary microbiome of volunteers with healthy peri-implant sites or volunteers with peri-implantitis. The highest relative abundance of Stenotrophomonas, Enterococcus and Leuconostoc genus, and Faecalibacterium prausnitzii, Haemophilus parainfluenzae, Prevotella copri, Bacteroides vulgatus, and Bacteroides stercoris bacterial species was found in participants with peri-implantitis when compared with those with healthy peri-implant sites.

Conclusion

Differences in salivary microbiome composition were observed between patients with healthy peri-implant sites and those with peri-implantitis. BoP could affect the diversity (beta diversity) of the salivary microbiome.

Saliva as a Source of Biomarkers for Periodontitis and Periimplantitis

Saliva has the potential to be used as a diagnostic and monitoring tool for various diseases if biomarkers of an adequate sensitivity and specificity could be identified. Several reviews and even meta-analyses have been performed in recent years, which have found some candidate biomarkers for periodontitis, like macrophage inflammatory protein-1 alpha, interleukin-1ß, interleukin-6, matrix metalloproteinase-8, or hemoglobin. However, none of those are currently in use to replace conventional periodontal diagnostics with a periodontal probe. For periimplantitis, to date, heterogeneity of different study protocols and implant types did not permit to discover clear biomarkers, which were able to distinguish between healthy and diseased implants. Few proinflammatory cytokines, similar to periodontitis, have been characterized as adjunct tools to clinical diagnosis. The additional determination of antimicrobial peptides, bone turnover markers, and bacteria could help to enhance sensitivity and specificity in a combined model for periodontitis and periimplantitis. Furthermore, proteomic approaches might be preferred over single biomarker determinations. A global consensus is also needed to harmonize salivary sampling methods as well as procedures of biomarker analysis to ensure future comparability.

Salivary and serum markers of angiogenesis in periodontitis in relation to smoking

OBJECTIVE

Angiogenesis is essential in maintenance of periodontal homeostasis, and it is regulated by growth factors and cytokines, including basic fibroblast growth factor (b-FGF), endoglin, platelet and endothelial cell adhesion molecule (PECAM-1), vascular endothelial growth factor (VEGF), soluble intercellular adhesion molecule-1 (sICAM-1), and soluble vascular cell adhesion molecule-1 (sVCAM-1). In this study, the salivary and serum concentrations of these angiogenesis-related proteins in relation to smoking and periodontitis were examined.

MATERIAL AND METHODS

Full-mouth periodontal status together with unstimulated whole saliva and serum samples was collected from 78 individuals, including 40 periodontitis patients (20 smokers and 20 nonsmokers) and 38 periodontally healthy controls (20 smokers and 18 nonsmokers). The Luminex®-xMAP™ technique was used for protein analyses.

RESULTS

Concentrations of all tested proteins in saliva as well as VEGF in serum were significantly higher in periodontitis patients than in healthy controls. In smokers, serum concentrations of endoglin (p = 0.017) and sICAM-1 (p = 0.001) were elevated in comparison to nonsmokers. After adjusting for smoking and gender, periodontitis associated significantly with salivary concentrations of b-FGF, PECAM-1, VEGF, sICAM-1, and sVCAM-1 (p < 0.01).

CONCLUSION

Taken together, salivary concentrations of b-FGF, PECAM-1, and VEGF associate with periodontitis. The suppressive effect of smoking on salivary marker levels is limited to periodontitis patients only.

CLINICAL RELEVANCE

Smoking-related suppression of salivary marker levels is observed only in periodontitis patients.

Identification of Salivary Microbiota and Its Association With Host Inflammatory Mediators in Periodontitis

Periodontitis is a microbial-induced chronic inflammatory disease, which may not only result in tooth loss, but can also contribute to the development of various systemic diseases. The transition from healthy to diseased periodontium depends on microbial dysbiosis and impaired host immune response. Although periodontitis is a common disease as well as associated with various systemic inflammatory conditions, the taxonomic profiling of the salivary microbiota in periodontitis and its association with host immune and inflammatory mediators has not been reported. Therefore, the aim of this study was to identify key pathogens and their potential interaction with the host's inflammatory mediators in saliva samples for periodontitis risk assessment. The microbial 16S rRNA gene sequencing and the levels of inflammatory mediators were performed in saliva samples from patients with chronic periodontitis and periodontally healthy control subjects. The salivary microbial community composition differed significantly between patients with chronic periodontitis and healthy controls. Our analyses identified a number of microbes, including bacteria assigned to Eubacterium saphenum, Tannerella forsythia, Filifactor alocis, Streptococcus mitis/parasanguinis, Parvimonas micra, Prevotella sp., Phocaeicola sp., and Fretibacterium sp. as more abundant in periodontitis, compared to healthy controls. In samples from healthy individuals, we identified Campylobacter concisus, and Veillonella sp. as more abundant. Integrative analysis of the microbiota and inflammatory mediators/cytokines revealed associations that included positive correlations between the pathogens Treponema sp. and Selenomas sp. and the cytokines chitinase 3-like 1, sIL-6Rα, sTNF-R1, and gp130/sIL-6Rβ. In addition, a negative correlation was identified between IL-10 and Filifactor alocis. Our results reveal distinct and disease-specific patterns of salivary microbial composition between patients with periodontitis and healthy controls, as well as significant correlations between microbiota and host-mediated inflammatory cytokines. The positive correlations between the pathogens Treponema sp. and Selenomas sp. and the cytokines chitinase 3-like 1, sIL-6Rα, sTNF-R1, and gp130/sIL-6Rβ might have the future potential to serve as a combined bacteria-host salivary biomarker panel for diagnosis of the chronic infectious disease periodontitis. However, further studies are required to determine the capacity of these microbes and inflammatory mediators as a salivary biomarker panel for periodontitis.

Lactate Dehydrogenase and β-Glucuronidase as Salivary Biochemical Markers of Periodontitis Among Smokers and Non-Smokers

Objectives

This study aimed to establish lactate dehydrogenase (LDH) and β-glucuronidase as salivary biomarkers of periodontitis among smokers and non-smokers.

Methods

This cross-sectional case-control study was conducted at the Aligarh Muslim University, Aligarh, India, between January and June 2017. A total of 200 participants were divided into four groups based on their periodontal and smoking statuses. Unstimulated mixed saliva samples were collected to estimate LDH and β-glucuronidase levels. In addition, total protein was estimated using Lowry's method.

Results

There was a significant increase in enzyme activity in the periodontitis groups compared to the non-periodontitis groups (P <0.001). However, significantly lower enzyme activity was observed among smokers, irrespective of periodontal status (P <0.001). Nevertheless, a receiver operating characteristic curve analysis indicated the diagnostic potential of both enzymes to be fair-to-excellent.

Conclusion

Although smoking was found to significantly alter enzyme activity, LDH and β-glucuronidase were reliable salivary biomarkers of periodontitis among both smokers and non-smokers.

Cumulative use of salivary markers with an adaptive design improves detection of periodontal disease over fixed biomarker thresholds

OBJECTIVE

Aim was to analyze the diagnostic ability of cumulative risk score (CRS), which uses salivary levels of Porphyromonas gingivalis, interleukin (IL)-1β, and matrix metalloproteinase (MMP)-8 in an adaptive design, compared to previously reported thresholds of each marker alone.

MATERIALS AND METHODS

Oral and general health information of 463 participants were included in the analysis. Having the percentage of bleeding on probing (BOP) > 25%, having at least two sites with probing pocket depth (PPD) of 4-5 mm or having at least one tooth with alveolar bone loss (ABL) of at least 1/3 of the root length were accepted as outcome variables. Being above the salivary threshold concentrations of P. gingivalis, IL-1β, and MMP-8 and CRS values were used as explanatory variables. Receiver operating characteristics (ROC) producing an area under the curve (AUC) and multinomial regression analysis were used in statistical analysis.

RESULTS

CRS provided AUCs larger than any other tested biomarker threshold. Sensitivity and specificity of CRS for detecting clinical markers of periodontitis were acceptable, and a strong association was observed between the highest CRS score and having at least two sites with PPD of 4-5 mm.

CONCLUSION

CRS brings additional power over fixed thresholds of single biomarkers in detecting periodontitis.

Salivary biomarkers in association with periodontal parameters and the periodontitis risk haplotype

Genetic factors play a role in periodontitis. Here we examined whether the risk haplotype of MHC class III region BAT1-NFKBIL1-LTA and lymphotoxin-α polymorphisms associate with salivary biomarkers of periodontal disease. A total of 455 individuals with detailed clinical and radiographic periodontal health data were included in the study. A 610 K genotyping chip and a Sequenom platform were used in genotyping analyses. Phospholipid transfer protein activity, concentrations of lymphotoxin-α, IL-8 and myeloperoxidase, and a cumulative risk score (combining Porphyromonas gingivalis, IL-1β and matrix metalloproteinase-8) were examined in saliva samples. Elevated IL-8 and myeloperoxidase concentrations and cumulative risk scores associated with advanced tooth loss, deepened periodontal pockets and signs of periodontal inflammation. In multiple logistic regression models adjusted for periodontal parameters and risk factors, myeloperoxidase concentration (odds ratio (OR); 1.37, P = 0.007) associated with increased odds for having the risk haplotype and lymphotoxin-α concentration with its genetic variants rs2857708, rs2009658 and rs2844482. In conclusion, salivary levels of IL-8, myeloperoxidase and cumulative risk scores associate with periodontal inflammation and tissue destruction, while those of myeloperoxidase and lymphotoxin-α associate with genetic factors as well.

Cytokine Levels and Human Herpesviruses in Saliva from Clinical Periodontal Healthy Subjects with Peri-Implantitis: A Case-Control Study

This study evaluated the presence of cytokines (IL-1β, IL-2, IL-4, IL-6, MCP-1, MIP-1α, MIP-1β, and TNF-α) and human herpesvirus (HSV1, HSV2, EBV, CMV, VZV, HHV6, HHV7, and HHV8) in saliva samples taken from subjects with and without peri-implantitis. Forty-two periodontally healthy subjects were divided according to peri-implant condition: healthy and peri-implantitis groups. The clinical parameters as probing depth, clinical attachment level, plaque index, gingival bleeding, bleeding on probing, and suppuration were evaluated. For cytokine detection, multiplex analysis was performed, and PCR assay was used to identify herpesviruses. No significant differences were found in cytokine levels between groups (p > 0.05). The presence of herpesvirus was 1.97-fold higher in patients with peri-implantitis (odds ratio, CI 0.52-7.49). The association of the presence or absence of herpesvirus with the salivary markers was statistically significant for MIP-1β (p = 0.0087) and TNF-α (p = 0.0437) only in the peri-implantitis group. The presence of herpesviruses in patients with peri-implantitis suggests the development of a proinflammatory environment, which is characterized by increased expression of MIP-1β and TNF-α in saliva.

Salivary cytokine levels in early gingival inflammation

Salivary protein levels have been studied in periodontitis. However, there is lack of information on salivary cytokine levels in early gingival inflammation. The aim of this study was to determine salivary levels of vascular endothelial growth factor (VEGF), interleukin (IL)-8, monocyte chemoattractant protein (MCP)-1, IL-1β, and IL-1 receptor antagonist (IL-1Ra) in gingival inflammation. Twenty-eight systemically and orally healthy nonsmokers abstained from oral hygiene protocols for 10 days. After that, self-performed cleaning was resumed for 14 days. Plaque and gingival indexes were measured, and saliva samples were collected at days 1, 4, 7, 10, and 24. Salivary cytokines were detected with Luminex®-xMAP™. Salivary IL-1β, IL-1Ra, and VEGF levels decreased after 10 days' development of experimental gingivitis and reached baseline levels at the end of the 2-week resolution period. Salivary IL-8 levels decreased and remained low during development and resolution of experimental gingivitis. Initial inflammation in gingival tissues is associated with a decrease in inflammatory cytokines in saliva. Further studies are needed to evaluate if inflammatory cytokines bind to their functional receptors within the gingival tissue during early gingivitis, which may limits their spillover to the gingival crevice and ultimately saliva.