Personalized medicine: an update of salivary biomarkers for periodontal diseases

A flexible glucose biosensor modified by reduced-swelling and conductive zwitterionic hydrogel enzyme membrane

This paper reports a flexible glucose biosensor which is modified by a reduced-swelling and conductive zwitterionic hydrogel enzyme membrane that contains two forms of chemical cross-links. One chemical cross-linking is induced by thermal initiators and forms the basal network of the hydrogel. Another cross-linking is achieved by the coordination interactions between the multivalent metal ion Al3+ and anionic group -COO- of zwitterionic poly-carboxy betaine (pCBMA), which significantly increase the cross-linking density of the zwitterionic hydrogel, improving the reduced-swelling property and reducing the pore size. The better reduced-swelling property and reduced diameters of pores within the zwitterionic hydrogel make less glucose oxidase (GOx) leakage, thus significantly improving the enzyme membrane's service life. By introducing the Al3+ and Cl-, the conductivity of the zwitterionic hydrogel is enhanced approximately 10.4-fold. According to the enhanced conductivity, the reduced-swelling property, and the high GOx loading capacity of the zwitterionic hydrogel, the sensitivity of the biosensor with GOx/pCBMA-Al3+ is significantly improved by 5 times and has a long service life. Finally, the proposed GOx/pCBMA-Al3+ biosensor was applied in non-invasive blood glucose detection on the human body, verifying the capability in practice.

Realizing the clinical utility of saliva for monitoring oral diseases

In the era of personalized/precision health care, additional effort is being expended to understand the biology and molecular mechanisms of disease processes. How these mechanisms are affected by individual genetics, environmental exposures, and behavioral choices will encompass an expanding role in the future of optimally preventing and treating diseases. Considering saliva as an important biological fluid for analysis to inform oral disease detection/description continues to expand. This review provides an overview of saliva as a diagnostic fluid and the features of various biomarkers that have been reported. We emphasize the use of salivary biomarkers in periodontitis and transport the reader through extant literature, gaps in knowledge, and a structured approach toward validating and determine the utility of biomarkers in periodontitis. A summation of the findings support the likelihood that a panel of biomarkers including both host molecules and specific microorganisms will be required to most effectively identify risk for early transition to disease, ongoing disease activity, progression, and likelihood of response to standard periodontal therapy. The goals would be to develop predictive algorithms that serve as adjunctive diagnostic tools which provide the clinician and patient important information for making informed clinical decisions.

Periodontal disease and emerging point-of-care technologies for its diagnosis

Periodontal disease (PD), a chronic inflammatory disorder that damages the tooth and its supporting components, is a common global oral health problem. Understanding the intricacies of these disorders, from gingivitis to severe PD, is critical for efficient treatment, diagnosis, and prevention in dental care. Periodontal biosensors and biomarkers are critical in improving oral health diagnostic skills. Clinicians may accomplish early identification, tailored therapy, and efficient tracking of periodontal diseases by using these technologies, ushering in a new age of accurate oral healthcare. Traditional periodontitis diagnostic methods frequently rely on physical probing and visual examinations, necessitating the development of point-of-care (POC) devices. As periodontal disorders necessitate more precise and rapid diagnosis, incorporating novel innovations in biosensors and biomarkers becomes increasingly crucial. These innovations improve our capacity to diagnose, monitor, and adapt periodontal therapies, bringing in the next phase of customized and effective dental healthcare. The review discusses the characteristics and stages of PD, clinical treatment techniques, prominent biomarkers and infection-associated factors that may be employed to determine PD, biomedical sensing, and POC appliances that have been created so far to diagnose stages of PD and its progression profile, as well as predicting future developments in this field.

Therapeutic Strategies and Genetic Implications for Periodontal Disease Management: A Systematic Review

The objective of this review is to identify the microbiological alterations caused by various therapy modalities by critically analyzing the current findings. We limited our search to English-language papers published between 1 January 2004 and 7 May 2024 in PubMed, Scopus, and Web of Science that were relevant to our topic. In the search approach, the Boolean keywords "microbio*" AND "periodontitis" were used. A total of 5152 papers were obtained from the databases Web of Science (2205), PubMed (1793), and Scopus (1154). This resulted in 3266 articles after eliminating duplicates (1886), and 1411 entries were eliminated after their titles and abstracts were examined. The qualitative analysis of the 22 final articles is included in this study. Research on periodontal disease shows that periodontitis alters the oral microbiome and increases antibiotic resistance. Treatments like scaling and root planing (SRP), especially when combined with minocycline, improve clinical outcomes by reducing harmful bacteria. Comprehensive mechanical debridement with antibiotics, probiotics, EMD with bone grafts, and other adjunctive therapies enhances periodontal health. Personalized treatment strategies and advanced microbial analyses are crucial for effective periodontal management and antibiotic resistance control.

Associations between immune-inflammatory markers, age, and periodontal status: a cross-sectional study

Since periodontal disease is associated with many systemic diseases, it is important to evaluate its effects on host responses in elderly individuals. To this end, this study investigated salivary interleukin (IL)-17, IL-18, toll-like receptor (TLR) 2, TLR4, and tumor necrosis factor-alpha (TNF-α) levels in patient groups with different periodontal health statuses and immunologically evaluated the relationship between age and periodontal health status. A total of 60 individuals aged 18-40 years (young individuals) and 60 individuals aged 65 years or older (elderly individuals) were included in this study. According to periodontal disease status, the patients were divided into periodontally healthy, gingivitis, and periodontitis subgroups. Clinical periodontal parameters, including probing depth (PD), clinical attachment level (CAL), plaque index (PI), and gingival index (GI), were recorded. Saliva samples were collected and analyzed using ELISA to determine the levels of IL-17, IL-18, TLR2, TLR4, and TNF-α. Higher clinical periodontal parameter (PD, CAL, PI, and GI) and inflammatory marker (IL-17, IL-18, TNF-α, TLR2, and TLR4) levels were found in patients with periodontitis than those in periodontally healthy individuals and patients with gingivitis (P < 0.05). Salivary inflammatory marker levels were significantly higher in elderly individuals than those in young individuals in all subgroups (P < 0.05). A positive correlation was found between inflammatory marker levels and clinical periodontal parameters, but there was no correlation between TLR2 and PI or GI. This study suggests a significant increase in host response to periodontal disease as the disease progresses, with the levels of cytokines and TLR expression exhibiting an increasing trend with age. Increased IL-17, IL-18, TLR2, TLR4, and TNF-α levels in elderly individuals in all periodontal health subgroups might suggest the role of these cytokines and TLR pathway in the pathogenesis of periodontal diseases.

Salivary inflammatory burden in pre- and postmenopausal women: Associations with body mass index, patient-reported health, serum cytokines, and periodontal parameters

BACKGROUND

The decline of estrogen levels during menopause impacts weight, mood, and overall health, both orally and systemically. This study assessed salivary levels of tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), IL-10, and IL-7 in postmenopausal (PMW) and regularly menstruating premenopausal (RMPW) women, while considering serum cytokine levels, body mass index (BMI), periodontal health, and self-reported physical and emotional well-being.

METHODS

In this study, 75 PMW and 71 RMPW were included. Clinical and periodontal parameters were evaluated, and perceived health was assessed with the Women's Health Questionnaire (WHQ). Cytokine levels in both saliva and serum were quantified by enzyme-linked immunosorbent assay (ELISA). Covariate evaluations of salivary cytokines were conducted using hierarchical linear regression modeling.

RESULTS

Cytokines were detectable in saliva from 71 PMW and 67 RMPW. In the initial unadjusted model, IL-7, IL-10, and TNF-α exibited significant differences between RMPW and PMW. However, these differences became non-significant (p > 0.05) in the final model after adjusting for age, which implies a negligible effect of the investigated covariates on salivary cytokine levels when age was considered. Lower levels of IL-6 in PMW, which initially showed no significant difference, became borderline (p = 0.054) in the final model after adjusting for age.

CONCLUSIONS

After adjusting for multiple factors, no significant difference was found in the salivary levels of the investigated cytokines between RMPW and PMW. Factors such as BMI, perceived health, serum cytokine levels, and periodontal parameters seem to minimally influence these levels in PMW. However, age may be a stronger confounding factor.

Exploring the Relation Between Interstitial Lung Diseases and Chronic Periodontitis: A Systematic Review

The objective of this systematic review is to determine the association between interstitial lung diseases and chronic periodontitis from various aspects such as microbial, biomarker, genetic, and environmental levels. A systematic review was carried out from 2000 to 2021 following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations including studies searched in PubMed-Medline, Google Scholar, and Cochrane databases. A total of more than 100 articles were obtained in the initial screening process. Out of these 42 studies fulfilled the inclusion criteria and were included in the study. According to the extracted data, there is mounting evidence suggesting the association between these two diseases. Our systematic review raises the prospect of a connection between chronic periodontitis and interstitial lung diseases, within the limitations of the studies we included.

Salivary Chloride Intracellular Channel 1 (CLIC1) as a Hub of Gene-Gene Interactome of Periodontitis With Diabetes Mellitus

Background and introduction Periodontal disease is one of the most prevalent chronic conditions that affects the oral cavity. Identifying and predicting biomarkers is essential for the prevention of high-morbidity oral diseases. The genomic interaction network identifies common hub genes involved in crucial protein formation in periodontal inflammation. Diabetes mellitus is a metabolic disorder that has a double-edged sword relationship with periodontitis. Chloride intracellular channel 1 (CLIC1) was identified as a hub gene linking the pathogenesis of periodontitis and diabetes mellitus using a bioinformatic tool. Therefore, this current study aimed to assess the concentration of the pro-inflammatory biomarker CLIC1 in saliva among individuals with periodontal health and those with periodontal disease linked to diabetes mellitus. Materials and methods Differentially expressed genes (DEGs) in periodontitis were identified using datasets retrieved from the Gene Expression Omnibus (GEO) database. DEGs were combined to build the network, and GeneMANIA was used to find and rank the interconnecting genes. CLIC1 was identified as the hub gene, and clinical validation was done using patient samples. The study involved 30 participants. Based on clinical and radiographic periodontal findings, they were split into three groups: healthy (group 1, n=10), with periodontitis but no diabetes mellitus (group 2, n=10), and with periodontitis and diabetes mellitus (group 3, n=10). The collection of saliva samples, followed by quantifying these samples, was performed using an enzyme-linked immunosorbent assay (ELISA). Results From network graph analysis, it was discovered that CLIC1 functions as a hub gene in the majority of toll-like receptor pathways. The mean concentration of CLIC1 in saliva increased consistently as the disease was observed in periodontitis patients and periodontitis patients with diabetes mellitus.  Conclusion CLIC1 concentrations were positively correlated with periodontitis in individuals with diabetes. Therefore, CLIC1 could be a diagnostic biomarker for patients with periodontitis. However, large-scale studies are needed to confirm more positive associations.

Cystatin SN (CST1) as a Novel Salivary Biomarker of Periodontitis

Identification of biomarkers could help in assessing periodontal health status and monitoring treatment outcomes. Therefore, the aim of this cross-sectional study was to identify potential innovative salivary biomarkers for the diagnosis of periodontitis using an untargeted proteomic approach. Forty-five healthy non-smoker participants diagnosed as having periodontally healthy conditions (H), severe periodontitis (P), and healthy but reduced periodontium after active periodontal treatment (T) were consecutively enrolled (15 per each group) in the study. A higher number of spots were identified in the proteome of unstimulated whole saliva collected from H and T subjects compared with P group, mainly within the range of 8-40 kDa. Protein spots of interest were analysed by MALDI-TOF-MS, allowing the identification of cystatin SN (CST1) isoform, as confirmed by Western blot. CST1 was markedly expressed in the H group, while it was absent in most P samples (p < 0.001). Interestingly, a distinct CST1 expression was observed in saliva from T patients. CST1 was negatively correlated with the percentage of pathological sites (p < 0.001) and was effective in discriminating active periodontitis from healthy periodontal status (whether H or T). Therefore, salivary CST1 may be a promising non-invasive biomarker for periodontal disease diagnosis and monitoring.

Effect of scaling and root planing with and without minocycline HCl microspheres on periodontal pathogens and clinical outcomes: A randomized clinical trial

BACKGROUND

This study tests the effects of scaling and root planing (SRP) versus SRP plus minocycline hydrochloride microspheres (SRP+MM) on 11 periodontal pathogens and clinical outcomes in Stage II-IV Grade B periodontitis participants.

METHODS

Seventy participants were randomized to receive SRP (n = 35) or SRP+MM (n = 35). Saliva and clinical outcomes were collected for both groups at baseline before SRP, 1-month reevaluation, and at 3- and 6-month periodontal recall. MM were delivered to pockets ≥5 mm immediately after SRP and immediately after the 3-month periodontal maintenance in the SRP+MM group. A proprietary saliva test* was utilized to quantitate 11 putative periodontal pathogens. Microorganisms and clinical outcomes were compared between groups using generalized linear mixed-effects models with fixed effects and random effects terms. Mean changes from baseline were compared between groups via group-by-visit interaction tests.

RESULTS

Significant reduction in Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Parvimonas micra, and Eikenella corrodens were identified at the 1-month reevaluation after SRP+MM. Six months after SRP with a re-application of MM 3 months after SRP, Fusobacterium nucleatum, Prevotella intermedia, Campylobacter rectus, and Eikenella corrodens were significantly reduced. SRP+MM participants had significant clinical outcome reductions in pockets ≥5 mm at the reevaluation, 3- and 6-month periodontal maintenance, and clinical attachment loss gains at the 6-month periodontal maintenance.

CONCLUSION

MM delivered immediately after SRP and reapplication at 3 months appeared to contribute to improved clinical outcomes and sustained decreased numbers of Fusobacterium nucleatum, Prevotella intermedia, Campylobacter rectus, and Eikenella corrodens at 6 months.

Efficacy of Proanthocyanidins in Nonsurgical Periodontal Therapy

BACKGROUND

The aim of this work was to evaluate the efficacy of proanthocyanidins (PACNs) as an adjunctive periodontal therapy in patients with periodontitis.

METHODS

Patients with periodontitis (stage III-IV) were included in this randomised clinical study. Patients with periodontitis received 2 different treatment modalities: minimally invasive nonsurgical therapy only (MINST group) or minimally invasive nonsurgical therapy and subgingival application of collagen hydrogels with PACNs (MINST + PACNs group). Clinical periodontal parameters, that is, pocket probing depth (PPD), clinical attachment level (CAL), bleeding on probing (BOP), plaque index (PI), were evaluated before treatment and after 8 weeks. Concentrations of immunologic markers, matrix metalloproteinase-3 (MMP-3), and tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) in saliva were assessed at baseline and at 8-week follow-up.

RESULTS

Forty-six patients diagnosed with periodontitis were randomised into 2 groups: 23 patients in the MINST group and 23 patients in the MINST + PACNs group received the intended treatment. PACNs combined with MINST resulted in additional statistically significant PPD reduction and CAL gain in moderate periodontal pockets by 0.5 mm (P < .05) on average compared to MINST alone. Additional use of PACNs did not result in additional statistically significant improvement of BOP or PI values. Application of PACNs showed significant reduction of MMP-3 levels in saliva after 8 weeks (P < .05).

CONCLUSIONS

Adjunctive use of PACNs in MINST resulted in better clinical outcomes for moderate pockets. Additional use of PACNs improved MMP-3 concentration in saliva more than MINST alone. Biochemical analysis revealed that MMP-3 concentration in saliva reflected the periodontal health state.

Progress in salivary glands: Endocrine glands with immune functions

The production and secretion of saliva is an essential function of the salivary glands. Saliva is a complicated liquid with different functions, including moistening, digestion, mineralization, lubrication, and mucosal protection. This review focuses on the mechanism and neural regulation of salivary secretion, and saliva is secreted in response to various stimuli, including odor, taste, vision, and mastication. The chemical and physical properties of saliva change dynamically during physiological and pathophysiological processes. Moreover, the central nervous system modulates salivary secretion and function via various neurotransmitters and neuroreceptors. Smell, vision, and taste have been investigated for the connection between salivation and brain function. The immune and endocrine functions of the salivary glands have been explored recently. Salivary glands play an essential role in innate and adaptive immunity and protection. Various immune cells such as B cells, T cells, macrophages, and dendritic cells, as well as immunoglobins like IgA and IgG have been found in salivary glands. Evidence supports the synthesis of corticosterone, testosterone, and melatonin in salivary glands. Saliva contains many potential biomarkers derived from epithelial cells, gingival crevicular fluid, and serum. High level of matrix metalloproteinases and cytokines are potential markers for oral carcinoma, infectious disease in the oral cavity, and systemic disease. Further research is required to monitor and predict potential salivary biomarkers for health and disease in clinical practice and precision medicine.

Peri-implant Bone Healing: Its Basic Osteogenesis and Biomarkers

The continuous sequence of bone healing phases starts off with osteoconduction to the implant surface, depending on the migration of osteogenic cells. Osteoneogenesis ensues resulting in a mineralised interfacial matrix and is followed by bone remodelling to the implant interface at discrete sites. Dental implant drilling procedure and placement produce osseous defect which is filled by blood. Within seconds, blood proteins are adsorbed onto the implant surface and platelets are activated resulting in the release of cytokines and growth factors. Further platelet aggregation initiates osteoconduction to the surface, followed by osteoneogenesis, forming an extracellular matrix. Subsequently, remodelling creates a bone to implant interface which can be explained through distance and contact osteogenesis. The dental implant surface has been shown to influence osteoconduction by modifying protein properties and adsorption around the implant. Salivary biomarkers may be considered as a specific and sensitive diagnostic tool to detect these changes in protein expressions after implant placement. Thus, the purpose of this narrative review is to provide a detailed account of the bone healing mechanism associated with dental implant placement, as well as how the implant surface architecture and protein release play a role in bone healing, and the potential use of saliva to detect these biomarkers.

Periodontal disease metabolomics signatures from different biofluids: a systematic review

BACKGROUND

Periodontitis is resulted from a complex interaction between genetics and epigenetics, microbial factors, and the host response. Metabolomics analyses reflect both the steady-state physiological equilibrium of cells or organisms as well as their dynamic metabolic responses to environmental stimuli.

AIM OF REVIEW

This systematic review of the literature aimed to assess which low molecular weight metabolites are more often found in biological fluids of individuals with periodontitis compared to individuals with gingivitis or periodontal health.

KEY SCIENTIFIC CONCEPTS OF REVIEW

All the included studies employed untargeted analysis. One or more biological fluids were analyzed, including saliva (n = 14), gingival crevicular fluid (n = 6), mouthwash (n = 1), serum (n = 3) and plasma (n = 1). Fifty-six main metabolites related to periodontitis have been identified in at least two independent studies by NMR spectroscopy or MS-based metabolomics. Saliva was the main biological fluid sampled. It is noteworthy that 14 metabolites of the 56 detected were identified as main metabolites in all studies that sampled the saliva. The majority of metabolites found consistently among studies were amino acids, organic acids and derivates: acetate, alanine, butyrate, formate, GABA, lactate, propionate, phenylalanine and valine. They were either up- or down-regulated in the studies or this information was not mentioned. The main metabolic pathway was related to phenylalanine, tyrosine and tryptophan biosynthesis. Metabolites more frequently found in individuals with periodontitis were related to both the host and to microorganism responses. Future studies are needed, and they should follow some methodological standards to facilitate their comparison.

Biomarkers of Periodontitis and Its Differential DNA Methylation and Gene Expression in Immune Cells: A Systematic Review

The characteristic epigenetic profile of periodontitis found in peripheral leukocytes denotes its impact on systemic immunity. In fact, this profile not only stands for periodontitis as a low-grade inflammatory disease with systemic effects but also as an important source of potentially valuable clinical biomarkers of its systemic effects and susceptibility to other inflammatory conditions. Thus, we aimed to identify relevant genes tested as epigenetic systemic biomarkers in patients with periodontitis, based on the DNA methylation patterns and RNA expression profiles in peripheral immune cells. A detailed protocol was designed following the Preferred Reporting Items for Systematic Review and Meta-analysis -PRISMA guideline. Only cross-sectional and case-control studies that reported potential systemic biomarkers of periodontitis in peripheral immune cell types were included. DNA methylation was analyzed in leukocytes, and gene expression was in polymorphonuclear and mononuclear cells. Hypermethylation was found in TLR regulators genes: MAP3K7, MYD88, IL6R, RIPK2, FADD, IRAK1BP1, and PPARA in early stages of periodontitis, while advanced stages presented hypomethylation of these genes. TGFB1I1, VNN1, HLADRB4, and CXCL8 genes were differentially expressed in lymphocytes and monocytes of subjects with poorly controlled diabetes mellitus, dyslipidemia, and periodontitis in comparison with controls. The DAB2 gene was differentially overexpressed in periodontitis and dyslipidemia. Peripheral blood neutrophils in periodontitis showed differential expression in 163 genes. Periodontitis showed an increase in ceruloplasmin gene expression in polymorphonuclears in comparison with controls. Several genes highlight the role of the epigenetics of peripheral inflammatory cells in periodontitis that could be explored in blood as a source of biomarkers for routine testing.

Validity of a combination of periodontal pathogens and salivary biomarkers as predictors of periodontitis

OBJECTIVE

Chronic periodontitis is caused by multiple risk factors. To predict chronic periodontitis in older people, we evaluated the association between a combination of major periodontal pathogens and salivary biomarkers and the presence of periodontitis.

METHODS

Stimulated saliva samples were collected to analyze the prevalence of Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia, and Prevotella intermedia, as well as four biomarkers: interleukin (IL)-1β, IL-6, tumor necrosis factor-α (TNF-α), and prostaglandin E2 (PGE2). A total of 201 Japanese patients were recruited. Oral examinations ware performed to determine chronic periodontitis as measured by Community Periodontal Index. The sociodemographic and behavioral characteristics were also obtained, and the parameters were adjusted as potential confounders to employ statistical models.

RESULTS

The odds ratio (OR) for the presence of P. gingivalis and the third tertile level of IL-1β as compared with the absence of P. gingivalis and the lowest tertile of IL-1β was highest in individuals with periodontitis (OR = 13.98; 95% confidence interval [CI] 3.87-50.52) with the best level (0.79) of area under the curve (AUC) based on the receiver operating characteristic curve. The OR for the presence of P. gingivalis and the third tertile of PGE2 was 7.76 (CI 1.89-31.91) with an AUC of 0.78. The coexistence of more than two periodontal bacteria and the third tertile of PGE2 was also strongly associated with chronic periodontitis (OR = 9.23, 95% CI 2.38-35.79) with an AUC of 0.76.

CONCLUSIONS

The combined information of the presence of P. gingivalis in stimulated saliva, and higher levels of salivary IL-1β may play a vital role in the detection and prediction of chronic periodontitis in older adults.

Genomic Medicine in Periodontal Disease: Old Issue, New Insights

Genetic variability is the main cause of phenotypic variation. Some variants may be associated with several diseases and can be used as risk biomarkers, identifying animals with higher susceptibility to develop the pathology. Genomic medicine uses this genetic information for risk calculation, clinical diagnosis and prognosis, allowing the implementation of more effective preventive strategies and/or personalized therapies. Periodontal disease (PD) is the inflammation of the periodontium induced mainly by bacterial plaque and is the leading cause of tooth loss. Microbial factors are responsible for the PD initiation; however, several studies support the genetic influence on the PD progression. The main purpose of the present publication is to highlight the main steps involved in the genomic medicine applied to veterinary patients, describing the flowchart from the characterization of the genetic variants to the identification of potential associations with specific clinical data. After investigating which genes might potentially be implicated in canine PD, the RANK gene, involved in the regulation of osteoclastogenesis, was selected to illustrate this approach. A case-control study was performed using DNA samples from a population of 90 dogs – 50 being healthy and 40 with PD. This analysis allowed for the discovery of four new intronic variations that were banked in GenBank (g.85A>G, g.151G>T, g.268A>G and g.492T>C). The results of this study are not intended to be applied exclusively to PD. On the contrary, this genetic information is intended to be used by other researchers as a foundation for the development of multiple applications in the veterinary clinical field.

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.

Diagnostic accuracy of active matrix metalloproteinase-8 point-of-care test for the discrimination of periodontal health status: Comparison of saliva and oral rinse samples

BACKGROUND AND OBJECTIVES

Assessment of biomarkers, specifically active matrix metalloproteinase-8 (aMMP-8), in saliva/oral rinses is a promising diagnostic approach for periodontal health and disease. Different oral fluids have specific advantages and limitations. This study investigates the effect of sampling different fluids on the accuracy of an aMMP-8 point of care test (POCT).

METHODS

Unstimulated whole saliva, a first, and a second oral rinse were sequentially taken from 95 consecutive adults. aMMP-8 was quantitatively determined with a lateral flow immunoassay (index test). A full-mouth periodontal examination was used to establish a diagnosis according to the 2017 World Workshop classification of periodontal diseases (reference standard). Diagnostic measures of the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity were assessed and compared.

RESULTS

In all oral fluid samples, periodontitis patients (N = 61) had significantly elevated aMMP-8 levels and increased test positivity rates compared with subjects with periodontal health or gingivitis (N = 34). The intra-individual comparison showed that aMMP-8 levels were significantly higher in 1st oral rinse compared with other samples (1^st oral rinse > saliva = 2^nd oral rinse, p = .007). The aMMP-8 test using 1st oral rinse exhibited the best accuracy for detecting periodontitis with a sensitivity of 80.3%, a specificity of 67.8% and an AUROC of 0.740.

CONCLUSIONS

A 30-second oral rinse with water omitting the prerinse provided the best accuracy to discriminate periodontal health and disease with an aMMP-8 POCT. This regimen seems promising for further studies in large representative populations to verify the current findings.

Effect of Non-surgical Periodontal Treatment on Salivary and Serum Biomarkers in Stage III Grade B and C Periodontitis

BACKGROUND

This study aimed to evaluate the levels of total matrix metalloproteinase-8 (MMP-8), macrophage-activating factors (MAF), macrophage inflammatory protein (MIP)-1α, macrophage colony-stimulating factor (M-CSF), interleukin (IL)-34 in saliva and serum of periodontally healthy, periodontitis stage III grade B (P-III-B) and grade C (P-III-C) participants and to compare the changes after non-surgical periodontal treatment (NSPT).

METHODS

A total of non-smoker and systemically healthy 65 participants, 20 periodontally healthy, 20 P-III-B, and 25 P-III-C were recruited for the study. The periodontal parameters were recorded, saliva and serum samples were obtained from all participants at baseline. In periodontitis groups, the periodontal parameters were reevaluated, and the samples were recollected at 1 and 3 months following the NSPT. MMP-8, MAF, MIP-1α, M-CSF, and IL34 levels were measured by ELISA. Receiver operating characteristics curve was performed for estimating the area under the curve (AUC).

RESULTS

All periodontal parameters were improved in periodontitis groups after NSPT (p<0.05). Among tested molecules, salivary MMP-8 and MAF were higher in both periodontitis groups compared to healthy controls (p<0.05) at baseline and significantly decreased after NSPT (p<0.05) to healthy levels or below. Salivary MMP-8 had the highest diagnostic ability both for P-III-B (AUC:0.78 sensitivity: 80%; specificity: 80%) and P-III-C (AUC:0.88 sensitivity: 88%; specificity: 80%). Moreover, after adjusting for age, periodontitis groups were associated with salivary MMP-8 and MAF levels (p<0.05).

CONCLUSION

The present study showed that high salivary MMP-8 and MAF levels were associated with non-smoker, systemically healthy P-III-B and P-III-C. Moreover, NSPT was remarkably reduced their levels. This article is protected by copyright. All rights reserved.

Increasing oral PMN during experimental gingivitis and its reversal by prophylaxis

This investigation evaluated clinical parameters and the levels of polymorphonuclear leukocytes [PMN] collected in an oral rinse amongst subjects who refrained from dental hygiene for a period of 12 days.

Methods

Study enrolled consenting adults and assigned to a non-prophy group [n = 16] and a separate prophy group [n = 27]. Both groups underwent clinical evaluations and sampling for PMN at baseline and on days 3,6,9 and 12 of study initiation. The prophy group underwent supragingival prophylaxis at the conclusion of the no-hygiene phase and recalled for a final clinical evaluation and PMN assessment 1 week later.

Results

Progressive increases in oral PMN were noted due to abstinence from oral hygiene (p < 0.05). Subjects registered PMN increases ranging from 20% recorded three days following abstinence of hygiene to the highest value of 298% at the 12-day evaluation (p < 0.05). One week after prophylaxis, average PMN scores were 22% lower than baseline (p < 0.05). Abstinence from dental hygiene led to progressive increases in clinical parameters for dental plaque, gingival inflammation and bleeding. Dental plaque, gingival index and gingival bleeding scores recorded increases of 59%, 64% and 126% respectively at the conclusion of the no-hygiene phase. Prophylaxis resulted in marked reductions in all clinical parameters.

Conclusions

Abstinence from dental hygiene corresponded with increasing scores for dental plaque, gingival inflammation and bleeding in conjunction with increasing oral PMN. These effects were irrespective of age or gender and were reversed by supragingival prophylaxis.

Minimally Invasive Periodontology: A Treatment Philosophy and Suggested Approach

Severe periodontitis is a highly prevalent dental disease. With the advent of implant dentistry, teeth are often extracted and replaced. Periodontal surgery, where indicated, could also result in increased trauma to the patient. This literature review discusses different treatment modalities for periodontitis and proposes a treatment approach emphasizing maximum preservation of teeth while minimizing morbidity to the patient. Scientific articles were retrieved from the MEDLINE/PubMed database up to January 2021 to identify appropriate articles that addressed the objectives of this review. This was supplemented with hand searching using reference lists from relevant articles. As tooth prognostication does not have a high predictive value, a more conservative approach in extracting teeth should be abided by. This may involve repeated rounds of nonsurgical periodontal therapy, and adjuncts such as locally delivered statin gels and subantimicrobial-dose doxycycline appear to be effective. Periodontal surgery should not be carried out at an early phase in therapy as improvements in nonsurgical therapy may be observed up to 12 months from initial treatment. Periodontal surgery, where indicated, should also be minimally invasive, with periodontal regeneration being shown to be effective over 20 years of follow-up. Biomarkers provide an opportunity for early detection of disease activity and personalised treatment. Quality of life is proposed as an alternative end point to the traditional biomedical paradigm focused on the disease state and clinical outcomes. In summary, minimally invasive therapy aims to preserve health and function of the natural dentition, thus improving the quality of life for patients with periodontitis.

Functionalized Mouth-Conformable Interfaces for pH Evaluation of the Oral Cavity

Oral health monitoring is highly desired, especially for in home use, however, current methods are not sensitive enough and technically convoluted for this purpose. This paper presents incorporation of bioactive materials and colorimetric chemical sensors into routinely used oral appliances transforming them into bioresponsive, conformable interfaces. Specifically, endodontic paper points and dental floss can be functionalized to locally sense and monitor pH variations within the oral cavity via color changes. Moreover, edible colorimetric indicators are developed and used to make sensing, edible devices in the form factor of candies that can dynamically and visually respond to acidity changes in saliva. These interfaces would enable early detection of caries (e.g., using dental floss and paper points) providing low-cost point of care devices that respond in real-time by detecting pH variations in biological fluids thus bringing monitoring to home settings .

The potential impact of salivary peptides in periodontitis

Periodontitis is a complex immune-inflammatory condition characterized by the disruption of the periodontal ligament and subsequent formation of periodontal pockets, and by alveolar bone loss, often resulting in tooth loss. A myriad of factors, namely, genetic, metabolic, immunological, and inflammatory, is associated with progression of periodontitis. Periodontitis is also associated with systemic conditions such as neoplastic disorders, obesity, and diabetes. The current diagnosis of this disease relies on clinical measurements such as clinical attachment loss and probing depth, which have poor precision due to patient, operator and probe-related factors. Thus, there is a need to develop reliable, objective, and reproducible biomarkers for early diagnosis of periodontitis. In this regard, saliva, with contributions from the gingival crevicular fluid, holds great potential. However, most of the information on biomarkers of periodontium-related salivary proteins has come from studies on the molecular pathogenesis of periodontitis. In periodontitis, a more holistic approach, such as the use of -omics technologies, for biomarker discovery, is needed. Herein, we review the biomarkers proposed to date for the assessment of periodontitis, with emphasis on the role of salivary peptides in periodontitis and their assessment by high-throughput saliva proteomics. We also discuss the challenges pertaining to the identification of new periodontitis biomarkers in saliva.

Salivary Biomarkers for Dental Caries Detection and Personalized Monitoring

This study investigated the potential of salivary bacterial and protein markers for evaluating the disease status in healthy individuals or patients with gingivitis or caries. Saliva samples from caries- and gingivitis-free individuals (n = 18), patients with gingivitis (n = 17), or patients with deep caries lesions (n = 38) were collected and analyzed for 44 candidate biomarkers (cytokines, chemokines, growth factors, matrix metalloproteinases, a metallopeptidase inhibitor, proteolytic enzymes, and selected oral bacteria). The resulting data were subjected to principal component analysis and used as a training set for random forest (RF) modeling. This computational analysis revealed four biomarkers (IL-4, IL-13, IL-2-RA, and eotaxin/CCL11) to be of high importance for the correct depiction of caries in 37 of 38 patients. The RF model was then used to classify 10 subjects (five caries-/gingivitis-free and five with caries), who were followed over a period of six months. The results were compared to the clinical assessments of dental specialists, revealing a high correlation between the RF prediction and the clinical classification. Due to the superior sensitivity of the RF model, there was a divergence in the prediction of two caries and four caries-/gingivitis-free subjects. These findings suggest IL-4, IL-13, IL-2-RA, and eotaxin/CCL11 as potential salivary biomarkers for identifying noninvasive caries. Furthermore, we suggest a potential association between JAK/STAT signaling and dental caries onset and progression.

Metabolomics of gingival crevicular fluid to identify biomarkers for periodontitis: A systematic review with meta-analysis

The present systematic review aimed to examine periodontitis-specific biomarkers in the gingival crevicular fluid (GCF) that could have a diagnostic relevance, and to provide a qualitative assessment of the current literature. Metabolites are reliable indicators of pathophysiological statuses, and their quantification in the GCF can provide an outlook of the changes associated with periodontitis and have diagnostic value. Relevant studies identified from PubMed, Embase, Cochrane Library, and Scopus databases were examined to answer the following PECO question: "In systemically healthy individuals, can concentration of specific metabolites in the GCF be used to discriminate subjects with healthy periodontium (H) or gingivitis from patients with periodontitis (P) and which is the diagnostic accuracy?" Quality of included studies was rated using a modified version of the QUADOMICS tool. Meta-analysis was conducted whenever possible. After the screening of 1,554 titles, 15 studies were selected, with sample size ranging from 30 to 93 subjects. Eleven studies performed targeted metabolomics analysis and provided data for 10 metabolites. Among the most consistent markers, malondialdehyde levels were found higher in the P group compared with H group (SMD = 2.86; 95% CI: 1.64, 4.08). Also, a significant increase of 8-hydroxy-deoxyguanosine, 4-hydroxynonenal, and neopterin was detected in periodontally diseased sites, while glutathione showed an inverse trend. When considering data from untargeted metabolomic analysis in four studies, more than 40 metabolites were found significantly discriminant, mainly related to amino acids and lipids degradation pathways. Notably, only one study reported measures of diagnostic accuracy. Several metabolites were differentially expressed in GCF of subjects across different periodontal conditions, having a major potential for investigating periodontal pathophysiology and for site-specific diagnosis. Oxidative stress-related molecules, such as malondialdehyde and 8-hydroxy-deoxyguanosine, were the most consistently associated to periodontitis (PROSPERO CRD42020188482).

Intra-individual cytokine profile in peri-implantitis and periodontitis: A cross-sectional study

AIM

To study cytokine profiles and intra-individual correlations in crevicular fluid samples at periodontitis, peri-implantitis, and healthy sites.

MATERIALS AND METHODS

Samples from gingival crevicular fluid (GCF) and peri-implant crevicular fluid (PICF) were collected from healthy and diseased sites in patients who had had dental implants for a minimum of 10 years. Cytokine levels were analyzed using the Bio-Plex Pro Human inflammation kit, which included biomarkers for the tumor necrosis factor-α (TNF-α) superfamily, regulatory T Cell (Treg) cytokines, and interferon (IFN) proteins.

RESULTS

Gingival crevicular fluid/PICF cytokine levels, determined in samples from 163 patients, were frequently lower for healthy tooth and implant sites compared to sites with periodontitis or peri-implantitis. In contrast, there were no significant differences in cytokine levels between peri-implant sites and periodontitis sites. Intra-individual correlations between cytokines at peri-implant sites were frequently significant. In addition, the cytokines IFN-λ1 and TNFSF12 were significantly correlated with the presence of peri-implantitis.

CONCLUSION

Within the limits of this study, the intra-individual cytokine profile did not differ between sites diagnosed with periodontitis and those diagnosed with peri-implantitis, but did differ between healthy tooth and healthy implant sites. Studying intra-individual cytokine profiles is a method to elucidate possible differences between the etiopathogeneses of periodontitis and peri-implantitis, since it is well known that immune responses to dysbiosis vary between individuals according to host factors. Thus, the findings of the present study are potentially relevant to the advancement of knowledge in this field.

A Roadmap towards Precision Periodontics

Periodontitis is among the most common health conditions and represents a major public health issue related to increasing prevalence and seriously negative socioeconomic impacts. Periodontitis-associated low-grade systemic inflammation and its pathological interplay with systemic conditions additionally raises awareness on the necessity for highly performant strategies for the prevention and management of periodontitis. Periodontal diagnosis is the backbone of a successful periodontal strategy, since prevention and treatment plans depend on the accuracy and precision of the respective diagnostics. Periodontal diagnostics is still founded on clinical and radiological parameters that provide limited therapeutic guidance due to the multifactorial complexity of periodontal pathology, which is why biomarkers have been introduced for the first time in the new classification of periodontal and peri-implant conditions as a first step towards precision periodontics. Since the driving forces of precision medicine are represented by biomarkers and machine learning algorithms, with the lack of periodontal markers validated for diagnostic use, the implementation of a precision medicine approach in periodontology remains in the very initial stage. This narrative review elaborates the unmet diagnostic needs in periodontal diagnostics, the concept of precision periodontics, periodontal biomarkers, and a roadmap toward the implementation of a precision medicine approach in periodontal practice.

Evaluation of active matrix metalloproteinase-8 (aMMP-8) chair-side test as a diagnostic biomarker in the staging of periodontal diseases

OBJECTIVE

There is a need for a reliable complementary diagnostic tool that ideally helps to screen, differentiate sites, activities of and predict future periodontal tissue destruction. The purpose of this cross-sectional study was to investigate the screening and prevention potential of the chair-side/point-of-care (PoC) diagnostic test of salivary active matrix metalloproteinase-8 (aMMP-8) levels at different stages of periodontal disease and periodontal health.

MATERIAL & METHODS

80 individuals were included in this study; 18 with periodontitis stage 3 (P-Stage III), 19 with periodontitis stage-4 (P-Stage IV), 21 with gingivitis, and 22 with clinically healthy periodontium (H). The aMMP-8 levels in GCF and saliva were analyzed by chairside point-of-care aMMP-8 lateral flow immunotest and also by a time-resolved immunofluorescence assay (IFMA).

RESULTS

The sensitivity of the chair-side/PoC test was 83.9 % while specificity was 79.2 %. The aMMP-8 IFMA levels in GCF were significantly higher in P-Stage IV group than P-Stage III, gingivitis and healthy groups (p = 0.01, p = 0.001, p = 0.00, respectively). Moreover, P-Stage III and gingivitis groups had significantly higher aMMP-8 IFMA levels than the healthy group (p < 0.05).

CONCLUSION

The aMMP-8 chair-side test showed promising results in its ability to recognize and predict the inflammatory status even at the very initial/early stages. aMMP-8 chair-side test could be a valuable adjunctive diagnostic and preventive tool to conventional clinical methods in detecting periodontal disease.

Salivary metabolomics for the diagnosis of periodontal diseases: a systematic review with methodological quality assessment

INTRODUCTION

Early diagnosis of periodontitis by means of a rapid, accurate and non-invasive method is highly desirable to reduce the individual and epidemiological burden of this largely prevalent disease.

OBJECTIVES

The aims of the present systematic review were to examine potential salivary metabolic biomarkers and pathways associated to periodontitis, and to assess the accuracy of salivary untargeted metabolomics for the diagnosis of periodontal diseases.

METHODS

Relevant studies identified from MEDLINE (PubMed), Embase and Scopus databases were systematically examined for analytical protocols, metabolic biomarkers and results from the multivariate analysis (MVA). Pathway analysis was performed using the MetaboAnalyst online software and quality assessment by means of a modified version of the QUADOMICS tool.

RESULTS

Twelve studies met the inclusion criteria, with sample sizes ranging from 19 to 130 subjects. Compared to periodontally healthy individuals, valine, phenylalanine, isoleucine, tyrosine and butyrate were found upregulated in periodontitis patients in most studies; while lactate, pyruvate and N-acetyl groups were the most significantly expressed in healthy individuals. Metabolic pathways that resulted dysregulated are mainly implicated in inflammation, oxidative stress, immune activation and bacterial energetic metabolism. The findings from MVA revealed that periodontitis is characterized by a specific metabolic signature in saliva, with coefficients of determination ranging from 0.52 to 0.99.

CONCLUSIONS

This systematic review summarizes candidate metabolic biomarkers and pathways related to periodontitis, which may provide opportunities for the validation of diagnostic or predictive models and the discovery of novel targets for monitoring and treating such a disease (PROSPERO CRD42020188482).

Prediction of Chronic Periodontitis Severity Using Machine Learning Models Based On Salivary Bacterial Copy Number

Periodontitis is a widespread chronic inflammatory disease caused by interactions between periodontal bacteria and homeostasis in the host. We aimed to investigate the performance and reliability of machine learning models in predicting the severity of chronic periodontitis. Mouthwash samples from 692 subjects (144 healthy controls and 548 generalized chronic periodontitis patients) were collected, the genomic DNA was isolated, and the copy numbers of nine pathogens were measured using multiplex qPCR. The nine pathogens are as follows: Porphyromonas gingivalis (Pg), Tannerella forsythia (Tf), Treponema denticola (Td), Prevotella intermedia (Pi), Fusobacterium nucleatum (Fn), Campylobacter rectus (Cr), Aggregatibacter actinomycetemcomitans (Aa), Peptostreptococcus anaerobius (Pa), and Eikenella corrodens (Ec). By adding the species one by one in order of high accuracy to find the optimal combination of input features, we developed an algorithm that predicts the severity of periodontitis using four machine learning techniques. The accuracy was the highest when the models classified “healthy” and “moderate or severe” periodontitis (H vs. M-S, average accuracy of four models: 0.93, AUC = 0.96, sensitivity of 0.96, specificity of 0.81, and diagnostic odds ratio = 112.75). One or two red complex pathogens were used in three models to distinguish slight chronic periodontitis patients from healthy controls (average accuracy of 0.78, AUC = 0.82, sensitivity of 0.71, and specificity of 0.84, diagnostic odds ratio = 12.85). Although the overall accuracy was slightly reduced, the models showed reliability in predicting the severity of chronic periodontitis from 45 newly obtained samples. Our results suggest that a well-designed combination of salivary bacteria can be used as a biomarker for classifying between a periodontally healthy group and a chronic periodontitis group.

Biosensor and Lab-on-a-chip Biomarker-identifying Technologies for Oral and Periodontal Diseases

Periodontitis is a complex multifactorial disease that can lead to destruction of tooth supporting tissues and subsequent tooth loss. The most recent global burden of disease studies highlight that severe periodontitis is one of the most prevalent chronic inflammatory conditions affecting humans. Periodontitis risk is attributed to genetics, host-microbiome and environmental factors. Empirical diagnostic and prognostic systems have yet to be validated in the field of periodontics. Early diagnosis and intervention prevents periodontitis progression in most patients. Increased susceptibility and suboptimal control of modifiable risk factors can result in poor response to therapy, and relapse. The chronic immune-inflammatory response to microbial biofilms at the tooth or dental implant surface is associated with systemic conditions such as cardiovascular disease, diabetes or gastrointestinal diseases. Oral fluid-based biomarkers have demonstrated easy accessibility and potential as diagnostics for oral and systemic diseases, including the identification of SARS-CoV-2 in saliva. Advances in biotechnology have led to innovations in lab-on-a-chip and biosensors to interface with oral-based biomarker assessment. This review highlights new developments in oral biomarker discovery and their validation for clinical application to advance precision oral medicine through improved diagnosis, prognosis and patient stratification. Their potential to improve clinical outcomes of periodontitis and associated chronic conditions will benefit the dental and overall public health.

Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva

This study aims to investigate and assess salivary biomarkers and microbial profiles as a means of diagnosing periodontitis. A total of 121 subjects were included: 28 periodontally healthy subjects, 24 with Stage I periodontitis, 24 with Stage II, 23 with Stage III, and 22 with Stage IV. Salivary proteins (including active matrix metalloproteinase-8 (MMP-8), pro-MMP-8, total MMP-8, C-reactive protein, secretory immunoglobulin A) and planktonic bacteria (including Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Porphyromonas nigrescens, Parvimonas micra, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, Streptococcus mutans, Staphylococcus aureus, Enterococcus faecalis, and Actinomyces viscosus) were measured from salivary samples. The performance of the diagnostic models was assessed by receiver operating characteristics (ROCs) and area under the ROC curve (AUC) analysis. The diagnostic models were constructed based on the subjects’ proteins and/or microbial profiles, resulting in two potential diagnosis models that achieved better diagnostic powers, with an AUC value > 0.750 for the diagnosis of Stages II, III, and IV periodontitis (Model PA-I; AUC: 0.796, sensitivity: 0.754, specificity: 0.712) and for the diagnosis of Stages III and IV periodontitis (Model PA-II; AUC: 0.796, sensitivity: 0.756, specificity: 0.868). This study can contribute to screening for periodontitis based on salivary biomarkers.

Oral Neutrophils: Underestimated Players in Oral Cancer

The composition of the oral milieu reflects oral health. Saliva provides an environment for multiple microorganisms, and contains soluble factors and immune cells. Neutrophils, which rapidly react on the changes in the microenvironment, are a major immune cell population in saliva and thus may serve as a biomarker for oral pathologies. This review focuses on salivary neutrophils in the oral cavity, their phenotype changes in physiological and pathological conditions, as well as on factors regulating oral neutrophil amount, activation and functionality, with special emphasis on oral cancer and its risk factors.

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.

ICP-Mass-Spectrometry Ionic Profile of Whole Saliva in Patients with Untreated and Treated Periodontitis

Over the past decade, there has been growing interest in the association between macro and trace minerals in body fluids and systemic diseases related to chronic inflammation and oxidative stress. Due to the paucity of data in the literature on periodontitis, the aim of this cross-sectional study was to assess the relationship between mineral elements in saliva and periodontal status in patients with untreated and treated periodontitis compared to periodontally healthy controls. Salivary samples from 66 nonsmoker healthy patients (20 periodontally healthy, 24 untreated severe periodontitis and 22 treated severe periodontitis) were analyzed by using inductively coupled plasma mass-spectrometry (ICP-MS). Significant increases in copper (Cu), sodium (Na), iron (Fe) and manganese (Mn) concentrations occurred in saliva of severe periodontitis subjects compared to periodontally healthy controls. No differences were detected between healthy controls and treated periodontitis patients apart from levels of zinc (Zn) and lithium (Li) that were found to be increased and reduced, respectively, in periodontitis group. Most subjects were correctly separated by cluster analysis into active periodontitis and periodontally healthy individuals. Treated periodontitis individuals were classified as healthy subjects. Based on these preliminary results, the assessment of salivary concentration of mineral elements might be useful in discriminating periodontal health and disease.

Association between circulating tumor necrosis factor receptors and oral bacterium in patients receiving hemodialysis: a cross-sectional study

BACKGROUND

High levels of tumor necrosis factor (TNF) receptors (TNFRs; TNFR1 and TNFR2), markers of inflammation, have been reported as significant predictors of mortality in hemodialysis patients. Porphyromonas gingivalis is a major pathogenic bacterium involved in periodontitis, which induces systemic inflammation. We investigated the association between the abundance of P. gingivalis in saliva and serum TNFR levels in hemodialysis patients.

METHODS

A cross-sectional study was conducted on 121 hemodialysis patients visiting a clinic in the Tokyo metropolitan area. Medical interviews and examinations, comprehensive dental examinations, bacterial examinations for P. gingivalis in saliva, and measurements of circulating TNFR levels were conducted. Multiple linear regression analysis was performed to evaluate the association between the number of P. gingivalis and circulating TNFR levels.

RESULTS

TNFR1 and TNFR2 were positively correlated with high-sensitivity C-reactive protein (hsCRP). Severe periodontitis was significantly associated with the number of P. gingivalis in saliva but not serum TNFR levels. The number of P. gingivalis was significantly associated with both TNFR1 and TNFR2 levels in sera after adjusting for age, sex, body mass index, smoking status, history of diabetes, prior cardiovascular disease events, serum levels of hsCRP and albumin, and severity of periodontitis [for TNFR1: coefficient 0.76, 95% confidence interval (CI) 0.14-1.37, p = 0.02; for TNFR2: coefficient 0.95, 95% CI 0.09-1.80, p = 0.03].

CONCLUSION

Circulating TNFR levels are associated with the number of P. gingivalis in saliva after adjusting for relevant clinical factors.

aMMP-8 Point-of-Care/Chairside Oral Fluid Technology as a Rapid, Non-Invasive Tool for Periodontitis and Peri-Implantitis Screening in a Medical Care Setting

This communication article addresses currently available rapid non-invasive methods to screen and detect periodontitis and dental peri-implantitis. In this regard, oral fluid biomarkers have been researched extensively but self-reported oral health (SROH)-questionnaires have also been developed. Both alternatives may offer a quick and easy way to screen and detect diseased patients. Active matrix metalloproteinase (aMMP-8) is one of the most validated biomarkers for screening and detecting periodontal breakdown related to periodontitis and peri-implantitis and monitoring their treatment effects revealing successful, less- and non-successful treatment results. Currently available aMMP-8 lateral-flow technologies allow this kind of analysis, as demonstrated here, to be conducted quantitatively online and real-time as point-of-care/chairside testing in dental and even medical care settings. In this study, an aMMP-8 peri-implant sulcular fluid point-of-care-test diagnosed peri-implantitis and healthy implants far more accurately than bleeding-on-probing or the other biomarkers, such as polymorphonuclear (PMN)/neutrophil elastase, myeloperoxidase and MMP-9. Although, SROH-questionnaires allow screening in similar settings but they lack the information about the current disease activity of periodontitis and peri-implantitis, which is of essential value in periodontal diagnostics and treatment monitoring. Thus, both methods can be considered as adjunct methods for periodontitis and peri-implant diagnostics, but the value of oral fluid biomarkers analysis does not seem to be substitutable.

Oral Fluid Biomarkers for Diagnosing Gingivitis in Human: A Cross-Sectional Study

Diagnoses based on oral fluid biomarkers have been introduced to overcome limitations of periodontal probe-based diagnoses. Diagnostic ability of certain biomarkers for periodontitis have been identified and widely studied, however, such studies targeting gingivitis is scarce. The aims of this study were to determine and compare the efficacies and accuracies of eight biomarkers in diagnosing gingivitis with the aid of receiver operating characteristic (ROC) curves. The probing depth (PD), clinical attachment loss (CAL), bleeding on probing (BOP), gingival index (GI), and plaque index (PI) were examined in 100 participants. Gingival crevicular fluid was collected using paper points, and whole-saliva samples were collected using cotton roll. Samples were analyzed using enzyme-linked immunosorbent assay kits for the different biomarkers. The levels of matrix metalloproteinase (MMP)-8, MMP-9, lactoferrin, cystatin C, myeloperoxidase (MPO), platelet-activating factor, cathepsin B, and pyridinoline cross-linked carboxyterminal telopeptide of type I collagen were analyzed. MPO and MMP-8 levels in saliva were strongly correlated with gingivitis, with Pearson’s correlation coefficients of 0.399 and 0.217, respectively. The area under the curve (AUC) was largest for MMP-8, at 0.814, followed by values of 0.793 and 0.777 for MPO and MMP-9, respectively. The clinical parameters of GI and PI showed strong correlations and large AUC values, whereas PD and CAL did not. MMP-8 and MPO were found to be effective for diagnosing gingivitis. Further investigations based on the results of this study may identify clinically useful biomarkers for the accurate and early detection of gingivitis.

Epigenetic reprogramming in periodontal disease: Dynamic crosstalk with potential impact in oncogenesis

Periodontitis is a chronic multifactorial inflammatory disease associated with microbial dysbiosis and characterized by progressive destruction of the periodontal tissues. Such chronic infectious inflammatory disease is recognized as a major public health problem worldwide with measurable impact in systemic health. It has become evident that the periodontal disease phenotypes are not only determined by the microbiome effect, but the extent of the tissue response is also driven by the host genome and epigenome patterns responding to various environmental exposures. More recently there is mounting evidence indicating that epigenetic reprogramming in response to combined intrinsic and environmental exposures, might be particularly relevant due its plasticity and potential application towards precision health. The complex epigenetic crosstalk is reflected in the prognosis and progress of periodontal diseases and may also lead to a favorable landscape for cancer development. This review discusses epigenomics modifications focusing on the role of DNA methylation and pathways linking microbial infection and inflammatory pathways, which are also associated with carcinogenesis. There is a more clear vision whereas 'omics' technologies applied to unveil relevant epigenetic factors could play a significant role in the treatment of periodontal disease in a personalized mode, evidencing that public health approach should coexist with precision individualized treatment.

Bone Turnover Markers in Chronic Periodontitis: A Literature Review

Chronic periodontitis (CP) is a multifactorial oral inflammatory disease characterized by progressive destruction of bone and ultimate tooth loss. The alarming rise in the prevalence of periodontitis has led to the development of innovative diagnostic techniques. Several quantifiable biomarkers in the gingival crevicular fluid (GCF) and saliva of chronic periodontitis patients have been detected in the field of oral fluid diagnostics. Bone turnover biomarkers hold a valuable diagnostic potential in determining the extent of alveolar bone destruction and the risk of future bone loss. This review article highlights the importance of bone turnover markers in facilitating earlier detection, accurate diagnosis, and effective treatment strategies, leading to optimal clinical management of chronic periodontitis.

Salivary neuropeptides, stress, and periodontitis

BACKGROUND

Scientific evidence for psychologic stress as a risk factor for periodontitis is fragmentary and relies mostly on either questionnaire-based or biomarker studies. The aim of this study is to investigate brain-derived neurotrophic factor, substance P, vasoactive intestinal peptide (VIP), neuropeptide Y (NPY), calcitonin gene-related peptide, and adrenomedullin as well as cortisol in saliva and serum in periodontal health and disease combined with different aspects of stress and possible associations with clinical parameters.

METHODS

In total, 56 patients with aggressive and chronic periodontitis and 44 healthy controls were screened by enzyme-linked immunosorbent assay and mass spectrometry for presence of neuropeptides and cortisol in saliva and serum. Psychologic stress was evaluated by validated questionnaires. All substances were explored for a possible relationship to periodontitis, clinical parameters, and stress.

RESULTS

VIP and NPY showed significantly higher levels in saliva but not in serum of patients with periodontitis. These neuropeptides correlated with the extent, severity, and bleeding on probing scores in patients with periodontitis. Females had significantly lower salivary VIP levels. There were no differences among participants regarding psychologic stress.

CONCLUSION

VIP and NPY in saliva could be potential sex-specific salivary biomarkers for periodontitis regardless of psychologic stress.

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.

Salivary levels of specialized pro-resolving lipid mediators as indicators of periodontal health/disease status

AIM

This cross-sectional case-control study aimed to determine if salivary levels of lipoxin A4 (LXA4), protectin D1 (PD1), resolvin E1 (RvE1) and maresin 1 (MaR1) might constitute a reflection of periodontal health/disease status.

MATERIALS AND METHODS

One hundred and two periodontitis patients and 61 healthy controls were recruited. Periodontal clinical status was determined by criteria based on full-mouth clinico-radiographical data. Salivary concentration of the analytes was calculated by enzyme-linked immunosorbent assay. The association between the biomarkers with disease status was assessed individually and adjusted for confounding using multivariate binary logistic regression models.

RESULTS

Significantly decreased LXA4 and increased PD1/MaR1 salivary levels were detected in periodontitis patients in comparison with healthy controls. However, no significant differences were observed for RvE1 levels between clinical groups. Clinical parameters such as probing depth, clinical attachment loss and extent were negatively correlated with LXA4, positively correlated with PD1/MaR1 and not correlated with RvE1 salivary levels. Logistic regression analyses revealed a strong/independent association of LXA4, PD1 and MaR1 salivary levels regarding disease status. Interaction effects between demographic predictor variables and salivary concentration of LXA4, PD1 and MaR1 were also identified.

CONCLUSION

The results of this study demonstrated a strong/independent association between reduced LXA4 and increased PD1/MaR1 salivary levels with periodontitis suggesting an imbalance in the specialized pro-resolving lipid mediators (SPMs) in periodontal disease.

Increased Risk of Polycystic Ovary Syndrome in Taiwanese Women with Chronic Periodontitis: A Nationwide Population-Based Retrospective Cohort Study

Background: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders among women of reproductive age. Both hormonal and inflammatory influences are assumed to affect periodontal tissues. Previous studies have shown that PCOS patients could have higher prevalence of gingival inflammation. However, the relationship between PCOS and chronic periodontitis (CP) is not clear. Materials and Methods: In this study, we evaluated the risk of PCOS from CP exposure in a nationwide population-based retrospective cohort study in Taiwan. We studied the claims data of Taiwanese population from 2001 to 2012. The 24,410 female patients with CP were identified from the National Health Insurance Database. The 24,410 controls were selected with randomly frequency matched by age, sex, and index year from the general population. The risk of PCOS was analyzed by Cox proportional hazards regression models, including sex, age, and comorbidities. Results: In this study, 24,410 female patients with CP (mean age: 35.14 ± 8.81 years) and 24,410 controls (mean age: 35.14 ± 8.8 years) were observed for 8.89 and 8.85 years, respectively. A total of 441 cases of PCOS were identified in CP cohort and 304 cases in non-CP cohort. Multivariate Cox regression analysis indicated that the incidence rate of PCOS was significantly higher in CP cohort than those in non-CP cohort (adjusted hazard ratio: 1.44, 95% confidence interval: 1.24-1.67). Conclusions: Taken together, this nationwide retrospective cohort study demonstrated that the risk of PCOS was significantly higher in female patients with CP than those without CP in Taiwan.

A rapid, non-invasive tool for periodontitis screening in a medical care setting

BACKGROUND

Since periodontitis is bi-directionally associated with several systemic diseases, such as diabetes mellitus and cardiovascular diseases, it is important for medical professionals in a non-dental setting to be able examine their patients for symptoms of periodontitis, and urge them to visit a dentist if necessary. However, they often lack the time, knowledge and resources to do so. We aim to develop and assess "quick and easy" screening tools for periodontitis, based on self-reported oral health (SROH), demographics and/or salivary biomarkers, intended for use by medical professionals in a non-dental setting.

METHODS

Consecutive, new patients from our outpatient clinic were recruited. A SROH questionnaire (8 questions) was conducted, followed by a 30 s oral rinse sampling protocol. A complete clinical periodontal examination provided the golden standard periodontitis classification: no/mild, moderate or severe periodontitis. Total periodontitis was defined as having either moderate or severe. Albumin and matrix metalloproteinase-8 concentrations, and chitinase and protease activities were measured in the oral rinses. Binary logistic regression analyses with backward elimination were used to create prediction models for both total and severe periodontitis. Model 1 included SROH, demographics and biomarkers. The biomarkers were omitted in the analysis for model 2, while model 3 only included the SROH questionnaire. The area under the receiver operating characteristic curves (AUROCC) provided the accuracy of each model. The regression equations were used to create scoring algorithms, composed of the remaining predictors, each with its own weight.

RESULTS

Of the 156 patients participating in this study, 67% were classified with total periodontitis and 33% had severe periodontitis. The models for total periodontitis achieved an AUROCC of 0.91 for model 1, 0.88 for model 2 and 0.81 for model 3. For severe periodontitis, this was 0.89 for model 1, 0.82 for model 2 and 0.78 for model 3. The algorithm for total periodontitis (model 2), which we consider valid for the Dutch population, was applied to create a freely accessible, web-based screening tool.

CONCLUSIONS

The prediction models for total and severe periodontitis proved to be feasible and accurate, resulting in easily applicable screening tools, intended for a non-dental setting.