Translational and clinical applications of salivary diagnostics

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.

Saliva sampling method influences oral microbiome composition and taxa distribution associated with oral diseases

Saliva is a readily accessible and inexpensive biological specimen that enables investigation of the oral microbiome, which can serve as a biomarker of oral and systemic health. There are two routine approaches to collect saliva, stimulated and unstimulated; however, there is no consensus on how sampling method influences oral microbiome metrics. In this study, we analyzed paired saliva samples (unstimulated and stimulated) from 88 individuals, aged 7-18 years. Using 16S rRNA gene sequencing, we investigated the differences in bacterial microbiome composition between sample types and determined how sampling method affects the distribution of taxa associated with untreated dental caries and gingivitis. Our analyses indicated significant differences in microbiome composition between the sample types. Both sampling methods were able to detect significant differences in microbiome composition between healthy subjects and subjects with untreated caries. However, only stimulated saliva revealed a significant association between microbiome diversity and composition in individuals with diagnosed gingivitis. Furthermore, taxa previously associated with dental caries and gingivitis were preferentially enriched in individuals with each respective disease only in stimulated saliva. Our study suggests that stimulated saliva provides a more nuanced readout of microbiome composition and taxa distribution associated with untreated dental caries and gingivitis compared to unstimulated saliva.

Proteomic Analysis of Salivary Extracellular Vesicles from COVID-19 Patients Reveals a Specific Anti-COVID-19 Response Protein Signature

Despite the understanding of the coronavirus disease-19 (COVID-19), the role of salivary extracellular vesicles (sEVs) in COVID-19 remains unclear. Exploring the proteomic cargo of sEVs could prove valuable for diagnostic and prognostic purposes in assessing COVID-19. The proteomic cargo of sEVs from COVID-19(+) subjects and their healthy close contacts (HCC) was explored. sEVs were isolated by ultracentrifugation from unstimulated saliva samples, and subsequently characterized through nanoparticle tracking, transmission electron microscopy, and Western blot analyses. The proteomic cargo of sEVs was processed by LC-MS/MS. sEVs were morphologically compatible with EVs, with the presence of Syntenin-1 and CD81 EV markers. The sEV pellet showed 1417 proteins: 1288 in COVID-19(+) cases and 1382 in HCC. In total, 124 proteins were differentially expressed in sEVs from COVID-19(+) subjects. "Coronavirus-disease response", "complement and coagulation cascades", and "PMN extracellular trap formation" were the most enriched KEGG pathways in COVID-19(+) cases. The most represented biological processes were "Hemoglobin and haptoglobin binding" and "oxygen carrier activity", and the best-denoted molecular functions were "regulated exocytosis and secretion" and "leucocyte and PMN mediated immunity". sEV proteomic cargo in COVID-19(+) suggests activity related to immune response processes, oxygen transport, and antioxidant mechanisms. In contrast, in HCC, sEV signature profiles are mainly associated with epithelial homeostasis.

Investigating the role of salivary Interleukin-40 levels in diagnosing periodontal diseases

BACKGROUND

The present study aimed to analyze IL-40, IL-1β, and MMP-8 levels in periodontitis as well as gingivitis and periodontal health, and to explore potential correlations between these biomarkers and standard clinical parameters.

MATERIALS AND METHODS

We collected saliva samples from 120 systemically healthy, non-smoking individuals aged between 18 and 63 years. These individuals were divided into three groups: healthy controls [S], gingivitis [G], and stage III grade B periodontitis [P]. IL-40, IL-1β, and MMP-8 levels in saliva samples were analyzed by ELISA.

RESULTS

We observed significantly elevated salivary IL-40 levels in the G group compared to the S group (p = 0.003). We found significantly higher salivary IL-1β levels in the P group compared to both the S and G groups (p = 0.000). Salivary MMP-8 levels were significantly higher in the P group than in the S group (p = 0.016).

CONCLUSION

Our study suggests that IL-40 and IL-1β may serve as effective salivary biomarkers for diagnosing gingivitis, while MMP-8 and IL-1β may be effective for distinguishing periodontitis. Based on our study's findings, it can be stated that IL-40 may serve as a new and effective biomarker for distinguishing individuals with gingivitis from healthy ones.

Beyond the effects of HIV infection and integrase inhibitors-based therapies on oral bacteriome

Oral microbiome is the second largest microbial community in humans after gut. Human immunodeficiency virus (HIV) infection triggers an impairment of the immune system which could favour the growth and the colonization of pathogens in the oral cavity, and this dysbiosis has been associated with oral manifestations that worsen the quality of life of these patients. Antiretroviral therapy (ART) could also drive changes in specific oral bacterial taxa associated with such periodontal diseases. Integrase strand transfer inhibitors (INSTIs), therapy of choice in the treatment of naive HIV-patients, are able to reverse the impact of HIV infection on systemic inflammation, gut permeability, and gut bacterial diversity/richness. The objective of this study was to analyse the effects of HIV infection per se and INSTIs on salivary bacteriome composition, taking into consideration other factors such as smoking, that could also have a significant impact on oral microbiome. To accomplish this objective, 26 non-HIV-infected volunteers and 30 HIV-infected patients (15 naive and 15 under INSTIs-regimen) were recruited. Salivary samples were collected to measure lysozyme levels. Oral bacteriome composition was analysed using 16S rRNA gene sequencing. Naive HIV-infected patients showed statistically higher levels of lysozyme compared to controls (p < 0.001) and INSTIs-treated patients (p < 0.05). Our study was unable to detect differences in α nor β-diversity among the three groups analysed, although significant differences in the abundance of some bacterial taxonomical orders were detected (higher abundance in the phylum Pseudomonadota, in the order Acholeplasmatales, and in the genera Ezakiella and Acholeplasma in the naive group compared to controls; and higher abundance in the phylum Mycoplasmatota, in the order Acholeplasmatales, and in the genera Acholeplasma and uncultured Eubacteriaceae bacterium in the INTIs-treated HIV-infected patients compared to controls). These differences seem to be partially independent of smoking habit. HIV infection and INSTIs effects on oral microbiota seem not to be very potent, probably due to the modulation of other factors such as smoking and the greatest outward exposure of the oral cavity.

Current Molecular, Cellular and Genetic Aspects of Peri-Implantitis Disease: A Narrative Review

(1) Background: Peri-implantitis is a multi-factorial disease with an inflammatory background that occurs in both soft and hard tissues surrounding implants. In recent years, the understanding of the cellular, molecular and genetic background of peri-implantitis has broadened. This study aims to summarize the currently available articles on the subject and highlight the most recent advances over the last 20 years. (2) Methods: For this study, the Embase and PubMed libraries were searched using the keywords: ("peri-implantitis" AND "cytokine" OR "genetics" OR "cellular") and ("peri-implantitis" AND "cytokine" OR "genetics" OR "cellular" AND "risk factors"). The search revealed a total of 3013 articles (992 from PubMed, 2021 from Embase). Following screening of the titles and abstracts and full-text reads, 55 articles were included. (3) Results: In peri-implantitis IL-6, IL-1β, TNF-α, MMP-8 and their genetic variations appear to be the most important cytokines in relation to not only pathogenesis, but also their potential diagnostic capabilities. Epithelial and inflammatory cells, along with those of the bone lineage, are prime cellular elements found in peri-implantitis. (4) Conclusions: A wide array of cells stand behind peri-implantitis, as well as cytokines and their genetic variations that take part in the process. However, the growing interest in this topic has led to the introduction of specific new diagnostic tools to enable a better understanding of patients' responses to treatment and, in turn, to even enable prediction of the risk of developing peri-implant disease.

Salivary leukocyte esterase activity by SillHa is a risk indicator of periodontal disease

BACKGROUND

There is increasing evidence that diagnostic salivary tests measuring inflammatory biomarkers are being developed to assess inflammatory status for early detection, prevention, and progression of periodontal disease. Therefore, the aim of the present study was to investigate and identify the salivary biomarker that can predict the inflammatory status of periodontal disease.

METHODS

A total of 36 patients (28 women and 8 men) with an average age of 57 years were investigated. Unstimulated saliva was collected from the recruited subjects and analyzed using SillHa, a saliva-testing device that measures bacteria count, saliva buffer capacity, acidity, leukocyte esterase, protein, and ammonia. Periodontal parameters were then obtained by clinical examination and initial periodontal therapy was performed. Data obtained with SillHa were compared with clinical periodontal parameters at baseline, re-examination (three months from baseline), and final examination (six months from re-examination).

RESULTS

Leukocyte esterase activity in saliva measured by SillHa; BOP and PCR measured by clinical examination showed a significant difference between baseline and final examination and between re-examination and final examination. Patients in the lower median group (group 1) had a significant difference in leukocyte esterase activity between baseline and final examination and re-examination and final examination. In addition, patients in Group 1 had significantly lower BOP between baseline and final examination. While patients in the higher median group (group 2) showed a modest decrease in leukocyte esterase activity, which was significant only between baseline and final examination, no significant changes were observed concerning BOP. Furthermore, the associated systemic disease was observed in 30% and 81.2% of group 1 and 2 patients, respectively.

CONCLUSION

The results suggest that leukocyte esterase activity in saliva measured by SillHa could serve as a reliable diagnostic marker for monitoring inflammatory status in periodontal disease.

A two-minute assay for electronic quantification of antibodies in saliva enabled through a reusable microfluidic multi-frequency impedance cytometer and machine learning analysis

The use of saliva as a diagnostic fluid has always been appealing due to the ability for rapid and non-invasive sampling for monitoring health status and the onset and progression of disease and treatment progress. Saliva is rich in protein biomarkers and provides a wealth of information for diagnosis and prognosis of various disease conditions. Portable electronic tools which rapidly monitor protein biomarkers would facilitate point-of-care diagnosis and monitoring of various health conditions. For example, the detection of antibodies in saliva can enable rapid diagnosis and tracking disease pathogenesis of various auto-immune diseases like sepsis. Here, we present a novel method involving immuno-capture of proteins on antibody coated beads and electrical detection of dielectric properties of the beads. The changes in electrical properties of a bead when capturing proteins are extremely complex and difficult to model physically in an accurate manner. The ability to measure impedance of thousands of beads at multiple frequencies, however, allows for a data-driven approach for protein quantification. By moving from a physics driven approach to a data driven approach, we have developed, for the first time ever to the best of our knowledge, an electronic assay using a reusable microfluidic impedance cytometer chip in conjunction with supervised machine learning to quantifying immunoglobulins G (IgG) and immunoglobulins A (IgA) in saliva within two minutes.

Correlation between caries activity and salivary microbiota in preschool children

Early childhood caries (ECC) is the most common chronic infectious oral disease in preschool children worldwide. It is closely related to the caries activity (CA) of children. However, the distribution characteristics of oral saliva microbiomes in children with different CA are largely underexplored. The aim of this study was to investigate the microbial community in saliva of preschool children with different CA and caries status, and to analyze the difference of microbial community in saliva of children with different CA and its correlation with ECC. Subjects were divided into 3 groups based on the Cariostat caries activity test: Group H, high CA (n=30); Group M, medium CA (n = 30); Group L, low CA (n=30). Questionnaire survey was used to explore the related influencing factors of CA. According to the caries status (on the basis of decayed mising filled teeth), these subjects were divided into caries-free group (dmft=0, n=19), caries-low group (0 < dmft ≤ 4, n=27) and caries-high group (dmft > 4, n=44). Microbial profiles of oral saliva were analyzed using 16S rRNA gene sequencing. There were significant differences in the microbial structure (P < 0.05). Scardovia and Selenomonas were the biomarkers of both H group and high caries group. The genus Abiotrophia and Lautropia were the biomarkers of both the L group and the low caries group, while the Lactobacillus and Arthrospira spp. were significantly enriched in the M group. The area under the ROC curve of the combined application of dmft score, age, frequency of sugary beverage intake, and the genus Scardovia, Selenomonas, and Campylobacter in screening children with high CA was 0.842. Moreover, function prediction using the MetaCyc database showed that there were significant differences in 11 metabolic pathways of salivary microbiota among different CA groups. Certain bacteria genera in saliva such as Scardovia and Selenomonas may be helpful in screening children with high CA.

Microfluidics based point-of-care for disease diagnostics

Microfluidics platform is widely used for several basic biological to advanced biotechnological applications. It reduces the expenditure of reagent consumption by readily reducing the volume of the reaction system. It is being used for early diagnosis of diseases, detection of pathogens, cancer markers, high-throughput screening and many such applications. Currently, microfluidics and lab-on-chip is integrated together with sample preparation, extraction, analysis and detection of biomarkers for disease diagnosis. This technology offers low-cost, rapid, sensitive and paper-based lateral flow mode of detection which is user-friendly and scalable. In this chapter, we highlight recent developments in microfluidics platform for disease diagnosis.

Biochemical Interaction between Materials Used for Interim Prosthetic Restorations and Saliva

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

Anticholinergic medication: Related dry mouth and effects on the salivary glands

OBJECTIVE

Salivary glands are among the most sensitive target organs of medications with anticholinergic (AC) properties, interrupting the neural stimulation of saliva secretion and reducing saliva flow. Hyposalivation results in dry mouth, leading to dental caries, intraoral infection, orofacial pain, problems with speaking and swallowing, and diminished oral health--related quality of life. Current understanding of the pharmacokinetics of AC medications and their effect on muscarinic receptors in the salivary glands were reviewed to assist clinicians in predicting salivary damage in patients with AC medication-induced dry mouth.

STUDY DESIGN

We summarized the literature related to the mechanisms and properties of AC medications, anticholinergic adverse effects, and their effect on salivary function and management strategies to prevent oral health damage.

RESULTS

Although a large number of studies reported on the frequencies of medication-induced dry mouth, we found very limited data on predicting individual susceptibility to AC medication--caused hyposalivation and no prospective clinical studies addressing this issue.

CONCLUSION

Dry mouth is most frequently caused by medications with AC properties, which interrupt the neural stimulation of saliva secretion. Interdisciplinary care should guide pharmacotherapeutics and dental interventions should aim in preventing AC salivary adverse effects and reducing the oral health burden from AC medication-induced dry mouth.

Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting

BACKGROUND

Periodontitis is among the most common chronic diseases worldwide, and it is one of the main reasons for tooth loss. Comprehensive profiling of the metabolite content of the saliva can enable the identification of novel pathways associated with periodontitis and highlight non-invasive markers to facilitate time and cost-effective screening efforts for the presence of periodontitis and the prediction of tooth loss.

METHODS

We first investigated cross-sectional associations of 13 oral health variables with saliva levels of 562 metabolites, measured by untargeted mass spectrometry among a sub-sample (n = 938) of the Study of Health in Pomerania (SHIP-2) using linear regression models adjusting for common confounders. We took forward any candidate metabolite associated with at least two oral variables, to test for an association with a 5-year tooth loss over and above baseline oral health status using negative binomial regression models.

RESULTS

We identified 84 saliva metabolites that were associated with at least one oral variable cross-sectionally, for a subset of which we observed robust replication in an independent study. Out of 34 metabolites associated with more than two oral variables, baseline saliva levels of nine metabolites were positively associated with a 5-year tooth loss. Across all analyses, the metabolites 2-pyrrolidineacetic acid and butyrylputrescine were the most consistent candidate metabolites, likely reflecting oral dysbiosis. Other candidate metabolites likely reflected tissue destruction and cell proliferation.

CONCLUSIONS

Untargeted metabolic profiling of saliva replicated metabolic signatures of periodontal status and revealed novel metabolites associated with periodontitis and future tooth loss.

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.

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

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

Oral Diagnostic Methods for the Detection of Periodontal Disease

Periodontitis is a common immune-inflammatory oral disease. Early detection plays an important role in its prevention and progression. Saliva is a reliable medium that mirrors periodontal health and is easily obtainable for identifying periodontal biomarkers in point-of-care diagnostics. The aim of this study is to evaluate the effectiveness of diagnostic salivary tests to determine periodontal status. Whole saliva (stimulated/unstimulated) from twenty healthy and twenty stage III grade B generalized periodontitis patients was tested for lactoferrin, alkaline phosphatase, calcium, density, osmolarity, pH, phosphate, buffer capacity, salivary flow rate and dynamic viscosity. A semi-quantitative urinary strip test was used to evaluate markers of inflammation in saliva (erythrocytes, leukocytes, urobilinogen, nitrite, glucose, bilirubin, and ketones), clinical periodontal parameters and pathogenic bacteria. Concentrations of lactoferrin, hemoglobin, and leukocytes were found to be significantly higher in the stimulated and unstimulated saliva in periodontitis patients compared to healthy patients, whereas alkaline phosphatase levels were higher in unstimulated saliva of periodontitis patients (p < 0.05). Periodontal biomarker analysis using test strips may be considered rapid and easy tool for distinguishing between periodontitis and healthy patients. The increase in lactoferrin, hemoglobin, and leucocytes-determined by strip tests-may provide a non-invasive method of periodontal diagnosis.

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

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

Molecular signatures of extracellular vesicles in oral fluids of periodontitis patients

OBJECTIVE

To characterize extracellular vesicles (EVs) in gingival crevicular fluid (GCF) and saliva samples from healthy/gingivitis and periodontitis patients and correlate them with clinical inflammatory periodontal parameters.

MATERIAL AND METHOD

An exploratory study, including 86 subjects, was conducted. Clinical and periodontal data were recorded, and oral fluid samples were obtained. EVs were precipitated by ExoQuick-TC™ and characterized by nanoparticle tracking (NanoSight™), Western blot (WB), transmission electron microscopy (TEM), and ELISA analysis.

RESULTS

TEM showed nanoparticles morphologically compatible with EVs, and WB analysis revealed bands of specific EV markers (CD9, TSG101, and Alix) in both oral fluids of periodontitis and healthy/gingivitis subjects. The total concentration of EVs in GCF was increased in periodontitis patients compared to healthy/gingivitis subjects (p = .017). However, we did not observe differences in the EV concentration of saliva samples (p = .190). The size of GCF-EVs was 144.2 nm in periodontitis and 160.35 nm in healthy/gingivitis patients (p = .038). The CD63 exosome marker was increased in GCF of periodontitis patients (p = .00001). The total concentration of EVs in GCF was correlated with bleeding on probing (rho = 0.63, p = .002), periodontal probing depth (rho = 0.56, p = .009), and clinical attachment level (rho = 0.48, p = .030).

CONCLUSION

Periodontitis patients have an increased concentration of EVs in GCF, and their role in periodontitis should be clarified.

Automated Process Incorporating Machine Learning Segmentation and Correlation of Oral Diseases with Systemic Health

Imaging fluorescent disease biomarkers in tissues and skin is a non-invasive method to screen for health conditions. We report an automated process that combines intraoral fluorescent porphyrin biomarker imaging, clinical examinations and machine learning for correlation of systemic health conditions with periodontal disease. 1215 intraoral fluorescent images, from 284 consenting adults aged 18-90, were analyzed using a machine learning classifier that can segment periodontal inflammation. The classifier achieved an AUC of 0.677 with precision and recall of 0.271 and 0.429, respectively, indicating a learned association between disease signatures in collected images. Periodontal diseases were more prevalent among males (p=0.0012) and older subjects (p=0.0224) in the screened population. Physicians independently examined the collected images, assigning localized modified gingival indices (MGIs). MGIs and periodontal disease were then cross-correlated with responses to a medical history questionnaire, blood pressure and body mass index measurements, and optic nerve, tympanic membrane, neurological, and cardiac rhythm imaging examinations. Gingivitis and early periodontal disease were associated with subjects diagnosed with optic nerve abnormalities (p<; 0.0001) in their retinal scans. We also report significant co-occurrences of periodontal disease in subjects reporting swollen joints (p=0.0422) and a family history of eye disease (p=0.0337). These results indicate cross-correlation of poor periodontal health with systemic health outcomes and stress the importance of oral health screenings at the primary care level. Our screening process and analysis method, using images and machine learning, can be generalized for automated diagnoses and systemic health screenings for other diseases.

Salivary Fingerprinting of Periodontal Disease by Infrared-ATR Spectroscopy

PURPOSE

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

EXPERIMENTAL DESIGN

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

RESULTS

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

CONCLUSION AND CLINICAL RELEVANCE

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

Proteomic analysis of whole saliva in chronic periodontitis

Periodontitis is a chronic inflammatory disease resulting from a dysbiosis of the dental biofilm and a dysregulated host response in susceptible individuals. It is characterized by periodontal attachment destruction, bone resorption and eventual tooth loss. Salivary biomarkers have been sought to predict and prevent periodontitis. This comparative study analyzed the salivary proteome of individuals with chronic periodontitis (CP) and periodontal health (PH) and correlated specific proteins with clinical parameters of disease by using mass spectrometry. Stimulated whole saliva was obtained 10 PH and 30 CP patients and pooled into 5 healthy control samples and 15 CP samples. After precipitation with TCA, samples were digested enzymatically with trypsin and analyzed by a LTQ Orbitrap Velos equipped with a nanoelectrospray ion source. A wide range of salivary proteins of various functions was significantly reduced in CP individuals, whereas salivary acidic proline-rich phosphoprotein, submaxillary gland androgen-regulated protein, histatin-1, fatty acid binding protein, thioredoxin and cystatin-SA were predominant in diseased patients and correlated significantly with signs of periodontal attachment loss and inflammation. In conclusion, few specific salivary proteins were associated with CP. These findings may contribute to the identification of disease indicators or signatures for the improvement of periodontal diagnosis. SIGNIFICANCE: Periodontitis is a chronic inflammatory disease that results in periodontal attachment destruction, bone resorption and eventual tooth loss. Salivary biomarkers have been sought to predict periodontitis. The analysis of the salivary proteome of individuals with chronic periodontitis indicated that several proteins of various functions were significantly reduced in these individuals, except for salivary acidic proline-rich phosphoprotein, submaxillary gland androgen-regulated protein, histatin, fatty acid binding protein, thioredoxin and cystatin. Differences in salivary proteome profiles between periodontal health and periodontitis may contribute to the identification of disease indicators and to the improvement of periodontal diagnosis and treatment.

Salivary Theranostics in Pediatric and Special Care Dentistry

Saliva as a microfluidic system offers numerous advantages for both general and oral health diagnostic and therapeutic procedures since its assembly is quick, stress-free, inexpensive and non-invasive. Moreover, saliva is frequently referred to as a mirror of the body due to the fact that it can reflect the physiological and pathological state of the body. More than a decade ago the term “Salivaomics” has been introduced with the aim of emphasizing the development of research, knowledge and applications of five salivary constituents: proteome, transcriptome, micro-RNA, metabolome, and microbiome. Contemporary oral health care delivery in pediatric and special care dentistry is focused toward the development of new diagnostic and therapeutical procedures that are essentially noninvasive due to common issue of intolerability to invasive procedures among these patients, with the possibility of increasing participation rates. Besides the criteria of being easily and non-invasive collected, there are additional standards that should be met before routine application in everyday clinical practice; the existence of specific biomarkers for a disease, and ability of having its biomarkers detected using present-day equipment. For example, there are recent suggestions that a salivary RNA panel could objectively differentiate children with autism spectrum disorder from their neurotypical peers. In addition, due to the ease of the administration, the oral cavity is an attractive site for the drug delivery systems development because through this route it is possible to realize mucosal and transmucosal, systemic effect. All these contemporary advances extended the salivary diagnostic approach from the oral to general health pointing towards a promising future of salivary diagnostics for personalized medicine devices.

MIP-1α and MCP-1 as salivary biomarkers in periodontal disease

Aim

Chemokines released by different host cells when exposed to the components of periodontopathic bacteria induce and maintain an inflammatory response in the periodontium. The aim of the study was to estimate the salivary levels of two chemokines, macrophage inflammatory protein-1 alpha (MIP-1α) and monocyte chemo attractant protein-1 (MCP-1) in health, gingivitis and periodontitis and to evaluate their role as reliable salivary biomarkers in discriminating gingivitis and periodontitis from health.

Methods

A cross sectional study was designed to estimate the levels of MIP-1α and MCP-1 in whole unstimulated saliva from 75 patients who were divided into healthy (Group 1, n = 25), gingivitis (Group 2, n = 25) and chronic generalized periodontitis (Group 3, n = 25). MIP-1α and MCP-1 levels were estimated by using ELISA and were correlated with clinical parameters. ROC curve analysis was done to determine the sensitivity and specificity of these biomarkers in distinguishing periodontal disease from health.

Results

Both the biomarkers were detected in all the saliva samples. There was a statistically significant difference in the concentration of both the analytes in Group 3 and Group 2 compared with Group 1 (p < 0.001). ROC curve analysis showed 100% sensitivity and specificity for MIP-1α and MCP-1 in discriminating periodontitis from health. For discriminating gingivitis from health, MIP-1α had a higher sensitivity and specificity (100% & 88% respectively) compared to MCP-1(84.1% & 80% respectively).

Conclusion

There is a substantial increase in the concentration of both MIP-1α and MCP-1 with increasing severity of periodontal disease. Both the analytes showed promising results as biomarkers for discriminating periodontal disease from health.

A Review of Selected Studies That Determine the Physical and Chemical Properties of Saliva in the Field of Dental Treatment

Physiological whole saliva is a unique body fluid constantly washing the mucous membranes of the mouth, throat, and larynx. Saliva is a clear, slightly acidic mucinous-serous secretion, composed of various electrolytes, small organic substances, proteins, peptides, and polynucleotides. There are many ways to use saliva as a biological fluid (biofluid). The significant advantages of saliva as a unique diagnostic material are its availability and the noninvasive method of collection. The aim of this review is to emphasize the diagnostic value of saliva as a research material in the configuration of its structure and secretion disorders. The data were obtained using the MEDLINE (PubMed) search engine, as well as an additional manual search. The analysis covered 77 articles selected from a group of 1986 publications and initially qualified for devising. The results were evaluated and checked for the correctness of qualifying in accordance with inclusion and exclusion criteria. The diagnostic use of saliva has attracted the attention of many researchers due to its noninvasive nature and relative simplicity of collection. In addition, it should be noted that the determination of chemical and physical saliva parameters can be effectively performed in the patient's presence in the dental office.

Detection of Biomarkers of Periodontal Disease in Human Saliva Using Stabilized, Vertical Flow Immunoassays

We report methods for stabilizing cellulose-based immunoassays and using this platform to analyze human saliva. Stabilization treatments of immunoassays for matrix metalloproteinases (MMP)-8 and -9, biomarkers of periodontal disease, were conducted and compared, revealing that anti-MMP-8 and -9 capture antibodies could be stabilized with the addition of a 5% trehalose solution to the test zones, followed by drying in a vacuum oven. After stabilization, the paper devices retained equivalent binding activity to that of freshly prepared tests for 14 days-a time frame that enables US-based clinical testing of this diagnostic assay. A saliva pretreatment method was developed to remove viscous elements without reducing the concentration or binding activity of dissolved proteins. Immunoassays were stored in ziplock bags containing desiccant, and used to detect nanomolar concentrations of MMP-9 in human saliva across the relevant clinical concentration range. These methods and findings facilitate rapid, affordable validation studies of this and other biomarkers that are found in saliva using vertical flow immunoassays.

Metagenomic and metatranscriptomic analysis of saliva reveals disease-associated microbiota in patients with periodontitis and dental caries

The taxonomic composition of the salivary microbiota has been reported to differentiate between oral health and disease. However, information on bacterial activity and gene expression of the salivary microbiota is limited. The purpose of this study was to perform metagenomic and metatranscriptomic characterization of the salivary microbiota and test the hypothesis that salivary microbial presence and activity could be an indicator of the oral health status. Stimulated saliva samples were collected from 30 individuals (periodontitis: n = 10, dental caries: n = 10, oral health: n = 10). Salivary microbiota was characterized using metagenomics and metatranscriptomics in order to compare community composition and the gene expression between the three groups. Streptococcus was the predominant bacterial genus constituting approx. 25 and 50% of all DNA and RNA reads, respectively. A significant disease-associated higher relative abundance of traditional periodontal pathogens such as Porphyromonas gingivalis and Filifactor alocis and salivary microbial activity of F. alocis was associated with periodontitis. Significantly higher relative abundance of caries-associated bacteria such as Streptococcus mutans and Lactobacillus fermentum was identified in saliva from patients with dental caries. Multiple genes involved in carbohydrate metabolism were significantly more expressed in healthy controls compared to periodontitis patients. Using metagenomics and metatranscriptomics we show that relative abundance of specific oral bacterial species and bacterial gene expression in saliva associates with periodontitis and dental caries. Further longitudinal studies are warranted to evaluate if screening of salivary microbial activity of specific oral bacterial species and metabolic gene expression can identify periodontitis and dental caries at preclinical stages.

Genetic analysis of saliva reveals the activity of bacteria linked to gum disease and tooth decay and may prove useful in early diagnosis. Daniel Belstrøm and colleagues at the University of Copenhagen, Denmark, with co-workers at Nanyang Technological University in Singapore, analyzed saliva from 10 patients with periodontitis gum disease, 10 with dental caries and 10 with good oral health. DNA analysis revealed which bacteria were present, while examining RNA revealed which bacterial genes were most active. The procedure identified greater abundance and activity of bacteria linked to each specific oral condition in the oral disease groups, and also found distinctive bacterial activity in those people with good oral health. Further studies should investigate the possibility of testing bacterial gene activity in saliva to identify oral diseases before they become clinically evident.

Point of Care- A Novel Approach to Periodontal Diagnosis-A Review

Periodontal disease, one of the prevalent oral diseases, is characterized by gingival inflammation and periodontal tissue destruction. Diagnosing this disease is challenging to the clinicians as the disease process is discontinuous and shows periods of exacerbation and remission. Traditional diagnostic methods basically tells about the past tissue destruction so new diagnostic methods are required which is able to detect the active state of the disease, determine the future progression and also estimates the response to the therapy, thereby helping in the better clinical management of the patient. Both saliva and Gingival crevicular fluid (GCF) are believed to be reliable medium to detect the biomarkers which plays a pivotal role in measuring the disease activity. Keeping these observations in mind rapid chairside tests are developed to diagnose periodontal disease called as Point of Care (POC) diagnostics which simplifies diagnosis and helps in improving the prognosis. This review article highlights about the biomarkers used in the diagnosis and throws light on the various available point of care diagnostic devices.

Impact of Oral Hygiene Discontinuation on Supragingival and Salivary Microbiomes

The purpose of the present study was to characterize and compare supragingival and salivary microbiotas during a 10-d period of oral hygiene discontinuation. We tested the hypothesis that the composition of the salivary microbiota will reflect local microbial changes associated with accumulated biofilm formation and maturation. Pooled supragingival plaque (n = 145) and stimulated saliva (n = 145) samples were collected and plaque and gingival indices were recorded from 29 orally healthy individuals at baseline, during oral hygiene discontinuation (days 4, 7, and 10), and 14 d after resumption of oral hygiene. Supragingival and salivary microbiotas were processed by next-generation sequencing (Human Oral Microbe Identification using Next Generation Sequencing) and microbial community profiles were compared. Microbial composition of supragingival plaque samples collected after 4, 7, and 10 d of oral hygiene discontinuation, as well as 14 d after reuptake of oral hygiene, differed significantly from baseline samples, by a 3-fold increase in relative abundance Leptotrichia species and a 2-fold decrease in Streptococcus species (adjusted P < 0.01). In saliva samples, a significant increase in relative abundance of Leptotrichia species (adjusted P < 0.01) was evident at day 7 but completely reversed 14 d after resumption of oral hygiene. While the salivary microbiota was resistant to accumulated local biofilm formation, data from this study showed that compositional changes of supragingival microbiotas were not reversed 14 d after resumption of oral hygiene, despite the restoration of plaque to baseline levels. (ClinicalTrials.gov UCPH_OI_002, NCT02913235).

Knowledge Transfer Statement: Data from this study showed compositional changes of supragingival microbiotas as a consequence of a 10-d period of oral hygiene discontinuation, that was not reversed 14 d after resumption of oral hygiene. Notably, oral hygiene discontinuation was associated with a significant increase in relative abundance of potential cariogenic Leptotrichia species and a decrease in Streptococcus species. Thus, findings from this study highlight the necessity of regular oral hygiene in the maintenance of oral homeostasis.

Influences of pH and Iron Concentration on the Salivary Microbiome in Individual Humans with and without Caries

This study aimed to identify the differences in the oral microbial communities in saliva from patients with and without caries by performing sequencing with the Illumina MiSeq platform, as well as to further assess their relationships with environmental factors (salivary pH and iron concentration). Forty-three volunteers were selected, including 21 subjects with and 22 without caries, from one village in Gansu, China. Based on 966,255 trimmed sequences and clustering at the 97% similarity level, 1,303 species-level operational taxonomic units were generated. The sequencing data for the two groups revealed that (i) particular distribution patterns (synergistic effects or competition) existed in the subjects with and without caries at both the genus and species levels and (ii) both the salivary pH and iron concentration had significant influences on the microbial community structure.

IMPORTANCE The significant influences of the oral environment observed in this study increase the current understanding of the salivary microbiome in caries. These results will be useful for expanding research directions and for improving disease diagnosis, prognosis, and therapy.

Salivary microbiota in individuals with different levels of caries experience

This study compared salivary bacterial profiles in two groups having a 10-fold difference in levels of caries experience, as it was hypothesized that the composition of the salivary microbiota might associate with the levels of caries experience.

Bacterial profiles in stimulated saliva samples from 85 individuals with low levels of caries experience (healthy group) and 79 individuals with high levels of caries experience (caries group) were analyzed by means of the Human Oral Microbiome Identification Next Generation Sequencing (HOMINGS) technique. Subsequently, saliva samples from caries-free individuals in the healthy group (n = 57) and the caries group (n = 31) were compared.

A significantly higher α-diversity (p < 0.0001) and a twofold higher relative abundance of Neisseria, Haemophilus, and Fusobacterium were recorded in saliva samples from the healthy group compared with the caries group. Differences observed were more pronounced when limiting the analyses to caries-free individuals in each group.

Data from this cross-sectional analysis suggest that low levels of caries experience might associate with a characteristic salivary bacterial composition different from that in individuals with high caries experience. Consequently, longitudinal studies are required to determine if the composition of the salivary microbiota might be a predictive factor of caries risk at the individual level.

Saliva diagnostics - Current views and directions

In this review, we provide an update on the current and future applications of saliva for diagnostic purposes. There are many advantages of using saliva as a biofluid. Its collection is fast, easy, inexpensive, and non-invasive. In addition, saliva, as a "mirror of the body," can reflect the physiological and pathological state of the body. Therefore, it serves as a diagnostic and monitoring tool in many fields of science such as medicine, dentistry, and pharmacotherapy. Introduced in 2008, the term "Salivaomics" aimed to highlight the rapid development of knowledge about various "omics" constituents of saliva, including: proteome, transcriptome, micro-RNA, metabolome, and microbiome. In the last few years, researchers have developed new technologies and validated a wide range of salivary biomarkers that will soon make the use of saliva a clinical reality. However, a great need still exists for convenient and accurate point-of-care devices that can serve as a non-invasive diagnostic tool. In addition, there is an urgent need to decipher the scientific rationale and mechanisms that convey systemic diseases to saliva. Another promising technology called liquid biopsy enables detection of circulating tumor cells (CTCs) and fragments of tumor DNA in saliva, thus enabling non-invasive early detection of various cancers. The newly developed technology-electric field-induced release and measurement (EFIRM) provides near perfect detection of actionable mutations in lung cancer patients. These recent advances widened the salivary diagnostic approach from the oral cavity to the whole physiological system, and thus point towards a promising future of salivary diagnostics for personalized individual medicine applications including clinical decisions and post-treatment outcome predictions. Impact statement The purpose of this mini-review is to make an update about the present and future applications of saliva as a diagnostic biofluid in many fields of science such as dentistry, medicine and pharmacotherapy. Using saliva as a fluid for diagnostic purposes would be a huge breakthrough for both patients and healthcare providers since saliva collection is easy, non-invasive and inexpensive. We will go through the current main diagnostic applications of saliva, and provide a highlight on the emerging, newly developing technologies and tools for cancer screening, detection and monitoring.

Metaproteomics of saliva identifies human protein markers specific for individuals with periodontitis and dental caries compared to orally healthy controls

Background

The composition of the salivary microbiota has been reported to differentiate between patients with periodontitis, dental caries and orally healthy individuals. To identify characteristics of diseased and healthy saliva we thus wanted to compare saliva metaproteomes from patients with periodontitis and dental caries to healthy individuals.

Methods

Stimulated saliva samples were collected from 10 patients with periodontitis, 10 patients with dental caries and 10 orally healthy individuals. The proteins in the saliva samples were subjected to denaturing buffer and digested enzymatically with LysC and trypsin. The resulting peptide mixtures were cleaned up by solid-phase extraction and separated online with 2 h gradients by nano-scale C₁₈ reversed-phase chromatography connected to a mass spectrometer through an electrospray source. The eluting peptides were analyzed on a tandem mass spectrometer operated in data-dependent acquisition mode.

Results

We identified a total of 35,664 unique peptides from 4,161 different proteins, of which 1,946 and 2,090 were of bacterial and human origin, respectively. The human protein profiles displayed significant overexpression of the complement system and inflammatory markers in periodontitis and dental caries compared to healthy controls. Bacterial proteome profiles and functional annotation were very similar in health and disease.

Conclusions

Overexpression of proteins related to the complement system and inflammation seems to correlate with oral disease status. Similar bacterial proteomes in healthy and diseased individuals suggests that the salivary microbiota predominantly thrives in a planktonic state expressing no disease-associated characteristics of metabolic activity.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Comparative analysis of bacterial profiles in unstimulated and stimulated saliva samples

Background and objective

The microbial profiles of stimulated saliva samples have been shown to differentiate between patients with periodontitis, patients with dental caries, and orally healthy individuals. Saliva was stimulated to allow for easy and rapid collection; however, microbial composition may not reflect the more natural, unstimulated state. The purpose of this study was to validate whether stimulated saliva is an adequate surrogate for unstimulated saliva in determining salivary microbiomes.

Design

Unstimulated (n=20) and stimulated (n=20) saliva samples were collected from 20 orally and systemically healthy, non-smoking participants. Salivary bacterial profiles were analyzed by means of the Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS), and statistical analysis was performed using Mann–Whitney test with Benjamini–Hochberg's correction for multiple comparison, cluster analysis, principal component analysis, and correspondence analysis.

Results

From a total of 40 saliva samples, 496 probe targets were identified with a mean number of targets per sample of 203 (range: 146–303), and a mean number of probe targets of 206 and 200 in unstimulated and stimulated saliva samples, respectively (p=0.62). Based on all statistical methods used for this study, the microbial profiles of unstimulated and stimulated saliva samples collected from the same person were not statistically significantly different.

Conclusions

Analysis of bacterial salivary profiles in unstimulated and stimulated saliva samples collected from the same individual showed comparable results. Thus, the results verify that stimulated saliva is an adequate surrogate of unstimulated saliva for microbiome-related studies.

Bacterial composition in whole saliva from patients with severe hyposalivation--a case-control study

OBJECTIVE

The purpose of this study was to compare the microbiota of stimulated whole saliva samples from patients with severe hyposalivation to samples from individuals with normal whole saliva flow rates. It was hypothesized that the two groups differ with regard to salivary bacterial profiles.

METHODS

This cross-sectional study included 36 participants (24 females and 12 males, mean age 58.5 years) with severe hyposalivation and 36 gender-, age-, and geographically matched participants with normal salivary secretion from the Danish Health Examination Survey (DANHES). The microbiota of stimulated whole saliva samples was characterized by HOMINGS.

RESULTS

The two groups had comparable caries experience measured by decayed, missed, filled surfaces/teeth and decayed, missed, filled root surfaces as well as active caries lesions. In addition, no single probe target was present with a significant difference in frequency or proportional presence between groups. Furthermore, data reduction by principal component analysis and correspondence analysis showed comparable bacterial community profiles between groups.

CONCLUSIONS

The results indicate that the salivary bacterial profiles of patients with severe hyposalivation do not differ from those of individuals with normal salivary secretion, when there are virtually no untreated active caries lesions present in the oral cavity.

Temporal Stability of the Salivary Microbiota in Oral Health

Objectives

Saliva is a biological fluid suitable for biomarker analysis, and differences in the salivary microbiota in oral health and disease have been reported. For such comparative analyses, time of sampling is critical since the bacterial composition may vary throughout the day, i.e., diurnal variation. The purpose of this study is to compare the salivary microbiome over time to determine the optimal time for sampling.

Design

Stimulated saliva samples were collected from 5 orally healthy individuals in 4 h intervals for 24 h, and collection was repeated 7 days later (number of samples per person, n = 12, total number of samples, n = 60). Salivary microbiota was analyzed using the Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS), and statistical analysis was performed using the Kruskal-Wallis test with Benjamini-Hochberg’s correction for multiple comparisons, cluster analysis, principal component analysis and correspondence analysis.

Results

From a total of 60 saliva samples, 477 probe targets were collectively identified with a mean number of probes per sample of 207 (range: 153–307). Little or no variation in microbial profiles within subjects was observed over time.

Conclusions

Although there was considerable variation between subjects, microbial profiles within subjects were stable throughout a 24 hour period and after 1 week. Since there is little or no evidence of diurnal variation of the salivary microbiome, time of sampling of saliva is not critical for perturbation or other microbial studies.

Exploration of Human Salivary Microbiomes--Insights into the Novel Characteristics of Microbial Community Structure in Caries and Caries-Free Subjects

Recently, high-throughput sequencing has improved the understanding of the microbiological etiology of caries, but the characteristics of the microbial community structure in the human oral cavity with and without caries are not completely clear. To better understand these characteristics, Illumina MiSeq high-throughput sequencing was utilized to analyze 20 salivary samples (10 caries-free and 10 caries) from subjects from the same town in Dongxiang, Gansu, China. A total of 5,113 OTUs (Operational Taxonomic Units, 97% cutoff) were characterized in all of the salivary samples obtained from the 20 subjects. A comparison of the two groups revealed that (i) the predominant phyla were constant between the two groups; (ii) the relative abundance of the genera Veillonella, Bifidobacterium, Selenomonas, Olsenella, Parascardovia, Scardovia, Chryseobacterium, Terrimonas, Burkholderia and Sporobacter was significantly higher in the group with caries (P < 0.05); and (iii) four genera with low relative abundance (< 0.01% on average), including two characteristic genera in caries (Chryseobacterium and Scardovia), significantly influenced the microbial community structure at the genus and OTU levels. Moreover, via co-occurrence and principal component analyses, the co-prevalence of the pathogenic genera was detected in the caries samples, but in the caries-free samples, the function of clustered genera was more random. This result suggests that a synergistic effect may be influencing the assembly of the caries microbial community, whereas competition may play a more dominant role in governing the microbial community in the caries-free group. Our findings regarding the characteristics of the microbial communities of the groups with and without caries might improve the understanding of the microbiological etiology of caries and might improve the prevention and cure of caries in the future.

MicroRNAs as biomarkers for dental diseases

MicroRNAs (miRNAs) are short, noncoding RNAs that act as key regulators of diverse biological processes by mediating translational repression or mRNA degradation of target genes. Recent studies discovered miRNAs in saliva, and these miRNAs are promising candidates for use as biomarkers of dental diseases. In this review, the results of miRNA studies in the dental field are presented, and a brief overview of the current progress, limitations, and perspectives regarding miRNA biomarkers for dental diseases is given.

Protein biomarkers and microbial profiles in peri-implantitis

OBJECTIVES

The aim of the present investigation was to determine the profile of peri-implant crevicular fluid (PICF) biomarkers combined with microbial profiles from implants with healthy peri-implant tissues and peri-implantitis to assess real-time disease activity.

MATERIAL AND METHODS

Sixty-eight patients were included in this cross-sectional study. They were divided into two groups: 34 patients with at least one healthy implant (control) and 34 with at least one peri-implantitis affected implant (test). Total DNA content and qPCR analysis for periodontal bacteria obtained from subgingival plaque samples (Aggregatibacter actinomycetemcomitans, Prevotella intermedia, Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola) and a PICF analysis for IL-1β, VEGF, MMP-8, TIMP-2, and OPG were performed. The individual and combined diagnostic ability of each biomarker for peri-implantitis and target bacterial species were analyzed.

RESULTS

The mean concentration of IL-1β (44.6 vs. 135.8 pg/ml; P < 0.001), TIMP-2 (5488.3 vs. 9771.8 pg/ml; P = 0.001), VEGF (59.1 vs. 129.0 pg/ml; P = 0.012), and OPG (66.5 vs. 111.7 pg/ml; P = 0.050) was increased in the peri-implantitis patients. The mean expression of MMP-8 (6029.2 vs. 5943.1 pg/ml; P = 0.454) and did not reveal a meaningful difference among groups. Total bacterial DNA of selected microorganisms was associated with a threefold or greater increase in peri-implantitis although no statistical significant difference. The ability to diagnose diseased sites was enhanced by T. denticola combined with IL-1β, VEGF, and TIMP-2 PICF levels.

CONCLUSION

The present data suggest that the increased levels of the selected PICF-derived biomarkers of periodontal tissue inflammation, matrix degradation/regulation, and alveolar bone turnover/resorption combined with site-specific microbial profiles may be associated with peri-implantitis and could have potential as predictors of peri-implant diseases.

Quantitative PCR analysis of salivary pathogen burden in periodontitis

Our aim was to investigate the value of salivary concentrations of four major periodontal pathogens and their combination in diagnostics of periodontitis. The Parogene study included 462 dentate subjects (mean age 62.9 ± 9.2 years) with coronary artery disease (CAD) diagnosis who underwent an extensive clinical and radiographic oral examination. Salivary levels of four major periodontal bacteria were measured by quantitative real-time PCR (qPCR). Median salivary concentrations of Porphyromonas gingivalis, Tannerella forsythia, and Prevotella intermedia, as well as the sum of the concentrations of the four bacteria, were higher in subjects with moderate to severe periodontitis compared to subjects with no to mild periodontitis. Median salivary Aggregatibacter actinomycetemcomitans concentrations did not differ significantly between the subjects with no to mild periodontitis and subjects with moderate to severe periodontitis. In logistic regression analysis adjusted for age, gender, diabetes, and the number of teeth and implants, high salivary concentrations of P. gingivalis, T. forsythia, and P. intermedia were significantly associated with moderate to severe periodontitis. When looking at different clinical and radiographic parameters of periodontitis, high concentrations of P. gingivalis and T. forsythia were significantly associated with the number of 4-5 mm periodontal pockets, ≥6 mm pockets, and alveolar bone loss (ABL). High level of T. forsythia was associated also with bleeding on probing (BOP). The combination of the four bacteria, i.e., the bacterial burden index, was associated with moderate to severe periodontitis with an odds ratio (OR) of 2.40 (95% CI 1.39-4.13). When A. actinomycetemcomitans was excluded from the combination of the bacteria, the OR was improved to 2.61 (95% CI 1.51-4.52). The highest OR 3.59 (95% CI 1.94-6.63) was achieved when P. intermedia was further excluded from the combination and only the levels of P. gingivalis and T. forsythia were used. Salivary diagnostics of periodontitis has potential especially in large-scale population studies and health promotion. The cumulative strategy appears to be useful in the analysis of salivary bacteria as markers of periodontitis.

Patient-Specific Variations in Biomarkers across Gingivitis and Periodontitis

This study investigates the use of saliva, as an emerging diagnostic fluid in conjunction with classification techniques to discern biological heterogeneity in clinically labelled gingivitis and periodontitis subjects (80 subjects; 40/group) A battery of classification techniques were investigated as traditional single classifier systems as well as within a novel selective voting ensemble classification approach (SVA) framework. Unlike traditional single classifiers, SVA is shown to reveal patient-specific variations within disease groups, which may be important for identifying proclivity to disease progression or disease stability. Salivary expression profiles of IL-1ß, IL-6, MMP-8, and MIP-1α from 80 patients were analyzed using four classification algorithms (LDA: Linear Discriminant Analysis [LDA], Quadratic Discriminant Analysis [QDA], Naïve Bayes Classifier [NBC] and Support Vector Machines [SVM]) as traditional single classifiers and within the SVA framework (SVA-LDA, SVA-QDA, SVA-NB and SVA-SVM). Our findings demonstrate that performance measures (sensitivity, specificity and accuracy) of traditional classification as single classifier were comparable to that of the SVA counterparts using clinical labels of the samples as ground truth. However, unlike traditional single classifier approaches, the normalized ensemble vote-counts from SVA revealed varying proclivity of the subjects for each of the disease groups. More importantly, the SVA identified a subset of gingivitis and periodontitis samples that demonstrated a biological proclivity commensurate with the other clinical group. This subset was confirmed across SVA-LDA, SVA-QDA, SVA-NB and SVA-SVM. Heatmap visualization of their ensemble sets revealed lack of consensus between these subsets and the rest of the samples within the respective disease groups indicating the unique nature of the patients in these subsets. While the source of variation is not known, the results presented clearly elucidate the need for novel approaches that accommodate inherent heterogeneity and personalized variations within disease groups in diagnostic characterization. The proposed approach falls within the scope of P4 medicine (predictive, preventive, personalized, and participatory) with the ability to identify unique patient profiles that may predict specific disease trajectories and targeted disease management.

Progress in oral personalized medicine: contribution of 'omics'

BACKGROUND

Precision medicine (PM), representing clinically applicable personalized medicine, proactively integrates and interprets multidimensional personal health data, including clinical, 'omics', and environmental profiles, into clinical practice. Realization of PM remains in progress.

OBJECTIVE

The focus of this review is to provide a descriptive narrative overview of: 1) the current status of oral personalized medicine; and 2) recent advances in genomics and related 'omic' and emerging research domains contributing to advancing oral-systemic PM, with special emphasis on current understanding of oral microbiomes.

DESIGN

A scan of peer-reviewed literature describing oral PM or 'omic'-based research conducted on humans/data published in English within the last 5 years in journals indexed in the PubMed database was conducted using mesh search terms. An evidence-based approach was used to report on recent advances with potential to advance PM in the context of historical critical and systematic reviews to delineate current state-of-the-art technologies. Special focus was placed on oral microbiome research associated with health and disease states, emerging research domains, and technological advances, which are positioning realization of PM.

RESULTS

This review summarizes: 1) evolving conceptualization of personalized medicine; 2) emerging insight into roles of oral infectious and inflammatory processes as contributors to both oral and systemic diseases; 3) community shifts in microbiota that may contribute to disease; 4) evidence pointing to new uncharacterized potential oral pathogens; 5) advances in technological approaches to 'omics' research that will accelerate PM; 6) emerging research domains that expand insights into host-microbe interaction including inter-kingdom communication, systems and network analysis, and salivaomics; and 7) advances in informatics and big data analysis capabilities to facilitate interpretation of host and microbiome-associated datasets. Furthermore, progress in clinically applicable screening assays and biomarker definition to inform clinical care are briefly explored.

CONCLUSION

Advancement of oral PM currently remains in research and discovery phases. Although substantive progress has been made in advancing the understanding of the role of microbiome dynamics in health and disease and is being leveraged to advance early efforts at clinical translation, further research is required to discern interpretable constituency patterns in the complex interactions of these microbial communities in health and disease. Advances in biotechnology and bioinformatics facilitating novel approaches to rapid analysis and interpretation of large datasets are providing new insights into oral health and disease, potentiating clinical application and advancing realization of PM within the next decade.

Elevated matrix metalloproteinase-8 in saliva and serum in polycystic ovary syndrome and association with gingival inflammation

This study aimed to investigate the levels of matrix metalloproteinase-8 (MMP-8) and tissue inhibitors of MMP-1 (TIMP-1) in saliva and serum samples of women with polycystic ovary syndrome (PCOS; n = 80) and matched systemically healthy controls ( n = 45), with varying degrees of gingival inflammation. Salivary levels of MMP-8 and the MMP-8/TIMP-1 ratio were significantly elevated in women with PCOS, who also exhibited more gingivitis than systemically healthy women. No major changes were observed in salivary TIMP-1 levels with regard to PCOS. Serum levels of MMP-8 and the MMP-8/TIMP-1 ratio were significantly higher in women with PCOS, irrespective of the presence of gingivitis, while there were no differences in TIMP-1 levels. A positive correlation was indicated between probing depth, bleeding on probing, plaque index and salivary or serum MMP-8 levels or MMP-8/TIMP-1 ratio in the case of PCOS, while a negative such correlation was revealed for TIMP-1 in systemically healthy women. Increased levels of MMP-8 in saliva and serum seem to be more pronounced in women with PCOS, and potentiated in the presence of gingival inflammation. Alterations in MMP/TIMP system triggered by local and systemic inflammation may be implicated in the pathogenesis of PCOS, or the deterioration of its clinical presentation.

Biologic markers of failing implants

Implants are exposed to a diverse oral environment and host responses that contribute to health or disease. For the last few decades, clinicians have relied on standard clinical and radiographic findings to assess the health of implants. However, recent studies involving the pathogenesis of peri-implantitis have identified microbial species and several putative biomarkers that could aid clinicians in this diagnostic process in the near future. This article provides an overview of the microbial species involved in implant health and disease and biomarkers found in oral fluids that relate to the underlying biological phases of a failing implant.

Metabolomics for biomarker discovery in gastroenterological cancer

The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis.