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

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.

Metabolic profiling of peri-implant crevicular fluid in peri-implantitis

OBJECTS

This study aims to explore the etiology of peri-implantitis by comparing the metabolic profiles in peri-implant crevicular fluid (PICF) from patients with healthy implants (PH) and those with peri-implantitis (PI).

MATERIALS AND METHODS

Fifty-six patients were enrolled in this cross-sectional study. PICF samples were collected and analyzed using both non-targeted and targeted metabolomics approaches. The relationship between metabolites and clinical indices including probing depth (PD), bleeding on probing (BOP), and marginal bone loss (MBL) was examined. Additionally, submucosal microbiota was collected and analyzed using 16S rRNA gene sequencing to elucidate the association between the metabolites and microbial communities.

RESULTS

Significant differences in metabolic profiles were observed between the PH and PI groups, with 179 distinct metabolites identified. In the PI group, specific amino acids and fatty acids were significantly elevated compared to the PH group. Organic acids including succinic acid, fructose-6-phosphate, and glucose-6-phosphate were markedly higher in the PI group, showing positive correlations with mean PD, BOP, and MBL. Metabolites that increased in the PI group positively correlated with the presence of Porphyromonas and Treponema and negatively with Streptococcus and Haemophilus.

CONCLUSIONS

This study establishes a clear association between metabolic compositions and peri-implant condition, highlighting enhanced metabolite activity in peri-implantitis. These findings open avenues for further research into metabolic mechanisms of peri-implantitis and their potential therapeutic implications.

Relationship Between Oral Health and Glaucoma Traits in the United Kingdom

PRCIS

In this cross-sectional analysis of UK Biobank participants, we find no adverse association between self-reported oral health conditions and either glaucoma or elevated intraocular pressures.

PURPOSE

Poor oral health may cause inflammation, which accelerates the progression of neurodegenerative diseases. We investigated the relationship between oral health and glaucoma.

PATIENTS

United Kingdom Biobank participants.

METHODS

This is a cross-sectional analysis of participants categorized by self-reported oral health status. Multivariable linear and logistic regression models were used. Primary analysis examined the association with glaucoma prevalence. Secondary analyses examined associations with IOP, macular retinal nerve fiber layer (mRNFL), and ganglion cell inner plexiform layer (mGCIPL) thicknesses, and interaction terms with multitrait glaucoma polygenic risk scores (MTAG PRS) or intraocular pressure (IOP) PRS.

RESULTS

A total of 170,815 participants (34.3%) reported current oral health problems, including painful or bleeding gums, toothache, loose teeth, and/or denture wear. A In all, 33,059, 33,004, 14,652, and 14,613 participants were available for analysis of glaucoma, IOP, mRNFL, and mGCIPL, respectively. No association between oral health and glaucoma was identified [odds ratio (OR): 1.04, 95% CI: 0.95-1.14]. IOPs were slightly lower among those with oral disease (-0.08 mm Hg, 95% CI: -0.15, -0.009); specifically, among those with loose teeth ( P =0.03) and denture-wearers ( P <0.0001). mRNFL measurements were lower among those with oral health conditions (-0.14 μm, 95% CI: -0.27, -0.0009), but mGCIPL measurements ( P =0.96) were not significantly different. A PRS for IOP or glaucoma did not modify relations between oral health and IOP or glaucoma ( P for interactions ≥​​​​0.17).

CONCLUSIONS

Self-reported oral health was not associated with elevated IOP or an increased risk of glaucoma. Future studies should confirm the null association between clinically diagnosed oral health conditions and glaucoma.

The interplay between gingival crevicular fluid microbiome and metabolomic profile in intensively treated people with type 1 diabetes - a combined metagenomic/metabolomic approach cross-sectional study

Aims

This study aimed to assess the gingival crevicular fluid (GCF) microbiome and metabolome of adults with type 1 diabetes (T1D) treated with continuous subcutaneous insulin infusion (CSII).

Methods

In this cross-sectional study, the GCF of adults with T1D treated with CSII and non-diabetic controls were sampled, and metagenomic/metabolomic analyses were performed.

Results

In total, 65 participants with T1D and 45 healthy controls with a mean age of 27.05 ± 5.95 years were investigated. There were 22 cases of mild gingivitis (G) in the T1D group. There were no differences considering the Shannon and Chao indices and β-diversity between people with T1D and G, with T1D without G, and healthy controls. Differential taxa were identified, which were mainly enriched in people with T1D and G. Acetic acid concentration was higher in people with T1D, regardless of the presence of G, than in healthy controls. Propionic acid was higher in people with T1D and G than in healthy controls. Isobutyric and isovaleric acid levels were higher in individuals with T1D and G than in the other two subgroups. The concentration of valeric acid was lower and that of caproic acid was higher in people with T1D (regardless of gingival status) than in healthy controls.

Conclusions

The identification of early changes in periodontal tissues by targeting the microbiome and metabolome could potentially enable effective prevention and initial treatment of periodontal disease in people with T1D.

Salivary elemental signature of dental caries: a systematic review and meta-analysis of ionomics studies

Trace- and macro-chemical elements are crucial for cellular physiological functioning, and their alterations in biological fluids might be associated with an underlying pathological state. Hence, this study aimed to examine and summarize the published literature concerning the application of salivary ionomics for caries diagnosis. An extensive search of studies was conducted using PubMed, EMBASE, Web of Science, and Scopus, without any language and year restriction for answering the following PECO question: "In subjects (i.e., children, adolescents, or adults) with good systematic health, are there any variations in the salivary concentrations of trace- or macro-elements between caries-free (CF) individuals and caries-active (CA) subjects?" A modified version of the QUADOMICS tool was used to assess the quality of the included studies. The Review Manager Version 5.4.1. was used for data analyses. The analysis of salivary chemical elements that significantly differed between CF and CA subjects was also performed. Thirty-four studies were included, involving 2299 CA and 1669 CF subjects, having an age range from 3 to 64 years in over 16 countries. The meta-analysis revealed a statistically significant difference (p < 0.05) in the salivary levels of calcium, phosphorus, chloride, magnesium, potassium, sodium, and zinc between CA and CF subjects, suggesting higher levels of calcium, phosphorus, potassium, and sodium in CF subjects while higher levels of chloride, magnesium, and zinc in CA patients. Half of the included studies (17/34) were considered high quality, while the remaining half were considered medium quality. Only zinc and chloride ions were found to be higher significantly and consistent in CF and CA subjects, respectively. Conflicting outcomes were observed for all other salivary chemical elements including aluminum, bromine, calcium, copper, fluoride, iron, potassium, magnesium, manganese, sodium, ammonia, nitrite, nitrate, phosphorus, lead, selenium, and sulfate ions.

Non-targeted metabolomics aids in sex pheromone identification: a proof-of-concept study with the triangulate cobweb spider, Steatoda triangulosa

Targeted metabolomics has been widely used in pheromone research but may miss pheromone components in study organisms that produce pheromones in trace amount and/or lack bio-detectors (e.g., antennae) to readily locate them in complex samples. Here, we used non-targeted metabolomics-together with high-performance liquid chromatography-mass spectrometry (HPLC-MS), gas chromatography-MS, and behavioral bioassays-to unravel the sex pheromone of the triangulate cobweb spider, Steatoda triangulosa. A ternary blend of three contact pheromone components [N-4-methylvaleroyl-O-isobutyroyl-L-serine (5), N-3-methylbutyryl-O-isobutyroyl-L-serine (11), and N-3-methylbutyryl-O-butyroyl-L-serine (12)] elicited courtship by S. triangulosa males as effectively as female web extract. Hydrolysis of 5, 11 and 12 at the ester bond gave rise to two mate-attractant pheromone components [butyric acid (7) and isobutyric acid (8)] which attracted S. triangulosa males as effectively as female webs. Pheromone components 11 and 12 are reported in spiders for the first time, and were discovered only through the use of non-targeted metabolomics and GC-MS. All compounds resemble pheromone components previously identified in widow spiders. Our study provides impetus to apply non-targeted metabolomics for pheromone research in a wide range of animal taxa.

The role of salivary galectin-3 and galectin-9 levels in plaque-induced gingivitis and periodontitis

Background

This study aimed to compare the salivary galectin-3 and galectin-9 levels in periodontitis, gingivitis, and periodontally healthy patients.

Methods

This study included 75 non-smokers who were systemically healthy. The clinical periodontal parameters of each participant were recorded. Individuals with periodontal health, gingivitis, and Stage II or Stage III Grade B periodontitis were allocated to the corresponding study groups (n = 25 each). Saliva samples were obtained from all individuals after they abstained from drinking and eating 1 h before sample collection. The galectin-3 and galectin-9 levels in the saliva were analyzed using enzyme-linked immunosorbent assay. One-way analysis of variance, student's t-test, Spearman correlation, and logistic regression were used for statistical analyses.

Results

The galectin-3 and galectin-9 levels were significantly higher in the periodontitis and gingivitis groups than in the healthy group (p < 0.001). The highest galectin-3 and galectin-9 levels were observed in the gingivitis group (p < 0.05). Overall, the galectin-3 levels were significantly higher than the galectin-9 levels in all the groups (p < 0.001).

Conclusions

The salivary galectin-3 and galectin-9 levels were high in patients with periodontitis and gingivitis, suggesting that they could be potential biomarkers for periodontal diseases.

Saliva biomarkers in oral disease

Saliva is a versatile biofluid that contains a wide variety of biomarkers reflecting both physiologic and pathophysiologic states. Saliva collection is noninvasive and highly applicable for tests requiring serial sampling. Furthermore, advances in test accuracy, sensitivity and precision for saliva has improved diagnostic performance as well as the identification of novel markers especially in oral disease processes. These include dental caries, periodontitis, oral squamous cell carcinoma (OSCC) and Sjögren's syndrome (SS). Numerous growth factors, enzymes, interleukins and cytokines have been identified and are the subject of much research investigation. This review highlights current procedures for successful determination of saliva biomarkers including preanalytical factors associated with sampling, storage and pretreatment as well as subsequent analysis. Moreover, it provides an overview of the diagnostic applications of these salivary biomarkers in common oral diseases.

Comparison of the Metabolic Profile between Unstimulated and Stimulated Saliva Samples from Pregnant Women with/without Obesity and Periodontitis

This study aimed to compare the metabolic profile of unstimulated (US) and stimulated (SS) saliva samples from pregnant women with/without obesity and periodontitis. Ninety-six pregnant women were divided into: obesity + periodontitis (OP = 20); obesity/no periodontitis (OWP = 27); normal BMI + periodontitis (NP = 20); and normal BMI/no periodontitis (NWP = 29). US and SS samples were collected by expectoration and chewing of sterilized parafilm gum, respectively, and samples were individually analyzed by Proton Nuclear Magnetic Resonance (1H-NMR). Univariate (t test and correlations) and multivariate (Principal Component Analysis-PCA, and Partial Least Square-Discriminant Analysis-PLS-DA with Variance Importance Projection-VIP scores) and Metabolite Set Enrichment Analysis were done (p < 0.05). Metabolites commonly found in all groups in elevated concentration in US samples were 5-Aminopentoate, Acetic acid, Butyric acid, Propionic acid, Pyruvic acid, and Succinic acid. They were mainly related to the butyrate metabolism, citric acid cycle, amino sugar metabolism, fatty acids biosynthesis, pyruvate metabolism, glutamate metabolism, and Warburg effect. Metabolites commonly found in all groups that were in elevated concentration in SS samples were Citrulline, Fumaric acid, Histidine, N-acetyl glutamine, N-acetylneuraminic acid, para-hydroxyphenylacetic acid, Proline, Tyrosine. Although some differences were found between unstimulated and stimulated saliva samples from pregnant women with/without obesity and periodontitis, stimulated saliva collection seems adequate, demonstrating similar metabolic pathways to unstimulated saliva samples when groups are compared.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

The prognostic prediction of periodontal non-surgery therapy in periodontitis patients based on surface-enhanced Raman measurements of pre-treatment saliva

Periodontitis is one of the most prevalent dental diseases, and the patients with periodontitis often suffer from refractory periodontitis or recurrence of disease due to improper or inadequate treatment. In clinical practice, the early and accurate assessment of post-treatment prognosis in periodontitis patients is always very important in order to implement timely interventions. In this study, a pre-treatment saliva SERS based prognostic protocol was explored to predict the prognosis of periodontal non-surgery therapy in periodontitis patients. According to the biomolecular analysis, significant differences in the levels of ascorbic acid, uric acid and glutathione are observed between good prognosis group and poor prognosis group, which are expected to serve as potential prognostic markers. Furthermore, high accuracy, sensitivity and specificity can also be achieved by using the proposed prognostic model. The excellent performance of the proposed method has demonstrated its potential for fast, accurate, and non-invasive prognostic prediction of periodontal non-surgery therapy in periodontitis patients, even at the time before implementing treatment, thus is expected to benefit timely and rational guidance on clinical interventions.

Dysbiosis of Oral Microbiota and Metabolite Profiles Associated with Type 2 Diabetes Mellitus

Several previous studies have shown that oral microbial disorders may be closely related to the occurrence and development of type 2 diabetes mellitus (T2DM). However, whether the function of oral microorganisms and their metabolites have changed in patients with T2DM who have not suffered from any oral diseases has not been reported. We performed metagenomic analyses and nontargeted metabolic analysis of saliva and supragingival plaque samples from patients with T2DM who have not suffered any oral diseases and normal controls. We found that periodontal pathogens such as Porphyromonas gingivalis and Prevotella melaninogenica were significantly enriched, while the abundances of dental caries pathogens such as Streptococcus mutans and Streptococcus sobrinus were not significantly different in patients with T2DM compared to those in normal controls. Metabolomic analyses showed that the salivary levels of cadaverine and L-(+)-leucine of patients with T2DM were significantly higher than those of normal controls, while the supragingival plaque levels of N-acetyldopamine and 3,4-dimethylbenzoic acid in patients with T2DM were significantly higher than those in the normal controls. Additionally, we identified the types of oral microorganisms related to the changes in the levels of circulating metabolites, and the oral microorganisms were involved in the dysregulation of harmful metabolites such as cadaverine and n, n-dimethylarginine. Overall, our study first described the changes in the composition of oral microorganisms and their metabolites in patients with T2DM who have not suffered any oral diseases, which will provide a direct basis for finding oral biomarkers for early warning of oral diseases in T2DM. IMPORTANCE The incidence of oral diseases in type 2 diabetic patients might increase, and the severity might also be more serious. At present, the relationship between oral microorganisms and type 2 diabetes mellitus (T2DM) has become a hot topic in systemic health research. However, whether the function of oral microorganisms and their metabolites have changed in patients with T2DM who have not suffered from any oral diseases has not been reported. We found that even if the oral condition of T2DM is healthy, their oral microbes and metabolites have changed, thus increasing the risk of periodontal disease. Our study first described the changes in the composition of oral microorganisms and their metabolites in T2DM who have not suffered any oral diseases and revealed the correlation between oral microorganisms and their metabolites, which will provide a direct basis for finding oral biomarkers for early warning of oral diseases in patients with T2DM.

"Do it yourself" protocol to fabricate dual-detection paper-based analytical device for salivary biomarker analysis

This paper describes the design and construction of dual microfluidic paper-based analytical devices (dual-μPADs) as a lab-on-paper platform involving a "do-it-yourself" fabrication protocol. The device comprises a colorimetric and electrochemical module to obtain a dual-mode signal readout sensing strategy. A 3D pen polymeric resin was used to prepare graphite carbon-based electrodes and hydrophobic barriers on paper substrates. The proposed carbon-based ink was employed to manufacture electrodes on paper based on a stencil-printing approach, which were further characterized by electrochemical and morphological analyses. The analytical performance of the dual-μPADs was simultaneously evaluated for lactate, pH, nitrite, and salivary amylase (sAA) analysis. To demonstrate the proof-of-concept, saliva samples collected from both healthy individuals and those with periodontitis were successfully tested to demonstrate the feasibility of the proposed devices. Samples collected from individuals previously diagnosed with periodontitis showed high levels of nitrite and sAA (> 94 μmol L^-1 and > 610 U mL^-1) in comparison with healthy individuals (≤ 16 μmol L^-1 and 545 U mL^-1). Moreover, periodontitis saliva resulted in acid solution and almost null lactate levels. Notably, this protocol supplies a simple way to manufacture dual-μPADs, a versatile platform for sensitive detecting of biomarkers in saliva playing a crucial role towards the point-of-care diagnosis of periodontal disease.

Microbiome, alveolar bone, and metabolites: Connecting the dots

The oral microbiome (OM) is a diverse and dynamic collection of species, separated from alveolar bone by the oral mucosa. Pathogenic shifts in the OM (dysbiosis) during periodontitis are associated with an inflammatory response in the oral mucosa that drives alveolar bone resorption. Alveolar bone is also affected by metabolic disorders such as osteoporosis. Accumulating evidence has linked another microbial community, the gut microbiome (GM), to systemic bone metabolism and osteoporosis. Underlying this connection is the biologic activity of metabolites, byproducts of host and bacterial activity. Limited evidence also suggests that metabolites in the oral cavity signal between the OM and immune system, influencing both alveolar bone homeostasis and pathologic bone destruction in periodontitis. While the oral cavity and gut are connected through the gastrointestinal tract, dissimilar roles for known metabolites between these two niches exemplify the difficulty in translating knowledge on gut-derived metabolites and bone metabolism to alveolar bone. Integrated metabolomic, transcriptomic, and metagenomic approaches hold promise for resolving these challenges and identifying novel metabolites which impact alveolar bone health. Further interrogation through mechanistic testing in pre-clinical models and carefully controlled clinical studies have potential to lead toward translation of these discoveries into meaningful therapies.

Salivary Antioxidant Capacity and Magnesium in Generalized Anxiety Disorder

Generalized anxiety disorder (GAD) is a prevalent disorder. The search for biomarkers may contribute to new knowledge about molecular pathogenesis and treatment. Since oxidative stress and micronutrient imbalance play a key role in the development of mental disorders, we aimed to study salivary antioxidant capacity and magnesium in patients with GAD in an anxiety model of solving problems with increasing complexity. The study subgroup consisted of 15 patients with GAD, and 17 healthy volunteers of the same age made up the control subgroup. Participants took a test with six levels of difficulty, which included false feedback. In this test, the participants were asked to remember the colors of balloons and react when the color changed. The reaction time, the number of correct answers, as well as biochemical parameters such as the antioxidant capacity of saliva and salivary magnesium, were assessed. There was no difference in the results of the quest between the subgroups; however, anxious participants spent more time at the moment of experimental frustration due to incorrect feedback and additional negative psycho-emotional load. Antioxidant capacity did not differ between the subgroups both before and after the experimental session. Average antioxidant capacity also did not change significantly at the endpoint of the experiment. However, the endpoint antioxidant capacity correlated negatively with the reaction time in anxious patients in the second block (where the false feedback as a frustrating factor appeared). Magnesium was initially significantly higher in the group of anxious participants and decreased at the experiment endpoint; in healthy patients, there were no changes in salivary magnesium at the endpoint. In conclusion, the compensatory potential of oxidative metabolism and magnesium in patients with GAD was spent with additional psycho-emotional stress, in contrast to healthy individuals, but it was sufficient to avoid exhaustion during experimental frustrating exposure.

Updates and Original Case Studies Focused on the NMR-Linked Metabolomics Analysis of Human Oral Fluids Part III: Implementations for the Diagnosis of Non-Cancerous Disorders, Both Oral and Systemic

This communication represents Part III of our series of reports based on the applications of human saliva as a useful and conveniently collectable medium for the discovery, identification and monitoring of biomarkers, which are of some merit for the diagnosis of human diseases. Such biomarkers, or others reflecting the dysfunction of specific disease-associated metabolic pathways, may also be employed for the prognostic pathological tracking of these diseases. Part I of this series set the experimental and logistical groundwork for this report, and the preceding paper, Part II, featured the applications of newly developed metabolomics technologies to the diagnosis and severity grading of human cancer conditions, both oral and systemic. Clearly, there are many benefits, both scientific and economic, associated with the donation of human saliva samples (usually as whole mouth saliva) from humans consenting to and participating in investigations focused on the discovery of biomolecular markers of diseases. These include usually non-invasive collection protocols, relatively low cost when compared against blood sample collection, and no requirement for clinical supervision during collection episodes. This paper is centred on the employment and value of 'state-of-the-art' metabolomics technologies to the diagnosis and prognosis of a wide range of non-cancerous human diseases. Firstly, these include common oral diseases such as periodontal diseases (from type 1 (gingivitis) to type 4 (advanced periodontitis)), and dental caries. Secondly, a wide range of extra-oral (systemic) conditions are covered, most notably diabetes types 1 and 2, cardiovascular and neurological diseases, and Sjögren's syndrome, along with a series of viral infections, e.g., pharyngitis, influenza, HIV and COVID-19. Since the authors' major research interests lie in the area of the principles and applications of NMR-linked metabolomics techniques, many, but not all, of the studies reviewed were conducted using these technologies, with special attention being given to recommended protocols for their operation and management, for example, satisfactory experimental model designs; sample collection and laboratory processing techniques; the selection of sample-specific NMR pulse sequences for saliva analysis; and strategies available for the confirmation of resonance assignments for both endogenous and exogenous molecules in this biofluid. This article also features an original case study, which is focussed on the use of NMR-based salivary metabolomics techniques to provide some key biomarkers for the diagnosis of pharyngitis, and an example of how to 'police' such studies and to recognise participants who perceive that they actually have this disorder but do not from their metabolic profiles and multivariate analysis pattern-based clusterings. The biochemical and clinical significance of these multidimensional metabolomics investigations are discussed in detail.

Data Processing and Analysis in Liquid Chromatography-Mass Spectrometry-Based Targeted Metabolomics

Mass spectrometry (MS)-based metabolomics provides high-dimensional datasets; that is, the data include various metabolite features. Data analysis begins by converting the raw data obtained from the MS to produce a data matrix (metabolite × concentrations). This is followed by several steps, such as peak integration, alignment of multiple data, metabolite identification, and calculation of metabolite concentrations. Each step yields the analytical results and the accompanying information used for the quality assessment of the anterior steps. Thus, the measurement quality can be analyzed through data processing. Here, we introduce a typical data processing procedure and describe a method to utilize the intermediate data as quality control. Subsequently, commonly used data analysis methods for metabolomics data, such as statistical analyses, are also introduced.

Metabolomic Profiles Associated with Obesity and Periodontitis during Pregnancy: Cross-Sectional Study with Proton Nuclear Magnetic Resonance (1H-NMR)-Based Analysis

This study aimed to elucidate the metabolomic signature associated with obesity and periodontitis during pregnancy in plasma and saliva biofluids. Ninety-eight pregnant women were divided into: with obesity and periodontitis (OP = 20), with obesity but without periodontitis (OWP = 27), with normal BMI but with periodontitis (NP = 21), with normal BMI and without periodontitis (NWP = 30). Saliva and plasma were analyzed by 1H-NMR for metabolites identification. Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA (sPLS-DA), and Variable Importance of Projection (VIP) were performed. ANOVA and Pearson’s correlation were applied (p < 0.05). Plasmatic analysis indicated the levels of glucose (p = 0.041) and phenylalanine (p = 0.015) were positively correlated with periodontal parameters and BMI, respectively. In saliva, periodontitis was mainly associated with high levels of acetic acid (p = 0.024), isovaleric acid, butyric acid, leucine, valine, isoleucine, and propionic acid (p < 0.001). High salivary concentrations of glycine (p = 0.015), succinic acid (p = 0.015), and lactate (p = 0.026) were associated with obesity. Saliva demonstrated a more elucidative difference than plasma, indicating the glucose-alanine cycle, alanine metabolism, valine, leucine and isoleucine degradation, glutamate metabolism, and Warburg effect as the main metabolic pathways.

Investigation of pathogenesis of hyperuricemia based on untargeted and targeted metabolomics

Hyperuricemia (HUA) seriously harms human health but the exact etiology and pathogenesis of HUA are not fully understood. Therefore, it is still of great significance to find effective biomarkers and explore the pathogenesis of HUA. Metabolomics reflects the influence of internal and external factors on system metabolism, explains the changes in metabolite levels during the development of diseases, and reveals the molecular mechanism of pathogenesis. Metabolomics is divided into untargeted metabolomics and targeted metabolomics according to different research modes. Each other's advantages can be fully utilized by combining the two so that the results of metabolomics research can be consummated. 20 HUA patients and 20 healthy individuals participated in the experiment, and untargeted metabolomics was employed to find 50 differential metabolites in HUA serum samples. Twelve candidate biomarkers were screened based on literature research and ROC Curve analysis for subsequent verification. Based on the UPLC-TQ-MS analysis platform, the targeted metabolomics detection methods were established and the content of 12 candidate biomarkers was precisely quantified. Compare with the results of untargeted metabolomics, the targeted metabolomics results were considered more reliable.

Moving beyond descriptive studies: harnessing metabolomics to elucidate the molecular mechanisms underpinning host-microbiome phenotypes

Advances in technology and software have radically expanded the scope of metabolomics studies and allow us to monitor a broad transect of central carbon metabolism in routine studies. These increasingly sophisticated tools have shown that many human diseases are modulated by microbial metabolism. Despite this, it remains surprisingly difficult to move beyond these statistical associations and identify the specific molecular mechanisms that link dysbiosis to the progression of human disease. This difficulty stems from both the biological intricacies of host-microbiome dynamics as well as the analytical complexities inherent to microbiome metabolism research. The primary objective of this review is to examine the experimental and computational tools that can provide insights into the molecular mechanisms at work in host-microbiome interactions and to highlight the undeveloped frontiers that are currently holding back microbiome research from fully leveraging the benefits of modern metabolomics.

Salivary Metabolomics for Oral Cancer Detection: A Narrative Review

The development of low- or non-invasive screening tests for cancer is crucial for early detection. Saliva is an ideal biofluid containing informative components for monitoring oral and systemic diseases. Metabolomics has frequently been used to identify and quantify numerous metabolites in saliva samples, serving as novel biomarkers associated with various conditions, including cancers. This review summarizes the recent applications of salivary metabolomics in biomarker discovery in oral cancers. We discussed the prevalence, epidemiologic characteristics, and risk factors of oral cancers, as well as the currently available screening programs, in India and Japan. These data imply that the development of biomarkers by itself is inadequate in cancer detection. The use of current diagnostic methods and new technologies is necessary for efficient salivary metabolomics analysis. We also discuss the gap between biomarker discovery and nationwide screening for the early detection of oral cancer and its prevention.

Salivary inflammatory mediators as biomarkers for oral mucositis and oral mucosal dryness in cancer patients: A pilot study

Oral mucositis (OM) is a common side effect in patients with cancer receiving chemotherapy and radiotherapy; however, no salivary mediator is known to be associated with OM. We aimed to determine candidate salivary inflammatory mediators potentially associated with OM in patients with cancer. To this end, we compared the relationships between OM grade, oral mucosal dryness, and inflammatory mediators (Interleukin (IL)-1β, IL-6, IL-10, IL-12p70, tumor necrosis factor (TNF), prostaglandin E2, and vascular endothelial growth factor) in patients with cancer and in healthy volunteers (HV). We collected saliva samples from 18 patients with cancer according to the following schedule: 1) within 14 days of treatment initiation, 2) within 3 days of OM occurrence, 3) when OM was improved or got worsened, and 4) within 7 days after chemotherapy completion. The oral care support team determined the OM grade at each sample collection point based on CTCAE version 5.0. Salivary inflammatory mediator concentrations were detected using cytometric bead array or enzyme-linked immunoassay. We compared oral mucosal dryness in pre- and post-index patients with cancer to that in HV (n = 33) using an oral moisture-checking device. Fourteen of eighteen patients experienced OM (four, grade 3 OM; four, grade 2 OM; six, grade 1 OM). IL-6, IL-10, and TNF salivary concentrations were significantly increased in the post-index group compared to those in the pre-index group (p = 0.0002, p = 0.0364, and p = 0.0160, respectively). Additionally, salivary IL-6, IL-10, and TNF levels were significantly higher in the post-index group than in the HV group (p < 0.0001, p < 0.05, and p < 0.05, respectively). Significant positive correlations were observed between OM grade and salivary IL-6, IL-10, and TNF levels (p = 0.0004, r = 0.4939; p = 0.0171, r = 0.3394; and p = 0007, r = 0.4662, respectively). Oral mucosal dryness was significantly higher in the HV than in the pre- and post-index groups (p < 0.001). Our findings suggest that salivary IL-6, IL-10, and TNF levels may be used as biomarkers for OM occurrence and grade in patients with cancer. Furthermore, monitoring oral mucosal dryness and managing oral hygiene before cancer treatment is essential.

Investigation of salivary biomarkers as indicators of skeletal and dental maturity in children

OBJECTIVE

Estimation of patient's skeletal maturity in orthodontics is essential for the diagnosis and treatment planning. The aim of the study was to investigate the potential use of metabolic fingerprint of saliva for bone growth and tooth development estimation.

MATERIALS AND METHODS

Saliva samples from 54 young patients were analysed by an untargeted gas chromatography-mass spectrometry metabolomics-based method. The skeletal maturity was calculated with the cervical vertebrae maturation method, and the dental age was estimated with the Demirjian method. Multivariate analysis and univariate analysis were performed to investigate differences within skeletal, dental and chronological age groups.

RESULTS

Metabolomic analysis identified 61 endogenous compounds. Mannose, glucose, glycerol, glyceric acid and pyroglutamic acid levels differentiated significantly with skeletal age (P = .02 to .043), while mannose, lactic acid, glycolic acid, proline, norleucine, 3-aminoisobutyric acid, threonine, cadaverine and hydrocinnamic acid levels differed within the dental age groups (P = .018 to .04); according to the chronological age, only the levels of mannose and 3-hydroxyphenylacetic acid showed variation (P = .029 and .048). The principal component analysis did not manage to highlight differences between the groups of the studied parameters.

CONCLUSION

Differentiated levels of mannose, glucose, glycerol, glyceric acid and pyroglutamic acid related to skeletal maturation were identified. According to dental development, the levels of mannose, lactic acid, glycolic acid, proline, norleucine, 3-aminoisobutyric acid, threonine, cadaverine and hydrocinnamic acid differed within the groups, while regarding chronological age, only the levels of mannose and 3-hydroxyphenylacetic acid showed variations. Further studies are required to prove their relation to skeletal and dental development pathway by applying complementary analytical techniques to wider cover the metabolome.

The Role of Candida albicans Virulence Factors in the Formation of Multispecies Biofilms With Bacterial Periodontal Pathogens

Periodontal disease depends on the presence of different microorganisms in the oral cavity that during the colonization of periodontal tissues form a multispecies biofilm community, thus allowing them to survive under adverse conditions or facilitate further colonization of host tissues. Not only numerous bacterial species participate in the development of biofilm complex structure but also fungi, especially Candida albicans, that often commensally inhabits the oral cavity. C. albicans employs an extensive armory of various virulence factors supporting its coexistence with bacteria resulting in successful host colonization and propagation of infection. In this article, we highlight various aspects of individual fungal virulence factors that may facilitate the collaboration with the associated bacterial representatives of the early colonizers of the oral cavity, the bridging species, and the late colonizers directly involved in the development of periodontitis, including the “red complex” species. In particular, we discuss the involvement of candidal cell surface proteins—typical fungal adhesins as well as originally cytosolic “moonlighting” proteins that perform a new function on the cell surface and are also present within the biofilm structures. Another group of virulence factors considered includes secreted aspartic proteases (Sap) and other secreted hydrolytic enzymes. The specific structure of the candidal cell wall, dynamically changing during morphological transitions of the fungus that favor the biofilm formation, is equally important and discussed. The non-protein biofilm-composing factors also show dynamic variability upon the contact with bacteria, and their biosynthesis processes could be involved in the stability of mixed biofilms. Biofilm-associated changes in the microbe communication system using different quorum sensing molecules of both fungal and bacterial cells are also emphasized in this review. All discussed virulence factors involved in the formation of mixed biofilm pose new challenges and influence the successful design of new diagnostic methods and the application of appropriate therapies in periodontal diseases.

Toward Personalized Oral Diagnosis: Distinct Microbiome Clusters in Periodontitis Biofilms

Periodontitis is caused by pathogenic subgingival microbial biofilm development and dysbiotic interactions between host and hosted microbes. A thorough characterization of the subgingival biofilms by deep amplicon sequencing of 121 individual periodontitis pockets of nine patients and whole metagenomic analysis of the saliva microbial community of the same subjects were carried out. Two biofilm sampling methods yielded similar microbial compositions. Taxonomic mapping of all biofilms revealed three distinct microbial clusters. Two clinical diagnostic parameters, probing pocket depth (PPD) and clinical attachment level (CAL), correlated with the cluster mapping. The dysbiotic microbiomes were less diverse than the apparently healthy ones of the same subjects. The most abundant periodontal pathogens were also present in the saliva, although in different representations. The single abundant species Tannerella forsythia was found in the diseased pockets in about 16–17-fold in excess relative to the clinically healthy sulcus, making it suitable as an indicator of periodontitis biofilms. The discrete microbial communities indicate strong selection by the host immune system and allow the design of targeted antibiotic treatment selective against the main periodontal pathogen(s) in the individual patients.

Macro and trace elements signature of periodontitis in saliva: A systematic review with quality assessment of ionomics studies

Objectives

The present systematic review examined the available evidence on distinctive salivary ion profile in periodontitis compared to periodontal health and provided a qualitative assessment of the literature.

Background

Macro and trace elements are essential for cellular physiology, and their changes in biological fluids can be revelatory of an underlying pathological status.

Methods

Data from relevant studies identified from PubMed, Embase, and Scopus databases were retrieved to answer the following PECO question: “In systemically healthy individuals, are there any differences in any salivary macro or trace element concentration between periodontally healthy subjects (H) and patients with periodontitis (P)?” Quality of included studies was rated using a modified version of the QUADOMICS tool. A consistency analysis was performed to identify significantly discriminant chemical elements.

Results

After the screening of 873 titles, 13 studies were included reporting data on 22 different elements. Among them, levels of sodium and potassium were consistently and significantly higher in P compared to H. Conflicting results were found for all the other elements, despite concentration of calcium, copper, and manganese mostly increased in saliva of P. Levels of magnesium were found higher in P than in H in 2 studies but lower in 3. Zinc resulted significantly increased in saliva from H compared to P individuals in 2 studies, but one study reported opposite results. Four studies were considered as high quality, while reporting of operative protocols and statistical analysis was a major limitation for the others. Due to high methodologic heterogeneity, meta‐analysis was not performed.

Conclusions

Levels of macro or trace elements were differentially identified in saliva across diverse periodontal conditions, having a major potential for investigation of oral homeostasis and for high‐resolution periodontal diagnosis. Products of inflammatory physiologic cellular impairment, such as sodium and potassium, were the most consistently associated with periodontitis (PROSPERO CRD42021235744).

Metabolic phenotyping of saliva to identify possible biomarkers of periodontitis using proton nuclear magnetic resonance

AIM

The aim of this study was to propose biomarker candidates for periodontitis via untargeted metabolomics analysis.

MATERIALS AND METHODS

Metabolic profiling was performed using saliva samples from 92 healthy controls (H) and 129 periodontitis patients (P) in the discovery cohort using proton nuclear magnetic resonance spectroscopy. Random forest was applied to identify metabolites that significantly differentiated the control group from the periodontitis group. Candidate metabolites were then validated in an independent validation cohort.

RESULTS

In the discovery set, the metabolic profiles of the P group were clearly separated from those of the H group. A total of 31 metabolites were identified in saliva, and 7 metabolites were selected as candidate biomarkers. These metabolites were further confirmed in the validation set. Ethanol, taurine, isovalerate, butyrate, and glucose were finally confirmed as biomarkers. Furthermore, the biomarker panel showed more than 0.9 of the area under curve value in both discovery and validation sets, indicating that panels were more effective than individual metabolites for diagnosing periodontitis.

CONCLUSIONS

We identified five metabolite biomarkers that discriminated patients with periodontitis from healthy controls in two independent cohorts. These biomarkers have the potential for periodontal screening, detection of periodontitis, and monitoring of the outcome of periodontal therapy.

Aging-Related Metabolic Dysfunction in the Salivary Gland: A Review of the Literature

Aging-related salivary dysfunction commonly induces the poor oral health, including decreased saliva flow and dental caries. Although the clinical significance of the salivary glands is well-known, the complex metabolic pathways contributing to the aging-dysfunction process are only beginning to be uncovered. Here, we provide a comprehensive overview of the metabolic changes in aging-mediated salivary gland dysfunction as a key aspect of oral physiology. Several metabolic neuropeptides or hormones are involved in causing or contributing to salivary gland dysfunction, including hyposalivation and age-related diseases. Thus, aging-related metabolism holds promise for early diagnosis, increased choice of therapy and the identification of new metabolic pathways that could potentially be targeted in salivary gland dysfunction.

Taxonomic and Gene Category Analyses of Subgingival Plaques from a Group of Japanese Individuals with and without Periodontitis

Periodontitis is an inflammation of tooth-supporting tissues, which is caused by bacteria in the subgingival plaque (biofilm) and the host immune response. Traditionally, subgingival pathogens have been investigated using methods such as culturing, DNA probes, or PCR. The development of next-generation sequencing made it possible to investigate the whole microbiome in the subgingival plaque. Previous studies have implicated dysbiosis of the subgingival microbiome in the etiology of periodontitis. However, details are still lacking. In this study, we conducted a metagenomic analysis of subgingival plaque samples from a group of Japanese individuals with and without periodontitis. In the taxonomic composition analysis, genus Bacteroides and Mycobacterium demonstrated significantly different compositions between healthy sites and sites with periodontal pockets. The results from the relative abundance of functional gene categories, carbohydrate metabolism, glycan biosynthesis and metabolism, amino acid metabolism, replication and repair showed significant differences between healthy sites and sites with periodontal pockets. These results provide important insights into the shift in the taxonomic and functional gene category abundance caused by dysbiosis, which occurs during the progression of periodontal disease.

Impact of Probiotics on the Salivary Microbiota and Salivary Levels of Inflammation-Related Proteins during Short-Term Sugar Stress: A Randomized Controlled Trial

Background: The purpose of the present investigation was to characterize the effect of probiotics on the composition of the salivary microbiota and salivary levels of inflammation-related proteins during short-term sugar stress. We tested the hypotheses that consumption of probiotics may partly counteract the detrimental influence of sugar stress on oral homeostasis. Methods: The present study was a five-week, blinded, randomized controlled trial with four study arms—A: sucrose and probiotic (n = 20); B: sucrose and placebo (n = 20); C: xylitol and probiotic (n = 20); D: xylitol and placebo (n = 20). Saliva samples were collected at baseline and after two and five weeks. The salivary microbiota was characterized by means of 16S rDNA sequencing, and sequences were referenced against the Human Oral Microbiome Database (HOMD). Neutrophil gelatinase-associated lipocalin (NGAL) and transferrin levels were quantified using immunoassays. Results: Sugar stress induced a significant increase in the relative abundance of the genus Streptococcus from 29.8% at baseline to 42.9% after two weeks. Changes were transient and were completely reversed three weeks after discontinuation of sugar stress. Xylitol and probiotics alone had no effect on the salivary microbiota, whereas the combination of xylitol and probiotics induced a significant decrease in the relative abundance of Streptococcus species from 37.6% at baseline to 23.0% at week 2. Sugar stress significantly increased salivary transferrin levels, and the effect was partly counteracted by concomitant use of probiotics. Conclusions: The data clearly demonstrate an impact of combined consumption of xylitol and probiotics on the composition of the salivary microbiota. Future studies are needed to evaluate whether the combined use of xylitol and the probiotic strains tested could have clinically protective effects during periods of sugar stress.

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).

Shared microbiological and immunological patterns in periodontitis and IBD: A scoping review

OBJECTIVES

To extract the microbiological and immunological evidence underpinning the association between periodontitis and inflammatory bowel disease (IBD).

METHODS

Relevant articles were sorted through a systematic search on PubMed, Embase, Scopus and Web of Science up to October 2020. Available evidence was grouped in three different clusters: (a) studies that examined oral microbial alterations in IBD patients; (b) studies that investigated intestinal dysbiosis in patients with periodontitis; and (c) evidence for a shared immunological pattern between the two conditions.

RESULTS

A total of 15 studies involving 1,171 patients were included. Oral microbiome, either subgingival or salivary, was consistently altered in patients with IBD compared to healthy subjects (a) Additionally, gut dysbiotic microbiota of IBD patients was colonized by pathobionts from oral origin, either via haematogenous or enteric route. Suffering from periodontitis is associated with lower alpha diversity in the gut microbiome (b) Lastly, both IBD and periodontitis are characterized by similar expression patterns of inflammatory cytokines at the gingival and gut levels that are exacerbated when both diseases are present (c).

CONCLUSIONS

Periodontitis and IBD share common dysbiotic and immunological traits. Well-designed preclinical models and longitudinal cohort studies are required to better explore the causal pathways between the two conditions (PROSPERO CRD42020194379).