Salivary Metabolomics for Diagnosis and Monitoring Diseases: Challenges and Possibilities

The Association between Salivary Metabolites and Gingival Bleeding Score in Healthy Subjects: A Pilot Study

Periodontal diseases, including gingivitis and periodontitis, are among the most prevalent diseases in humans. Gingivitis is the mildest form of periodontal disease, characterized by inflammation of the gingiva caused by the accumulation of dental plaque. Salivary diagnostics are becoming increasingly popular due to the variation in saliva composition in response to pathological processes. We used a metabolomics approach to investigate whether a specific saliva metabolic composition could indicate preclinical stage of gingivitis. 1H-NMR spectroscopy was used to obtain the salivary metabolite profiles of 20 healthy subjects. Univariate/multivariate statistical analysis evaluated the whole saliva metabolite composition, and the Full-Mouth Bleeding Score (FMBS) was employed as a classification parameter. Identifying a signature of specific salivary metabolites could distinguish the subjects with high FMBS scores but still within the normal range. This set of metabolites may be due to the enzymatic activities of oral bacteria and be associated with the early stages of gingival inflammation. Although this analysis is to be considered exploratory, it seems feasible to establish an FMBS threshold that distinguishes between the absence and presence of early inflammatory alterations at the salivary level.

Salivary metabolites are promising noninvasive biomarkers of drug-induced liver injury

BACKGROUND

Drug-induced liver injury (DILI) is one of the most common adverse events of medication use, and its incidence is increasing. However, early detection of DILI is a crucial challenge due to a lack of biomarkers and noninvasive tests.

AIM

To identify salivary metabolic biomarkers of DILI for the future development of noninvasive diagnostic tools.

METHODS

Saliva samples from 31 DILI patients and 35 healthy controls (HCs) were subjected to untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with tandem mass spectrometry. Subsequent analyses, including partial least squares-discriminant analysis modeling, t tests and weighted metabolite coexpression network analysis (WMCNA), were conducted to identify key differentially expressed metabolites (DEMs) and metabolite sets. Furthermore, we utilized least absolute shrinkage and selection operato and random fores analyses for biomarker prediction. The use of each metabolite and metabolite set to detect DILI was evaluated with area under the receiver operating characteristic curves.

RESULTS

We found 247 differentially expressed salivary metabolites between the DILI group and the HC group. Using WMCNA, we identified a set of 8 DEMs closely related to liver injury for further prediction testing. Interestingly, the distinct separation of DILI patients and HCs was achieved with five metabolites, namely, 12-hydroxydodecanoic acid, 3-hydroxydecanoic acid, tetradecanedioic acid, hypoxanthine, and inosine (area under the curve: 0.733-1).

CONCLUSION

Salivary metabolomics revealed previously unreported metabolic alterations and diagnostic biomarkers in the saliva of DILI patients. Our study may provide a potentially feasible and noninvasive diagnostic method for DILI, but further validation is needed.

Salivary Metabolites Produced by Oral Microbes in Oral Diseases and Oral Squamous Cell Carcinoma: A Review

In recent years, salivary metabolome studies have provided new biological information and salivary biomarkers to diagnose different diseases at early stages. The saliva in the oral cavity is influenced by many factors that are reflected in the salivary metabolite profile. Oral microbes can alter the salivary metabolite profile and may express oral inflammation or oral diseases. The released microbial metabolites in the saliva represent the altered biochemical pathways in the oral cavity. This review highlights the oral microbial profile and microbial metabolites released in saliva and its use as a diagnostic biofluid for different oral diseases. The importance of salivary metabolites produced by oral microbes as risk factors for oral diseases and their possible relationship in oral carcinogenesis is discussed.

Comprehensive mapping of saliva by multiomics in children with idiopathic nephrotic syndrome

AIM

Saliva can reflect an individual's physiological status or susceptibility to systemic disease. However, little attention has been given to salivary analysis in children with idiopathic nephrotic syndrome (INS). We aimed to perform a comprehensive analysis of saliva from INS children.

METHODS

A total of 18 children (9 children with INS and 9 normal controls) were recruited. Saliva was collected from each INS patient in the acute and remission phases. 16S rRNA gene sequencing, widely targeted metabolomics, and 4D-DIA proteomics were performed.

RESULTS

Actinobacteria and Firmicutes were significantly enriched in the pretreatment group compared with the normal control group, while Bacteroidota and Proteobacteria were significantly decreased. A total of 146 metabolites were identified as significantly different between INS children before treatment and normal controls, which covers 17 of 23 categories. KEGG enrichment analysis revealed three significantly enriched pathways, including ascorbate and aldarate metabolism, pentose and glucuronate interconversions, and terpenoid backbone biosynthesis (P < 0.05). A total of 389 differentially expressed proteins were selected between INS children before treatment and normal controls. According to the KEGG and GO enrichment analyses of the KOGs, abnormal ribosome structure and function and humoral immune disorders were the most prominent differences between INS patients and normal controls in the proteomic analysis.

CONCLUSION

Oral microbiota dysbiosis may modulate the metabolic profile of saliva in children with INS. It is hypothesized that children with INS might have "abnormal ribosome structure and function" and "humoral immune disorders".

Comparisons of different extraction methods and solvents for saliva samples

INTRODUCTION

Changes in the categories and concentrations of salivary metabolites may be closely related to oral, intestinal or systemic diseases. To study salivary metabolites, the first analytical step is to extract them from saliva samples as much as possible, while reducing interferences to a minimum. Frequently used extraction methods are protein precipitation (PPT), liquid-liquid extraction (LLE) and solid-phase extraction (SPE), with various organic solvents. The types and quantities of metabolites extracted with different methods may vary greatly, but few studies have systematically evaluated them.

OBJECTIVES

This study aimed to select the most suitable methods and solvents for the extraction of saliva according to different analytical targets.

METHODS

An untargeted metabolomics approach based on liquid chromatography-mass spectrometry was applied to obtain the raw data. The numbers of metabolites, repeatability of the data and intensities of mass spectrometry signals were used as evaluation criteria.

RESULTS

PPT resulted in the highest coverage. Among the PPT solvents, acetonitrile displayed the best repeatability and the highest coverage, while acetone resulted in the best signal intensities for the extracted compounds. LLE with the mixture of chloroform and methanol was the most suitable for the extraction of small hydrophobic compounds.

CONCLUSION

PPT with acetonitrile or acetone was recommended for untargeted analysis, while LLE with the mixture of chloroform and methanol was recommended for small hydrophobic compounds.

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.

Advances in Research on Pig Salivary Analytes: A Window to Reveal Pig Health and Physiological Status

Saliva is an important exocrine fluid that is easy to collect and is a complex mixture of proteins and other molecules from multiple sources from which considerable biological information can be mined. Pig saliva, as an easily available biological liquid rich in bioactive ingredients, is rich in nucleic acid analytes, such as eggs, enzymes, amino acids, sugars, etc. The expression levels of these components in different diseases have received extensive attention, and the analysis of specific proteins, metabolites, and biological compositions in pig saliva has become a new direction for disease diagnosis and treatment. The study of the changes in analytes in pig saliva can provide a new strategy for early diagnosis, prognosis assessment, and treatment of diseases. In this paper, the detection methods and research progress of porcine salivary analytes are reviewed, the application and research progress of porcine salivary analytes in diseases are discussed, and the future application prospect is presented.

Salivary metabolomics in patients with oral lichen planus: a preliminary study based on NMR spectroscopy

OBJECTIVES

The present preliminary study aimed to investigate the salivary metabolic profile in patients with asymptomatic oral lichen planus (OLP) using nuclear magnetic resonance (NMR) spectroscopy.

MATERIAL AND METHODS

Stimulated whole mouth saliva (SWMS) samples were collected from 15 reticular OLP female patients and 15 from age- and sex-matched controls (HCs). A total of 23 metabolites were identified and quantified. Mann-Whitney's U test was used to compare the determined concentration salivary metabolite concentrations between OLP patients and the healthy controls.

RESULTS

The concentration of acetate, methylamine, and pyruvate was elevated, whereas the concentration of tyrosine was decreased in the saliva of OLP patients compared with HCs. To identify a combination of metabolites, multivariate discrimination function analysis (DFA) was conducted. DFA analysis have shown that the most powerful discrimination between the groups was achieved when methylamine and tyrosine were considered as combined biomarkers.

CONCLUSIONS

Salivary tyrosine was of particular interest and a promising finding for the screening of OLP and its progression. Further longitudinal studies are required to establish it as a reliable salivary biomarker in OLP.

CLINICAL RELEVANCE

The salivary metabolic profiling can describe the pathologic characteristics of OLP on non-invasive saliva samples and NMR analysis. Salivary metabolites provide details to considered early detectors and to impact oral health of OLP patients.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Metabolomics analysis in saliva from periodontally healthy, gingivitis and periodontitis patients

OBJECTIVE

The aim of this study was to investigate metabolomics markers in the saliva of patients with periodontal health, gingivitis and periodontitis.

BACKGROUND

The use of metabolomics for diagnosing and monitoring periodontitis is promising. Although several metabolites have been reported to be altered by inflammation, few studies have examined metabolomics in saliva collected from patients with different periodontal phenotypes.

METHODS

Saliva samples collected from a total of 63 patients were analysed by nuclear magnetic resonance (NMR) followed by ELISA for interleukin (IL)-1β. The patient sample, well-characterised clinically, included periodontal health (n = 8), gingivitis (n = 19) and periodontitis (n = 36) cases, all non-smokers and not diabetic.

RESULTS

Periodontal diagnosis (healthy/gingivitis/periodontitis) was not associated with any salivary metabolites in this exploratory study. Periodontal staging showed nominal associations with acetoin (p = .030) and citrulline (p = .047). Among other investigated variables, the use of systemic antibiotics in the previous 3 months was associated with higher values of the amino acids taurine, glycine and ornithine (p = .002, p = .05 and p = .005, respectively, at linear regression adjusted for age, gender, ethnicity, body mass index and staging).

CONCLUSION

While periodontal staging was marginally associated with some salivary metabolites, other factors such as systemic antibiotic use may have a much more profound effect on the microbial metabolites in saliva. Metabolomics in periodontal disease is still an underresearched area that requires further observational studies on large cohorts of patients, aiming to obtain data to be used for clinical translation.

Data Mining of Microarray Datasets in Translational Neuroscience

Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.

Identification of potential salivary biomarkers for Sjögren's syndrome with an untargeted metabolomic approach

INTRODUCTION

Despite the rise of metabolomics over the past years, and particularly salivary metabolomics, little research on Sjögren's syndrome (SS) biomarkers has focused on the salivary metabolome.

OBJECTIVES

This study aims to identify metabolites that could be used as biomarkers for SS.

METHODS

Using the software called XCMS online, the salivary metabolic profiles obtained with liquid chromatography coupled to high-resolution mass spectrometry for 18 female SS patients were compared to those obtained for 22 age-matched female healthy controls.

RESULTS AND CONCLUSION

A total of 91 metabolites showed differential expression in SS patients. A putative identification was proposed with the use of a database for 37 of these metabolites and, of these, 16 identifications were confirmed. Given the identified metabolites, some important metabolic pathways, such as amino acid metabolism, purine metabolism, or even the citric acid cycle seem to be affected. Through the analyses of the ROC (receiver operating characteristic) curves, three metabolites, namely alanine, isovaleric acid, and succinic acid, showed both good sensitivity (respectively 1.000, 1.000, and 0.750) and specificity (respectively 0.692, 0.615, and 0.692) for identifying SS and could then be interesting biomarkers for a potential salivary diagnosis test.

Untargeted Metabolomic Profiling of Aqueous and Lyophilized Pooled Human Feces from Two Diet Cohorts Using Two-Dimensional Gas Chromatography Coupled with Time-of-Flight Mass Spectrometry

The metabolic profiles of human feces are influenced by various genetic and environmental factors, which makes feces an attractive biosample for numerous applications, including the early detection of gut diseases. However, feces is complex, heterogeneous, and dynamic with a significant live bacterial biomass. With such challenges, stool metabolomics has been understudied compared to other biospecimens, and there is a current lack of consensus on methods to collect, prepare, and analyze feces. One of the critical steps required to accelerate the field is having a metabolomics stool reference material available. Fecal samples are generally presented in two major forms: fecal water and lyophilized feces. In this study, two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) was used as an analytical platform to characterize pooled human feces, provided by the National Institute of Standards and Technology (NIST) as Research-Grade Test Materials. The collected fecal samples were derived from eight healthy individuals with two different diets: vegans and omnivores, matched by age, sex, and body mass index (BMI), and stored as fecal water and lyophilized feces. Various data analysis strategies were presented to determine the differences in the fecal metabolomic profiles. The results indicate that the sample storage condition has a major influence on the metabolic profiles of feces such that the impact from storage surpasses the metabolic differences from the diet types. The findings of the current study would contribute towards the development of a stool reference material.

Surface Active Salivary Metabolites Indicate Oxidative Stress and Inflammation in Obstructive Sleep Apnea

PURPOSE

Obstructive sleep apnea (OSA), a highly prevalent and potentially serious sleep disorder, requires effective screening tools. Saliva is a useful biological fluid with various metabolites that might also influence upper airway patency by affecting surface tension in the upper airway. However, little is known about the composition and role of salivary metabolites in OSA. Therefore, we investigated the metabolomics signature in saliva from the OSA patients and evaluated the associations between identified metabolites and salivary surface tension.

METHODS

We studied 68 subjects who visited sleep clinic due to the symptoms of OSA. All underwent full-night in-lab polysomnography. Patients with apnea-hypopnea index (AHI) < 10 were classified to the control, and those with AHI ≥ 10 were the OSA groups. Saliva samples were collected before and after sleep. The centrifuged saliva samples were analyzed by liquid chromatography with high-resolution mass spectrometry (ultra-performance liquid chromatography-tandem mass spectrometry; UPLC-MS/MS). Differentially expressed salivary metabolites were identified using open source software (XCMS) and Compound Discoverer 2.1. Metabolite set enrichment analysis (MSEA) was performed using MetaboAnalyst 5.0. The surface tension of the saliva samples was determined by the pendant drop method.

RESULTS

Three human-derived metabolites (1-palmitoyl-2-[5-hydroxyl-8-oxo-6-octenoyl]-sn-glycerol-3-phosphatidylcholine [PHOOA-PC], 1-palmitoyl-2-[5-keto-8-oxo-6-octenoyl]-sn-glycerol-3-phosphatidylcholine [KPOO-PC], and 9-nitrooleate) were significantly upregulated in the after-sleep salivary samples from the OSA patients compared to the control group samples. Among the candidate metabolites, only PHOOA-PC was correlated with the AHI. In OSA samples, salivary surface tension decreased after sleep. The differences in surface tension were negatively correlated with PHOOA-PC and 9-nitrooleate concentrations. Furthermore, MSEA revealed that arachidonic acid-related metabolism pathways were upregulated in the after-sleep samples from the OSA group.

CONCLUSIONS

This study revealed that salivary PHOOA-PC was correlated positively with the AHI and negatively with salivary surface tension in the OSA group. Salivary metabolomic analysis may improve our understanding of upper airway dynamics and provide new insights into novel biomarkers and therapeutic targets in OSA.

Oral Sources of Salivary Metabolites

The oral cavity is very diverse, where saliva plays an important role in maintaining oral health. The metabolism of saliva has been used to investigate oral diseases as well as general diseases, mainly to detect diagnostic biomarkers. There are many sources of salivary metabolites in the mouth. The online English language search and PubMed databases were searched to retrieve relevant studies on oral salivary metabolites. The physiological balance of the mouth is influenced by many factors that are reflected in the salivary metabolite profile. Similarly, the dysbiosis of microbes can alter the salivary metabolite profile, which may express oral inflammation or oral diseases. This narrative review highlights the factors to be considered when examining saliva and its use as a diagnostic biofluid for different diseases. Salivary metabolites, mainly small molecular metabolites may enter the bloodstream and cause illness elsewhere in the body. The importance of salivary metabolites produced in the oral cavity as risk factors for general diseases and their possible relationship to the body’s function are also discussed.

Saliva Metabolomic Profile in Dental Medicine Research: A Narrative Review

Metabolomic research tends to increase in popularity over the years, leading to the identification of new biomarkers related to specific health disorders. Saliva is one of the most newly introduced and systematically developed biofluids in the human body that can serve as an informative substance in the metabolomic profiling armamentarium. This review aims to analyze the current knowledge regarding the human salivary metabolome, its alterations due to physiological, environmental and external factors, as well as the limitations and drawbacks presented in the most recent research conducted, focusing on pre—analytical and analytical workflows. Furthermore, the use of the saliva metabolomic profile as a promising biomarker for several oral pathologies, such as oral cancer and periodontitis will be investigated.

Salivary Interleukin Levels in Oral Squamous Cell Carcinoma and Oral Epithelial Dysplasia: Findings from a Sri Lankan Study

The incidence of oral squamous cell carcinoma (OSCC), and its precursor, oral epithelial dysplasia (OED), is on the rise, especially in South Asia. OSCC is the leading cancer in males in Sri Lanka, with >80% diagnosed at advanced clinical stages. Early detection is paramount to improve patient outcome, and saliva testing is a promising non-invasive tool. The aim of this study was to assess salivary interleukins (lL1β, IL6, and IL8) in OSCC, OED and disease-free controls in a Sri Lankan study cohort. A case-control study with OSCC (n = 37), OED (n = 30) patients and disease-free controls (n = 30) was conducted. Salivary lL1β, IL6, and IL8 were quantified using enzyme-linked immuno-sorbent assay. Comparisons between different diagnostic groups and potential correlations to risk factors were assessed. Salivary levels for the three tested interleukins increased from disease-free controls through OED, and were highest in OSCC samples. Furthermore, the levels of IL1β, IL6, and IL8 increased progressively with OED grade. The discrimination between patients (OSCC and OED) and controls, as assessed by AUC of receiver operating characteristic curves, was 0.9 for IL8 (p = 0.0001) and 0.8 for IL6 (p = 0.0001), while IL1β differentiated OSCC from controls (AUC 0.7, p = 0.006). No significant associations were found between salivary interleukin levels and smoking, alcohol, and betel quid risk factors. Our findings suggest that salivary IL1β, IL6, and IL8 are associated with disease severity of OED, and are potential biomarkers for predicting disease progression in OED, and the screening of OSCC.

Salivary Metabolomics in the Diagnosis and Monitoring of Neurodegenerative Dementia

Millions of people suffer with dementia worldwide. However, early diagnosis of neurodegenerative diseases/dementia (NDD) is difficult, and no specific biomarkers have been found. This study aims to review the applications of salivary metabolomics in diagnostics and the treatment monitoring of NDD A literature search of suitable studies was executed so that a total of 29 original research articles were included in the present review. Spectroscopic methods, mainly nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry, give us a broad view of changes in salivary metabolites in neurodegenerative diseases. The role of different salivary metabolites in brain function is discussed. Further studies with larger patient cohorts should be carried out to investigate the association between salivary metabolites and brain function and thus learn more about the complicated pathways in the human body.

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.

A Preliminary Pilot Study: Metabolomic Analysis of Saliva in Oral Candidiasis

Early detection of oral candidiasis is essential. However, most currently available methods are time-consuming and useful only for screening patients. Previous studies on the relationship between oral candidiasis and saliva have focused on saliva volume and not on its components. Therefore, to clarify the effects of oral candidiasis on salivary metabolites, the relationship between salivary components and oral candidiasis was investigated by comparing the salivary metabolites of oral candidiasis patients and those not previously diagnosed with candidiasis. Forty-five participants visiting our university hospital were included and classified into two groups, the Candida group and the control group, based on the Candida detection test results. The unstimulated saliva was collected using the spitting method over 15 min, and the stimulated saliva was collected using the gum-chewing method over 10 min. The saliva volume was measured, and the saliva samples were frozen and analyzed metabolomically. Metabolome analysis revealed 51 metabolites with peak detection rates exceeding 50%. There was no significant difference in age and sex between the Candida and control groups. In the Candida group, five metabolites (tyrosine, choline, phosphoenolpyruvate, histidine, and 6-phosphogluconate) were significantly elevated in the unstimulated, two (octanoic acid and uridine monophosphate(UMP)) were significantly increased, and four (ornithine, butyrate, aminovalerate and aminolevulinate) were significantly decreased in the stimulated saliva. This study suggests the possibility of identifying metabolites specific to patients with oral candidiasis, which could aid prompt diagnosis.

Integrated analysis of the salivary microbiome and metabolome in chronic and aggressive periodontitis: A pilot study

This pilot study was designed to identify the salivary microbial community and metabolic characteristics in patients with generalized periodontitis. A total of 36 saliva samples were collected from 13 patients with aggressive periodontitis (AgP), 13 patients with chronic periodontitis (ChP), and 10 subjects with periodontal health (PH). The microbiome was evaluated using 16S rRNA gene high-throughput sequencing, and the metabolome was accessed using gas chromatography-mass spectrometry. The correlation between microbiomes and metabolomics was analyzed by Spearman’s correlation method. Our results revealed that the salivary microbial community and metabolite composition differed significantly between patients with periodontitis and healthy controls. Striking differences were found in the composition of salivary metabolites between AgP and ChP. The genera Treponema, Peptococcus, Catonella, Desulfobulbus, Peptostreptococcaceae_[XI] ([G-2], [G-3] [G-4], [G-6], and [G-9]), Bacteroidetes_[G-5], TM7_[G-5], Dialister, Eikenella, Fretibacterium, and Filifactor were present in higher levels in patients with periodontitis than in the healthy participants. The biochemical pathways that were significantly different between ChP and AgP included pyrimidine metabolism; alanine, aspartate, and glutamate metabolism; beta-alanine metabolism; citrate cycle; and arginine and proline metabolism. The differential metabolites between ChP and AgP groups, such as urea, beta-alanine, 3-aminoisobutyric acid, and thymine, showed the most significant correlations with the genera. These differential microorganisms and metabolites may be used as potential biomarkers to monitor the occurrence and development of periodontitis through the utilization of non-invasive and convenient saliva samples. This study reveals the integration of salivary microbial data and metabolomic data, which provides a foundation to further explore the potential mechanism of periodontitis.

The Assessment of Serum Cytokines in Oral Squamous Cell Carcinoma Patients: An Observational Prospective Controlled Study

Background: The oral squamous cell carcinoma (OSCC) tumor microenvironment (TME) is a complex interweb of cells and mediators balancing carcinogenesis, inflammation, and the immune response. However, cytokines are not only secreted within the TME but also released by a variety of other cells that do not comprise the TME; therefore, a thorough assessment of humoral changes in OSCC should include the measurement of serum cytokines. Methods: We assessed the role of various serum cytokines in the evolution of OSCC, before and after treatment, versus a control group. We measured the serum concentrations of MIP-1α, IL-1β, IL-4, IL-6, IL-8, IL-10, and TNF-α. Results: Significantly higher values (p < 0.01) were noted for IL-1β, IL-6, IL-8, IL-10, and TNF-α in the OSCC group before treatment (n = 13) compared with the control group (n = 14), and the increased concentrations persisted after treatment (n = 11). Furthermore, the variations in the values of MIP-1α, IL-1β, IL-10, and TNF-α are correlated both before and after treatment (p < 0.01). In the pretherapeutic group, IL-6 and IL-8 concentrations also correlate with IL-1β and IL-10 serum levels (p < 0.01), while in the posttherapeutic group, IL-4 varies with MIP-1α and TNF-α (p < 0.01). Conclusion: In OSCC patients, serum cytokine levels are significantly higher compared with control, but they are not significantly altered by treatment, therefore implying that they are also influenced by systemic factors. The interactions between all involved cytokines and the various pathways they regulate warrant further studies to clarify their definitive roles.

Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes

Objective

The concentrations of endogenous metabolites in saliva can be altered based on the systemic condition of the hosts and may, in theory, serve as a reflection of systemic disease progression. Hemoglobin A1C is used clinically to measure long-term average glycemic control. The aim of the study was to demonstrate if there were differences in the salivary metabolic profiles between well and poorly controlled type 1 and type 2 subjects with diabetes. Subjects and Methods. Subjects with type 1 and type 2 diabetes were enrolled (n = 40). The subjects were assigned to phenotypic groups based on their current level of A1C: <7 = well-controlled and >7 = poorly controlled. Demographic data, age, gender, and ethnicity, were used to match the two phenotypic groups. Whole saliva samples were collected and immediately stored at -80°C. Samples were spiked using an isotopically labeled internal standard and analyzed by UPLC-TOF-MS using a Waters SYNAPT G2-Si mass spectrometer.

Results

Unsupervised principal components analysis (PCA) and orthogonal partial least squares regression discrimination analysis (OPLS-DA) were used to define unique metabolomic profiles associated with well and poorly controlled diabetes based on A1C levels.

Conclusion

OPLS-DA demonstrates good separation of well and poorly controlled in both type 1 and type 2 diabetes. This provides evidence for developing saliva-based monitoring tools for diabetes.

Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta-analysis

BACKGROUND

Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.

METHODS

We conducted a meta-analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random- or fixed-effects model. Area under the curve (AUC) and summary receiver-operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.

RESULTS

Our systematic review and meta-analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713-0.740) and 0.717 (95% CI: 0.703-0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364-0.432) and 2.597 (95% CI: 2.389-2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624-9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post-test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non-MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent-free biophotonic), and nations.

CONCLUSION

Saliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.

Salivary metabolomics with machine learning for colorectal cancer detection

As the worldwide prevalence of colorectal cancer (CRC) increases, it is vital to reduce its morbidity and mortality through early detection. Saliva‐based tests are an ideal noninvasive tool for CRC detection. Here, we explored and validated salivary biomarkers to distinguish patients with CRC from those with adenoma (AD) and healthy controls (HC). Saliva samples were collected from patients with CRC, AD, and HC. Untargeted salivary hydrophilic metabolite profiling was conducted using capillary electrophoresis–mass spectrometry and liquid chromatography–mass spectrometry. An alternative decision tree (ADTree)‐based machine learning (ML) method was used to assess the discrimination abilities of the quantified metabolites. A total of 2602 unstimulated saliva samples were collected from subjects with CRC (n = 235), AD (n = 50), and HC (n = 2317). Data were randomly divided into training (n = 1301) and validation datasets (n = 1301). The clustering analysis showed a clear consistency of aberrant metabolites between the two groups. The ADTree model was optimized through cross‐validation (CV) using the training dataset, and the developed model was validated using the validation dataset. The model discriminating CRC + AD from HC showed area under the receiver‐operating characteristic curves (AUC) of 0.860 (95% confidence interval [CI]: 0.828‐0.891) for CV and 0.870 (95% CI: 0.837‐0.903) for the validation dataset. The other model discriminating CRC from AD + HC showed an AUC of 0.879 (95% CI: 0.851‐0.907) and 0.870 (95% CI: 0.838‐0.902), respectively. Salivary metabolomics combined with ML demonstrated high accuracy and versatility in detecting CRC.

Translating Science into Improved Health for All

Our world is at a turning point with biological and social pathogens wreaking havoc at the same time that science and technology are exploding with new discoveries. It is a pivotal time for the new report Oral Health in America: Advances and Challenges to be released and a pivotal time for our profession to take action and lead. The art, science, and practice of dentistry is very different from 20 y ago when the original Surgeon General's report was released. We are on the precipice of individualized health care where providers will collaborate to deliver diagnostics and therapeutics that are data driven and inclusive of the social determinants of health. To move forward with alacrity requires a strong scientific foundation, effective educational approaches, an understanding of the upstream determinants of health, and partnerships across the health professions and beyond. Oral health has never been more important, and now is the time for our profession to further develop, elevate, and translate the science into practice and policy to improve the nation's health.

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.

Benefits and Implications of Resveratrol Supplementation on Microbiota Modulations: A Systematic Review of the Literature

Resveratrol is a polyphenol that has been shown to possess many applications in different fields of medicine. This systematic review has drawn attention to the axis between resveratrol and human microbiota, which plays a key role in maintaining an adequate immune response that can lead to different diseases when compromised. Resveratrol can also be an asset in new technologies, such as gene therapy. PubMed, Cochrane Library, Scopus, Web of Science, and Google Scholar were searched to find papers that matched our topic dating from 1 January 2017 up to 18 January 2022, with English-language restriction using the following Boolean keywords: (“resveratrol” AND “microbio*”). Eighteen studies were included as relevant papers matching the purpose of our investigation. Immune response, prevention of thrombotic complications, microbiota, gene therapy, and bone regeneration were retrieved as the main topics. The analyzed studies mostly involved resveratrol supplementation and its effects on human microbiota by trials in vitro, in vivo, and ex vivo. The beneficial activity of resveratrol is evident by analyzing the changes in the host’s genetic expression and the gastrointestinal microbial community with its administration. The possibility of identifying individual microbial families may allow to tailor therapeutic plans with targeted polyphenolic diets when associated with microbial dysbiosis, such as inflammatory diseases of the gastrointestinal tract, degenerative diseases, tumors, obesity, diabetes, bone tissue regeneration, and metabolic syndrome.

Salivary Metabolomics for Oral Squamous Cell Carcinoma Diagnosis: A Systematic Review

Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer in which the consumption of tobacco and alcohol is considered to be the main aetiological factor. Salivary metabolome profiling could identify novel biochemical pathways involved in the pathogenesis of various diseases. This systematic review was designed to answer the question “Are salivary metabolites reliable for the diagnosis of oral squamous cell carcinoma?”. Following the inclusion and exclusion criteria, nineteen studies were included (according to PRISMA statement guidelines). In all included studies, the diagnostic material was unstimulated whole saliva, whose metabolome changes were determined by different spectroscopic methods. At the metabolic level, OSCC patients differed significantly not only from healthy subjects but also from patients with oral leukoplakia, lichen planus or other oral potentially malignant disorders. Among the detected salivary metabolites, there were the indicators of the impaired metabolic pathways, such as choline metabolism, amino acid pathways, polyamine metabolism, urea cycle, creatine metabolism, glycolysis or glycerolipid metabolism. In conclusion, saliva contains many potential metabolites, which can be used reliably to early diagnose and monitor staging in patients with OSCC. However, further investigations are necessary to confirm these findings and to identify new salivary metabolic biomarkers.