Global metabolomic analysis of human saliva and plasma from healthy and diabetic subjects, with and without periodontal disease

Polyamine biomarkers as indicators of human disease

The significant increase of periodontitis, chronic kidney disease (CKD), Alzheimer's disease and cancer can be attributed to an ageing population. Each disease produces a range of biomarkers that can be indicative of disease onset and progression. Biomarkers are defined as cellular (intra/extracellular components and whole cells), biochemical (metabolites, ions and toxins) or molecular (nucleic acids, proteins and lipids) alterations which are measurable in biological media such as human tissues, cells or fluids. An interesting group of biomarkers that merit further investigation are the polyamines. Polyamines are a group of molecules consisting of cadaverine, putrescine, spermine and spermidine and have been implicated in the development of a range of systemic diseases, in part due to their production in periodontitis. Cadaverine and putrescine within the periodontal environment have demonstrated cell signalling interfering abilities, by way of leukocyte migration disruption. The polyamines spermine and spermidine in tumour cells have been shown to inhibit cellular apoptosis, effectively prolonging tumorigenesis and continuation of cancer within the host. Polyamine degradation products such as acrolein have been shown to exacerbate renal damage in CKD patients. Thus, the use of such molecules has merit to be utilized in the early indication of such diseases in patients.

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

INTRODUCTION

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Salivary biomarkers for discriminating periodontitis in the presence of diabetes

AIM

Salivary biomarkers can help in assessment of periodontitis; however, concentrations may be altered in the presence of diabetes. Hence, the ability of salivary biomarkers to discriminate periodontally healthy type II diabetics (T2DM) from T2DM who have periodontitis was examined.

METHODS

Ninety-two participants (29 with T2DM with chronic periodontitis, DWP; 32 T2DM without chronic periodontitis, DWoP; and 31 Not Periodontitis, NP) provided saliva and clinical parameters of periodontal health were recorded. Salivary concentrations of interleukin (IL)-1β, IL-6, matrix metalloproteinase-8 (MMP-8), macrophage inflammatory protein-1α (MIP-1α), adiponectin and resistin were measured by immunoassay.

RESULTS

Salivary analyte concentrations for IL-1β, MMP-8 and resistin correlated with clinical parameters of periodontitis, with MMP-8 demonstrating the strongest positive correlation with PD ≥5 mm (p < 0.0001). Periodontal health was reflected in salivary analyte concentrations by group, with concentrations of IL-1β and MMP-8 showing significant associations with periodontitis (p ≤ 0.04) that increased in concentration from health to DWoP to DWP. Odds ratio (OR) analyses showed that MMP-8 discriminated periodontitis from NP (OR of 8.12; 95% CI: 1.01-65.33; p = 0.03) and in the presence of T2DM (DWP vs DWoP, OR = 5.09; 95% CI: 1.24-20.92; p = 0.03).

CONCLUSION

Salivary MMP-8 and IL-1β discriminate periodontitis in T2DM.

Salivary metabolomics for cancer detection

Introduction: Saliva is an ideal biofluid that can be collected in a noninvasive manner, enabling safe and frequent screening of various diseases. Recent studies have revealed that salivary metabolomics analysis has the potential to detect both oral and systemic cancers. Area covered: We reviewed the technical aspects, as well as applications, of salivary metabolomics for cancer detection. The topics include the effects of preconditioning and the method of sample collection, sample storage, processing, measurement, data analysis, and validation of the results. We also examined the rational relationship between salivary biomarkers and tumors distant from the oral cavity. A strategy to establish standard operating protocols for obtaining reproducible quantification data is also discussed Expert opinion: Salivary metabolomics reflects oral and systematic health status, which potently enables cancer detection. The sensitivity and specificity of each marker and their combinations have been well evaluated, but a validation study is required. Further, the standard operating protocol for each procedure should be established to obtain reproducible data before clinical usage.

Gingival fibroblasts dynamically reprogram cellular metabolism during infection of Porphyromonas gingivalis

OBJECTIVE

The purpose of the present study was to explore the sequential changes in the cellular metabolism in gingival fibroblasts (GFs) in response toPorphyromonas gingvalis (P. gingivalis) ATCC33277 infection.

DESIGN

GFs were treated withP. gingivalis at the MOI of 50 for 4, 24 and 48 h to mimic the early, medium, and late phase in the bacterial infection. LDH assay and cell counting kit-8 were utilized to explore cell death and proliferation. Real-time PCR was utilized to explore the gene transcription of pro-inflammatory genes. The relative levels of biomolecules in GFs were measured by gas chromatography-mass spectrometry. Principal component analysis and orthogonal partial least-squares-discriminant analysis were performed to visualize the metabolic difference among experimental groups. In addition, pathway analysis was conducted regarding differential metabolites in GFs.

RESULTS

P. gingivalis infection triggered significant gene transcription of IL-1β, IL 6, MCP 1, and MMP 1 in GFs. In addition, P. gingivalis stimulated cell proliferation of GFs at MOI of 10, 50 and 250. Moreover, P. gingivalis triggered significant cell death at higher MOI. 69, 173 and 148 metabolites were qualitatively detected at 4, 24 and 48 h after P. gingivalis infection respectively in GFs, showing a sequential change of different phase. Kyoto Encyclopedia of Genes and Genomes pathway analysis demonstrated that ATP-binding cassette transporters, glutathione, purine and pyrimidine metabolism was significantly altered in different phase.

CONCLUSIONS

Human GFs may sequentially rewire metabolomics to shape the inflammatory responses and support the proliferation of host cells during P. gingivalis infection.

Alteration of salivary microbiome in periodontitis with or without type-2 diabetes mellitus and metformin treatment

We aimed to explore the effects of type-2 diabetes mellitus (T2DM) and hypoglycemic therapy on the salivary microbiome in periodontitis patients and identify the potential salivary micro-biomarker for the early warning of T2DM. Saliva samples were collected from healthy individuals (Health), periodontitis patients (P), T2DM patients, periodontitis patients with T2DM (DAP), and DAP patients treated with Metformin (Met). Samples were determined by16S rRNA gene sequencing. 29 phyla, 322 genera, and 333 species of salivary microbiome were annotated. Compared to the Health group, the P and DAP group showed a significantly higher diversity of saliva microbiota, while the T2DM and Met group had no significant difference in microbial abundance but showed a trend of increasing diversity. Other than well-known periodontitis-inducing pathogens, the proportion of Prevotella copri, Alloprevotella rava, and Ralstonia pickettii, etc. were also significantly increased in periodontitis patients with or without T2DM. After effective glycemic control, the abundance of Prevotella copri, Alloprevotella rava, Ralstonia pickettii, etc. decreased in periodontitis patients with companion T2DM. The accuracies of the classification models in differentiating Health-vs.-P, DAP-vs.-P, and T2DM-vs.-P were 100%, 96.3%, and 98.1%, respectively. Hypoglycemic therapy could reconstruct the saliva microbiota and hence improve the localized conditions of diabetes patients with periodontitis.

Salivary metabolite levels in perinatally HIV-infected youth with periodontal disease

INTRODUCTION

Salivary metabolite profiles are altered in adults with HIV compared to their uninfected counterparts. Less is known about youth with HIV and how oral disorders that commonly accompany HIV infection impact salivary metabolite levels.

OBJECTIVE

As part of the Adolescent Master Protocol multi-site cohort study of the Pediatric HIV/AIDS Cohort Study (PHACS) network we compared the salivary metabolome of youth with perinatally-acquired HIV (PHIV) and youth HIV-exposed, but uninfected (PHEU) and determined whether metabolites differ in PHIV versus PHEU.

METHODS

We used three complementary targeted and discovery-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflows to characterize salivary metabolite levels in 20 PHIV and 20 PHEU youth with and without moderate periodontitis. We examined main effects associated with PHIV and periodontal disease, and the interaction between them.

RESULTS

We did not identify differences in salivary metabolite profiles that remained significant under stringent control for both multiple between-group comparisons and multiple metabolites. Levels of cadaverine, a known periodontitis-associated metabolite, were more abundant in individuals with periodontal disease with the difference being more pronounced in PHEU than PHIV. In the discovery-based dataset, we identified a total of 564 endogenous peptides in the metabolite extracts, showing that proteolytic processing and amino acid metabolism are important to consider in the context of HIV infection.

CONCLUSION

The salivary metabolite profiles of PHIV and PHEU youth were overall very similar. Individuals with periodontitis particularly among the PHEU youth had higher levels of cadaverine, suggesting that HIV infection, or its treatment, may influence the metabolism of oral bacteria.

Finding distinctions between oral cancer and periodontitis using saliva metabolites and machine learning

OBJECTIVE

The aim of this research is the study of metabolic pathways related to oral cancer and periodontitis along with development of machine-learning model for elucidation of these diseases based on saliva metabolites of patients.

METHODS

Data mining, metabolomic pathways analysis, study of metabolite-gene networks related to these diseases. Machine-learning and deep-learning methods for development of the model for recognition of oral cancer versus periodontitis, using patients' saliva.

RESULTS

The most accurate classifications between oral cancer and periodontitis were performed using neural networks, logistic regression and stochastic gradient descent confirmed by the separate 10-fold cross-validations. The best results were achieved by the deep-learning neural network with the TensorFlow program. Accuracy of the resulting model was 79.54%. The other methods, which did not rely on deep learning, were able to achieve comparable, although slightly worse results with respect to accuracy.

CONCLUSION

Our results demonstrate a possibility to distinguish oral cancer from periodontal disease by analysis the saliva metabolites of a patient, using machine-learning methods. These findings may be useful in the development of a non-invasive method to aid care providers in determining between oral cancer and periodontitis quickly and effectively.

Metabolome of canine and human saliva: a non-targeted metabolomics study

INTRODUCTION

Saliva metabolites are suggested to reflect the health status of an individual in humans. The same could be true with the dog (Canis lupus familiaris), an important animal model of human disease, but its saliva metabolome is unknown. As a non-invasive sample, canine saliva could offer a new alternative material for research to reveal molecular mechanisms of different (patho)physiological stages, and for veterinary medicine to monitor dogs' health trajectories.

OBJECTIVES

To investigate and characterize the metabolite composition of dog and human saliva in a non-targeted manner.

METHODS

Stimulated saliva was collected from 13 privately-owned dogs and from 14 human individuals. We used a non-targeted ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-qTOF-MS) method to measure metabolite profiles from saliva samples.

RESULTS

We identified and classified a total of 211 endogenous and exogenous salivary metabolites. The compounds included amino acids, amino acid derivatives, biogenic amines, nucleic acid subunits, lipids, organic acids, small peptides as well as other metabolites, like metabolic waste molecules and other chemicals. Our results reveal a distinct metabolite profile of dog and human saliva as 25 lipid compounds were identified only in canine saliva and eight dipeptides only in human saliva. In addition, we observed large variation in ion abundance within and between the identified saliva metabolites in dog and human.

CONCLUSION

The results suggest that non-targeted metabolomics approach utilizing UHPLC-qTOF-MS can detect a wide range of small compounds in dog and human saliva with partially overlapping metabolite composition. The identified metabolites indicate that canine saliva is potentially a versatile material for the discovery of biomarkers for dog welfare. However, this profile is not complete, and dog saliva needs to be investigated in the future with other analytical platforms to characterize the whole canine saliva metabolome. Furthermore, the detailed comparison of human and dog saliva composition needs to be conducted with harmonized study design.

Unravelling the Potential of Salivary Volatile Metabolites in Oral Diseases. A Review

Fostered by the advances in the instrumental and analytical fields, in recent years the analysis of volatile organic compounds (VOCs) has emerged as a new frontier in medical diagnostics. VOCs analysis is a non-invasive, rapid and inexpensive strategy with promising potential in clinical diagnostic procedures. Since cellular metabolism is altered by diseases, the resulting metabolic effects on VOCs may serve as biomarkers for any given pathophysiologic condition. Human VOCs are released from biomatrices such as saliva, urine, skin emanations and exhaled breath and are derived from many metabolic pathways. In this review, the potential of VOCs present in saliva will be explored as a monitoring tool for several oral diseases, including gingivitis and periodontal disease, dental caries, and oral cancer. Moreover, the analytical state-of-the-art for salivary volatomics, e.g., the most common extraction techniques along with the current challenges and future perspectives will be addressed unequivocally.

Changes of saliva microbiota in the onset and after the treatment of diabetes in patients with periodontitis

The relationship between type 2 diabetes mellitus (T2DM) and oral microbiota is still insufficiently recognized. In the present study, we compared the salivary microbiome of nondiabetic individuals, treatment-naïve diabetic patients, and diabetic patients treated with metformin or a combination of insulin and other drugs. The α- and β-diversity demonstrated significant differences in the salivary microbiome between the nondiabetic people and patients with a history of diabetes, while little divergence was found among individuals with a history of diabetes. After characterizing the effects of periodontitis on the microbial composition of each group, the salivary microbiome of the treatment-naïve diabetic patient group was compared with that of nondiabetic people and the metformin/combined treatment groups. The results revealed changes in the contents of certain bacteria after both the onset and the treatment of diabetes; among these differential bacteria, Blautia_wexlerae, Lactobacillus_fermentum, Nocardia_coeliaca and Selenomonas_artemidis varied in all processes. A subsequent correlational analysis of the differential bacteria and clinical characteristics demonstrated that salivary microbes were related to drug treatment and certain pathological changes. Finally, the four common differential bacteria were employed for distinguishing the treatment-naïve diabetic patients from the nondiabetic people and the treated patients, with prediction accuracies of 83.3%, 75% and 75%, respectively.

Effect of smokeless tobacco use on salivary glutathione levels among chronic periodontitis patients before and after non-surgical periodontal therapy

INTRODUCTION

Smokeless tobacco (SLT) jeopardizes periodontal health and also produces an imbalance between reactive oxygen species (ROS) and antioxidants (AO) such as glutathione. Glutathione is an important redox regulator in saliva and its maintenance is essential for periodontal health. Periodontitis patients have a reduced total AO capacity in whole saliva, and periodontal therapy restores the redox balance. Hence, the purpose of this study was to investigate the effects of smokeless tobacco use on saliva glutathione levels in patients with chronic periodontitis and to evaluate these effects after non-surgical periodontal therapy.

METHODS

The study included 100 subjects in four groups; healthy, gingivitis, and chronic periodontitis (CP) patients with and without SLT use. Saliva samples were collected, and clinical periodontal parameters were recorded at baseline and at one month after non-surgical periodontal therapy. Glutathione levels were analyzed using spectrophotometry at 412 nm. Statistical analysis was carried out using paired t-test, chi-squared, and analysis of variance (ANOVA).

RESULTS

Mean glutathione values in saliva were found to be lower in periodontitis patients compared to SLT users at baseline and at 1 month post non-surgical periodontal therapy (p<0.001) In addition, non-surgical therapy leads to a highly significant improvement in the glutathione levels in gingivitis, in the CP with and without ST groups (p<0.001).

CONCLUSIONS

Successful non-surgical periodontal therapy leads to considerable progress in the redox balance, thus regulating glutathione levels and reducing the effects of SLT on the periodontium. This emphasises the importance of non-surgical therapy, especially among SLT users.

Biochemical Analysis of Three Biological Fluids and its Response to Non-Surgical Periodontal Therapy in Pre and Postmenopausal Women with Periodontitis

Objectives

Periodontitis is a common chronic inflammatory disease characterized by the destruction of the supporting structures of the teeth. The stages of menopause also worsen inflammatory condition. Biomarkers from biological fluids can be used as a diagnostic indicator to correlate these two conditions of present and future disease activity. The aim of the present study was to evaluate the neopterin levels in three biological fluids obtained from pre- and postmenopausal women with periodontitis following non-surgical periodontal therapy (NSPT, that is, scaling).

Methods

This was a cross-sectional interventional study. Thirty women, aged 40–60 years, with periodontitis were selected according to their menstrual history. They were divided into the pre- and postmenopausal groups, with each group including 15 participants. The neopterin levels were measured in both groups at baseline and 3 months after NSPT. Intergroup comparison and percentage decrement analysis were performed using the independent sample t test, and intragroup comparison was performed using the paired t test.

Results

There were statistically significant reductions in the mean values of saliva, urine, and plasma from baseline to 3 months after NSPT in the groups. Intergroup comparison showed no significant values in the postmenopausal group, and a significant reduction was seen in the mean values was seen in the mean values.

Conclusions

Neopterin levels decreased at 3 months after NSPT in both the groups, suggesting that NSPT can be a gold standard therapy and that the neopterin level could be a indicator to identify periodontal destruction.

Age and gender characteristics of the biochemical composition of saliva: Correlations with the composition of blood plasma

Background

Recently, the attention of researchers to the study of the properties of human saliva, as a material with unique properties and diagnostic capabilities, has increased.

Research objective

to study the connection of the biochemical composition of saliva and blood plasma in the norm, depending on gender and age.

Methods

107 volunteers took part in the study, including 46 female (37.2 ± 3.9 years old) and 61 male (36.1 ± 2.8 years old). In all samples of saliva and blood plasma, 16 biochemical parameters were determined, including mineral and protein composition, enzyme activity. Non-parametric statistical methods were used to process the data.

Results

It has been shown that it is difficult to establish an unambiguous relation between biochemical parameters of saliva and blood plasma. The calculation of the Spearman correlation coefficients showed that only 7 of the 16 parameters demonstrate the presence of a weak correlation between the content in saliva and plasma.

Conclusion

In general, the determination of the composition of saliva may have an independent diagnostic value; in this case, drawing a parallel with the composition of serum and blood plasma is not advisable. Nevertheless, the use of saliva in clinical laboratory diagnostics is associated with the need to establish criteria for the norm and pathology for each biochemical parameter.

The Clinical Utility of Salivary Biomarkers in the Identification of Type 2 Diabetes Risk and Metabolic Syndrome

Type 2 diabetes is traditionally diagnosed by the use of an oral glucose tolerance test and/or HbA1c, both of which require serum collection. Various biomarkers, which are measurable biological substances that provide clinical insight on disease state, have also been effective in the early identification and risk prediction of inflammatory diseases. Measuring biomarker concentrations has traditionally been obtained through serum collection as well. However, numerous biomarkers are detectable in saliva. Salivary analysis has more recently been introduced into research as a potential non-invasive, cost-effective diagnostic for the early identification of type 2 diabetes risk in adults and youth. Therefore, the purpose of this review was to compare 6 established inflammatory biomarkers of type 2 diabetes, in serum and saliva, and determine if similar diagnostic effectiveness is seen in saliva. A lack of standardized salivary analysis, processing, and collection accounts for errors and inconsistencies in conclusive data amongst studies. Proposing a national standardization in salivary analysis, coupled with increased data and research on the utility of saliva as a diagnostic, poses the potential for salivary analysis to be used in diagnostic settings.

Peri-Implantitis Diagnosis and Prognosis Using Biomarkers in Peri-Implant Crevicular Fluid: A Narrative Review

Dental implant diseases, peri-implantitis (PI) and peri-implant mucositis (PIM), have shown wide prevalence in recent studies. Despite the prevalence, diagnosing peri-implant disease (PID) remains challenging as common diagnostic methods of periodontal probing and radiographs may be inaccurate. These methods only document pre-existing destruction rather than current disease activity. Furthermore, there is no current model to predict the progression of PID. Though a predictive model is lacking, biomarkers may offer some potential. Biomarkers are commonly used in medicine to objectively determine disease state, or responses to a therapeutic intervention. Gingival crevicular fluid (GCF) biomarkers have moderate diagnostic validity in periodontitis. Biomarkers in peri-implant crevicular fluid (PICF) also show promising results in regard to their diagnostic and prognostic value. The aim of this review is to summarize the current knowledge of PICF biomarkers in the diagnosis of PID and evaluate their validity to predict disease progression. This review found that PICF studies utilize different methods of sampling and interpretation with varying validity (sensitivity and specificity). A number of promising diagnostic techniques were identified. Commercially available chair-side tests for MMP-8 to diagnose periodontal disease and PID activity are now available. Future directions include proteomics and metabolomics for accurate, site-specific diagnosis and prediction of PID progression. Although more research is needed, this review concludes that the assessment of proinflammatory cytokines (IL-1β, TNFα, MMP-8) in the PICF may be of value to diagnose PI and PIM but current research remains insufficient to indicate whether biomarkers predict peri-implant disease progression.

Pathway Analysis of Global Metabolomic Profiles Identified Enrichment of Caffeine, Energy, and Arginine Metabolism in Smokers but Not Moist Snuff Consumers

Existing US epidemiological data demonstrate that consumption of smokeless tobacco, particularly moist snuff, is less harmful than cigarette smoking. However, the molecular and biochemical changes due to moist snuff consumption relative to smoking remain incompletely understood. We previously reported that smokers (SMK) exhibit elevated oxidative stress and inflammation relative to moist snuff consumers (MSC) and non-tobacco consumers (NTC), based on metabolomic profiling data of saliva, plasma, and urine from MSC, SMK, and NTC. In this study, we investigated the effects of tobacco consumption on additional metabolic pathways using pathway-based analysis tools. To this end, metabolic pathway enrichment analysis and topology analysis were performed through pair-wise comparisons of global metabolomic profiles of SMK, MSC, and NTC. The analyses identified >8 significantly perturbed metabolic pathways in SMK compared with NTC and MSC in all 3 matrices. Among these differentially enriched pathways, perturbations of caffeine metabolism, energy metabolism, and arginine metabolism were mostly observed. In comparison, fewer enriched metabolic pathways were identified in MSC compared with NTC (5 in plasma, none in urine and saliva). This is consistent with our transcriptomics profiling results that show no significant differences in peripheral blood mononuclear cell gene expression between MSC and NTC. These findings, taken together with our previous biochemical, metabolomic, and transcriptomic analysis results, provide a better understanding of the relative changes in healthy tobacco consumers, and demonstrate that chronic cigarette smoking, relative to the use of smokeless tobacco, results in more pronounced biological changes, which could culminate in smoking-related diseases.

Metabolic Profile of Supragingival Plaque Exposed to Arginine and Fluoride

Caries lesions develop when acid production from bacterial metabolism of dietary carbohydrates outweighs the various mechanisms that promote pH homeostasis, including bacterial alkali production. Therapies that provide arginine as a substrate for alkali production in supragingival oral biofilms have strong anticaries potential. The objective of this study was to investigate the metabolic profile of site-specific supragingival plaque in response to the use of arginine (Arg: 1.5% arginine, fluoride-free) or fluoride (F: 1,100 ppm F/NaF) toothpastes. Eighty-three adults of different caries status were recruited and assigned to treatment with Arg or F for 12 wk. Caries lesions were diagnosed using International Caries Detection and Assessment System II, and plaque samples were collected from caries-free and carious tooth surfaces. Taxonomic profiles were obtained by HOMINGS (Human Oral Microbe Identification using Next Generation Sequencing), and plaque metabolism was assessed by the levels of arginine catabolism via the arginine deiminase pathway (ADS), acidogenicity, and global metabolomics. Principal component analysis (PCA), partial least squares-discriminant analysis, analysis of variance, and random forest tests were used to distinguish metabolic profiles. Of the 509 active lesions diagnosed at baseline, 70 (14%) were inactive after 12 wk. Generalized linear model showed that enamel lesions were significantly more likely to become inactive compared to dentin lesions (P < 0.0001), but no difference was found when treatment with Arg was compared to F (P = 0.46). Arg significantly increased plaque ADS activity (P = 0.031) and plaque pH values after incubation with glucose (P = 0.001). F reduced plaque lactate production from endogenous sources (P = 0.02). PCA revealed differences between the metabolic profiles of plaque treated with Arg or F. Arg significantly affected the concentrations of 16 metabolites, including phenethylamine, agmatine, and glucosamine-6-phosphate (P < 0.05), while F affected the concentrations of 9 metabolites, including phenethylamine, N-methyl-glutamate, and agmatine (P < 0.05). The anticaries mechanisms of action of arginine and fluoride are distinct. Arginine metabolism promotes biofilm pH homeostasis, whereas fluoride is thought to enhance resistance of tooth minerals to low pH and reduce acid production by supragingival oral biofilms.

Consumer Safety Considerations of Skin and Oral Microbiome Perturbation

Microbiomes associated with human skin and the oral cavity are uniquely exposed to personal care regimes. Changes in the composition and activities of the microbial communities in these environments can be utilized to promote consumer health benefits, for example, by reducing the numbers, composition, or activities of microbes implicated in conditions such as acne, axillary odor, dandruff, and oral diseases. It is, however, important to ensure that innovative approaches for microbiome manipulation do not unsafely disrupt the microbiome or compromise health, and where major changes in the composition or activities of the microbiome may occur, these require evaluation to ensure that critical biological functions are unaffected. This article is based on a 2-day workshop held at SEAC Unilever, Sharnbrook, United Kingdom, involving 31 specialists in microbial risk assessment, skin and oral microbiome research, microbial ecology, bioinformatics, mathematical modeling, and immunology. The first day focused on understanding the potential implications of skin and oral microbiome perturbation, while approaches to characterize those perturbations were discussed during the second day. This article discusses the factors that the panel recommends be considered for personal care products that target the microbiomes of the skin and the oral cavity.

Biomolecular Analysis of Beta Dose-Dependent Cutaneous Radiation Injury in a Porcine Model

While cutaneous radiation injury (CRI) is generally referenced as a consequence of a nuclear attack, it can also be caused by less dangerous events such as the use of dirty bombs, industrial radiological accidents, or accidental overexposure of beta (β) particle or gamma (γ) radiation sources in medical procedures. Although the gross clinical consequences of these injuries have been well documented, relatively little is known about the molecular changes underlying the progression of pathology. Here we describe a porcine model of cutaneous radiation injury after skin was exposed to strontium-90 b particle at doses of 16-42 Gy and characterize the anatomical and molecular changes over 70 days. The results show that irradiated sites displayed dosedependent increases in erythema and moist desquamation that peaked between days 35 and 42. Dose-dependent histopathological changes were observed, with higher doses exhibiting increased inflammation and epidermal hyperplasia beyond day 35. Furthermore, immunohistochemistry showed that exposure to 37 Gy β-particle radiation decreased epidermal cell proliferation and desmosomal junction proteins at day 70, suggesting compromised epidermal integrity. Metabolomic analysis of biopsies revealed dose- and time-dependent changes as high as 252-fold in several metabolites not previously linked to CRI. These alterations were seen in pathways reflecting protein degradation, oxidative stress, eicosanoid production, collagen matrix remodeling, mitochondrial stress, cell membrane composition and vascular disruption. Taken together, these data show that exposure to high doses of β particle damaged the molecular processes underlying skin integrity to a greater extent and for a longer period of time than has been shown previously. These findings further understanding of radiation-induced skin injury and serve as a foundation for the development and testing of potential therapeutics to treat CRI.

The Saliva Metabolome in Association to Oral Health Status

Periodontitis is one of the most prevalent oral diseases worldwide and is caused by multifactorial interactions between host and oral bacteria. Altered cellular metabolism of host and microbes releases a number of intermediary end products known as metabolites. There is an increasing interest in identifying metabolites from oral fluids such as saliva to widen the understanding of the complex pathogenesis of periodontitis. It is believed that some metabolites might serve as indicators toward early detection and screening of periodontitis and perhaps even for monitoring its prognosis in the future. Because contemporary periodontal screening methods are deficient, there is an urgent need for novel approaches in periodontal screening procedures. To this end, we associated oral parameters (clinical attachment level, periodontal probing depth, supragingival plaque, supragingival calculus, number of missing teeth, and removable denture) with a large set of salivary metabolites ( n = 284) obtained by mass spectrometry among a subsample ( n = 909) of nondiabetic participants from the Study of Health in Pomerania (SHIP-Trend-0). Linear regression analyses were performed in age-stratified groups and adjusted for potential confounders. A multifaceted image of associated metabolites ( n = 107) was revealed with considerable differences according to age groups. In the young (20 to 39 y) and middle-aged (40 to 59 y) groups, metabolites were predominantly associated with periodontal variables, whereas among the older subjects (≥60 y), tooth loss was strongly associated with metabolite levels. Metabolites associated with periodontal variables were clearly linked to tissue destruction, host defense mechanisms, and bacterial metabolism. Across all age groups, the bacterial metabolite phenylacetate was significantly associated with periodontal variables. Our results revealed alterations of the salivary metabolome in association with age and oral health status. Among our comprehensive panel of metabolites, periodontitis was significantly associated with the bacterial metabolite phenylacetate, a promising substance for further biomarker research.

Metabolomics in chronic lung diseases

Chronic lung diseases represent a significant global burden. Their increasing incidence and complexity render a comprehensive, multidisciplinary and personalized approach to each patient, critically important. Most recently, unique biochemical pathways and disease markers have been identified through large-scale metabolomic studies. Metabolomics is the study of metabolic pathways and the measurement of unique biomolecules in a living system. Analysing samples from different compartments such as bronchoalveolar lavage fluid (BALF) and plasma has proven useful for the characterization of a number of pathological conditions and offers promise as a clinical tool. For example, several studies using mass spectrometry (MS) have shown alterations in the sphingolipid metabolism of chronic obstructive pulmonary disease (COPD) sufferers. In this article, we present a practical review of the application of metabolomics to the study of chronic lung diseases (CLD): COPD, idiopathic pulmonary fibrosis (IPF) and asthma. The insights, which the analytical strategies employed in metabolomics, have provided to the dissection of the biochemistry of CLD and future clinical biomarkers are explored.

Evaluating All Potential Oral Complications of Diabetes Mellitus

Diabetes mellitus (DM) is associated with several microvascular and macrovascular complications, such as retinopathy, nephropathy, neuropathy, and cardiovascular diseases. The pathogenesis of these complications is complex, and involves metabolic and hemodynamic disturbances, including hyperglycemia, insulin resistance, dyslipidemia, hypertension, and immune dysfunction. These disturbances initiate several damaging processes, such as increased reactive oxygen species (ROS) production, inflammation, and ischemia. These processes mainly exert their damaging effect on endothelial and nerve cells, hence the susceptibility of densely vascularized and innervated sites, such as the eyes, kidneys, and nerves. Since the oral cavity is also highly vascularized and innervated, oral complications can be expected as well. The relationship between DM and oral diseases has received considerable attention in the past few decades. However, most studies only focus on periodontitis, and still approach DM from the limited perspective of elevated blood glucose levels only. In this review, we will assess other potential oral complications as well, including: dental caries, dry mouth, oral mucosal lesions, oral cancer, taste disturbances, temporomandibular disorders, burning mouth syndrome, apical periodontitis, and peri-implant diseases. Each oral complication will be briefly introduced, followed by an assessment of the literature studying epidemiological associations with DM. We will also elaborate on pathogenic mechanisms that might explain associations between DM and oral complications. To do so, we aim to expand our perspective of DM by not only considering elevated blood glucose levels, but also including literature about the other important pathogenic mechanisms, such as insulin resistance, dyslipidemia, hypertension, and immune dysfunction.

Discriminating high-risk cervical Human Papilloma Virus infections with urinary biomarkers via non-targeted GC-MS-based metabolomics

Genital human papillomavirus (HPV) is the world’s most commonly diagnosed sexually transmitted infection, and high-risk HPV types are strongly linked to cervical dysplasia and carcinoma. Puerto Ricans are among the US citizens with higher HPV prevalence and lower screening rates and access to treatment. This bleak statistic was as a motivation to detect biomarkers for early diagnosis of HPV in this population. We collected both urine and cervical swabs from 43 patients attending San Juan Clinics. Cervical swabs were used for genomic DNA extractions and HPV genotyping with the HPV SPF10-LiPA25 kit, and gas chromatography-mass spectrometry (GC-MS) was employed on the urine-derived products for metabolomics analyses. We aimed at discriminating between patients with different HPV categories: HPV negative (HPV-), HPV positive with simultaneous low and high-risk infections (HPV+B) and HPV positive exclusively high-risk (HPV+H). We found that the metabolome of HPV+B is closer to HPV- than to HPV+H supporting evidence that suggests HPV co-infections may be antagonistic due to viral interference leading to a lower propensity for cervical cancer development. In contrast, metabolites of patients with HPV+H were significantly different from those that were HPV-. We identified three urinary metabolites 5-Oxoprolinate, Erythronic acid and N-Acetylaspartic acid that discriminate HPV+H cases from negative controls. These metabolites are known to be involved in a variety of biochemical processes related to energy and metabolism and may likely be biomarkers for HPV high-risk cervical infection. However, further validation should follow using a larger patient cohort and diverse populations to confirm our finding.

Effects of inter-day and intra-day variation on salivary metabolomic profiles

BACKGROUND

Salivary secretion is an important parameter reflecting the health status of an individual and has been used clinically for the diagnosis of various oral diseases, such as xerostomia. Salivary metabolomic profiling is considered an emerging potential tool for the detection of various systemic diseases. To our knowledge, this is the first study to investigate the quantitative relationship between salivary secretion volume and salivary metabolomic profile.

METHODS

To evaluate inter- and intra-day variations in salivary secretion, 234 saliva samples were collected three times per day for three days from 13 subjects and analyzed. Capillary electrophoresis-mass spectrometry was used for non-targeted quantification of water-soluble metabolites.

RESULTS

No significant inter- or intra-day variations were observed in salivary secretion volume. No significant inter-day variations were observed in metabolomic patterns. In contrast, significant intra-day variations were observed in salivary metabolomic profiles. The difference was more obvious for stimulated saliva than for unstimulated saliva. These profile changes were independent of salivary secretion volume.

CONCLUSIONS

Our results indicated that diurnal change had a greater effect on salivary metabolomic profiles than the other factors. Hence, sampling time should be tightly controlled to minimize unexpected bias in the clinical use of salivary metabolomics.

Effect of non-surgical periodontal therapy on salivary metabolic fingerprint of generalized chronic periodontitis using nuclear magnetic resonance spectroscopy

OBJECTIVE

Metabolomic analysis of saliva proved its accuracy in discriminating patients with generalized chronic periodontitis (GCP) from healthy subjects by identifying specific molecular signatures of the disease. There is lack of investigations concerning the effect of periodontal treatment on individual metabolic fingerprints. Therefore, the aim of this study was to determine whether non-surgical periodontal therapy could change salivary metabolomic profile in GCP to one more similar to periodontal health.

DESIGN

Unstimulated whole saliva of 32 controls and 19 GCP patients were obtained prior to and 3 months after conventional staged non-surgical periodontal therapy. Metabolic profiling was performed using Nuclear Magnetic Resonance (NMR) spectroscopy, followed by univariate and multivariate paired approaches to assess the changes introduced by the therapy.

RESULTS

In GCP group, periodontal treatment led to an improvement in all clinical parameters (p < 0.001). The accuracy of the multivariate model in discriminating the metabolomic profile of each GCP patient at two time points was 92.5%. Despite the almost perfect separation of the spectra in the metabolic space, the univariate analysis failed to identify significant variations in single metabolite content. The post-treatment metabolic profile of GCP patients could not be assimilated to that of healthy controls who exhibited different levels of lactate, pyruvate, valine, proline, tyrosine, and formate.

CONCLUSIONS

Based on these data, NMR-spectroscopic analysis revealed that, despite significant changes in the overall metabolomic fingerprint after non-surgical therapy, GCP patients maintained a distinctive metabolic profile compared to healthy individuals.

The salivary microbiome of diabetic and non-diabetic adults with periodontal disease

BACKGROUND

A comparison of the salivary microbiome of non-diabetic and diabetic cohorts having periodontal health, gingivitis and periodontitis could reveal microbial signatures unique to each group that will increase understanding of the role of oral microbiota in the pathogenesis of disease, and assist with diagnosis and risk assessment for both periodontal disease and diabetes.

METHODS

A group of individuals diagnosed with type 2 diabetes (T2D) was compared with a group without T2D. For both the diabetic and non-diabetic cohorts, three subgroups were established: periodontal health, gingivitis, and periodontitis. Salivary DNA was extracted (n = 146), polymerase chain reaction was performed to amplify 16S rRNA hypervariable region V3-V4, and constructed libraries were sequenced and subjected to bioinformatic and statistical analyses.

RESULTS

Microbiome analysis resulted in 88 different genus level operational taxonomic units (OTUs) for differential abundance testing. Results were largely described by two trends. Trend 1 showed OTUs that increased in abundance with increasing periodontal disease, and in diabetics relative to non-diabetics. Trend 1 OTUs comprised a mix of primarily anaerobic commensals and potential periodontopathogens. Trend 2 was driven primarily by genera that decreased in abundance in those with diabetes relative to those without diabetes, which included other anaerobes associated with periodontal disease. Overall, oral microbial diversity decreased in diabetics and increased with progression of periodontal disease compared with periodontally healthy controls.

CONCLUSION

Although select microbiota increased in both diabetes and periodontal disease progression, these genera decreased in co-existing diabetes and periodontal disease. These findings suggest that the genera abundance continues to change with additional stress imposed by co-existing conditions.

Analysis of metabolic profiles of generalized aggressive periodontitis

BACKGROUND AND OBJECTIVE

The specific pathogenesis of generalized aggressive periodontitis (GAgP) has not yet been clarified, and few studies have focused on the association between GAgP and metabolomics. To elucidate the roles of metabolic profiles in the status of GAgP, this study aimed to identify the differential metabolic profiles between patients with GAgP and healthy controls using an untargeted metabolomic profiling method.

MATERIAL AND METHODS

Serum and gingival crevicular fluid samples were collected from healthy controls (n = 20) and patients with GAgP (n = 20) in this cross-sectional study. The relative levels of biomarkers in the samples were measured by gas chromatography-mass spectrometry. Principal components analysis and orthogonal partial least-squares discriminant analysis were used for statistical analysis. Metabolites were analysed qualitatively using the FiehnLib and NIST databases. Full-mouth probing depth and clinical attachment loss were recorded as indexes of periodontal disease.

RESULTS

A total of 349 metabolites were qualitatively detected in the gingival crevicular fluid samples, and 200 metabolites were detected in the serum samples. Compared with healthy controls, patients with GAgP showed significant increases in serum urea and allo-inositol levels. In contrast, glutathione, 2,5-dihydroxybenzaldehyde, adipic acid and 2-deoxyguanosine levels were decreased in patients with GAgP. In the gingival crevicular fluid samples, noradrenaline, uridine, α-tocopherol, dehydroascorbic acid, xanthine, galactose, glucose-1-phosphate and ribulose-5-phosphate levels were increased in patients with GAgP, while thymidine, glutathione and ribose-5-phosphate levels were decreased.

CONCLUSION

The metabolomics analysis by gas chromatography-mass spectrometry is an effective and minimally non-invasive way to differentiate the metabolites characteristic of patients with GAgP. Both serum and gingival crevicular fluid metabolomics are significantly different between patients with GAgP and healthy controls. These metabolic profiles have great potential in detecting GAgP and helping to understand its underlying mechanisms.

Relationship between human immunodeficiency virus (HIV-1) infection and chronic periodontitis

INTRODUCTION

Current studies show that, even in the era of antiretroviral therapies, HIV-1 infection is associated with more severe and frequent refractory chronic periodontitis. Areas covered: This review, based on a systematic analysis of the literature, intends to provide an update on factors that may be involved in the pathogenesis of periodontal disease in HIV-1-infected patients, including local immunosuppression, oral microbial factors, systemic inflammation, salivary markers, and the role of gingival tissue as a possible reservoir of HIV-1. Expert commentary: The therapeutic revolution of ART made HIV-1 infection a chronic controllable disease, reduced HIV-1 mortality rate, restored at least partially the immune response and dramatically increased life expectancy of HIV-1-infected patients. Despite all these positive aspects, chronic periodontitis assumes an important role in the HIV-1 infection status for activating systemic inflammation favoring viral replication and influencing HIV-1 status, and also acting as a possible reservoir of HIV-1. All these issues still need to be clarified and validated, but have important clinical implications that certainly will benefit the diagnosis and management of chronic periodontitis in HIV-1-infected patients, and also contributes to HIV-1 eradication.

Levels of oxidative stress biomarkers and bone resorption regulators in apical periodontitis lesions infected by Epstein-Barr virus

AIM

To investigate whether apical periodontitis lesions infected by Epstein-Barr virus (EBV) exhibit higher levels of oxidative stress biomarkers [8-hydroxydeoxyguanosine (8-OHdG) and oxidized glutathione (GSSG)] and bone resorption regulators [receptor activator of nuclear factor (NF-κB) ligand (RANKL) and osteoprotegerin (OPG)] compared to EBV-negative periapical lesions and healthy pulp tissues.

METHODOLOGY

The experimental group consisted of 30 EBV-positive and 30 EBV-negative periapical lesions collected in conjunction with apicoectomy. The pulp tissues of 20 impacted third molars were used as healthy controls. The qualitative and quantitative analysis of EBV was performed by nested and real-time polymerase chain reaction (PCR), respectively. The levels of RANKL and OPG were analysed by reverse transcriptase real-time PCR. The levels of 8-OHdG and GSSG were determined by enzyme-linked immunosorbent assay (ELISA). Mann-Whitney U-test and Spearman's correlation were used for statistical analysis.

RESULTS

The levels of RANKL, OPG, 8-OHdG and GSSG were significantly higher in apical periodontitis lesions compared to healthy pulp controls (P = 0.001, P < 0.001, P < 0.001 and P < 0.05, respectively). RANKL and OPG mRNA expression was significantly higher in EBV-positive compared to EBV-negative periapical lesions (P < 0.05). There was no significant correlation between EBV copy numbers and levels of RANKL, OPG, 8OH-dG and GSSG in apical periodontitis.

CONCLUSION

Levels of bone resorption regulators and oxidative stress biomarkers were increased in apical periodontitis compared to healthy pulp tissues. EBV-positive periapical lesions exhibited higher levels of RANKL and OPG compared to EBV-negative periapical lesions. EBV may contribute to progression of apical periodontitis via enhanced production of bone resorption regulators.

Cutting Edge Methods for Non-Invasive Disease Diagnosis Using E-Tongue and E-Nose Devices

Biomimetic cross-reactive sensor arrays (B-CRSAs) have been used to detect and diagnose a wide variety of diseases including metabolic disorders, mental health diseases, and cancer by analyzing both vapor and liquid patient samples. Technological advancements over the past decade have made these systems selective, sensitive, and affordable. To date, devices for non-invasive and accurate disease diagnosis have seen rapid improvement, suggesting a feasible alternative to current standards for medical diagnostics. This review provides an overview of the most recent B-CRSAs for diagnostics (also referred to electronic noses and tongues in the literature) and an outlook for future technological development.

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

INTRODUCTION

Advances in the development of high-resolution metabolomics (HRM) have provided new opportunities for their use in characterizing exposures to environmental air pollutants and air pollution-related disease etiologies. Exposure assessment studies have considered blood, breath, and saliva as biological matrices suitable for measuring responses to air pollution exposures. The current study examines comparability among these three matrices using HRM and explores their potential for measuring mobile-source air toxics.

METHODS

Four participants provided saliva, exhaled breath concentrate (EBC), and plasma before and after a 2 h road traffic exposure. Samples were analyzed on a Thermo Scientific QExactive MS system in positive electrospray ionization mode and resolution of 70 000 full-width at half-maximum with C18 chromatography. Data were processed using an apLCMS and xMSanalyzer on the R statistical platform.

RESULTS

The analysis yielded 7110, 6019, and 7747 reproducible features in plasma, EBC, and saliva, respectively. Correlations were moderate-to-strong (R = 0.41-0.80) across all pairwise comparisons of feature intensity within profiles, with the strongest between EBC and saliva. The associations of mean intensities between matrix pairs were positive and significant, controlling for subject and sampling time effects. Six out of 20 features shared in all three matrices putatively matched a list of known mobile-source air toxics.

CONCLUSIONS

Plasma, saliva, and EBC have largely comparable metabolic profiles measurable through HRM. These matrices have the potential to be used in identification and measurement of exposures to mobile-source air toxics, though further, targeted study is needed.

Identification of a discriminative metabolomic fingerprint of potential clinical relevance in saliva of patients with periodontitis using 1H nuclear magnetic resonance (NMR) spectroscopy

Periodontitis is characterized by the loss of the supporting tissues of the teeth in an inflammatory-infectious context. The diagnosis relies on clinical and X-ray examination. Unfortunately, clinical signs of tissue destruction occur late in the disease progression. Therefore, it is mandatory to identify reliable biomarkers to facilitate a better and earlier management of this disease. To this end, saliva represents a promising fluid for identification of biomarkers as metabolomic fingerprints. The present study used high-resolution ¹H-nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to identify the metabolic signature of active periodontitis. The metabolome of stimulated saliva of 26 patients with generalized periodontitis (18 chronic and 8 aggressive) was compared to that of 25 healthy controls. Principal Components Analysis (PCA), performed with clinical variables, indicated that the patient population was homogeneous, demonstrating a strong correlation between the clinical and the radiological variables used to assess the loss of periodontal tissues and criteria of active disease. Orthogonal Projection to Latent Structure (OPLS) analysis showed that patients with periodontitis can be discriminated from controls on the basis of metabolite concentrations in saliva with satisfactory explained variance (R2X = 0.81 and R2Y = 0.61) and predictability (Q2Y = 0.49, CV-AUROC = 0.94). Interestingly, this discrimination was irrespective of the type of generalized periodontitis, i.e. chronic or aggressive. Among the main discriminating metabolites were short chain fatty acids as butyrate, observed in higher concentrations, and lactate, γ-amino-butyrate, methanol, and threonine observed in lower concentrations in periodontitis. The association of lactate, GABA, and butyrate to generate an aggregated variable reached the best positive predictive value for diagnosis of periodontitis. In conclusion, this pilot study showed that 1H-NMR spectroscopy analysis of saliva could differentiate patients with periodontitis from controls. Therefore, this simple, robust, non-invasive method, may offer a significant help for early diagnosis and follow-up of periodontitis.

Biofluid lipidome: a source for potential diagnostic biomarkers

Lipidomics is the identification and quantitation of changes in the lipidome of a cell, tissue, organ or biofluid in health and disease using high resolution mass spectrometry. Lipidome of a particular organism has relevance to the disease manifestation as it reflects the metabolic changes which can be a consequence of the disease. Hence these changes in the molecules can be considered as potential markers for screening and early detection of the disease. Biological fluids as blood/serum/plasma, urine, saliva, tear and cerebrospinal fluid, due to their accessibility, offer ease of collection with minimal or no discomfort to the patient and provide a ready footprint of the metabolic changes occurring during disease. This review provides a brief introduction to lipidomics and its role in understanding the metabolic changes in health and disease followed by discussion on the chemical diversity of the lipid species and their biological role, mammalian lipids and their metabolism and role of lipids in pathogens and the immune response before dwelling further into importance of studying lipidome in various biological fluids. The challenges in performing a lipidomic analysis at the experimental and data analysis stages are discussed.

Oral microbe-host interactions: influence of β-glucans on gene expression of inflammatory cytokines and metabolome profile

Background

The aim of this study was to evaluate the effects of β-glucan on the expression of inflammatory mediators and metabolomic profile of oral cells [keratinocytes (OBA-9) and fibroblasts (HGF-1) in a dual-chamber model] infected by Aggregatibacter actinomycetemcomitans. The periodontopathogen was applied and allowed to cross the top layer of cells (OBA-9) to reach the bottom layer of cells (HGF-1) and induce the synthesis of immune factors and cytokines in the host cells. β-glucan (10 μg/mL or 20 μg/mL) were added, and the transcriptional factors and metabolites produced were quantified in the remaining cell layers and supernatant.

Results

The relative expression of interleukin (IL)-1-α and IL-18 genes in HGF-1 decreased with 10 μg/mL or 20 μg/mL of β-glucan, where as the expression of PTGS-2 decreased only with 10 μg/mL. The expression of IL-1-α increased with 20 μg/mL and that of IL-18 increased with 10 μg/mL in OBA-9; the expression of BCL 2, EP 300, and PTGS-2 decreased with the higher dose of β-glucan. The production of the metabolite 4-aminobutyric acid presented lower concentrations under 20 μg/mL, whereas the concentrations of 2-deoxytetronic acid NIST and oxalic acid decreased at both concentrations used. Acetophenone, benzoic acid, and pinitol presented reduced concentrations only when treated with 10 μg/mL of β-glucan.

Conclusions

Treatment with β-glucans positively modulated the immune response and production of metabolites.

Salivary inflammatory markers and microbiome in normoglycemic lean and obese children compared to obese children with type 2 diabetes

BACKGROUND

There is emerging evidence linking diabetes with periodontal disease. Diabetes is a well-recognized risk factor for periodontal disease. Conversely, pro-inflammatory molecules released by periodontally-diseased tissues may enter the circulation to induce insulin resistance. While this association has been demonstrated in adults, there is little information regarding periodontal status in obese children with and without type 2 diabetes (T2D). We hypothesized that children with T2D have higher rates of gingivitis, elevated salivary inflammatory markers, and an altered salivary microbiome compared to children without T2D.

METHODS

Three pediatric cohorts ages 10-19 years were studied: lean (normal weight-C), obese (Ob), and obese with T2D (T2D). Each subject completed an oral health survey, received a clinical oral examination, and provided unstimulated saliva for measurement of inflammatory markers and microbiome analysis.

RESULTS

The diabetes group was less likely to have had a dental visit within the last six months. Body mass index (BMI) Z-scores and waist circumference/height ratios were similar between Ob and T2D cohorts. The number of carious lesions and fillings were similar for all three groups. The gingival index was greater in the T2D group compared to the Ob and C groups. Although salivary microbial diversity was minimal between groups, a few differences in bacterial genus composition were noted.

CONCLUSIONS

Obese children with T2D show a trend toward poorer oral health compared to normal weight and obese children without T2D. This study characterizes the salivary microbiome of children with and without obesity and T2D. This study supports a modest link between T2D and periodontal inflammation in the pediatric population.

Distinct signatures of dental plaque metabolic byproducts dictated by periodontal inflammatory status

Onset of chronic periodontitis is associated with an aberrant polymicrobial community, termed dysbiosis. Findings regarding its etiology obtained using high-throughput sequencing technique suggested that dysbiosis holds a conserved metabolic signature as an emergent property. The purpose of this study was to identify robust biomarkers for periodontal inflammation severity. Furthermore, we investigated disease-associated metabolic signatures of periodontal microbiota using a salivary metabolomics approach. Whole saliva samples were obtained from adult subjects before and after removal of supragingival plaque (debridement). Periodontal inflamed surface area (PISA) was employed as an indicator of periodontal inflammatory status. Based on multivariate analyses using pre-debridement salivary metabolomics data, we found that metabolites associated with higher PISA included cadaverine and hydrocinnamate, while uric acid and ethanolamine were associated with lower PISA. Next, we focused on dental plaque metabolic byproducts by selecting salivary metabolites significantly decreased following debridement. Metabolite set enrichment analysis revealed that polyamine metabolism, arginine and proline metabolism, butyric acid metabolism, and lysine degradation were distinctive metabolic signatures of dental plaque in the high PISA group, which may be related to the metabolic signatures of disease-associated communities. Collectively, our findings identified potential biomarkers of periodontal inflammatory status and also provide insight into metabolic signatures of dysbiotic communities.

Salivary glucose in monitoring glycaemia in patients with type 1 diabetes mellitus: a systematic review

BACKGROUND

Incidence of type 1 diabetes mellitus is increasing worldwide. Monitoring glycaemia is essential for control of diabetes mellitus. Conventional blood-based measurement of glucose requires venepuncture or needle prick, which is not free from pain and risk of infection. The non-invasiveness, ease and low-cost in collection made saliva an attractive alternative sample. The objective of this review was to systematically review the evidence on the relationship between salivary glucose level and blood glucose level in monitoring glycaemia in patients with type 1 diabetes mellitus.

METHODS

We searched studies which evaluate salivary glucose levels and serum glycaemia in type 1 diabetes mellitus in electronic databases of MEDLINE, EMBASE, Ovid and Google Scholar. We selected the eligible studies, following the inclusion criteria set for this review. Due to heterogeneity of studies, we conducted qualitative synthesis of studies.

RESULTS

Ten observational studies were included in this review, including a total of 321 cases and 323 controls with ages between 3 and 61 years and the majority were males (62%). Two studies were done exclusively on children below 17 years old. The significant difference between salivary glucose levels in type 1 diabetes mellitus and controls were reported in 6 studies with 8 data sets. Five studies with 7 datasets reported the correlation coefficient between salivary glucose and blood glucose in patients with diabetes.

CONCLUSIONS

Findings suggest that salivary glucose concentrations may be helpful in monitoring glycaemia in type 1 diabetes mellitus. However, the utility of using salivary glucose level to monitor glycaemia should be evaluated in future well designed, prospective studies with adequate number of participants with type 1 diabetes mellitus.

Plasma metabolic profiling and novel metabolite biomarkers for diagnosing prostate cancer

Prostate cancer (PCa) is the second leading cause of cancer death among men and associated with profound metabolic changes.

High-throughput metabolomics enables biomarker discovery in prostate cancer

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in the world.

A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research

The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions.

[Application of saliva in disease diagnosis]

Saliva is secreted by salivary glands and performs a variety of functions, including mouth cleaning and protection, antibacterial activity, and digestion. With the rapid progress in salivaomics, saliva became recognized as a potential pool of biological markers. Being a non-invasive and safe source, saliva is a potential substitute for blood in diagnosis and prognosis of diseases. This review summarizes the latest advancement in saliva-related studies and presents the potential value of saliva in early diagnosis of oral diseases, such as dental caries, periodontal disease, cancer, diabetes, and other systemic disorders. Saliva biomarkers can reveal changes ranging from changes in biochemical index, DNA, RNA, and proteins to the diversification of microbiota structure. By integrating recent data, this paper discusses the clinical significance and application prospect of saliva in early diagnosis of diseases and in translational and precision medicine.

Saliva in the diagnosis of diseases

Saliva is secreted from the salivary glands and has multiple functions, including mouth cleaning and protection, antibacterial effects and digestion. With the rapid advancement in salivaomics, saliva is well recognized as a pool of biological markers. Saliva, as a non-invasive and safe source, could be a substitute for blood in the diagnosis and prognosis of diseases. This review summarizes the latest advancements in saliva-related studies and addresses the potential value of saliva in the early diagnosis of oral diseases, such as dental caries and periodontal disease, as well as cancer, diabetes and other systemic disorders. Saliva biomarkers range from changes in the biochemical indices of DNA, RNA and proteins to the diversification of microbiota structures. This study integrates data reported in the recent literature and discusses the clinical significance and prospects for the application of saliva in the early diagnosis of diseases, translational medicine and precision medicine.

Resolvin E1 Reverses Experimental Periodontitis and Dysbiosis

Periodontitis is a biofilm-induced inflammatory disease characterized by dysbiosis of the commensal periodontal microbiota. It is unclear how natural regulation of inflammation affects the periodontal biofilm. Promoters of active resolution of inflammation, including resolvin E1 (RvE1), effectively treat inflammatory periodontitis in animal models. The goals of this study were 1) to compare periodontal tissue gene expression in different clinical conditions, 2) to determine the impact of local inflammation on the composition of subgingival bacteria, and 3) to understand how inflammation impacts these changes. Two clinically relevant experiments were performed in rats: prevention and treatment of ligature-induced periodontitis with RvE1 topical treatment. The gingival transcriptome was evaluated by RNA sequencing of mRNA. The composition of the subgingival microbiota was characterized by 16S rDNA sequencing. Periodontitis was assessed by bone morphometric measurements and histomorphometry of block sections. H&E and tartrate-resistant acid phosphatase staining were used to characterize and quantify inflammatory changes. RvE1 treatment prevented bone loss in ligature-induced periodontitis. Osteoclast density and inflammatory cell infiltration in the RvE1 groups were lower than those in the placebo group. RvE1 treatment reduced expression of inflammation-related genes, returning the expression profile to one more similar to health. Treatment of established periodontitis with RvE1 reversed bone loss, reversed inflammatory gene expression, and reduced osteoclast density. Assessment of the rat subgingival microbiota after RvE1 treatment revealed marked changes in both prevention and treatment experiments. The data suggest that modulation of local inflammation has a major role in shaping the composition of the subgingival microbiota.

Prediction of Periodontal Inflammation via Metabolic Profiling of Saliva

Periodontal disease is characterized by chronic inflammation in subgingival areas, where a vast array of inflammation-associated metabolites are likely produced from tissue breakdown, increased vascular permeability, and microbial metabolism and then eventually show a steady flow into saliva. Thus, prolonged periodontal inflammation is a key feature of disease activity. Although salivary metabolomics has drawn attention for its potential use in diagnosis of periodontal disease, few authors have used that to investigate periodontal inflammation detection. In this pilot study, the authors explored the use of salivary metabolites to reflect periodontal inflammation severity with a recently proposed parameter-periodontal inflamed surface area (PISA)-used to quantify the periodontal inflammatory burden of individual patients with high accuracy. Following PISA determination, whole saliva samples were collected from 19 subjects before and after removal of supragingival plaque and calculus (debridement) with an ultrasonic scaler to assess the influence of the procedure on salivary metabolic profiles. Metabolic profiling of saliva was performed with gas chromatography coupled to time-of-flight mass spectrometry, followed by multivariate regression analysis with orthogonal projections to latent structures (OPLS) to investigate the relationship between PISA and salivary metabolic profiles. Sixty-three metabolites were identified. OPLS analysis showed that postdebridement saliva provided a more refined model for prediction of PISA than did predebridement samples, which indicated that debridement may improve detection of metabolites eluted from subgingival areas in saliva, thus more accurately reflecting the pathophysiology of periodontitis. Based on the variable importance in the projection values obtained via OPLS, 8 metabolites were identified as potential indicators of periodontal inflammation, of which the combination of cadaverine, 5-oxoproline, and histidine yielded satisfactory accuracy (area under the curve = 0.881) for diagnosis of periodontitis. The authors' findings identified potential biomarkers that may be useful for reflecting the severity of periodontal inflammation as part of monitoring disease activity in periodontitis patients.

Metabolomic Analysis of Gingival Crevicular Fluid Using Gas Chromatography/Mass Spectrometry

Periodontitis is one of the most prevalent threats to oral health as the most common cause of tooth loss. In order to perform effective treatment, a clinical test that detect sites where disease activity is high and predicts periodontal tissue destruction is strongly desired, however, it is still difficult to prognose the periodontal tissue breakdown on the basis of conventional methods. The aim of this study is to examine the usefulness of gas chromatography/mass spectrometry (GC/MS), which could eventually be used for on-site analysis of metabolites in gingival crevicular fluid (GCF) in order to objectively diagnose periodontitis at a molecular level. GCF samples were collected from two diseased sites (one site with a moderate pocket and another site with a deep pocket) from each patient and from clinically healthy sites of volunteers. Nineteen metabolites were identified using GC/MS. Total ion current chromatograms showed broad differences in metabolite peak patterns between GCF samples obtained from healthy sites, moderate-pocket sites, and deep-pocket sites. The intensity difference of some metabolites was significant at sites with deep pockets compared to healthy sites. Additionally, metabolite intensities at moderate-pocket sites showed an intermediate profile between the severely diseased sites and healthy sites, which suggested that periodontitis progression could be observed with a changing metabolite profile. Principal component analysis confirmed these observations by clearly delineating healthy sites and sites with deep pockets. These results suggest that metabolomic analysis of GCF could be useful for prediction and diagnosis of periodontal disease in a single visit from a patient and provides the groundwork for establishing a new, on-site diagnostic method for periodontitis.

Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders

Metabolic profiling provides a powerful diagnostic tool complementary to genomics and proteomics. The pain, discomfort and probable iatrogenic injury associated with invasive or minimally invasive diagnostic methods, render them unsuitable in terms of patient compliance and participation. Metabolic profiling of biomatrices like urine, breath, saliva, sweat and feces, which can be collected in a painless manner, could be used for noninvasive diagnosis. This review article covers the noninvasive metabolic profiling studies that have exhibited diagnostic potential for diseases and disorders. Their potential applications are evident in different forms of cancer, metabolic disorders, infectious diseases, neurodegenerative disorders, rheumatic diseases and pulmonary diseases. Large scale clinical validation of such diagnostic methods is necessary in future.