Saliva: a fluid of study for OMICS

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.

Applicability of Gene Expression in Saliva as an Alternative to Blood for Biodosimetry and Prediction of Radiation-induced Health Effects

As the great majority of gene expression (GE) biodosimetry studies have been performed using blood as the preferred source of tissue, searching for simple and less-invasive sampling methods is important when considering biodosimetry approaches. Knowing that whole saliva contains an ultrafiltrate of blood and white blood cells, it is expected that the findings in blood can also be found in saliva. This human in vivo study aims to examine radiation-induced GE changes in saliva for biodosimetry purposes and to predict radiation-induced disease, which is yet poorly characterized. Furthermore, we examined whether transcriptional biomarkers in blood can also be found equivalently in saliva. Saliva and blood samples were collected in parallel from radiotherapy (RT) treated patients who suffered from head and neck cancer (n = 8) undergoing fractioned partial-body irradiations (1.8 Gy/fraction and 50-70 Gy total dose). Samples were taken 12-24 h before first irradiation and ideally 24 and 48 h, as well as 5 weeks after radiotherapy onset. Due to the low quality and quantity of isolated RNA samples from one patient, they had to be excluded from further analysis, leaving a total of 24 saliva and 24 blood samples from 7 patients eligible for analysis. Using qRT-PCR, 18S rRNA and 16S rRNA (the ratio being a surrogate for the relative human RNA/bacterial burden), four housekeeping genes and nine mRNAs previously identified as radiation responsive in blood-based studies were detected. Significant GE associations with absorbed dose were found for five genes and after the 2nd radiotherapy fraction, shown by, e.g., the increase of CDKN1A (2.0 fold, P = 0.017) and FDXR (1.9 fold increased, P = 0.002). After the 25th radiotherapy fraction, however, all four genes (FDXR, DDB2, POU2AF1, WNT3) predicting ARS (acute radiation syndrome) severity, as well as further genes (including CCNG1 [median-fold change (FC) = 0.3, P = 0.013], and GADD45A (median-FC = 0.3, P = 0.031)) appeared significantly downregulated (FC = 0.3, P = 0.01-0.03). A significant association of CCNG1, POU2AF1, HPRT1, and WNT3 (P = 0.006-0.04) with acute or late radiotoxicity could be shown before the onset of these clinical outcomes. In an established set of four genes predicting acute health effects in blood, the response in saliva samples was similar to the expected up- (FDXR, DDB2) or downregulation (POU2AF1, WNT3) in blood for up to 71% of the measurements. Comparing GE responses (PHPT1, CCNG1, CDKN1A, GADD45A, SESN1) in saliva and blood samples, there was a significant linear association between saliva and blood response of CDKN1A (R2 = 0.60, P = 0.0004). However, the GE pattern of other genes differed between saliva and blood. In summary, the current human in vivo study, (I) reveals significant radiation-induced GE associations of five transcriptional biomarkers in salivary samples, (II) suggests genes predicting diverse clinical outcomes such as acute and late radiotoxicity as well as ARS severity, and (III) supports the view that blood-based GE response can be reflected in saliva samples, indicating that saliva is a "mirror of the body" for certain but not all genes and, thus, studies for each gene of interest in blood are required for saliva.

Pinching dynamics, extensional rheology, and stringiness of saliva substitutes

Saliva substitutes are human-made formulations extensively used in medicine, food, and pharmaceutical research to emulate human saliva's biochemical, tribological, and rheological properties. Even though extensional flows involving saliva are commonly encountered in situations such as swallowing, coughing, sneezing, licking, drooling, gleeking, and blowing spit bubbles, rheological evaluations of saliva and its substitutes in most studies rely on measured values of shear viscosity. Natural saliva possesses stringiness or spinnbarkeit, governed by extensional rheology response, which cannot be evaluated or anticipated from the knowledge of shear rheology response. In this contribution, we comprehensively examine the rheology of twelve commercially available saliva substitutes using torsional rheometry for rate-dependent shear viscosity and dripping-onto-substrate (DoS) protocols for extensional rheology characterization. Even though most formulations are marketed as having suitable rheology, only three displayed measurable viscoelasticity and strain-hardening. Still, these too, failed to emulate the viscosity reduction with the shear rate observed for saliva or match perceived stringiness. Finally, we explore the challenges in creating saliva-like formulations for dysphagia patients and opportunities for using DoS rheometry for diagnostics and designing biomimetic fluids.

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.

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.

Identification of Salivary Metabolic Signatures Associated with Primary Sjögren's Disease

Sjögren's disease (SjD) is the second most prevalent autoimmune disorder that involves chronic inflammation of exocrine glands. Correct diagnosis of primary SjD (pSjD) can span over many years since disease symptoms manifest only in advanced stages of salivary and lachrymal glandular destruction, and consensus diagnostic methods have critical sensitivity and selectivity limitations. Using nuclear magnetic resonance (NMR) spectroscopy, we determined the composition of metabolites in unstimulated saliva samples from 30 pSjD subjects and 30 participants who do not have Sjögren's disease (non-Sjögren's control group, NS-C). Thirty-four metabolites were quantified in each sample, and analysis was conducted on both non-normalized (concentration) and normalized metabolomics data from all study participants (ages 23-78) and on an age-restricted subset of the data (ages 30-70) while applying false discovery rate correction in determining data significance. The normalized data of saliva samples from all study participants, and of the age-restricted subset, indicated significant increases in the levels of glucose, glycerol, taurine, and lactate, as well as significant decreases in the levels of 5-aminopentanoate, acetate, butyrate and propionate, in subjects with pSjD compared to subjects in the NS-C group. Additionally, a significant increase in choline was found only in the age-restricted subset, and a significant decrease in fucose was found only in the whole study population in normalized data of saliva samples from the pSjD group compared to the NS-C group. Metabolite concentration data of saliva samples from all study participants, but not from the age-restricted subset, indicated significant increases in the levels of glucose, glycerol, taurine, and lactate in subjects with pSjD compared to controls. The study showed that NMR metabolomics can be implemented in defining salivary metabolic signatures that are associated with disease status, and can contribute to differential analysis between subjects with pSjD and those who are not affected with this disease, in the clinic.

Precision Medicine in Oral Health and Diseases: A Systematic Review

Precision medicine (PM) is personalized medicine that can develop targeted medical therapies for the individual patient, in which "omics" sciences lead to an integration of data that leads to highly predictive models of the functioning of the individual biological system. They enable rapid diagnosis, assessment of disease dynamics, identification of targeted treatment protocols, and reduction of costs and psychological stress. "Precision dentistry" (DP) is one promising application that need further investigation; the purpose of this paper is therefore to give physicians an overview of the knowledge they need to enhance treatment planning and patient response to therapy. A systematic literature review was conducted on the PubMed, Scopus, and Web of Science databases by analyzing the articles examining the role of precision medicine in dentistry. PM aims to shed light on cancer prevention strategies, by identifying risk factors, and on malformations such as orofacial cleft. Another application is pain management by repurposing drugs created for other diseases to target biochemical mechanisms. The significant heritability of traits regulating bacterial colonization and local inflammatory responses is another result of genomic research, and is useful for DP in the field of caries and periodontitis. This approach may also be useful in the field of orthodontics and regenerative dentistry. The possibility of creating an international network of databases will lead to the diagnosis, prediction, and prevention of disease outbreaks, providing significant economic savings for the world's health care systems.

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.

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.

Comparative Analysis of Saliva and Plasma Proteins Patterns in Pregnant Cows—Preliminary Studies

Simple Summary

One of the most crucial topics about cattle breeding is pregnancy. During this state, there are many changes in protein expression and abundance. These changes find reflection not only in plasma protein patterns but also in saliva, which is easier to obtain than blood. The aim of this study was the analysis of plasma and salivary protein profiles in pregnant cows in order to search for valuable markers of pregnancy status. In this study, the presence of apolipoproteins possibly related to bovine pregnancy was confirmed both in plasma and saliva. This means that saliva can be considered a good source of information about the condition of the organism, including during pregnancy. It is possible that the comparison of salivary and plasma proteomes can be a helpful tool to assess the pregnancy status of cattle, and can be useful for developing rapid tests from saliva.

Abstract

Pregnancy is a physiological state that can be described, from a biochemical point of view, using protein patterns. The present study focused on the comparison of protein patterns between the saliva and plasma of pregnant cows to search for possible markers which are present both in plasma and saliva. Saliva and plasma were collected from healthy, pregnant (3–4 months) and non-pregnant (C; n = 4) cows aged between 4 and 8 years (P; n = 8) from the same farm. Biological material was analyzed using 2D electrophoresis and MS identification. Among identified spots, there were those which could be related to pregnancy (e.g., apolipoproteins I and II in all examined matrices or transforming growth factor-beta-induced protein ig-h3 in albumin-free plasma) as well as those which are responsible for regulating of cellular processes (e.g., pyruvate kinase and aspartate aminotransferase in all examined matrices, or lactate dehydrogenase, phosphoglycerate kinase, and NADH dehydrogenase in plasma). Further identification of common spots and those only specific to saliva as well as the comparison between other periods of pregnancy are necessary; it is already clear that saliva can be considered a valuable diagnostic matrix containing potential markers of physiological and pathological status.

Development of analytical methods to study the salivary metabolome: impact of the sampling

Advances in metabolomics have allowed the identification and characterization of saliva metabolites that can be used as biomarkers. However, discrepancies can be noted with the content of the same biomarker being increased or decreased for a given disease. Differences in the way saliva is collected, stored, and/or treated could cause these discrepancies. Indeed, there is no standardized method for saliva sampling and analysis. In this work, two chromatographic modes were used, i.e., RP-LC and HILIC both coupled to MS used in positive and negative ionization modes. The analytical conditions were optimized with a mixture of 90 compounds naturally present in saliva, representative of the wide range of molecular mass and polarity of salivary metabolites and being described as having a differential expression in various pathologies. These four methods were applied to the analysis of saliva samples collected by spitting, aspiration, or Salivette® with or without prior rinsing of the mouth. Rinsing had an effect on some metabolite concentrations. As it can induce an additional parameter of variability to the sampling, it seems therefore preferable to use methods without rinsing while effects of these parameters on the metabolites are investigated. Saliva obtained by spitting and aspiration gave statistically equivalent results for 84% of the metabolites studied. Conversely, Salivette® gave different results since the majority of the metabolites chosen for the study were not quantified in the samples. The Salivette® does not seem therefore to be a suitable sampling method for an untargeted analysis of the salivary metabolome, unlike aspiration and spitting.

Evaluation of the Use of Saliva Metabolome as a Surrogate of Blood Metabolome in Assessing Internal Exposures to Traffic-Related Air Pollution

In the omics era, saliva, a filtrate of blood, may serve as an alternative, noninvasive biospecimen to blood, although its use for specific metabolomic applications has not been fully evaluated. We demonstrated that the saliva metabolome may provide sensitive measures of traffic-related air pollution (TRAP) and associated biological responses via high-resolution, longitudinal metabolomics profiling. We collected 167 pairs of saliva and plasma samples from a cohort of 53 college student participants and measured corresponding indoor and outdoor concentrations of six air pollutants for the dormitories where the students lived. Grand correlation between common metabolic features in saliva and plasma was moderate to high, indicating a relatively consistent association between saliva and blood metabolites across subjects. Although saliva was less associated with TRAP compared to plasma, 25 biological pathways associated with TRAP were detected via saliva and accounted for 69% of those detected via plasma. Given the slightly higher feature reproducibility found in saliva, these findings provide some indication that the saliva metabolome offers a sensitive and practical alternative to blood for characterizing individual biological responses to environmental exposures.

Systems Biology in Periodontitis

Systems biology is a promising scientific discipline that allows an integrated investigation of host factors, microbial composition, biomarkers, immune response and inflammatory mediators in many conditions such as chronic diseases, cancer, neurological disorders, and periodontitis. This concept utilizes genetic decoding, bioinformatic, flux-balance analysis in a comprehensive approach. The aim of this review is to better understand the current literature on systems biology and identify a clear applicability of it to periodontitis. We will mostly focus on the association between this condition and topics such as genomics, transcriptomics, proteomics, metabolomics, as well as contextualize delivery systems for periodontitis treatment, biomarker detection in oral fluids and associated systemic conditions.

The promise of graphene-based transistors for democratizing multiomics studies

As biological research has synthesized genomics, proteomics, metabolomics, and transcriptomics into systems biology, a new multiomics approach to biological research has emerged. Today, multiomics studies are challenging and expensive. An experimental platform that could unify the multiple omics approaches to measurement could increase access to multiomics data by enabling more individual labs to successfully attempt multiomics studies. Field effect biosensing based on graphene transistors have gained significant attention as a potential unifying technology for such multiomics studies. This review article highlights the outstanding performance characteristics that makes graphene field effect transistor an attractive sensing platform for a wide variety of analytes important to system biology. In addition to many studies demonstrating the biosensing capabilities of graphene field effect transistors, they are uniquely suited to address the challenges of multiomics studies by providing an integrative multiplex platform for large scale manufacturing using the well-established processes of semiconductor industry. Furthermore, the resulting digital data is readily analyzable by machine learning to derive actionable biological insight to address the challenge of data compatibility for multiomics studies. A critical stage of systems biology will be democratizing multiomics study, and the graphene field effect transistor is uniquely positioned to serve as an accessible multiomics platform.

Salivary Metabolomics Reveals that Metabolic Alterations Precede the Onset of Schizophrenia

Schizophrenia is a complex and highly heterogeneous mental illness with a prodromal period called clinical high risk (CHR) for psychosis before onset. Metabolomics is greatly promising in analyzing the pathology of complex diseases and exploring diagnostic biomarkers. Therefore, we conducted salivary metabolomics analysis in 83 first-episode schizophrenia (FES) patients, 42 CHR individuals, and 78 healthy controls with ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The mass spectrometry raw data have been deposited on the MetaboLights (ID: MTBLS3463). We found downregulated aromatic amino acid metabolism, disturbed glutamine and nucleotide metabolism, and upregulated tricarboxylic acid cycle in FES patients, which existed even in the CHR stage and became more intense with the onset of the schizophrenia. Moreover, differential metabolites can be considered as potential diagnostic biomarkers and indicate the severity of the different clinical stages of disease. Furthermore, three disordered pathways were closely related to peripheral indicators of inflammatory response, oxidative stress, blood-brain barrier damage, and salivary microbiota. These results indicate that the disorder of oral metabolism occurs earlier than the onset of schizophrenia and is concentrated and intensified with the onset of disease, which may originate from the dysbiotic salivary microbiota and cause the onset of schizophrenia through the peripheral inflammatory response and redox system, suggesting the importance of oral-brain connection in the pathogenesis of schizophrenia.

Effect of Chemo-radiotherapy on Salivary Flora of Oral Cancer Patients

Management of cancers of oral cancers has remained a major challenge in India and globally. Radiotherapy and chemotherapy are mostly employed for treatment which inflicts changes in oral mucosa and makes it vulnerable for bacterial colonization and eventual infections. This study aims at evaluating the changes in oropharyngeal flora (bacteria and yeast) in oral cancer patients treated by a combination of chemo-radiotherapy with the control groups comprising of non-cancerous patients living in the same environment. This prospective evaluation included Seventy-seven patients with oral squamous cell carcinomas in the study group. Whereas the control group comprised of twenty-five non-cancerous patients. Saliva samples were collected from patients with oral carcinomas and those of the control group for bacteriological examination, and were transported within 2 hours to the laboratory and immediately inoculated and incubated. The oral microflora samples collected were evaluated for the presence of bacteria in saliva in both study and control group of patients. We evaluated the change in salivary oral flora during chemo-radiotherapy treatment. A statistically significant increase in growth of normal as well as abnormal oral flora was observed post-radiation. Escherichia coli showed a significant decrease in post-RT and also near to significant in control. Various changes in salivary oral flora were observed during the course of chemo-radiotherapy in study and controls groups. This shows that there are some sensitive spots in the oral cavity where the occurrence of oral cancer is more.

A Metabolomic Profile Predictive of New Osteoporosis or Sarcopenia Development

The increasing number of patients with osteoporosis and sarcopenia is a global concern among countries with progressively aging societies. The high medical costs of treating those patients suggest that prevention rather than treatment is preferable. We enrolled 729 subjects who attended both the second and third surveys of the Research on Osteoarthritis/Osteoporosis Against Disability (ROAD) study. Blood samples were collected from subjects at the second survey, and then a comprehensive metabolomic analysis was performed. It was found that 35 had newly developed osteoporosis at the third survey performed four years later, and 39 were newly diagnosed with sarcopenia at the third survey. In the second survey, we found that serum Gly levels were significantly higher even after adjustment for age, sex, and BMI in subjects with newly developed osteoporosis relative to those who remained osteoporosis-negative during the four-year follow-up. We also show that serum taurine levels were significantly lower at the second survey, even after adjustment for age, sex, and BMI in subjects with newly developed sarcopenia during the four-year follow-up compared with those not diagnosed with sarcopenia at the second or third surveys. Though our sample size and odds ratios were small, increased Gly and decreased taurine levels were found to be predictive of new development of osteoporosis and sarcopenia, respectively, within four years.

Longitudinal saliva omics responses to immune perturbation: a case study

Saliva omics has immense potential for non-invasive diagnostics, including monitoring very young or elderly populations, or individuals in remote locations. In this study, multiple saliva omics from an individual were monitored over three periods (100 timepoints) involving: (1) hourly sampling over 24 h without intervention, (2) hourly sampling over 24 h including immune system activation using the standard 23-valent pneumococcal polysaccharide vaccine, (3) daily sampling for 33 days profiling the post-vaccination response. At each timepoint total saliva transcriptome and proteome, and small RNA from salivary extracellular vesicles were profiled, including mRNA, miRNA, piRNA and bacterial RNA. The two 24-h periods were used in a paired analysis to remove daily variation and reveal vaccination responses. Over 18,000 omics longitudinal series had statistically significant temporal trends compared to a healthy baseline. Various immune response and regulation pathways were activated following vaccination, including interferon and cytokine signaling, and MHC antigen presentation. Immune response timeframes were concordant with innate and adaptive immunity development, and coincided with vaccination and reported fever. Overall, mRNA results appeared more specific and sensitive (timewise) to vaccination compared to other omics. The results suggest saliva omics can be consistently assessed for non-invasive personalized monitoring and immune response diagnostics.

Serum and Saliva Levels of Cancer Antigen 15-3, Carcinoembryonic Antigen, Estradiol, Vaspin, and Obestatin as Biomarkers for the Diagnosis of Breast Cancer in Postmenopausal Women

OBJECTIVE

To find suitable biomarkers for diagnosis of Breast cancer in serum and saliva; also, to examine the correlation between salivary and serum concentrations of suitable biomarkers.

METHODS

This case-control study included 30 women with breast cancer as a case group and 30 healthy women as a matched control group. Blood and saliva specimens were collected from all participants. We evaluated serum and salivary cancer antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), estradiol, vaspin, and obestatin concentrations. Mann-Whitney U testing and Spearman correlation coefficients were used for statistical analysis.

RESULTS

Serum and salivary concentrations of estradiol were significantly higher in patients with breast cancer (BC) than in healthy women (P < .05). Also, serum CEA and salivary obestatin concentrations were significantly higher in BC patients than in the control group (P < .05). However, there was no significant difference between other parameters in patients with BC and controls. We observed a positive correlation between serum and salivary concentrations of CA15-3, as well as a negative correlation between serum and salivary concentrations of vaspin and obestatin.

CONCLUSION

The results of this study demonstrated that concentrations of CEA and estradiol in serum, obestatin in serum and saliva, and estradiol in saliva were significantly different between the 2 groups.

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.

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.

Validation and Application of a Derivatization-Free RP-HPLC-DAD Method for the Determination of Low Molecular Weight Salivary Metabolites

Saliva is an interesting, non-conventional, valuable diagnostic fluid. It can be collected using standardized sampling device; thus, its sampling is easy and non-invasive, it contains a variety of organic metabolites that reflect blood composition. The aim of this study was to validate a user-friendly method for the simultaneous determination of low molecular weight metabolites in saliva. We have optimized and validated a high throughput, direct, low-cost reversed phase liquid chromatographic method with diode array detection method without any pre- or post-column derivatization. We indexed salivary biomolecules in 35 whole non-stimulated saliva samples collected in 8 individuals in different days, including organic acids and amino acids and other carbonyl compounds. Among these, 16 whole saliva samples were collected by a single individual over three weeks before, during and after treatment with antibiotic in order to investigate the dynamics of metabolites. The concentrations of the metabolites were compared with the literature data. The multianalyte method here proposed requires a minimal sample handling and it is cost-effectiveness as it makes possible to analyze a high number of samples with basic instrumentation. The identification and quantitation of salivary metabolites may allow the definition of potential biomarkers for non-invasive "personal monitoring" during drug treatments, work out, or life habits over time.

Relevance of serum and salivary sialic acid in oral cancer diagnostics

To review the relevance of sialic acid as a tumour marker in oral cancer. Tumour marker are useful in the screening for early malignancy. Sialic acids are important in determining the surface properties of cells and has been implicated in cellular invasiveness, adhesiveness, and immunogenicity. Sialic acids are commonly found at the outermost end of glycan chains of all cell types. Increase in the levels of sialic acid in oral cancer indicates its importance as a tumour marker.Both serum and salivary sialic acid levels can be used as a screening tool and a diagnostic aid for oral cancer. Salivary sialic acid can be used as a non-invasive, cost effective and reliable diagnostic methods for screening and monitoring of oral cancer. In patients with oral cancer, glycoprotein metabolism is altered. Increase in the levels of sialic acid in oral cancer indicate its importance as a tumour marker. Changes in the serum is reflected in saliva. Salivary sialic acid can be used as non-invasive, cost effective and reliable diagnostic methods for screening and monitoring of oral cancer. Early the diagnosis, better the prognosis.

Biochemical analysis of oral fluids for disease detection

The field of diagnostics using invasive blood testing represents the majority of diagnostic tests used as part of routine health monitoring. The relatively recent introduction of salivary diagnostics has lead to a major paradigm shift in diagnostic analyses. Additionally, in this era of big data, oral fluid testing has shown promising outcomes in a number of fields, particularly the areas of genomics, microbiomics, proteomics, metabolomics, and transcriptomics. Despite the analytical challenges involved in the interpretation of large datasets generated from biochemical studies involving bodily fluids, including saliva, many studies have identified novel oral biomarkers for diagnosing oral and systemic diseases. In this regard, oral biofluids, including saliva, gingival crevicular fluid (GCF), peri-implant crevicular fluid (PICF), dentinal tubular fluid (DTF), are now attracting increasing attention due to their important attributes, such as noninvasive sampling, easy handling, low cost, and more accurate diagnosis of oral diseases. Recently, the utilization of salivary diagnostics to evaluate systemic diseases and monitor general health has increased in popularity among clinicians. Saliva contains a wide range of protein, DNA and RNA biomarkers, which assist in the diagnosis of multiple diseases and conditions, including cancer, cardiovascular diseases (CVD), auto-immune and degenerative diseases, respiratory infections, oral diseases, and microbial (viral, bacterial and fungal) diseases. Moreover, due to its noninvasive nature and ease-of-adoption by children, it is now being used in mass screening programs, oral health-related studies and clinical trials in support of the development of therapeutic agents. The recent advent of highly sensitive technologies, such as next-generation sequencing, mass spectrometry, highly sensitives ELISAs, and homogeneous immunoassays, suggests that even small quantities of salivary biomarkers are able to be assayed accurately, providing opportunities for the development of many future diagnostic applications (including emerging technologies, such as point-of-care and rapid molecular technologies). The present article explores the omics and biochemical compositions of various oral biofluids with important value in diagnostics and monitoring.

Oral squamous cell carcinoma diagnosed from saliva metabolic profiling

Saliva is a noninvasive biofluid that can contain metabolite signatures of oral squamous cell carcinoma (OSCC). Conductive polymer spray ionization mass spectrometry (CPSI-MS) is employed to record a wide range of metabolite species within a few seconds, making this technique appealing as a point-of-care method for the early detection of OSCC. Saliva samples from 373 volunteers, 124 who are healthy, 124 who have premalignant lesions, and 125 who are OSCC patients, were collected for discovering and validating dysregulated metabolites and determining altered metabolic pathways. Metabolite markers were reconfirmed at the primary tissue level by desorption electrospray ionization MS imaging (DESI-MSI), demonstrating the reliability of diagnoses based on saliva metabolomics. With the aid of machine learning (ML), OSCC and premalignant lesions can be distinguished from the normal physical condition in real time with an accuracy of 86.7%, on a person by person basis. These results suggest that the combination of CPSI-MS and ML is a feasible tool for accurate, automated diagnosis of OSCC in clinical practice.

Saliva as a non-invasive tool for assessment of metabolic and inflammatory biomarkers in children

BACKGROUND & AIMS

Epidemiological studies in school-age children are challenging, particularly those that aim to analyse metabolic markers on blood samples obtained via invasive and stressful procedures. The objective of this paper is to evaluate the use of saliva, as a non-invasive tool in epidemiological studies performed in school-age children, to capture metabolic changes associated with body mass index (BMI), dietary characteristics and physical activity in both boys and girls.

METHODS

This is an observational study in which healthy children of ages between 8 and 12 years (n = 129, 60 girls and 69 boys) from three schools in a Mediterranean area of Spain were included. A panel of biomarkers was measured in serum and saliva and correlated with BMI, dietary characteristics and physical activity.

RESULTS

Significant positive correlation between serum and salivary levels were detected for CRP (r = 0.770) in all included children, and boys (r = 0.805) and girls (r = 0.775) separately (P < 0.001, in all cases) and for insulin in girls (r = 0.442; P < 0.05). Among all studied salivary biomarkers, insulin was significantly correlated with the three factors studied: positively with BMI and negatively with dietary characteristics (intake and composition) and physical activity (P < 0.05). Obesity and diet composition were both positively associated to pro-inflammatory biomarkers, CRP and IL1b; while diet composition shared with physical activity levels the correlation with IL6 (positive with energy, fat, carbohydrate and saturated fatty acid intake, and negative with cholesterol intake and average physical activity in boys), NGF and glucose (in both cases correlations were negative with diet composition and physical activity variables) (P < 0.05, in all cases). Sex differences were detected in serum glucose and TNFα.

CONCLUSIONS

Biomarkers in saliva are able to capture differences in BMI, dietary characteristics and physical activity levels in school-age children. Saliva may potentially constitute a useful non-invasive and stress-free tool to evaluate metabolic markers of inflammation and/or metabolism related to BMI and lifestyle in a sex-dependent manner.

HS-SPME-GC-MS approach for the analysis of volatile salivary metabolites and application in a case study for the indirect assessment of gut microbiota

In this work, a straightforward analytical approach based on headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry was developed for the analysis of salivary volatile organic compounds without any prior derivatization step. With a sample volume of 500 μL, optimal conditions were achieved by allowing the sample to equilibrate for 10 min at 50 °C and then extracting the samples for 10 min at the same temperature, using a carboxen/polydimethylsiloxane fibre. The method allowed the simultaneous identification and quantification of 20 compounds in sample headspace, including short-chain fatty acids and their derivatives which are commonly analysed after analyte derivatization. The proof of applicability of the methodology was performed with a case study regarding the analysis of the dynamics of volatile metabolites in saliva of a single subject undergoing 5-day treatment with rifaximin antibiotic. Non-stimulated saliva samples were collected over 3 weeks from a nominally healthy volunteer before, during, and after antibiotic treatment. The variations of some metabolites, known to be produced by the microbiota and by bacteria that are susceptible to antibiotics, suggest that the study of the dynamics of salivary metabolites can be an excellent indirect method for analysing the gut microbiota. This approach is novel from an analytical standpoint, and it encourages further studies combining saliva metabolite profiles and gut microbiota dynamics. Graphical abstract.

Mapping Relative Differences in Human Salivary Gland Secretions by Dried Saliva Spot Sampling and nanoLC-MS/MS

Dried saliva spot sampling is a minimally invasive technique for the spatial mapping of salivary protein distribution in the oral cavity. In conjunction with untargeted nano-flow liquid chromatography tandem mass spectrometry (nanoLC-MS/MS) analysis, DSS is used to compare the proteomes secreted by unstimulated parotid and submandibular/sublingual salivary glands. Two hundred and twenty proteins show a statistically significant association with parotid gland secretion, while 30 proteins are at least tenfold more abundant in the submandibular/sublingual glands. Protein identifications and label-free quantifications are highly reproducible across the paired glands on three consecutive days, enabling to establish the core proteome of glandular secretions categorized into eight salivary protein groups according to their biological functions. The data suggest that the relative contributions of the salivary glands fine-tune the biological activity of human saliva via medium-abundant proteins. A number of biomarker candidates for Sjögren's syndrome are observed among the gland-specifically expressed proteins, which indicates that glandular origin is an important factor to consider in salivary biomarker discovery.

Specimen Collection for Translational Studies in Hidradenitis Suppurativa

Hidradenitis suppurativa (HS) is a chronic inflammatory disorder characterized by painful nodules, sinus tracts, and scars occurring predominantly in intertriginous regions. The prevalence of HS is currently 0.053-4%, with a predominance in African-American women and has been linked to low socioeconomic status. The majority of the reported literature is  retrospective, population based, epidemiologic studies. In this regard, there is a need to establish a repository of biospecimens, which represent appropriate gender and racial demographics amongst HS patients. These efforts will diminish knowledge gaps in understanding the disease pathophysiology. Hence, we sought to outline a step-by-step protocol detailing how we established our HS biobank to facilitate the formation of other HS tissue banks. Equipping researchers with carefully detailed processes for collection of HS specimens would accelerate the accumulation of well-organized human biological material. Over time, the scientific community will have access to a broad range of HS tissue biospecimens, ultimately leading to more rigorous basic and translational research. Moreover, an improved understanding of the pathophysiology is necessary for the discovery of novel therapies for this debilitating disease. We aim to provide high impact translational research methodology for cutaneous biology research and foster multidisciplinary collaboration and advancement of our understanding of cutaneous diseases.

A Historical Review of Persian Medicine Studies into Saliva Manifestations for Potential Applications for Diagnosis and Management of Metabolic Syndrome

BACKGROUND AND OBJECTIVES

Regarding the development of diagnostic tests based on saliva and the prevalence of metabolic syndrome (MetS), the aim of this study is to review Persian Medicine manuscripts in the field of saliva manifestations, its relation to metabolic syndrome, and treatment recommendations.

METHODS

This study is a mini-review. We investigated the canon of medicine and some important Persian medical or pharmaceutical manuscripts from the 9th to the 19th centuries. PubMed and Google Scholar databases were explored for finding relevant information about the relationship between saliva and metabolic syndrome and its treatment.

RESULTS

Studies have suggested that maldigestion is one of the important causes of MetS. Sialorrhea may be an early symptom of maldigestion. Attention to sialorrhea and its treatment may be useful in the prevention and treatment of metabolic syndrome based on PM sources. In PM, sialorrhea is treated with 3 major approaches: lifestyle modification along with simple or compound medicines.

CONCLUSION

Saliva manifestations could be considered as early symptoms of metabolic syndrome. As mentioned in WHO strategies, traditional medicine can be used along with modern medicine due to its effectiveness in the management of various ailments.

Biochemical changes in saliva of cows with inflammation: A pilot study

Saliva contains a variety of compounds that can change in local and systemic pathologies including inflammation. Although changes in acute phase proteins and markers of oxidative stress in saliva during inflammation in humans and different animal species have been described, no data exist about possible changes during inflammation in analytes in saliva of cows. The aim of the present study was to evaluate changes in selected salivary biomarkers of stress, inflammation and immune system, and oxidative stress in cows with inflammation. For this purpose, bovine mastitis was used as model. Saliva and serum from 18 clinically healthy cows and 18 cows with clinical mastitis were used in the study. A panel of analytes integrated by alpha-amylase, cortisol, haptoglobin, adenosine deaminase, cholinesterase, total antioxidant capacity, lactate, and uric acid was measured in all samples and differences between the two groups of animals were evaluated. Significant increases in cortisol, alpha-amylase, uric acid, lactate and significant decreases in cholinesterase were detected in saliva of cows with mastitis. These results indicate that that cows with mastitis show changes in salivary biomarkers that reflect presence of stress, inflammation and oxidative stress in the animals.

Evaluation of Biochemical Parameters Present in the Saliva of Patients with Chronic Periodontitis: Results from a Meta-Analysis

AIMS

Periodontitis results from the presence of periodontopathogenic bacterial activity in the region of the gingival sulcus promoting tissue degradation and alveolar bone resorption. Biochemical analysis of the saliva can be used as a less invasive method for disease prognosis. This study aimed to evaluate the relationship between biochemical protein levels in the saliva sample of patients with chronic periodontitis and healthy patients.

MATERIALS AND METHODS

A literature review was performed using electronic databases (Cochrane Library, Google Scholar, MEDLINE, PubMed, and Web of Science) for studies published before July 2, 2016. The abstracts were evaluated, and the data extraction was performed by two calibrated examiners. The mean difference, and heterogeneity were calculated, and funnel plots were produced.

RESULTS

Twenty case-control studies were selected with 2436 patients with chronic periodontitis and 1787 controls. The meta-analysis showed that increased levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatine kinase (CK), lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and acid phosphatase (ACP) were all associated with periodontitis (p < 0.05), while blood urea nitrogen (BUN) and osteoprotegerin (OPG) levels did not show statistical differences between cases and controls (p > 0.05).

CONCLUSIONS

This meta-analysis evidenced that increased levels of AST, ALT, CK, gama glutamil transferase (GGT), LDH, ALP, and ACP are associated in patients with chronic periodontitis, while BUN and OPG level in saliva did not present differences between groups.

Association between periodontal pathogens and systemic disease

A growing body of literature suggests that there is a link between periodontitis and systemic diseases. These diseases include cardiovascular disease, gastrointestinal and colorectal cancer, diabetes and insulin resistance, and Alzheimer's disease, as well as respiratory tract infection and adverse pregnancy outcomes. The presence of periodontal pathogens and their metabolic by-products in the mouth may in fact modulate the immune response beyond the oral cavity, thus promoting the development of systemic conditions. A cause-and-effect relationship has not been established yet for most of the diseases, and the mediators of the association are still being identified. A better understanding of the systemic effects of oral microorganisms will contribute to the goal of using the oral cavity to diagnose and possibly treat non-oral systemic disease.

Grading system for periodontitis by analyzing levels of periodontal pathogens in saliva

Periodontitis is an infectious disease that is associated with microorganisms that colonize the tooth surface. Clinically, periodontal condition stability reflects dynamic equilibrium between bacterial challenge and host response. Therefore, periodontal pathogen assessment can assist in the early detection of periodontitis. Here we developed a grading system called the periodontal pathogen index (PPI) by analyzing the copy numbers of multiple pathogens both in healthy and chronic periodontitis patients. We collected 170 mouthwash samples (64 periodontally healthy controls and 106 chronic periodontitis patients) and analyzed the salivary 16S rRNA levels of nine pathogens using multiplex, quantitative real-time polymerase chain reaction. Except for Aggregatibacter actinomycetemcomitans, copy numbers of all pathogens were significantly higher in chronic periodontitis patients. We classified the samples based on optimal cut-off values with maximum sensitivity and specificity from receiver operating characteristic curve analyses (AUC = 0.91, 95% CI: 0.87-0.96) into four categories of PPI: Healthy (1-40), Moderate (41-60), At Risk (61-80), and Severe (81-100). PPI scores were significantly higher in all chronic periodontitis patients than in the controls (odds ratio: 31.7, 95% CI: 13.41-61.61) and were associated with age, scaling as well as clinical characteristics including clinical attachment level and plaque index. Our PPI grading system can be clinically useful for the early assessment of pathogenic bacterial burden and follow-up monitoring after periodontitis treatment.

Potential role of nuclear magnetic resonance spectroscopy to identify salivary metabolite alterations in patients with head and neck cancer

The analysis of the salivary metabolomic profile may offer an early phase approach to assess the changes associated with a wide range of diseases including head and neck cancer. The aim of the present study was to investigate the potential of nuclear magnetic resonance (NMR) spectroscopy for detecting the salivary metabolic changes associated with head and neck squamous cell carcinoma (HNSCC). Unstimulated whole-mouth saliva samples collected from HNSCC patients (primary tumour was located either in the larynx or in the oral cavity) and healthy controls were analysed by ¹H-NMR spectroscopy. Reliably identified salivary metabolites were quantified and the determined concentration values were compared group-wise using a Mann-Whitney U-test. Multivariate discrimination function analysis (DFA) was conducted to identify such a combination of metabolites, when considered together, that gives maximum discrimination between the groups. HNSCC patients exhibited significantly increased concentrations of 1,2-propanediol (P=0.032) and fucose (P=0.003), while proline levels were significantly decreased (P=0.043). In the DFA model, the most powerful discrimination was achieved when fucose, glycine, methanol and proline were considered as combined biomarkers, resulting in a correct classification rate of 92.1%, sensitivity of 87.5% and specificity of 93.3%. To conclude, NMR spectrometric analysis was revealed to be a feasible approach to study the metabolome of saliva that is sensitive to metabolic changes in HNSCC and straightforward to collect in a non-invasive manner. Salivary fucose was of particular interest and therefore, controlled longitudinal studies are required to assess its clinical relevance as a diagnostic biomarker in HNSCC.

Role of Salivary Biomarkers in Oral Cancer Detection

Oral cancers are the sixth most frequent cancer with a high mortality rate. Oral squamous cell carcinoma accounts for more than 90% of all oral cancers. Standard methods used to detect oral cancers remain comprehensive clinical examination, expensive biochemical investigations, and invasive biopsy. The identification of biomarkers from biological fluids (blood, urine, saliva) has the potential of early diagnosis. The use of saliva for early cancer detection in the search for new clinical markers is a promising approach because of its noninvasive sampling and easy collection methods. Human whole-mouth saliva contains proteins, peptides, electrolytes, organic, and inorganic salts secreted by salivary glands and complimentary contributions from gingival crevicular fluids and mucosal transudates. This diagnostic modality in the field of molecular biology has led to the discovery and potential of salivary biomarkers for the detection of oral cancers. Biomarkers are the molecular signatures and indicators of normal biological, pathological process, and pharmacological response to treatment hence may provide useful information for detection, diagnosis, and prognosis of the disease. Saliva's direct contact with oral cancer lesions makes it more specific and potentially sensitive screening tool, whereas more than 100 salivary biomarkers (DNA, RNA, mRNA, protein markers) have already been identified, including cytokines (IL-8, IL-1b, TNF-α), defensin-1, P53, Cyfra 21-1, tissue polypeptide-specific antigen, dual specificity phosphatase, spermidine/spermineN1-acetyltransferase , profilin, cofilin-1, transferrin, and many more. However, further research is still required for the reliability and validation of salivary biomarkers for clinical applications. This chapter provides the latest up-to-date list of known and emerging potential salivary biomarkers for early diagnosis of oral premalignant and cancerous lesions and monitoring of disease activity.

Saliva in the "Omics" era: A promising tool in paediatrics

In vulnerable populations, such as infants and children, saliva makes the perfect diagnostic medium because of its noninvasive collection, easy handling and storage of samples. Its unique biomarker profiles help tremendously in the diagnosis of many diseases and conditions. In fact, saliva genomics, proteomics, transcriptomics, metabolomics and microbiome-based discoveries have led to complementary and powerful diagnostic information. In children and neonates, saliva is the preferred medium not only for diagnosis of caries and aggressive periodontitis but also for a number of systemic conditions, metabolic diseases, cognitive functions, stress assessment and evaluation of immunological and inflammatory responses to vaccination. In this review, we provide an overview of current and future applications of saliva diagnostics to various diseases and conditions and highlight studies in paediatrics across the "omic" spectrum. Emerging frontiers in salivary diagnostics research that may significantly advance the field are also highlighted.

Salivary biomarkers and proteomics: future diagnostic and clinical utilities

Saliva testing is a non-invasive and inexpensive test that can serve as a source of information useful for diagnosis of disease. As we enter the era of genomic technologies and -omic research, collection of saliva has increased. Recent proteomic platforms have analysed the human salivary proteome and characterised about 3000 differentially expressed proteins and peptides: in saliva, more than 90% of proteins in weight are derived from the secretion of three couples of "major" glands; all the other components are derived from minor glands, gingival crevicular fluid, mucosal exudates and oral microflora. The most common aim of proteomic analysis is to discriminate between physiological and pathological conditions. A proteomic protocol to analyze the whole saliva proteome is not currently available. It is possible distinguish two type of proteomic platforms: top-down proteomics investigates intact naturally-occurring structure of a protein under examination; bottom-up proteomics analyses peptide fragments after pre-digestion (typically with trypsin). Because of this heterogeneity, many different biomarkers may be proposed for the same pathology. The salivary proteome has been characterised in several diseases: oral squamous cell carcinoma and oral leukoplakia, chronic graft-versus-host disease Sjögren's syndrome and other autoimmune disorders such as SAPHO, schizophrenia and bipolar disorder, and genetic diseases like Down's Syndrome and Wilson disease. The results of research reported herein suggest that in the near future human saliva will be a relevant diagnostic fluid for clinical diagnosis and prognosis.

Quantitation of the cellular content of saliva and buccal swab samples

Buccal swabs and saliva are the two most common oral sampling methods used for medical research. Often, these samples are used interchangeably, despite previous evidence that both contain buccal cells and blood leukocytes in different proportions. For some research, such as epigenetic studies, the cell types contributing to the analysis are highly relevant. We collected such samples from twelve children and twenty adults and, using Papanicolaou staining, measured the proportions of epithelial cells and leukocytes through microscopy. To our knowledge, no studies have compared cellular heterogeneity in buccal swab and saliva samples from adults and children. We confirmed that buccal swabs contained a higher proportion of epithelial cells than saliva and that children have a greater proportion of such cells in saliva compared to adults. At this level of resolution, buccal swabs and saliva contained similar epithelial cell subtypes. Gingivitis in children was associated with a higher proportion of leukocytes in saliva samples but not in buccal swabs. Compared to more detailed and costly methods such as flow cytometry or deconvolution methods used in epigenomic analysis, the procedure described here can serve as a simple and low-cost method to characterize buccal and saliva samples. Microscopy provides a low-cost tool to alert researchers to the presence of oral inflammation which may affect a subset of their samples. This knowledge might be highly relevant to their specific research questions, may assist with sample selection and thus might be crucial information despite the ability of data deconvolution methods to correct for cellular heterogeneity.

Developing and Standardizing a Protocol for Quantitative Proton Nuclear Magnetic Resonance (1H NMR) Spectroscopy of Saliva

Metabolic profiling by 1H NMR spectroscopy is an underutilized technology in salivary research, although preliminary studies have identified promising results in multiple fields (diagnostics, nutrition, sports physiology). Translation of preliminary findings into validated, clinically approved knowledge is hindered by variability in protocol for the collection, storage, preparation, and analysis of saliva. This study aims to evaluate the effects of differing sample pretreatments on the 1H NMR metabolic profile of saliva. Protocol considerations are highly varied in the current literature base, including centrifugation, freeze-thaw cycles, and different NMR quantification methods. Our findings suggest that the 1H NMR metabolite profile of saliva is resilient to any change resulting from freezing, including freezing of saliva prior to centrifuging. However, centrifugation was necessary to remove an unidentified broad peak between 1.24 and 1.3 ppm, the intensity of which correlated strongly with saliva cellular content. This peak obscured the methyl peak from lactate and significantly affected quantification. Metabolite quantification was similar for saliva centrifuged between 750 g to 15 000 g. Quantification of salivary metabolites was similar whether quantified using internal phosphate-buffered sodium trimethylsilyl-[2,2,3,3-2H4]-propionate (TSP) or external TSP in a coaxial NMR tube placed inside the NMR tube containing the saliva sample. Our results suggest that the existing literature on salivary 1H NMR will not have been adversely affected by variations of the common protocol; however, use of TSP as an internal standard without a buffered medium appears to affect metabolite quantification, notably for acetate and methanol. We include protocol recommendations to facilitate future NMR-based studies of saliva.

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.

Influence of saliva on the oral microbiota

Saliva plays a major role in determining the composition and activity of the oral microbiota, via a variety of mechanisms. Molecules, mainly from saliva, form a conditioning film on oral surfaces, thus providing receptors for bacterial attachment. The attached cells use saliva components, such as glycoproteins, as their main source of nutrients for growth. Oral bacteria work sequentially and in a concerted manner to catabolize these structurally complex molecules. Saliva also buffers the pH in the biofilm to around neutrality, creating an environment which is conducive to the growth of many oral bacteria that provide important benefits to the host. Components of the adaptive and innate host defences are delivered by saliva, and these often function synergistically, and at sublethal concentrations, so a complex relationship develops between the host and the resident microbiota. Dysbiosis can occur rapidly if the flow of saliva is perturbed.

A serum metabolomics-based profile in low bone mineral density postmenopausal women

Osteoporosis is characterized as a metabolic disorder of bone tissue, and various metabolic markers are now available to support its diagnosis and evaluate treatment effects. Substances produced as end products of metabolomic activities are the correlated factors to the biological or metabolic status, and thus, metabolites are considered highly sensitive markers of particular pathological states, including osteoporosis. Here we undertook comprehensive serum metabolomics analysis in postmenopausal women with or without low bone mineral density (low BMD vs controls) for the first time using capillary electrophoresis/mass spectrometry. Among the metabolites tested, 57 were detected in sera. Levels of hydroxyproline, Gly-Gly and cystine, differed significantly between groups, with Gly-Gly and cystine significantly lower in the low BMD group and hydroxyproline, a reported marker of osteoporosis, significantly higher. Levels of TRACP5b, a bone resorption marker, were significantly higher in the low BMD group, supporting the study's validity. Taken together, our findings represent novel metabolomic profiling in low BMD in postmenopausal women.

Metabolomics of Head and Neck Cancer: A Mini-Review

Metabolomics is used in systems biology to enhance the understanding of complex disease processes, such as cancer. Head and neck cancer (HNC) is an epithelial malignancy that arises in the upper aerodigestive tract and affects more than half a million people worldwide each year. Recently, significant effort has focused on integrating multiple “omics” technologies for oncological research. In particular, research has been focused on identifying tumor-specific metabolite profiles using different sample types (biological fluids, cells and tissues) and a variety of metabolomic platforms and technologies. With our current understanding of molecular abnormalities of HNC, the addition of metabolomic studies will enhance our knowledge of the pathogenesis of this disease and potentially aid in the development of novel strategies to prevent and treat HNC. In this review, we summarize the proposed hypotheses and conclusions from publications that reported findings on the metabolomics of HNC. In addition, we address the potential influence of host-microbe metabolomics in cancer. From a systems biology perspective, the integrative use of genomics, transcriptomics and proteomics will be extremely important for future translational metabolomic-based research discoveries.