Metabolomics analysis of saliva from patients with primary Sjögren's syndrome

Salivary metabolomic identification of biomarker candidates for oral melanoma and oral squamous cell carcinoma in dogs

BACKGROUND

Oral melanoma (OM) and oral squamous cell carcinoma (OSCC) are frequently diagnosed in dogs, presenting a challenge in distinguishing them from benign oral tumors (BN). Salivary metabolomic biomarkers offer a practical solution because of saliva's direct contact with tumors and the noninvasive nature of collection.

OBJECTIVE

Assess the diversity and abundance of the salivary metabolome in dogs with BN, OM, and OSCC using amine/phenol submetabolome analysis and high-performance chemical isotope labeling liquid chromatography-mass spectrometry (CIL LC-MS).

ANIMALS

Study included 11 BN, 24 OM, 10 OSCC, and 20 healthy control dogs.

METHODS

Case-control cross-sectional study was conducted to assess salivary submetabolic profiles in dogs with BN, OM, and OSCC and healthy dogs. Samples were labeled with 12C-dansyl chloride and analyzed using CIL LC-MS targeted to amine- and phenol-containing metabolites for amine/phenol submetabolome analysis.

RESULTS

Distinct clusters and significant differences in metabolite concentrations were observed among the oral cancer, BN, and control groups. A total of 154 and 66 metabolites showed significantly altered concentrations, particularly in OM and OSCC, respectively, when compared with BN (Padj < .05). Potential metabolic biomarkers were identified for each cancer, including decreased concentrations of seryl-arginine and sarcosine in OSCC. Moreover, high-confidence putative metabolites were identified, including an increase in tryptophyl-threonine and a decrease in 1,2-dihydroxynapthalene-6-sulfonic acid and hydroxyprolyl-hydroxyproline for OM.

CONCLUSIONS AND CLINICAL IMPORTANCE

We identified high coverage of the amine/phenol submetabolome, including seryl-arginine, and sarcosine, in OSCC. Our findings emphasize the potential of these biomarkers for distinguishing between oral OSCC and BN in dogs.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

Application of omics in Sjögren's syndrome

OBJECTIVE

The pathogenesis, diagnosis, and treatment of Sjögren's syndrome (SS) face many challenges, and there is an urgent need to develop new technologies to improve our understanding of SS.

METHODS

By searching the literature published domestically and internationally in the past 20 years, this artical reviewed the research of various omics techniques in SS.

RESULTS

Omics technology provided valuable insights into the pathogenesis, early diagnosis, condition and efficacy evaluation of SS. It is helpful to reveal the pathogenesis of the disease and explore new treatment schemes, which will open a new era for the study of SS.

CONCLUSION

At present, omics research has made some gratifying achievements, but there are still many uncertainties. Therefore, in the future, we should improve research techniques, standardize the collection of samples, and adopt a combination of multi-omics techniques to jointly study the pathogenesis of SS and provide new schemes for its treatment.

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.

NMR-Based Metabolomics Demonstrates a Metabolic Change during Early Developmental Stages from Healthy Infants to Young Children

The present study aims to identify the salivary metabolic profile of healthy infants and young children, and to correlate this with age, salivary gland maturation, and dentition. Forty-eight children were selected after clinical evaluation in which all intraoral structures were examined. Total unstimulated saliva was collected, and salivary metabolites were analyzed by 1H Nuclear Magnetic Resonance (NMR) at 25 °C. Partial least squares discriminant analysis (PLS-DA), orthogonal PLS-DA (O-PLS-DA), and univariate analysis were used, adopting a 95% confidence interval. The study showed a distinct salivary metabolomic profile related to age and developmental phase. The saliva of children in the pre-eruption teeth period showed a different metabolite profile than that of children after the eruption. However, more evident changes were observed in the saliva profile of children older than 30 months. Alanine, choline, ethanol, lactate, and sugar region were found in higher levels in the saliva of patients before 30 months old. Acetate, N-acetyl sugar, butyrate, caproate, creatinine, leucine, phenylalanine, propionate, valine, succinate, and valerate were found to be more abundant in the saliva of children after 30 months old. The saliva profile is a result of changes in age and dental eruption, and these findings can be useful for monitoring the physiological changes that occur in infancy.

Salivary metabolome indicates a shift in tyrosine metabolism in patients with burning mouth syndrome: a prospective case-control study

ABSTRACT

The pathophysiology of primary burning mouth syndrome (BMS) remains controversial. Targeted analyses or "omics" approach of saliva provide diagnostic or pathophysiological biomarkers. This pilot study's primary objective was to explore the pathophysiology of BMS through a comparative analysis of the salivary metabolome among 26 BMS female cases and 25 age- and sex-matched control subjects. Secondary objectives included comparative analyses of inflammatory cytokines, neuroinflammatory markers, and steroid hormones among cases and control subjects, and among BMS patients according to their clinical characteristics. Salivary metabolome, neuroinflammatory markers, cytokines, and steroids were, respectively, analysed by liquid chromatography coupled with mass spectrometry, ELISA and protease activity assay, and multiparametric Luminex method. Among the 166 detected metabolites, univariate analysis did not find any discriminant metabolite between groups. Supervised multivariate analysis divided patients into 2 groups with an accuracy of 60% but did not allow significant discrimination (permutation test, P = 0.35). Among the metabolites contributing to the model, 3 belonging to the tyrosine pathway ( l -dopa, l -tyrosine, and tyramine) were involved in the discrimination between cases and control subjects, and among BMS patients according to their levels of pain. Among the detectable molecules, levels of cytokines, steroid hormones, and neuroinflammatory markers did not differ between cases and control subjects and were not associated with characteristics of BMS patients. These results do not support the involvement of steroid hormones, inflammatory cytokines, or inflammatory neurogenic mediators in the pathophysiology of pain in BMS, whereas the observed shift in tyrosine metabolism may indicate an adaptative response to chronic pain or an impaired dopaminergic transmission.

Metabolic Profile of Whole Unstimulated Saliva in Patients with Sjögren’s Syndrome

(1) Background: Primary Sjögren’s Syndrome (pSS) is a multi-system autoimmune disease that involves the exocrine glands. Lymphocytes infiltrate the gland tissue, leading to anatomical modification and hypofunction. Even if the prognosis of pSS is favorable, quality of life is typically reduced due to the diverse manifestations of the disease. The aim of this study is to compare the salivary metabolomes of pSS with healthy controls (HCs). (2) Methods: Seven cases were selected from a cohort of pSS patients, and six age- and sex-matched HCs were recruited from a cohort of volunteers. Whole unstimulated saliva was collected for NMR analysis. Our metabolomic analysis focused on 360 ms total echo 1D 1H NMR CPMG spectra. Metabolites detected with CPMG NMR spectra were assigned through 2D NMR spectra (COSY, TOCSY, and HSQC). (3) Results: About 50 metabolites were detected and assigned. Unsupervised exploratory PCA returned partial clustering, and PLS-DA improved the separation between pSS and HCs, highlighting a pool of metabolites distinctly describing each group. (4) Conclusions: Despite the limited number of samples, the presented preliminary data are promising. PLS-DA indicated well-defined group separation, suggesting that the application of 1H-NMR metabolomics is suitable for the study of pSS.

Identification of diagnostic markers related to fecal and plasma metabolism in primary Sjögren's syndrome

BACKGROUND

Accurate diagnostic techniques for patients with primary Sjögren's syndrome (pSS) are needed. This study aimed to investigate new biomarkers related to fecal and plasma metabolism from pSS patients.

METHODS

The feces and plasma of 21 pSS patients and 18 controls admitted to the Second Hospital of Shanxi Medical University were collected for analysis. Metabolites in feces and plasma were quantified using liquid chromatography-mass spectrometry. The metabolic pathway alterations caused by pSS were studied and the expression of metabolites in the intersecting pathway was analyzed in the feces and plasma of pSS patients. Metabolites that showed the same alterations in feces and plasma in pSS patients were considered as diagnostic markers and receiver operating characteristic curves were generated to analyze the sensitivity of these markers in diagnosing pSS.

RESULTS

There were 114 and 92 upregulated metabolites and 54 and 125 downregulated metabolites in the feces and plasma of pSS patients, respectively. These metabolites were enriched in 8 pathways for feces and 12 pathways for plasma. Arginine biosynthesis, Linoleic acid metabolism, Tyrosine metabolism, Taurine and hypotaurine metabolism were pathways enriched by metabolites in both samples. Twelves metabolites were enriched in the above four pathways, while only 9,10-12,13-Diepoxyoctadecanoate, Tyramine, 9-OxoODE and 2-Hydroxyethanesulfonate showed the same trend. The candidate diagnostic markers were all predictive, with better diagnostic sensitivity in plasma samples.

CONCLUSIONS

9,10-12,13-Diepoxyoctadecanoate, Tyramine, 9-OxoODE, 2-Hydroxyethanesulfonate were metabolism-related diagnostic markers for pSS feces and plasma.

Machine learning based on metabolomics reveals potential targets and biomarkers for primary Sjogren’s syndrome

Background: Using machine learning based on metabolomics, this study aimed to construct an effective primary Sjogren’s syndrome (pSS) diagnostics model and reveal the potential targets and biomarkers of pSS.

Methods: From a total of 39 patients with pSS and 38 healthy controls (HCs), serum specimens were collected. The samples were analyzed by ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry. Three machine learning algorithms, including the least absolute shrinkage and selection operator (LASSO), random forest (RF), and extreme gradient boosting (XGBoost), were used to build the pSS diagnosis models. Afterward, four machine learning methods were used to reduce the dimensionality of the metabolomics data. Finally, metabolites with significant differences were screened and pathway analysis was conducted.

Results: The area under the curve (AUC), sensitivity, and specificity of LASSO, RF and XGBoost test set all reached 1.00. Orthogonal partial least squares discriminant analysis was used to classify the metabolomics data. By combining the results of the univariate false discovery rate and the importance of the variable in projection, we identified 21 significantly different metabolites. Using these 21 metabolites for diagnostic modeling, the AUC, sensitivity, and specificity of LASSO, RF, and XGBoost all reached 1.00. Metabolic pathway analysis revealed that these 21 metabolites are highly correlated with amino acid and lipid metabolisms. On the basis of 21 metabolites, we screened the important variables in the models. Further, five common variables were obtained by intersecting the important variables of three models. Based on these five common variables, the AUC, sensitivity, and specificity of LASSO, RF, and XGBoost all reached 1.00.2-Hydroxypalmitic acid, L-carnitine and cyclic AMP were found to be potential targets and specific biomarkers for pSS.

Conclusion: The combination of machine learning and metabolomics can accurately distinguish between patients with pSS and HCs. 2-Hydroxypalmitic acid, L-carnitine and cyclic AMP were potential targets and biomarkers for pSS.

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.

Multi-Omic Biomarkers for Patient Stratification in Sjogren's Syndrome-A Review of the Literature

Sjögren's syndrome (SS) is a heterogeneous autoimmune rheumatic disease (ARD) characterised by dryness due to the chronic lymphocytic infiltration of the exocrine glands. Patients can also present other extra glandular manifestations, such as arthritis, anaemia and fatigue or various types of organ involvement. Due to its heterogenicity, along with the lack of effective treatments, the diagnosis and management of this disease is challenging. The objective of this review is to summarize recent multi-omic publications aiming to identify biomarkers in tears, saliva and peripheral blood from SS patients that could be relevant for their better stratification aiming at improved treatment selection and hopefully better outcomes. We highlight the relevance of pro-inflammatory cytokines and interferon (IFN) as biomarkers identified in higher concentrations in serum, saliva and tears. Transcriptomic studies confirmed the upregulation of IFN and interleukin signalling in patients with SS, whereas immunophenotyping studies have shown dysregulation in the immune cell population frequencies, specifically CD4⁺and C8⁺T activated cells, and their correlations with clinical parameters, such as disease activity scores. Lastly, we discussed emerging findings derived from different omic technologies which can provide integrated knowledge about SS pathogenesis and facilitate personalised medicine approaches leading to better patient outcomes in the future.

Analysis of the saliva metabolic signature in patients with primary Sjögren’s syndrome

Background

The saliva metabolome has been applied to explore disease biomarkers. In this study we characterized the metabolic profile of primary Sjögren’s syndrome (pSS) patients and explored metabolomic biomarkers.

Methods

This work presents a liquid chromatography-mass spectrometry-based metabolomic study of the saliva of 32 patients with pSS and 38 age- and sex-matched healthy adults. Potential pSS saliva metabolite biomarkers were explored using test group saliva samples (20 patients with pSS vs. 25 healthy adults) and were then verified by a cross-validation group (12 patients with pSS vs. 13 healthy adults).

Results

Metabolic pathways, including tryptophan metabolism, tyrosine metabolism, carbon fixation, and aspartate and asparagine metabolism, were found to be significantly regulated and related to inflammatory injury, neurological cognitive impairment and the immune response. Phenylalanyl-alanine was discovered to have good predictive ability for pSS, with an area under the curve (AUC) of 0.87 in the testing group (validation group: AUC = 0.75).

Conclusion

Our study shows that salivary metabolomics is a useful strategy for differential analysis and biomarker discovery in pSS.

The Involvement of Alarmins in the Pathogenesis of Sjögren's Syndrome

Sjögren’s syndrome (SS) is a chronic autoimmune disease that affects exocrine glands, primarily the salivary and lachrymal glands. It is characterized by lymphoplasmacytic infiltration of the glandular tissues, ultimately leading to their dysfunction and destruction. Besides classic dry eyes and dry mouth defined as sicca syndrome, patients affected by the disease also typically display symptoms such as fatigue, pain and in more than 50% of cases, systemic manifestations such as arthritis, interstitial lung involvement, neurological involvement and an increased risk of lymphoma. The pathophysiological mechanisms underlying SS still remain elusive. The crucial role of innate immunity has been advocated in recent years regarding the pathogenesis of pSS, especially in the initiation and progression toward autoimmunity. Alarmins are endogenous molecules that belong to the large family of damage associated molecular pattern (DAMP). Alarmins are rapidly released, ensuing cell injury and interacting with pattern recognition receptors (PRR) such as toll-like receptors (TLR) to recruit and activate cells of the innate immune system and to promote adaptive immunity responses. This review highlights the current knowledge of various alarmins and their role in the pathogenesis of pSS.

[Research Progress in the Association between Amino Acid Metabolism of Oral Microorganisms and Host Cells and Oral Diseases]

Amino acids, the substrate of protein synthesis, are an important source of energy and nutrition, second only to glucose. Previous studies have found that both microorganisms and their host cells can metabolize amino acids, and the metabolites are widely involved in the regulation of various biological processes, including inflammation and immune response. Exploring the changes in amino acid metabolism during the pathogenesis and progression of diseases has become a new hot topic of research. We summarized in this review the research progress in the pathogenesis and progression of common oral diseases, including dental caries, periodontal diseases, Sjögren's syndrome, and even oral tumors, related to metabolism pathways of amino acids, especially tryptophan and arginine, and their metabolites, attempting to provide a theoretical basis for enhancing understanding of the pathogenic mechanism of the oral diseases, as well as guidance for clinical treatment.

Updates and Original Case Studies Focused on the NMR-Linked Metabolomics Analysis of Human Oral Fluids Part I: Emerging Platforms and Perspectives

1H NMR-based metabolomics analysis of human saliva, other oral fluids, and/or tissue biopsies serves as a valuable technique for the exploration of metabolic processes, and when associated with ’state-of-the-art’ multivariate (MV) statistical analysis strategies, provides a powerful means of examining the identification of characteristic metabolite patterns, which may serve to differentiate between patients with oral health conditions (e.g., periodontitis, dental caries, and oral cancers) and age-matched heathy controls. This approach may also be employed to explore such discriminatory signatures in the salivary 1H NMR profiles of patients with systemic diseases, and to date, these have included diabetes, Sjörgen’s syndrome, cancers, neurological conditions such as Alzheimer’s disease, and viral infections. However, such investigations are complicated in view of quite a large number of serious inconsistencies between the different studies performed by independent research groups globally; these include differing protocols and routes for saliva sample collection (e.g., stimulated versus unstimulated samples), their timings (particularly the oral activity abstention period involved, which may range from one to 12 h or more), and methods for sample transport, storage, and preparation for NMR analysis, not to mention a very wide variety of demographic variables that may influence salivary metabolite concentrations, notably the age, gender, ethnic origin, salivary flow-rate, lifestyles, diets, and smoking status of participant donors, together with their exposure to any other possible convoluting environmental factors. In view of the explosive increase in reported salivary metabolomics investigations, in this update, we critically review a wide range of critical considerations for the successful performance of such experiments. These include the nature, composite sources, and biomolecular status of human saliva samples; the merits of these samples as media for the screening of disease biomarkers, notably their facile, unsupervised collection; and the different classes of such metabolomics investigations possible. Also encompassed is an account of the history of NMR-based salivary metabolomics; our recommended regimens for the collection, transport, and storage of saliva samples, along with their preparation for NMR analysis; frequently employed pulse sequences for the NMR analysis of these samples; the supreme resonance assignment benefits offered by homo- and heteronuclear two-dimensional NMR techniques; deliberations regarding salivary biomolecule quantification approaches employed for such studies, including the preprocessing and bucketing of multianalyte salivary NMR spectra, and the normalization, transformation, and scaling of datasets therefrom; salivary phenotype analysis, featuring the segregation of a range of different metabolites into ‘pools’ grouped according to their potential physiological sources; and lastly, future prospects afforded by the applications of LF benchtop NMR spectrometers for direct evaluations of the oral or systemic health status of patients at clinical ‘point-of-contact’ sites, e.g., dental surgeries. This commentary is then concluded with appropriate recommendations for the conduct of future salivary metabolomics studies. Also included are two original case studies featuring investigations of (1) the 1H NMR resonance line-widths of selected biomolecules and their possible dependence on biomacromolecular binding equilibria, and (2) the combined univariate (UV) and MV analysis of saliva specimens collected from a large group of healthy control participants in order to potentially delineate the possible origins of biomolecules therein, particularly host- versus oral microbiome-derived sources. In a follow-up publication, Part II of this series, we conduct censorious reviews of reported observations acquired from a diversity of salivary metabolomics investigations performed to evaluate both localized oral and non-oral diseases. Perplexing problems encountered with these again include those arising from sample collection and preparation protocols, along with 1H NMR spectral misassignments.

Saliva Metabolomics in Dry Mouth Patients with Head and Neck Cancer or Sjögren’s Syndrome

The etiology of dry mouth conditions is multi-faceted. Patients radiated after head and neck cancer (HNC) and those with primary Sjögren’s syndrome (pSS) share many of the same symptoms despite different causes. With the aim of better understanding the pathophysiology and biochemical processes behind dry mouth with different etiologies, we investigated the metabolic profile of 10 HNC patients, 9 pSS patients and 10 healthy controls using high-performance liquid chromatography-high resolution mass spectrometry (HPLC-MS) metabolomics. Principal component analysis (PCA) revealed different metabolic profiles when comparing all subjects included in the study. Both patient groups showed higher ratios of several pyrimidine nucleotides and nucleosides when compared to controls. This finding may indicate that purinergic signaling plays a role in dry mouth conditions. Moreover, significantly increased levels of DL-3-aminoisobutyric acid were found in HNC patients when compared to controls, and a similar tendency was observed in the pSS patients. Furthermore, a dysregulation in amino acid metabolism was observed in both patient groups. In conclusion, metabolomics analysis showed separate metabolic profiles for HNC and pSS patients as compared to controls that could be useful in diagnostics and for elucidating the different pathophysiologies. The demonstrated dysregulation of pyrimidine nucleotides and levels of metabolites derived from amino acids in the patient groups should be studied further.

Diagnostic approach to thyroid cancer based on amino acid metabolomics in saliva by ultra-performance liquid chromatography with high resolution mass spectrometry

Thyroid cancer is a malignant disease with dramatically low advanced-stage 10-year survival. Meanwhile, the metabolites in saliva are becoming a wealthy source of disease biomarkers. However, there is a lack of non-invasive analytical methods for the identification of biomarkers in saliva for the preoperative diagnosis of thyroid cancer. Therefore, we developed an ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) method to simultaneously determine the metabolic levels of 10 amino acids in saliva, aiming to study the amino acid metabolism profile to promote early diagnosis of thyroid cancer. We tested unstimulated whole saliva from patients with papillary thyroid carcinoma (PTC; n = 61) and healthy controls (HC; n = 61), and used receiver operating characteristic (ROC) curves to establish the diagnostic value of potential markers. The method validation results showed good precision, linearity (R² > 0.99), recovery (92.2 %-110.3 %), intra- and inter-day precision (RSD < 7 % and RSD < 9 %, respectively). The concentration of 10 amino acids was significantly different between PTC and HC in human salivary analysis (P < 0.05), the area under the curve (AUC) values of a single marker for the diagnosis of PTC were ranging from 0.678 to 0.833. A panel of alanine, valine, proline, phenylalanine was selected in combination yielded the AUC of 0.936, which will improve the accuracy of early diagnosis of thyroid cancer (sensitivity: 91.2 %; specificity: 85.2 %). This study proved the possibility of salivary amino acid biomarkers for PTC early diagnosis, providing a simple auxiliary way for the non-invasive diagnosis of thyroid cancer.

Low-Dose Doxycycline Treatment Normalizes Levels of Some Salivary Metabolites Associated with Oral Microbiota in Patients with Primary Sjögren's Syndrome

Saliva is a complex oral fluid, and plays a major role in oral health. Primary Sjögren’s syndrome (pSS), as an autoimmune disease that typically causes hyposalivation. In the present study, salivary metabolites were studied from stimulated saliva samples (n = 15) of female patients with pSS in a group treated with low-dose doxycycline (LDD), saliva samples (n = 10) of non-treated female patients with pSS, and saliva samples (n = 14) of healthy age-matched females as controls. Saliva samples were analyzed with liquid chromatography mass spectrometry (LC-MS) based on the non-targeted metabolomics method. The saliva metabolite profile differed between pSS patients and the healthy control (HC). In the pSS patients, the LDD treatment normalized saliva levels of several metabolites, including tyrosine glutamine dipeptide, phenylalanine isoleucine dipeptide, valine leucine dipeptide, phenylalanine, pantothenic acid (vitamin B5), urocanic acid, and salivary lipid cholesteryl palmitic acid (CE 16:0), to levels seen in the saliva samples of the HC. In conclusion, the data showed that pSS is associated with an altered saliva metabolite profile compared to the HC and that the LLD treatment normalized levels of several metabolites associated with dysbiosis of oral microbiota in pSS patients. The role of the saliva metabolome in pSS pathology needs to be further studied to clarify if saliva metabolite levels can be used to predict or monitor the progress and treatment of pSS.

Salivary Metabolomics for Diagnosis and Monitoring Diseases: Challenges and Possibilities

Saliva is a useful biological fluid and a valuable source of biological information. Saliva contains many of the same components that can be found in blood or serum, but the components of interest tend to be at a lower concentration in saliva, and their analysis demands more sensitive techniques. Metabolomics is starting to emerge as a viable method for assessing the salivary metabolites which are generated by the biochemical processes in elucidating the pathways underlying different oral and systemic diseases. In oral diseases, salivary metabolomics has concentrated on periodontitis and oral cancer. Salivary metabolites of systemic diseases have been investigated mostly in the early diagnosis of different cancer, but also neurodegenerative diseases. This mini-review article aims to highlight the challenges and possibilities of salivary metabolomics from a clinical viewpoint. Furthermore, applications of the salivary metabolic profile in diagnosis and prognosis, monitoring the treatment success, and planning of personalized treatment of oral and systemic diseases are discussed.

Time-Course of Salivary Metabolomic Profiles during Radiation Therapy for Head and Neck Cancer

Oral mucositis (OM) is one of the most frequently observed adverse oral events in radiation therapy for patients with head and neck cancer. Thus, objective evaluation of OM severity is needed for early and timely intervention. Here, we analyzed the time-course of salivary metabolomic profiles during the radiation therapy. The severity of OM (National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events v3.0) of nine patients with head and neck cancer was evaluated. Partial least squares regression-discriminant analysis, using samples collected before radiation therapy, showed that histidine and tyrosine highly discriminated high-grade OM from low-grade OM before the start of radiation therapy (significant difference, p = 0.048 for both metabolites). Further, the pretreatment concentrations of gamma-aminobutyric acid and 2-aminobutyric acids were higher in the high-grade OM group. Although further validations are still necessary, this study showed potentially associated metabolites with worse radiotherapy-related OM among patients with head and neck cancer.

Analysis of Salivary Metabolites by Nuclear Magnetic Resonance Before and After Oral Mucosa Cleaning of Infants in the Pre-dental Period

The aim of the present study was to verify if a protocol for cleaning the oral cavity of infants in the pre-dental period can reduce extrinsic salivary metabolites observed through Nuclear Magnetic Resonance (NMR). A cross-sectional clinical study with a convenience sample was conducted, and infants were recruited at the UFRJ Pediatric Dentistry Clinic. Participants who had used antibiotics and/or antifungals up to 3 months before and whose legal guardians did not consent or sign the Informed Consent Form were excluded. An anamnesis was performed with the guardians and the participants' intraoral clinical examination. Initial collection of unstimulated total saliva was performed using an automatic pipette with sterile plastic tips in the buccal floor region, at least 1 h after the last feeding. Subsequently, the infants' oral mucosa was cleaned with gauze moistened with filtered water, and after 5 min, a new collection was performed, using the same methodology. The obtained samples were immediately transferred on ice to the laboratory, centrifuged (10,000 g), and stored at −80°C. The NMR analyses were performed using a 500-MHz spectrometer Bruker, Germany); evaluations were done via the 1H and 1H-1H TOCSY spectra for metabolite signaling. Eleven pre-dental infants were evaluated, with a mean age of 3.8 months, including six girls (55%). Of these, nine participants (82%) were exclusively breastfed. The higher presence of components such as lactose, glucose, sugars, acetate, alanine, and lactate were observed in the samples before oral mucosa cleaning. Regarding the type of diet, more lactose was observed in the saliva of patients who were exclusively breastfed than those that received mixed feeding. We conclude that the oral mucosa cleaning of infants in the pre-dental period tends to reduce the concentration of extrinsic components from the diet, such as lactose, in the salivary metabolomic profile analyzed by NMR.

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

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

Untargeted lipidomics reveals specific lipid abnormalities in Sjögren's syndrome

OBJECTIVE

The relationship between serum lipid variations in SS and healthy controls was investigated to identify potential predictive lipid biomarkers.

METHODS

Serum samples from 230 SS patients and 240 healthy controls were collected. The samples were analysed by ultrahigh-performance liquid chromatography coupled with Q Exactive™ spectrometry. Potential lipid biomarkers were screened through orthogonal projection to latent structures discriminant analysis and further evaluated by receiver operating characteristic analysis.

RESULTS

A panel of three metabolites [phosphatidylcholine (18:0/22:5), triglyceride (16:0/18:0/18:1) and acylcarnitine (12:0)] was identified as a specific biomarker of SS. The receiver operating characteristic analysis showed that the panel had a sensitivity of 84.3% with a specificity of 74.8% in discriminating patients with SS from healthy controls.

CONCLUSION

Our approach successfully identified serum biomarkers associated with SS patients. The potential lipid biomarkers indicated that SS metabolic disturbance might be associated with oxidized lipids, fatty acid oxidation and energy metabolism.

Positive Effects of Saliva on Oral Candidiasis: Basic Research on the Analysis of Salivary Properties

The major causes of oral candidiasis include decreased salivary flow rate and the use of ill-fitting dentures. However, the relationships among prosthetic treatment, saliva, and Candida albicans have not been elucidated. This study aimed to examine the effects of prosthetic treatment and changes in saliva (mainly the salivary flow rate) on oral candidiasis symptoms. Participants requiring prosthetic treatment underwent testing for C. albicans, salivary flow rate, intraoral symptoms, and bite force at the initial visit and four months after treatment to evaluate pretreatment and post-treatment changes. The relationships among C. albicans, salivary flow rate, dentures, and intraoral symptoms were analyzed using multiple regression analysis. Denture treatment improved activity against C. albicans as well as the salivary flow rate, intraoral symptoms, and masticatory function. Multiple regression analysis revealed that changes in the stimulated salivary flow rate due to prosthetic treatment significantly improved C. albicans detection (p = 0.011), intraoral symptoms (p = 0.037), and bite force (p = 0.031). This study showed that prosthetic treatment improved salivary flow and intraoral symptoms and confirmed the influence of stimulated salivary flow rate changes.

Comparison and Analysis of Gut Microbiota in Children With IgA Vasculitis With Different Clinical Symptoms

Background: Henoch-Schönlein purpura, now called immunoglobulin A (IgA) vasculitis, is a common autoimmune disease in children, its association with gut microbiota composition remains unknown. Methods: The collected cases were divided into three groups: G1 group of simple skin type, G2 group with no digestive tract expression, G3 group of mixed digestive tract, and C group of healthy children. The fecal samples of each group of children were collected and the sequencing data was processed and analyzed. The dilution curve reflected the reasonableness of the amount of sequencing data. Results: The number of species composition sequences in the G1, G2 and G3 groups was lower than that in the C group, especially for the G2 and G3 groups. The four most abundant bacteria were Bacteroidetes, Firmicutes, Proteobacteria and Actinobacteria. The relative abundance of Proteobacteria in the G2 and G3 groups was significantly higher than that in the G1 and C groups, while the relative abundance of Actinobacteria was significantly reduced, and the relative abundance of Actinobacteria in the G1 group was lower than that in the C group. Principal component analysis of the UPGMA clustering tree and each group of samples showed that the microbial community composition of the same group of samples was similar. Conclusions: The abundance of intestinal microbes in children with IgA vasculitis is lower than in normal children. Bacteroidetes, Firmicutes, Proteobacteria and Actinobacteria are the four most abundant bacteria in the intestinal flora of children. Proteobacteria and Actinobacteria are associated with organ involvement in IgA vasculitis.

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.

Variability of salivary metabolite levels in patients with Sjögren's syndrome

PURPOSE

To investigate inter- and intra-individual variation in the levels and outputs (concentration multiplied by salivary flow rate) of salivary metabolites in patients with primary Sjögren's syndrome (pSS).

METHODS

A total of 56 samples of stimulated saliva were collected from 14 female pSS patients during four laboratory visits within 20 weeks and analyzed using proton nuclear magnetic resonance spectroscopy. Single saliva samples from each of 15 controls were also analyzed.

RESULTS

Among 21 quantified metabolites, choline was significantly elevated in the pSS patients at each time point (P ≤ 0.015), taurine at the last three time points (P ≤ 0.013), alanine at the last two time points (P ≤ 0.007) and glycine at the last time point (P = 0.005). Inter-individual variation in metabolite concentrations was generally larger among the patients than among the controls, and significantly large variations were observed for glycine (P ≤ 0.007, all time points), choline (P ≤ 0.033, three last time points) and alanine (P = 0.028, baseline). Metabolite output analysis showed that choline had the lowest intra-patient variation.

CONCLUSION

In spite of considerable intra- and inter-individual variation, levels and outputs of specific metabolites in patients with pSS differ from those in controls, and may be potentially applicable as new biological markers for monitoring of the response to treatment.

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.

Caution in studying and interpreting the lupus metabolome

Several metabolomics studies have shed substantial light on the pathophysiological pathways underlying multiple diseases including systemic lupus erythematosus (SLE). This review takes stock of our current understanding of this field. We compare, collate, and investigate the metabolites in SLE patients and healthy volunteers, as gleaned from published metabolomics studies on SLE. In the surveyed primary reports, serum or plasma samples from SLE patients and healthy controls were assayed using mass spectrometry or nuclear magnetic resonance spectroscopy, and metabolites differentiating SLE from controls were identified. Collectively, the circulating metabolome in SLE is characterized by reduced energy substrates from glycolysis, Krebs cycle, fatty acid β oxidation, and glucogenic and ketogenic amino acid metabolism; enhanced activity of the urea cycle; decreased long-chain fatty acids; increased medium-chain and free fatty acids; and augmented peroxidation and inflammation. However, these findings should be interpreted with caution because several of the same metabolic pathways are also significantly influenced by the medications commonly used in SLE patients, common co-morbidities, and other factors including smoking and diet. In particular, whereas the metabolic alterations relating to inflammation, oxidative stress, lipid peroxidation, and glutathione generation do not appear to be steroid-dependent, the other metabolic changes may in part be influenced by steroids. To conclude, metabolomics studies of SLE and other rheumatic diseases ought to factor in the potential contributions of confounders such as medications, co-morbidities, smoking, and diet.

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.

Combining surface-enhanced Raman scattering (SERS) of saliva and two-dimensional shear wave elastography (2D-SWE) of the parotid glands in the diagnosis of Sjögren's syndrome

In this study, we combine the molecular structural information gained by SERS of saliva samples with the morphological data given by two-dimensional shear wave elastography (2D-SWE) (SuperSonic Imagine, Aixplorer) of parotid glands in the case of n = 31 patients with Sjögren's syndrome (SjS) and n = 22 controls, with the aim to discriminate between the two groups. The overall classification accuracy yielded by a hybrid principal component analysis-linear discriminant analysis (PCA-LDA) model based on both SERS and elastography (81%) was superior to that yielded by SERS spectra alone (75%) and elastography data alone (71%). This preliminary study is the first report on the use of 2D-SWE of parotid glands for the diagnosis of SjS as well as the first to describe the diagnosis of SjS based on the SERS spectra of dried saliva samples, the results suggesting that the strategy of combining the two methods could improve the diagnosis of SjS.

Intraoral Microbial Metabolism and Association with Host Taste Perception

Metabolomics has been identified as a means of functionally assessing the net biological activity of a particular microbial community. Considering the oral microbiome, such an approach remains largely underused. While the current knowledge of the oral microbiome is constantly expanding, there are several deficits in knowledge particularly relating to their interactions with their host. This work uses nuclear magnetic resonance spectroscopy to investigate metabolic differences between oral microbial metabolism of endogenous (i.e., salivary protein) and exogenous (i.e., dietary carbohydrates) substrates. It also investigated whether microbial generation of different metabolites may be associated with host taste perception. This work found that in the absence of exogenous substrate, oral bacteria readily catabolize salivary protein and generate metabolic profiles similar to those seen in vivo. Important metabolites such as acetate, butyrate, and propionate are generated at relatively high concentrations. Higher concentrations of metabolites were generated by tongue biofilm compared to planktonic salivary bacteria. Thus, as has been postulated, metabolite production in proximity to taste receptors could reach relatively high concentrations. In the presence of 0.25 M exogenous sucrose, increased catabolism was observed with increased concentrations of a range of metabolites relating to glycolysis (lactate, pyruvate, succinate). Additional pyruvate-derived molecules such as acetoin and alanine were also increased. Furthermore, there was evidence that individual taste sensitivity to sucrose was related to differences in the metabolic fate of sucrose in the mouth. High-sensitivity perceivers appeared more inclined toward continual citric acid cycle activity postsucrose, whereas low-sensitivity perceivers had a more efficient conversion of pyruvate to lactate. This work collectively indicates that the oral microbiome exists in a complex balance with the host, with fluctuating metabolic activity depending on nutrient availability. There is preliminary evidence of an association between host behavior (sweet taste perception) and oral catabolism of sugar.

Microbiota and metabolites in rheumatic diseases

As a gigantic community in the human body, the microbiota exerts pleiotropic roles in human health and disease ranging from digestion and absorption of nutrients from food, defense against infection of pathogens, to regulation of immune system development and immune homeostasis. Recent advances in "omics" studies and bioinformatics analyses have broadened our insights of the microbiota composition of the inner and other surfaces of the body and their interactions with the host. Apart from the direct contact of microbes at the mucosal barrier, metabolites produced or metabolized by the gut microbes can serve as important immune regulators or initiators in a wide variety of diseases, including gastrointestinal diseases, metabolic disorders and systemic rheumatic diseases. This review focuses on the most recent understanding of how the microbiota and metabolites shape rheumatic diseases. Studies that explore the mechanistic interplay between microbes, metabolites and the host could thereby provide clues for novel methods in the diagnosis, therapy, and prevention of rheumatic diseases.

Salivary Metabolomics: From Diagnostic Biomarker Discovery to Investigating Biological Function

Metabolomic profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, metabolomic analysis of saliva, the most readily-available human biofluid, has lagged. This review explores the history of saliva-based metabolomics and summarizes current knowledge of salivary metabolomics. Current applications of salivary metabolomics have largely focused on diagnostic biomarker discovery and the diagnostic value of the current literature base is explored. There is also a small, albeit promising, literature base concerning the use of salivary metabolomics in monitoring athletic performance. Functional roles of salivary metabolites remain largely unexplored. Areas of emerging knowledge include the role of oral host-microbiome interactions in shaping the salivary metabolite profile and the potential roles of salivary metabolites in oral physiology, e.g., in taste perception. Discussion of future research directions describes the need to begin acquiring a greater knowledge of the function of salivary metabolites, a current research direction in the field of the gut metabolome. The role of saliva as an easily obtainable, information-rich fluid that could complement other gastrointestinal fluids in the exploration of the gut metabolome is emphasized.

Discovering new metabolite alterations in primary sjögren's syndrome in urinary and plasma samples using an HPLC-ESI-QTOF-MS methodology

Sjögren's Syndrome (SjS) is a complex autoimmune disease characterized by the affection of the exocrine glands and the involvement of multiple organs. Although a greater number of biomarker studies have been carried out in recent years, the origin and pathogenesis are not yet well known and therefore there is a need to continue studying this pathology. This work aims to find metabolic changes in biological samples (plasma and urine), which could help identify the metabolic pathways affected by the SjS pathogenesis. The samples collected from SjS patients and healthy volunteers were analyzed by a fingerprinting metabolomic approach based on HPLC-ESI-QTOF-MS methodology. After feature pre-selection by univariate statistical tests, an integrated PLS-DA model using data from urine and plasma was constructed obtaining a good classification between cases and controls (AUROC = 0.839 ± 0.021). 31 and 38 metabolites in plasma and urine, respectively, showed significant differences between healthy volunteers and SjS patients and were proposed for their identification. From them, 12 plasma and 24 urinary metabolites could be annotated. In general, the main metabolic pathways altered in SjS patients were related to the metabolism of phospholipids, fatty acids, and amino acids, specially tryptophan, proline and phenylalanine.

Identification of a Shared Microbiomic and Metabolomic Profile in Systemic Autoimmune Diseases

Dysbiosis has been described in systemic autoimmune diseases (SADs), including systemic lupus erythematosus (SLE), Sjögren’s syndrome (SjS), and primary anti-phosholipid syndrome (PAPS), however the biological implications of these associations are often elusive. Stool and plasma samples from 114 subjects, including in SLE (n = 27), SjS (n = 23), PAPs (n = 11) and undifferentiated connective tissue (UCTD, n = 26) patients, and geographically-matched healthy controls (HCs, n = 27), were collected for microbiome (16s rRNA gene sequencing) and metabolome (high-performance liquid chromatography coupled to mass spectrometry) analysis to identify shared characteristics across diseases. Out of 130 identified microbial genera, a subset of 29 bacteria was able to differentiate study groups (area under receiver operating characteristics (AUROC) = 0.730 ± 0.025). A fair classification was obtained with a subset of 41 metabolic peaks out of 254 (AUROC = 0.748 ± 0.021). In both models, HCs were well separated from SADs, while UCTD largely overlapped with the other diseases. In all of the SADs pro-tolerogenic bacteria were reduced, while pathobiont genera were increased. Metabolic alterations included two clusters comprised of: (a) members of the acylcarnitine family, positively correlating with a Prevotella-enriched cluster and negatively correlating with a butyrate-producing bacteria-enriched cluster; and (b) phospholipids, negatively correlating with butyrate-producing bacteria. These findings demonstrate a strong interaction between intestinal microbiota and metabolic function in patients with SADs.

Metabolomic profiling reveals salivary hypotaurine as a potential early detection marker for medication-related osteonecrosis of the jaw

Medication-related osteonecrosis of the jaw (MRONJ) is a rare but serious adverse event of bone-modifying agents used to prevent bone complications in cancer patients with bone metastasis. Currently, early treatment is the only way to prevent further progression, as the pathogenesis of MRONJ has not yet been elucidated, and a standard treatment has not been established. The aim of this study was to identify a marker for early detection marker of MRONJ by exploring substances in saliva specific to MRONJ at an early stage. We collected salivary samples from 17 patients with MRONJ and conducted metabolomic analyses using capillary electrophoresis mass spectrometry for non-targeted analysis of hydrophilic metabolites. In the screening cohort, we compared the saliva of patients with stage ≥1 advanced MRONJ (n = 9) with that of controls without MRONJ before chemotherapy (n = 9). The top 5 most elevated salivary metabolites were histamine, 3-(4-hydroxyphenyl)propionate, malonate, carnosine, and hypotaurine. In the validation cohort, we analyzed additional patients with stage ≥1 advanced MRONJ (n = 8) and controls without MRONJ after chemotherapy (n = 9), confirming a significant 2.28-fold elevation in the salivary concentration of hypotaurine. These results revealed elevated salivary hypotaurine concentration as a potential marker for the early detection of MRONJ.

Emerging role of metabolomics in rheumatology

The pursuit for understanding disease pathogenesis, in this age of rapid laboratory diagnostics and fast-paced research, has led scientists worldwide to take recourse in hypothesis-free approaches for molecular diagnosis. Metabolomics is one such powerful tool that explores comprehensibly the metabolic alternations in human diseases. It involves study of small molecules of less than 1 kD in size by either LSMS or nuclear magnetic resonance. Unlike genomics, which tells us what may have happened, metabolomics reflects what did happen. The NMR technique has an advantage of analyzing metabolites without sample preparation, thereby diminishing artifacts, is less cumbersome and with the latest database on Metabolome; about 30 000 metabolites can be identified. The study of metabolomics for several rheumatic diseases, including rheumatoid arthritis, lupus, osteoarthritis and vasculitis, has revealed distinctive metabolic signatures. Thus, metabolomics is a technique that promises precision medicine with better biomarkers, robust predictors of drug response and of disease outcome, discovery of newer metabolites and pathways in disease pathogenesis, and finally, targeted drug development. This review intends to decipher its relevance in common rheumatic diseases.

Current concepts on Sjögren's syndrome - classification criteria and biomarkers

Sjögren's syndrome is a lymphoproliferative disease with autoimmune features characterized by mononuclear cell infiltration of exocrine glands, notably the lacrimal and salivary glands. These lymphoid infiltrations lead to dryness of the eyes (keratoconjunctivitis sicca), dryness of the mouth (xerostomia), and, frequently, dryness of other surfaces connected to exocrine glands. Sjögren's syndrome is associated with the production of autoantibodies because B-cell activation is a consistent immunoregulatory abnormality. The spectrum of the disease extends from an organ-specific autoimmune disorder to a systemic process and is also associated with an increased risk of B-cell lymphoma. Current treatments are mainly symptomatic. As a result of the diverse presentation of the syndrome, a major challenge remains to improve diagnosis and therapy. For this purpose an international set of classification criteria for primary Sjögren's syndrome has recently been developed and validated and seems well suited for enrolment in clinical trials. Salivary gland biopsies have been examined and histopathology standards have been developed, to be used in clinical trials and patient stratification. Finally, ultrasonography and saliva meet the need of non-invasive imaging and sampling methods for discovery and validation of disease biomarkers in Sjögren's syndrome.

Tooth loss in Sjögren's syndrome patients compared to age and gender matched controls

BACKGROUND

To analyze the prevalence and location of tooth loss in Sjögren's syndrome (SS) patients and compare them with an age- and gender-matched control group.

MATERIAL AND METHODS

Dental charts and x-rays of 108 (SS) patients were retrieved from an academic dental center and special care dentistry department. For each SS patient, an age- and gender-matched non-SS patient was randomly selected. Medication, number of extractions and date and location of extractions were assessed. Differences between SS and non-SS patients were analyzed using Mann-Whitney U tests, Chi-square tests and Fisher's exact tests.

RESULTS

Significantly more SS patients were edentulous compared to the non-SS group (14.8% versus 1.9%, p = 0.001). SS patients had a 61% higher risk to have experienced one or more extractions than control patients. In the SS group, there was a non-significant tendency for more maxillary teeth to have been extracted than mandibular teeth (42:34). In the control group, the number of extractions in the maxilla and mandible were comparable (21:20). When divided into sextants, the number of SS patients with one or more extractions was significantly higher than for non-SS patients for each sextant (p = 0.001 to p = 0.032). The largest difference in the proportion of patients with one or more extractions between the SS and non-SS patients occurred in the upper anterior sextant (3.4 times more frequent).

CONCLUSIONS

SS patients are more prone to experience dental extractions compared to patients without SS. It could be speculated that this is related to a decreased salivary secretion.

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.

Identification of Metabolite Biomarkers for Gout Using Capillary Ion Chromatography with Mass Spectrometry

Gout is a common form of inflammatory arthritis, and the detailed pathogenic mechanisms for this metabolic disorder remain largely unknown. In this study, we first profiled the salivary metabolites in 8 patients with gout, 15 patients with hyperuricaemia (HUA), and 15 healthy individuals using capillary ion chromatography (CIC) with tandem mass spectrometry (MS/MS). Forty-nine salivary metabolites were found to be significantly changed between gout patient and healthy control groups, and 26 salivary metabolites were significantly different between gout and HUA patient groups. Three metabolite biomarkers, uric acid, oxalic acid, and l-homocysteic acid (HCA), were selected for validation in the saliva samples of 30 patients with gout, 30 patients with HUA, and 30 healthy control subjects. By using commercial assay kits for the measurements, salivary uric acid and oxalic acid levels were found to be significantly higher in gout patients than healthy controls, whereas salivary HCA level was significantly higher in gout patients than both HUA patients and healthy controls. These assay measurements were in line with those obtained by CIC-MS/MS. In conclusion, we have demonstrated a new application of CIC-MS/MS for the discovery of novel metabolite biomarkers of gout. Validated biomarkers may be used for noninvasive, diagnostic and prognostic applications in gout. Future studies are warranted to investigate the clinical utility of these identified biomarkers for monitoring gout flare and/or treatment efficacy.

Advancing Point-of-Care (PoC) Testing Using Human Saliva as Liquid Biopsy

Salivary diagnostics is an emerging field for the encroachment of point of care technology (PoCT). The necessity of the development of point-of-care (PoC) technology, the potential of saliva, identification and validation of biomarkers through salivary diagnostic toolboxes, and a broad overview of emerging technologies is discussed in this review. Furthermore, novel advanced techniques incorporated in devices for the early detection and diagnosis of several oral and systemic diseases in a non-invasive, easily-monitored, less time consuming, and in a personalised way is explicated. The latest technology detection systems and clinical utilities of saliva as a liquid biopsy, electric field-induced release and measurement (EFIRM), biosensors, smartphone technology, microfluidics, paper-based technology, and how their futuristic perspectives can improve salivary diagnostics and reduce hospital stays by replacing it with chairside screening is also highlighted.

Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome

Objectives

Multiomics study was conducted to elucidate the crucial molecular mechanisms of primary Sjögren’s syndrome (SS) pathology.

Methods

We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation.

Results

Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 ­T cells­ were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS.

Conclusions

Our multiomics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.

Effect of timing of collection of salivary metabolomic biomarkers on oral cancer detection

The aim of this study is to evaluate the effect of duration after meals for saliva collections for oral cancer detection using metabolomics. Saliva samples were collected from oral cancer patients (n = 22) and controls (n = 44). Saliva from cancer patients was collected 12 h after dinner, and 1.5 and 3.5 h after breakfast. Control subjects fasted >1.5 h prior to saliva collection. Hydrophilic metabolites were analyzed using capillary electrophoresis mass spectrometry. Levels of 51 metabolites differed significantly in controls vs. oral cancer patients at the 12-h fasting time point (P < 0.05). Fifteen and ten metabolites differed significantly at the 1.5- and 3.5-h time points, respectively. The area of under receiver operating characteristic curve for discriminating oral cancer patients from controls was greatest at the 12-h fasting time point. The collection time after meals affects levels of salivary metabolites for oral cancer screening. The 12-h fasting after dinner time point is optimal. This study contributes to design of saliva collection protocols for metabolomics-based biomarker discovery.

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.

Oral Biofluid Biomarker Research: Current Status and Emerging Frontiers

Salivary diagnostics is a rapidly advancing field that offers clinicians and patients the potential of rapid, noninvasive diagnostics with excellent accuracy. In order for the complete realization of the potential of saliva, however, extensive profiling of constituents must be conducted and diagnostic biomarkers must be thoroughly validated. This article briefly overviews the process of conducting a study of salivary biomarkers in a patient cohort and highlights the studies that have been conducted on different classes of molecules in the saliva. Emerging frontiers in salivary diagnostics research that may significantly advance the field will also be highlighted.