Changes in the Salivary Metabolic Profile of Generalized Periodontitis Patients after Non-surgical Periodontal Therapy: A Metabolomic Analysis Using Nuclear Magnetic Resonance Spectroscopy

Radiation-induced changes in salivary metabolite profile and pathways in head and neck cancer patients

INTRODUCTION

This longitudinal study assessed the salivary metabolic profile in patients with head and neck cancer (HNC) treated with radiotherapy (RT). This study aims to investigate salivary metabolites and biological oral pathways induced by RT.

METHODS

Clinical data and unstimulated whole-mouth saliva (USWMS) were obtained from 45 HNC patients before, during, and one week after the RT. Data was also collected from 30 healthy controls. NMR spectroscopy identified and quantified 24 metabolites. Spearman's rank correlation analysis and pathway enrichment analysis (MetaboAnalyst 6.0) was performed to check the effect of cancer therapy on the correlation and pathways of different salivary metabolites.

RESULTS

Of 24 metabolites identified, 17 salivary metabolites showed a consistent decrease in the concentration during and after treatment of HNC patients. The metabolite proline decreased, whereas fucose and 1,2-Propanediol were increased in the saliva causing altered redox balance and abnormal fucosylation in HNC patients compared to controls. Spearman correlation analysis indicated changes between pyruvate and some other metabolites, including alanine, trimethylamine, choline, taurine, and succinate, during RT. Five pathways (Pyruvate metabolism; Glycolysis / Gluconeogenesis; Glycine, serine, and threonine metabolism; Glyoxylate and dicarboxylate metabolism; and Alanine, aspartate and glutamate metabolism) are affected, demonstrating the metabolic dysregulation due to RT. The pyruvate metabolism was overpresented with the high Pathway Impact score.

CONCLUSION

Salivary metabolomics analysis revealed significant alterations in the metabolic profile of HNC patients undergoing RT, providing valuable insights into treatment-induced oral pathobiological changes. Alterations in salivary pathways during RT suggest disturbances in redox homeostasis, oxidative stress, and inflammation. The ability to monitor salivary metabolites and pathways non-invasively holds promise to personalized medicine in HNC treatment by enabling early detection of treatment-related toxicities, monitoring treatment response, and tailoring interventions to patient needs.

Metabolomics Analysis as a Tool in Periodontitis Diagnosis: A Systematic Review

OBJECTIVES

This study aims to summarize recent studies available on untargeted metabolomics employed for periodontitis diagnosis, from saliva and gingival crevicular fluid samples, to identify recurring metabolites with biomarker-value potential. A secondary objective was to analysudurue the protocols of existing studies, to facilitate further research.

MATERIAL AND METHODS

Three databases were electronically searched for relevant studies (PubMed, Web of Science, Scopus). Risk of bias assessment was performed using the Newcastle-Ottawa scale (NOS). Data was extracted from studies, regarding general characteristics and conclusions, population characteristics, periodontal protocols, and metabolomics protocols. Metabolic pathway analysis was performed for recurrent metabolites.

RESULTS

After screening 405 studies, 13 studies (10 using saliva samples, 3 using GCF samples) were included. 22 metabolites were identified in more than one study and included into the pathway analysis. Butyrate, lactate, isoleucine, glucose, pyruvate, isovalerate, hypoxanthine/xanthine, proline, valine, phenylalanine, and ethanol were most frequently encountered and were found upregulated in periodontitis patients compared to periodontally healthy patients.

CONCLUSIONS

Metabolomics could provide valuable opportunities in validating potential biomarkers or diagnosis panels, contributing to the screening, prognosis, progression and monitoring of periodontitis. Further studies on larger populations and using established protocols are needed. (PROSPERO CRD42023470339).

Manipulating the diseased oral microbiome: the power of probiotics and prebiotics

Dental caries and periodontal disease are amongst the most prevalent global disorders. Their aetiology is rooted in microbial activity within the oral cavity, through the generation of detrimental metabolites and the instigation of potentially adverse host immune responses. Due to the increasing threat of antimicrobial resistance, alternative approaches to readdress the balance are necessary. Advances in sequencing technologies have established relationships between disease and oral dysbiosis, and commercial enterprises seek to identify probiotic and prebiotic formulations to tackle preventable oral disorders through colonisation with, or promotion of, beneficial microbes. It is the metabolic characteristics and immunomodulatory capabilities of resident species which underlie health status. Research emphasis on the metabolic environment of the oral cavity has elucidated relationships between commensal and pathogenic organisms, for example, the sequential metabolism of fermentable carbohydrates deemed central to acid production in cariogenicity. Therefore, a focus on the preservation of an ecological homeostasis in the oral environment may be the most appropriate approach to health conservation. In this review we discuss an ecological approach to the maintenance of a healthy oral environment and debate the potential use of probiotic and prebiotic supplementation, specifically targeted at sustaining oral niches to preserve the delicately balanced microbiome.

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

OBJECTIVE

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Periodontal disease metabolomics signatures from different biofluids: a systematic review

BACKGROUND

Periodontitis is resulted from a complex interaction between genetics and epigenetics, microbial factors, and the host response. Metabolomics analyses reflect both the steady-state physiological equilibrium of cells or organisms as well as their dynamic metabolic responses to environmental stimuli.

AIM OF REVIEW

This systematic review of the literature aimed to assess which low molecular weight metabolites are more often found in biological fluids of individuals with periodontitis compared to individuals with gingivitis or periodontal health.

KEY SCIENTIFIC CONCEPTS OF REVIEW

All the included studies employed untargeted analysis. One or more biological fluids were analyzed, including saliva (n = 14), gingival crevicular fluid (n = 6), mouthwash (n = 1), serum (n = 3) and plasma (n = 1). Fifty-six main metabolites related to periodontitis have been identified in at least two independent studies by NMR spectroscopy or MS-based metabolomics. Saliva was the main biological fluid sampled. It is noteworthy that 14 metabolites of the 56 detected were identified as main metabolites in all studies that sampled the saliva. The majority of metabolites found consistently among studies were amino acids, organic acids and derivates: acetate, alanine, butyrate, formate, GABA, lactate, propionate, phenylalanine and valine. They were either up- or down-regulated in the studies or this information was not mentioned. The main metabolic pathway was related to phenylalanine, tyrosine and tryptophan biosynthesis. Metabolites more frequently found in individuals with periodontitis were related to both the host and to microorganism responses. Future studies are needed, and they should follow some methodological standards to facilitate their comparison.

Systematic Review of NMR-Based Metabolomics Practices in Human Disease Research

Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.

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

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

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

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

Metabolite and lipoprotein profiles reveal sex-related oxidative stress imbalance in de novo drug-naive Parkinson's disease patients

Parkinson’s disease (PD) is the neurological disorder showing the greatest rise in prevalence from 1990 to 2016. Despite clinical definition criteria and a tremendous effort to develop objective biomarkers, precise diagnosis of PD is still unavailable at early stage. In recent years, an increasing number of studies have used omic methods to unveil the molecular basis of PD, providing a detailed characterization of potentially pathological alterations in various biological specimens. Metabolomics could provide useful insights to deepen our knowledge of PD aetiopathogenesis, to identify signatures that distinguish groups of patients and uncover responsive biomarkers of PD that may be significant in early detection and in tracking the disease progression and drug treatment efficacy. The present work is the first large metabolomic study based on nuclear magnetic resonance (NMR) with an independent validation cohort aiming at the serum characterization of de novo drug-naive PD patients. Here, NMR is applied to sera from large training and independent validation cohorts of German subjects. Multivariate and univariate approaches are used to infer metabolic differences that characterize the metabolite and the lipoprotein profiles of newly diagnosed de novo drug-naive PD patients also in relation to the biological sex of the subjects in the study, evidencing a more pronounced fingerprint of the pathology in male patients. The presence of a validation cohort allowed us to confirm altered levels of acetone and cholesterol in male PD patients. By comparing the metabolites and lipoproteins levels among de novo drug-naive PD patients, age- and sex-matched healthy controls, and a group of advanced PD patients, we detected several descriptors of stronger oxidative stress.

Metagenomic and Metatranscriptomic Insight Into Oral Biofilms in Periodontitis and Related Systemic Diseases

The oral microbiome is one of the most complex microbial communities in the human body and is closely related to oral and systemic health. Dental plaque biofilms are the primary etiologic factor of periodontitis, which is a common chronic oral infectious disease. The interdependencies that exist among the resident microbiota constituents in dental biofilms and the interaction between pathogenic microorganisms and the host lead to the occurrence and progression of periodontitis. Therefore, accurately and comprehensively detecting periodontal organisms and dissecting their corresponding functional activity characteristics are crucial for revealing periodontitis pathogenesis. With the development of metagenomics and metatranscriptomics, the composition and structure of microbial communities as well as the overall functional characteristics of the flora can be fully profiled and revealed. In this review, we will critically examine the currently available metagenomic and metatranscriptomic evidence to bridge the gap between microbial dysbiosis and periodontitis and related systemic diseases.

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.