Saliva and Plasma Reflect Metabolism Altered by Diabetes and Periodontitis

Identifying metabolic biomarkers and pathways in pulpitis: a metabolomic study using ultra-high-performance liquid chromatography/orbitrap mass spectrometry

BACKGROUND

Pulpitis, which is often triggered by caries and trauma, is a significant clinical challenge due to its prevalence. This research aims to uncover potential metabolic biomarkers for pulpitis and map out the implicated metabolic pathways, thereby laying a foundation for enhanced diagnostic and preventive strategies.

METHODOLOGY

We analyzed pulp samples from 12 participants (six who had pulpitis and six who had healthy teeth) using serum metabolomics via ultra-high-performance liquid chromatography coupled with Orbitrap mass spectrometry. Important biomarkers were pinpointed via multivariate analysis and orthogonal partial least squares discriminant analysis. Additionally, correlation and biomarker pathway enrichment analyses were conducted to explore the relations between differentially expressed biomarkers and their associated biological pathways. Specific metabolites of interest were further examined via alkaline phosphatase (ALP) staining, Alizarin Red staining, and RT-qPCR analysis.

RESULTS

We identified 22 significant biomarkers (13 increased, nine decreased) related to 18 metabolic pathways in pulpitis cases. Key biomarkers included ascorbic acid, inosine, allopurinol riboside, and L-asparagine, in which ascorbic acid and inosine showed the most substantial downregulation and strongest association with pulpitis. Notably, aminoacyl-tRNA biosynthesis and retrograde endocannabinoid signaling pathways were closely linked with pulpitis. Ascorbic acid enhanced the osteogenic differentiation, calcium deposition, as well as the expression of osteogenic genes of human dental pulp stem cells (DPSCs).Conclusions: The identified biomarkers and metabolic pathways offer insights into the pathogenesis of pulpitis and have potential applications in developing preventive treatments.

Metabolomics Applications for Diagnosing Peri-Implantitis: A Systematic Review of In Vivo Studies

Background/Objectives: Peri-implantitis is a prevalent inflammatory condition affecting dental implants, leading to increased treatment costs, patient dissatisfaction, and potential implant failure. Novel biomarker-based approaches may contribute to early detection, thereby decreasing the burden of the disease. The aim of this review was to assess in vivo studies using metabolomics to identify the metabolic profiles and potential biomarkers of peri-implantitis. Methods: The protocol for this study was registered with PROSPERO (CRD42025634865). Five databases and grey literature sources (PubMed, Scopus, Web of Science, ProQuest, and Google Scholar) were searched using keywords related to metabolomics and peri-implantitis. Studies were selected by independent, inter-calibrated researchers. Data were extracted using predefined, custom forms. The risk of bias was assessed using the ROBINS-I tool. Results: An electronic literature search retrieved 543 articles, of which five were selected. All studies were published within the last five years of the search. All but one study used untargeted metabolomics, and all studies identified metabolites associated with peri-implantitis or distinct metabolomic profiles of peri-implantitis. SCFAs and lysine metabolites were recurring in the results, confirming the findings of previous metabolomic studies on periodontal disease. Conclusions: Metabolomics has not been widely used to study peri-implantitis. Evidence from existing studies confirms the findings of metabolomics studies on periodontitis. Several metabolites related to PI are associated with immune response, tissue degradation, and cellular energy pathways. Integrating -omics technologies into peri-implantitis diagnosis may facilitate biomarker discovery and improve early detection strategies.

Emerging biomarkers in type 2 diabetes mellitus

Diabetes mellitus is a chronic condition caused by high blood glucose resulting from insufficient insulin production or cellular resistance to insulin action or both. It is one of the fastest-growing public health concerns worldwide. Development of long-term nephropathy, retinopathy, neuropathy, and cardiovascular disease are some of the complications commonly associated with poor blood glycemic control. Type 2 diabetes mellitus (T2DM), the most prevalent type of diabetes, accounts for around 95 % of all cases globally. Although middle-aged or older adults are more likely to develop T2DM, its prevalence has grown in children and young people due to increased obesity, sedentary lifestyle and poor nutrition. Furthermore, it is believed that more than 50 % of cases go undiagnosed annually. Routine screening is essential to ensure early detection and reduce risk of life-threatening complications. Herein, we review traditional biomarkers and highlight the ongoing pursuit of novel and efficacious biomarkers driven by the objective of achieving early, precise and prompt diagnoses. It is widely acknowledged that individual biomarkers will inevitably have certain limitations necessitating the need for integrating multiple markers in screening.

Salivary microbiome and biomarker characteristics of diabetics with periodontitis

OBJECTIVE

To examine the characteristics of the salivary microbiome in Type 2 diabetes mellitus (T2DM) patients with or without periodontitis.

BACKGROUND

Periodontitis has been identified as clear sequelae of T2DM. This chronic oral disease also impacts the management of the clinical features of diabetes. The oral microbiome characteristics in T2DM with and without periodontitis, as well as the response of this oral microbiome to nonsurgical therapy have not been well described. Knowledge of key oral biological features could help address the observed poorer clinical presentation of T2DM patients.

METHODS

The oral microbiome in saliva of adult cohorts periodontally healthy/non-diabetic (non-periodontitis; NP; n = 31), T2DM without periodontitis (DWoP; n = 32), and T2DM with periodontitis (DWP; n = 29) were characterized by microbial molecular analysis using V3-V4 sequencing and Luminex or ELISA techniques for salivary host analytes.

RESULTS

Phyla distribution showed DWP with significantly lower levels of Firmicutes and Actinobacteria and higher levels of Fusobacteria and Spirochetes compared to the healthier groups. Approximately 10% of the detected microbial species showed significant differences in frequency and level of colonization among the DWP, DWoP, and NP samples. A subset of bacteria were significantly correlated with clinical disease features, as well as a specific repertoire of salivary analytes, in particular matrix metalloproteinase (MMP)8/MMP9, interleukin-1ß, B-cell activating factor, and resistin differed between the groups and were related to specific taxa. Principal component analysis that identified a majority of the DWP subjects microbiome was unique based upon an array of 27 taxa out of up to 255 detected in the saliva samples.

CONCLUSION

T2DM patients with periodontitis show unique oral microbiome and salivary analyte composition compared to diabetics or non-diabetic persons without periodontitis. Specific members of the oral microbiome relate directly to the clinical disease features and/or salivary biomolecules in T2DM individuals.

Association of socio-demographic characteristics, comorbidities, lifestyle habits, and saliva parameters with dental caries in adults with obesity

OBJECTIVE

To describe the oral health status of patients with obesity and to explore the socio-demographic characteristics, comorbidities, lifestyle habits (tobacco, alcohol, sweet/acidic diet), and saliva parameters most associated with the dental caries experience.  Material and methods: We conducted a cross-sectional analysis of 204 patients' data with obesity attending a therapeutic education programme. Caries experience (number of decayed, missing, and filled teeth [DMFT]), periodontal status, oral hygiene, occlusal tooth wear, masticatory inefficiency, and saliva parameters were recorded.

RESULTS

Mean DMFT was 12 ± 7 and was independently associated with age (mean 47 ± 14 years; for 1 standard deviation (SD) increase: β = 0.22, 95% confidence interval [CI] = 0.16-0.29), female sex (72%; β = 3.76, 95% CI = 1.65-5.87), brushing <2 times/day (35%; β = 2.86, 95% CI = 0.81-4.90), salivary buffering capacity (low [46%] vs. normal [40%]: β = 2.02, 95% CI = 0.08-3.95; very low [10%] vs. normal: β = 3.34, 95% CI = 0.31-6.37), and salivary consistency (bubbly [30%] vs. clear [57%]: β = 2.45, 95% CI = 0.52-4.38).

CONCLUSIONS

Improving patients' competencies for oral care, such as teeth brushing twice daily, is necessary to limit the burden of dental caries in individuals with obesity. Acting on salivary composition may also be of interest, and further studies are required to explore the underlying mechanisms.

Salivary features of periodontitis and gingivitis in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is associated with cellular abnormalities, tissue and organ dysfunctions, and periodontitis. This investigation examined the relationship between the oral microbiome and salivary biomarkers in T2DM patients with or without periodontitis. This cohort (35-80 years) included systemically healthy non-periodontitis (NP; n = 31), T2DM without periodontitis (DWoP; n = 32) and T2DM with periodontitis (DWP; n = 29). The oral microbiome [Operational Taxonomic Units (OTUs)] (16 s rRNA sequencing) and targeted host salivary biomarkers (immunoassays) were assessed. We identified 47 OTUs that were significantly different in abundance between NP samples and any disease subset or between disease subgroups. The most unique microbiome patterns were observed in the DWP group. Differences in genera/species abundance were also observed when T2DM patients were stratified by extent of periodontal inflammation and disease (i.e., generalized versus localized gingivitis/periodontitis). Salivary biomarkers showed significant elevations in MMP-8, MMP-9, resistin, IL-1β, IL-6, IFNα, and BAFF (THFSR13b) comparing generalized to localized periodontitis. Salivary analytes showed significant positive correlations with specific microbiome members, predominantly in DWP patients. Odds ratio analyses reinforced that a panel of biologic markers (IL-6, MMP-8) and bacteria (e.g., Bacteroidetes, Fusobacteria, Spirochaetes) discriminated the severity and extent of periodontal disease in this diabetic population.

Metabolomics: Unveiling biological matrices in precision nutrition and health

Precision nutrition, an expanding field at the intersection of nutrition science and personalized medicine, is rapidly evolving with metabolomics integration. Metabolomics, facilitated by advanced technologies like mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy, facilitates comprehensive profiling of metabolites across diverse biological samples. From the perspective of health care systems, precision nutrition gains relevance due to the substantial impact of prevalent non-communicable diseases (NCDs) on societal well-being, which is directly linked with dietary habits and eating behavior. Furthermore, biomarker products derived from metabolomics have been utilized in Europe, the USA, and Brazil to understand metabolic dysregulations and tailor diets accordingly. Despite its burgeoning status, metabolomics holds great potential in revolutionizing nutritional science, particularly with the integration of artificial intelligence and machine learning, offering novel insights into personalized dietary interventions and disease prediction. This narrative review emphasizes the transformative impact of metabolomics in precision and delineates avenues for future research and application, paving the way for a more tailored and practical approach to nutrition management.

Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults

AIMS/HYPOTHESIS

Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites.

METHODS

We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors.

RESULTS

Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures.

CONCLUSIONS/INTERPRETATION

The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

Study on pulp metabolism of patients with pulpitis using ultra-performance liquid chromatography coupled with Orbitrap mass spectrometry

BACKGROUND AND AIMS

Pulpitis, a pulp disease caused by caries, trauma, and other factors, has a high clinical incidence. This study focused on identifying possible metabolic biomarkers of pulpitis cases and analyzing the related metabolic pathways for providing a theoretical foundation to diagnose and prevent pulpitis.

MATERIALS AND METHODS

Pulp samples from 20 pulpitis cases together with 20 normal participants were analyzed with a serum metabolomics approach using ultra-high-performance liquid chromatography (UPLC)/Orbitrap mass spectrometry. Moreover, this work carried out multivariate statistical analysis for screening potential biomarkers of pulpitis.

RESULTS

Through biomarker analysis and identification, such as partial least squares discrimination analysis, orthogonal partial least squares discriminant analysis model establishment, correlation analysis, and biomarker pathway analysis, 40 biomarkers associated with 20 metabolic pathways were identified, including 20 upregulated and 20 downregulated metabolites. Those major biomarkers included oxoglutaric acid, inosine, citric acid, and PA(14:1(9Z)/PGD1). Among them, oxoglutaric acid and inosine were most significantly downregulated and had the highest correlation with pulpitis. Among these metabolic pathways, GABAergic synapse and alanine, aspartate, and glutamate metabolism were positively correlated with pulpitis. 4.

CONCLUSIONS

These biomarkers as well as metabolic pathways may offer the theoretical foundation to understand pulpitis pathogenesis and develop preventive drugs.

The polymicrobial pathogenicity of Porphyromonas gingivalis

Accumulating microbiome data and mechanistic studies in vitro and in vivo have refined our understanding of the oral microbiota as a functionally integrated polymicrobial community. Emergent properties of these communities are driven to a large extent by interspecies communication which can be based on physical association, secreted small molecules or nutritional exchange. Porphyromonas gingivalis is a consensus periodontal pathogen; however, virulence is only expressed in the context of a polymicrobial community. Multivalent fimbriae mediate attachment to other oral species which can initiate a distinct transcriptional program in both constituents of the binding pair. P. gingivalis also responds to small molecules and nutritional cues produced by partner organisms. Physiological interdependence forms the basis of complex networks of cooperating organisms which begin to resemble an organismal entity exhibiting a spectrum of pathogenic potential.

Salivary metabolomics in oral potentially malignant disorders and oral cancer patients-a systematic review with meta-analysis

OBJECTIVES

The aim of this systematic review and meta-analysis is to assess the diagnostic potential of salivary metabolomics in the detection of oral potentially malignant disorders (OPMDs) and oral cancer (OC).

MATERIALS AND METHODS

A systematic review was performed in accordance with the 3rd edition of the Centre for Reviews and Dissemination (CRD) and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Electronic searches for articles were carried out in the PubMed, Web of Science, and Scopus databases. The quality assessment of the included studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS) and the new version of the QUADOMICS tool. Meta-analysis was conducted whenever possible. The effect size was presented using the Forest plot, whereas the presence of publication bias was examined through Begg's funnel plot.

RESULTS

A total of nine studies were included in the systematic review. The metabolite profiling was heterogeneous across all the studies. The expression of several salivary metabolites was found to be significantly altered in OPMDs and OCs as compared to healthy controls. Meta-analysis was able to be conducted only for N-acetylglucosamine. There was no significant difference (SMD = 0.15; 95% CI - 0.25-0.56) in the level of N-acetylglucosamine between OPMDs, OC, and the control group.

CONCLUSION

Evidence for N-acetylglucosamine as a salivary biomarker for oral cancer is lacking. Although several salivary metabolites show changes between healthy, OPMDs, and OC, their diagnostic potential cannot be assessed in this review due to a lack of data. Therefore, further high-quality studies with detailed analysis and reporting are required to establish the diagnostic potential of the salivary metabolites in OPMDs and OC.

CLINICAL RELEVANCE

While some salivary metabolites exhibit significant changes in oral potentially malignant disorders (OPMDs) and oral cancer (OC) compared to healthy controls, the current evidence, especially for N-acetylglucosamine, is inadequate to confirm their reliability as diagnostic biomarkers. Additional high-quality studies are needed for a more conclusive assessment of salivary metabolites in oral disease diagnosis.

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

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

Total Antioxidant Capacity of Saliva and Its Correlation with pH Levels among Dental Students under Different Stressful Conditions

(1) Background: This cross-sectional study conducted at the Faculty of Dental Medicine, Timisoara, Romania, between December 2022 and February 2023 aims to assess salivary total antioxidant capacity and pH levels in dental students experiencing non-stressful and stressful situations and explore potential correlations between these factors. (2) Methods: Saliva samples were collected during two different periods: before an Oral Health course and before the Oral Health exam, under stressful conditions. Ethical principles were followed, and informed consent was obtained. Data on age, gender, health status, drug use, smoking habits, and anxiety levels were recorded. Saliva was collected using the draining method and pH was measured using indicator paper strips. Total antioxidant capacity (TAC) was determined using a commercial assay kit. Statistical analysis involved descriptive statistics, Student's t-test to compare pH and TAC between study groups, and Pearson's correlation coefficient to analyze the correlation between salivary pH and TAC within each group, with p < 0.05 indicating significance. (3) Results: This study involved 80 participants, comprising 26 males and 54 females, all enrolled in the 5th year of the Oral Health course, with ages ranging from 20 to 53 and a mean age of 23.62 (±4.19) years. Pearson's correlation results show a statistically significant negative relationship between the STAI test and TAC during the stress-free period (-0.02 **, N = 80, p < 0.01). (4) Conclusions: There are variations in saliva's antioxidant capacity in response to different stress conditions. Dental students experienced a higher level of stress before academic assessments compared to the non-stress period during the course.

Human Serum and Salivary Metabolomes: Diversity and Closeness

Saliva, which contains molecular information that may reflect an individual's health status, has become a valuable tool for discovering biomarkers of oral and general diseases. Due to the high vascularization of the salivary glands, there is a molecular exchange between blood and saliva. However, the composition of saliva is complex and influenced by multiple factors. This study aimed to investigate the possible relationships between the salivary and serum metabolomes to gain a comprehensive view of the metabolic phenotype under physiological conditions. Using 1H-NMR spectroscopy, we obtained the serum metabolite profiles of 20 healthy young individuals and compared them with the metabolomes of parotid, submandibular/sublingual, and whole-saliva samples collected concurrently from the same individuals using multivariate and univariate statistical analysis. Our results show that serum is more concentrated and less variable for most of the shared metabolites than the three saliva types. While we found moderate to strong correlations between serum and saliva concentrations of specific metabolites, saliva is not simply an ultrafiltrate of blood. The intense oral metabolism prevents very strong correlations between serum and salivary concentrations. This study contributes to a better understanding of salivary metabolic composition, which is crucial for utilizing saliva in laboratory diagnostics.

Dysbiosis of oral microbiome persists after dental treatment-induced remission of periodontal disease and dental caries

IMPORTANCE

We characterized the oral conditions, salivary microbiome, and metabolome after dental treatment by investigating the state after treatment completion and transition to self-care. Dental treatment improved oral health conditions, resulting in oral disease remission; however, the imbalanced state of the salivary microbiome continued even after remission. Although the results of this study are preliminary, owing to the small number of participants in each group when compared to larger cohort studies, they indicate that the risk of disease may remain higher than that of healthy participants, thereby demonstrating the importance of removing dental plaque containing disease-related bacteria using appropriate care even after treatment completion. We also identified bacterial species with relative abundances that differed from those of healthy participants even after remission of symptoms, which may indicate that the maturation of certain bacterial species must be controlled to improve the oral microbiome and reduce the risk of disease recurrence.

Monitoring saliva compositions for non-invasive detection of diabetes using a colorimetric-based multiple sensor

The increasing population of diabetic patients, especially in developing countries, has posed a serious risk to the health sector, so that the lack of timely diagnosis and treatment process of diabetes can lead to threatening complications for the human lifestyle. Here, a multiple sensor was fabricated on a paper substrate for rapid detection and controlling the progress of the diabetes disease. The proposed sensor utilized the sensing ability of porphyrazines, pH-sensitive dyes and silver nanoparticles in order to detect the differences in saliva composition of diabetic and non-diabetic patients. A unique color map (sensor response) was obtained for each studied group, which can be monitored by a scanner. Moreover, a good correlation was observed between the colorimetric response resulting from the analysis of salivary composition and the fasting blood glucose (FBG) value measured by standard laboratory instruments. It was also possible to classify participants into two groups, including patients caused by diabetes and those were non-diabetic persons with a total accuracy of 88.9%. Statistical evaluations show that the multiple sensor can be employed as an effective and non-invasive device for continuous monitoring of diabetes, substantially in the elderly.

Utilising the precision nutrition toolkit in the path towards precision medicine

The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.

Salivary Metabolomic Signatures and Body Mass Index in Italian Adolescents: A Pilot Study

CONTEXT

Obesity surveillance is scarce in adolescents, and little is known on whether salivary metabolomics data, emerging minimally invasive biomarkers, can characterize metabolic patterns associated with overweight or obesity in adolescents.

OBJECTIVE

This pilot study aims to identify the salivary molecular signatures associated with body mass index (BMI) in Italian adolescents.

METHODS

Saliva samples and BMI were collected in a subset of n = 74 young adolescents enrolled in the Public Health Impact of Metal Exposure study (2007-2014). A total of 217 untargeted metabolites were identified using liquid chromatography-high resolution mass spectrometry. Robust linear regression was used to cross-sectionally determine associations between metabolomic signatures and sex-specific BMI-for-age z-scores (z-BMI).

RESULTS

Nearly 35% of the adolescents (median age: 12 years; 51% females) were either obese or overweight. A higher z-BMI was observed in males compared to females (P = .02). One nucleoside (deoxyadenosine) and 2 lipids (18:0-18:2 phosphatidylcholine and dipalmitoyl-phosphoethanolamine) were negatively related to z-BMI (P < .05), whereas 2 benzenoids (3-hydroxyanthranilic acid and a phthalate metabolite) were positively associated with z-BMI (P < .05). In males, several metabolites including deoxyadenosine, as well as deoxycarnitine, hyodeoxycholic acid, N-methylglutamic acid, bisphenol P, and trigonelline were downregulated, while 3 metabolites (3-hydroxyanthranilic acid, theobromine/theophylline/paraxanthine, and alanine) were upregulated in relation to z-BMI (P < .05). In females, deoxyadenosine and dipalmitoyl-phosphoethanolamine were negatively associated with z-BMI while deoxycarnitine and a phthalate metabolite were positively associated (P < .05). A single energy-related pathway was enriched in the identified associations in females (carnitine synthesis, P = .04).

CONCLUSION

Salivary metabolites involved in nucleotide, lipid, and energy metabolism were primarily altered in relation to BMI in adolescents.

Salivary metabolic signatures of carotid atherosclerosis in patients with type 2 diabetes hospitalized for treatment

Atherosclerosis is a life-threatening disease associated with morbidity and mortality in patients with type 2 diabetes (T2D). This study aimed to characterize a salivary signature of atherosclerosis based on evaluation of carotid intima-media thickness (IMT) to develop a non-invasive predictive tool for diagnosis and disease follow-up. Metabolites in saliva and plasma samples collected at admission and after treatment from 25 T2D patients hospitalized for 2 weeks to undergo medical treatment for diabetes were comprehensively profiled using metabolomic profiling with gas chromatography-mass spectrometry. Orthogonal partial least squares analysis, used to explore the relationships of IMT with clinical markers and plasma and salivary metabolites, showed that the top predictors for IMT included salivary allantoin and 1,5-anhydroglucitol (1,5-AG) at both the baseline examination at admission and after treatment. Furthermore, though treatment induced alterations in salivary levels of allantoin and 1,5-AG, it did not modify the association between IMT and these metabolites (p _interaction > 0.05), and models with these metabolites combined yielded satisfactory diagnostic accuracy for the high IMT group even after treatment (area under curve = 0.819). Collectively, this salivary metabolite combination may be useful for non-invasive identification of T2D patients with a higher atherosclerotic burden in clinical settings.

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.

Metabolomics profiling reveals berberine-inhibited inflammatory response in human gingival fibroblasts by regulating the LPS-induced apoptosis signaling pathway

This article examines berberine’s biological effects and molecular mechanisms with an inflammatory response model induced by lipopolysaccharide (LPS) in human gingival fibroblasts (HGFs) using metabolomics. The viability of HGFs was determined using the cell counting kit-8 (CCK8). ELISA was used to measure inflammatory cytokines, including interleukin-6 (IL-6), interleukin-1β (IL-1β), and tumor necrosis factor- α (TNF-α). An investigation of western blots was conducted to investigate the related proteins of apoptosis. Low concentrations of berberine (0.1, 0.5, and 1 μmol L⁻¹) did not affect HGF growth, whereas high concentrations of berberine (5–25 μmol L⁻¹) significantly activated cell proliferation. Berberine suppressed the elevated secretion of IL-6, IL-1β, and TNF-α induced by LPS in HGF. Western blot analysis showed that 10 μmol L⁻¹ of berberine significantly inhibited LPS-induced apoptosis signaling pathway activation. Our results suggested that berberine could inhibit LPS-induced apoptosis and the production of proinflammatory mediators in HGFs cells. Berberine may be a potential therapeutic drug for the management of periodontitis.

Alterations and Correlations of Gut Microbiota and Fecal Metabolome Characteristics in Experimental Periodontitis Rats

Objectives

Periodontitis affects the progression of many diseases, while its detailed mechanism remains unclear. This study hopes to provide new ideas for exploring its mechanism by analyzing the gut microbiota and fecal metabolic characteristics of experimental periodontitis rats.

Methods

A total of 10 rats were randomly divided into ligature-induced experimental periodontitis (EP) group and healthy control group. After 4 weeks of the experiment, the feces of all rats were collected for sequencing through 16S ribosomal DNA (rDNA) sequencing technology and liquid chromatography–mass spectrometry (LC–MS).

Results

16S rDNA sequencing results showed that the β-diversity of gut microbiota was significantly different between the EP and control group, and the levels of dominant genera were different. Compared with the control group, Ruminococcus, Escherichia, and Roseburia were significantly enriched in EP, and Coprococcus, Turicibacter, Lachnospira were significantly decreased. Correlation analysis showed that Roseburia exhibited the highest correlation within the genus. Of 3,488 qualitative metabolites, 164 metabolites were upregulated and 362 metabolites were downregulated in EP. Enrichment analysis showed that periodontitis significantly changed 45 positive/negative ion metabolic pathways. Five KEGG pathways, protein digestion and absorption, tyrosine metabolism, glycolysis/gluconeogenesis, niacin and nicotinamide metabolism, and oxidative phosphorylation, are enriched in both the microbiome and metabolome. Correlation analysis showed that the genera with significant differences in periodontitis were usually significantly correlated with more metabolites, such as Roseburia, Lachnospira, Escherichia, Turicibacter, and Ruminococcus. The genera with the same changing trend tended to have a similar correlation with some certain metabolites. In addition, vitamin D2 and protoporphyrin IX have the most significant correlations with microorganisms.

Conclusion

Our study reveals that periodontitis alters gut microbiota and fecal metabolites. The correlation analysis of microbiota and metabolome provides a deeper understanding of periodontitis, and also provides a direction for the study of periodontitis affecting other diseases.