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

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

Nuclear magnetic resonance spectroscopic analysis of salivary metabolome in sarcoidosis.

BACKGROUND: Sarcoidosis is a systemic granulomatous disease of unknown cause which has diverse clinical impacts, ranging from benign to very severe, which may therefore require systemic treatment. Only a few tools are currently available to monitor management in these patients. OBJECTIVES: As sarcoidosis is known to affect salivary glands, we hypothesized that analysis of saliva could reveal valuable biomarkers for disease management. We designed a comparative analysis of salivary metabolomics in patients and controls using Nuclear Magnetic Resonance (NMR). METHODS: Metabolomic profiles of saliva collected from 24 sarcoidosis patients and 45 controls were obtained by proton NMR spectroscopy with multivariate statistical analysis, followed by metabolite identification and pathway analysis. Oral and dental examinations were performed concomitantly, together with assessment of smoking habits. RESULTS: A predictive salivary metabolomic signature associated with sarcoidosis was computed with the Orthogonal Partial least squares discriminant analysis (OPLS) model. Six metabolites were altered in samples from sarcoidosis patients compared to controls, including decreased levels of methanol and butyrate and increased levels of lactate, acetate and N-butyrate. CONCLUSION: This study showed that NMR metabolomics can discriminate saliva samples from sarcoidosis patients and controls. According to these preliminary results, saliva studies in sarcoidosis patients would be particularly useful to identify potentially relevant biomarkers. A study based on a larger number of patients at different stages of the disease or with treated patients is needed to assess the clinical relevance of NMR metabolomics in sarcoidosis.