Unbiased metabolic profiling has rapidly enhanced disease characterization and drug development. Periodontal disease and Type 2 diabetes have long shown a bidirectional relationship which has been greatly researched. The identification of a molecular signature of periodontitis could identify biochemicals, potential biomarkers, that may be leveraged to assist in the diagnosis and monitoring of periodontal disease. Additionally, biochemicals common to both diseases may further the research and development of effective oral care therapeutics with benefits for periodontal and diabetic patients.
Objective:
The purpose of this study was to provide biological insights on how dental disease and diabetes are associated and explore potential biomarkers indicative of that association by way of a global unbiased metabolomics screening of saliva and plasma.
Method:
161 human saliva samples were analyzed in this study and divided into 6 groups: 3 groups of diabetics with healthy periodontium, gingivitis or periodontitis, and 3 groups of non-diabetic subjects with healthy periodontium, gingivitis or periodontitis. The volunteer subjects met all inclusion/exclusion criteria and signed the IRB approved consent. Metabolon analyzed the samples via mass spectrometry technology as described in Evans et al.
Result:
Progression of gingival disease in the two groups was associated with increased energetic stress, increased oxidative stress (purine degradation pathway), elevated amino acids from protein degradation, and amplified ω-3 and ω-6 fatty acid levels which are associated with prostaglandin formation. Small biochemical signatures within the diabetic cohort also were identified including trans-4-hydroxyproline (collagen reorganization), elevated kynurenine (involved in inflammatory signaling), and increased sphingomyelin molecules which are associated with cellular/tissue signaling.
Conclusion:
The biochemicals identified in this study provide additional resolution to the bidirectional relationship between periodontitis and diabetes. Upon further validation, diagnostic measures could be implemented in order to identify the progression of gum disease in diabetics and monitor the effectiveness of treatment of periodontal disease.