Mass Spectrometry and Gingival Crevicular Fluid Biomarkers

Background: Gingival crevicular fluid has been suggested as a possible source of biomarkers for periodontal disease progression. Objectives: To assess whether the mass spectrometric analysis of GCF will allow for the discrimination of sites based on clinical indices and the prediction of sites which would lose periodontal attachment. Methods: Forty-one periodontal maintenance subjects were followed over 12 months, with clinical measurements taken at baseline and every 3 months thereafter. Gingival crevicular fluid was collected from subjects at each visit and analysed with MALDI mass spectrometry. Samples were classified based upon pocket depth (PD), modified gingival index, plaque index (MGI) and attachment loss, and analysed within these groups. A genetic algorithm was used to create a model which can be used to identify sites which would undergo disease breakdown. Results: Three-hundred and eighty-five GCF samples were analysed. Twenty-five sites under observation in 14 patients suffered breakdown of > 2 mm over the 12 month period. Three of 5 smokers had a site with attachment loss. The clinical indices of PD, MGI, plaque levels and bleeding served as poor discriminators of GCF mass spectra. For attachment loss sites, the use of models generated from GCF mass spectra allowed for breakdown sites to be predicted with a high specificity (97% recognition capability and 67% cross validation). Conclusions: Models generated from GCF mass spectra allow for the prediction of sites which will suffer from attachment loss from a single test. The small number of patients in this study means that the results cannot be properly validated, and more work in this area is required. The use of algorithm generated models of disease opens up a novel area for future research in the area of diagnostics in periodontology and other disciplines of dentistry.