Abstract

Aim: To discover and validate differential protein biomarker expression in saliva and gingival crevicular
fluid (GCF) to discriminate objectively between periodontal health and plaque-induced periodontal
disease states.
Materials and methods: 190 participants were recruited from two centres (Birmingham and Newcastle
upon Tyne, UK) comprising healthy, gingivitis, periodontitis and edentulous donors. Samples from the
Birmingham cohort were analysed by quantitative mass spectrometry proteomics for biomarker
discovery. Shortlisted candidate proteins were then verified by enzyme-linked immunosorbent assay
in both cohorts. Leave-one-out cross validation logistic regression analysis was used to identify the
best performing biomarker panels.
Results: 95 proteins were identified in both GCF and saliva samples and 15 candidate proteins were
selected based upon differences discovered between the donor groups. The best performing panels
to distinguish between: health or gingivitis and periodontitis contained matrix metalloproteinase-9
(MMP9), S100A8, alpha-1-acid glycoprotein (A1AGP), pyruvate kinase and age (area under the curve
(AUC) 0.970); health and gingivitis contained MMP9, S100A8, A1AGP, pyruvate kinase but not age
(AUC 0.768); and mild-moderate and advanced periodontitis contained MMP9, S100A8, A1AGP,
pyruvate kinase and age (AUC 0.789).
Conclusion(s): Biomarker panels containing four proteins with and without age as a further parameter
can distinguish between periodontal health and disease states.