IADR Abstract Archives
Identification of Salivary Biomarkers of Periodontitis Using Proximity Extension Assays
Objectives: Identification of periodontitis biomarkers in saliva could aid patient management and reveal novel insights into periodontal pathogenesis. The proximity extension assay (PEA) is a highly sensitive, quantitative approach for multiplex analysis of proteins and we used this technology to identify novel periodontitis-associated biomarkers.
Methods: Saliva was collected from 15 periodontally healthy volunteers and 15 patients with untreated periodontitis (probing depths [PD] >5mm at >8 teeth and >30% BOP). All were non-smokers, and systemically healthy. 276 proteins were quantified by PEA (Olink Proteomics, Uppsala, Sweden) and the relative levels of individual proteins between health and disease analysed using Welches t-test adjusted for multiple testing using the False Discovery Rate method. Verification of candidate biomarkers was carried out by ELISA (Quantikine, Biotechne).
Results: 181 of 276 proteins analysed were detected in >75% of the samples and, of these, 71 proteins had statistically significantly different levels in periodontitis. Among the biomarkers significantly elevated in periodontitis were matrix metalloproteinase-9 (P=9.6x10-4), hepatocyte growth factor (P=7.8x10-4) and urokinase plasminogen activator (P=2.9x10-3). Urokinase plasminogen activator receptor (uPAR) was one novel biomarker identified in this study; this mediator was significantly elevated in the PEA analysis (P=7.3x10-4) and by ELISA analysis of a larger patient cohort from the same study (N=30 and N=34 from periodontitis and healthy subjects respectively; P <0.001). Furthermore, salivary uPAR levels correlated significantly with clinical measures of periodontitis e.g. PD (P<0.01) and %BOP (P<0.001). Intriguingly, 45 of the 71 identified candidate biomarkers were proteins associated with cardiovascular disease. Also, at least 12 of these biomarkers have key roles in monocyte/macrophage regulation and 8 of these are significantly correlated with age in the healthy control group.
Conclusions: This novel multiplex approach afforded by the PEA technology revealed several candidate biomarkers for periodontitis. Further characterisation of these biomarkers may reveal pathogenic links between periodontitis, monocyte/macrophage function and cardiovascular disease.
Methods: Saliva was collected from 15 periodontally healthy volunteers and 15 patients with untreated periodontitis (probing depths [PD] >5mm at >8 teeth and >30% BOP). All were non-smokers, and systemically healthy. 276 proteins were quantified by PEA (Olink Proteomics, Uppsala, Sweden) and the relative levels of individual proteins between health and disease analysed using Welches t-test adjusted for multiple testing using the False Discovery Rate method. Verification of candidate biomarkers was carried out by ELISA (Quantikine, Biotechne).
Results: 181 of 276 proteins analysed were detected in >75% of the samples and, of these, 71 proteins had statistically significantly different levels in periodontitis. Among the biomarkers significantly elevated in periodontitis were matrix metalloproteinase-9 (P=9.6x10-4), hepatocyte growth factor (P=7.8x10-4) and urokinase plasminogen activator (P=2.9x10-3). Urokinase plasminogen activator receptor (uPAR) was one novel biomarker identified in this study; this mediator was significantly elevated in the PEA analysis (P=7.3x10-4) and by ELISA analysis of a larger patient cohort from the same study (N=30 and N=34 from periodontitis and healthy subjects respectively; P <0.001). Furthermore, salivary uPAR levels correlated significantly with clinical measures of periodontitis e.g. PD (P<0.01) and %BOP (P<0.001). Intriguingly, 45 of the 71 identified candidate biomarkers were proteins associated with cardiovascular disease. Also, at least 12 of these biomarkers have key roles in monocyte/macrophage regulation and 8 of these are significantly correlated with age in the healthy control group.
Conclusions: This novel multiplex approach afforded by the PEA technology revealed several candidate biomarkers for periodontitis. Further characterisation of these biomarkers may reveal pathogenic links between periodontitis, monocyte/macrophage function and cardiovascular disease.