Diagnostic Accuracy of Novel Protein Biomarkers in Saliva to Detect Periodontitis Using Untargeted 'SWATH' Mass Spectrometry

Aim: To discover new salivary biomarkers to diagnose periodontitis and evaluate the impact of age and smoking on predictive capacity.

Material and methods: Saliva samples were collected from 44 healthy periodontal individuals and 41 with periodontitis. Samples were analysed by sequential window acquisition of all theoretical mass spectra (SWATH-MS), and proteins were identified by employing the UniProt database. The diagnostic capacity of the molecules was determined with generalized additive models. The models obtained were single-protein unadjusted and adjusted for age and smoking status, besides two-protein combinations.

Results: Eight single salivary proteins had a bias-corrected accuracy (bc-ACC) of 78.8%-86.8% (bc-sensitivity/bc-specificity of 62.5%-86.9%/60.9%-98.1%) to diagnose periodontitis. Predictive capacity increased more by adjusting for age (bc-ACC: 94.1%-98.2%; bc-sensitivity/bc-specificity: 90.2%-98.6%/93.6%-97.2%) than smoking (bc-ACC: 83.9%-90.4%; bc-sensitivity/bc-specificity: 73.6%-89.9%/76.2%-96.4%). These proteins were keratin, type II cytoskeletal 1, protein S100-A8, β-2-microglobulin, neutrophil defensin 1, lysozyme C, ubiquitin-60S ribosomal protein L40, isoform 2 of tropomyosin α-3 chain and resistin. Two dual combinations showed bc-sensitivity/bc-specificity of > 90%: β-2-microglobulin with profilin-1, and lysozyme C with zymogen granule protein 16 homologue B.

Conclusions: New salivary biomarkers show good or excellent ability to diagnose periodontitis. Age has a more significant influence on the accuracy of the single biomarkers than smoking, with results comparable to two-protein combinations.