Using SWATH‐MS to identify new molecular biomarkers in gingival crevicular fluid for detecting periodontitis and its response to treatment

Abstract

AbstractAimTo identify new biomarkers to detect untreated and treated periodontitis in gingival crevicular fluid (GCF) using sequential window acquisition of all theoretical mass spectra (SWATH‐MS).Materials and MethodsGCF samples were collected from 44 periodontally healthy subjects and 40 with periodontitis (Stages III–IV). In the latter, 25 improved clinically 2 months after treatment. Samples were analysed using SWATH‐MS, and proteins were identified by the UniProt human‐specific database. The diagnostic capability of the proteins was determined with generalized additive models to distinguish the three clinical conditions.ResultsIn the untreated periodontitis vs. periodontal health modelling, five proteins showed excellent or good bias‐corrected (bc)‐sensitivity/bc‐specificity values of >80%. These were GAPDH, ZG16B, carbonic anhydrase 1, plasma protease inhibitor C1 and haemoglobin subunit beta. GAPDH with MMP‐9, MMP‐8, zinc‐α‐2‐glycoprotein and neutrophil gelatinase‐associated lipocalin and ZG16B with cornulin provided increased bc‐sensitivity/bc‐specificity of >95%. For distinguishing treated periodontitis vs. periodontal health, most of these proteins and their combinations revealed a predictive ability similar to previous modelling. No model obtained relevant results to differentiate between periodontitis conditions.ConclusionsNew single and dual GCF protein biomarkers showed outstanding results in discriminating untreated and treated periodontitis from periodontal health. Periodontitis conditions were indistinguishable. Future research must validate these findings.