AimTo 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.

中文翻译：

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使用 SWATH-MS 鉴定牙龈沟液中的新分子生物标志物，用于检测牙周炎及其对治疗的反应


目的使用所有理论质谱的顺序窗口采集 （SWATH-MS） 确定新的生物标志物，以检测牙龈沟液 （GCF） 中未经治疗和已治疗的牙周炎。材料和方法从 44 名牙周健康受试者和 40 名牙周炎 （III-IV 期） 受试者中收集 GCF 样本。在后者中，25 例在治疗后 2 个月临床上有所改善。使用 SWATH-MS 分析样品，并通过 UniProt 人类特异性数据库鉴定蛋白质。用广义加法模型确定蛋白质的诊断能力，以区分 3 种临床情况。结果在未经治疗的牙周炎与牙周健康模型中，五种蛋白质显示出极好或良好的偏倚校正 （bc） 敏感性/bc 特异性值 >80%。它们是 GAPDH 、 ZG16B 、碳酸酐酶 1 、血浆蛋白酶抑制剂 C1 和血红蛋白亚基 β。含 MMP-9、MMP-8、锌-α-2-糖蛋白和中性粒细胞明胶酶相关脂质运载蛋白的 GAPDH 以及含山茱萸蛋白的 ZG16B 提供增加的 bc 敏感性/bc 特异性 >95%。为了区分治疗过的牙周炎与牙周健康，这些蛋白质中的大多数及其组合显示出类似于以前建模的预测能力。没有模型获得区分牙周炎情况的相关结果。结论新的单双 GCF 蛋白生物标志物在区分未经治疗和治疗的牙周炎与牙周健康方面显示出出色的效果。牙周炎状况难以区分。未来的研究必须验证这些发现。