Bellei Elisa, Bertoldi Carlo, Monari Emanuela, Bergamini Stefania
Proteomic Lab, Department of Surgery, Medicine, Dentistry and Morphological Sciences with Transplant Surgery, Oncology and Regenerative Medicine Relevance, University-Hospital of Modena and Reggio Emilia, Via del Pozzo 71, 41124 Modena, Italy.
Unit of Dentistry and Oral-Maxillofacial Surgery, Periodontology Section, Department of Surgery, Medicine, Dentistry and Morphological Sciences with Transplant Surgery, Oncology and Regenerative Medicine Relevance, University-Hospital of Modena and Reggio Emilia, Via del Pozzo 71, 41124 Modena, Italy.
Materials (Basel). 2022 Mar 15;15(6):2161. doi: 10.3390/ma15062161.
Periodontal disease is a widespread disorder comprising gingivitis, a mild early gum inflammation, and periodontitis, a more severe multifactorial inflammatory disease that, if left untreated, can lead to the gradual destruction of the tooth-supporting apparatus. To date, effective etiopathogenetic models fully explaining the clinical features of periodontal disease are not available. Obviously, a better understanding of periodontal disease could facilitate its diagnosis and improve its treatment. The purpose of this study was to employ a proteomic approach to analyze the gingival crevicular fluid (GCF) of patients with severe periodontitis, in search of potential biomarkers. GCF samples, collected from both periodontally healthy sites (H-GCF) and the periodontal pocket (D-GCF), were subjected to a comparison analysis using sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). A total of 26 significantly different proteins, 14 up-regulated and 12 down-regulated in D-GCF vs. H-GCF, were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The main expressed proteins were inflammatory molecules, immune responders, and host enzymes. Most of these proteins were functionally connected using the STRING analysis database. Once validated in a large scale-study, these proteins could represent a cluster of promising biomarkers capable of making a valuable contribution for a better assessment of periodontitis.
牙周病是一种广泛存在的疾病，包括牙龈炎（一种轻度的早期牙龈炎症）和牙周炎（一种更严重的多因素炎症性疾病，如果不治疗，会导致牙齿支持组织逐渐破坏）。迄今为止，尚无能够充分解释牙周病临床特征的有效病因发病模型。显然，更好地了解牙周病有助于其诊断并改善治疗。本研究的目的是采用蛋白质组学方法分析重度牙周炎患者的龈沟液（GCF），以寻找潜在的生物标志物。从牙周健康部位（H-GCF）和牙周袋（D-GCF）收集的GCF样本，使用十二烷基硫酸钠-聚丙烯酰胺凝胶电泳（SDS-PAGE）进行比较分析。通过液相色谱-串联质谱（LC-MS/MS）鉴定出总共26种在D-GCF与H-GCF中有显著差异的蛋白质，其中14种上调，12种下调。主要表达的蛋白质是炎症分子、免疫应答分子和宿主酶。使用STRING分析数据库对这些蛋白质中的大多数进行了功能关联分析。一旦在大规模研究中得到验证，这些蛋白质可能代表一组有前景的生物标志物，能够为更好地评估牙周炎做出有价值的贡献。
