Department of Orthodontics, State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China.
Department of Temporomandibular Joint, State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China.
J Proteomics. 2022 Aug 30;266:104647. doi: 10.1016/j.jprot.2022.104647. Epub 2022 Jun 30.
To identify gingival recession-related biomarkers in orthodontic patients, we compared the proteome of gingival crevicular fluids (GCF) from healthy gingiva without orthodontic treatment (GH), healthy gingiva undergoing orthodontic treatment (OGH), and recessed gingiva undergoing orthodontic treatment (OGR).
GCF samples were obtained from the anterior teeth of 15 volunteers (n = 5/group). Quantitative proteomic analysis was performed using DIA-based liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to annotate differentially expressed proteins (DEPs). Receiver-operating characteristic (ROC) analysis was performed to detect and filter biomarker candidates, while Protein-Protein Interaction (PPI) Networks were utilized to determine the interactions between these DEPs.
A total of 253, 238, and 101 DEPs were found in OGR vs. OGH, OGR vs. GH, and OGH vs. GH groups, respectively. Based on the Venn diagram of three groups, 128 DEPs in OGR vs. OGH group were identified as specific proteins associated with progressive gingival recession (GR) during orthodontic treatment. Molecular function analysis showed that 128 DEPs were enriched in "molecular binding", including antigen binding, RNA binding, double-stranded RNA binding, cadherin binding involved in cell-cell adhesion, vinculin binding, S100 protein binding, and Ral GTPase binding. The majority of these DEPs were also involved in cytoskeletal regulation. In addition, biological process analysis showed an enrichment in translation, while cellular component analysis indicated that 128 DEPs were related to extracellular exosome. Furthermore, Ribosome and Phagosome were the top two terms in KEGG analysis. The results of ROC analysis demonstrated that 26 proteins could be potential biomarker candidates for GR. PPI networks analysis predicted that IQGAP1, ACTN1, TLN1, VASP, FN1, FERMT3, MYO1C, RALA, RPL35, SEC61G, KPNB1, and NPM1 could be involved in the development of GR via cytoskeletal regulation.
In summary, we identified several GCF proteins associated with GR after orthodontic treatment. These findings could contribute to the prevention of GR in susceptible patients before the initiation of orthodontic treatment.
Orthodontic patients with GR often report esthetic defects or root hypersensitivity during orthodontic treatment, especially at the anterior teeth site. GCF, rich in protein, is an easily accessible source of potential biomarkers for the diagnosis of periodontal diseases; however, little is known about the changes in GCF proteome associated with GR in orthodontic patients. In this study we firstly used DIA-based LC-MS/MS to evaluate the proteome and to identify the biomarker candidates for GR in orthodontic patients. These findings will improve our understanding of GR during orthodontic treatment, and could contribute to an earlier diagnosis, or even prevention, of GR in susceptible populations before orthodontic treatment.
为了鉴定正畸患者的牙龈退缩相关生物标志物，我们比较了来自未经正畸治疗的健康牙龈（GH）、正在接受正畸治疗的健康牙龈（OGH）和正在接受正畸治疗的退缩牙龈（OGR）的龈沟液（GCF）的蛋白质组。
从 15 名志愿者的前牙中获得 GCF 样本（n=5/组）。使用基于 DIA 的液相色谱-串联质谱法（LC-MS/MS）进行定量蛋白质组学分析。使用基因本体论（GO）术语和京都基因与基因组百科全书（KEGG）途径注释差异表达蛋白（DEPs）。使用受试者工作特征（ROC）分析来检测和筛选生物标志物候选物，而蛋白质-蛋白质相互作用（PPI）网络则用于确定这些 DEPs 之间的相互作用。
OGR 与 OGH、OGR 与 GH 和 OGH 与 GH 组分别发现了 253、238 和 101 个 DEP。根据三组的维恩图，OGR 与 OGH 组中的 128 个 DEP 被确定为与正畸治疗中进行性牙龈退缩（GR）相关的特定蛋白。分子功能分析表明，128 个 DEP 富集于“分子结合”，包括抗原结合、RNA 结合、双链 RNA 结合、涉及细胞间粘附的钙粘蛋白结合、 vinculin 结合、S100 蛋白结合和 Ral GTPase 结合。这些 DEP 中的大多数还参与细胞骨架调节。此外，生物过程分析显示翻译丰富，而细胞成分分析表明，128 个 DEP 与细胞外 exosome 有关。此外，核糖体和吞噬体是 KEGG 分析中的前两个术语。ROC 分析的结果表明，26 种蛋白质可能是 GR 的潜在生物标志物候选物。PPI 网络分析预测，IQGAP1、ACTN1、TLN1、VASP、FN1、FERMT3、MYO1C、RALA、RPL35、SEC61G、KPNB1 和 NPM1 可能通过细胞骨架调节参与 GR 的发展。
总之，我们鉴定了一些与正畸治疗后 GR 相关的 GCF 蛋白。这些发现可能有助于在正畸治疗开始前预防易感患者的 GR。
患有 GR 的正畸患者在正畸治疗期间经常报告美观缺陷或根过敏，尤其是在前牙部位。富含蛋白质的 GCF 是牙周病诊断的潜在生物标志物的易得来源；然而，人们对正畸患者与 GR 相关的 GCF 蛋白质组的变化知之甚少。在这项研究中，我们首次使用基于 DIA 的 LC-MS/MS 评估蛋白质组并鉴定正畸患者 GR 的生物标志物候选物。这些发现将提高我们对正畸治疗期间 GR 的认识，并有助于在正畸治疗前更早地诊断甚至预防易感人群的 GR。
