Abstract：
OBJECTIVE: To describe the microbiological composition of subgingival dental plaque and molecular profile of gingival crevicular fluid (GCF) of periodontal furcation-involved defects.
METHODS: Fifty-seven participants with periodontitis contributed with a degree II-III furcation involvement (FI), a non-furcation (NF) periodontal defect and a periodontally healthy site (HS). Subgingival plaque was analysed by sequencing the V3-V4 region of the 16S rRNA gene, and a multiplex bead immunoassay was carried out to estimate the GCF levels of 18 GCF biomarkers. Aiming to explore inherent patterns and the intrinsic structure of data, an AI-clustering method was also applied.
RESULTS: In total, 171 subgingival plaque and 84 GCF samples were analysed. Four microbiome clusters were identified and associated with FI, NF and HS. A reduced aerobic microbiota (p = .01) was detected in FI compared with NF; IL-6, MMP-3, MMP-8, BMP-2, SOST, EGF and TIMP-1 levels were increased in the GCF of FI compared with NF.
CONCLUSIONS: This is the first study to profile periodontal furcation defects from a microbiological and inflammatory standpoint using conventional and AI-based analyses. A reduced aerobic microbial biofilm and an increase of several inflammatory, connective tissue degradation and repair markers were detected compared with other periodontal defects.
METHODS: Fifty-seven participants with periodontitis contributed with a degree II-III furcation involvement (FI), a non-furcation (NF) periodontal defect and a periodontally healthy site (HS). Subgingival plaque was analysed by sequencing the V3-V4 region of the 16S rRNA gene, and a multiplex bead immunoassay was carried out to estimate the GCF levels of 18 GCF biomarkers. Aiming to explore inherent patterns and the intrinsic structure of data, an AI-clustering method was also applied.
RESULTS: In total, 171 subgingival plaque and 84 GCF samples were analysed. Four microbiome clusters were identified and associated with FI, NF and HS. A reduced aerobic microbiota (p = .01) was detected in FI compared with NF; IL-6, MMP-3, MMP-8, BMP-2, SOST, EGF and TIMP-1 levels were increased in the GCF of FI compared with NF.
CONCLUSIONS: This is the first study to profile periodontal furcation defects from a microbiological and inflammatory standpoint using conventional and AI-based analyses. A reduced aerobic microbial biofilm and an increase of several inflammatory, connective tissue degradation and repair markers were detected compared with other periodontal defects.
摘要：
目的：描述牙龈下牙菌斑的微生物学组成和牙周分叉缺损的龈沟液（GCF）的分子谱。
方法：57名牙周炎患者参与II-III度分叉（FI），非分叉（NF）牙周缺损和牙周健康部位（HS）。通过对16SrRNA基因的V3-V4区域进行测序来分析龈下菌斑，并进行了多重珠免疫测定以估计18个GCF生物标志物的GCF水平。旨在探索数据的内在模式和内在结构，还应用了人工智能聚类方法。
结果：总计，分析了171个龈下菌斑和84个GCF样品。确定了四个微生物群簇，并与FI相关，NF和HS。与NF相比，FI中检测到需氧微生物群减少（p=0.01）；IL-6，MMP-3，MMP-8，BMP-2，SOST，与NF相比，FI的GCF中EGF和TIMP-1水平升高。
结论：这是第一项从微生物学和炎症角度使用常规和基于AI的分析来描述牙周分叉缺陷的研究。需氧微生物生物膜的减少和几种炎症的增加，与其他牙周缺损相比，检测到结缔组织降解和修复标志物。
方法：57名牙周炎患者参与II-III度分叉（FI），非分叉（NF）牙周缺损和牙周健康部位（HS）。通过对16SrRNA基因的V3-V4区域进行测序来分析龈下菌斑，并进行了多重珠免疫测定以估计18个GCF生物标志物的GCF水平。旨在探索数据的内在模式和内在结构，还应用了人工智能聚类方法。
结果：总计，分析了171个龈下菌斑和84个GCF样品。确定了四个微生物群簇，并与FI相关，NF和HS。与NF相比，FI中检测到需氧微生物群减少（p=0.01）；IL-6，MMP-3，MMP-8，BMP-2，SOST，与NF相比，FI的GCF中EGF和TIMP-1水平升高。
结论：这是第一项从微生物学和炎症角度使用常规和基于AI的分析来描述牙周分叉缺陷的研究。需氧微生物生物膜的减少和几种炎症的增加，与其他牙周缺损相比，检测到结缔组织降解和修复标志物。
