The use of next generation sequencing and bioinformatics has revealed the complexity and richness of the human oral microbiota. While some species are well known for their periodontal pathogenicity, the molecular‐based approaches for bacterial identification have raised awareness about new putative periodontal pathogens. Although they are found increased in case of periodontitis, there is currently a lack of data on their interrelationship with the periodontal measures. We processed the sequencing data of the subgingival microbiota of 75 patients with hemochromatosis and chronic periodontitis in order to characterize the well‐described and newly identified subgingival periodontal pathogens. We used correlation tests and statistical models to assess the association between the periodontal pathogens and mean pocket depth, and to determine the most relevant bacterial biomarkers of periodontitis severity. Based on correlation test results, nine taxa were selected and included in the statistical models. The multiple linear regression models adjusted for systemic and periodontal clinical variables showed that mean pocket depth was negatively associated with Aggregatibacter and Rothia, and positively associated with Porphyromonas. Furthermore, a bacterial ratio that was previously described as a signature of dysbiosis in periodontitis (%Porphyromonas+%Treponema+%Tannerella)/(%Rothia+%Corynebacterium) was the most significant predictor. In this specific population, we found that the best model in predicting the mean pocket depth was microbial dysbiosis using the dysbiosis ratio taxa formula. While further studies are needed to assess the validity of these results on the general population, such a dysbiosis ratio could be used in the future to monitor the subgingival microbiota.

中文翻译：

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慢性牙周炎的牙周病原体和临床参数。

下一代测序和生物信息学的使用揭示了人类口腔微生物群的复杂性和丰富性。尽管有些物种因其牙周致病性而闻名，但是基于分子的细菌鉴定方法已经提高了人们对新的牙周病原体的认识。尽管发现它们在牙周炎的情况下有所增加，但是目前缺乏有关它们与牙周措施之间相互关系的数据。我们处理了75例血色素沉着病和慢性牙周炎患者的龈下微生物群的测序数据，以表征经过充分描述和新发现的龈下牙周病原体。我们使用相关测试和统计模型来评估牙周病原体与平均囊袋深度之间的关联，并确定与牙周炎严重程度最相关的细菌生物标记。根据相关性测试结果，选择了九个分类单元并将其包括在统计模型中。调整了系统和牙周临床变量的多元线性回归模型显示，平均囊袋深度与聚合细菌和罗氏菌与卟啉菌正相关。此外，以前被描述为牙周炎中生物合成异常的细菌比率（％卟啉单胞菌+％梅毒螺旋体+％丹妮氏菌）/（％玫瑰果+％棒状杆菌）是最重要的预测因子。在这一特定人群中，我们发现，使用菌群比比率分类单元公式预测微生物平均菌群深度是预测平均囊袋深度的最佳模型。尽管需要进一步的研究来评估这些结果对普通人群的有效性，但这种营养不良率将来仍可用于监测龈下微生物群。