Periodontitis is a multifactorial disease that progresses via dynamic interaction between bacterial and host-derived genetic factors. The recent trend of omics analyses has discovered many periodontitis-related risk factors. However, how much the individual factor affects the pathogenesis of periodontitis is still unknown. This article aims to identify multiple key factors related to the pathogenesis of periodontitis and quantitatively predict the influence of each factor on alveolar bone resorption by omics analysis and mathematical modeling. First, we induced periodontitis in mice (n = 3 or 4 at each time point) by tooth ligation. Next, we assessed alveolar bone resorption by micro-computed tomography, alterations in the gene expression by RNA sequencing, and the microbiome of the gingivae by 16S ribosomal RNA sequencing during disease pathogenesis. Omics data analysis identified key players (bacteria and molecules) involved in the pathogenesis of periodontitis. We then constructed a mathematical model of the pathogenesis of periodontitis by employing ordinary differential equations that described the dynamic regulatory interplay between the key players and predicted the alveolar bone integrity as output. Finally, we estimated the model parameters using our dynamic experimental data and validated the model prediction of influence on alveolar bone resorption by in vivo experiments. The model predictions and experimental results revealed that monocyte recruitment induced by bacteria-mediated Toll-like receptor activation was the principal reaction regulating alveolar bone resorption in a periodontitis condition. On the other hand, osteoblast-mediated osteoclast differentiation had less impact on bone integrity in a periodontitis condition.

中文翻译：

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基于组学的数学模型揭示了实验性小鼠模型中牙周炎的发病机制。

牙周炎是一种多因素疾病，通过细菌和宿主遗传因素之间的动态相互作用而进展。组学分析的最新趋势发现了许多与牙周炎相关的危险因素。然而，个体因素对牙周炎发病机制的影响程度尚不清楚。本文旨在通过组学分析和数学模型，找出与牙周炎发病机制相关的多个关键因素，并定量预测各因素对牙槽骨吸收的影响。首先，我们通过牙齿结扎诱发小鼠牙周炎（每个时间点 n = 3 或 4）。接下来，我们通过微型计算机断层扫描评估牙槽骨吸收，通过 RNA 测序评估基因表达的变化，并通过 16S 核糖体 RNA 测序评估疾病发病机制中的牙龈微生物组。组学数据分析确定了参与牙周炎发病机制的关键参与者（细菌和分子）。然后，我们通过采用常微分方程构建了牙周炎发病机制的数学模型，该模型描述了关键参与者之间的动态调节相互作用，并预测牙槽骨完整性作为输出。最后，我们利用动态实验数据估计了模型参数，并通过体内实验验证了模型对牙槽骨吸收影响的预测。模型预测和实验结果表明，细菌介导的 Toll 样受体激活诱导的单核细胞募集是牙周炎条件下调节牙槽骨吸收的主要反应。另一方面，成骨细胞介导的破骨细胞分化对牙周炎条件下的骨完整性影响较小。