Department of Stomatology, Wuxi Children's Hospital, 214023 Wuxi, Jiangsu, China.
State Key Laboratory of Food Science and Technology, Jiangnan University, 214122 Wuxi, Jiangsu, China.
J Clin Pediatr Dent. 2023 Mar;47(2):58-67. doi: 10.22514/jocpd.2023.012. Epub 2023 Mar 3.
Early childhood caries (ECC) negatively affects children's growth due to its close relation to an imbalance of the oral microbiota. This study aimed to evaluate the distribution of the oral microbiota in children with ECC and healthy individuals.
The oral microbiota of 20 children with dental caries from both carious teeth (CC cohort) and healthy teeth (CH cohort), and the oral microbiota of 20 healthy control children (HH cohort) were subjected to 16S rDNA sequencing.
The results revealed significant differences between the microbial structure of the CC and CH cohorts of every child with ECC. The most common microbes were , , , and . Specifically, the CC cohort contained , , and , the CH cohort contained , and , and the HH cohort mainly contained , , and . Lastly, we established a random forest model consisting of 10 genera (, , ) which demonstrated promising clinical diagnostic ability (area under the curve (AUC) = 89.8%). These findings indicate that oral microbiota can potentially be used as therapeutic targets or diagnostic markers for the early prediction and prevention of caries in children.
由于儿童龋与口腔微生物失衡密切相关，早期儿童龋（ECC）会对儿童的生长发育产生负面影响。本研究旨在评估患有 ECC 的儿童与健康个体的口腔微生物群分布。
对 20 名患有龋齿的儿童（CC 队列）的龋齿牙齿和健康牙齿（CH 队列）以及 20 名健康对照儿童（HH 队列）的口腔微生物群进行 16S rDNA 测序。
结果表明，每个患有 ECC 的儿童的 CC 和 CH 队列的微生物结构之间存在显著差异。最常见的微生物是 、 、 、 。具体而言，CC 队列包含 、 、 ，CH 队列包含 、 、 ，HH 队列主要包含 、 、 。最后，我们建立了一个由 10 个属（、、）组成的随机森林模型，该模型具有有前途的临床诊断能力（曲线下面积（AUC）=89.8%）。这些发现表明，口腔微生物群可能可作为儿童龋早期预测和预防的治疗靶点或诊断标志物。
