Geographic Variation Did Not Affect the Predictive Power of Salivary Microbiota for Caries in Children With Mixed Dentition

地理差异并不影响唾液微生物群对混合牙列期儿童龋齿的预测能力

阅读:1

Abstract

Dental caries is one of the most prevalent chronic oral diseases, affecting approximately half of children worldwide. The microbial composition of dental caries may depend on age, oral health, diet, and geography, yet the effect of geography on these microbiomes is largely underexplored. Here, we profiled and compared saliva microbiota from 130 individuals aged 6 to 8 years old, representing both healthy children (H group) and children with caries-affected (C group) from two geographical regions of China: a northern city (Qingdao group) and a southern city (Guangzhou group). First, the saliva microbiota exhibited profound differences in diversity and composition between the C and H groups. The caries microbiota featured a lower alpha diversity and more variable community structure than the healthy microbiota. Furthermore, the relative abundance of several genera (e.g., Lactobacillus, Gemella, Cryptobacterium and Mitsuokella) was significantly higher in the C group than in the H group (p<0.05). Next, geography dominated over disease status in shaping salivary microbiota, and a wide array of salivary bacteria was highly predictive of the individuals' city of origin. Finally, we built a universal diagnostic model based on 14 bacterial species, which can diagnose caries with 87% (AUC=86.00%) and 85% (AUC=91.02%) accuracy within each city and 83% accuracy across cities (AUC=92.17%). Although the detection rate of Streptococcus mutans in populations is not very high, it could be regarded as a single biomarker to diagnose caries with decent accuracy. These findings demonstrated that despite the large effect size of geography, a universal model based on salivary microbiota has the potential to diagnose caries across the Chinese child population.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。