Geographic Variation Did Not Affect the Predictive Power of Salivary Microbiota for Caries in Children With Mixed Dentition - Li, Shanshan; Huang, Shi; Guo, Yi; Zhang, Ying; Zhang, Lijuan; Li, Fan; Tan, Kaixuan; Lu, Jie; Chen, Zhenggang; Guo, Qingyuan; Tang, Yongping; Teng, Fei; et al. (Frontiers in Cellular and Infection Microbiology, 2021)
Dental caries is one of the most prevalent chronic infectious diseases and affects approximately half of children worldwide. The microbial composition may depend on age, oral health, diet, and geography, yet the effect of geography on caries microbiomes is largely underexplored. Here, we profiled and compared saliva microbiota from 130 individuals aged from 6 to 8 years old, representing both healthy (H group) and severe caries (C group) children from two geographical regions of China: a northern city (Qingdao group) and a southern one (Guangzhou group). Firstly, saliva microbiota exhibited profound alterations in diversity and composition between the C and H groups. Caries microbiota featured a lower alpha diversity and more variable community structure than the healthy one. Furthermore, the relative abundance of several genera (e.g., Lactobacillus, Gemella, Cryptobacterium and Mitsuokella) was significantly higher in C group than in 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%). While Streptococcus mutans can be developed as a single proxy to diagnose caries with decent accuracy, its occurrence rate in populations was still low. 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 human populations.