Background Although lactobacilli are frequently detected in children with early childhood caries (ECC), the roles of specific lactobacilli species remain unclear. Streptococcus mutans, a well-established cariogenic species, was included as a reference organism. Limosilactobacillus fermentum, Ligilactobacillus salivarius, Lactobacillus acidophilus, and Lacticaseibacillus rhamnosus were selected in the study aiming to investigate the prospective associations between lactobacilli species and caries increment based on machine learning approaches. Methods A prospective cohort of 282 children aged 3–4 years was established in Shanghai, China. Participants received clinical examinations at baseline and 1-year follow-up. Baseline saliva samples were collected. The detection and quantification of the targeted species in salivary samples were performed by quantitative real-time PCR. Logistic regression and machine-learning analyses were conducted to evaluate associations with caries increment. Results L. fermentum, L. salivarius, L. rhamnosus, and S. mutans were positively correlated to caries increment. L. fermentum was highly detectable (82.6%) in the saliva and significantly correlated with S. mutans. Furthermore, positive correlations existed between L. fermentum, and L. acidophilus, L. rhamnosus and L. salivarius. The ratio of L. salivarius to S. mutans was significantly correlated to caries increment. In the logistic regression model, caries experience and high levels of caries activity test were significantly associated with caries increment, whereas the associations between salivary bacterial abundance and caries increment were no longer statistically significant after adjustment. SHAP analysis based on light gradient boosting machine identified S. mutans and L. fermentum as the top important bacterial features contributing to the prediction of caries increment. Conclusions Salivary detection and abundance of specific lactobacilli species were prospectively associated with caries increment in preschool children. Among the species examined, L. fermentum may contribute to the overall microbial predictive profile in machine-learning models rather than acting as an independent predictor of caries increment. The observed association involving L. salivarius and S. mutans suggests a potential ecological relationship that warrants further investigation.

The role of salivary lactobacilli in early childhood caries increment

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2026年7月28日

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Yu Zhang,
Yating Xu,
Liangzhi Tu,
Minyi Xu,
Jingyu Zhan,
Xiping Feng,
Xi Chen

摘要

Background

Although lactobacilli are frequently detected in children with early childhood caries (ECC), the roles of specific lactobacilli species remain unclear. Streptococcus mutans, a well-established cariogenic species, was included as a reference organism. Limosilactobacillus fermentum, Ligilactobacillus salivarius, Lactobacillus acidophilus, and Lacticaseibacillus rhamnosus were selected in the study aiming to investigate the prospective associations between lactobacilli species and caries increment based on machine learning approaches.

Methods

A prospective cohort of 282 children aged 3–4 years was established in Shanghai, China. Participants received clinical examinations at baseline and 1-year follow-up. Baseline saliva samples were collected. The detection and quantification of the targeted species in salivary samples were performed by quantitative real-time PCR. Logistic regression and machine-learning analyses were conducted to evaluate associations with caries increment.

Results

L. fermentum, L. salivarius, L. rhamnosus, and S. mutans were positively correlated to caries increment. L. fermentum was highly detectable (82.6%) in the saliva and significantly correlated with S. mutans. Furthermore, positive correlations existed between L. fermentum, and L. acidophilus, L. rhamnosus and L. salivarius. The ratio of L. salivarius to S. mutans was significantly correlated to caries increment. In the logistic regression model, caries experience and high levels of caries activity test were significantly associated with caries increment, whereas the associations between salivary bacterial abundance and caries increment were no longer statistically significant after adjustment. SHAP analysis based on light gradient boosting machine identified S. mutans and L. fermentum as the top important bacterial features contributing to the prediction of caries increment.

Conclusions

Salivary detection and abundance of specific lactobacilli species were prospectively associated with caries increment in preschool children. Among the species examined, L. fermentum may contribute to the overall microbial predictive profile in machine-learning models rather than acting as an independent predictor of caries increment. The observed association involving L. salivarius and S. mutans suggests a potential ecological relationship that warrants further investigation.