Prediction of Future Caries in 1-Year-Old Children via the Salivary Microbiome

儿童早期龋齿 医学 微生物群 唾液 牙科 普雷沃菌属 队列 内科学 口腔健康 生物 生物信息学 遗传学 细菌
作者
Ratcha Raksakmanut,Panida Thanyasrisung,Sirima Sritangsirikul,Kemporn Kitsahawong,Ana Lucía Seminario,Waranuch Pitiphat,Oranart Matangkasombut
出处
期刊:Journal of Dental Research [SAGE Publishing]
卷期号:102 (6): 626-635 被引量:8
标识
DOI:10.1177/00220345231152802
摘要

Dental caries is the most common chronic disease in children that causes negative effects on their health, development, and well-being. Early preventive interventions are key to reduce early childhood caries prevalence. An efficient strategy is to provide risk-based targeted prevention; however, this requires an accurate caries risk predictor, which is still lacking for infants before caries onset. We aimed to develop a caries prediction model based on the salivary microbiome of caries-free 1-y-old children. Using a nested case-control design within a prospective cohort study, we selected 30 children based on their caries status at 1-y follow-up (at 2 y old): 10 children who remained caries-free, 10 who developed noncavitated caries, and 10 who developed cavitated caries. Saliva samples collected at baseline before caries onset were analyzed through 16S rRNA gene sequencing. The results of β diversity analysis showed a significant difference in salivary microbiome composition between children who remained caries-free and those who developed cavitated caries at 2 y old (analysis of similarities, Benjamini-Hochberg corrected, P = 0.042). The relative abundance of Prevotella nanceiensis, Leptotrichia sp. HMT 215, Prevotella melaninogenica, and Campylobacter concisus in children who remained caries-free was significantly higher than in children who developed cavitated caries (Wilcoxon rank sum test, P = 0.024, 0.040, 0.049, and 0.049, respectively). These taxa were also identified as biomarkers for children who remained caries-free (linear discriminant analysis effect size, linear discriminant analysis score = 3.69, 3.74, 3.53, and 3.46). A machine learning model based on these 4 species distinguished between 1-y-old children who did and did not develop cavitated caries at 2 y old, with an accuracy of 80%, sensitivity of 80%, and specificity of 80% (area under the curve, 0.8; 95% CI, 44.4 to 97.5). Our findings suggest that these salivary microbial biomarkers could assist in predicting future caries in caries-free 1-y-old children and, upon validation, are promising for development into an adjunctive tool for caries risk prediction for prevention and monitoring.
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