Prediction of Early Childhood Caries via Spatial-Temporal Variations of Oral Microbiota

Abstract

Microbiota-based prediction of chronic infections is promising yet not well established. Early childhood caries (ECC) is the most common infection in children. Here we simultaneously tracked microbiota development at plaque and saliva in 50 4-year-old preschoolers for 2 years; children either stayed healthy, transitioned into cariogenesis, or experienced caries exacerbation. Caries onset delayed microbiota development, which is otherwise correlated with aging in healthy children. Both plaque and saliva microbiota are more correlated with changes in ECC severity (dmfs) during onset than progression. By distinguishing between aging- and disease-associated taxa and exploiting the distinct microbiota dynamics between onset and progression, we developed a model, Microbial Indicators of Caries, to diagnose ECC from healthy samples with 70% accuracy and predict, with 81% accuracy, future ECC onsets for samples clinically perceived as healthy. Thus, caries onset in apparently healthy teeth can be predicted using microbiota, when appropriately de-trended for age.