| Literature DB >> 26355216 |
Fei Teng1, Fang Yang2, Shi Huang3, Cunpei Bo3, Zhenjiang Zech Xu4, Amnon Amir4, Rob Knight4, Junqi Ling5, Jian Xu6.
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.Entities:
Keywords: early-childhood caries; microbial indicators of caries; microbiota; plaque; saliva
Mesh:
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Year: 2015 PMID: 26355216 DOI: 10.1016/j.chom.2015.08.005
Source DB: PubMed Journal: Cell Host Microbe ISSN: 1931-3128 Impact factor: 21.023