Using Microbiota Composition To Predict Tooth Decay In Children

Tracking oral microbiota in young in children could help predict and prevent dental cavities.

AsianScientist (Sep. 17, 2015) – Scientists have developed a method to predict whether young children go on to develop tooth decay based on their profile of microbiota. This research has been published in Cell Host & Microbe.

Dental caries is a worldwide health concern, affecting humans of all ages and generating enormous social costs. Early childhood caries (ECC), the most common oral disease in children, affects approximately 60 to 90 percent of children worldwide.

ECC leads to sustained demineralization of enamel and dentin, and the infection can spread from the affected tooth to surrounding soft tissues, resulting in swelling and inflammation in highly advanced cases. Once started, the damage to teeth is irreversible, with patients continuing to suffer from a higher risk of new lesions and even tooth loss over their entire lifespan. Therefore, preventive intervention to control ECC is of particular clinical significance.

Microbiota are present everywhere in the biosphere. Can we employ them as indigenous ‘biosensors’ to diagnose and predict the health of their ecosystems? A joint research team from the Single-Cell Center, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences and the Guanghua School and Hospital of Stomatology, Sun Yat-sen University has developed a microbiota-based approach for predicting early childhood caries.

Graduate student Teng Fei and her colleagues simultaneously tracked microbiota development in plaque and saliva for two years in 50 four-year-old preschoolers who either stayed healthy, transitioned into cariogenesis or experienced caries exacerbation. They found that the onset of caries delayed the development of microbiota that otherwise are correlated with aging in healthy children.

By distinguishing between aging- and disease-associated taxa and exploiting the distinct microbiota dynamics between onset and progression, they proposed a novel microbial indicators of caries (MiC) model that can predict future ECC onset for samples clinically perceived as healthy with 81 percent accuracy.

Compared with traditional caries risk assessment methods such as oral bacteria count, chemical characteristics of saliva, baseline caries status, as well as personal questionnaires (e.g., oral hygiene), MiC is objective and independent of the human examiner’s visual observation, individual judgment and microbial culture, leading to satisfactory reproducibility and comparability among examiners.

Furthermore, the study revealed that, in healthy children, oral microbial composition is age-dependent. That is, the ‘oral microbiota age’ of healthy children was consistent with their corresponding chronological age. However, in children with caries onset and progression, their ‘oral microbiota age’ was derailed from their corresponding chronological age. ‘Oral microbiota age’ can thus serve as a population-wide early alarm system for predicting ECC risk.

Human health and nutrition are closely linked to their microbial symbionts, collectively called the ‘second human genome’. Diagnosis and prediction of chronic disease based on human microbiota has been drawing significant attention, yet only a few cases have been published so far. Therefore, the findings in this study may be of reference value to those studying the microbiota inhabiting other human body sites and microbiota in the ocean, soil and air.

The article can be found at: Teng et al. (2015) Prediction of Early Childhood Caries via Spatial-Temporal Variations of Oral Microbiota.


Source: Chinese Academy of Sciences.
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