Prediction of Early Childhood Caries via Spatial-Temporal Variations of Oral Microbiota.
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.
Department of Operative Dentistry and Endodontics, Guanghua School and Hospital of Stomatology, Sun Yat-sen University, Guangzhou, 510055, China; Single-Cell Center, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, 266101, China.
Fei
F
Teng
Department of Stomatology, Qingdao Municipal Hospital, Qingdao, Shandong, 266101 China.
Fang
F
Yang
Single-Cell Center, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, 266101, China.
Shi
S
Huang
Single-Cell Center, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, 266101, China.
Cunpei
C
Bo
Departments of Pediatrics and Computer Science & Engineering, University of California, San Diego, La Jolla, CA 92093, USA.
Zhenjiang Zech
ZZ
Xu
Departments of Pediatrics and Computer Science & Engineering, University of California, San Diego, La Jolla, CA 92093, USA.
Amnon
A
Amir
Departments of Pediatrics and Computer Science & Engineering, University of California, San Diego, La Jolla, CA 92093, USA.
Rob
R
Knight
Department of Operative Dentistry and Endodontics, Guanghua School and Hospital of Stomatology, Sun Yat-sen University, Guangzhou, 510055, China. Electronic address: lingjq@mail.sysu.edu.cn.
Junqi
J
Ling
Single-Cell Center, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, 266101, China. Electronic address: xujian@qibebt.ac.cn.
Jian
J
Xu
D002675:Child, Preschool; D004269:DNA, Bacterial / Q000737:chemistry / Q000235:genetics; D004275:DNA, Ribosomal / Q000737:chemistry / Q000235:genetics; D003731:Dental Caries / Q000175:diagnosis* / Q000382:microbiology*; D003773:Dental Plaque / Q000382:microbiology*; D006801:Humans; D064307:Microbiota; D015233:Models, Statistical; D008969:Molecular Sequence Data; D011379:Prognosis; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D012463:Saliva / Q000382:microbiology*; D017422:Sequence Analysis, DNA
D004269:DNA, Bacterial; D004275:DNA, Ribosomal; D012336:RNA, Ribosomal, 16S
early-childhood caries; microbial indicators of caries; microbiota; plaque; saliva