The Predictive Potentiality of Salivary Microbiome for the Recurrence of Early Childhood Caries

Abstract

The aim of this study was to investigate the variation of the salivary microbiota in the recurrence of early childhood caries (ECC), and to explore and verify the potential microbial indicators of ECC recurrence. Saliva samples from kindergarten children were tracked every 6 months for 1 year. Finally, in total 28 children and 84 samples were placed on the analysis phase: 7 children with ECC recurrence made up the ECC-recurrence (ER) group, 6 children without ECC recurrence constituted the non-ECC-recurrence (NER) group, and 15 children who kept ECC-free were set as the ECC-free (EF) group. DNA amplicons of the V3-V4 hypervariable region of the bacterial 16S rDNA were generated and sequencing was performed using Illumina MiSeq PE250 platform. No statistically significant differences of the Shannon indices were found in both cross-sectional and longitudinal comparisons. Furthermore, both principal coordinates analysis (PCoA) and heatmap plots demonstrated that the salivary microbial community structure might have potentiality to predict ECC recurrence at an early phase. The relative abundance of Fusobacterium, Prevotella, Leptotrichia, and Capnocytophaga differed significantly between the ER and NER groups at baseline. The values of area under the curve (AUC) of the four genera and their combined synthesis in the prediction for ECC recurrence were 0.857, 0.833, 0.786, 0.833, and 0.952, respectively. The relative abundance of Fusobacterium, Prevotella, Leptotrichia, and Capnocytophaga and their combination showed satisfactory accuracy in the prediction for ECC recurrence, indicating that salivary microbiome had predictive potentiality for recurrence of this disease. These findings might facilitate more effective strategy to be taken in the management of the recurrence of ECC.

Keywords: early childhood caries; predictive potentiality; recurrence; salivary microbiome; sequencing analysis.

Figure 1

(A) The comparison of Chao1 index among three groups within same time point. *P < 0.05. (B) The comparison of Chao1 index among three time points within same group. *P < 0.05. (C) The comparison of Shannon index among three groups within same time point. (D) The comparison of Shannon index among three time points within same group.

Figure 2

(A) Principal coordinates analysis (PCoA) based on weighted UniFrac distance exhibiting the variation of microbiota community structure from T1 to T2 in the three groups. Each symbol represents one sample: red for T1, blue for T2. (B) PCoA based on weighted UniFrac distance exhibiting the variation of community structure from T1 to T3 in the three groups. Each symbol represents one sample: red for T1, blue for T3. (C) PCoA based on weighted UniFrac distance exhibiting the variation of community structure from T2 to T3 in the three groups. Each symbol represents one sample: red for T2, blue for T3.

Figure 3

(A) Principal coordinates analysis (PCoA) based on weighted UniFrac distance of community structure at baseline. Each symbol represents one sample: red for the ER group (n = 7); blue for the NER group (n = 6); green for the EF group (n = 15). (B) Correlation-Heatmap based on weighted UniFrac distance of the three groups at baseline. Trees were clustered based on weighted UniFrac distance: green for the ER group (n = 7); blue for the NER group (n = 6); tangerine for the EF group (n = 15).

Figure 4

Comparison of relative abundance of bacteria by genus between the ER and NER groups at baseline. *P < 0.05.

Figure 5

Receiver-operating characteristic (ROC) analysis of ECC recurrence using detected genera assessed by the area under the curve (AUC).