Sex-Based Diverse Plaque Microbiota in Children with Severe Caries

Severe early childhood caries (S-ECC) is a multifactorial disease that can lead to suffering and reduced oral health–related quality of life in young children. The bacterial and fungal composition of dental plaque and how children’s sex is associated with S-ECC are largely unknown. In this study, V4-16S rRNA and ITS1 rRNA gene amplicon sequencing was used to compare the plaque bacteriome and mycobiome of children <72 mo of age: 40 with S-ECC (15 males, 25 females) and 40 caries-free (19 males, 21 females). Health- and nutrition-related questionnaire data were also investigated. This study aimed to analyze potential sex-based differences in the supragingival plaque microbiota of young children with S-ECC and those caries-free. Behavioral and nutritional habit differences were observed between children with S-ECC and those caries-free and between male and female children. Overall, higher levels of Veillonella dispar, Streptococcus mutans, and other bacterial species were found in the S-ECC group as compared with caries-free controls ( P < 0.05). A significant difference in the abundance of Neisseria was observed between males and females with S-ECC ( P < .05). Fungal taxonomic analysis showed significantly higher levels of Candida dubliniensis in the plaque of children with S-ECC as compared with those caries-free ( P < 0.05), but no differences were observed with Candida albicans ( P > 0.05). Significant differences in the relative abundance of Mycosphaerella, Cyberlindnera, and Trichosporon fungal species were also observed between the caries-free and S-ECC groups ( P < 0.05). Machine learning analysis revealed the most important bacterial and fungal species for classifying S-ECC versus caries-free. Different patterns of crosstalk between microbial species were observed between male and female children. Our work demonstrates that plaque microbiota and sex may be important determinants for S-ECC and could be factors to consider for inclusion in caries risk assessment tools.