Altered gut microbiota is associated with autism spectrum disorders (ASD), a group of complex, fast growing but difficult-to-diagnose neurodevelopmental disorders worldwide. However, the role of the oral microbiota in ASD remains unexplored. Via high-throughput sequencing of 111 oral samples in 32 children with ASD and 27 healthy controls, we demonstrated that the salivary and dental microbiota of ASD patients were highly distinct from those of healthy individuals. Lower bacterial diversity was observed in ASD children compared to controls, especially in dental samples. Also, principal coordinate analysis revealed divergences between ASD patients and controls. Moreover, pathogens such as Haemophilus in saliva and Streptococcus in plaques showed significantly higher abundance in ASD patients, whereas commensals such as Prevotella, Selenomonas, Actinomyces, Porphyromonas, and Fusobacterium were reduced. Specifically, an overt depletion of Prevotellaceae co-occurrence network in ASD patients was obtained in dental plaques. The distinguishable bacteria were also correlated with clinical indices, reflecting disease severity and the oral health status (i.e. dental caries). Finally, diagnostic models based on key microbes were constructed, with 96.3% accuracy in saliva. Taken together, this study characterized the habitat-specific profile of the oral microbiota in ASD patients, which might help develop novel strategies for the diagnosis of ASD.

Objectives: To assess and compare the oral health status of children with and without autism spectrum disorders (ASD) in China.Methods: This study recruited 144 children with ASD and 228 unrelated children with typical development (TD) aged 3-16 years from China. Data were collected using parentreported questionnaires. Oral problems (oral symptoms and habits), oral health measures (oral hygiene practice and dental care experience), and the impact on the child's quality of life (based on a modified version of the Parental-Caregiver Perception Questionnaire) were assessed and compared between the two groups.Results: Children with ASD had worse oral health status than children with TD. Oral symptoms were more prevalent in the ASD group, especially halitosis (p < 0.001), food impaction (p < 0.001), and oral lesions (p < 0.001), than the TD group. The rate of damaging oral habits, including mouth breathing (p < 0.001) and object biting (p < 0.05), was also high in the ASD group. Compared with the TD group, more children with ASD did not brush their teeth independently and frequently (p < 0.001), had difficulty accessing dental care (p < 0.01), and reported unpleasant dental experiences (p < 0.001). The presence of ASD was associated with decreased oral health-related quality of life (p < 0.001) in these children and their families. Conclusion:Oral problems such as halitosis and bad oral habits are more prevalent among children with ASD. These children also lack oral hygiene practice and dental visits. This situation negatively impacts their quality of life, and must be brought to the attention of their treating dentists.

Objectives: Autism spectrum disorders (ASD) are neurodevelopmental disorders with changes in the gut and oral microbiota. Based on the intimate relationship between the oral microbiota and oral mucosal immunity, this study aimed to investigate changes in salivary immunoglobulin A (IgA) level in ASD and the underlying mechanism for any such changes.Methods: We recruited 36 children diagnosed with ASD and 35 normally developing children and measured their salivary IgA content using enzyme-linked immunosorbent assay (ELISA). The valproate (VPA) -treated ASD mouse model was established by prenatal exposure to valproate and mouse salivary IgA content was also quantified by ELISA. The submandibular glands of VPA and control mice were isolated and analyzed using qRT-PCR, immunofluorescence staining, and flow cytometry. ASD-related Streptococci were co-incubated with the human salivary gland (HSG) cell line, and western blotting was used to detect the levels of relevant proteins.Results: We found that salivary IgA content was significantly decreased in patients with ASD and had a significant ASD diagnostic value. The salivary IgA content also decreased in VPA mice and was significantly correlated with autistic-like behaviors among them. The mRNA and protein levels of the polymeric immunoglobulin receptor (Pigr) were downregulated in the submandibular glands of VPA mice and the Pigr mRNA level was positively correlated with mouse salivary IgA content. HSG cells treated with ASD-related Streptococci had reduced PIGR protein level.Conclusion: Therefore, protective IgA levels were reduced in the saliva of individuals with ASD, which correlated with the bacteria-induced downregulation of Pigr in salivary glands. This study suggests a new direction for ASD diagnosis and prevention of oral diseases in ASD cohorts and provides evidence for the ASD mucosal immunophenotype in the oral cavity.

The characteristics of the oral microbiota may depend on oral health, age, diet, and geography, but the influence of the geographic setting on the oral microbiota has received limited attention. The characteristics of oral microbiota have been reported to differ between urban and rural environments. In order to minimize the influence of genetic background, we recruited 54 volunteers from the same ethnic group, living in urban and rural areas of Gansu Province, China. We collected dental plaque samples and divided them into four groups according to the participant’s area of residence and dental caries status. We sequenced the 16S rRNA of these samples using the Pacific Biosciences sequencing platform and analyzed the correlation between the geographic area and the characteristics of the oral microbiota. Analysis of the alpha and beta diversity revealed that there were significant differences in diversity and composition of dental plaque microflora among the four groups. Cluster analysis revealed that geographic area played an important role in determining the oral microbiota. Network analysis of oral microorganisms showed that geographic differences had major influence on the composition characteristics and internal structure of oral microorganisms. We found that some dominant strains which may play a key role in maintaining oral health, such as Streptococcus oralis, Capnocytophaga sputigena, Porphyromonas catoniae, Corynebacterium matruchotii, Haemophilus parainfluenzae, and Prevotella loescheii, were less affected by the geographic setting. These results provide a deeper understanding of factors influencing the composition of the oral microbiota and could contribute to early diagnosis and effective prevention of dental caries in different settings.

The oral microbiota has been implicated in various neurologic conditions, including autism spectrum disorder (ASD), a category of neurodevelopmental disorders defined by core behavioral impairments. Recent data propose the etiopathogenetic role of intestinal microbiota in ASD. The aim of the present study was to elucidate whether the oral microbiota contributes to the pathogenesis of ASD. On the basis of microbial changes detected in the oral cavity of children with ASD, we transferred oral microbiota from donors with ASD and typical development (TD) into an antibiotic-mediated microbiota-depleted mouse model and found that the ASD microbiota is sufficient to induce ASD-like behaviors, such as impaired social behavior. Mice receiving oral microbiota from the ASD donor showed significantly different microbiota structures in their oral cavity and intestinal tract as compared with those receiving TD microbiota and those not receiving any bacterium. The prefrontal cortex of ASD microbiota recipient mice displayed an alternative transcriptional profile with significant upregulation of serotonin-related gene expression, neuroactive ligand-receptor interaction, and TGF-β signaling pathway relative to that in TD microbiota recipient mice. The expression of serotonin-related genes was significantly increased in ASD microbiota recipient mice and was associated with selective autistic behaviors and changes in abundance of specific oral microbiota, including species of Bacteroidetes [G-7], Porphyromonas, and Tannerella. Machine learning based on the causal inference method confirmed a contributing role of Porphyromonas sp. HMT 930 in ASD. Taken together, the oral microbiota of children with ASD can lead to ASD-like behaviors, differences in microbial community structures, and altered neurosignaling activities in recipient mice; this highlights the mouth-microbial-brain connections in the development of neuropathology and provides a novel strategy to fully understand the etiologic mechanism of ASD.