Tongue-coating microbiota as a predictive biomarker of washed microbiota transplantation efficacy in pediatric autism: integration with clinical features.

舌苔微生物群作为预测儿童自闭症患者舌苔微生物群移植疗效的生物标志物:与临床特征的整合

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作者:Zhong Hao-Jie, Pan Zhao-Yu, Wei Yao-Fei, Yu Qian, Wu Lei, Wei Hong, He Xing-Xiang
BACKGROUND: Alterations in both oral and gut microbiota have been identified in children with autism spectrum disorder (ASD), but the interaction between these microbiota and their potential to predict outcomes of fecal microbiota transplantation (FMT) remain poorly understood. METHODS: This study investigated the structure and function of the tongue-coating microbiota in children with ASD and explored its correlation with ASD symptoms and gut microbiota. Germ-free ASD mice, colonized with healthy gut microbiota, and children with ASD treated with washed microbiota transplantation (WMT) were assessed for changes in autism symptoms and microbiota composition. Predictive models were also developed based on pre-treatment tongue-coating microbiota and clinical features to forecast WMT outcomes. RESULTS: Significant alterations were detected in the tongue-coating microbiota of children with ASD, with several bacterial species showing associations with ASD symptoms and gut microbiota composition. Following WMT, both mice and children exhibited substantial improvements in autism-related behaviors, alongside marked shifts in their gut and tongue-coating microbiota. A significant decrease in Haemophilus in the tongue-coating microbiota, which positively correlated with ASD severity, was observed. Additionally, a reduction in chemoheterotrophic and fermentation functions in the tongue-coating microbiota was identified. Predictive models utilizing pre-treatment tongue-coating microbiota and clinical data demonstrated comparable accuracy to those based on gut microbiota for forecasting WMT outcomes. CONCLUSIONS: These findings highlight a significant interaction between gut and tongue-coating microbiota in ASD, which may play a pivotal role in treatment outcomes. Predictive models integrating pre-treatment microbiota and clinical features could improve precision treatment strategies for children with ASD undergoing WMT.

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