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Sci Rep. 2018 Sep 18;8(1):13981. doi: 10.1038/s41598-018-32219-2.

Analysis of gut microbiota profiles and microbe-disease associations in children with autism spectrum disorders in China.

Zhang M1,2, Ma W3, Zhang J4, He Y1,2, Wang J5,6.

Author information

1
Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing, 100191, China.
2
Autism Research Center, Peking University Health Science Center, Beijing, 100191, China.
3
Central Laboratory, Navy General Hospital of PLA, Beijing, 100191, China.
4
Department of pediatrics, Peking University Third Hospital, Beijing, 100191, China.
5
Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing, 100191, China. wjuan@hsc.pku.edu.cn.
6
Autism Research Center, Peking University Health Science Center, Beijing, 100191, China. wjuan@hsc.pku.edu.cn.

Abstract

Autism spectrum disorder (ASD) is a set of complex neurodevelopmental disorders. Recent studies reported that children with ASD have altered gut microbiota profiles compared with typical development (TD) children. However, few studies on gut bacteria of children with ASD have been conducted in China. Here, in order to elucidate changes of fecal microbiota in children with ASD, 16S rRNA sequencing was conducted and the 16S rRNA (V3-V4) gene tags were amplified. We investigated differences in fecal microbiota between 35 children with ASD and 6 TD children. At the phylum level, the fecal microbiota of ASD group indicated a significant increase of the Bacteroidetes/Firmicutes ratio. At the genus level, we found that the relative abundance of Sutterella, Odoribacter and Butyricimonas was much more abundant in the ASD group whereas the abundance of Veillonella and Streptococcus was decreased significantly compared to the control group. Functional analysis demonstrated that butyrate and lactate producers were less abundant in the ASD group. In addition, we downloaded the association data set of microbe-disease from human microbe-disease association database and constructed a human disease network including ASD using our gut microbiome results. In this microbe-disease network based on microbe similarity of diseases, we found that ASD is positively correlated with periodontal, negatively related to type 1 diabetes. Therefore, these results suggest that microbe-based disease analysis is able to predict novel connection between ASD and other diseases and may play a role in revealing the pathogenesis of ASD.

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