Dataset Information

Altered Gut Microbiota in Chinese Children With Autism Spectrum Disorders.

ABSTRACT: The link between gut microbes and autism spectrum disorders (ASD) has been already observed in some studies, but some bacterial families/species were found to be inconsistently up or down regulated. This issue has been rarely explored in the Chinese population. In this study, we assessed whether or not gut microbiota dysbiosis was associated with children with ASD in China. We enrolled 45 children with ASD (6-9 years of age; 39 boys and 6 girls) and 45 sex- and age-matched neurotypical children. Dietary and other socio-demographic information was obtained via questionnaires. We characterized the composition of the fecal microbiota using bacterial 16S ribosomal RNA (16S rRNA) gene sequencing. The ASD group showed less diversity and richness of gut microbiota than the neurotypical group, as estimated by the abundance-based coverage estimator index and the phylogenetic diversity index. The analysis of beta diversity showed an altered microbial community structure in the ASD group. After adjustment for confounders and multiple testing corrections, no significant group difference was found in the relative abundance of microbiota on the level of the phylum. At the family level, children with ASD had a lower relative abundance of Acidaminococcaceae than the healthy controls. Moreover, a decrease in the relative abundance of genera Lachnoclostridium, Tyzzerella subgroup 4, Flavonifractor, and unidentified Lachnospiraceae was observed in ASD group. This study provides further evidence of intestinal microbial dysbiosis in ASD and sheds light on the characteristics of the gut microbiome of autistic children in China.

SUBMITTER: Ma B

PROVIDER: S-EPMC6414714 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Altered Gut Microbiota in Chinese Children With Autism Spectrum Disorders.

Ma Bingjie B Liang Jingjing J Dai Meixia M Wang Jue J Luo Jingyin J Zhang Zheqing Z Jing Jin J

Frontiers in cellular and infection microbiology 20190306

The link between gut microbes and autism spectrum disorders (ASD) has been already observed in some studies, but some bacterial families/species were found to be inconsistently up or down regulated. This issue has been rarely explored in the Chinese population. In this study, we assessed whether or not gut microbiota dysbiosis was associated with children with ASD in China. We enrolled 45 children with ASD (6-9 years of age; 39 boys and 6 girls) and 45 sex- and age-matched neurotypical children. ...[more]

PMID: 30895172

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Project description:BackgroundAutism spectrum disorder (ASD) is a type of neurodevelopmental disease that is frequently accompanied by sleep disorder. Herein, we investigated changes in the gut microbiota and its metabolites correlated with core symptoms and sleep problems in children with ASD.MethodsOne hundred and twenty children diagnosed with ASD based on Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria were enrolled in our study. The Autism Behavior Checklist (ABC), Social Responsiveness Scale (SRS), and Childhood Autism Rating Scale (CARS) were used to assess autism symptoms, and the Children Sleep Habits Questionnaire (CSHQ) was employed to evaluate sleep problems in children with ASD. The 120 children were divided into a sleep disorder group (n = 60) and a control group without sleep disorder (n = 60) according to the CSHQ answers. Illumina MiSeq analysis of 16S rRNA genes was used to compare differences in gut microbiota, and metabolomics analysis was employed to asses associated metabolites.ResultsSRS and CARS scores for the sleep disorder group were significantly higher than for the control group (p < 0.05). The abundances of butyrate-producing bacteria Faecalibacterium and Agathobacter were reduced significantly in the sleep disorder group (p < 0.05), and this was negatively correlated with CSHQ score (p = 0.007 and p = 0.014, respectively). The abundance of Agathobacter was also negatively associated with the ABC language score (p = 0.044). Furthermore, levels of 3-hydroxybutyric acid and melatonin were significantly lower (p < 0.05) while serotonin levels were higher (p < 0.05) in the sleep disorder group. The 3-hydroxybutyric acid level was positively associated with Faecalibacterium abundance (p = 0.000), and melatonin was positively associated with the abundance of Faecalibacterium (p = 0.036) and Agathobacter (p = 0.041). We also observed negative correlations between 3-hydroxybutyric acid and CSHQ (p = 0.000) and CARS (p = 0.009), between melatonin and CSHQ (p = 0.002) and ABC sensory score (p = 0.021), and a positive correlation between serotonin and CSHQ (p = 0.002) and ABC sensory score (p = 0.025).ConclusionsASD children with sleep disorder exhibited declines in the abundance of Faecalibacterium and Agathobacter, decreased levels of 3-hydroxybutyric acid and melatonin, and an increase in serotonin. These changes may aggravate sleep problems and core symptoms in children with ASD.

Project description:Autism spectrum disorders (ASD) affect 1% of children. Although there is no cure, early diagnosis and behavioral intervention can relieve the symptoms. The clinical heterogeneity of ASD has created a need for improved sensitive and specific laboratory diagnostic methods. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analysis of the metabolome has shown great potential to uncover biomarkers for complex diseases such as ASD. Here, we used a two-step discovery-validation approach to identify potential novel metabolic biomarkers for ASD. Urine samples from 57 children with ASD and 81 matched children with typical development (TD) were analyzed by LS-MS/MS to assess differences in urinary amino acids and their metabolites (referred to as UAA indicators). A total of 63 UAA indicators were identified, of which 21 were present at significantly different levels in the urine of ASD children compared with TD children. Of these 21, the concentrations of 19 and 10 were higher and lower, respectively, in the urine of ASD children compared with TD children. Using support vector machine modeling and receiver operating characteristic curve analysis, we identified a panel of 7 UAA indicators that discriminated between the samples from ASD and TD children (lysine, 2-aminoisobutyric acid, 5-hydroxytryptamine, proline, aspartate, arginine/ornithine, and 4-hydroxyproline). Among the significantly changed pathways in ASD children were the ornithine/urea cycle (decreased levels of the excitatory amino acid aspartate [p = 2.15 × 10-10] and increased arginine/ornithine [p = 5.21 × 10-9]), tryptophan metabolism (increased levels of inhibitory 5-hydroxytryptamine p = 3.62 × 10-9), the methionine cycle (increased methionine sulfoxide [p = 1.46 × 10-10] and decreased homocysteine [p = 2.73 × 10-7]), and lysine metabolism (reduced lysine [p = 7.8 × 10-9], α-aminoadipic acid [p = 1.16 × 10-9], and 5-aminovaleric acid [p = 1.05 × 10-5]). Collectively, the data presented here identify a possible imbalance between excitatory and inhibitory amino acid metabolism in ASD children. The significantly altered UAA indicators could therefore be potential diagnostic biomarkers for ASD.

Project description:BackgroundIn recent years, observational studies have provided evidence supporting a potential association between autism spectrum disorder (ASD) and gut microbiota. However, the causal effect of gut microbiota on ASD remains unknown.MethodsWe identified the summary statistics of 206 gut microbiota from the MiBioGen study, and ASD data were obtained from the latest Psychiatric Genomics Consortium Genome-Wide Association Study (GWAS). We then performed Mendelian randomization (MR) to determine a causal relationship between the gut microbiota and ASD using the inverse variance weighted (IVW) method, simple mode, MR-Egger, weighted median, and weighted model. Furthermore, we used Cochran's Q test, MR-Egger intercept test, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out analysis to identify heterogeneity and pleiotropy. Moreover, the Benjamin-Hochberg approach (FDR) was employed to assess the strength of the connection between exposure and outcome. We performed reverse MR analysis on the gut microbiota that were found to be causally associated with ASD in the forward MR analysis to examine the causal relationships. The enrichment analyses were used to analyze the biological function at last.ResultsBased on the results of IVW results, genetically predicted family Prevotellaceae and genus Turicibacter had a possible positive association with ASD (IVW OR=1.14, 95% CI: 1.00-1.29, P=3.7×10-2), four gut microbiota with a potential protective effect on ASD: genus Dorea (OR=0.81, 95% CI: 0.69-0.96, P=1.4×10-2), genus Ruminiclostridium5 (OR=0.81, 95% CI: 0.69-0.96, P=1.5×10-2), genus Ruminococcus1 (OR=0.83, 95% CI: 0.70-0.98, P=2.8×10-2), and genus Sutterella (OR=0.82, 95% CI: 0.68-0.99, P=3.6×10-2). After FDR multiple-testing correction we further observed that there were two gut microbiota still have significant relationship with ASD: family Prevotellaceae (IVW OR=1.24; 95% CI: 1.09-1.40, P=9.2×10-4) was strongly positively correlated with ASD and genus RuminococcaceaeUCG005 (IVW OR=0.78, 95% CI: 0.67-0.89, P=6.9×10-4) was strongly negatively correlated with ASD. The sensitivity analysis excluded the influence of heterogeneity and horizontal pleiotropy.ConclusionOur findings reveal a causal association between several gut microbiomes and ASD. These results deepen our comprehension of the role of gut microbiota in ASD's pathology, providing the foothold for novel ideas and theoretical frameworks to prevent and treat this patient population in the future.

Dataset Information

Altered Gut Microbiota in Chinese Children With Autism Spectrum Disorders.

Publications

Altered Gut Microbiota in Chinese Children With Autism Spectrum Disorders.

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