Comparison of gut microbiota in autism spectrum disorders and neurotypical boys in China:A case-control study

Background:Autism spectrum disorders(ASDs)are a set of complex neurobiological disorders.Growing evidence has shown that the microbiota that resides in the gut can modulate brain development via the gut–brain axis.However,direct clinical evidence of the role of the microbiota–gut–brain axis in ASD is relatively limited.Methods:A case-control study of 71 boys with ASD and 18 neurotypical controls was conducted at China-Japan Friendship Hospital.Demographic information and fecal samples were collected,and the gut microbiome was evaluated and compared by 16S ribosomal RNA gene sequencing and metagenomic sequencing.Results:A higher abundance of operational taxonomic units(OTUs)based on fecal bacterial profiling was observed in the ASD group.Significantly different microbiome profiles were observed between the two groups.At the genus level,we observed a decrease in the relative abundance of Escherichia,Shigella,Veillonella,Akkermansia,Provindencia,Dialister,Bifidobacterium,Streptococcus,Ruminococcaceae UCG_002,Megasphaera,Eubacterium_coprostanol,Citrobacter,Ruminiclostridium_5,and Ruminiclostridium_6 in the ASD cohort,while Eisenbergiella,Klebsiella,Faecalibacterium,and Blautia were significantly increased.Ten bacterial strains were selected for clinical discrimination between those with ASD and the neurotypical controls.The highest AUC value of the model was 0.947.Conclusion:Significant differences were observed in the composition of the gut microbiome between boys with ASD and neurotypical controls.These findings contribute to the knowledge of the alteration of the gut microbiome in ASD patients,which opens the possibility for early identification of this disease.

Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease

Dysregulation of the gut microbiome has been implicated in the progression of many diseases.This study explored the role of microbial and metabolic signatures,and their interaction between the Human inflammatory bowel disease(IBD)and healthy controls(HCs)based on the combination of machine learning and traditional statistical analysis,using data collected from the Human Microbiome Project(HMP)and the Integrative Human Microbiome Project(iHMP).It was showed that the microbial and metabolic signatures of IBD patients were significantly different from those of HCs.Compared to HCs,IBD subjects were characterized by 25 enriched species and 6 depleted species.Furthermore,a total of 17 discriminative pathways were identified between the IBD and HC groups.Those differential pathways were mainly involved in amino acid,nucleotide biosynthesis,and carbohydrate degradation.Notably,co-occurrence network analysis revealed that non-predominant bacteria Ruminococcus_obeum and predominant bacteria Faecalibacterium_prausnitzii formed the same broad and strong co-occurring relationships with pathways.Moreover,the essay identified a combinatorial marker panel that could distinguish IBD from HCs.Receiver Operating Characteristic(ROC)and Decision Curve Analysis(DCA)confirmed the high accuracy(AUC=0.966)and effectiveness of the model.Meanwhile,an independent cohort used for external validation also showed the identical high efficacy(AUC=0.835).These findings showed that the gut microbes may be relevant to the pathogenesis and pathophysiology,and offer universal utility as a non-invasive diagnostic test in IBD.