# Gut microbiota and its metabolism in autism spectrum disorder: from pathogenesis to therapy

## TL;DR

This review explores how gut microbiota and its metabolites contribute to autism and how targeting them may help treat symptoms.

## Contribution

The paper systematically reviews gut microbiota's role in autism and highlights potential therapeutic strategies.

## Key findings

- ASD patients show reduced gut microbiota diversity and imbalanced Bacteroidetes/Firmicutes ratios.
- Gut microbiota metabolites influence neurobehavior by affecting the blood-brain barrier and neuroinflammation.
- Interventions like probiotics and fecal microbiota transplantation may alleviate ASD symptoms.

## Abstract

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterized by social communication deficits and repetitive behaviors. Studies show that nearly half of ASD patients have gastrointestinal symptoms such as abdominal pain and diarrhea, indicating the important role of gut microbiota in its pathogenesis. This review finds that ASD patients exhibit reduced gut microbiota diversity and imbalanced Bacteroidetes/Firmicutes ratio, with abnormal microbial structure affecting neurobehavior through the gut-brain axis. Abnormalities in gut microbiota metabolites (short-chain fatty acids, phenolic compounds, bile acids, amino acids, etc.) are key mediators, which can exacerbate symptoms by affecting BBB permeability, neuroinflammation, and neurotransmitter balance. The gut-brain axis regulates ASD through mechanisms including the HPA axis, vagus nerve, immune pathways, and barrier functions. Gut microbiota-targeted interventions (exercise, dietary intervention, fecal microbiota transplantation, prebiotics/probiotics, etc.) can alleviate gastrointestinal and behavioral symptoms of ASD by regulating microbiota balance and improving metabolic environment. However, there are still issues such as unclear metabolite regulation mechanisms and significant individual differences in interventions. Future studies should combine multi-omics and artificial intelligence to identify core targets, develop personalized plans, and promote clinical translation.