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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Published on: September 12, 2011
Microbiota-gut-brain axis in autism spectrum disorder: integrating brain structure, function, and transcriptomics
Guoping Wang1, Wenjing Liu2, Yueqin Chen3
1College of Medical Imaging and Laboratory, Jining Medical University, 272000, Jining, Shandong Province, China.
None:
Growing evidence indicates that disruption of the microbiota-gut-brain (MGB) axis is a key factor in autism spectrum disorder (ASD), affecting neurodevelopment, neural circuit function, and behavior. This review synthesizes multidisciplinary data to clarify mechanistic links between the MGB axis and ASD and to evaluate microbiota-targeted therapeutic strategies. We conducted a narrative synthesis of clinical and translational studies, including human cohort and case-control investigations, animal models, multi-omics analyses, immune profiling, multimodal brain assessments (structural/functional MRI and transcriptomics), and interventional trials. Emphasis was placed on evidence of microbiota-brain associations, intervention outcomes, and methodological limitations. Key findings reveal that individuals with ASD commonly exhibit gut microbiome dysbiosis and altered metabolomic signatures that can influence central nervous system function; three core bidirectional signaling routes link gut microbes to brain outcomes-microbial metabolite production (e.g., short-chain fatty acids, tryptophan metabolites), immune-mediated pathways, and neuroendocrine-vagal communication. Accumulating data associate ASD-related microbial profiles with changes in brain structure, functional connectivity, and transcriptomic patterns, supporting a mechanistic role for the MGB axis in ASD phenotypes. Microbiota-targeted interventions show promising effects on gastrointestinal symptoms, metabolic biomarkers, and selected behavioral measures in small studies, but results are heterogeneous and current evidence is insufficient for widespread clinical application. Integrating multimodal neuroimaging with multi-omics and machine learning provides a promising framework to identify reproducible microbial-brain biomarkers for early detection, clinical subtyping, and stratified treatment. Key challenges include methodological heterogeneity, limited causal inference, small and heterogeneous cohorts, and ethical/safety concerns for pediatric interventions. The MGB axis is a plausible pathogenic mechanism and therapeutic target in ASD. Translating mechanistic insights into precision clinical applications requires standardized, multicenter, longitudinal deep-phenotyping studies that combine multimodal imaging, comprehensive multi-omics, rigorous randomized trials, and careful ethical oversight.
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