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Exploring the Gut-Brain-Behavior Axis With Biomarkers, Probiotic Efficacy, and Artificial Intelligence Algorithms

Exploring the Gut-Brain-Behavior Axis With Biomarkers, Probiotic Efficacy, and Artificial Intelligence Algorithms

Recruiting
4-15 years
All
Phase N/A

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Overview

This groundbreaking human study on the ASD microbiome includes probiotic clinical trials, investigation of treatment biomarkers, machine learning/deep learning platform development for ASD classification and prediction, and identification of diagnostic biomarkers. Upon completion, the investigators anticipate publishing at least 12 SCI papers and/or patents and establishing an auxiliary diagnosis platform for both clinical and academic purposes. The findings will offer new insights into the pathogenetic mechanisms, improving early detection, diagnosis, and treatment, ultimately advancing precision medicine for ASD.

Description

With an increased prevalence of autism spectrum disorder (ASD) worldwide and in Taiwan, ASD demands urgent attention due to its lasting impact, unclear causes, and limited diagnostic and treatment options. Recent studies highlight disruptions in the gut-brain axis, particularly in ASD. Building on PI Gau's prior research on altered gut microbiota in autism spectrum disorder (ASD), this proposed 4-year study aims to develop evidence-based probiotic intervention (GKB7) and treatment biomarkers for behavioral interventions (Naturalistic Developmental Behavioral Interventions, NDBI, and Program for the Education and Enrichment of Relational Skills, PEERSĀ®) through comprehensive assessments. The ultimate goal is to establish probiotic treatments and diagnostic/treatment biomarkers for ASD utilizing a deep-learning multimodal auxiliary platform.

Specific Aims:

S.I To conduct a randomized, double-blind, placebo-controlled trial to assess the treatment effects of Clostridium butyricum GKB7 on ASD.

S.II To investigate the effect of NDBI intervention trials using metagenomics as the outcome measure.

S.III To evaluate the effect of PEERSĀ® interventional trials with metagenomics as the outcome measure.

S.IV To develop an artificial intelligence (machine/deep learning) multimodal auxiliary prediction platform that integrates environmental, behavioral/clinical, neurocognitive/imaging, and metagenomic data for ASD diagnosis, subtyping, and impairment prediction.

S.V To identify microbiome and metabolomic biomarkers and endophenotypes of ASD, and to establish Gut-Brain-Behavioral Axes in ASD.

Eligibility

Inclusion Criteria:

  • Children and adolescents aged 4 to 15 who are clinically diagnosed with ASD according to DSM-5 criteria and confirmed by the ADI-R/ADOS.
  • Caregivers cooperate with all the assessments and stool and blood collection.

Exclusion Criteria:

  • A history of major psychiatric disorders (e.g., schizophrenia, bipolar disorder, major depression), neurological disorders, and substances use disorders.
  • Difficulty following instructions.
  • Consumption of antibiotics and yogurt or probiotic products two weeks prior to enrollment.

Study details
    Autism Spectrum Disorder

NCT06677840

National Taiwan University Hospital

6 September 2025

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