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Elevated Microbially-Derived Metabolites in Autism: A Possible Diagnostic Screening Test for a Distinct ASD Phenotype
Christina Flynn1, Kevin Carr, Paul Whiteley
1Arizona State University.
Research Square
|November 19, 2025
Summary
Children with autism spectrum disorder (ASD) show high levels of harmful microbially-derived metabolites (MDMs) in urine. These findings suggest a new ASD subtype, ASD-MDM, and a potential diagnostic screening tool.
Area of Science:
- Neuroscience
- Metabolomics
- Pediatrics
Background:
- Autism spectrum disorder (ASD) is associated with elevated urinary microbially-derived metabolites (MDMs) in some children.
- These MDMs may impact neurodevelopment via the gut-brain axis.
- A gut dysbiosis sub-phenotype is hypothesized in most ASD individuals.
Purpose of the Study:
- To investigate urinary MDM concentrations in children with ASD compared to typically developing (TD) children.
- To explore the potential of MDMs as biomarkers for ASD diagnosis and sub-phenotyping.
- To identify a distinct ASD phenotype characterized by MDMs, termed ASD-MDM.
Main Methods:
- Multi-site study involving 52 children with ASD and 47 TD children (ages 2-11).
- Urine samples analyzed using untargeted and targeted Liquid Chromatography and Mass Spectrometry (LC-MS).
- Quantification of various MDMs, including phenylalanine-derived, tryptophan-derived, and yeast-derived metabolites.
Main Results:
- Children with ASD exhibited significantly higher concentrations of numerous MDMs compared to TD children.
- Nearly all ASD children had elevated MDMs, with some concentrations 100-1000x higher than TD controls.
- Classification based on elevated MDMs achieved 90% sensitivity and 100% specificity for ASD detection.
Conclusions:
- Elevated urinary MDMs are a significant finding in children with ASD, suggesting a gut-brain axis connection.
- The MDM System™ shows promise as a non-invasive diagnostic screening tool for ASD in children aged 2-11.
- Approximately 90% of ASD cases may represent a distinct phenotype, ASD-MDM, identifiable through urinary metabolite profiling.

