A pilot study found that elevated gut bacteria-derived metabolites can identify many children with autism, raising the possibility of a simple urine-based screening tool and a newly proposed ASD subtype associated with microbiome dysfunction.
Study: Elevated microbial-derived metabolites in autism: Potential diagnostic screening test for distinct ASD phenotypes. Image credit: Prostock-studio/Shutterstock.com
Recent research published in molecular psychiatry investigated whether urinary microbial metabolite (MDM) concentrations could objectively differentiate children with autism spectrum disorder (ASD) from neurotypical children.
ASD: clinical complexity, microbiome associations, and unresolved mechanisms
ASD is a complex neurodevelopmental condition characterized by early-onset challenges in social communication, restricted interests, and repetitive behaviors. Symptoms vary widely in presentation and severity, ranging from people who require serious support to people who are able to live independently with relatively mild difficulties. ASD results from a complex genetic and environmental interaction.
Over recent decades, the prevalence of ASD in the United States has increased dramatically, increasing pressure on families, health care systems, and support services. Approximately 10% of cases are associated with an identifiable genetic syndrome, but the underlying cause of most cases remains unknown. Given this heterogeneity, researchers are increasingly considering identifying biologically distinct ASD subtypes as an important step toward developing targeted treatment strategies.
Early behavioral intervention is most effective within the first two years of life, but diagnosis usually occurs much later. This delay highlights the urgent need for non-invasive early screening tools to enable timely intervention and reduce long-term clinical and economic impact.
A significant proportion of patients with ASD experience chronic gastrointestinal (GI) symptoms, which often appear within the first 3 years of life in parallel with the severity of the ASD. Consistent evidence points to dysbiosis of the gut microbiota in ASD, showing a different microbial profile compared to that of neurotypical individuals. This dysbiosis alters metabolic and immune pathways, including the production of short-chain fatty acids (SCFAs), cytokines, and neurotransmitters, supporting a possible mechanistic link between the gut microbiota and neurodevelopment via the gut-brain axis.
Microbial metabolites such as p-cresol and indoxyl sulfate are found at high levels in people with ASD. These compounds, especially when present in high amounts early in life, can have negative effects on gut health, immune function, and brain signaling. Therefore, there is a need to identify specific microbial and metabolic markers that can distinguish between different types of ASD and support early diagnosis and more targeted treatments.
Analysis of urine metabolites to screen for ASD
In the current study, we developed a biomedical screening test for ASD by measuring MDM in the urine of children with ASD and typically developing (TD) children. A total of 52 children with ASD and 47 children with TD, aged 2 to 11 years, were recruited from four sites in the United States. The diagnosis of ASD was confirmed by expert raters using the Childhood Autism Rating Scale and Social Responsiveness Scale-2 (SRS-2; score >68). A urine sample was collected.
Metabolite extraction and liquid chromatography-mass spectrometry (LC-MS) analysis were performed according to standard protocols, and metabolites were annotated and quantified in comparison to urinary creatinine. An initial untargeted LC-MS approach was used for discovery, followed by targeted quantitative LC-MS follow-up analysis.
A new multivariate analysis, the Microbially-Derived Metabolite System™ (MDM System™), was created to identify children with ASD with dysbiosis. Each participant’s MDM concentration was compared to the TD range. The score reflected the number of elevated MDMs.
Distinct microbial metabolite profiles differentiate children with ASD and TD
Both the TD and ASD groups were age matched, and the TD group was intentionally gender balanced. Metabolite analysis did not find any significant sex differences. The analysis focused on metabolites produced by microorganisms grouped as phenylalanine-derived, tryptophan-derived, or yeast/other.
Six phenylalanine-derived metabolites and eight tryptophan-derived metabolites were significantly increased in ASD, with increases ranging from 29% to 1882%. Many ASD participants had metabolite levels that exceeded those of all TD cases. The yeast metabolite arabinitol was also 51% higher in ASD, and N-formyl methionine was 70% lower. These findings highlight a unique metabolic profile in ASD.
Most ASD participants had significantly higher levels of tryptophan or phenylalanine-derived metabolites, or both, compared to TD children. In a subgroup of ASD participants, increases in arabinitol and decreases in N-formylmethionine often occurred together. Metabolite levels were generally higher in ASD, except for N-formyl methionine.
The MDM System™ total score, which reflects the number of highly elevated metabolites per participant, averaged 3.3 in ASD and 0 in TD. Semi-quantitative analysis using a single elevated metabolite threshold achieved 90% sensitivity and 100% specificity for ASD.
There was no significant correlation between MDM total score and age in ASD. Multivariate models such as Fisher Discriminant Analysis (FDA), neural networks, and Naive Bayes consistently achieved high diagnostic accuracy with area under the receiver operating characteristic curve values up to 0.86.
Univariate analysis identified 10 metabolites that were significantly elevated in ASD, most of them related to phenylalanine and tryptophan. Some compounds, such as p-cresol, were elevated only in a subset of ASD cases, and detection limits influenced the results for certain compounds.
Metabolites such as p-cresol and indole-3-propionic acid provide strong group separation. Although a significant number of ASD participants had elevated tryptophan- or phenylalanine-related metabolites, elevated yeast metabolites were less frequent. Highly correlated metabolites such as indolepropionic acid and beta-carboline may reflect microbial dysbiosis rather than external exposure. Metabolites with more undetectable samples contribute less to the MDM System™ algorithm.
For targeted quantitative analysis, the MDM System™ demonstrated 100% specificity and 78% sensitivity; Although performance was lower than in the first semi-quantitative analysis, the reproducibility of the overall methodology was improved. FDA also showed that the most effective metabolite combinations had area under the curve values greater than 0.7, with minimal additional increases due to the addition of metabolites.
This finding also led the researchers to propose the following: A hypothetical ASD subtype called “microbial-derived metabolite-associated ASD” (ASD-MDM). Based on study data, the authors suggest that approximately 80-90% of children with ASD in their cohort may belong to this metabolically distinct subgroup, but the proposed classification requires independent validation before it can be considered an established ASD phenotype.
conclusion
The current study highlights the importance of MDM in a significant subpopulation of children with ASD. What MDM System™ development offers This is a promising proof-of-concept approach for future early screening and identification of children with a high likelihood of ASD.
However, this result is based on a relatively small pilot cohort, and the authors stress that independent validation in a larger cohort is still needed before the test can be considered clinically established.. Continued research, including validation in independent cohorts and exploration of microbiome-based treatments, is essential to fully understand the potential of these advances to improve outcomes for children with ASD.
The paper also notes that several authors hold patents, patent applications, or commercial interests related to ASD diagnosis and the MDM System™, highlighting the importance of independently reproducing study results.
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Reference magazines:
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C. K. Flynn et al. (2026). Elevated microbial-derived metabolites in autism: Potential diagnostic screening test for distinct ASD phenotypes. Molecular psychiatry. 1-11. Doi: https://doi.org/10.1038/s41380-026-03620-5. https://www.nature.com/articles/s41380-026-03620-5
