Promising Biomarkers Could Enhance Early Autism Diagnosis

Urinary Metabolites and Eye-Tracking: Potential Aids in Autism Diagnosis

Early diagnosis of autism spectrum disorder (ASD) can improve outcomes for children, but current methods rely on behavioral assessments that are subjective and often delayed. Two recent studies explore how objective biomarkers might complement these evaluations.

A Urinary Clue to Autism

A study published in Nature found that certain gut bacteria-produced chemicals (called metabolites) were elevated in the urine of some autistic children. These metabolites, which are byproducts of microbial activity in the digestive system, were significantly higher in a subset of autistic children compared to neurotypical peers. The research suggests this could eventually help identify some cases earlier, though it's not yet clear what percentage of autistic children this applies to.

Eye-Tracking as a Diagnostic Aid

Research in JAMA Network Open tested whether measuring how children look at social scenes could help identify autism. The study of 500 children found this eye-tracking method was about 80% accurate in distinguishing autistic from non-autistic children in primary care settings. While promising, the authors note this approach needs testing in more diverse populations before widespread use.

Why This Research Matters

With current autism diagnoses often taking years, these biomarkers could eventually help reduce wait times when used alongside standard evaluations. They may be particularly valuable in areas with limited access to specialists, as explained in Contemporary Pediatrics. However, experts caution these are not standalone diagnostic tools.

Key Considerations Moving Forward

• Limited applicability: The urine test appears to identify only some autistic children with specific metabolic patterns, as noted in the Nature study.
• Diversity needs: The eye-tracking method requires validation across different racial, ethnic, and socioeconomic groups, per Frontiers research.
• Implementation challenges: Cost, training needs, and equipment availability could affect real-world use, as discussed in Science Advances.
• Timeline: Most experts estimate these tools are at least 3-5 years from routine clinical use, pending further trials.