New Study Links Autism Diagnosis to Unique Gut Microbiome

Researchers identify distinct microbial markers in children with autism, offering potential for earlier and more accurate diagnoses.

Analysis of over 1,600 stool samples reveals 31 unique microbial signatures in children with autism.
The study broadens focus beyond bacteria to include fungi, viruses, and archaea in the gut.
Machine learning models based on these markers show high accuracy in predicting autism.
Experts believe this approach could reduce diagnostic delays and improve early intervention.
Further research is needed to confirm the microbiome's role and validate findings across diverse populations.