#AI reads Urine# A targeted metabolomic study investigating alterations in urine metabolites of Slovak children with autism spectrum disorders

To investigate the pathophysiological mechanism and potential biomarkers of autism spectrum disorder (ASD), this study conducted targeted metabolomic analysis on urine samples from 35 ASD children and 30 age-matched typically developing children. Using LC-MS/MS technology to detect 185 metabolites, the results showed that compared with healthy controls, the urine of ASD children had significantly higher levels of pimelylcarnitine (C7-DC) and glycerophospholipid PCaaC34:1, as well as a significantly lower level of nonanoylcarnitine (C9) (p<0.05). These changes in acylcarnitines and glycerophospholipids suggest that ASD may be associated with mitochondrial dysfunction and imbalanced fatty acid metabolism, and these metabolites are expected to serve as potential biomarkers for ASD. However, further validation of their diagnostic sensitivity and disease-specificity in larger sample sizes is required.

Activitas Nervosa Superior Rediviva 67(3):116-121

DOI: 10.31577/ansr.2025.67.3.3

Youhe Gao

Statement: During the preparation of this work the author(s) used Doubao / AI reading for summarizing the content. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

For earlier AI Reads Urine articles：

https://www.keaipublishing.com/en/journals/advances-in-biomarker-sciences-and-technology/ai-reads-urine/