AUTHOR=Xu Xin-Jie , Cai Xiao-E , Meng Fan-Chao , Song Tian-Jia , Wang Xiao-Xi , Wei Yi-Zhen , Zhai Fu-Jun , Long Bo , Wang Jun , You Xin , Zhang Rong
TITLE=Comparison of the Metabolic Profiles in the Plasma and Urine Samples Between Autistic and Typically Developing Boys: A Preliminary Study
JOURNAL=Frontiers in Psychiatry
VOLUME=12
YEAR=2021
URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2021.657105
DOI=10.3389/fpsyt.2021.657105
ISSN=1664-0640
ABSTRACT=Background: Autism spectrum disorder (ASD) is defined as a pervasive developmental disorder which is caused by genetic and environmental risk factors. Besides the core behavioral symptoms, accumulated results indicate children with ASD also share some metabolic abnormalities.
Objectives: To analyze the comprehensive metabolic profiles in both of the first-morning urine and plasma samples collected from the same cohort of autistic boys.
Methods: In this study, 30 autistic boys and 30 tightly matched healthy control (HC) boys (age range: 2.4~6.7 years) were recruited. First-morning urine and plasma samples were collected and the liquid chromatography–mass spectrometry (LC-MS) was applied to obtain the untargeted metabolic profiles. The acquired data were processed by multivariate analysis and the screened metabolites were grouped by metabolic pathway.
Results: Different discriminating metabolites were found in plasma and urine samples. Notably, taurine and catechol levels were decreased in urine but increased in plasma in the same cohort of ASD children. Enriched pathway analysis revealed that perturbations in taurine and hypotaurine metabolism, phenylalanine metabolism, and arginine and proline metabolism could be found in both of the plasma and urine samples.
Conclusion: These preliminary results suggest that a series of common metabolic perturbations exist in children with ASD, and confirmed the importance to have a comprehensive analysis of the metabolites in different biological samples to reveal the full picture of the complex metabolic patterns associated with ASD. Further targeted analyses are needed to validate these results in a larger cohort.