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Urinary Metabonomic Profiling Discriminates Between Children with Autism and Their Healthy Siblings.

  • Liang, Yujie1, 2
  • Xiao, Zhou1
  • Ke, Xiaoyin1
  • Yao, Paul1
  • Chen, Yangxia1
  • Lin, Ling1, 2
  • Lu, Jianping1, 2
  • 1 Department of Child and Adolescent Psychiatry, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Key Laboratory for Psychological Healthcare and Shenzhen Institute of Mental Health, Shenzhen, Guangdong, China (mainland). , (China)
  • 2 Faculty of Mental health, Shenzhen University, Shenzhen, Guangdong, China (mainland). , (China)
Published Article
Medical Science Monitor
"International Scientific Information, Inc."
Publication Date
Nov 25, 2020
DOI: 10.12659/MSM.926634
PMID: 33237888


BACKGROUND Autism spectrum disorder (ASD) is a complicated neuropsychiatric disease that displays significant heterogeneity. The diagnosis of ASD is currently primarily dependent upon descriptions of clinical symptoms, and it remains urgent to find biological markers for the detection and diagnosis of autism. The current study applied the urinary metabolic profiling approach to characterize metabolic phenotypes in ASD. MATERIAL AND METHODS Urine was obtained from children with ASD and their matched healthy siblings. Samples were analyzed using 1H NMR-based methods designed to measure a broad range of metabolites. Partial least-square-discriminant analysis (PLS-DA) was used to develop models to identify metabonomic variations that can be used to distinguish between individuals with ASD and their unaffected siblings. RESULTS A significant difference was observed between the metabolomic profiles of children with ASD and that of their healthy siblings. An increase in the levels of tryptophan, hippurate, glycine, and creatine, and a decrease in trigonelline, melatonin, pantothenate, serotonin, and taurine were observed compared to the control group. We conclude that several metabolic pathways are affected by autism, which suggests that a gut-brain link may be important in the pathophysiology of ASD. CONCLUSIONS 1H NMR-based metabonomic analysis of the urine can determine perturbations of specific metabolic pathways related to ASD and help identify a characteristic metabolic fingerprint to better understand the disease and its causes.

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