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Front Cell Neurosci. 2019 Jan 25;13:7. doi: 10.3389/fncel.2019.00007. eCollection 2019.

Altered Urinary Amino Acids in Children With Autism Spectrum Disorders.

Author information

1
Shiyan Prevention and Health Care Center of Shenzhen, Shenzhen, China.
2
Division of Neonatology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
3
Division of Neonatology, The Maternal and Child Health Care Hospital of Huadu District, Huadu Affiliated Hospital of Guangdong Medical University, Guangzhou, China.
4
Imunobio, Shenzhen, China.
5
Xiamen Branch of Children's Hospital of Fudan University (Xiamen Children's Hospital), Xiamen, China.
6
Division of Neurosurgery, Tianjin Children's Hospital, Tianjin, China.
7
Tianjin Jinnan Xiaozhan Hospital, Tianjin, China.
8
Shanghai Key Laboratory of Birth Defects, Division of Neonatology, Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China.
9
Shanghai Key Laboratory of Birth Defects, Division of Neonatology, Xiamen Branch of Children's Hospital of Fudan University (Xiamen Children's Hospital), Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China.

Abstract

Autism spectrum disorders (ASD) affect 1% of children. Although there is no cure, early diagnosis and behavioral intervention can relieve the symptoms. The clinical heterogeneity of ASD has created a need for improved sensitive and specific laboratory diagnostic methods. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analysis of the metabolome has shown great potential to uncover biomarkers for complex diseases such as ASD. Here, we used a two-step discovery-validation approach to identify potential novel metabolic biomarkers for ASD. Urine samples from 57 children with ASD and 81 matched children with typical development (TD) were analyzed by LS-MS/MS to assess differences in urinary amino acids and their metabolites (referred to as UAA indicators). A total of 63 UAA indicators were identified, of which 21 were present at significantly different levels in the urine of ASD children compared with TD children. Of these 21, the concentrations of 19 and 10 were higher and lower, respectively, in the urine of ASD children compared with TD children. Using support vector machine modeling and receiver operating characteristic curve analysis, we identified a panel of 7 UAA indicators that discriminated between the samples from ASD and TD children (lysine, 2-aminoisobutyric acid, 5-hydroxytryptamine, proline, aspartate, arginine/ornithine, and 4-hydroxyproline). Among the significantly changed pathways in ASD children were the ornithine/urea cycle (decreased levels of the excitatory amino acid aspartate [p = 2.15 × 10-10] and increased arginine/ornithine [p = 5.21 × 10-9]), tryptophan metabolism (increased levels of inhibitory 5-hydroxytryptamine p = 3.62 × 10-9), the methionine cycle (increased methionine sulfoxide [p = 1.46 × 10-10] and decreased homocysteine [p = 2.73 × 10-7]), and lysine metabolism (reduced lysine [p = 7.8 × 10-9], α-aminoadipic acid [p = 1.16 × 10-9], and 5-aminovaleric acid [p = 1.05 × 10-5]). Collectively, the data presented here identify a possible imbalance between excitatory and inhibitory amino acid metabolism in ASD children. The significantly altered UAA indicators could therefore be potential diagnostic biomarkers for ASD.

KEYWORDS:

ASD; LC-MS/MS; children; metabolome; urinary amino acids

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