Altered Urinary Amino Acids in Children With Autism Spectrum Disorders

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.

FIGURE 1

Study design. The study was performed in two stages. In the discovery stage, urine samples were collected and profiled for UAAs and related metabolites by LC-MS/MS. PLS-DA and PERMANOVA were applied to determine which of the indicators could distinguish between ASD and TD children. In the validation stage, additional urine samples were collected to verify whether the identified UAAs and metabolites could be potential biomarkers for the diagnosis of ASD. AUC, area under the receiver operating characteristic curve; FDR, false discovery rate; ROC, receiver operating characteristic. See text for all other abbreviations.

FIGURE 2

Urinary amino acid profiling distinguishes between ASD children and TD children. (A,B) PLS-DA analysis of discovery (A) and validation (B) samples showing that UAA indicators can clearly distinguish between ASD and TD children (p = 0.0014 and p = 0.0001, respectively, by PERMANOVA). (C) Venn diagrams showing the number of UAA indicators identified during the discovery and validation stages. (D) Receiver operating characteristic curve analysis of 7 UAA indicators identified by SVM model training as best able to distinguish between ASD and TD children.

FIGURE 3

Mechanisms of UAA involvement in excitatory and inhibitory amino acid metabolism. The diagram shows the potential mechanisms by which the significant differences in UAA indicators identified between ASD and TD children might contribute to alterations in excitatory and inhibitory amino acid metabolism. Abnormalities in the Orn/urea and Met cycles and in Trp and Lys metabolism could lead to a decline in excitatory amino acids (e.g., glutamate and Asp) as well as a concomitant increase in inhibitory amino acids (e.g., 5HT).