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Alterations of several types of metabolites related to microbiota-gut-brain axis in urine of children with autism spectrum disorder

Bibliographic Data

ID15524804
AuthorsKangwei Shen (Ministry of Education, corresponding author), Jingjing Huang (0000-0003-0522-9923, University for the Creative Arts), Dianzhi Liu (0000-0002-7839-3444, Soochow University), Qing Lu (0000-0002-7943-966X, Ministry of Education), Xuejun Kang (0000-0003-0258-1462, Ministry of Education), Yan Yan (0000-0001-5357-0187, Suzhou Research Institute)
Year2026
Volume17
Publication date2026-03-24
Open AccessYes
TypeARTICLE
VenueFrontiers in Psychiatry (JOURNAL)
Journal identifiersISSN: 1664-0640 • E-ISSN: 1664-0640
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2026.1784658
OpenAlexW7140168228
LanguageEN
References cited39

Introduction Multiple studies have shown that autism spectrum disorder (ASD) is accompanied by abnormalities in multiple metabolic pathways, however, the fluctuations of certain metabolites involved in these pathways have shown controversial results. This study aimed to identify metabolic characteristics that can distinguish children with ASD by using targeted metabolomics analysis on several types of metabolites related to the microbiota-gut-brain axis. Methods A total of 54 children with ASD and 47 healthy children (HC) were recruited. Data from the Autism Behavior Checklist (ABC) scale for children with ASD were collected. Based on chromatography/mass spectrometry analysis, the metabolic characteristics of several types of metabolites related to the microbiota-gut-brain axis were discovered in urine samples. Single-variable and multi-variable analyses were conducted using MetaboAnalyst 6.0 and SPSS 27.0.1 to identify potential differential metabolites. The association between differential metabolite concentrations and ABC scores in children with ASD was evaluated using Spearman’s rank correlation analysis. Results and Discussion Seven differential indicators, namely the ratio of cortisol to cortisone (R), creatinine, cortisol, taurine, histamine, homocysteine, and methionine were identified. The combined index diagnostic model constructed based on these indicators demonstrated strong discriminatory power, with an area under the receiver operating characteristic (ROC) curve of 0.943, a sensitivity of 92.6%, and a specificity of 93.7%. The above-mentioned biochemical indicators may be involved in the pathological physiological process of autistic behavioral symptoms from different aspects. These findings contribute to a better understanding of the underlying mechanisms of ASD

Autism · Autism spectrum disorder · Childhood Autism Rating Scale · Metabolite · Metabolomics · Pathological · Receiver operating characteristic · Urine · Autism Spectrum Disorder Research · Gut microbiota and health · Tryptophan and brain disorders

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