AUTHOR=Ma Yu , Zhou Hao , Li Chunpei , Zou Xiaobing , Luo Xuerong , Wu Lijie , Li Tingyu , Chen Xiang , Mao Meng , Huang Yi , Li Erzhen , An Yanpeng , Zhang Lili , Wang Tianqi , Xu Xiu , Yan Weili , Jiang Yonghui , Wang Yi
TITLE=Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary 1H-NMR Metabolomics Analysis
JOURNAL=Frontiers in Psychiatry
VOLUME=12
YEAR=2021
URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2021.624767
DOI=10.3389/fpsyt.2021.624767
ISSN=1664-0640
ABSTRACT=Background: Autism spectrum disorder (ASD) is a group of early-onset neurodevelopmental disorders. However, there is no valuable biomarker for the early diagnosis of ASD. Our large-scale and multi-center study aims to identify metabolic variations between ASD and healthy children and to investigate differential metabolites and associated pathogenic mechanisms.
Methods: One hundred and seventeen autistic children and 119 healthy children were recruited from research centers of 7 cities. Urine samples were assayed by 1H-NMR metabolomics analysis to detect metabolic variations. Multivariate statistical analysis, including principal component analysis (PCA), and orthogonal projection to latent structure discriminant analysis (OPLS-DA), as well as univariate analysis were used to assess differential metabolites between the ASD and control groups. The differential metabolites were further analyzed by receiver operating characteristics (ROC) curve analysis and metabolic pathways analysis.
Results: Compared with the control group, the ASD group showed higher levels of glycine, guanidinoacetic acid, creatine, hydroxyphenylacetylglycine, phenylacetylglycine, and formate and lower levels of 3-aminoisobutanoic acid, alanine, taurine, creatinine, hypoxanthine, and N-methylnicotinamide. ROC curve showed relatively significant diagnostic values for hypoxanthine [area under the curve (AUC) = 0.657, 95% CI 0.588 to 0.726], creatinine (AUC = 0.639, 95% CI 0.569 to 0.709), creatine (AUC = 0.623, 95% CI 0.552 to 0.694), N-methylnicotinamide (AUC = 0.595, 95% CI 0.523 to 0.668), and guanidinoacetic acid (AUC = 0.574, 95% CI 0.501 to 0.647) in the ASD group. Combining the metabolites creatine, creatinine and hypoxanthine, the AUC of the ROC curve reached 0.720 (95% CI 0.659 to 0.777). Significantly altered metabolite pathways associated with differential metabolites were glycine, serine and threonine metabolism, arginine and proline metabolism, and taurine and hypotaurine metabolism.
Conclusions: Urinary amino acid metabolites were significantly altered in children with ASD. Amino acid metabolic pathways might play important roles in the pathogenic mechanisms of ASD.