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Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary (1)H-NMR Metabolomics Analysis
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...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144639/ https://www.ncbi.nlm.nih.gov/pubmed/34045978 http://dx.doi.org/10.3389/fpsyt.2021.624767 |
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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 |
author_facet | 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 |
author_sort | Ma, Yu |
collection | PubMed |
description | 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 (1)H-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. |
format | Online Article Text |
id | pubmed-8144639 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81446392021-05-26 Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary (1)H-NMR Metabolomics Analysis 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 Front Psychiatry Psychiatry 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 (1)H-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. Frontiers Media S.A. 2021-05-11 /pmc/articles/PMC8144639/ /pubmed/34045978 http://dx.doi.org/10.3389/fpsyt.2021.624767 Text en Copyright © 2021 Ma, Zhou, Li, Zou, Luo, Wu, Li, Chen, Mao, Huang, Li, An, Zhang, Wang, Xu, Yan, Jiang and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry 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 Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary (1)H-NMR Metabolomics Analysis |
title | Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary (1)H-NMR Metabolomics Analysis |
title_full | Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary (1)H-NMR Metabolomics Analysis |
title_fullStr | Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary (1)H-NMR Metabolomics Analysis |
title_full_unstemmed | Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary (1)H-NMR Metabolomics Analysis |
title_short | Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary (1)H-NMR Metabolomics Analysis |
title_sort | differential metabolites in chinese autistic children: a multi-center study based on urinary (1)h-nmr metabolomics analysis |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144639/ https://www.ncbi.nlm.nih.gov/pubmed/34045978 http://dx.doi.org/10.3389/fpsyt.2021.624767 |
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