Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary 1H-NMR Metabolomics Analysis

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.

Preparation and Characterization of Calcium-Incorporated Rosa roxburghii Tratt and Its Efficacy on Bone Mineral Density in Rats

“…The FTIR, 1 H-NMR, and UV spectroscopy of FE and FECa were recorded to determine the binding site of calcium ions [ 17 – 20 ].…”

San-Huang-Yi-Shen Capsule Ameliorates Diabetic Nephropathy in Rats Through Modulating the Gut Microbiota and Overall Metabolism

“…Guanidineacetic acid is an immediate precursor of creatine biosynthesis, however, this reaction causes elevated levels of homocysteine in the blood. This can result in vasculopathy, which is one of the causes of diabetic macrovascular and microvascular complications in diabetic patients ( De Luis et al, 2005 ; Zhao et al, 2018 ; Ma et al, 2020 ). L-glutamic acid and L-glutamine are interconvertible.…”

Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children

“…For example, one could imagine two metabolites that have the same concentrations in TD and ASD, but whose correlation changes with age or other conditions (e.g, diet; example [ 48 ]). Much of the literature on biomarkers of ASD and/or IDD has focused on the search for individual molecules, or statistical combinations of molecules, which are predictive of ASD-related morbidity or diagnosis [ 16 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 ]. However, few metabolomic studies have moved beyond individual, isolated biomarkers, focusing instead on metabolic pathway analysis, in which whole metabolic pathways are analyzed for significant changes.…”

“…Single-metabolite analyses of annotated features subsets also suffered from the burden of multiple testing, although some metabolites remained significantly associated with diagnosis after applying the FDR correction. Although none of the annotated metabolites were significantly associated with ASD after FDR corrections, the four maternal metabolites most associated with increased ASD ( O -phosphoethanolamine [ 89 ], indole [ 80 , 90 ], betaine [ 79 , 91 ], and serine [ 53 , 72 , 87 , 88 , 92 , 93 , 94 ]) were in pathways previously implicated in ASD etiology. Further, acetylcarnitine, one of the most associated maternal single metabolites for Non-TD (positive node), has also been previously identified as a metabolic marker of ASD [ 95 ].…”