Metabolic profiling reveals altered amino acid and fatty acid metabolism in children with Williams Syndrome

Abstract

Williams Syndrome (WS) is a rare neurodevelopmental disorder with a prevalence of 1 in 7500 to 1 in 20,000 individuals, caused by a microdeletion in chromosome 7q11.23. Despite its distinctive clinical features, the underlying metabolic alterations remain largely unexplored. This study employs targeted metabolomics to investigate the metabolic characteristics of children with WS. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified significant dysregulation of 15 metabolites, with 11 upregulated and 4 downregulated. Notably, amino acids such as alanine, proline, and arginine were significantly elevated. Fatty acid metabolism showed pronounced upregulation of long-chain saturated fatty acids (C18:0, C20:0, C22:0, C24:0, C26:0, and C28:0) and downregulation of long-chain unsaturated fatty acids (C18:2 LA, C22:6 DHA, C16:1 PLA, and t-C18:1 EA), except for upregulated nervonic acid (C24:1) and arachidonic acid (C20:4). Metabolic pathway analysis highlighted disruptions in arginine synthesis, arginine/proline metabolism, alanine, aspartate and glutamate metabolism, biosynthesis of unsaturated fatty acids, linoleic acid metabolism, and arachidonic acid metabolism. This study provides the first comprehensive analysis of amino acid and fatty acid metabolism in children with WS, offering insights into the disorder's complex metabolic landscape. Further validation in larger cohorts is essential to confirm these findings and their potential as biomarkers and therapeutic targets.

Keywords: Amino acids; Arachidonic acid (ARA); Docosahexaenoic acid (DHA); Long-chain saturated fatty acids (LC-SFAs); Targeted metabolomics; Williams Syndrome.

Fig. 1

Principal Component Analysis (PCA), Three-Dimensional PCA (3D PCA), and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) were employed to assess amino acid and fatty acid metabolites, revealing a clear separation between the WS and control groups. (a) PCA score plots. (b) 3D PCA score plots. (c) OPLS-DA score plots. (d) Variable Importance in Projection (VIP) scores of OPLS-DA. (e) Results of Permutation Tests (n = 1000) Confirming the robustness and validity of the OPLS-DA Model.

Fig. 2

Comparative Analysis of Metabolic Profiles Between Williams Syndrome (WS) and Healthy Control Groups. (a) The volcano plot analysis identified significant changes in 15 metabolites. At the top, 3 out of the 40 detected amino acids were significantly upregulated. At the bottom, of the 22 detected organic acids, 4 were significantly downregulated and 8 were significantly upregulated. Differential metabolites were defined as those with a fold change > 1.5 in WS compared to healthy controls. A threshold of VIP > 1.0 and FDR < 0.05 was used to distinguish differential metabolites from non-significant ones. (b) Hierarchical clustering of Spearman’s rank correlation of change in metabolite levels. Clusters 1–4 were selected based on distinct correlation patterns among the features, as well as significant differences observed when compared to the control group. Red represents positive correlations and blue represents negative correlations. (c) Hierarchical clustering analysis demonstrates distinctive metabolic profiles between WS and healthy control groups. (d) The heatmap displays differences in the top 25 metabolites with the most significant changes between WS and healthy controls.

Fig. 3

Metabolomics pathway analysis (MetPA). (a) MetPA bubble plots (b) Network view of MetPA.