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Updated: Jun 12, 2026

One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure
Published on: June 25, 2010
Metabolomic Profiles in Down Syndrome: A Scoping Review of Convergent and Context-Dependent Patterns
Carolina Gastélum Guerrero1, Alma M Guadrón Llanos2, Loranda Calderón Zamora3
1Posgrado en Ciencias en Biomedicina Molecular, Facultad de Medicina, Universidad Autónoma de Sinaloa, Culiacán, Sinaloa, Mexico.
Background:
Individuals with Down syndrome (DS) face a high burden of health complications, yet the molecular underpinnings remain incompletely defined.
Objective:
The objective of this study is to systematically identify metabolomic changes in individuals with DS and how they relate to DS-associated conditions.
Methods:
A scoping review of the literature was performed across four online databases to identify studies profiling metabolites in people with DS using untargeted or targeted metabolomics procedures. The findings were narratively synthesised to provide a comprehensive overview of patterns of convergence and variability across studies.
Results:
Thirty-four studies examining metabolites in individuals with DS were identified. The combined findings revealed widespread disruptions in energy (e.g., tricarboxylic acid cycle intermediates and acylcarnitines), one-carbon (e.g., methionine and the SAM/SAH axis), amino acid (e.g., tryptophan-kynurenine and glutamate/GABA) and lipid (e.g., phospholipids and sphingolipids) metabolism, along with changes in immune and neurotransmitter pathways. These metabolic alterations are associated with phenotypic variability and comorbidities in DS. However, the evidence reflects partially convergent and context-dependent patterns, with substantial variability across studies.
Conclusion:
Metabolic disturbances are common in DS, suggesting candidate metabolic signatures that still require independent replication and validation. Current evidence is predominantly cross-sectional and associative, limiting causal inference. Integrating metabolomics with multi-omics approaches may enhance the understanding of DS-related health issues and support future translation into clinical applications.
