Blood and urine metabolomics in children with autism spectrum disorder: biomarker discovery and clinical translation within a multi-pathway convergence framework
Year: 2026
Type: article
Abstract: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and restricted, repetitive behaviors, and is diagnosed in an increasing proportion of children worldwide. Diagnosis is currently based on standardized behavioral observation and developmental history, and no validated biological marker is yet available for routine clinical use. Metabolomics, a key branch of systems biology, captures the downstream metabolic phenotype resulting from gene–environment interactions, offering a complementary avenue for identifying candidate biomarkers and elucidating mechanisms in ASD. In recent years, blood- and urine-based metabolomic studies have identified alterations across several metabolic domains in children with ASD—amino acid and lipid metabolism, oxidative stress and antioxidant defense, gut-microbiota-derived metabolites, mitochondrial/energy metabolism, and purine metabolism. Nevertheless, cross-study consistency of reported biomarkers remains limited, and methodological challenges—including small sample sizes, analytical platform heterogeneity, and inadequate control of confounding factors—constrain the translation of research findings into clinical diagnostic tools. This narrative review integrates the latest evidence from blood and urine metabolomics within a “multi-pathway convergence” framework, constructing a six-domain panoramic map of metabolic disturbances in children with ASD, evaluating the complementarity and convergent value of dual-biofluid biomarkers, delineating the metabolic features with the most reproducible cross-biofluid patterns, and proposing a phased translational pathway from biomarker discovery to clinical diagnostic panel development.
Source: Frontiers in Psychiatry
Authors: Fengzhen Guo, Yi Zhang, Yamin Kong, Bingxiang Ma
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7225787771