Urinary 11-metabolite panel distinguishes ADHD from controls in children
Investigators analyzed urinary metabolomic profiles from 67 children with ADHD and 98 healthy controls using NMR and UPLC-QTOF-MS to evaluate links with organophosphate pesticide exposure and oxidative stress. The study identified significant alterations in tricarboxylic acid cycle and amino acid metabolism, with metabolite levels positively correlating with exposure and stress biomarkers. An 11-compound urinary panel demonstrated strong discriminatory performance, achieving an AUC of 0.8450 in the discovery phase and 0.8748 in validation. These results highlight a potential laboratory-based metabolomic signature for ADHD assessment, though larger multi-center studies are required before clinical adoption.
The original study
Targeted and Untargeted Urinary Metabolomic Analyses of Organophosphate Pesticides Exposure and Attention-Deficit/Hyperactivity Disorder in Children.
- Authors
- Tseng HY, Lo CJ, Subramani B, Hou JW, Yu CJ, Fang TY, et al.
- Journal
- Metabolomics : Official journal of the Metabolomic Society
- Type
- Journal Article
- PMID
- 42517949
Original abstract
INTRODUCTION: Exposure to organophosphate pesticides (OPs) has been associated with increased oxidative stress and a higher risk of attention-deficit/hyperactivity disorder (ADHD). However, metabolic insights underlying ADHD and the potential pathophysiological role of OPs exposure remain limited. OBJECTIVE: This study characterized urinary metabolomic profiles associated with ADHD and examined their associations with OPs exposure and oxidative stress. METHODS: Urinary metabolites from 67 children with ADHD and 98 controls were analyzed using nuclear magnetic resonance (NMR) spectroscopy and ultra-perforamnce liquid chromatography quadrupole time-of-flight mass spectrometry analysis (UPLC-QTOF-MS). Dimethyl phosphate (DMP) and 4-hydroxy-2-nonenal-mercapturic acid (HNE-MA) were used as biomarkers of OPs exposure and oxidative stress, respectively. Children were classified into high- and low-exposure/concentration groups based on DMP or HNE-MA levels. RESULTS: Urinary metabolomic profiles differed significantly between children with ADHD and controls. Several metabolites also differed between children with high and low DMP or HNE-MA levels. Metabolites involved in the tricarboxylic acid cycle were significantly higher in ADHD children and positively correlated with both DMP and HNE-MA. Pathway analysis suggested alterations in energy-related and amino acid metabolic pathways. Stepwise logistic regression and receiver operating characteristic curve analysis identified an 11-compound biomarker panel with good discriminatory performance in the discovery (AUC: 0.8450) and validation (AUC: 0.8748) stages. CONCLUSION: This metabolomic analysis suggests that OPs exposure and oxidative stress may be associated with metabolic changes in ADHD, particularly in energy metabolism and amino acid pathways. The identified biomarker panel may help distinguish children with ADHD from controls. Larger studies with multiple exposure assessments are warranted.