Metabolomic Profiling in Children with Sleep Disorders: An Exploratory Pilot Study - Roberta Pintus; M. Evangelisti; C. Piras; M. Arpinelli; F. Vassilios; A. Noto; G. Di Nardo; Maria Pia Villa (Journal of Clinical Medicine, 2026)
Objectives: To analyze the metabolomic profile of children with sleep disorders to understand whether there are distinct and specific metabolic patterns related to the severity and type of sleep disorders (neurological or respiratory). Materials and Methods: This is an observational pilot study. Patients referred to our department for sleep disorders—both neurological and breath-related sleep disturbances—were enrolled. All patients received an anamnestic interview, clinical evaluation, polysomnographic sleep study and urine collection for the metabolomic analysis. Results: Obstructive sleep apnea (OSA) patients were divided into mild and moderate while the third group was represented by patients with parasomnias. The oxalic acid and ribose increased in moderate OSA and pavor compared to mild patients, while 3-hydroxypropionic decreased. Furthermore, the pyroglutamic acid, aminomalonica acid, urea, p-cresol, glycine, 4-hydroxyphenyl acetate, citric acid and ethanolamine increased in moderate OSA patients with respect to mild ones. Finally, hippuric acid and glutamic acid decreased in moderate patients compared to mild ones. The enrichment analysis revealed that urea cycle, tryptophan metabolism, glucose-alanine cycle, glutathione metabolism and beta-alanine metabolism were the most significantly discriminant pathways between OSA patients, while the pentose phosphate pathway, propanoate metabolism, Warburg effect, citric acid cycle and transfer of acetyl group into mitochondria were the most significantly discriminant pathways between mild OSA and pavor patients. Conclusions: our data reveal interesting correlations between metabolomics and sleep disorders that deserve further investigations in larger cohorts of patients and the integration of different approaches to enhance our understanding of the field and guide clinicians toward precise and personalized patient management.