Identification of metabolic pathway disturbances using multimodal metabolomics in autistic disorders in a Middle Eastern population

Abstract We analyzed for the first time the metabolic profile of Lebanese children affected by autistic disorders to compare this profile to other metabolomics studies and to identify the associated metabolic disturbances. Urine samples of 40 patients with Autism spectrum disorder (ASD) and 40 healthy matched controls were analyzed using nuclear magnetic resonance (NMR) and liquid chromatography coupled to high-resolution mass spectrometry (LC–MS). Multivariate analysis on analytical data fusion was conducted on the training set of 50 urine samples, and then validated with a test set of 30 samples, this repeated 10 times. The model was also evaluated using a receiver operating characteristic curve showing a specificity and a sensitivity of 86% and 80%, respectively. Among the most significant metabolites that contributed to the discrimination between ASD and controls, we confirmed the perturbations of tyrosine, 2-hydroxybutyrate, creatine and glutamate. We found new metabolites such as trigonelline, cysteic acid and guanine. We found metabolic perturbations including amino acids, carbohydrates and oxidative stress pathways which added value for the contribution of known metabolic disturbances in ASD observed in populations of other ethnic and geographic origins.