Autism Spectrum Disorders (ASD) are a group of developmental disorders caused by environmental and genetic factors. Diagnosis is based on behavioral and developmental signs detected before 3 years of age with no reliable biological marker. The purpose of this study was to evaluate the potential use of a 2D NMR-based approach to express the global biochemical signature of autistic individuals compared to normal controls. This technique has greater spectral resolution than to 1D (1)H NMR spectroscopy, which is limited by overlapping signals. The urinary metabolic profiles of 30 autistic and 28 matched healthy children were obtained using a (1)H-(13)C NMR-based approach. The data acquired were processed by multivariate orthogonal partial least-squares discriminant analysis (OPLS-DA). Some discriminating metabolites were identified: β-alanine, glycine, taurine and succinate concentrations were significatively higher, and creatine and 3-methylhistidine concentrations were lower in autistic children than in controls. We also noted differences in several other metabolites that were unidentified but characterized by a cross peak correlation in (1)H-(13)C HSQC. Statistical models of (1)H and (1)H-(13)C analyses were compared and only 2D spectra allowed the characterization of statistically relevant changes [R(2)Y(cum)=0.78 and Q(2)(cum)=0.60] in the low abundance metabolites. This method has the potential to contribute to the diagnosis of neurodevelopment disorders but needs to be validated on larger cohorts and on other developmental disorders to define its specificity.
Keywords: Autism spectrum disorders; HSQC NMR spectroscopy; Metabolomics; OPLS-DA; Urinary metabolites.
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