Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. Aims of this study were to characterize a metabolic signature of ASD, and to evaluate multi-platform analytical methodologies in order to develop predictive tools for diagnosis and disease follow up. Urines were analyzed using: 1H- and 1 H-13C-NMR-based approaches and LC-HRMS-based approaches (ESI+ and ESI- on a HILIC and C18 chromatography column). Data tables obtained from the six analytical modalities on a training set of 46 urines (22 autistic children and 24 controls) were processed by multivariate analysis (OPLS-DA). Prediction of each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and ROC curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLSDA model showed an enhanced performance (R 2Y(cum)=0.88, Q 2 (cum)=0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC=0.91, p-value 0.006). Metabolites that are most significantly different between autistic and control children (p<0.05) are indoxyl sulfate, N-\u2329-Acetyl-L-arginine, methyl guanidine and phenylacetylglutamine. This multi-modality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population

Methylphenidate et troubles du développement (étude de 5 enfants accueillis à l'hôpital de jour de Tours)

TOURS-BU Sciences Pharmacie (372612104) / SudocSudocFranceF

Pathologies pédopsychiatriques aux urgences pédiatriques de l'hôpital Clocheville

TOURS-BU Médecine (372612103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Description clinique et nosographique de la population du centre de ressources autisme de Tours depuis sa création en 2000 à l'aide d'outils spécifiques à l'enfant

TOURS-BU Médecine (372612103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Place de la psychopathologie dans la prise en charge des enfants et adolescents obèses

TOURS-BU Médecine (372612103) / SudocPARIS-BIUM (751062103) / SudocTOURS-Inst.Eur.Hist.Alimentation (372615207) / SudocSudocFranceF

La dyspraxie développementale de l'enfant

TOURS-BU Médecine (372612103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

La dyspraxie développementale de l'enfant

TOURS-BU Médecine (372612103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Voice acoustics allow classifying autism spectrum disorder with high accuracy

Abstract Early identification of children on the autism spectrum is crucial for early intervention with long-term positive effects on symptoms and skills. The need for improved objective autism detection tools is emphasized by the poor diagnostic power in current tools. Here, we aim to evaluate the classification performance of acoustic features of the voice in children with autism spectrum disorder (ASD) with respect to a heterogeneous control group (composed of neurotypical children, children with Developmental Language Disorder [DLD] and children with sensorineural hearing loss with Cochlear Implant [CI]). This retrospective diagnostic study was conducted at the Child Psychiatry Unit of Tours University Hospital (France). A total of 108 children, including 38 diagnosed with ASD (8.5 ± 0.25 years), 24 typically developing (TD; 8.2 ± 0.32 years) and 46 children with atypical development (DLD and CI; 7.9 ± 0.36 years) were enrolled in our studies. The acoustic properties of speech samples produced by children in the context of a nonword repetition task were measured. We used a Monte Carlo cross-validation with an ROC (Receiving Operator Characteristic) supervised k-Means clustering algorithm to develop a classification model that can differentially classify a child with an unknown disorder. We showed that voice acoustics classified autism diagnosis with an overall accuracy of 91% [CI95%, 90.40%-91.65%] against TD children, and of 85% [CI95%, 84.5%–86.6%] against an heterogenous group of non-autistic children. Accuracy reported here with multivariate analysis combined with Monte Carlo cross-validation is higher than in previous studies. Our findings demonstrate that easy-to-measure voice acoustic parameters could be used as a diagnostic aid tool, specific to ASD

Atypical sound discrimination in children with ASD as indicated by cortical ERPs

Abstract Background Individuals with autism spectrum disorder (ASD) show a relative indifference to the human voice. Accordingly, and contrarily to their typically developed peers, adults with autism do not show a preferential response to voices in the superior temporal sulcus; this lack of voice-specific response was previously linked to atypical processing of voices. In electroencephalography, a slow event-related potential (ERP) called the fronto-temporal positivity to voice (FTPV) is larger for vocal than for non-vocal sounds, resulting in a voice-sensitive response over right fronto-temporal sites. Here, we investigated the neurophysiological correlates of voice perception in children with and without ASD. Methods Sixteen children with autism and 16 age-matched typically developing children heard vocal (speech and non-speech) and non-vocal sounds while their electroencephalographic activity was recorded; overall IQ was smaller in the group of children with ASD. ERP amplitudes were compared using non-parametric statistical tests at each electrode and in successive 20-ms time windows. Within each group, differences between conditions were assessed using a non-parametric Quade test between 0 and 400 ms post-stimulus. Inter-group comparisons of ERP amplitudes were performed using non-paired Kruskal-Wallis tests between 140 and 180 ms post-stimulus. Results Typically developing children showed the classical voice-sensitive response over right fronto-temporal electrodes, for both speech and non-speech vocal sounds. Children with ASD did not show a preferential response to vocal sounds. Inter-group analysis showed no difference in the processing of vocal sounds, both speech and non-speech, but significant differences in the processing of non-vocal sounds over right fronto-temporal sites. Conclusions Our results demonstrate a lack of voice-preferential response in children with autism spectrum disorders. In contrast to observations in adults with ASD, the lack of voice-preferential response was attributed to an atypical response to non-vocal sounds, which was overall more similar to the event-related potentials evoked by vocal sounds in both groups. This result suggests atypical maturation processes in ASD impeding the specialization of temporal regions in voice processing