A brain structural connectivity biomarker for autism spectrum disorder diagnosis in early childhood.

Background: Autism spectrum disorder (ASD) is associated with altered brain development, but it is unclear which specific structural changes may serve as potential diagnostic markers, particularly in young children at the age when symptoms become fully established. Furthermore, such brain markers need to meet the requirements of precision medicine and be accurate in aiding diagnosis at an individual rather than only a group level. Objective: This study aimed to identify and model brain-wide differences in structural connectivity using diffusion tensor imaging (DTI) in young ASD and typically developing (TD) children. Methods: A discovery cohort including 93 ASD and 26 TD children and two independent validation cohorts including 12 ASD and 9 TD children from three different cities in China were included. Brain-wide (294 regions) structural connectivity was measured using DTI (fractional anisotropy, FA) together with symptom severity and cognitive development. A connection matrix was constructed for each child for comparisons between ASD and TD groups. Pattern classification was performed on the discovery dataset and the resulting model was tested on the two independent validation datasets. Results: Thirty-three structural connections showed increased FA in ASD compared to TD children and associated with both autistic symptom severity and impaired general cognitive development. The majority (29/33) involved the frontal lobe and comprised five different networks with functional relevance to default mode, motor control, social recognition, language and reward. Overall, classification achieved very high accuracy of 96.77% in the discovery dataset, and 91.67% and 88.89% in the two independent validation datasets. Conclusions: Identified structural connectivity differences primarily involving the frontal cortex can very accurately distinguish novel individual ASD from TD children and may therefore represent a robust early brain biomarker which can address the requirements of precision medicine.

The salience of competing nonsocial objects reduces gaze toward social stimuli, but not the eyes, more in typically developing than autistic boys.

Decreased attention to social information is considered an early emerging symptom of autism spectrum disorder (ASD), although the underlying causes remain controversial. Here we explored the impact of nonsocial object salience on reduced attention to social stimuli in male ASD compared with typically developing (TD) children. Correlations with blood concentrations of neuropeptides linked with social cognition were also investigated. Eye-tracking was performed in 102 preschool-aged boys (50 ASD, 52 TD) using a paradigm with social (faces) versus nonsocial (objects) stimuli presented in pairs in two conditions where nonsocial stimulus salience was varied. Basal oxytocin (OXT) and vasopressin concentrations were measured in blood. Compared with TD boys those with ASD viewed social stimuli less only when they were paired with low-salience nonsocial objects. Additionally, boys with ASD spent less time than TD ones viewing facial features, particularly the eyes. In TD boys, OXT concentrations and cognitive development scores were positively associated with time spent viewing the eye region, whereas for boys with ASD associations with time spent viewing faces were negative. Reduced gaze toward social stimuli in ASD relative to TD individuals may therefore be influenced by how salient the paired nonsocial objects are for the latter. On the other hand, reduced interest in the eyes of faces in boys with ASD is not influenced by how salient competing nonsocial stimuli are. Basal OXT concentrations and cognitive development scores are predictive of time spent viewing social stimuli in TD boys (eyes) and those with ASD (faces) but in the opposite direction. LAY SUMMARY: Children with autism exhibit reduced attention to social paired with nonsocial stimuli compared to typically developing children. Using eye-tracking we show this difference is due to typically developing rather than autistic boys being more influenced by how interesting competing nonsocial objects are. On the other hand, reduced time looking at the eyes in autistic relative to typically developing boys is unaffected by nonsocial object salience. Time spent viewing social stimuli is associated with cognitive development and blood levels of oxytocin.

Comparison of the Metabolic Profiles in the Plasma and Urine Samples Between Autistic and Typically Developing Boys: A Preliminary Study.

Background: Autism spectrum disorder (ASD) is defined as a pervasive developmental disorder which is caused by genetic and environmental risk factors. Besides the core behavioral symptoms, accumulated results indicate children with ASD also share some metabolic abnormalities. Objectives: To analyze the comprehensive metabolic profiles in both of the first-morning urine and plasma samples collected from the same cohort of autistic boys. Methods: In this study, 30 autistic boys and 30 tightly matched healthy control (HC) boys (age range: 2.4~6.7 years) were recruited. First-morning urine and plasma samples were collected and the liquid chromatography-mass spectrometry (LC-MS) was applied to obtain the untargeted metabolic profiles. The acquired data were processed by multivariate analysis and the screened metabolites were grouped by metabolic pathway. Results: Different discriminating metabolites were found in plasma and urine samples. Notably, taurine and catechol levels were decreased in urine but increased in plasma in the same cohort of ASD children. Enriched pathway analysis revealed that perturbations in taurine and hypotaurine metabolism, phenylalanine metabolism, and arginine and proline metabolism could be found in both of the plasma and urine samples. Conclusion: These preliminary results suggest that a series of common metabolic perturbations exist in children with ASD, and confirmed the importance to have a comprehensive analysis of the metabolites in different biological samples to reveal the full picture of the complex metabolic patterns associated with ASD. Further targeted analyses are needed to validate these results in a larger cohort.