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Neural Biomarkers Distinguish Severe From Mild Autism Spectrum Disorder Among High-Functioning Individuals.

ABSTRACT: Several previous studies have reported atypicality in resting-state functional connectivity (FC) in autism spectrum disorder (ASD), yet the relatively small effect sizes prevent us from using these characteristics for diagnostic purposes. Here, canonical correlation analysis (CCA) and hierarchical clustering were used to partition the high-functioning ASD group (i.e., the ASD discovery group) into subgroups. A support vector machine (SVM) model was trained through the 10-fold strategy to predict Autism Diagnostic Observation Schedule (ADOS) scores within the ASD discovery group (r = 0.30, P < 0.001, n = 260), which was further validated in an independent sample (i.e., the ASD validation group) (r = 0.35, P = 0.031, n = 29). The neuroimage-based partition derived two subgroups representing severe versus mild autistic patients. We identified FCs that show graded changes in strength from ASD-severe, through ASD-mild, to controls, while the same pattern cannot be observed in partitions based on ADOS score. We also identified FCs that are specific for ASD-mild, similar to a partition based on ADOS score. The current study provided multiple pieces of evidence with replication to show that resting-state functional magnetic resonance imaging (rsfMRI) FCs could serve as neural biomarkers in partitioning high-functioning autistic individuals based on their symptom severity and showing advantages over traditional partition based on ADOS score. Our results also indicate a compensatory role for a frontocortical network in patients with mild ASD, indicating potential targets for future clinical treatments.

SUBMITTER: Chen D

PROVIDER: S-EPMC8134539 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Impairments in social communication (coupled with intact nonsocial language skills) are common in autism spectrum disorder (ASD). However, the neural correlates of these social communication deficits in adolescents and young adults with ASD are not fully understood. The communication checklist self-report (CC-SR) was administered to adolescents and young adults with ASD (n = 52) and typically developing (TD) controls (n = 64) to assess structural-language, pragmatic-language, and social-engagement. One high-resolution T1-weighted structural image was obtained from each participant. FreeSurfer was used to quantify cortical thickness. A main effect of diagnosis, with the ASD group performing worse than the TD group on all three CC-SR scales, and a diagnosis by scale interaction, driven by low social-engagement self-ratings in the ASD group, were found. There were also group differences in the relationship between scores on two of the three CC-SR scales and cortical thickness in multiple regions (pragmatic-language: left rostral frontal; social-engagement: left medial prefrontal). These interactions were driven by poorer self-ratings of language/social skills associated with decreased cortical thickness in the ASD group, while in the TD group worse self-ratings were associated with thicker cortex. Self-ratings of language/social-communication were lower in the ASD than the TD group. Moreover, language/social-communication self-ratings showed a different relationship with cortical thickness for the ASD and TD groups in the left inferior frontal region for pragmatic language ratings and the left medial prefrontal cortex for social engagement ratings. These findings suggest thinner cortex is associated with more impaired pragmatic language and social communication abilities in ASD. Autism Res 2018, 11: 1175-1186. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The present study examines the associations between brain structure and language/social communication ability in adolescents and young adults with autism spectrum disorder (ASD) as compared to neurotypical adolescents and young adults. We utilized thickness of the cerebral cortex as a measure of brain structure, and we found different correlations between language or social communication ability and cortical thickness in distinct regions for the ASD and TD groups. These findings suggest that for regions implicated in language/social communication ability, decreased cortical thickness is associated with more impaired pragmatic language and social communication abilities in ASD.

Project description:BackgroundEarly identification and treatment of individuals with autism spectrum disorder (ASD) improves outcomes, but specific evidence needed to individualize treatment recommendations is lacking. Biomarkers that could be routinely measured within the clinical setting could potentially transform clinical care for patients with ASD. This demonstration project employed collection of biomarker data during regular autism specialty clinical visits and explored the relationship of biomarkers with clinical ASD symptoms.MethodsEighty-three children with ASD, aged 5-10 years, completed a multi-site feasibility study integrating the collection of biochemical (blood serotonin, urine melatonin sulfate excretion) and clinical (head circumference, dysmorphology exam, digit ratio, cognitive and behavioral function) biomarkers during routine ASD clinic visits. Parents completed a demographic survey and the Aberrant Behavior Checklist-Community. Cognitive function was determined by record review. Data analysis utilized Wilcoxon two-sample tests and Spearman correlations.ResultsParticipants were 82% male, 63% White, 19% Hispanic, with a broad range of functioning. Group means indicated hyperserotonemia. In a single regression analysis adjusting for race and median household income, higher income was associated with higher levels of blood serotonin and urine melatonin sulfate excretion levels (p = 0.004 and p = 0.04, respectively). Melatonin correlated negatively with age (p = 0.048) and reported neurologic problems (p = 0.02). Dysmorphic status correlated with higher reported stereotyped behavior (p = 0.02) and inappropriate speech (p = 0.04).ConclusionThis demonstration project employed collection of multiple biomarkers, allowed for examination of associations between biochemical and clinical measures, and identified several findings that suggest direction for future studies. This clinical research model has promise for integrative biomarker research in individuals with complex, heterogeneous neurodevelopmental disorders such as ASD.

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Neural Biomarkers Distinguish Severe From Mild Autism Spectrum Disorder Among High-Functioning Individuals.

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