Research into the causes and treatments of Autism Spectrum Disorders (ASD) are limited by extreme heterogeneity in how children and adults present at our clinics. There is an increasing appreciation for inattention and hyperactivity/impulsivity symptoms as a contributing factor to heterogeneity in ASD. Our work shows that the presence of these symptoms leads to worse outcomes (more maladaptive behaviors and poorer daily living skills). Clinicians have adapted diagnostics and treatments from Attention Deficit/Hyperactivity Disorder (ADHD), but this approach has shown reduced efficacy of methylphenidate (i.e., ritalin) treatment in children with ASD. This suggests an alternative pathophysiology for the ADHD symptoms. The proposed study will use functional MRI and rest state MRI along with novel, data-driven methods to examine brain networks disrupted in children with ASD and ADHD symptoms. This approach has two distinct advantages: 1) a basal ganglia-thalamocortical loop tapped by response inhibition is well- defined and known to be disrupted in children with prototypical ADHD;and 2) our data-driven methods make no a priori assumptions about potential sub-groups identified or connectivity among brain regions. We will examine the presence of ADHD symptoms and inhibitory control in everyday settings in 8-10-year-old children with ASD (n=30) and typically developing controls (n=15). These children will complete fMRI and resting state scans to examine functional neuroanatomy and functional connectivity of response inhibition. We hypothesize that our data-driven variance methods will identify one pattern of children with ASD and few ADHD symptoms and two patterns of ASD subgroups with significant ADHD symptoms: one group with fMRI response inhibition activation patterns similar to prototypical ADHD children, and one group with patterns distinct from prototypical ADHD. We hypothesize that functional connectivity among networks involved in response inhibition will have greater intra-network correlations and lower inter-network correlations as ADHD symptoms and everyday inhibitory control impairments decrease in the ASD group. If successful, we will identify novel biologically- based subgroups to characterize ASD, as well as identify novel treatment targets for ADHD symptoms that can be tested in future therapeutic trials.
Research into the causes and treatments of ASD is limited by extreme heterogeneity, and no studies to our knowledge have attempted to reduce this heterogeneity at the neural level by examining the impact of comorbid ADHD symptoms. Also, our use of new, data-driven analysis methods will identify subgroups of ASD that is based on biology. If successful, these new subgroups of children with ASD will reduce heterogeneity for future genetic investigations and serve as a guide for future therapeutic trials for reducing ADHD symptoms in ASD.
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