Under the diagnostic umbrella of Autism Spectrum Disorder (ASD), tremendous variability is observed across affected individuals, likely reflecting distinct etiological mechanisms. Yet, most research to date has treated ASD as a unitary condition, typically comparing individuals with ASD to matched controls. This strategy has not only hindered our progress in unraveling the neurobiological mechanisms that give rise to ASD symptomatology but, importantly, such an approach also undermines the potential of translational research to contribute to `precision medicine' in ASD. In this project, we will take a critical first step toward dissecting the significant heterogeneity observed in ASD by combining state-of-the-art imaging methods, novel approaches to account for genetic susceptibility, and a deep phenotypic characterization of a large sample of youth with ASD. Specifically, we will collect and analyze a rich dataset of brain-based measures (resting-state and task-related fMRI) of unparalleled resolution and quality in order to characterize individual differences in brain network properties and examine how these may relate to a rich phenotypic battery of measures tapping into key domains of interest in our center. Using innovative fMRI activation paradigms as neural assays of social attention, sensory responsivity, and reward function, we will also examine how patterns of brain responses in associated neural circuits co-vary within and between individuals in order to determine how neural over- responsivity to sensory stimuli impacts neural processing of socially relevant stimuli, and assess how distinct neural endophenotypes of social, sensory, and reward responsivity relate to altered connectivity in functional brain networks and behavioral phenotypes. Lastly, building upon our prior imaging-genetics studies, we will examine how polygenic risk, as well as risk variants on selected ASD-associated polymorphisms, influence brain function, network connectivity, and core ASD symptomatology. Our overarching hypothesis is that both distinct and shared neuroendophenotypes will be identified based on different brain function and connectivity metrics and that these will map onto varying dimensions of social and sensory responsivities as manifested at the behavioral and neural level. We further expect that higher polygenic risk will be predictive of increasingly aberrant patterns of brain activity and connectivity as well as overall ASD symptom severity, whereas genetic variance on specific ASD-associated polymorphisms will selectively modulate brain function and network connectivity in brain circuits where these ASD risk genes are expressed. By employing (a) cutting-edge imaging methods to examine brain function and connectivity, (b) innovative paradigms to relate social attention and motivation to sensory processing atypicalities, (c) novel approaches to integrate genetic risk with neural and behavioral phenotypes, and (d) sophisticated data-analytic strategies to sensibly stratify our ASD sample, the proposed studies will foster our understanding of the neural mechanisms underlying heterogeneity in ASD thereby ultimately contributing to the development of more personalized and efficacious interventions.
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