Brittany G. Travers, Ph.D. - US grants

PROJECT SUMMARY/ABSTRACT The brainstem is a complex and early-developing brain region that is responsible for sensory, motor, autonomic, and critical-for-life functions. The first biology-based hypothesis of autism spectrum disorder (ASD) suggested that the reticular formation of the brainstem may be a root cause of ASD symptoms. However, technological barriers have prevented the field from being able to reliably characterize substructures of the brainstem in vivo in children. Excitingly, new technological advances now allow us to examine the microstructural properties of the brainstem's nuclei and individual white matter tracts. The overall scientific premise of this proposal is that brainstem substructures may hold key insights into overall brain development and into the underpinnings of ASD. The overall objective of the proposed work is to identify specific white matter tracts and nuclei within the brainstem that subserve the comorbid sensorimotor and core symptom challenges of ASD and to contextualize brainstem properties in reference to other brain regions implicated in ASD. Given the functions of the brainstem, we hypothesize that the microstructural properties of the brainstem substructures are associated with comorbid sensorimotor symptoms and core social-communication and repetitive-behavior symptoms implicated in ASD. We further hypothesize that the brainstem relates distinctly to other brain regions in ASD, due to the brainstem's role in early brain development. Guided by strong preliminary data, these hypotheses will be tested through three specific aims: 1) Determine extent to which the microstructure of brainstem substructures is associated with individual differences in comorbid sensorimotor symptoms; 2) Determine extent to which microstructure of brainstem substructures is associated with individual differences in core social-communication and repetitive- behavior symptoms; and 3) Identify the distinct correspondence among brainstem substructures and the surrounding brain. A key innovation is that we will accomplish these aims by applying a diffusion-weighted imaging (DWI) technique that addresses the previous challenges of brainstem imaging to provide a clear and anatomically precise image of the brainstem and its substructures. With this technique, we will quantify the microstructure of brainstem substructures (and surrounding brain) in 80 children with ASD (6-9 years old) and 80 age-matched children with typical development. Standardized assessments will characterize sensorimotor and core symptom profiles. The successful completion of this research will provide a quantitative characterization of brainstem substructures in relation to the comorbid sensorimotor features and core symptoms in ASD, and it will provide a quantitative characterization of brainstem substructures in ASD in relation to overall brain metrics. These contributions will be significant because they will advance the understanding of the neurobiological basis for ASD, elucidate the neurological underpinnings of the comorbid sensorimotor challenges and core symptoms in ASD, and provide quantitative biomarkers to be used as outcome measures in clinical trials.

PROJECT SUMMARY/ABSTRACT Autism spectrum disorder (ASD) frequently co-occurs with attention-deficit/hyperactivity disorder (ADHD). Individuals with ASD have a 22 times greater risk of having ADHD compared with those without ASD, and recent evidence suggests that ASD co-occurs with ADHD at a higher rate than with any other mental health disorder. The negative impact of this co-occurrence on the individual is substantial; those presenting with both disorders (ASD/+ADHD) show lower cognitive functioning, more severe social impairment, and greater delays in adaptive functioning than individuals presenting with ASD without ADHD (ASD/-ADHD). The overall rationale of this proposal is that a multidisciplinary integration of genomic, neuroimaging, behavioral, human stem cell, and machine learning approaches may reveal key insights into the mechanisms underlying the debilitating and common co-occurrence of ASD/+ADHD in children. The overall objective of the proposed work is to identify the etiological mechanisms underlying ASD/-ADHD and ASD/+ADHD. We hypothesize that children with ASD/+ADHD will have unique genetic, molecular, cellular, brain structural, and neurobehavioral features compared to children with ASD/-ADHD. This hypothesis will be tested through four specific aims: 1) to identify prospective longitudinal behavioral and neuroimaging predictors of ASD/+ADHD compared to ASD/-ADHD; 2) to characterize molecular and cellular features of neurons differentiated from induced pluripotent stem cells (iPSCs) generated from individuals with ASD/-ADHD and ASD/+ADHD; 3) to identify and quantify the overlapping genetic architectures for ASD and ADHD; and 4) to develop a machine learning model integrating multi-modal data to predict ASD/-ADHD and ASD/+ADHD. Innovations of the proposed study include the application of state-of-the-art neuroimaging (optimized to facilitate brain imaging in difficult-to-scan populations), a prospective longitudinal design (to account for individual differences in the developmental course of ADHD symptoms as children with ASD age), iPSCs (to identify distinct cellular and molecular profiles), novel statistical methods for multi-phenotype modeling and gene identification, and an innovative multiview machine learning approach that integrates multi-modal data to identify the functional genomic elements and gene regulatory networks that underlie the emergence of ASD/+ADHD. This project is highly responsive to the IDDRC RFA, as it involves comprehensive -omic approaches to markedly increase our understanding of more than a single IDD condition to improve diagnosis and to facilitate future biomarker development. The knowledge gained will be significant because it can be used to inform a far more powerful multi-modal assessment of ASD and ADHD that integrates behavioral observations with technically advanced (but highly feasible) biological assays. These findings will have important implications for early screening and diagnosis of ASD and ADHD and will provide distinct biology-based targets for future biomarker development.