Brain-based biomarkers of restricted and repetitive behaviors in toddlers at risk for autism

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Abstract Autism spectrum disorder (ASD) affects one in 44 children. 1 Early diagnosis is critical for optimizing outcomes, yet children are not typically diagnosed until 4 years of age.2 In concert with early behavioral signs, early neural markers could identify toddlers at risk of developing ASD to aid earlier diagnosis and targeted interventions. Neuroimaging studies have primarily examined structural brain abnormalities in toddlers at high risk of developing ASD3. A growing body of work provides evidence for functional brain network connectivity alterations in older children with ASD (7-12 years of age).4 While innovative dynamic functional magnetic resonance imaging (fMRI) methods reveal candidate brain networks of dysfunction underlying the heterogeneity of the disorder and symptom severity in older children with ASD,567,8no study to date has evaluated the relationship between brain network dynamics and behavioral outcomes in toddlers with ASD. Restricted and repetitive behaviors (RRBs), core symptoms of ASD,9 are particularly understudied. The goal of this project is to identify early functional brain biomarkers of ASD and brain-behavior relationships with RRB outcomes across mixed clinical and typically developing (TD) groups. This study will utilize a dataset previously collected by the UCSD ACE Center comprised of toddlers (12-36 months, n = 231) who were identified as either TD or at-risk for a developmental disability using an early screening form (Communication and Symbolic Behavior Scales Developmental Profile; CSBS-DP).10Some toddlers were later diagnosed with ASD (n = 89), TD (n = 70), other diagnosis (n = 72; Language Delay, Developmental Delay, and Autism Features). Since the sample includes multiple diagnostic groups, this dataset offers a unique opportunity to examine early brain biomarkers for ASD and RRBs across diagnostic categories, as envisioned by the Research Domain Criteria (RDoC) approach.11 Early behavioral indicators alone do not always clearly indicate which children will go onto to develop ASD.12 The results from this study may lead to the development of reliable biomarkers to identify children at risk for ASD in concert with overt behavioral signs of the disorder. Neural biomarkers of ASD and RRBs will in turn lead to earlier and more efficient diagnosis and treatments. This work builds upon the applicant’s previous research experience at the UCSD ACE Center collecting neuroimaging data from toddlers.13 The applicant has previously examined dynamic brain biomarkers of RRB symptoms in older children with ASD (8-12 yo),7,14–16 reviewed the brain biomarker literature in toddlers with ASD,3analyzed large lifespan neuroimaging datasets (n = 601), and gained a foundation in statistics and clinical neuroscience. Through formal coursework and individual meetings, the applicant plans to engage in four major areas of training: (1) cutting-edge analyses to assess brain dynamics using functional neuroimaging data, (2) sophisticated statistical approaches for modelling longitudinal data, (3) considerations for conducting research with young children at risk for autism, and (4) career development.