Among the many race-based health disparities that have persistently plagued the US population,1 the disproportionate burden of adverse neurodevelopmental outcomes to Black children affected by autism spectrum disorder (ASD) is particularly devastating given its major lifelong consequences. Recently, in 3 successive reports from the Autism and Developmental Disabilities Monitoring (ADDM) program of the US Centers for Disease Control and Prevention (CDC) (birth cohort years 2014, 2016, and 2018), we and our collaborators reported that although the prevalence of community-diagnosed ASD had equalized for Black and non-Hispanic White (NHW) children in the United States, there has persisted a pronounced racial disparity in the proportion of ASD-affected children with comorbid intellectual disability (ID), on the order of 50% for Black children with ASD vs 20% for White children with ASD.2 Here, we provide data to support the following: much earlier diagnosis is possible; early diagnosis alone is not likely to close the ID comorbidity disparity; and judicious efforts over care as usual are necessary to ensure that Black children have access to timely implementation of developmental therapy, for which we observed promising associations with improved cognitive and adaptive outcomes in our sample.

Patients with autism spectrum disorders and intellectual disability can be clinically complex and often have limited access to psychiatric care. Because little is known about post-graduate clinical education in autism spectrum disorder and intellectual disability, we surveyed training directors of child and adolescent psychiatry fellowship programs. On average, child and adolescent psychiatry directors reported lectures of 3 and 4 h per year in autism spectrum disorder and intellectual disability, respectively. Training directors commonly reported that trainees see 1-5 patients with autism spectrum disorder or intellectual disability per year for outpatient pharmacological management and inpatient treatment. Overall, 43% of directors endorsed the need for additional resources for training in autism spectrum disorder and intellectual disability, which, coupled with low didactic and clinical exposure, suggests that current training is inadequate.

Male sex is a strong risk factor for autism spectrum disorder (ASD). The leading theory for a "female protective effect" (FPE) envisions males and females have "differing thresholds" under a "liability threshold model" (DT-LTM). Specifically, this model posits that females require either a greater number or larger magnitude of risk factors (i.e., greater liability) to manifest ASD, which is supported by the finding that a greater proportion of females with ASD have highly penetrant genetic mutations. Herein, we derive testable hypotheses from the DT-LTM for ASD, investigating heritability, familial recurrence, correlation between ASD penetrance and sex ratio, population traits, clinical features, the stability of the sex ratio across diagnostic changes, and highlight other key prerequisites. Our findings reveal that several key predictions of the DT-LTM are not supported by current data, requiring us to establish a different conceptual framework for evaluating alternate models that explain sex differences in ASD.

Brain differences linked to autism spectrum disorder (ASD) can manifest before observable symptoms. Studying these early neural precursors in larger and more diverse cohorts is crucial for advancing our understanding of developmental pathways and potentially facilitating earlier identification. EEG is an ideal tool for investigating early neural differences in ASD, given its scalability and high tolerability in infant populations. In this context, we integrated EEG into an existing multi-site MRI study of infants with a higher familial likelihood of developing ASD. This paper describes the comprehensive protocol established to collect longitudinal, high-density EEG data from infants across five sites as part of the Infant Brain Imaging Study (IBIS) Network and reports interim feasibility and data quality results. We evaluated feasibility by measuring the percentage of infants from whom we successfully collected each EEG paradigm. The quality of task-free data was assessed based on the duration of EEG recordings remaining after artifact removal. Preliminary analyses revealed low data loss, with average in-session loss rates at 4.16 % and quality control loss rates at 11.66 %. Overall, the task-free data retention rate, accounting for both in-session issues and quality control, was 84.16 %, with high consistency across sites. The insights gained from this preliminary analysis highlight key sources of data attrition and provide practical considerations to guide similar research endeavors.