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Abstract Background Eye tracking (ET) is a powerful methodology for studying attentional processes through quantification of eye movements. The precision, usability, and cost-effectiveness of ET render it a promising platform for developing biomarkers for use in clinical trials for autism spectrum disorder (ASD). Methods The Autism Biomarkers Consortium for Clinical Trials conducted a multisite, observational study of 6–11-year-old children with ASD (n = 280) and typical development (TD, n = 119). The ET battery included: Activity Monitoring, Social Interactive, Static Social Scenes, Biological Motion Preference, and Pupillary Light Reflex tasks. A priori, gaze to faces in Activity Monitoring, Social Interactive, and Static Social Scenes tasks were aggregated into an Oculomotor Index of Gaze to Human Faces (OMI) as the primary outcome measure. This work reports on fundamental biomarker properties (data acquisition rates, construct validity, six-week stability, group discrimination, and clinical relationships) derived from these assays that serve as a base for subsequent development of clinical trial biomarker applications. Results All tasks exhibited excellent acquisition rates, met expectations for construct validity, had moderate or high six-week stabilities, and highlighted subsets of the ASD group with distinct biomarker performance. Within ASD, higher OMI was associated with increased memory for faces, decreased autism symptom severity, and higher verbal IQ and pragmatic communication skills. Limitations No specific interventions were administered in this study, limiting information about how ET biomarkers track or predict outcomes in response to treatment. This study did not consider co-occurrence of psychiatric conditions nor specificity in comparison with non-ASD special populations, therefore limiting our understanding of the applicability of outcomes to specific clinical contexts-of-use. Research-grade protocols and equipment were used; further studies are needed to explore deployment in less standardized contexts. Conclusions All ET tasks met expectations regarding biomarker properties, with strongest performance for tasks associated with attention to human faces and weakest performance associated with biological motion preference. Based on these data, the OMI has been accepted to the FDA’s Biomarker Qualification program, providing a path for advancing efforts to develop biomarkers for use in clinical trials.

Abstract Background Offspring born to mothers with gestational diabetes mellitus (GDM) are more likely to have negative neurodevelopmental health outcomes, early obesity, type 2 diabetes, and metabolic syndrome in childhood, adolescence, and adulthood. Standard of care management for GDM and type 2 diabetes mellitus during pregnancy is insulin, but oral sulfonylurea use is increasing, and these medications cross the placenta. Literature on treatment with sulfonylureas for maternal GDM has focused on maternal glycemic control and neonatal outcomes. Studies that have evaluated the long‐term outcomes of children exposed to sulfonylureas in utero are limited. Objective This study evaluated anthropometric and neurodevelopmental outcomes of 55 children (ages 5–10) born to mothers with diabetes during pregnancy treated with sulfonylurea or insulin. Methods and Results A group of 25 sulfonylurea‐exposed and 30 insulin‐exposed participants were age‐ and sex‐matched between groups. No significant differences were identified in z‐scores for body mass index (BMI), waist circumference, skinfold measurements, and body fat or rates of overweight/obese BMI between groups. On performance‐based cognitive assessment, the sulfonylurea‐exposed group had significantly lower scores on inhibition (p = 0.043). Conclusion In summary, children with in utero sulfonylurea exposure had similar physical measurements compared to children with insulin exposure and lower performance on a measure of executive function (inhibition), which is associated with adverse health outcomes.

Recent proposals have suggested the potential for neural biomarkers to improve clinical trial processes in neurodevelopmental conditions; however, few efforts have identified whether chronological age-based adjustments will be necessary (as used in standardized behavioral assessments). Event-related potentials (ERPs) demonstrate early differences in the processing of faces vs. objects in the visual processing system by 4 years of age and age-based improvement (decreases in latency) through adolescence. Additionally, face processing has been proposed to be related to social skills as well as autistic social-communication traits. While previous reports suggest delayed latency in individuals with autism spectrum disorder (ASD), extensive individual and age based heterogeneity exists. In this report, we utilize a sample of 252 children with ASD and 118 children with typical development (TD), to assess the N170 and P100 ERP component latencies (N170L and P100L, respectively), to upright faces, the face specificity effect (difference between face and object processing), and the inversion effect (difference between face upright and inverted processing) in relation to age. First, linear mixed models (LMMs) were fitted with fixed effect of age at testing and random effect of participant, using all available data points to characterize general age-based development in the TD and ASD groups. Second, LMM models using only the TD group were used to calculate age-based residuals in both groups. The purpose of residualization was to assess how much variation in ASD participants could be accounted for by chronological age-related changes. Our data demonstrate that the N170L and P100L responses to upright faces appeared to follow a roughly linear relationship with age. In the ASD group, the distribution of the age-adjusted residual values suggest that ASD participants were more likely to demonstrate slower latencies than would be expected for a TD child of the same age, similar to what has been identified using unadjusted values. Lastly, using age-adjusted values for stratification, we found that children who demonstrated slowed age-adjusted N170L had lower verbal and non-verbal IQ and worse face memory. These data suggest that age must be considered in assessing the N170L and P100L response to upright faces as well, and these adjusted values may be used to stratify children within the autism spectrum.

Biomarker development is currently a high priority in neurodevelopmental disorder research. For many types of biomarkers (particularly biomarkers of diagnosis), reliability over short periods is critically important. In the field of autism spectrum disorder (ASD), resting electroencephalography (EEG) power spectral densities (PSD) are well-studied for their potential as biomarkers. Classically, such data have been decomposed into pre-specified frequency bands (e.g., delta, theta, alpha, beta, and gamma). Recent technical advances, such as the Fitting Oscillations and One-Over-F (FOOOF) algorithm, allow for targeted characterization of the features that naturally emerge within an EEG PSD, permitting a more detailed characterization of the frequency band-agnostic shape of each individual’s EEG PSD. Here, using two resting EEGs collected a median of 6 days apart from 22 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the Autism Biomarkers Consortium for Clinical Trials, we estimate test-retest reliability based on the characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set of basis functions that characterize individual power spectrum shapes. We show that individuals exhibit idiosyncratic PSD signatures that are stable over recording sessions using both characterizations. Our data show that EEG activity from a brief 2-min recording provides an efficient window into characterizing brain activity at the single-subject level with desirable psychometric characteristics that persist across different analytical decomposition methods. This is a necessary step towards analytical validation of biomarkers based on the EEG PSD and provides insights into parameters of the PSD that offer short-term reliability (and thus promise as potential biomarkers of trait or diagnosis) vs. those that are more variable over the short term (and thus may index state or other rapidly dynamic measures of brain function). Future research should address the longer-term stability of the PSD, for purposes such as monitoring development or response to treatment.

Clinical research in neurodevelopmental disorders remains reliant upon clinician and caregiver measures. Limitations of these approaches indicate a need for objective, quantitative, and reliable biomarkers to advance clinical research. Extant research suggests the potential utility of multiple candidate biomarkers; however, effective application of these markers in trials requires additional understanding of replicability, individual differences, and intra-individual stability over time. The Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is a multi-site study designed to investigate a battery of electrophysiological (EEG) and eye-tracking (ET) indices as candidate biomarkers for autism spectrum disorder (ASD). The study complements published biomarker research through: inclusion of large, deeply phenotyped cohorts of children with ASD and typical development; a longitudinal design; a focus on well-evidenced candidate biomarkers harmonized with an independent sample; high levels of clinical, regulatory, technical, and statistical rigor; adoption of a governance structure incorporating diverse expertise in the ASD biomarker discovery and qualification process; prioritization of open science, including creation of a repository containing biomarker, clinical, and genetic data; and use of economical and scalable technologies that are applicable in developmental populations and those with special needs. The ABC-CT approach has yielded encouraging results, with one measure accepted into the FDA’s Biomarker Qualification Program to date. Through these advances, the ABC-CT and other biomarker studies in progress hold promise to deliver novel tools to improve clinical trials research in ASD.

It has been proposed that early differences in sensory responsiveness arise from atypical neural function and produce cascading effects on development across domains. This longitudinal study prospectively followed infants at heightened risk for autism spectrum disorder (ASD) based on their status as younger siblings of children diagnosed with ASD (Sibs-ASD) and infants at relatively lower risk for ASD (siblings of typically developing children; Sibs-TD) to examine the developmental sequelae and possible neurophysiological substrates of a specific sensory response pattern: unusually intense interest in nonsocial sensory stimuli or “sensory seeking.” At 18 months, sensory seeking and social orienting were measured with the Sensory Processing Assessment, and a potential neural signature for sensory seeking (i.e., frontal alpha asymmetry) was measured via resting state electroencephalography. At 36 months, infants’ social symptomatology was assessed in a comprehensive diagnostic evaluation. Sibs-ASD showed elevated sensory seeking relative to Sibs-TD, and increased sensory seeking was concurrently associated with reduced social orienting across groups and resting frontal asymmetry in Sibs-ASD. Sensory seeking also predicted later social symptomatology. Findings suggest that sensory seeking may produce cascading effects on social development in infants at risk for ASD and that atypical frontal asymmetry may underlie this atypical pattern of sensory responsiveness. Keywords: Sensory, Autism, Infant siblings, Longitudinal, Frontal asymmetry, EEG

The objective of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is to evaluate a set of lab-based behavioral video tracking (VT), electroencephalography (EEG), and eye tracking (ET) measures for use in clinical trials with children with autism spectrum disorder (ASD). Within the larger organizational structure of the ABC-CT, the Data Acquisition and Analytic Core (DAAC) oversees the standardization of VT, EEG, and ET data acquisition, data processing, and data analysis. This includes designing and documenting data acquisition and analytic protocols and manuals; facilitating site training in acquisition; data acquisition quality control (QC); derivation and validation of dependent variables (DVs); and analytic deliverables including preparation of data for submission to the National Database for Autism Research (NDAR). To oversee consistent application of scientific standards and methodological rigor for data acquisition, processing, and analytics, we developed standard operating procedures that reflect the logistical needs of multi-site research, and the need for well-articulated, transparent processes that can be implemented in future clinical trials. This report details the methodology of the ABC-CT related to acquisition and QC in our Feasibility and Main Study phases. Based on our acquisition metrics from a preplanned interim analysis, we report high levels of acquisition success utilizing VT, EEG, and ET experiments in a relatively large sample of children with ASD and typical development (TD), with data acquired across multiple sites and use of a manualized training and acquisition protocol.

Individuals with Attention Deficit Hyperactivity Disorder (ADHD) tend to perform cognitive tasks with greater Response Time Variability (RTV). Greater RTV in ADHD may be due to inefficient functional connectivity of the brain during information processing. This study aimed to investigate the relationship between brain connectivity, RTV, and levels of ADHD symptoms. Twenty-eight children aged 9–12 years and 49 adolescents aged 15–18 years performed the Sustained Attention to Response Task (SART) while EEG was recorded. The participants’ levels of ADHD symptoms were measured using self- and parent-rated questionnaires. The ex-Gaussian analysis and The Fast Fourier Transform were used to measure multiple aspects of RTV. Functional connectivity between 64 electrodes was computed during task performance, and global efficiency and modularity were calculated, reflecting integration and segregation of the brain, respectively. There was a positive association between multiple RTV measures and the level of ADHD symptoms, where participants with higher levels of ADHD symptoms showed greater RTV, except for sigma from the ex-Gaussian analysis. More efficient brain network activity, measured by global efficiency, was associated with reduced RTV. Children showed greater RTV and less efficient brain network activity compared with the adolescents. These findings support the view that stable responses are achieved with more integrated (and efficient) brain connectivity.

OBJECTIVES/SPECIFIC AIMS: Background: Children with autism spectrum disorder (ASD) show a broad range of unusual responses to sensory stimuli and experiences. It has been hypothesized that early differences in sensory responsiveness arise from atypical neural function and produce “cascading effects” on development across a number of domains, impacting social and communication skill, as well as broader development in children affected by ASD. A primary challenge to confirming these hypotheses is that ASD cannot be definitely diagnosed in the earliest stages of development (i.e., infancy). A potential solution is to prospectively follow infants at heightened risk for ASD based on their status as infant siblings of children who are diagnosed. We examined the developmental sequelae and possible neurophysiological substrates of three different patterns of sensory responsiveness—hyporesponsiveness (reduced or absent responding to sensory stimuli) and hyperresponsiveness (exaggerated responding to sensory stimuli), as well as sensory seeking (craving of or fascination with certain sensory experiences). Infants at high risk (HR) for ASD were compared with a control group of infants at relatively lower risk for ASD (LR; siblings of children with typical developmental histories). Objectives: Research questions included: (a) Do HR infants differ from LR infants in early sensory responsiveness?, (b) Does sensory responsiveness predict future ASD and related symptomatology? and (c) Is sensory responsiveness predicted by resting brain states? METHODS/STUDY POPULATION: Methods: To answer these questions, we carried out a longitudinal correlational investigation in which 20 HR infants and 20 LR controls matched on sex and chronological age were followed over 18 months. At entry to the study, when infants were 18 months old, sensory responsiveness was measured using the Sensory Processing Assessment and the Sensory Experiences Questionnaire, and a number of putative neural signatures of early sensory differences were measured via resting state EEG. When infants were 24 and 36 months of age, ASD and related symptomatology was evaluated in a comprehensive diagnostic evaluation. RESULTS/ANTICIPATED RESULTS: Results: HR infants trended towards increased hyporesponsiveness and hyperresponsiveness and showed significantly elevated levels of sensory seeking relative to LR controls at 18 months of age. Both groups, furthermore, displayed a high degree of heterogeneity in sensory responsiveness. Atypical sensory responsiveness (increased hyperresponsiveness and/or hyporesponsiveness, as well as sensory seeking behavior) predicted several aspects of ASD and related symptomatology, including social, communication, and play skill, and was associated with differences in resting brain state, including metrics of oscillatory power, complexity, and connectivity, as well as hemispheric asymmetry. Moderation analyses revealed that several relations varied according to risk group, such that associations were stronger in magnitude in the HR Versus LR group. DISCUSSION/SIGNIFICANCE OF IMPACT: Conclusion: Findings provide empirical support for the notion that early sensory responsiveness may produce cascading effects on development in infants at heightened risk for ASD. Differences in resting brain states may underlie atypical behavioral patterns of sensory responsiveness. From a clinical standpoint, results suggest that early sensory differences may be useful for predicting developmental trajectories, and be potentially important targets for early preventive intervention, in infants at risk for autism.