Shafali Jeste - US grants

DESCRIPTION (provided by applicant): Autism Spectrum Disorders (ASD) are a phenotypically heterogeneous group of neurodevelopmental disorders being diagnosed at growing rates in toddlers and young children, with prevalence estimates of 1%. Many children have limited expressive language at the time of diagnosis, and only 50% make significant gains in communication, even with intensive interventions. Unfortunately, intervention studies in ASD have struggled to reliably predict language gain, and, importantly, to differentiate pre-verbal from non-verbal children. One major limitation is the reliance on standardized behavioral assessments, which only capture overt behaviors. Innovative methodology is needed to better characterize the neural correlates of cognitive and perceptual domains important for language acquisition and to apply these methods to inform intervention studies. Such knowledge will allow us to design and apply more effective, targeted interventions for children with ASD based on baseline phenotypes. This study proposes to apply electrophysiological measures to better characterize the neural correlates of two cognitive domains essential for language acquisition: joint attention and statistical learning, along with resting state EEG power, in young children with ASD prior to entry into an intensive behavioral intervention and then after completion of the intervention, in order to determine if specific electrophysiological profiles can predict language acquisition and gain. Combined with the activities outlined in the training plan, this research proposal represents a timely effort to apply translational methods to behavioral intervention studies in order to enrich the conventional predictors of outcome in ASD. The principle unifying this study is that a better understanding of the neural mechanisms underlying the behavioral and cognitive deficits in ASD will inform predictors of treatment response, which, in turn, will facilitate the development of more targeted interventions for these children. This study is in line with objective 1 (strategy 1.3) and objective 3 (strategy 3.1) of the NIMH strategic plan. Specifically, to (1) "identify and integrate biological markers (biomarkers) and behavioral indicators associated with mental disorders," and to (2) "further develop innovative interventions and designs for intervention studies." ! PUBLIC HEALTH RELEVANCE: Language impairment is very common in children with Autism Spectrum Disorders (ASD), with 50% remaining non-verbal even with intensive treatments. Clinicians struggle to predict which children will actually make gains in language at the time of a child's diagnosis, largely because of the limitations of standardized testing to characterize these children. This study proposes to couple behavioral testing with advanced electrophysiology to predict language outcomes after treatment in children with ASD. This study has the potential to improve our ability to predict language outcomes which, in turn, will allow clinicians to make more informed treatment recommendations and to provide more detailed prognostic information to patients and their families.

DESCRIPTION (provided by applicant): Autism Spectrum Disorders (ASD) are a phenotypically heterogeneous group of neurodevelopmental disorders being diagnosed at growing rates in toddlers and young children, with prevalence estimates of 1%. Many children have limited expressive language at the time of diagnosis, and only 50% make significant gains in communication, even with intensive interventions. Unfortunately, intervention studies in ASD have struggled to reliably predict language gain, and, importantly, to differentiate pre-verbal from non-verbal children. One major limitation is the reliance on standardized behavioral assessments, which only capture overt behaviors. Innovative methodology is needed to better characterize the neural correlates of cognitive and perceptual domains important for language acquisition and to apply these methods to inform intervention studies. Such knowledge will allow us to design and apply more effective, targeted interventions for children with ASD based on baseline phenotypes. This study proposes to apply electrophysiological measures to better characterize the neural correlates of two cognitive domains essential for language acquisition: joint attention and statistical learning, along with resting state EEG power, in young children with ASD prior to entry into an intensive behavioral intervention and then after completion of the intervention, in order to determine if specific electrophysiological profiles can predict language acquisition and gain. Combined with the activities outlined in the training plan, this research proposal represents a timely effort to apply translational methods to behavioral intervention studies in order to enrich the conventional predictors of outcome in ASD. The principle unifying this study is that a better understanding of the neural mechanisms underlying the behavioral and cognitive deficits in ASD will inform predictors of treatment response, which, in turn, will facilitate the development of more targeted interventions for these children. This study is in line with objective 1 (strategy 1.3) and objective 3 (strategy 3.1) of the NIMH strategic plan. Specifically, to (1) identify and integrate biological markers (biomarkers) and behavioral indicators associated with mental disorders, and to (2) further develop innovative interventions and designs for intervention studies.

Project Summary/Abstract The ongoing goal of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is to establish electroencephalography (EEG) and eye-tracking (ET) biomarkers that can be used for stratification and/or as sensitive and reliable objective assays related to social function in autism spectrum disorder (ASD) clinical trials. This renewal application seeks to further validate promising measures through three studies designed to enhance and extend the original ABC-CT study: (1) a confirmation study of the original findings in a new cohort using similar design (T1: Baseline, T2: 6 weeks post baseline, T3: 24 weeks post baseline) and sample size/characteristics (200 with ASD, 200 with typical development (TD)); (2) a follow-up study of the original cohort (N=399) to re-administer the biomarker and clinical batteries 2.5-4 years after original ABC-CT enrollment; (3) a feasibility study of parallel EEG and ET biomarkers in preschool-aged (3-5-year-old) children (25 with ASD, 25 with TD). The biomarker and clinical batteries measure key facets of social-communication in ASD using well- validated paradigms appropriate for the intended developmental and cognitive range. The study will rely on the same leadership and five Collaborating Implementation Sites (?Sites?) from the first phase, all highly experienced in multi-site collaborative clinical research using the proposed clinical, EEG, and ET methodologies. The Data Coordinating Core (DCC) will provide a secure informatics infrastructure for communication and data integration across the consortium to ensure organized data management, quality control, and reliable upload to the National Database for Autism Research (NDAR) and NIH Data Repositories. The Data Acquisition and Analysis Core (DAAC) will oversee consistent use of scientific standards and methodological rigor for data acquisition, processing, and analytics. The Administrative Core, in coordination with federal partners in this cooperative agreement, will oversee the operations of the sites, DCC, and DAAC to ensure methodologically and ethically rigorous, efficient completion of study aims: 1) In the confirmation study with a new cohort, evaluate whether EEG and ET measures, individually or in combination, have utility as stratification biomarkers and/or sensitive, reliable measures of change in clinical trials; 2) In the follow-up study of the original ABC-CT cohort, assess long-term stability, sensitivity to change, and longitudinal predictive value of the markers; 3) In the feasibility study, determine the viability of parallel EEG and ET measures as potential biomarkers in 3-5-year-old children with ASD and TD. Blood (DNA) samples will be collected from participants with ASD and biological parents for future genomic analyses, and raw, processed, and analyzed data will be shared to create a community resource accessible for use by all qualified investigators. These objectives are designed to further develop promising biomarkers to advance qualification with the FDA Biomarker Qualification Program.

Project: Abstract The proposal is truly translational, as it draws from clinical observation and moves towards rigorous quantification of biomarkers of cognitive impairment in both mouse models and patients. Such a study will serve as a model for studies of other neurodevelopmental disorders in our comprehensive Center. These biomarkers can then, in future studies, be directly related to gene expression. First, we will identify a mechanism-based electrophysiological biomarker of cognitive dysfunction and potential responsiveness to treatment in a genetically well-defined syndrome highly associated with ID. Standardized measures of cognition are limited in their ability to quantify subtle individual differences or to capture clinical heterogeneity that may inform prognosis and intervention. Our group has considerable expertise in the integration of EEG biomarkers with behavior to better characterize children with neurodevelopmental disorders. Second, we will perform parallel studies in mouse models, in order to validate and better understand the genetic basis of biomarker identified in humans and to begin to test treatments that may alter both the cell activation patterns and behavior in these mouse models. Specifically we will test how abnormal oscillations disrupt information flow in awake behaving animals, allowing us to directly link electrophysiological changes to cognition. Innovative methods to study electrophysiological markers in both mouse models and patients. The human EEG experiments in the Jeste Lab will make use of new analysis techniques to measure signal complexity and to quantify resting state spectral power from challenging populations. The mouse experiments will make use of custom-made high density electrophysiological recordings from hundreds of neurons with silicon probes targeted to multiple cortical regions. New attention-based multimodal set shifting task designed in the Golshani lab to record the activity of large neuronal populations during flexible decision making and attentional set shifting, a cognitive domain that is affected in the disorder. Finally, we will use a new generation of miniaturized microscopes to record the activity patterns of large populations of hippocampal neurons over days during learning, allowing us for the first time to follow population dynamics in the same group of neurons during learning and extinction. Importantly, these studies are rooted in gaining a new understanding of ID at a systems level with a desire to find convergence in mechanisms and evidence-based treatments for individuals with this heterogeneous group of disorder.

PROJECT SUMMARY Identification of the earliest markers of risk for ASD holds tremendous clinical relevance, as it informs the implementation of early interventions that may attenuate symptoms and even prevent the development of ASD. Historically, infant siblings of children with ASD have constituted the primary focus of research in early markers. However, other high risk groups based on genetic diagnosis have been identified over the past several years. Studying infants at heightened genetic risk for ASD affords us a valuable opportunity to examine both distinct and shared neurobiological pathways to the core features that define autism symptoms. Such investigations not only shed light on mechanisms underlying atypical development in high-risk infants, but they can also clarify the ideal timing and target of early interventions that may modulate developmental trajectories. Here, we take a genetics-first approach and investigate biomarkers of risk for ASD and predictors of outcome in early infancy in three genetically defined groups with elevated risk: infants with an older sibling with ASD (familial risk), infants with Tuberous Sclerosis Complex (TSC), and infants with 22q11.2 deletion syndrome (22q11). We select these groups both because of our unique ability to study these populations at UCLA and because they allow us to examine ASD as it emerges in the context of three genetic pathways: polygenic risk (familial risk), single gene mutations (TSC), and copy number variation (22q11.2 deletion). We combine electrophysiology (EEG) with magnetic resonance imaging (MRI) to examine neurodevelopmental processes in the first year of life that may underlie the impairments that define ASD: (1) resting state/baseline neural synchrony and connectivity, (2) low level sensory processing and (3) brain activity and connectivity in language and salience networks. We study infants at 1.5, 3, 6, 9, 12 months with MRI (1.5 and 9 months), EEG (3-12 months), and behavioral (3-12 months) assays and then perform standardized assessments of cognition and autism symptoms at 12, 24 and 36 months. The project has synergy with the other ACE projects. Infants demonstrating early signs of ASD in this project will be referred to the infant intervention study in Project II (PI: Kasari). With Project III (PI: Dapretto), we share leadership and employ common measures of brain activity and connectivity. This project also will rely on the Diagnostic and Phenotyping Core (PI: McCracken, Co-PI Gulsrud) for developmental and diagnostic testing. We also will integrate with the Biomarkers Core (PI: Geschwind, Co-PI Jeste), with data collection performed in the Jeste and Dapretto labs and imaging/EEG data combined with data from the other projects for larger scale analyses of heterogeneity from infancy to adolescence. Saliva samples for genetics will be gathered at baseline from all participants for analysis of CNV's and polygenic risk. Each aim of this project is grounded in the overarching hypotheses that we will: (1) identify distinct behavioral and brain based trajectories and areas of convergence across these risk groups in early development and (2) quantify predictive markers of atypical development and ASD across groups before age 12 months. !

PROJECT SUMMARY/ABSTRACT Background: Children with Tuberous Sclerosis Complex (TSC) are at high risk for neurodevelopmental disorders, with rates of autism spectrum disorder (ASD) approaching 60%. Prospective studies have found that infants with TSC demonstrate delays in social communication skills in the first year of life. However, to date no studies have investigated whether early behavioral intervention can improve social communication skills in infants with TSC. Objectives: The overarching goal of the study is to determine if social communication function can be improved in infants with TSC with a targeted, short-term behavioral intervention called JASPER (Joint Attention, Symbolic Play, Engagement, Regulation), and to enrich traditional outcome measures by combining behavioral measures with electrophysiological (EEG) biomarkers of social communication. These biomarkers can capture subtle changes in brain development that may reflect responses to treatment prior to an overt behavioral change, particularly relevant for children with significantly delayed development, and they can inform the neural mechanisms underlying the behavioral changes found with intervention. Hypothesis: It is expected that, compared to a wait list control group, infants receiving the JASPER intervention will demonstrate greater gains in social communication skills, with changes captured both behaviorally and electrophysiologically. Methodology: A total of 60 infants with TSC ages 12-36 months will be recruited across two sites with an established collaboration in TSC research, UCLA and Boston Children's Hospital, with each infant randomized to treatment or wait list control group. The wait list control design allows all infants to receive intervention while still maintaining a non-treatment comparison group. Treatment will consist of 12 weeks of weekly intervention sessions. Assessments (clinical, behavioral and EEG) will be performed before treatment, after treatment, 3 months after completion, and then 12 months after completion. Controls will undergo assessments at the same time points, and then will start intervention at month 6. Assessments will include behavioral measures of social communication skills, cognition, language and adaptive function, and EEG measure of resting state brain activity, visual and face processing. Impact: Early intervention improves cognitive and behavioral outcomes in ASD, yet no studies have investigated the effects of targeted, early behavioral intervention in infants with TSC. Evidence of efficacy of early intervention will justify its value for all infants with TSC, improving developmental outcomes and attenuating symptoms that lead to the diagnosis of neurodevelopmental disabilities in TSC. Moreover, this study holds relevance for intervention research across neurodevelopmental disorders through its integration of EEG biomarkers with behavioral measures, as such methodology may more readily capture the effects of treatment in pre-verbal and developmentally delayed infants.

Project Abstract Duplications of 15q11.3-21.1 (Dup15q syndrome) are highly penetrant for intellectual disability (ID), autism spectrum disorder (ASD) and epilepsy (Finucane et al., 2016). Several genes in the region, particularly UBE3A and a cluster of GABAA receptor genes, are critical for neural development, disrupting synaptic protein synthesis and degradation as well as inhibitory neurotransmission. In a previous study, we identified an electrophysiological biomarker of this syndrome defined by increased beta band oscillations that likely reflect aberrant GABAergic neurotransmission (Frohlich et al., 2016). As we further explored properties of this biomarker, we discovered that the sleep physiology in these children is profoundly abnormal, with grossly attenuated slow wave sleep and reduced sleep spindle density. Healthy sleep physiology is necessary for robust cognitive development, from early infancy through adulthood, (den Bakker et al., 2018; Fogel & Smith, 2011; Hahn et al., 2018; Tham, Schneider, & Broekman, 2017), and there is extensive evidence of physiological sleep impairment in neurodevelopmental disorders (Gruber & Wise, 2016; Kose, Yilmaz, Ocakoglu, & Ozbaran, 2017; Tessier et al., 2015). We hypothesize that abnormal sleep physiology directly undermines cognitive development in Dup15q syndrome and may serve as a quantifiable and modifiable target for pharmacological or even behavioral interventions. Through a partnership with the Dup15q Alliance (patient advocacy group) and our UCLA Intellectual and Developmental Disabilities Research Center (IDDRC), we propose a comprehensive study of sleep electrophysiology and cognition in Dup15q syndrome. We will collect previously recorded overnight clinical EEG?s from children with Dup15q syndrome across the country and compare these EEG?s to those of children with nonsyndromic ID and typical development. We will ask whether sleep physiology, specifically (1) spindle density, (2) percent slow wave sleep, (3) percent spikes in slow wave sleep and (4) absolute beta power in stage 1 and 2 of sleep differentiates Dup15q syndrome from these comparison groups and whether these variables relate to cognition and adaptive skills. The field of neurodevelopmental disorders has sorely lacked quantifiable electrophysiological biomarkers that relate to disease mechanisms, and sleep EEG may represent a robust biomarker that sheds light on the etiology of cognitive impairment while also serving as a surrogate endpoint in clinical trials, particularly for Dup15q syndrome. Moreover, the pipeline that we have developed, from building a remote clinical EEG repository to performing semi-automated sleep EEG signal processing can inform other biomarker studies in syndromic and nonsyndromic forms of ID.

ABSTRACT Despite tremendous effort by parents, researchers, clinicians, and educators, autism spectrum disorder (ASD) continues to present a significant, lifelong challenge to most affected individuals and their families. Studies of early development in infants at risk for ASD (such as infants with older siblings with ASD: ?HR infant siblings? ? who have a ~20% chance of developing ASD) can identify early, presymptomatic predictors of ASD that can then improve early screening and promote presymptomatic intervention. Behavioral studies of these HR infant siblings have identified atypical behaviors in the second year of life in the social domain, with some evidence of motor delays and differences in social attention within the first year. However, in part because of the limited behavioral repertoire of infants, investigators have struggled to identify consistent first-year-of-life behaviors that predict later ASD in a clinically actionable manner. We propose that the earliest measures of atypical development should directly assay brain function. The Infant Brain Imaging Study (IBIS) Network has used MRI methods to reveal functional and structural brain changes in the first year of life in HR infant siblings. These brain changes are present prior to the emergence of behavioral features of ASD and accurately predict ASD at 24 months of age (positive predictive value >= 80%). While scientifically promising, MRI's cost and reduced availability limit its potential scalability for use in HR infants to use as a general population screener in clinical settings. Electroencephalography (EEG) and eye tracking (ET) represent two scalable methods that can measure brain function and can help to identify predictive biomarkers of ASD in early infancy. EEG and ET are developmentally sensitive and accessible in community, real-world settings. In spring 2019, the Infant Brain Imaging Study (IBIS) Network will launch a new study of 250 HR infants designed to replicate and extend its predictive MRI findings. Here, we propose to add EEG and ET measures of brain function to this study, testing HR infants from IBIS at 6 and 12 months of age, and assessing clinical outcomes at 24 months of age with clinical outcomes assessed at 24 months of age. We will examine brain network function at rest, during low level sensory processing, and during social information processing. Our hypothesis is that these scalable EEG/ET biomarkers will (Aim 1) accurately identify infants with a later diagnosis of ASD and will (Aim 2) relate to ASD-associated behaviors at 24 months of age. Capitalizing on this unprecedented opportunity to integrate EEG/ET with neuroimaging in the same cohort of infants, in Aim 3 we also propose to explore the predictive power of these combined measures, and the association between EEG/ET and MRI features. The overarching goal of this proposal is to lower the age of detection of autism to early infancy, making intervention before the emergence of ASD-specific behavioral features feasible and more effective. Positive findings in the proposed study will also facilitate the future extension of presymptomatic predictive testing from HR infants to infants in the general population.