Karen Pierce - US grants

Current research suggests that an attentional deficit may underlie autistic disorder (AD) symptomology. The main purpose of the proposed study are: (1) to determine the extent to which type (e.g., nonverbal), number (i.e., 1-4) and distribution (i.e., simultaneous vs sequential) of cues affects the social perception of AD children and (2) to determine general patterns of attention to environmental stimuli in AD. In the proposed study, 30 AD children, 30 children with mental retardation and 30 normally functioning children matched on gender and language age will participate. Subjects will be presented with two experimental tasks: a social perception (SP) and a general attention (GA) task. During the SP task, participants will view a series of 38 brief (e.g., 20 sec) videotaped vignettes of child-child interactions and asked a series of questions following the presentation of each vignette. Vignettes will contain one through four social cues which will be presented wither simultaneously or sequentially. During the GA task subjects will also view vignettes containing 1-4 cues presented either simultaneously or sequentially, but the children in these vignettes will not be interacting. It is hypothesized that AD children will: (1) show deficits in social perception when compared to controls; (2) perform better on SP and GA tasks with one cue, and worse on tasks with multiple cues and (3) perform better when cues are presented sequentially versus simultaneously. Pilot research (i.e., Pierce, et al 1995) suggests that AD children perform better on social tasks containing single cues versus tasks with multiple cues. Data will be analyzed mainly using MANOVA's. The focus of this proposal is to test the hypothesis that a newly identified family of neural proteins mediate synaptic specificity by forming intercellular junctions. A major objective of developmental neurobiology is to understand how nerve cells interconnect with such specificity. Though several molecules involved in neuronal pathfinding have been identified, virtually nothing is known about how neurons recognize their correct synaptic partners. What seems certain is that the molecular signals involved in connectivity are different than those for pathfinding. Proper selection of a target requires the growth cone to distinguish among myriad closely packed potential targets. The growth cone must then collapse and intercellular signals must be exchanged to initiate synaptic specializations. An ideal connectivity molecule would both mediate cellular attachment and allow signal exchange. Gap junctions could serve both these functions in the nervous system. Since the first proposal by Fischbach that transient gap junctions may precede formation of chemical synapses, several studies have demonstrated transient gap junctions in the developing nervous system. Though many gap junctions are formed by a family of proteins called connexins, there is evidence that other neural ga; junction proteins exist. This proposal focuses on a newly identified family of neural proteins (the OPUS family) that have predicted structural similarity to the connexins. The best understood members of this family are involved in mediating specific synaptic connections. For example, passover, a defining member of the OPUS family, is required for formation of synapses between a few identified neurons in Drosophila. This suggests the possibility that connexin-like molecules may have evolved in the nervous system to mediate the specific cellular recognition required for synaptic choice. This proposal is aimed at testing this hypothesis. The proposal includes in vitro and in vivo experiments to examine possible functions of pas at a molecular and cellular level. The idea that PAS (protein) forms intercellular junctions that mediate cellular recognition and intercellular communications will be tested in two ways. First, pas alleles, as well as other OPUS members will be expressed in Xenopus oocytes by injecting in vitro generated mRNA. The oocytes will then be paired and tested for functional junctions by looking for electrical coupling. This system has been used extensively to study connexin genes. A collaboration has been arranged with one of the developers of this system, Dr. David Paul at the Harvard medical school. Second, pas will be expressed in gap junction defective cell lines and coupling tested by scrape loading Lucifer Yellow or neurobiotin. The cell lines offer the possibility of more in depth study of the properties of gap junctions if they do form. In addition, some connexins fail to form junctions in the oocyte system for unknown reasons. In addition to testing the hypothesis that pas forms gap junctions, the proposal also addresses the question of whether pas is involved in mediating specific interactions between cells. Lastly, experiments are suggested for structure/function analysis of pas by testing in vitro generated mutants in the oocyte and cell culture systems as well as in flies. The health relatedness of the project is difficult to assess, but given the complexity and specificity of synapse formation, it seems likely that defects in this process may underlie a number of neurological disorders.

functional magnetic resonance imaging; social perception; neural information processing; autism; bioimaging /biomedical imaging; brain imaging /visualization /scanning; behavioral /social science research tag; human subject; clinical research;

Our Autism Center of Excellence (ACE) aims to discover the mechanisms related to early brain overgrowth in autism and to define specific behavioral and biological factors associated with infants at-risk for the disorder. These goals can only be achieved if autism is studied prospectively. Currently, the only prospective strategy in use is the baby-sibling design. Unfortunately, the baby-sib approach is weighed down by heavy research costs, long time frames to identify and follow cases, and only represents autism as it occurs in multiplex families. The Clinical Phenotype: Recruitment and Assessment Core (CPRAC) will implement a different strategy, called the 1-Year Well-Baby Check-Up Approach, to identify and study infants at risk for an ASD prospectively. As shown in the preliminary results section, this approach has the potential to identify at-risk cases quickly, and for a fraction of the cost of baby-sib research. Importantly, this unbiased approach will identify ASD cases from singleton and multiplex families alike, and as such may more realistically represent the population of autism. This method will allow infants at-risk for an ASD as well as those at-risk for a developmental disorder (DD) to participate in MRI (Project 1), fMRI (Project 2) and genetic research studies (Projects 3 and 4) beginning at 12-months in age. The CPRAC will also recruit, using the same approach, age, gender and ethnicity-matched typical controls. Thus, the CPRAC will recruit a total of 3 study groups: at-risk ASD, at-risk DD, and typical. The CPRAC will also thoroughly characterize each study infant using standardized clinical and experimental measures in the general areas of social, cognitive, language, and exploration behavior. Infants will also receive a thorough physical and neurological examination and have blood samples collected through CPRAC services. The CPRAC will follow infants longitudinally and collect selected study data every 6 months until each participant turns three years old. CPRAC investigators will implement quality control of assessments and adhere to all research subject protection guidelines including HIPAA. In summary, the CPRAC will be responsible for: 1) identification and recruitment of 12-month old infants; 2) diagnostic and psychometric evaluations of study infants every 6 months 3) coordination of each infant's participation in Projects 1-4;4) final diagnoses when each participant turns three. The CPRAC will also be responsible for informed consent and ensuring compliance with current clinical and research standards and guidelines, including HIPAA. The CPRAC will also work closely with investigators on each of the projects, as well as the other Cores.

No other period in human life matches the magnitude and astonishing increase in neural functional capacity as the transition from neonate to infant to toddler. Within a month or two following birth, the infant begins to smile and around first birthday begins to speak. Soon thereafter he coordinates speech and gesture in order to garner the attention of others. By the time he is two, he can speak in short sentences and has a rich repertoire of socio-emotional responding. Of all autism biology, the greatest mystery is what neural malfunction fails to provide this leap in social, emotional and language capacity. The only safe and powerful method for observing human neural function directly is functional MRI. While there are now thousands of fMRI studies in mature humans, not a single fMRI experiment has attempted to discover the neurofunctional bases of this incredible achievement in typical infants or its profound failure in the autistic infant. We have performed ground-breaking pilot fMRI studies of typical and autistic toddlers mapping for the first time the regions of the brain that are involved in responding to language, social and emotion sounds. We have done this in the only way feasible: while the toddler is in natural sleep and not moving. This method of mapping neural function and malfunction allows testing to be done comparably regardless of developmental age or level of mental or behavioral ability;infants at all ages and levels of functioning can be studied equivalently. We therefore propose the first-of-its-kind fMRI study of infants at-risk for autism at 12 and 24 months. Our proposed natural sleep fMRI experiments will be the first to map the neural systems activated by social, emotional and language information in the autistic, developmental^ delayed, and typically developing infant. Abnormal fMRI activation patterns will be identified that characterize and predict social emotional and language behavioral deficits as measured in clinical assessment and diagnosis Core B. Behavioral deficits in these three areas are among the first red flags signaling possible autism in the infant, and through our studies we will identify the first neurofunctional biomarkers of early development in autism. Identification of these neural functional biomarkers of early development in autism will enable us through collaboration with the MRI Project 1, genetic Projects 3 and 4, the Treatment Core C and the Integrated Biostatistics Core D, to perform the first ever analyses that will establish relationships between brain function on the one hand and neuroanatomy, gene expression and genetic polymorphisms, clinical variables and treatment effectiveness on the other.

DESCRIPTION (provided by applicant): There is a paucity of behavioral data and an absence of biological data on autism at 12 months of age. The reason for these major gaps in vital information is because autism remains behaviorally, not biologically, defined and diagnosed. Prospective, hypothesis- driven studies of behavior and biology in autistic infants would be powerful and are essential, but are missing. Currently, the infant sibling design is the only prospective approach in use. This design is strong but also has limitations including high costs, long-time scale, potential for sampling bias, and the heavy demands on the researcher to identify, recruit, and maintain contact long-term with large numbers of mothers and infants. We propose a different prospective strategy, called the "1-Year Well Baby Check-Up Approach", that does not involve any of these limitations. Because most babies see their pediatrician at 1 year, we propose to have 60 pediatricians give a brief screening questionnaire to parents while in the waiting room, the CSBS-DP Infant Toddler Checklist (Wetherby and Prizant, 2002), at every 1-year well baby check-up. Infants whose scores fall outside of the normal range will be referred to us for follow-up diagnostic and psychometric testing. Babies judged to be at-risk for autism or developmental delay (DD) will be followed longitudinally to determine the success rate of this procedure. Control subjects will be babies who score within the normal range on the checklist. Success of this model approach can have an immediate impact on pediatric practice. Babies judged to be at-risk for autism or DD, as well as controls, will participate in two studies aimed at demonstrating that important behavioral and biological information can be obtained via this approach. In one study, to address the important question of immunological abnormality in autism early in life, we will use state- of-the-art methods to assay plasma levels of specific immune significant cytokines and growth factors. In the second study, to address important questions about early social interest and orienting abnormalities in autism, we will use a quantitative experimental procedure for investigating social preference behavior and eye gaze patterns. Successful identification of biological and behavioral features of autism at 12 months of age will have a major impact by introducing the possibility of pediatric referral of high risk infants for quantitative and objective tests that can aid in earlier diagnostic and treatment decisions.7.

DESCRIPTION (provided by applicant): Currently, parent report screening tools (e.g., M-CHAT, CSBS) are the only standardized screening options available to pediatricians for the early detection of autism. As demonstrated in our previous work (the 1-Year Well-Baby Check-Up Approach, Pierce et al., 2011), such screens have valuable strengths, but also weaknesses, including the impact of parent characteristics on how they rate their child's behavior and high false positive rates. Autism is a disorder that has its roots in abnormal early brain development, yet early identification rests largely in the hands of parent report measures, rather than in the domain of more objective, quantifiable behavior. To move beyond parent report as the only early screening choice, novel procedures for screening must be researched. During our last grant cycle we developed a novel eye-tracking test, the Geometric Preference Test for Autism (GeoPref Test). This simple one-minute test shows dynamic, colorful geometric moving patterns on half of a computer monitor and colorful active people on the other half. Of >440 toddlers tested using standard eye tracking technology, almost every toddler who fixated at high rates on the geometric patterns was ASD, and not typical or developmentally delayed. Thus, our laboratory experiments demonstrated exceptionally high, 99%, specificity of the GeoPref Test for detecting ASD. A low false positive rate is essential in a screening tool because false positives overload the system and create anxiety. Equally important in this heterogeneous disorder, the 1-min test identified 37% of all ASD toddlers. This is a larger percentage than any other early genetic, proteomic, neuroimaging or neurobehavioral screen, and it is fast, easy, and highly ASD specific. Aim 1 will identify methods to integrate ASD specific test into clinical practice as a 2nd tier screen for babies who fail a routine 1st tier pencil and paper screen (i.e., the CSBS). Results will greatly improve the accuracy of early detection and speed referral of babies for diagnostic and treatment services. Using a portable eye tracker, 39 pediatricians will give the GeoPref Test in their office to toddlers who fail the CSBS who will in turn be referred to our Center for blinded diagnosis. This will be the first translation of an eye tracking finding on ASD into real-world clinical practice. In an effort to fully understand the clinical phenotype of ASD toddlers that fail the GeoPref Test, Aim 2 will use novel experimental tests, such as a test of exploration, as well as standardized tests such as the Mullen, to identify clinical profiles tha distinguish these toddlers from others with an ASD. Although the GeoPref Test identifies a large subgroup of 37% of all ASD toddlers, equally fast, and accurate tests are needed to identify the remaining ASD toddlers. Aim 3 proposes to develop new eye tracking tests, specifically novel social orienting and motherese paradigms, to detect these toddlers. Random forest classification algorithms will identify eye gaze signatures that best identify subgroups of ASD toddlers. All toddlers will receive a final blinded diagnosis at 30-36 months.

DESCRIPTION (provided by applicant): We previously demonstrated that our early intervention model system, which was centered on using the CSBS to screen all babies at the 1-year check-up as standard of care, resulted in a mean age of 12 months for screening, 14 months for evaluation, and 18 months for treatment participation. These are far younger ages than is common in the U.S. Our 3-stage model system, Get SET (S=Screen; E=Evaluate; T=Treat) Early, screened >10,000 1 year olds in our first trial run1 detecting over 100 ASD and other developmental delayed toddlers. We will build on this highly effective model by implementing a new version in two major cities: San Diego and Phoenix; Los Angeles, Irvine, and Phoenix will provide baseline control data. In Phoenix, we test the feasibility of establishing the Get SET Early model in a city with one of the lowest median incomes and oldest age of first diagnosis in America. In AIM #1, the Screen and Refer Early stage, we will create a Pediatrician Network with 100 members. In San Diego we will utilize our existing Pediatrician Network and test new innovations such as a repeat triple screen at 12, 18, and 24 months to ensure that no toddlers are missed. Speed of referral for evaluation will be compared and contrasted using parent (self) and automatic (referral i- Pad App) options. We will track every toddler with an eventual ASD diagnosis within circumscribed medical groups to determine the true sensitivity and specificity of the screening tool and the percentage of ASD toddlers detected by our model. Anonymous survey data regarding screening habits will be administered to parents and pediatricians. AIM #2 implements the Evaluate and Refer Early stage. Its key attribute is an ASD Early Evaluation Clinic that specializes in the rapid scheduling and evaluation of every referred screened positive toddler. Toddlers will enter the program at the age they fail the screen (i.e., 12, 18 or 24 months) and will be thoroughly diagnostically evaluated and tracked once per year until they turn 3 years. This specialty Clinic is at our Autism Center in San Diego and will be developed at SARRC in Phoenix. Automated versus optional self-referral for treatment will be tested and compared. AIM #3 implements the Treat Early stage. Its key attributes are a network of providers of empirically based treatment and the innovative use of an inexpensive and readily available web-based treatment tracking system to document engagement. Treatment Networks will be created in San Diego and Phoenix. Primary outcome measures include rates and ages of screening and referral, evaluation and referral, and treatment engagement; sustainability across years; diagnostic, clinical and demographic characteristics of subjects; professional and parent satisfaction at each stage. We hypothesize that providing screening tools with clear cut-off scores and guidelines for automatic referral for evaluation and treatment, will result in dramatically lowering mean age of diagnosis and treatment in Phoenix from 4-5 years down to 1-2 years; San Diego will likewise have mean ages of 1-2 years for diagnosis and treatment making them significantly earlier than Los Angeles and Irvine control sites.

Project Summary/Abstract Despite the annual $268 billion cost of ASD in the U.S. and the tens of millions spent annually on research, ?precision? medicine does not exist in any meaningful way for ASD infants and toddlers. The heterogeneity of early neural and behavioral developmental trajectories in ASD has stymied the search for explanations, and the identification of clinically useful biomarkers of prognosis as well as the discovery of biotargets that could be used to develop maximally effective treatments. In our proposed studies, 175 ASD, typical, language delayed (LD) and global developmental delayed (GDD) toddlers will participate in a series of language- relevant (nursery rhymes vs music) and social emotion fMRI paradigms (own mother?s voice vs stranger?s) as well as resting state connectivity paradigms to begin to address this major gap in the field. Toddlers will be recruited using our novel general population based screening approach that provides unique and complementary data to those from baby sibling studies. In order to generate a rich clinical profile of each toddler, multiple language and social measures will be taken, including CELF-R, Mullen and Vineland. In order to examine change and leverage powerful longitudinal modeling approaches, toddlers will be clinically assessed and imaged at both 1-2 and 3-4 years. State-of-the-field MEMB and ME-ICA denoising approaches will be utilized that yield highly reliable high signal-to-noise functional imaging that outperforms previous fMRI approaches and enhances effect size estimates and statistical power; this greatly benefits robustness in our analyses, reliability, split sample feasibility, and exploratory prognostic biomarker modeling. Multiple analytic methods (e.g., PLS, seed-PLS, ICA, spectral DCM, PPI) will be applied to identify brain-language and brain- social emotion relationships; model neural and clinical trajectories from 1-2 to 3-4 years; reveal language- and social emotion-relevant fMRI activation and connectivity patterns at 1-2 years that are predictive of language and social outcomes; discover underlying neural-clinical subtypes; model continuous variation in still other neural measures that predict continuous language and social measures; identify fMRI-MRI relationships; define how language and social emotion neural deficits tap into shared neural network resources in early development; and examine similarities and differences in brain-behavioral relationships across multiple groups which then allows for sensitive tests of whether brain-behavioral patterns are common across diagnostic boundaries (e.g., LD, GDD and ASD poor language toddlers in an RDoC fashion) or specific to a subgroup of individuals. Our studies will identify clinically meaningful early-age neural biomarkers that predict which ASD children will go on to have good language outcomes and which poor ones, and others that predict social outcome. Compelling ASD language and social biotargets will be found that can be tested for response to specific, targeted interventions in future experimental therapeutic paradigms.

Children with ASD, on average, are not identified and treated until around age 4?years, several years beyond the first signs and symptoms. Even when toddlers are diagnosed as ASD, parents and clinicians have little information to guide treatment decisions or predict the early course of that child's next few years. Research is needed to discover objective biomarkers that detect ASD at early ages with high accuracy, indicate disorder subtypes linked to definable clinical profiles, and convey prognostic information. The discovery of such biomarkers have been elusive, in part, because most studies utilize small sample sizes and fail to include non?ASD delay contrast groups which are essential to enhance specificity. Our proposal plans to fill this gap by leveraging eye tracking technology to determine if visual fixation patterns in a large sample of very young (12?36 months) ASD and non?ASD toddlers (n=225) from the general population can be used to discover an eye tracking biomarker profile of ASD. The prognostic power of our eye tracking biomarkers will be determined by linking initial eye tracking scores to clinical profiles 1?2 years later. Given the heterogeneity in ASD, it is unlikely that a single eye tracking test would detect all toddlers. Here we plan to remedy this by testing the utility of a battery of 9 developmentally appropriate, short (~1?minute each), eye tracking tests that each tap into a foundational domain in ASD symptoms including: visual social attention, gaze shifting, and auditory social attention. Our tests will objectively quantify key metrics such as overall fixation levels within social versus non?social images, the frequency of gaze alterations during joint attention and gaze following tests and, using unique gaze contingent technology, the degree to which a toddler prefers to listen to prosodic, emotionally valent, motherese speech. Our preliminary findings suggest that several of our proposed eye tracking tests have extremely high diagnostic accuracy. Findings, however, are sometimes not replicated in science, and we proactively address this by proposing concurrent, independent and exact (equipment, software, paradigms, procedures) replication testing of each of our eye tracking tests within an independent cohort of toddlers at U. Washington (n=90 toddlers). Thus, in AIM 1 we will discover an eye tracking biomarker that detects ASD at early ages (12?36 months) with high accuracy using artificial neural networks at UCSD, and then we will independently test replication of its performance at U Washington. To enhance interpretability, our approach will incorporate patterns of metrics from each eye tracking test to produce an Autism Risk Score (ARS) scaled from 0?100 that represents the level of ASD risk for a toddler. In AIM 2, using a rich clinical battery that captures each toddler's social, language, cognitive and symptom severity profile derived from a combination of standardized, parent report, and free?play testing, we will identify clinically meaningful eye?tracking based subtypes of ASD using unbiased network clustering approaches. In AIM 3 we will examine the prognostic utility of our eye tracking test battery by identifying the degree to which eye tracking?based profiles at ages 12?36 months can predict social, language, cognitive and attention abilities 1?2 years later.

Autism spectrum disorder (ASD) impacts almost 2% of children born today, yet very little is known regarding how to positively alter the outcomes of affected children. On the one hand, many, including the American Academy of Pediatrics, believe that early universal screening at well baby check?ups is an important step towards a positive outcome because it can lead to early treatment. In contrast, the United States Preventive Services Task Force (USPSTF) recently failed to endorse early universal ASD screening, noting that the benefits of doing so are poorly understood. What is needed to inform the debate is to examine the outcomes of a large cohort of children detected very early via universal screening at well?baby checks, and to compare them to children who did not participate in an early detection program. Here we propose to do just that: We will examine the school age outcomes (age 6?10 years) of an unprecedented sample size of 242 children with ASD detected very early in San Diego and Phoenix (i.e., ?west coast cohort?) through our Get SET Early program, which involved screening with the CSBS at well baby check? ups (mean age 17.7 months, range 12?24 months), and immediate referral for comprehensive evaluation and treatment if warranted. They will then be compared to a cohort of 242 ASD community children matched on age, gender, race, ethnicity, and SES who did not participate in our early detection program (Total N = 484). Given the rarity and uniqueness of our cohort, we plan to characterize outcomes not only on traditional measures of cognition, social behavior, etc., but also on outcome on school achievement (e.g., fully mainstreamed and/or lost their diagnosis) and family functioning (do families experience less stress?). Since the national mean age of ASD diagnosis is around 4 years, we expect that children in the community cohort will have later ages of diagnosis and poorer outcomes than those identified early via the Get SET Early program. With scientific rigor and reproducibility in mind, we will proactively test the replication of findings in an independent cohort (N=103) of toddlers screened in Boston, Philadelphia, and New Haven (i.e., ?east coast cohort?) through Project Early and a matched community cohort from the same region (Total N=120). Our specific aims are: AIM 1a: we will identify clinically meaningful outcome subtypes of ASD in our west coast cohort using unbiased network clustering approaches. AIM 1b: with this unique longitudinal cohort, we will examine changes in symptom profile, IQ and adaptive functioning between toddler and school ages. AIM 1c: we will evaluate program impact by comparing the outcomes children in our early?detected to the community cohort. AIM 1d: we will examine how well findings are replicated in our East coast sample. AIM 2: using complimentary regression and machine learning techniques, with our total sample collapsed across both west and east coast cohorts (N=602), we will test our model that earlier age at identification and treatment leads to improved outcomes. To examine other factors relating to a good outcome, moderating variables such as SES and level of treatment participation will also be included in our models. AIM 3: since state context (e.g., policies, guidelines) could also play a role in outcomes, in we plan to collect key state?level information to place our findings in context.