2008 — 2012 |
Jacob, Suma |
K23Activity Code Description: To provide support for the career development of investigators who have made a commitment of focus their research endeavors on patient-oriented research. This mechanism provides support for a 3 year minimum up to 5 year period of supervised study and research for clinically trained professionals who have the potential to develop into productive, clinical investigators. |
Autism: Neuropeptide Hormones and Potential Pathway Genes @ University of Illinois At Chicago
[unreadable] DESCRIPTION (provided by applicant): Autism spectrum disorders (ASD) are increasingly recognized, but the mechanisms that lead to the development of these disorders are poorly understood. With the emergence of improved diagnostic measures and genetic technology, the field has realized that phenotypic heterogeneity is largely due to multiple genes. There are few investigators trained to identify phenotypic differences in behavior and physiology within this broad diagnostic spectrum, and even fewer simultaneously trained to integrate this with the study of genetic underpinnings. The candidate has had structured child psychiatry training and will now expand on her research skills through a unique integration of clinical and basic science. The 5 year training proposal (K23) will permit her to develop into an independent clinical investigator by gaining expertise in measuring clinical and neurochemical subphenotypes as well as applying genetic tools to examine associations. The project described below has been designed to develop relevant research skills to bridge interdisciplinary fields under the mentorship of Edwin Cook, Jr., M.D., a clinical research expert in autism and genetics, and C. Sue Carter, Ph.D., a basic science expert in specific neurohormonal measures that have been shown to vary in autism. The principal investigator will study children with ASD by focusing on clinical phenotype, neurochemical measures and genetic associations of related neuropeptide hormones, including oxytocin (OT) which is currently under trial for ASD treatment. Using an existing sample of patients, the investigator will examine whether genes in the OT and vasopressin (AVP) systems are associated with autism overall, and with specific phenotypic subgroups. She will also conduct a clinical study to test the hypothesis that phenotypic differences in peripheral OT levels are related to allelic variance of specific OT pathway processing genes. Over the 5-year training period, 250 outpatient subjects with ASD, ages 5-18 years, will be recruited for diagnostic, OT/AVP blood assay, and genetic pathway testing. They will be an eligible subset of the 650 patients fully assessed by the University of Illinois at Chicago (UIC) Autism Center of Excellence and Simons Genetics Projects. UIC provides an ideal environment for training given the overlap of multidisciplinary expertise and support to establish a program of research within this highly needed scientific interface. [unreadable] [unreadable] [unreadable]
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0.943 |
2020 — 2021 |
Elison, Jed Thomas (co-PI) [⬀] Jacob, Suma |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Parsing Early Emerging Heterogeneity Related to Autism Spectrum Disorder @ University of Minnesota
A major impediment to early identification and intervention for autism spectrum disorder (ASD) is our limited understanding of how different children present signs as toddlers, including what risk symptoms coincide across multiple dimensions to predict outcome. Our objectives are to quantify behavioral and brain connectivity based subtypes of risk that model the variability of ASD symptom expression in a community sample of toddlers. We will then test the predictive validity of this approach in the same cohort of children at three years of age in order to identify risk profiles that differentially predict later cognitive, behavioral, and clinical features. First, we will implement two unsupervised data-driven computational approaches in a community sample of 3000 children between 18-24 months old in order to characterize clusters of risk profiles. We hypothesize that each approach will identify a proportion of high-risk individuals consistent with epidemiological estimates of ASD and associated developmental disabilities (e.g., language or global DD). Based on our preliminary data, we anticipate that ~300 children will be identified by these data-driven risk-profiling methods. We also hypothesize that distinct patterns of structural and functional connectivity will distinguish groups of at-risk children and that these groups will differ from low-risk children. All children will be scanned with the same brain imaging sequences and procedures implemented in the Baby Connectome Project and will be compared to data from 100 low-risk children from that project. Our neuroimaging sample of 300 children will be reassessed at age three with direct clinical assessment using gold-standard diagnostic instruments as well as parent report. This will allow us to validate the risk profiling approach implemented at 18-24 months, to compare with a current screening approach, and to refine the risk profiling approach with supervised training of prediction algorithms that incorporates behavioral/clinical outcome data. We expect this method for risk stratification/subtyping to better model the heterogeneity inherent to the early at-risk and resilient phenotypes, which will subsequently improve early identification/diagnosis efforts. These outcomes will have translational impact because improved methods for early identification in ASD are necessary for the successful development of efficacious, personalized early interventions.
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