As a computational psychiatry faculty candidate with a strong background in neuroimaging and quantitative data analysis, I seek mentored-support to incorporate genetic and transcriptomic data into my work during my path towards independence as an investigator. I propose a project at the intersection of human neuroimaging, genomics and transcriptomics, using computational tools from network theory to investigate risk for schizophrenia and other forms of chronic psychosis. Prior work suggests that synaptic over-pruning in adolescence disrupts functional and structural connectivity within brain networks, giving rise to symptoms and functional impairments associated with schizophrenia. This process is a product of the interplay of genetic and environmental factors in development, and it is reflected in alterations observed in structural and functional neuroimaging. Network-based analytic approaches allow one to extract deeper insights into the nature of the disturbances in network function, in contrast to simpler attempts to link complex diseases to single brain regions, genes or proteins. The project uses an imaging-genomics approach to test whether networks of genes that are implicated in schizophrenia risk by genome-wide studies of common genetic variants ? and have been shown in many cases to be related to synaptic integrity ? affect the development of cortical thickness and the functional connections within and between brain networks in typical adolescence. The project also proposes to directly test whether these genetic factors jointly influence these imaging phenotypes and psychosis risk in clinical samples. To meet the research goals of the project, I require formal training in genomics and transcriptomics approaches (and especially their intersection with neuroimaging research). The primary mentorship team (Drs Pearlson and Glahn) has specific expertise in imaging-genomics in clinical datasets, as well as extensive experience as successful research mentors. Other key contributors and consultants provide expertise in imaging-transcriptomics (Dr Holmes), developmental neuroimaging (Dr Satterthwaite), data and network science (Dr Bassett), developmental transcriptomics (Dr Geschwind) and statistical genetics (Dr Blangero). This proposal will provide me with the direct training in research methodology and career support that is required for me to become a fully independent investigator, using tools from neuroimaging, genomics and transcriptomics to investigate psychosis pathogenesis.

Public Health Relevance

The NIMH Council Workgroup on Genomics recently highlighted the central challenge of translating the highly polygenic risk for psychiatric disorders into clear pathophysiologic mechanisms. This application will prepare the candidate for a career that addresses this core challenge by engaging him in big data integration across functional hierarchical levels (genomics, transcriptomics, and neuroimaging phenomics) for the purpose of linking neuroimaging evidence of synaptic over-pruning to its molecular underpinnings. By combining brain MRI, genomic and transcriptomic data in clinical and developmental samples, this project targets genetic signals that both influence brain function and contribute to schizophrenia risk.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Clinical Investigator Award (CIA) (K08)
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Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
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Chavez, Mark
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Children's Hospital of Philadelphia
United States
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