| 2018 — 2020 |
Forsyth, Jennifer Katherine |
K08Activity Code Description:
To provide the opportunity for promising medical scientists with demonstrated aptitude to develop into independent investigators, or for faculty members to pursue research aspects of categorical areas applicable to the awarding unit, and aid in filling the academic faculty gap in these shortage areas within health profession's institutions of the country. |
From Genotypes to Phenotypes in Schizophrenia: a Developmental Functional Genomics Approach @ University of California Los Angeles
PROJECT SUMMARY Efforts to understand the core biological processes underlying schizophrenia (SCZ) have been hampered by the clinical and genetic heterogeneity of the disorder. However, large-scale genomic studies have begun to yield major insights into the genetic architecture of SCZ. Applying a developmental functional genomics approach to characterize findings from large-scale genomic studies of SCZ and related disorders, and examine relationships between genotypes and phenotypes in well-characterized cohorts may therefore help determine which neurotypical processes are most impacted by genetic risk for SCZ, and facilitate the discovery of links between specific genotypes and phenotypes in SCZ. In line with NIMH Strategic Objective 1, the PI therefore aims to: 1) integrate large-scale genomic findings for schizophrenia and related neurodevelopmental disorders with gene co-expression networks derived from the developing human brain to understand the impact of polygenic risk for schizophrenia on brain development at the clinical population level; and 2) using a unique cohort of 500 predominantly recent-onset SCZ patients with rich clinical, cognitive, and structural magnetic resonance imaging phenotyping, determine whether specific genetic risk profiles predict distinct phenotypes among SCZ patients. In particular, the PI will evaluate the extent to which common and rare variants associated with SCZ and related neurodevelopmental disorders converge on developmentally regulated biological pathways (Aim 1), derived from applying weighted gene co-expression network analyses (WGCNA) to BrainSpan transcriptomic data. Then, using common and rare variant data derived from genome-wide association study (GWAS) chips and whole exome sequencing in a cohort of 500 SCZ patients at UCLA, the PI will test whether common variants, rare variants, and/or their combination in biologically-partitioned genetic risk profiles (partitioned based on BrainSpan modules developed in Aim 1) predict current and premorbid clinical and cognitive phenotypes (Aim 2); and/or specific neuroanatomic characteristics (Aim 3). Through structured coursework, mentoring from a team of distinguished scientists (Drs. Bearden, Ophoff, Nuechterlein, and Geschwind), and UCLA's outstanding infrastructure for genomics, neuroimaging, and psychosis research, the proposed research and training plan will allow the PI to extend her training to work with whole-genome genotyping and exome sequencing data; deepen her knowledge of bioinformatics, neurodevelopmental disorders, and neuroimaging; and ultimately, transition to an independent investigator able to integrate genomic, clinical, and neuroimaging data to help map the pathogenesis of SCZ through development. Successful completion of this project will provide mechanistic insights into the neurotypical processes impacted by genetic risk for SCZ and has the potential to inform biologically valid subtypes of SCZ with distinct developmental trajectories, in line with NIMH Strategic Objective 2.
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