# From Genotypes to Phenotypes in Schizophrenia: A Developmental Functional Genomics Approach

> **NIH NIH K08** · UNIVERSITY OF WASHINGTON · 2022 · $183,338

## Abstract

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 650 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 650 SCZ patients, 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
Eichler), and UCLA and UW’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, ...

## Key facts

- **NIH application ID:** 10490530
- **Project number:** 7K08MH118577-04
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Jennifer Katherine Forsyth
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $183,338
- **Award type:** 7
- **Project period:** 2018-09-12 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10490530

## Citation

> US National Institutes of Health, RePORTER application 10490530, From Genotypes to Phenotypes in Schizophrenia: A Developmental Functional Genomics Approach (7K08MH118577-04). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/10490530. Licensed CC0.

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