# Beyond GWAS: High Throughput Functional Genomics & Epigenome Editing to Elucidate the Effects of Genetic Associations for Schizophrenia

> **NIH NIH R01** · DUKE UNIVERSITY · 2022 · $1,599,191

## Abstract

Project Summary
Schizophrenia (SCZ) genomics has achieved unprecedented advances. A decade ago, there was perhaps one
solid finding, and there are now ~270 loci that meet consensus criteria for significance and replication. As
observed for other complex psychiatric disorders, the identified regions are overwhelmingly noncoding,
strongly suggesting that genetic variation in gene regulatory elements is a major mechanistic contributor.
Further investigation of those regulatory mechanisms is precluded by a fundamental gap in the ability to
identify, characterize, and quantify brain-relevant regulatory elements, and limited understanding of how
genetic variation within those elements influences their function.
To address this knowledge gap, this project will comprehensively identify, characterize, quantify, and validate
noncoding functional noncoding regulatory elements and variants in neuronal cells. The central hypothesis of
the proposal is that noncoding variation contributes to psychiatric disorders by directly altering the function of
regulatory elements in the brain. The motivation for the proposed study is that identifying regulatory
mechanisms of psychiatric disorders has the potential to translate into improved diagnosis and treatment.
Powered by a team with strong interdisciplinary expertise in psychiatric disorders, functional genomics,
technology development, and statistical genetics, this hypothesis will be tested by completing three specific
aims: 1) Comprehensive integration of diverse data types to generate hypotheses that “connect”
psychiatric genetic results to specific genes; 2) perform high-throughput CRISPR epigenome editing
screens to test Aim 1 hypotheses in a natural biological context; 3) Develop mechanistic understanding and
validate functional noncoding SCZ risk variants using TF binding assays and iPS-derived neurons from SCZ
cases with high genetic risk scores.
Our approach is innovative because it uses a highly complementary and diverse set of experimental
approaches to drive targeted genetic and functional investigation into regulatory mechanisms relevant for SCZ.
In doing so, the proposed research provides a much-needed path forward to understand how noncoding
variation contributes to complex human phenotypes.

## Key facts

- **NIH application ID:** 10377555
- **Project number:** 5R01MH125236-02
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** GREGORY E CRAWFORD
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,599,191
- **Award type:** 5
- **Project period:** 2021-04-01 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10377555

## Citation

> US National Institutes of Health, RePORTER application 10377555, Beyond GWAS: High Throughput Functional Genomics & Epigenome Editing to Elucidate the Effects of Genetic Associations for Schizophrenia (5R01MH125236-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10377555. Licensed CC0.

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