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

NIH RePORTER · NIH · R01 · $1,653,935 · view on reporter.nih.gov ↗

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
10115982
Project number
1R01MH125236-01
Recipient
DUKE UNIVERSITY
Principal Investigator
GREGORY E CRAWFORD
Activity code
R01
Funding institute
NIH
Fiscal year
2021
Award amount
$1,653,935
Award type
1
Project period
2021-04-01 → 2026-01-31