# Delineating genetic risk to addiction via analysis of 3D chromatin architecture

> **NIH NIH DP1** · WHITEHEAD INSTITUTE FOR BIOMEDICAL RES · 2021 · $555,750

## Abstract

Project Summary:
Addition to opioids and substance abuse disorders are one of the most urgent public health
crises in the US, with drug overdose being the leading cause of accidental death. 20% of
individuals who try heroin become addicted to opioids. Genetics plays a major role in defining
this variability. Opioid addiction is estimated to be 60% heritable, however the variants and
genes that define this heritability have remained elusive. As has been observed with diseases
like schizophrenia, increased sample size and power for Genome Wide Association Studies
may help to reveal more of the genetic basis of addiction. However, identifying the loci
associated with addiction is only the first step. In order to translate these findings into insights
that can further treatment or prevention of substance abuse disorders we must also determine
the consequence of addiction susceptibility loci. Delineating the genes, pathways, and cellular
phenotypes that are altered by a given risk locus is a substantial challenge and has been the
major roadblock in the translation of GWAS results to clinically actionable findings. We propose
to utilize 3-dimensional architecture of the genome to enable a hypothesis-driven evaluation of
the genetic risk to addiction. This approach will entail identifying the cis-regulatory elements that
control gene expression in tissues, cell types and contexts that are relevant to the
pathophysiology of addiction. We propose to combine post-mortem tissue studies with iPS-
derived astrocytes, microglia, oligodendrocytes and dopaminergic neurons to provide deeper
resolution of the cell types and brain regions which contribute to addiction susceptibility. Finally,
we propose to utilize the iPS-derived cell types to identify loci may be suitable for functional
studies and utilize genome editing to investigate the impact of regulatory elements associated
with risk to addiction. Rather than analyze each cis-regulatory element and SNP individually,
this approach will evaluate the genetic variation across all regulatory elements that control
expression of a shared target gene. This approach has the potential identify new risk loci for
addiction and streamline the identification of the mechanism by which these variants contribute
to addiction susceptibility.

## Key facts

- **NIH application ID:** 10224157
- **Project number:** 5DP1DA044337-05
- **Recipient organization:** WHITEHEAD INSTITUTE FOR BIOMEDICAL RES
- **Principal Investigator:** Olivia Gabrielle Corradin
- **Activity code:** DP1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $555,750
- **Award type:** 5
- **Project period:** 2017-09-15 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10224157

## Citation

> US National Institutes of Health, RePORTER application 10224157, Delineating genetic risk to addiction via analysis of 3D chromatin architecture (5DP1DA044337-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10224157. Licensed CC0.

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