# A SYSTEMS APPROACH TO THE GENETIC STUDY OF ALCOHOL DEPENDENCE

> **NIH NIH R01** · LIEBER INSTITUTE, INC. · 2020 · $390,754

## Abstract

Alcohol dependence (AD), one of the leading causes of disability worldwide, is a chronic and recurrent
psychiatric illness. Twin studies have established a significant genetic contribution to AD susceptibility.
Variations in hundreds of genes likely contribute to the etiology of AD, with each genetic variant conferring only
a small increase in risk. Although numerous genes may contribute to the etiology of complex diseases, they
tend to fall into a smaller number of biological pathways. In addition, accumulating evidence suggests a large
portion of the risk variants for complex diseases are located in regulatory DNA sequences in disease-related
tissue or cell types. Studies leveraging already existing data may increase the power of gene discovery for
these disorders, which include AD. This proposal aims to employ a systems biology-based approach to identify
gene networks and regulatory variants underlying AD. To that end, we will perform integrated analysis of
genome-wide association studies (GWAS) of AD with brain-specific differential gene co-expression networks
(DCNs) and transcriptional regulatory networks (TRNs). Our approach to network construction will use brain
region-specific data, on gene expression and regulatory function. Our specific aims are: 1) Identify gene
subnetworks underlying AD through integrated analysis of GWAS with brain-specific DCNs; 2) Identify
regulatory risk variant sets through integrated analysis of GWAS with brain-specific TRNs; and 3) Evaluate the
function of identified gene subnetworks and regulatory variants using existing imaging genetics data. We have
assembled an outstanding multidisciplinary team with expertise in AD genetics, genomics, computational
biology, and neuroimaging. Our goal is to apply multidisciplinary and cutting-edge analytical strategies in the
service of advancing the field of AD genetics. The identification and characterization of risk genes and
regulatory variants would help improve our understanding of the biological mechanisms that underlie AD,
moving us closer to designing effective prevention and treatment for the disorder.

## Key facts

- **NIH application ID:** 10187881
- **Project number:** 7R01AA024486-06
- **Recipient organization:** LIEBER INSTITUTE, INC.
- **Principal Investigator:** SHIZHONG HAN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $390,754
- **Award type:** 7
- **Project period:** 2017-03-01 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10187881

## Citation

> US National Institutes of Health, RePORTER application 10187881, A SYSTEMS APPROACH TO THE GENETIC STUDY OF ALCOHOL DEPENDENCE (7R01AA024486-06). Retrieved via AI Analytics 2026-06-02 from https://api.ai-analytics.org/grant/nih/10187881. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*