# Center for Genetic Studies of Drug Abuse in Outbred Rats

> **NIH NIH P50** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2020 · $354,375

## Abstract

Project 4: Summary
While genome­wide association studies (GWAS) have linked many genetic loci to complex diseases, the loci
mapped thus far account for a small fraction of the total genetic variation affecting these phenotypes. This
limitation is common to both human GWAS and GWAS in model organisms such as the heterogeneous stock
(HS) rats that are the focus of this center. To better capture the genetic signal, we (laboratory of Project 4
Director Trey Ideker) and many others have argued that GWAS results must be integrated with fundamental
knowledge of molecular and cell biology, as captured by biological network models. To this end, we will create
computational analysis tools to synthesize GWAS data with molecular network information, advancing the
current state of computational genetic analysis. These tools will be benchmarked and applied in the context of
diverse drug abuse­related behavioral phenotypes studied by Projects 1, 2, and 3, as well as phenotypes being
studied by the separately funded “affiliated grants.” Work will progress along three Specific Aims: First, we will
mature and apply the technique of network propagation for gene association analysis. In recent studies,
network propagation has been shown to substantially boost power to identify reproducible and functional
genetic associations, while also providing concrete hypotheses as to the underlying molecular mechanisms
transmitting genotype to phenotype. We will also extend this method to integrate Transcript Wide Association
Study (TWAS) approaches. Second, we will develop molecular networks as a tool for translation of GWAS
results between rat and human studies related to drug abuse. This aim will rely on the conservation of
molecular pathways between species to find overlapping mechanisms associated with both rat and human
phenotypes. Third, we will build on the above results to develop a hierarchical reference model of pathways in
which genetic variation is associated with drug abuse. We will explore the extent to which this pathway
hierarchy can be used to structure a deep artificial neural network (ANN) for translation of genotype to
phenotype. This system, based on a previously published prototype in budding yeast, will be extended along
significant lines for application to mammalian genetics. If successful, it will not only make accurate predictions
of phenotype from genotype, it will also be interpretable and fuel mechanistic hypotheses relevant to the
development of novel treatments for drug abuse.

## Key facts

- **NIH application ID:** 9971506
- **Project number:** 5P50DA037844-08
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Trey Ideker
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $354,375
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9971506

## Citation

> US National Institutes of Health, RePORTER application 9971506, Center for Genetic Studies of Drug Abuse in Outbred Rats (5P50DA037844-08). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9971506. Licensed CC0.

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