# Use of Next-Gen Sequencing to Identify Genetic Variants that Influence compulsive Oxycodone Intake in Outbred Rats

> **NIH NIH U01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2023 · $924,074

## Abstract

Abstract
The purpose of the NIDA Animal Genetics Program is to identify genetic, genomic, epigenetic variants,
physiology and brain functions that contribute to addiction-like behaviors, related behavioral endophenotypes,
and behavioral comorbidities to substance use disorder. During the past four years, our multidisciplinary and
highly collaborative consortium has been identifying gene variants that are associated with increased
vulnerability to compulsive oxycodone use, tolerance to the analgesic effects of oxycodone, and development
of withdrawal-induced hyperalgesia by performing the first GWAS using an advanced model of chronic
intravenous oxycodone self-administration in N/NIH heterogeneous stock (HS). We have also created the first
preclinical oxycodone biobank which enables researchers who do not have the resources to perform chronic
intravenous self-administration or next-generation genome sequencing to perform advanced genetic,
molecular, and cellular studies to further our understanding of the biological changes underlying addiction-like
behaviors. While these efforts have been very successful in achieving the planned milestones, it has become
clear that our project would benefit from an even larger sample size. In particular, increasing sample sizes lead
to exponential rather than linear increase in the number of loci identified, and would allow us to identify sex-
specific gene variants. Moreover, in the past four years there has been tremendous technological advances in
behavioral and genetic analysis that can be leveraged to provide unprecedented access to identify the single
nucleotide and structural variants that contribute to complex behavioral endophenotypes of high relevance to
oxycodone use-disorders. The first goal of this competing renewal is to double the sample size of the current
GWAS to increase the number of gene variants identified including sex-specific variants and meet the
demands of the Biobank. The second goal is to use high-throughput behavioral phenotyping using markerless
pose estimation based on machine learning with deep neural network to identify behavioral endophenotypes
that can help predict and identify individuals with a resistant, mild, moderate, or severe phenotype of
oxycodone addiction-like behaviors. The third goal is to use methodological improvements of the genetic
analysis, including the analysis of structural variants and tandem repeats, as well as enhanced integration with
gene expression data. The fourth goal is to strengthen the oxycodone biobank infrastructure. This project is
likely to continue having a sustained and powerful impact on the field because it will provide an exponential
increase in the number of genetic loci identified, eQTLs and PheWAS analysis related to addiction-like
behavior; establish the first high-throughput behavioral motifs analysis of addiction-like behaviors using parallel
video-recording and automated machine learning analysis; identify novel behavioral endopheno...

## Key facts

- **NIH application ID:** 10671889
- **Project number:** 2U01DA044451-07
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Olivier George
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $924,074
- **Award type:** 2
- **Project period:** 2018-04-01 → 2028-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10671889

## Citation

> US National Institutes of Health, RePORTER application 10671889, Use of Next-Gen Sequencing to Identify Genetic Variants that Influence compulsive Oxycodone Intake in Outbred Rats (2U01DA044451-07). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10671889. Licensed CC0.

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