The steady rise in prescription opioids such as oxycodone has led to widespread abuse and deaths in the US.
importance of drug pharmacokinetics in determining abuse potential, we have designed an oral
operant rat self-administration (SA) procedure to model the pattern of drug intake of most human users/abusers
of oxycodone, who initiate using oral tablets. Although genetic variants play important roles in susceptibility to
opioid addiction, very limited data are available regarding specific genes and sequence variants that predispose
to opioid addiction, and under what conditions.
We propose to use an innovative hybrid rat diversity panel
(HRDP), which consists of 91 diverse rat genomes, to identify genetic variants influencing operant oxycodone
intake in rats. The HRDP is unique in that it: 1) contains a high level of genetic diversity similar to that of human
populations; 2) provides a way to control oxycodone exposure and to systematically study gene-by-environment
and gene-by-drug interactions; and 3) integrates multi-omics "addictome" data: from genetics to epigenomics to
brain connectomes to treatments. We have three aims: Aim 1: We will analyze whole genome sequencing data
to define virtually all sequence variants that underlie heritable variations. De novo assemblies will be conducted
using linked-reads data for selected high impact strains. Hi-C data (Dovetail Genomics) will be generated to
further improve the quality of these assemblies. We will also generate RNA-seq data for key brain regions to
obtain mechanistic insights into oxycodone intake. Aim 2: Using the HRDP (both sexes), we will phenotype oral
oxycodone SA with a unique behavioral model. Rats will also be tested for sensitivity to pain, social behaviors,
and anxiety-like traits - all signs of oxycodone withdrawal. Critically, we estimated the heritability (h2) of
oxycodone intake in the range of 0.3 – 0.4. When using n=6/sex, the effective h2 is ~0.8 —sufficient for high
precision mapping. Aim 3: We will use systems genetics methods to map and integrate behavioral phenotypes
with sequence and transcriptome data. Both forward (QTL) and reverse (PheWAS) genetic methods will be used.
We use new linear mixed models to map and test candidate genes with key cofactors using the GeneNetwork2
platform. Finally, we evaluate the translational relevance of candidate genes and biomarkers by comparison to
GWAS cohorts and longitudinal reports of addiction in humans. Technical and conceptual advances that underlie
this application are: new genomic methods combined with highly diverse rat populations allow us to quickly
define novel gene variants that modulate key phases of opiate addiction. It is highly likely that a subset of variants
and molecular networks we define will provide key components of a predictive framework linking sequence
differences to human opioid addiction and potential treatments. This project uses new systems genetics
approaches, open source genomic data and software, and a new type of hybrid rodent mapping panel to
precisely define causal linkages between DNA variation and voluntary oxycodone intake.