The current opioid epidemic is fueled by the steady rise of prescription painkillers, such as OxyContin, which is a controlled-release tablet of oxycodone. Although both clinical and animal studies have found that the rate of onset of drug action influences the development of addiction, the exceptionally strong abuse liability of oxycodone was manifested even when it was consumed in the controlled-release from. The heritability of opioid addiction has been estimated to be approximately 0.5 in humans. However, few human genetics studies have been conducted due to the difficulty in assembling the necessary large study population. In this proposal, we aim to conduct a genetic mapping study to identify genetic factors influencing oxycodone-motivated behaviors and vulnerability to stress, a major risk factor of opioid use disorder. To follow the clinical use pattern, we developed an operant oral oxycodone self-administration model, where rats voluntarily consume oral oxycodone to obtain doses that are well above clinical prescriptions. The WMI and WLI inbred strains of rats we propose to use in this study were selectively bred from the stress-vulnerable Wistar Kyoto rat. The WMI is an established animal model of depression and vulnerability to stress, while the WLI serves as its isogenic control. Our preliminary data showed higher levels of oxycodone intake and oxycodone seeking in the WMI compared to the WLI strains. We also found that females have higher oxycodone intake than males. There were also strain and sex differences in basal plasma corticosterone (CORT) and steady-state hippocampal glucocorticoid receptor (Nr3c1) expression. We therefore hypothesized that genetically-determined stress response to oxycodone withdrawal drives the strain differences in oxycodone self-administration and reinstatement of oxycodone seeking.
In Aim 1, we will use a reduced complexity mapping strategy to identify the causal genetic factors for oxycodone and stress response phenotypes. This mapping strategy is supported by the high heritability, large effect size of strain on phenotypes, and existing whole genome sequencing data for the WMI and WLI strains ( ~100x coverage per strain, with ~4,400 high confidence polymorphisms between strains).
In Aim 2, we will identify candidate genes using a systems genetics approach. The low number of segregating variants between WLI and WMI greatly facilitates this goal.
In Aim 3, we will confirm causal genes using an established knockin CAG-LSL-Cas9 rat model on the WMI/WLI genetic background.
