Discovery of novel pharmacotherapeutic targets for opioid addiction

发现阿片类药物成瘾的新药物治疗靶点

基本信息

项目摘要

PROJECT SUMMARY/ABSTRACT The US is in the midst of an opioid abuse and overdose epidemic. Oxycodone is one of the most prescribed analgesics, is the first opioid many people experience, and has physiochemical properties that allow it to accumulate in the brain at rates higher than other opioids, perhaps explaining its considerable abuse potential. Here, I seek to perform high-throughput experiments to generate brain-wide data on the cellular and molecular mechanisms of cue-induced reinstatement to oxycodone seeking. Specifically, I propose to use FosCreER mice to fluorescently `tag' neuronal ensembles activated by cue-induced reinstatement. I will then use cutting-edge transcriptomics to identify relapse-related genes in these cellular ensembles that drive reinstatement. I will then prioritize, and test, whether these genes may serve substrates for the development of novel medications to prevent relapse using a ”circuit therapeutic” approach. In aim 1, iDISCO+, a lipid clearing method, will produce brain-wide data on regions activated by relapse. I will then use ClearMap, a published Python package, to conduct high-throughput detection of activated neurons and registration of coordinates onto the Allen Brain Atlas. I will then rigorously examine this large data set, and test whether reinstatement-responsive cell ensembles in prioritized structures contribute to relapse behavior. In aim 2, I will focus on cellular populations in brain regions shown to be required for relapse-related behavior, and will again tag neurons activated by reinstatement in these sites. Tissue will be dissected, and fluorescence activated cell sorting will be used to isolate these activated neurons for trancriptomic profiling via RNA-Seq. Together, these two aims will yield large data sets directly related to the neurocircuitry and molecular biology of reinstatement of oxycodone seeking. I will once again rigorously analyze these data sets, with strict adherence to pre-established criteria, to prioritize reinstatement-responsive genes most likely to represent efficacious targets for development of novel pharmacotherapeutics. Following completion of the training phase, in aim 3 I will extend these findings to both rat and mouse models of self-administration, and will validate that these transcriptomic adaptations occur across species, and that they are detected as changes in functional proteins. Once again, I will rigorously prioritize these targets for translational potential. In aim 4 I will use pharmacological agents that modulate prioritized protein targets to determine whether they can block cue-induced reinstatement of oxycodone seeking, focusing on compounds that may be able to quickly move into clinical settings. The training added in this proposal will allow me to emerge as an exceptionally well-rounded independent investigator. During my independent career I will perform translational research to develop novel circuit-based therapeutics for prevention of relapse.
项目总结/文摘

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Opposing roles for striatonigral and striatopallidal neurons in dorsolateral striatum in consolidating new instrumental actions.
  • DOI:
    10.1038/s41467-021-25460-3
  • 发表时间:
    2021-08-25
  • 期刊:
  • 影响因子:
    16.6
  • 作者:
    Smith ACW;Jonkman S;Difeliceantonio AG;O'Connor RM;Ghoshal S;Romano MF;Everitt BJ;Kenny PJ
  • 通讯作者:
    Kenny PJ
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Alexander Wanless Smith其他文献

Alexander Wanless Smith的其他文献

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{{ truncateString('Alexander Wanless Smith', 18)}}的其他基金

Discovery of novel pharmacotherapeutic targets for opioid addiction
发现阿片类药物成瘾的新药物治疗靶点
  • 批准号:
    9891675
  • 财政年份:
    2020
  • 资助金额:
    $ 17.15万
  • 项目类别:
Discovery of novel pharmacotherapeutic targets for opioid addiction
发现阿片类药物成瘾的新药物治疗靶点
  • 批准号:
    10596237
  • 财政年份:
    2020
  • 资助金额:
    $ 17.15万
  • 项目类别:
Discovery of novel pharmacotherapeutic targets for opioid addiction
发现阿片类药物成瘾的新药物治疗靶点
  • 批准号:
    10616803
  • 财政年份:
    2020
  • 资助金额:
    $ 17.15万
  • 项目类别:

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