Opioid effects on cognition and addiction: Molecular underpinnings

项目摘要 阿片类药物过量每天导致130多名美国人死亡，每年造成47,500多人死亡， 每23天9/11袭击中的死亡人数。治疗阿片类药物使用障碍(OUD)的最佳方法是 药物辅助治疗，如美沙酮、丁丙诺啡或纳曲酮，不足以支撑 这场流行病。未能治疗OUD的原因是不了解OUD的分子病理生理学， 包括其作为一种生物、心理和行为疾病的临床表现，神经生物学 强化其消费的机制，以及重复消费如何影响其他神经认知 流程。赫德实验室最近发现了一个与该蛋白下游的OUD相关的基因组位点。 人类海洛因滥用者纹状体神经元中的酪氨酸激酶FYN。此外，海洛因增加了Fyn 海洛因自我给药大鼠纹状体和初级纹状体神经元的表达 文化。Fyn使tau磷酸化，tau的过度磷酸化被认为是神经纤维缠结的先导， 这是神经认知疾病的特征。该方案利用高通量电子病历(EMR) 从西奈山健康系统研究长期阿片类药物暴露如何影响神经认知的几率 疾病(NCD)在人口层面上，以及来自哥伦比亚大学和哥伦比亚大学其他两家医院的EMR 来复制这些效应，使用相同的分析管道。此外，我提出了机械论 Fyn在眶前叶皮质(OFC)过度表达的研究，已知该区域在NCD和OUD中受影响， 用动物模型研究海洛因SA和认知行为。此外，我还使用了一种机器学习方法 从人死后OFC组织获得的RNA-SEQ数据，以将受试者分类为属于 海洛因过量组或对照组基于~10个基因的表达。三个特征(基因)重要性度量 重点介绍了在人类OFC中降低的转录产物SHISA7，这一发现在OFC中也得到了复制 接受海洛因自我给药的大鼠。SHISA7和FYN均调节AMPA的突触功能 受体，是谷氨酸能神经元突触后密度的组成部分。我会研究一下影响 使用这种机器学习方法确定的SHISA7在海洛因SA和OFC中的过度表达 动物模型中的认知行为。最后，我将对Fyn-OFC进行RNA测序实验。 和Shisa7操纵的动物，并在下游的生物信息学分析中，解析基因的关键驱动因素 网络，以确定解释这些基因对海洛因SA和 认知行为。来自人类的高通量临床和基因表达数据可以为翻译， 使用动物模型的机制研究将使人们能够对分子有深远的了解 阿片类药物对认知和成瘾影响的潜在干扰。

Project Summary Opioid overdoses kill more than 130 Americans every day, yielding over 47,500 deaths per year, and the same number of deaths in the 9/11 attacks every 23 days. The best treatments for opioid use disorder (OUD) are medication-assisted therapies such as methadone, buprenorphine, or naltrexone, and are inadequate to buttress the epidemic. Failure to treat OUD is sourced in not understanding the molecular pathophysiology of OUD, including its clinical manifestations as a biological, psychological, and behavioral disease, the neurobiological mechanisms that reinforce its consumption, and how repeated consumption affects other neurocognitive processes. The Hurd lab recently discovered a genomic locus associated with OUD, downstream of the protein tyrosine-kinase FYN, in striatal neurons from human heroin abusers. Additionally, heroin increased Fyn expression in the striatum of rats that undergo heroin self-administration (SA), and in primary striatal neuronal cultures. FYN phosphorylates tau, and hyperphosphorylation of tau is known to precede neurofibrillary tangles, a hallmark of neurocognitive disease. This proposal leverages high-throughput electronic medical records (EMR) from the Mount Sinai Health System to examine how chronic opioid exposure affects the odds of neurocognitive disease (NCD) on a population level, and EMR from two other hospitals at Columbia University and the University of San Francisco to replicate these effects, using the same analysis pipeline. Additionally, I propose mechanistic studies of Fyn overexpression in the orbitofrontal cortex (OFC), a region known to be affected in NCD and OUD, on heroin SA and cognitive behaviors using animal models. Further, I used a machine learning approach with RNA-seq data obtained from human post-mortem OFC tissue to classify subjects as either belonging to the heroin overdose or control group based on the expression of ~10 genes. Three feature (gene) importance metrics highlighted a transcript, SHISA7, that was reduced in the human OFC, and this finding was replicated in the OFC of rats that underwent heroin self-administration. SHISA7 and FYN both regulate the synaptic function of AMPA receptors, and are components of the post-synaptic density of glutamatergic neurons. I will examine the impact of overexpressing SHISA7, identified using this machine learning approach, in the OFC on heroin SA and cognitive behaviors in animal models. Finally, I will conduct RNA-sequencing experiments on the OFC from Fyn- and Shisa7-manipulated animals, and in downstream bioinformatics analyses, parse key drivers of gene networks to identify potential mechanisms that account for the contribution of these genes to heroin SA and cognitive behaviors. High-throughput clinical and gene expression data from the human can inform translational, mechanistic studies using animal models that will enable a far-reaching understanding of the molecular disturbances underlying the effects of opioids on cognition and addiction.