Discovery of genetic and genomic mechanisms driving the relationship between social reward and cocaine addiction

项目摘要 吸毒成瘾是一个严重的公共卫生危机，它是由基因强烈驱动的。一个基本的驱动力， 成瘾是以牺牲社会奖励为代价追求药物奖励的重复选择， 非成瘾个体的人类行为。尽管这一现象在人类中的重要性 成瘾，对社会奖励的偏好超过药物的遗传机制 奖励（以下称社会奖励偏好）是完全未被探索的，因为缺乏一个 相关小鼠模型。建立一个社会奖励偏好的小鼠模型将能够利用 巨大的小鼠遗传学工具包，用于发现和表征驱动这种特性的机制， 极端，代表着对一个关键成瘾媒介的脆弱性和抵抗力。为此，我们建议 利用先进的小鼠种群前所未有的遗传多样性和特殊的结构- 静脉注射可卡因自我给药范式对发现遗传和基因组机制的有效性 驱动社会奖励偏好。为了量化小鼠的社会奖励偏好，我们将使用最近的 为大鼠引入范例，其中受试者做出二元选择：（1）静脉内自我给药 成瘾药物或（2）短暂地与同种相互作用。为了获得最大的表型变异， 为了能够发现驱动社会奖励偏好的遗传机制，我们将使用来自 协作杂交（CC）小鼠组，包含小鼠物种中90%的遗传多样性， 能够整合研究中的基因组和表型数据集。在目标1中，我们将量化 来自8个CC品系的雄性和雌性小鼠对社会奖励相对于可卡因奖励的偏好。我们将 量化这些表型的遗传性，并鉴定表现出对社会性疾病的脆弱性和抗性的菌株。 奖励偏好表型（例如，相对于社会奖励，对可卡因奖励的强烈偏好，以及 反之亦然）。在目标2中，我们将量化在操作性自我调节后丘脑核中的基因表达。 管理社会奖励，轭暴露于社会奖励，假暴露于社会奖励， 来自Aim 1中使用的相同八个CC品系的小鼠。我们将在八个CC菌株和scRNA中进行RNA-seq- seq在两个极端CC菌株中。我们将整合基因表达数据（目标2）和行为数据（目标1）， 鉴定预测社会奖励偏好细胞类型特异性基因表达特征。成功 这些目标的完成将为（1）今后深入描述已确定的机制奠定基础 潜在的社会奖励偏好的小鼠;（2）持久的社区资源，使遗传相关性 跨表型、实验和实验室的CC菌株的子集之间的分析;以及（3）精确的 和强大的管道，为未来的表征社会奖励偏好在整个面板的60 CC菌株。 最终，这项工作将有助于开发新颖，更有效的成瘾治疗方法。

PROJECT ABSTRACT Drug addiction is a critical public health crisis that is strongly genetically driven. A fundamental driver of human addiction is the repeated choice to pursue a drug reward at the expense of a social reward, a strong reinforcer of human behavior in non-addicted individuals. Despite the importance of this phenomenon in human addiction, the genetic mechanisms underlying variation in the preference for a social reward over a drug reward (henceforth social reward preference) have been totally unexplored because of the absence of a relevant mouse model. Establishing a mouse model of social reward preference would enable leveraging the vast mouse genetics toolkit for discovery and characterization of the mechanisms driving this trait, which, at its extremes, represents vulnerability to and resistance to a key addiction vector. To this end, we propose to harness the unprecedented genetic diversity of advanced mouse populations and the exceptional construct- validity of the intravenous cocaine self-administration paradigm to discover genetic and genomic mechanisms driving social reward preference. To quantify social reward preference in the mouse, we will use a recently introduced paradigm for the rat in which the subject makes a binary choice to (1) intravenously self-administer an addictive drug or (2) briefly interact with a conspecific. To capture maximum phenotypic variation and enable discovery of genetic mechanisms driving social reward preference, we will use mice from the Collaborative Cross (CC) mouse panel which contains 90% of the genetic diversity in the mouse species and enables the integration of genomic and phenomic datasets across studies. In Aim 1 we will quantify the preference for social reward relative to cocaine reward in male and female mice from eight CC strains. We will quantify heritability of these phenotypes and identify strains exhibiting vulnerability and resistance to social reward preference phenotypes (e.g., strong preference for a cocaine reward relative to a social reward, and vice versa). In Aim 2 we will quantify gene expression in the nucleus accumbens following operant self- administration of a social reward, yoked exposure to a social reward, and sham exposure to a social reward in mice from the same eight CC strains used in Aim 1. We will perform RNA-seq in eight CC strains and scRNA- seq in two extreme CC strains. We will integrate gene expression data (Aim 2) with behavioral data (Aim 1) to identify cell-type specific gene expression signatures predictive of social reward preference. The successful completion of these aims will provide (1) a foundation for future deep characterization of identified mechanisms underlying social reward preference in mice; (2) a lasting community resource enabling genetic correlational analysis among a subset of the CC strains across phenotypes, experiments, and laboratories; and (3) a refined and robust pipeline for future characterization of social reward preference in the full panel of 60 CC strains. Ultimately, this work will contribute to the development of novel, more effective addiction treatments.