Building Bridges to Allow Cross-species Translational genetics for the Study of Addiction

项目总结 物质使用障碍是最常见的精神障碍之一，也是导致残疾的主要原因 在世界各地。在过去的十年里，全基因组关联研究已经确定了大量的基因 导致上瘾的基因(阿片类药物、烟草、大麻、酒精)。将这些发现转化为机械的洞察力， 了解成瘾的病理生理学的必要的第一步，并最终导致新的 治疗，是具有挑战性的。模式生物是理解人类基因组变异如何影响的极好工具 特征。然而，将人类GWAS数据与模型生物研究相结合一直是有限的。这是因为 GWA不会导致基因的识别，而是导致基因变异(或SNPs)的识别，这些基因变异不容易被翻译过来 物种。此外，人类GWA已经表明成瘾的风险是高度多基因的，但现有的应对策略 跨物种翻译不能捕捉成瘾的多基因结构。我提出了一个创新的解决方案 通过开发跨物种多基因翻译框架来解决这一问题。多基因风险分数(PR)，这是一种 广泛用于人类遗传学研究的工具，通过汇总大量SNP的贡献来预测某一性状的风险。 因为这些SNP是物种特有的，所以不可能对另一个物种应用PRS。我提议使用 转录分析，以克服这一障碍。利用来自完善的统计数据的资源和技术 基因工具，我将开发一种方法，允许将多基因信号从人类转化为啮齿动物，并且- 反过来说。这将通过使用以下步骤来完成：1)在人类和 2)使用GTEx和类似数据集的转录数据 从模型生物到建立基因预测模型，允许根据以下条件估计个体的转录水平 基因信息，3)确定这些估计转录水平和成瘾相关特征之间的关联 以及4)使用这些基因水平的关联(而不是SNP水平的关联)来计算多基因转录本风险 分数(PTRS)。这种方法将SNPs翻译成基因估计的基因表达水平，然后利用 事实上，虽然不同物种之间不存在相同的SNPs，但基因正交学可以用于在物种之间进行翻译。在……里面 此外，我将使用补充方法，包括跨物种网络分析和其他工具，这些工具也 说明 成瘾的多基因特性。开发工具，允许多基因研究在 通过开辟全新的研究路线，人类和模式生物将具有变革性。例如，PTRS 将提供一种新的方法来验证成瘾的动物模型，因为将有可能从经验上测试 人类成瘾的遗传特征与啮齿动物成瘾表型的遗传特征有关。PTRS将 也是药物重新定位的工具包，即旨在确定小分子和其他干预措施的研究 这可以改变模式生物中的全球基因表达，从而降低风险，正如PTRS和Network预测的那样- 基于分析。

PROJECT SUMMARY Substance use disorders are among the most common psychiatric disorders and are a leading cause of disability throughout the world. Over the last decade, genome-wide association studies (GWAS) have identified numerous genetic loci that contribute to addiction (opioid, tobacco, cannabis, alcohol). Turning these discoveries into mechanistic insights, a necessary first step for understanding the pathophysiology of addiction, and ultimately leading to the development of new therapies, is challenging. Model organisms serve as excellent tools to understand how human genomic variation affects traits. However, integration of human GWAS data with studies in model organisms has been limited. This is because GWAS do not lead to the identification of genes, but genetic variants (or SNPs), which cannot be easily translated across species. In addition, human GWAS have shown that risk for addiction is highly polygenic, but the existing strategies for cross-species translation do not capture the polygenic architecture of addiction. I am proposing an innovative solution to this problem by developing a framework for cross-species polygenic translation. Polygenic risk scores (PRS), which are a widely used tool for human genetic studies, predict risk for a trait by summing the contributions of numerous SNPs. Because these SNPs are species-specific, it is not possible to apply a PRS to another species. I am proposing to use transcriptomic analyses to overcome this obstacle. Leveraging resources and techniques from well-established statistical genetic tools, I will develop a method that will allow translation of polygenic signals from humans to rodents, and vice- versa. This will be accomplished by using the following steps: 1) use GWAS for addiction-related traits in human and model organisms to compile catalogs of genetic variants; 2) use transcriptomic data from GTEx and analogous datasets from model organisms to build gene prediction models, allowing estimation of transcript levels in individuals based on genotype information, 3) determine the association between these estimated transcript levels and addiction-related traits and 4) use these gene-level associations (rather than SNP level associations) to calculate Polygenic Transcriptomic Risk Scores (PTRS). This approach translates SNPs into gene estimated gene expression levels and then takes advantage of the fact that, while the same SNPs do not exist across species, gene orthology can be used to translate between species. In addition, I will use complementary methodologies, including cross-species network analyses and other tools, that also account for the polygenic nature of addiction. Developing tools that allow polygenic studies to share information between humans and model organisms will be transformative by opening up entirely new lines of research. For example, PTRS will provide a novel means of validating animal models of addiction, as it will be possible to empirically test whether the genetic signature for addiction in humans is related to the genetic signature of addiction phenotypes in rodents. PTRS will also serve as a toolkit for drug repositioning, namely studies aimed at identifying small molecules and other interventions that can alter the global gene expression in model organisms in a way that lower risk, as predicted by PTRS and network- based analyses.